Quantum computing – Wikipedia

Computation based on quantum mechanics

A quantum computer is a computer that exploits quantum mechanical phenomena.At small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior using specialized hardware.Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern "classical" computer.In particular, a large-scale quantum computer could break widely-used encryption schemes and aid physicists in performing physical simulations; however, the current state of the art is still largely experimental and impractical.

The basic unit of information in quantum computing is the qubit, similar to the bit in traditional digital electronics. Unlike a classical bit, a qubit can exist in a superposition of its two "basis" states, which loosely means that it is in both states simultaneously. When measuring a qubit, the result is a probabilistic output of a classical bit. If a quantum computer manipulates the qubit in a particular way, wave interference effects can amplify the desired measurement results. The design of quantum algorithms involves creating procedures that allow a quantum computer to perform calculations efficiently.

Physically engineering high-quality qubits has proven challenging.If a physical qubit is not sufficiently isolated from its environment, it suffers from quantum decoherence, introducing noise into calculations.National governments have invested heavily in experimental research that aims to develop scalable qubits with longer coherence times and lower error rates.Two of the most promising technologies are superconductors (which isolate an electrical current by eliminating electrical resistance) and ion traps (which confine a single atomic particle using electromagnetic fields).

Any computational problem that can be solved by a classical computer can also be solved by a quantum computer. Conversely, any problem that can be solved by a quantum computer can also be solved by a classical computer, at least in principle given enough time. In other words, quantum computers obey the ChurchTuring thesis. This means that while quantum computers provide no additional advantages over classical computers in terms of computability, quantum algorithms for certain problems have significantly lower time complexities than corresponding known classical algorithms. Notably, quantum computers are believed to be able to quickly solve certain problems that no classical computer could solve in any feasible amount of timea feat known as "quantum supremacy." The study of the computational complexity of problems with respect to quantum computers is known as quantum complexity theory.

For many years, the fields of quantum mechanics and computer science formed distinct academic communities. Modern quantum theory developed in the 1920s to explain the waveparticle duality observed at atomic scales,[4] and digital computers emerged in the following decades to replace human computers for tedious calculations.[5] Both disciplines had practical applications during World War II; computers played a major role in wartime cryptography,[6] and quantum physics was essential for the nuclear physics used in the Manhattan Project.[7]

As physicists applied quantum mechanical models to computational problems and swapped digital bits for quantum bits (qubits), the fields of quantum mechanics and computer science began to converge.In 1980, Paul Benioff introduced the quantum Turing machine, which uses quantum theory to describe a simplified computer.[8]When digital computers became faster, physicists faced an exponential increase in overhead when simulating quantum dynamics,[9] prompting Yuri Manin and Richard Feynman to independently suggest that hardware based on quantum phenomena might be more efficient for computer simulation.[10][11]In a 1984 paper, Charles Bennett and Gilles Brassard applied quantum theory to cryptography protocols and demonstrated that quantum key distribution could enhance information security.[13][14]

Quantum algorithms then emerged for solving oracle problems, such as Deutsch's algorithm in 1985,[15] the BernsteinVazirani algorithm in 1993,[16] and Simon's algorithm in 1994.[17]These algorithms did not solve practical problems, but demonstrated mathematically that one could gain more information by querying a black box in superposition, sometimes referred to as quantum parallelism.Peter Shor built on these results with his 1994 algorithms for breaking the widely-used RSA and DiffieHellman encryption protocols, which drew significant attention to the field of quantum computing.[20]In 1996, Grover's algorithm established a quantum speedup for the widely-applicable unstructured search problem.[21] The same year, Seth Lloyd proved that quantum computers could simulate quantum systems without the exponential overhead present in classical simulations,[23] validating Feynman's 1982 conjecture.[24]

Over the years, experimentalists have constructed small-scale quantum computers using trapped ions and superconductors.[25]In 1998, a two-qubit quantum computer demonstrated the feasibility of the technology,[26][27] and subsequent experiments have increased the number of qubits and reduced error rates.[25]In 2019, Google AI and NASA announced that they had achieved quantum supremacy with a 54-qubit machine, performing a computation that is impossible for any classical computer.[28][29][30] However, the validity of this claim is still being actively researched.[31][32]

According to some researchers, noisy intermediate-scale quantum (NISQ) machines may have specialized uses in the near future, but noise in quantum gates limits their reliability.[33]The threshold theorem shows how increasing the number of qubits can mitigate errors, but fully fault-tolerant quantum computing remains "a rather distant dream".[33]Estimates suggest that a quantum computer with nearly 3million fault-tolerant qubits could factor a 2,048-bit integer in five months.[35][36]

In recent years, investment in quantum computing research has increased in the public and private sectors.[37][38]As one consulting firm summarized,[39]

...investment dollars are pouring in, and quantum-computing start-ups are proliferating.... While quantum computing promises to help businesses solve problems that are beyond the reach and speed of conventional high-performance computers, use cases are largely experimental and hypothetical at this early stage.

Computer engineers typically describe a modern computer's operation in terms of classical electrodynamics.Within these "classical" computers, some components (such as semiconductors and random number generators) may rely on quantum behavior, but these components are not isolated from their environment, so any quantum information quickly decoheres.While programmers may depend on probability theory when designing a randomized algorithm, quantum mechanical notions like superposition and interference are largely irrelevant for program analysis.

Quantum programs, in contrast, rely on precise control of coherent quantum systems. Physicists describe these systems mathematically using linear algebra. Complex numbers model probability amplitudes, vectors model quantum states, and matrices model the operations that can be performed on these states. Programming a quantum computer is then a matter of composing operations in such a way that the resulting program computes a useful result in theory and is implementable in practice.

The prevailing model of quantum computation describes the computation in terms of a network of quantum logic gates. This model is a complex linear-algebraic generalization of boolean circuits.[a]

A memory consisting of n {textstyle n} bits of information has 2 n {textstyle 2^{n}} possible states. A vector representing all memory states thus has 2 n {textstyle 2^{n}} entries (one for each state). This vector is viewed as a probability vector and represents the fact that the memory is to be found in a particular state.

The bits of classical computers are not capable of being in superposition, so one entry must have a value of 1 (i.e. a 100% probability of being in this state) and all other entries would be zero.

In quantum mechanics, probability vectors can be generalized to density operators. The quantum state vector formalism is usually introduced first because it is conceptually simpler, and because it can be used instead of the density matrix formalism for pure states, where the whole quantum system is known.

Consider a simple memory consisting of only one quantum bit. When measured, this memory may be found in one of two states: the zero state or the one state. We may represent the state of this memory using Dirac notation so that

The state of this one-qubit quantum memory can be manipulated by applying quantum logic gates, analogous to how classical memory can be manipulated with classical logic gates. One important gate for both classical and quantum computation is the NOT gate, which can be represented by a matrix

X | 0 = | 1 {textstyle X|0rangle =|1rangle } and X | 1 = | 0 {textstyle X|1rangle =|0rangle } .

The mathematics of single qubit gates can be extended to operate on multi-qubit quantum memories in two important ways. One way is simply to select a qubit and apply that gate to the target qubit while leaving the remainder of the memory unaffected. Another way is to apply the gate to its target only if another part of the memory is in a desired state. These two choices can be illustrated using another example. The possible states of a two-qubit quantum memory are

In summary, a quantum computation can be described as a network of quantum logic gates and measurements. However, any measurement can be deferred to the end of quantum computation, though this deferment may come at a computational cost, so most quantum circuits depict a network consisting only of quantum logic gates and no measurements.

Quantum parallelism refers to the ability of quantum computers to evaluate a function for multiple input values simultaneously. This can be achieved by preparing a quantum system in a superposition of input states, and applying a unitary transformation that encodes the function to be evaluated. The resulting state encodes the function's output values for all input values in the superposition, allowing for the computation of multiple outputs simultaneously. This property is key to the speedup of many quantum algorithms.

There are a number of models of computation for quantum computing, distinguished by the basic elements in which the computation is decomposed.

A quantum gate array decomposes computation into a sequence of few-qubit quantum gates. A quantum computation can be described as a network of quantum logic gates and measurements. However, any measurement can be deferred to the end of quantum computation, though this deferment may come at a computational cost, so most quantum circuits depict a network consisting only of quantum logic gates and no measurements.

Any quantum computation (which is, in the above formalism, any unitary matrix of size 2 n 2 n {displaystyle 2^{n}times 2^{n}} over n {displaystyle n} qubits) can be represented as a network of quantum logic gates from a fairly small family of gates. A choice of gate family that enables this construction is known as a universal gate set, since a computer that can run such circuits is a universal quantum computer. One common such set includes all single-qubit gates as well as the CNOT gate from above. This means any quantum computation can be performed by executing a sequence of single-qubit gates together with CNOT gates. Though this gate set is infinite, it can be replaced with a finite gate set by appealing to the Solovay-Kitaev theorem.

A measurement-based quantum computer decomposes computation into a sequence of Bell state measurements and single-qubit quantum gates applied to a highly entangled initial state (a cluster state), using a technique called quantum gate teleportation.

An adiabatic quantum computer, based on quantum annealing, decomposes computation into a slow continuous transformation of an initial Hamiltonian into a final Hamiltonian, whose ground states contain the solution.[42]

A topological quantum computer decomposes computation into the braiding of anyons in a 2D lattice.[43]

The quantum Turing machine is theoretically important but the physical implementation of this model is not feasible. All of these models of computationquantum circuits,[44] one-way quantum computation,[45] adiabatic quantum computation,[46] and topological quantum computation[47]have been shown to be equivalent to the quantum Turing machine; given a perfect implementation of one such quantum computer, it can simulate all the others with no more than polynomial overhead. This equivalence need not hold for practical quantum computers, since the overhead of simulation may be too large to be practical.

Quantum cryptography could potentially fulfill some of the functions of public key cryptography. Quantum-based cryptographic systems could, therefore, be more secure than traditional systems against quantum hacking.[48]

Progress in finding quantum algorithms typically focuses on this quantum circuit model, though exceptions like the quantum adiabatic algorithm exist. Quantum algorithms can be roughly categorized by the type of speedup achieved over corresponding classical algorithms.[49]

Quantum algorithms that offer more than a polynomial speedup over the best-known classical algorithm include Shor's algorithm for factoring and the related quantum algorithms for computing discrete logarithms, solving Pell's equation, and more generally solving the hidden subgroup problem for abelian finite groups.[49] These algorithms depend on the primitive of the quantum Fourier transform. No mathematical proof has been found that shows that an equally fast classical algorithm cannot be discovered, although this is considered unlikely.[50][self-published source?] Certain oracle problems like Simon's problem and the BernsteinVazirani problem do give provable speedups, though this is in the quantum query model, which is a restricted model where lower bounds are much easier to prove and doesn't necessarily translate to speedups for practical problems.

Other problems, including the simulation of quantum physical processes from chemistry and solid-state physics, the approximation of certain Jones polynomials, and the quantum algorithm for linear systems of equations have quantum algorithms appearing to give super-polynomial speedups and are BQP-complete. Because these problems are BQP-complete, an equally fast classical algorithm for them would imply that no quantum algorithm gives a super-polynomial speedup, which is believed to be unlikely.

Some quantum algorithms, like Grover's algorithm and amplitude amplification, give polynomial speedups over corresponding classical algorithms.[49] Though these algorithms give comparably modest quadratic speedup, they are widely applicable and thus give speedups for a wide range of problems. Many examples of provable quantum speedups for query problems are related to Grover's algorithm, including Brassard, Hyer, and Tapp's algorithm for finding collisions in two-to-one functions,[52] which uses Grover's algorithm, and Farhi, Goldstone, and Gutmann's algorithm for evaluating NAND trees,[53] which is a variant of the search problem.

A notable application of quantum computation is for attacks on cryptographic systems that are currently in use. Integer factorization, which underpins the security of public key cryptographic systems, is believed to be computationally infeasible with an ordinary computer for large integers if they are the product of few prime numbers (e.g., products of two 300-digit primes).[54] By comparison, a quantum computer could efficiently solve this problem using Shor's algorithm to find its factors. This ability would allow a quantum computer to break many of the cryptographic systems in use today, in the sense that there would be a polynomial time (in the number of digits of the integer) algorithm for solving the problem. In particular, most of the popular public key ciphers are based on the difficulty of factoring integers or the discrete logarithm problem, both of which can be solved by Shor's algorithm. In particular, the RSA, DiffieHellman, and elliptic curve DiffieHellman algorithms could be broken. These are used to protect secure Web pages, encrypted email, and many other types of data. Breaking these would have significant ramifications for electronic privacy and security.

Identifying cryptographic systems that may be secure against quantum algorithms is an actively researched topic under the field of post-quantum cryptography.[55][56] Some public-key algorithms are based on problems other than the integer factorization and discrete logarithm problems to which Shor's algorithm applies, like the McEliece cryptosystem based on a problem in coding theory.[55][57] Lattice-based cryptosystems are also not known to be broken by quantum computers, and finding a polynomial time algorithm for solving the dihedral hidden subgroup problem, which would break many lattice based cryptosystems, is a well-studied open problem.[58] It has been proven that applying Grover's algorithm to break a symmetric (secret key) algorithm by brute force requires time equal to roughly 2n/2 invocations of the underlying cryptographic algorithm, compared with roughly 2n in the classical case,[59] meaning that symmetric key lengths are effectively halved: AES-256 would have the same security against an attack using Grover's algorithm that AES-128 has against classical brute-force search (see Key size).

The most well-known example of a problem that allows for a polynomial quantum speedup is unstructured search, which involves finding a marked item out of a list of n {displaystyle n} items in a database. This can be solved by Grover's algorithm using O ( n ) {displaystyle O({sqrt {n}})} queries to the database, quadratically fewer than the ( n ) {displaystyle Omega (n)} queries required for classical algorithms. In this case, the advantage is not only provable but also optimal: it has been shown that Grover's algorithm gives the maximal possible probability of finding the desired element for any number of oracle lookups.

Problems that can be efficiently addressed with Grover's algorithm have the following properties:[60][61]

For problems with all these properties, the running time of Grover's algorithm on a quantum computer scales as the square root of the number of inputs (or elements in the database), as opposed to the linear scaling of classical algorithms. A general class of problems to which Grover's algorithm can be applied[62] is Boolean satisfiability problem, where the database through which the algorithm iterates is that of all possible answers. An example and possible application of this is a password cracker that attempts to guess a password. Breaking symmetric ciphers with this algorithm is of interest to government agencies.[63]

Since chemistry and nanotechnology rely on understanding quantum systems, and such systems are impossible to simulate in an efficient manner classically, many[who?] believe quantum simulation will be one of the most important applications of quantum computing.[64] Quantum simulation could also be used to simulate the behavior of atoms and particles at unusual conditions such as the reactions inside a collider.[65]

Quantum simulations might be used to predict future paths of particles and protons under superposition in the double-slit experiment.[66]

About 2% of the annual global energy output is used for nitrogen fixation to produce ammonia for the Haber process in the agricultural fertilizer industry (even though naturally occurring organisms also produce ammonia). Quantum simulations might be used to understand this process and increase the energy efficiency of production.[67]

Quantum annealing relies on the adiabatic theorem to undertake calculations. A system is placed in the ground state for a simple Hamiltonian, which slowly evolves to a more complicated Hamiltonian whose ground state represents the solution to the problem in question. The adiabatic theorem states that if the evolution is slow enough the system will stay in its ground state at all times through the process.

Since quantum computers can produce outputs that classical computers cannot produce efficiently, and since quantum computation is fundamentally linear algebraic, some express hope in developing quantum algorithms that can speed up machine learning tasks.[68][69]

For example, the quantum algorithm for linear systems of equations, or "HHL Algorithm", named after its discoverers Harrow, Hassidim, and Lloyd, is believed to provide speedup over classical counterparts.[70][69] Some research groups have recently explored the use of quantum annealing hardware for training Boltzmann machines and deep neural networks.[71][72][73]

In the field of computational biology, quantum computing has the potential to play a big role in solving many biological problems. Given how computational biology is using generic data modeling and storage, its applications to computational biology are expected to arise as well.[74]

Deep generative chemistry models emerge as powerful tools to expedite drug discovery. However, the immense size and complexity of the structural space of all possible drug-like molecules pose significant obstacles, which could be overcome in the future by quantum computers. Quantum computers are naturally good for solving complex quantum many-body problems[75] and thus may be instrumental in applications involving quantum chemistry. Therefore, one can expect that quantum-enhanced generative models[76] including quantum GANs[77] may eventually be developed into ultimate generative chemistry algorithms.

There are a number of technical challenges in building a large-scale quantum computer.[78] Physicist David DiVincenzo has listed these requirements for a practical quantum computer:[79]

Sourcing parts for quantum computers is also very difficult. Superconducting quantum computers, like those constructed by Google and IBM, need helium-3, a nuclear research byproduct, and special superconducting cables made only by the Japanese company Coax Co.[80]

The control of multi-qubit systems requires the generation and coordination of a large number of electrical signals with tight and deterministic timing resolution. This has led to the development of quantum controllers which enable interfacing with the qubits. Scaling these systems to support a growing number of qubits is an additional challenge.[81]

One of the greatest challenges involved with constructing quantum computers is controlling or removing quantum decoherence. This usually means isolating the system from its environment as interactions with the external world cause the system to decohere. However, other sources of decoherence also exist. Examples include the quantum gates, and the lattice vibrations and background thermonuclear spin of the physical system used to implement the qubits. Decoherence is irreversible, as it is effectively non-unitary, and is usually something that should be highly controlled, if not avoided. Decoherence times for candidate systems in particular, the transverse relaxation time T2 (for NMR and MRI technology, also called the dephasing time), typically range between nanoseconds and seconds at low temperature.[82] Currently, some quantum computers require their qubits to be cooled to 20 millikelvin (usually using a dilution refrigerator[83]) in order to prevent significant decoherence.[84] A 2020 study argues that ionizing radiation such as cosmic rays can nevertheless cause certain systems to decohere within milliseconds.[85]

As a result, time-consuming tasks may render some quantum algorithms inoperable, as attempting to maintain the state of qubits for a long enough duration will eventually corrupt the superpositions.[86]

These issues are more difficult for optical approaches as the timescales are orders of magnitude shorter and an often-cited approach to overcoming them is optical pulse shaping. Error rates are typically proportional to the ratio of operating time to decoherence time, hence any operation must be completed much more quickly than the decoherence time.

As described in the threshold theorem, if the error rate is small enough, it is thought to be possible to use quantum error correction to suppress errors and decoherence. This allows the total calculation time to be longer than the decoherence time if the error correction scheme can correct errors faster than decoherence introduces them. An often-cited figure for the required error rate in each gate for fault-tolerant computation is 103, assuming the noise is depolarizing.

Meeting this scalability condition is possible for a wide range of systems. However, the use of error correction brings with it the cost of a greatly increased number of required qubits. The number required to factor integers using Shor's algorithm is still polynomial, and thought to be between L and L2, where L is the number of digits in the number to be factored; error correction algorithms would inflate this figure by an additional factor of L. For a 1000-bit number, this implies a need for about 104 bits without error correction.[87] With error correction, the figure would rise to about 107 bits. Computation time is about L2 or about 107 steps and at 1MHz, about 10 seconds. However, other careful estimates[35][36] lower the qubit count to 3million for factorizing 2,048-bit integer in 5 months on a trapped-ion quantum computer.

Another approach to the stability-decoherence problem is to create a topological quantum computer with anyons, quasi-particles used as threads, and relying on braid theory to form stable logic gates.[88][89]

Quantum supremacy is a term coined by John Preskill referring to the engineering feat of demonstrating that a programmable quantum device can solve a problem beyond the capabilities of state-of-the-art classical computers.[90][91][92] The problem need not be useful, so some view the quantum supremacy test only as a potential future benchmark.[93]

In October 2019, Google AI Quantum, with the help of NASA, became the first to claim to have achieved quantum supremacy by performing calculations on the Sycamore quantum computer more than 3,000,000 times faster than they could be done on Summit, generally considered the world's fastest computer.[94][95][96] This claim has been subsequently challenged: IBM has stated that Summit can perform samples much faster than claimed,[97][98] and researchers have since developed better algorithms for the sampling problem used to claim quantum supremacy, giving substantial reductions to the gap between Sycamore and classical supercomputers[99][100][101] and even beating it.[102][103][104]

In December 2020, a group at USTC implemented a type of Boson sampling on 76 photons with a photonic quantum computer, Jiuzhang, to demonstrate quantum supremacy.[105][106][107] The authors claim that a classical contemporary supercomputer would require a computational time of 600 million years to generate the number of samples their quantum processor can generate in 20 seconds.[108]

On November 16, 2021, at the quantum computing summit, IBM presented a 127-qubit microprocessor named IBM Eagle.[109]

Some researchers have expressed skepticism that scalable quantum computers could ever be built, typically because of the issue of maintaining coherence at large scales, but also for other reasons.

Bill Unruh doubted the practicality of quantum computers in a paper published in 1994.[110] Paul Davies argued that a 400-qubit computer would even come into conflict with the cosmological information bound implied by the holographic principle.[111] Skeptics like Gil Kalai doubt that quantum supremacy will ever be achieved.[112][113][114] Physicist Mikhail Dyakonov has expressed skepticism of quantum computing as follows:

For physically implementing a quantum computer, many different candidates are being pursued, among them (distinguished by the physical system used to realize the qubits):

The large number of candidates demonstrates that quantum computing, despite rapid progress, is still in its infancy.[143]

Any computational problem solvable by a classical computer is also solvable by a quantum computer. Intuitively, this is because it is believed that all physical phenomena, including the operation of classical computers, can be described using quantum mechanics, which underlies the operation of quantum computers.

Conversely, any problem solvable by a quantum computer is also solvable by a classical computer. It is possible to simulate both quantum and classical computers manually with just some paper and a pen, if given enough time. More formally, any quantum computer can be simulated by a Turing machine. In other words, quantum computers provide no additional power over classical computers in terms of computability. This means that quantum computers cannot solve undecidable problems like the halting problem and the existence of quantum computers does not disprove the ChurchTuring thesis.

While quantum computers cannot solve any problems that classical computers cannot already solve, it is suspected that they can solve certain problems faster than classical computers. For instance, it is known that quantum computers can efficiently factor integers, while this is not believed to be the case for classical computers.

The class of problems that can be efficiently solved by a quantum computer with bounded error is called BQP, for "bounded error, quantum, polynomial time". More formally, BQP is the class of problems that can be solved by a polynomial-time quantum Turing machine with an error probability of at most 1/3. As a class of probabilistic problems, BQP is the quantum counterpart to BPP ("bounded error, probabilistic, polynomial time"), the class of problems that can be solved by polynomial-time probabilistic Turing machines with bounded error. It is known that B P P B Q P {displaystyle {mathsf {BPPsubseteq BQP}}} and is widely suspected that B Q P B P P {displaystyle {mathsf {BQPsubsetneq BPP}}} , which intuitively would mean that quantum computers are more powerful than classical computers in terms of time complexity.

The exact relationship of BQP to P, NP, and PSPACE is not known. However, it is known that P B Q P P S P A C E {displaystyle {mathsf {Psubseteq BQPsubseteq PSPACE}}} ; that is, all problems that can be efficiently solved by a deterministic classical computer can also be efficiently solved by a quantum computer, and all problems that can be efficiently solved by a quantum computer can also be solved by a deterministic classical computer with polynomial space resources. It is further suspected that BQP is a strict superset of P, meaning there are problems that are efficiently solvable by quantum computers that are not efficiently solvable by deterministic classical computers. For instance, integer factorization and the discrete logarithm problem are known to be in BQP and are suspected to be outside of P. On the relationship of BQP to NP, little is known beyond the fact that some NP problems that are believed not to be in P are also in BQP (integer factorization and the discrete logarithm problem are both in NP, for example). It is suspected that N P B Q P {displaystyle {mathsf {NPnsubseteq BQP}}} ; that is, it is believed that there are efficiently checkable problems that are not efficiently solvable by a quantum computer. As a direct consequence of this belief, it is also suspected that BQP is disjoint from the class of NP-complete problems (if an NP-complete problem were in BQP, then it would follow from NP-hardness that all problems in NP are in BQP).[147]

The relationship of BQP to the basic classical complexity classes can be summarized as follows:

It is also known that BQP is contained in the complexity class # P {displaystyle color {Blue}{mathsf {#P}}} (or more precisely in the associated class of decision problems P # P {displaystyle {mathsf {P^{#P}}}} ),[147] which is a subclass of PSPACE.

It has been speculated that further advances in physics could lead to even faster computers. For instance, it has been shown that a non-local hidden variable quantum computer based on Bohmian Mechanics could implement a search of an N-item database in at most O ( N 3 ) {displaystyle O({sqrt[{3}]{N}})} steps, a slight speedup over Grover's algorithm, which runs in O ( N ) {displaystyle O({sqrt {N}})} steps. Note, however, that neither search method would allow quantum computers to solve NP-complete problems in polynomial time.[148] Theories of quantum gravity, such as M-theory and loop quantum gravity, may allow even faster computers to be built. However, defining computation in these theories is an open problem due to the problem of time; that is, within these physical theories there is currently no obvious way to describe what it means for an observer to submit input to a computer at one point in time and then receive output at a later point in time.[149][150]

Read the original post:

Quantum computing - Wikipedia

What is Quantum Computing? | IBM

Quantum computers are elegant machines, smaller and requiring less energy than supercomputers. An IBM Quantum processor is a wafer not much bigger than the one found in a laptop. And a quantum hardware system is about the size of a car, made up mostly of cooling systems to keep the superconducting processor at its ultra-cold operational temperature.

A classical processor uses bits to perform its operations. A quantum computer uses qubits (CUE-bits) to run multidimensional quantum algorithms.

SuperfluidsYour desktop computer likely uses a fan to get cold enough to work. Our quantum processors need to be very cold about a hundredth of a degree above absolute zero. To achieve this, we use super-cooled superfluids to create superconductors.

SuperconductorsAt those ultra-low temperatures certain materials in our processors exhibit another important quantum mechanical effect: electrons move through them without resistance. This makes them "superconductors."

When electrons pass through superconductors they match up, forming "Cooper pairs." These pairs can carry a charge across barriers, or insulators, through a process known as quantum tunneling. Two superconductors placed on either side of an insulator form a Josephson junction

ControlOur quantum computers use Josephson junctions as superconducting qubits. By firing microwave photons at these qubits, we can control their behavior and get them to hold, change, and read out individual units of quantum information.

SuperpositionA qubit itself isn't very useful. But it can perform an important trick: placing the quantum information it holds into a state of superposition, which represents a combination of all possible configurations of the qubit. Groups of qubits in superposition can create complex, multidimensional computational spaces. Complex problems can be represented in new ways in these spaces.

EntanglementEntanglement is a quantum mechanical effect that correlates the behavior of two separate things. When two qubits are entangled, changes to one qubit directly impact the other. Quantum algorithms leverage those relationships to find solutions to complex problems

Read more:

What is Quantum Computing? | IBM

Quantum Computing – Intel

Quantum Computing Research

Quantum computing employs the properties of quantum physics like superposition and entanglement to perform computation. Traditional transistors use binary encoding of data represented electrically as on or off states. Quantum bits or qubits can simultaneously operate in multiple states enabling unprecedented levels of parallelism and computing efficiency.

Todays quantum systems only include tens or hundreds of entangled qubits, limiting them from solving real-world problems. To achievequantum practicality, commercial quantum systems need to scale to over a million qubits and overcome daunting challenges like qubit fragility and software programmability. Intel Labs is working to overcome these challenges with the help of industry and academic partners and has made significant progress.

First, Intel is leveraging its expertise in high-volume transistor manufacturing to develophot silicon spin-qubits, much smaller computing devices that operate at higher temperatures. Second, theHorse Ridge IIcryogenic quantum control chip provides tighter integration. And third, thecryoproberenables high-volume testing that is helping to accelerate commercialization.

Even though we may be years away from large-scale implementation, quantum computing promises to enable breakthroughs in materials, chemicals and drug design, financial and climate modeling, and cryptography.

View post:

Quantum Computing - Intel

What Is Quantum Computing? | NVIDIA Blog

Twenty-seven years before Steve Jobs unveiled a computer you could put in your pocket, physicist Paul Benioff published a paper showing it was theoretically possible to build a much more powerful system you could hide in a thimble a quantum computer.

Named for the subatomic physics it aimed to harness, the concept Benioff described in 1980 still fuels research today, including efforts to build the next big thing in computing: a system that could make a PC look in some ways quaint as an abacus.

Richard Feynman a Nobel Prize winner whose wit-laced lectures brought physics to a broad audience helped establish the field, sketching out how such systems could simulate quirky quantum phenomena more efficiently than traditional computers. So,

Quantum computing is a sophisticated approach to making parallel calculations, using the physics that governs subatomic particles to replace the more simplistic transistors in todays computers.

Quantum computers calculate using qubits, computing units that can be on, off or any value between, instead of the bits in traditional computers that are either on or off, one or zero. The qubits ability to live in the in-between state called superposition adds a powerful capability to the computing equation, making quantum computers superior for some kinds of math.

Using qubits, quantum computers could buzz through calculations that would take classical computers a loooong time if they could even finish them.

For example, todays computers use eight bits to represent any number between 0 and 255. Thanks to features like superposition, a quantum computer can use eight qubits to represent every number between 0 and 255, simultaneously.

Its a feature like parallelism in computing: All possibilities are computed at once rather than sequentially, providing tremendous speedups.

So, while a classical computer steps through long division calculations one at a time to factor a humongous number, a quantum computer can get the answer in a single step. Boom!

That means quantum computers could reshape whole fields, like cryptography, that are based on factoring what are today impossibly large numbers.

That could be just the start. Some experts believe quantum computers will bust through limits that now hinder simulations in chemistry, materials science and anything involving worlds built on the nano-sized bricks of quantum mechanics.

Quantum computers could even extend the life of semiconductors by helping engineers create more refined simulations of the quantum effects theyre starting to find in todays smallest transistors.

Indeed, experts say quantum computers ultimately wont replace classical computers, theyll complement them. And some predict quantum computers will be used as accelerators much as GPUs accelerate todays computers.

Dont expect to build your own quantum computer like a DIY PC with parts scavenged from discount bins at the local electronics shop.

The handful of systems operating today typically require refrigeration that creates working environments just north of absolute zero. They need that computing arctic to handle the fragile quantum states that power these systems.

In a sign of how hard constructing a quantum computer can be, one prototype suspends an atom between two lasers to create a qubit. Try that in your home workshop!

Quantum computing takes nano-Herculean muscles to create something called entanglement. Thats when two or more qubits exist in a single quantum state, a condition sometimes measured by electromagnetic waves just a millimeter wide.

Crank up that wave with a hair too much energy and you lose entanglement or superposition, or both. The result is a noisy state called decoherence, the equivalent in quantum computing of the blue screen of death.

A handful of companies such as Alibaba, Google, Honeywell, IBM, IonQ and Xanadu operate early versions of quantum computers today.

Today they provide tens of qubits. But qubits can be noisy, making them sometimes unreliable. To tackle real-world problems reliably, systems need tens or hundreds of thousands of qubits.

Experts believe it could be a couple decades before we get to a high-fidelity era when quantum computers are truly useful.

Predictions of when we reach so-called quantum computing supremacy the time when quantum computers execute tasks classical ones cant is a matter of lively debate in the industry.

The good news is the world of AI and machine learning put a spotlight on accelerators like GPUs, which can perform many of the types of operations quantum computers would calculate with qubits.

So, classical computers are already finding ways to host quantum simulations with GPUs today. For example, NVIDIA ran a leading-edge quantum simulation on Selene, our in-house AI supercomputer.

NVIDIA announced in the GTC keynote the cuQuantum SDK to speed quantum circuit simulations running on GPUs. Early work suggests cuQuantum will be able to deliver orders of magnitude speedups.

The SDK takes an agnostic approach, providing a choice of tools users can pick to best fit their approach. For example, the state vector method provides high-fidelity results, but its memory requirements grow exponentially with the number of qubits.

That creates a practical limit of roughly 50 qubits on todays largest classical supercomputers. Nevertheless weve seen great results (below) using cuQuantum to accelerate quantum circuit simulations that use this method.

Researchers from the Jlich Supercomputing Centre will provide a deep dive on their work with the state vector method in session E31941 at GTC (free with registration).

A newer approach, tensor network simulations, use less memory and more computation to perform similar work.

Using this method, NVIDIA and Caltech accelerated a state-of-the-art quantum circuit simulator with cuQuantum running on NVIDIA A100 Tensor Core GPUs. It generated a sample from a full-circuit simulation of the Google Sycamore circuit in 9.3 minutes on Selene, a task that 18 months ago experts thought would take days using millions of CPU cores.

Using the Cotengra/Quimb packages, NVIDIAs newly announced cuQuantum SDK, and the Selene supercomputer, weve generated a sample of the Sycamore quantum circuit at depth m=20 in record time less than 10 minutes, said Johnnie Gray, a research scientist at Caltech.

This sets the benchmark for quantum circuit simulation performance and will help advance the field of quantum computing by improving our ability to verify the behavior of quantum circuits, said Garnet Chan, a chemistry professor at Caltech whose lab hosted the work.

NVIDIA expects the performance gains and ease of use of cuQuantum will make it a foundational element in every quantum computing framework and simulator at the cutting edge of this research.

Sign up to show early interest in cuQuantum.

Learn more about quantum computing on the NVIDIA Technical Blog.

Originally posted here:

What Is Quantum Computing? | NVIDIA Blog

Quantiki | Quantum Information Portal and Wiki

Welcome to Quantiki

Welcome to Quantiki, the world's leading portal for everyone involved in quantum information science. No matter if you are a researcher, a student or an enthusiast of quantum theory, this is the place you are going to find useful and enjoyable! While here on Quantiki you can: browse our content, including fascinating and educative articles, then create your own account and log in to gain more editorial possibilities.

Add new content, such as information about upcoming quantum events, open positions for quantum scientists and existing quantum research groups. We also encourage to follow us using social media sites.

EDF Lab is opening a position in Quantum Combinatorial Optimization.You'll be a part of one of the most active quantum player in french industry and you'll be involved in the development of algorithms, their tests, thair applications to real machines.Contact me for further details or apply in the following link :

https://www.edf.fr/edf-recrute/offre/detail/2022-58062

Have you ever wanted to take part in the development of top photonic quantum technologies which will change our future? Are you eager to work side by side and learn from with the best quantum scientists, space agencies and high-tech companies? Do you want to boost your career in academia or business R&D in Europe and beyond? If your answer is yes, you are highly creative and hold a PhD in physics, computer science or mathematics or you will graduate in the next few months, then join our multi-national Quantum Technologies Research Group led by Prof. Magdalena Stobiska at the University of Warsaw. We have now 3 open positions which we plan to fill as soon as possible.

Two postdoctoral positions are available at the Institute for Quantum Computing (https://uwaterloo.ca/institute-for-quantum-computing/), University of Waterloo, in the field of superconducting devices. The positions are with the Superconducting Quantum Devices group and will be supervised by Adrian Lupascu.

Ph.D. Thesis: Optimized Hardware Designs for Quantum LDPC Decoders(Partially founded by European QuantERA programme, an international consortium involving partners in France, Germany, Spain and Finland https://quantera.eu/equip/)

PhD positions supervised by Ryan LaRose (https://www.ryanlarose.com/) are available at MSU-Q (https://msuq.natsci.msu.edu/) in the broad areas of quantum computing theory, quantum algorithms, and scientific computing in quantum information. Successful applicants will be motivated learners seeking to contribute novel research to advance the theory and applications of quantum information science.

Premium Drupal Theme by Adaptivethemes.com

Read more:

Quantiki | Quantum Information Portal and Wiki

Learn quantum computing: a field guide – IBM Quantum

Quantum theory is a revolutionary advancement in physics and chemistrythat emerged in the early twentieth century. It is an elegantmathematical theory able to explain the counterintuitive behavior ofsubatomic particles, most notably the phenomenon of entanglement. Inthe late twentieth century it was discovered that quantum theory appliesnot only to atoms and molecules, but to bits and logic operations in acomputer. This realization has brought about a revolution in thescience and technology of information processing, making possible kindsof computing and communication hitherto unknown in the Information Age.

Our everyday computers perform calculations and process information using thestandard (or classical) model ofcomputation, which dates back toTuring and vonNeumann. In thismodel, all information is reducible to bits, which can take the valuesof either 0 or 1. Additionally, all processing can be performed via simple logicgates (AND, OR, NOT, XOR, XNOR)acting on one or two bits at a time, or be entirely described by NAND (or NOR).At any point in its computation, aclassical computers state is entirely determined by the states of allits bits, so that a computer with n bits can exist in one of2^n possible states, ranging from 00...0 to11...1 .

The power of the quantum computer, meanwhile, lies in its much richerrepertoire of states. A quantum computer also has bits but instead of0 and 1, its quantum bits, or qubits, can represent a 0, 1, or linearcombination of both, which is a property known as superposition.This on its own is no special thing, since a computer whose bits can beintermediate between 0 and 1 is just an analog computer, scarcely morepowerful than an ordinary digital computer. However, a quantum computertakes advantage of a special kind of superposition that allows forexponentially many logical states at once, all the states from|00...0rangle to |11...1rangle . This is a powerfulfeat, and no classical computer can achieve it.

The vast majority of quantum superpositions, and the ones most useful for quantumcomputation, are entangled. Entangled states are states of the whole computerthat do not correspond to any assignment of digital or analog states ofthe individual qubits. A quantum computer is therefore significantly more powerfulthan any one classical computer whether it be deterministic,probabilistic, or analog.

While todays quantum processors are modest in size, their complexity growscontinuously. We believe this is the right time to build and engage a communityof new quantum learners, spark further interest in those who are curious,and foster a quantum intuition in the greater community.By making quantum concepts more widely understood even on a generallevel we can more deeply explore all the possibilities quantumcomputing offers, and more rapidly bring its exciting power to a worldwhose perspective is limited by classical physics.

With this in mind, we created the IBM Quantum Composer to provide the hands-onopportunity to experiment with operations on a real quantum computingprocessor. This field guide contains a series of topicsto accompany your journey as you create your own experiments, run them insimulation, and execute them on real quantum processorsavailable via IBM Cloud.

If quantum physics sounds challenging to you, you are not alone. But ifyou think the difficulty lies in hard math, think again. Quantum conceptscan, for the most part, be described by undergraduate-level linear algebra,so if you have ever taken a linear algebra course, the math will seem familiar.

The true challenge of quantum physics is internalizing ideas that arecounterintuitive to our day-to-day experiences in the physical world,which of course are constrained by classical physics. To comprehendthe quantum world, you must build a new intuition for a set of simple butvery different (and often surprising) laws.

The counterintuitive principles of quantum physics are:

1.A physical system in a definite state can still behaverandomly.

2.Two systems that are too far apart to influence each other cannevertheless behave in ways that, though individually random,are somehow strongly correlated.

Unfortunately, there is no single simple physicalprinciple from which these conclusions follow and we must guard againstattempting to describe quantum concepts in classical terms!The best we can do is to distill quantum mechanics down to a fewabstract-sounding mathematical laws, from which all the observed behaviorof quantum particles (and qubits in a quantum computer) can be deduced andpredicted.

Keep those two counterintuitive ideas in the back of your mind, let goof your beliefs about how the physical world works, and begin exploringthe quantum world!

Continue reading here:

Learn quantum computing: a field guide - IBM Quantum

Quantum Computing | Computer Science – Yale University

Quantum computing is entering an exciting new era. Small to medium-scale quantum computers are being built and tested; fast quantum algorithms are being discovered for problems that are previously unsolvable on conventional computers. Yale has been at the forefront of that progress, recognized for its leadership in Quantum Science. Through interdisciplinary research and pioneering innovations, our Yale CS faculty advances the state-of-the-art in quantum computing and quantum information science, building upon insights and lessons from classical computer science.

Yongshan Dings Lab Todays quantum computers are still moderate in size and prone to making errors, while most existing quantum applications require a large number of qubits and a high level of accuracy in operations. To bridge this gap, Dings Lab creates innovative techniques to improve the efficiency of algorithms and software, by adapting to hardware architectures. Working closely with experimentalists, their current efforts include constructing novel error-correcting protocols to guarantee robust computation and designing new algorithms that are less resource-intensive and more error-resilient.

Nisheeth Vishnois group is interested, on the one hand, in the design of quantum algorithms that can go beyond classical algorithms for optimization and sampling problems and, on the other hand, in the design of algorithms for computational problems arising in quantum mechanics.

Lin Zhongs Lab Quantum Computers rely on classical hardware for control (using microwave signals) and error correction (using FPGAs), which bears strong similarity to wireless communication systems: just imagine your smartphone is a qubit under the control of a base station. Toward fault-tolerant quantum computing, hundreds or even thousands of qubits must be controlled in tight synchrony and with errors corrected. Leveraging their experience in building scalable, massive MIMO communication systems, Lin Zhongs Lab design and experiment with scalable control systems for fully error-corrected, fault-tolerant quantum computers, in collaboration with quantum scientists.

At Yale, experts across areas including computer science, applied physics, electrical engineering, chemistry, physics, statistics & data science, and mathematics work together to advance the frontier of quantum computing and information processing. Quantum at Yale is a showcase of the vibrant research activities here at Yale.

Originally posted here:

Quantum Computing | Computer Science - Yale University

Introduction to quantum computing – GeeksforGeeks

Improve Article

Save Article

Like Article

Improve Article

Save Article

Computers are getting smaller and faster day by day because electronic components are getting smaller and smaller. But this process is about to meet its physical limit.

Electricity is the flow of electrons. Since the size of transistors is shrinking to the size of a few atoms, transistors cannot be used as switches because electrons may transfer themselves to the other side of blocked passage by the process called quantum tunneling.

Quantum mechanics is a branch of physics that explores the physical world at a most fundamental level. At this level, particles behave differently from the classical world taking more than one state at the same time and interacting with other particles that are very far away. Phenomena like superposition and entanglement take place.

In classical computing for example there are 4 bits. The combination of 4 bits can represent 2^4=16 values in total and one value a given instant. But in a combination of 4 qubits, all 16 combinations are possible at once.

What can quantum computers do?

Continue reading here:

Introduction to quantum computing - GeeksforGeeks

Quantum Leap: "The big bang of quantum computing will come in this decade" – CTech

In the few images that IBM has released, its quantum computing lab looks like the engine room of a spaceship: bright white rooms with countless cables dangling from the ceiling down to a floating floor, pierced with vents. This technological tangle is just the background for the main show: rows of metal supports on which hang what look like... white solar boilers.

There, within these boilers, a historical revolution is taking shape. IBM, a computing dinosaur more than a century old, is trying to reinvent itself by winning one of the most grueling, expensive and potentially promising scientific races ever: the race to develop the quantum computer. "We are living in the most exciting era in the history of computing," says Dario Gil, Senior Vice President of IBM and head of the company's research division, in an exclusive interview with Calcalist. "We are witnessing a moment similar to the one recorded in the 40s & 50s of the last century, when the first classic computers were built." A few weeks after this conversation, his statements were further confirmed, when the Nobel Prize Committee announced the awarding of the prize in the field of physics to three researchers whose research served as a milestone in the development of the field.

The name Dario Gil shakes a lot of quanta and cells in the brains, and maybe even in the hearts, of physicists and computer engineers all over the world. This is the person who leads the most advanced effort in the world to develop a quantum computer. In September, when Gil landed in Tel Aviv for a short visit to give the opening lecture at the IBM conference, the hall was packed with senior engineers, researchers from the top universities in Israel, and representatives of government bodies - all enthralled by what Gil had to say.

2 View gallery

Dario Gil.

(Photo: Elad Gershgoren)

Gil (46) was born in Spain and moved to the United States to study at MIT University. He completed his doctoral studies there, and immediately after graduation began working at IBM in a series of research and development positions. Since 2019, he has been leading the company's research division, which has 3,000 engineers at 21 sites, including Israel. Under his management, in 2016, IBM built the first quantum computer whose services are available to anyone: if you have a complicated question, you can go to the IBM Quantum Experience website, remotely access one of the quantum computers through the cloud - and, perhaps, receive an answer. But as with everything related to quantum computing, it just sounds simple.

"Quantum computing is not just a name for an extremely fast computer," says Gill. In fact, he explains, the quantum computer is no longer a supercomputer that uses the same binary method that is accepted in every classical computer, but a completely new machine, another step in the evolution leading from strings of shells, through beaded invoices and calculating bars, to gear-based mechanical computers, to the electronic computer and now to the quantum computer. "Essentially, the quantum computer is a kind of simulator of nature, through which it is possible to simulate natural processes, and thus solve problems that previously had no solution," explains Gil. "If the classical computer is a combination of mathematics and information, then quantum computing is a combination of physics and information."

This connection makes it possible to solve certain types of problems with unprecedented speed: Google, which is also developing a quantum computer, claimed in 2019 that it had reached "quantum supremacy" a demonstration of a calculation that a quantum computer would perform more efficiently than a classical computer. The researchers at Google showed how a quantum computer performed in 200 seconds a calculation that they claim would have required a classical computer ten thousand years to complete. This claim has since been disproved by other researchers, who have presented an algorithm that allows a classical computer to perform the same calculation in a reasonable amount of timebut even this Google failure provides an idea of the enormous power a quantum computer will have.

"The quantum computer does not make the classical computer superfluous: they will live together, and each of them will solve different problems," explains Gil. "It's like asking you how to get from point A to point B: you can walk, ride a bicycle, travel by car or fly. If the distance between these points is 50 km, you won't fly between them, right? Accordingly, it is a mode suitable for a classic computer. A quantum computer allows you to fly, even to the moon, and quickly."

You will soon explain to me how it works, and in which areas exactly, but before that, let's start from the bottom line: what can we do with it?

"Quantum computing will make it possible to crack a series of problems that seemed unsolvable, in a way that will change the world. Many of these issues are related to energy. Others are related to the development of new and exciting materials. We tend to take the materials available to us for granted, but in the past there were eras that were defined by the materials that dominated them - The Stone Age', the 'Bronze Age', the 'Iron Age'. Quantum computing will help us develop materials with new properties, therefore the first sector that is already using it is industry, especially the car industry: the car manufacturers are interested in better chemistry, which will enable the production of more efficient and durable batteries for electric vehicles. For a normal computer this is a huge task, and to complete it we have to give up accuracy and settle for approximate answers only, but quantum computing can help quickly develop materials that will fit the task, even without entering the lab. The efficiency of a quantum computer when it comes to questions in chemistry is also used in the pharmaceutical industry, There they are beginning to make initial use of such computers to examine the properties of molecules, and in this way to speed up the development of new drugs; and also in the fertilizer industry, which will be able to develop substances whose production will not harm the environment.

The uses are not limited to the material world. "For the financial sector, for example, the quantum computer enables the analysis of scenarios, risk management and forecasting, and the industry is already very interested in such possible applications, which could provide the general public with dramatically improved performance in investment portfolios, for example.

2 View gallery

IBM.

(Photo: Shutterstock)

At the same time, there are industries that quantum computing will force to recalculate their course, and the information security industry is at the forefront. The modern encryption systems (mainly RSA, one of whose developers is the Israeli Prof. Adi Shamir) are asymmetric: each recipient publishes a code that allows the information sent to them to be encrypted ("public key"), which includes the product of two large prime numbers that are kept secret. To decipher the encrypted information, this product must be broken down into factors - but without knowing what the initial numbers are, "this task would require a normal computer to calculate for many years," explains Gil. "However, for the quantum computer, such a calculation can be a matter of seconds."

There is a real threat here to an entire industry, the logic behind which has been built since the 1970s, and now suddenly the ground is cracking under it.

"True, a normal computer needs ten thousand years to solve an encryption that a quantum computer would solve in an instant. That is why the quantum computer threatens the world of cyberspace and encryption, which are the basis of all global information security. This is an example that is not related to physics or nature, but simply to the stronger and faster computing power of the quantum computer.

The computer that works against all the rules of intuition

To understand the power of the quantum computer, this concept, "quantum computing", must first be broken down. The first step is to stop thinking in the familiar concepts of one and zero. Forget about bits and binaries. The key to understanding quantum computing is the recognition that this dichotomy is not there: instead of the bit, quantum computing relies on a basic unit of information called a qubit (short for "quantum bit"). The qubit is simultaneously one, zero and everything in between.

This is the moment to stop and explain the theory that underlies the quantum computer, and which seems to go against common sense. "Quantum theory makes it possible to explain the behavior of very, very small particles," Gil explains. "At school we are presented with a model of an atom that looks like a planet, with a nucleus and electrons moving around, but at the beginning of the 20th century, this model turned out to be not very accurate." This happened when physicists such as Max Planck and Albert Einstein realized that light, which until then physics saw as a wave, also behaves as a particle - and the energy of this particle can only be described in "quantum" jumps, that is, as discrete packets. In the decades that followed, this theory was developed more and more, and proved to be effective in describing a variety of phenomena in the world of particles. And yet, its deep meanings remain obscure even today.

Such is, for example, the idea that a particle is in more than one place. According to quantum theory, a particle moving between two points moves simultaneously in all the paths between them, a state called "superposition". It's not that we don't know its exact location: it just doesn't have one. Instead, it has a distribution of possible locations that coexist. In other words, reality is not certain, but probabilistic.

And this is not the only puzzle posed by quantum theory. Another confusing concept is "entanglement", a situation in which several particles exhibit identical physical values, and respond simultaneously to a change in one of them, even if they are at a great distance from each other. Gil suggests thinking of it as tossing two coins: anyone who has studied statistics knows that the probabilities of getting a "head" or a "tail" on each of them are independent. But in the quantum model, if the coins (representing particles here) are intertwined, then tossing one of them will result in the same result in the other. "Einstein didn't believe in interweaving, and hated these patterns," Gil says with a smile.

Measurements that affect the results? A reality that is not absolute but statistical? Particles that become twins even at infinite distance? If these ideas sound puzzling, incomprehensible or counter-intuitive to you, you are not alone: "Whoever comes across quantum theory and is not left stunned, has not understood it," said the physicist Niels Bohr, Einstein's contemporary and his great nemesis, who won the Nobel Prize for his contribution to the development of the theory (Einstein, by the way, had reservations about Bohr's interpretation of the theory's conclusions). Another physicist who won the Nobel Prize for his contribution to the theory, Richard Feynman, commented on this when he said: "If you think you have understood quantum theory, you have not."

The same Feynman is the father of quantum computing: he wanted to simulate the behavior of particles, but due to the probabilistic nature of the theory, a classical computer that would try to perform such a simulation would require an enormous amount of calculations, so that the simulation would become impractical. "Feynman, and like him other physicists, thought that the field of computing focused on mathematical horizons and moved too far away from nature, and that physics could be more connected to the world of information," explains Gil. "In a historic lecture he gave in 1981, Feynman claimed that there was nothing to give a classical computer to deal with particle simulation, because nature is not classical. He said, 'If we want to simulate nature, we need a machine that behaves like nature, in a quantum way.'" In 1998, this vision was realized, when the first quantum computer was built at the University of Oxford in Great Britain.

A quantum computer utilizes the enigmatic properties of quantum theory, those that are not fully understood by us, to perform calculation operations. In a normal computer, the basic unit of information is a "bit", which can have one of two values, 0 or 1; Using such bits makes it possible to perform any calculation imaginable - although some of these calculations may take a very long time. In a quantum computer, the qubit, thanks to superposition, represents not one absolute value, but a distribution of values. "You can think of it as a question of more dimensions: one and zero are just the ends, the poles of a coin for example, but it can also have a sideways tilt," explains Gil. Using statistical approaches it is possible to examine the state of the qubit and obtain useful results. This probabilistic approach is not suitable for every problem, but in solving certain problems it is infinitely more efficient than the classical computer's search for an absolute answer.

"Because of the entanglement effect, it is also possible to cause the qubits to influence each other," says Gil. And since each qubit represents an entire field of possibilities, each addition of a qubit increases the number of possible connections between the qubits with exponentially increasing power (in the classical computer, on the other hand, the addition of bits grows linearly). At the moment, IBM holds the record for qubits: last year it unveiled a quantum processor with 127 qubits, and its stated goal is to launch a processor with 433 qubits this year, and a processor with 1,021 qubits next year.

Three degrees colder than outer space

This ambition is more pretentious than it seems. It turns out that "building a machine that will behave like nature" is a complex story like no other: the qubits are very sensitive to outside influences, which makes building a computer a very complicated and expensive business. "The quantum computer is very powerful, but at the same time also very delicate," explains Gil: "It utilizes physical processes that occur in the world, but such processes are a system in which everything is connected, everything affects everything, and this can disrupt the results: if energy from the outside world goes inside and connect to the qubits, this will make them behave like normal bits, and thus the unique ability of quantum computation will be lost. Therefore, a quantum computer must be very isolated from the entire environment. The big challenge is to produce a system that is sufficiently isolated from the outside world, but not too isolated."

When I try to find out what the cost of building a quantum computer is - and IBM has already built 40 of them - Gil avoids a clear answer, but it is enough to hear what this effort entails: "There are several different approaches to building a quantum computer; IBM chose a cryogenic approach, meaning deep freezing, and the use of superconductors. The temperature in the computer is close to absolute zero: at the bottom of its case the temperature is minus 273 degrees Celsiusthree degrees less than the temperature of outer space, and less than one degree above absolute zero. The temperature should be close to absolute zero, but not reach it, because then there is no movement at all, Not even of the atoms."

The result is a cooling and protection case that resembles a water heater in its shape, and inside it has the calculation unit, whose shape gave it the nickname "chandelier" according to Gil and his team. "Inside the layers of protection there is a cylinder with the processor in it. Even if only a fraction of an energy particle enters the computer, literally a fraction of nothing, it will be enough to disrupt the results," Gil clarifies.

The great sensitivity, and the protection requirements derived from it, mean that the quantum computer is quite cumbersome: in the newest models, which try to include more and more qubits, the case already reaches a height of several meters. To some extent it is reminiscent of the first generations of classic computers, which looked like huge cabinets. Those classic computers kept getting smaller and smaller, until today we squeeze millions of times more computing power into a simple smartphone, but in the case of quantum computers, we cannot expect a similar process: "The quantum computer requires unique conditions that cannot be produced in a simple terminal device, and this will not change in the foreseeable future," Gil explains. "I believe that quantum computing will be a service that we can access remotely, as we access cloud services today. It will work similar to what IBM already enables today: the computer sits with us, and we make it possible to access the 'brain' and receive answers. Of the 40 computers we have built since 2016, today 20 are available to the public. About half a million users all over the world have already made use of the capabilities of the quantum computer we built, and based on this use, about a thousand scientific publications have already been published."

Google and Microsoft are heating up the competition

IBM is not the only company participating in the quantum computing race, but Gil exudes full confidence in its ability to lead it: according to him, most competitors only have parts of the overall system, but not a complete computer available to solve problems. Google, as mentioned, is a strong contender in this race, and it also allows remote access to its quantum computing service, Google Quantum AI; Microsoft is also working to provide a similar service on its cloud platform, Azure.

Meanwhile, quantum computing is a promise "on paper". The theoretical foundations for this revolution were laid already 40 years ago, the first proofs were presented more than 20 years ago, the industry has been buzzing around this field for several years - and we still haven't seen uses that would serve a regular person.

"If you go back to the 1940s, when the first computers were invented, you will see that even then the uses and advantages of the new invention were not clear. Those who saw the first computers said, 'Oh, great, you can use it to crack the code of encryption machines in wars, maybe even calculate routes of ballistic missiles, and that's it. Who's going to use it? Nobody,'" Gil laughs. "In the same way, the success of quantum computing will depend on its uses: how easy it will be to program, how large the community of users will be, what talents will get there. The quantum revolution will be led by a community, which is why education for this field is so important: we need more and more smart people to start to think 'how can I use quantum computing to advance my field'.

"What is beginning these days is the democratization phase of quantum computing, which will allow anyone to communicate with the computer without being an advanced programmer in the field: it will be possible to approach it with a question or a task that will be written in the classical languages of one or zero. That is why we are already seeing more use of quantum computing capacity today.

"There are also many startups that do not actually work to establish a quantum computer, but focus on various components of this world (for example, the Israeli company Quantum Machines, which develops hardware and software systems for quantum computers, and last July was selected by the Innovation Authority to establish the Israeli Quantum Computing Center). The activity of such companies creates a completely new ecosystem, thus promoting the industry and accelerating its development, just as is happening today in the field of ordinary computers. IBM will not rely only on itself either: we would like to benefit from the innovation of smart people in this field, of course also in Israel.

"I am convinced that the big bang of quantum computing will happen in this decade. Our ambition at IBM is to demonstrate 'quantum supremacy' already in the next three years. I believe that the combination of advances in artificial intelligence, together with quantum computing, will bring about a revolution in the industry of the kind that Nvidia made in its market (Nvidia developed unique processors for gaming computers, which made it the chip company that reached a billion dollar revenue the fastest.) Quantum computing can generate enormous value in the industry. It is phenomenally difficult, but it is clear to me that we will see the uses already in the current decade."

The Nobel Prize opens a new horizon for quantum computing

Quantum computing has ignited the imagination of researchers for many decades, but until now it has not left the confines of laboratories. However, the awarding of the Nobel Prize to three researchers in the field indicates that the vision is becoming a real revolution. Alain Aspect of France, the American John Clauser and Austrian Anton Zeilinger received the award for research they conducted (separately) since the 1970s, in which they examined the phenomenon of quantum entanglement (described in the article), proved its existence and laid tracks for its technological use.

The awarding of the Nobel Prize to the entanglement researchers proves that quantum computing is more than a mental exercise for a sect of physicists, and is a defining moment for companies that invest capital in the development of the field. They are pushed to this effort due to a fundamental change in the world in which they operate: in recent decades, the world of computing has operated according to "Moore's Law", which foresees that the density of transistors in computer processors will double every two years in a way that will increase the computing power of these chips. However, as the industry approaches the physical limit after which it will be impossible to cram more transistors onto a chip, the need to develop a quantum computer has become acute.

The numbers also signal that something is happening in the field. In 2020, the scope of the quantum computing market was less than half a billion dollars, but at the end of 2021, in a signal that the vision is beginning to be realized, the research company IDC published an estimate according to which in 2027 the scope of the market will reach $8.6 billion and investments in the field will amount to $16 billion (compared to $700 million in 2020 and $1.4 billion in 2021). IBM CEO Arvind Krishna also recently estimated that in 2027 quantum computing will become a real commercial industry.

Read more from the original source:

Quantum Leap: "The big bang of quantum computing will come in this decade" - CTech

Strategic Partnership Agreement to Develop the Quantum Computing Market in Japan and Asia-Pacific – PR Newswire

TOKYO, CAMBRIDGE, England and BROOMFIELD, Colo., Oct. 18, 2022 /PRNewswire/ -- Mitsui & Co., Ltd ("Mitsui") and Quantinuum have signed a strategic partnership agreement to collaborate in the delivery of quantum computing in Japan and the Asia-Pacific region.

Mitsui, which is committed to digital transformation, and Quantinuum, one of the world's leading quantum computing companies, integrated across hardware and software, have entered this strategic partnership to develop quantum computing use cases, which are expected to drive significant business transformation and innovation in the future.

Mitsui and Quantinuum will accelerate collaboration, cooperation, and development of new business models. They will jointly pursue quantum application development and provide value added services to organizations working across a variety of quantum computing domains, which is expected to be worth US$450B US$850B worldwide by 2040.*

Yoshio Kometani, Representative Director, Executive Vice President and Chief Digital Information Officer of Mitsui & Co., Ltd. stated:"We are very pleased with the strategic partnership between Mitsui and Quantinuum. By combining Quantinuum's cutting-edge quantum computing expertise and diverse quantum talents with Mitsui's broad business platform and network, we will work together to provide new value to our customers and create new business value in a wide range of industrial fields."

Ilyas Khan, Founder and CEO of Quantinuum stated:"The alliance between Mitsui and Quantinuum demonstrates our shared commitment to accelerating quantum computing across all applications and use cases in a diverse range of sectors, including chemistry, finance, and cybersecurity. Today's announcement reinforces our belief in the global quantum leadership shown by corporations and governments in Japan, pioneered by corporate leaders like Mitsui."

Details of the Strategic Partnership

Collaboration areas and applications

Recent Achievements by Quantinuum

About Mitsui & Co., Ltd.

Location: 1-2-1 Otemachi, Chiyoda-ku, Tokyo

Established: 1947

Representative: Kenichi Hori, President and Representative Director

Mitsui & Co., Ltd. (8031: JP) is a global trading and investment company with a diversified business portfolio that spans approximately 63 countries in Asia, Europe, North, Central & South America, The Middle East, Africa and Oceania.

Mitsui has about 5,500 employees and deploys talent around the globe to identify, develop, and grow businesses in collaboration with a global network of trusted partners. Mitsui has built a strong and diverse core business portfolio covering the Mineral and Metal Resources, Energy, Machinery and Infrastructure, and Chemicals industries.

Leveraging its strengths, Mitsui has further diversified beyond its core profit pillars to create multifaceted value in new areas, including innovative Energy Solutions, Healthcare & Nutrition and through a strategic focus on high-growth Asian markets. This strategy aims to derive growth opportunities by harnessing some of the world's main mega-trends: sustainability, health & wellness, digitalization and the growing power of the consumer.

Mitsui has a long heritage in Asia, where it has established a diverse and strategic portfolio of businesses and partners that gives it a strong differentiating edge, provides exceptional access for all global partners to the world's fastest growing region and strengthens its international portfolio.

For more information on Mitsui & Co's businesses visit, https://www.mitsui.com/jp/en/index.html

About Quantinuum

Location: Cambridge, U.K., Broomfield, Colorado, U.S.A.

Established: December 2021 (through the merger of Honeywell Quantum Solutions (U.S.) and Cambridge Quantum Computing (U.K.))

Representative: Ilyas Khan, CEO; Tony Uttley, COO; Shuya Kekke, CEO & Representative Director, Japan

Quantinuum is one of the world's largest integrated quantum computing companies, formed by the combination of Honeywell Quantum Solutions' world-leading hardware and Cambridge Quantum's class-leading middleware and applications. Science-led and enterprise-driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Its focus is to create scalable and commercial quantum solutions to solve the world's most pressing problems in fields such as energy, logistics, climate change, and health. The company employs over 480 individuals, including 350 scientists, at nine sites across the United States, Europe, and Japan.

Selected major customers (in Japan): Nippon Steel Corporation, JSR Corporation

http://www.quantinuum.com

Photo - https://mma.prnewswire.com/media/1923231/Quantinuum.jpgPhoto - https://mma.prnewswire.com/media/1923232/Quantinuum_System_Model.jpg

SOURCE Quantinuum LLC

View post:

Strategic Partnership Agreement to Develop the Quantum Computing Market in Japan and Asia-Pacific - PR Newswire

VW teams with Canadian quantum computing company Xanadu on batteries – Automotive News Canada

Quantum computing, Ardey added in a release, might trigger a revolution in material science that will feed into the companys in-house battery expertise.

Leaving the bits and bytes of classical computing behind, quantum computers rely on qubits, and are widely seen as having potential to solve complex problems that traditional computers could not work through on reasonable timelines.

The automaker and Toronto-based technology firm have already been collaborating on research into material science, computational chemistry, and quantum algorithms for about a year. That early work set the foundation for the formal partnership, Volkswagen said.

The goal of the research is to develop quantum algorithms that can simulate how a blend of battery materials will interact more quickly than traditional computer models. Computational chemistry, which is traditionally used for such work, Ardey said, is reaching limitations when it comes to battery research.

Juan Miguel Arrazola, head of algorithms at Xanadu, said the partnership is part of the Canadian companys drive to make quantum computers truly useful.

Focusing on batteries is a strategic choice given the demand from industry and the prospects for quantum computing to aid in understanding the complex chemistry inside a battery cell.

Using the quantum algorithms, Volkswagen said it aims to develop battery materials that are safer, lighter and cheaper.

Go here to read the rest:

VW teams with Canadian quantum computing company Xanadu on batteries - Automotive News Canada

The world, and todays employees, need quantum computing more than ever – VentureBeat

Did you miss a session from MetaBeat 2022? Head over to the on-demand library for all of our featured sessions here.

Quantum computing can soon address many of the worlds toughest, most urgent problems.

Thats why the semiconductor legislation Congress just passed is part of a $280 billion package that will, among other things, direct federal research dollars toward quantum computing.

Quantum computing will soon be able to:

The economy and the environment are clearly two top federal government agenda items.Congress in July was poised to pass the most ambitious climate bill in U.S. history. The New York Times said that the bill would pump hundreds of billions of dollars into low-carbon energy technologies like wind turbines, solar panels and electric vehicles and would put the United States on track to slash its greenhouse gas emissions to roughly 40% below 2005 levels by 2030. This could help to further advance and accelerate the adoption of quantum computing.

Low-Code/No-Code Summit

Join todays leading executives at the Low-Code/No-Code Summit virtually on November 9. Register for your free pass today.

Because quantum technology can solve many previously unsolvable problems, a long list of the worlds leading businesses including BMW and Volkswagen, FedEx, Mastercard and Wells Fargo, and Merck and Roche are making significant quantum investments. These businesses understand that transformation via quantum computing, which is quickly advancing with breakthrough technologies, is coming soon. They want to be ready when that happens.

Its wise for businesses to invest in quantum computing because the risk is low and the payoff is going to be huge. As BCG notes: No one can afford to sit on the sidelines as this transformative technology accelerates toward several critical milestones.

The reality is that quantum computing is coming, and its likely not going to be a standalone technology. It will be tied to the rest of the IT infrastructure supercomputers, CPUs and GPUs.

This is why companies like Hewlett Packard Enterprise are thinking about how to integrate quantum computing into the fabric of the IT infrastructure. Its also why Terra Quantum AG is building hybrid data centers that combine the power of quantum and classical computing.

Amid these changes, employees should start now to get prepared. There is going to be a tidal wave of need for both quantum Ph.D.s and for other talent such as skilled quantum software developers to contribute to quantum efforts.

Earning a doctorate in a field relevant to quantum computing requires a multi-year commitment. But obtaining valuable quantum computing skills doesnt require a developer to go back to college, take out a student loan or spend years studying.

With modern tools that abstract the complexity of quantum software and circuit creation, developers no longer require Ph.D.-level knowledge to contribute to the quantum revolution, enabling a more diverse workforce to help businesses achieve quantum advantage. Just look at the winners in the coding competition that my company staged. Some of these winners were recent high school graduates, and they delivered highly innovative solutions.

Leading the software stack, quantum algorithm design platforms allow developers to design sophisticated quantum circuits that could not be created otherwise. Rather than defining tedious low-level gate connections, this approach uses high-level functional models and automatically searches millions of circuit configurations to find an implementation that fits resource considerations, designer-supplied constraints and the target hardware platform. New tools like Nvidias QODA also empower developers by making quantum programming similar to how classical programming is done.

Developers will want to familiarize themselves with quantum computing, whichwill be an integral arrow in their metaphorical quiver of engineering skills. People who add quantum skills to their classical programming and data center skills will position themselves to make more money and be more appealing to employers in the long term.

Many companies and countries are experimenting with and adopting quantum computing. They understand that quantum computing is evolving rapidly and is the way of the future.

Whether you are a business leader or a developer, its important to understand that quantum computing is moving forward. The train is leaving the station will you be on board?

Erik Garcell is technical marketing manager at Classiq.

Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.

If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.

You might even considercontributing an articleof your own!

Read More From DataDecisionMakers

Go here to see the original:

The world, and todays employees, need quantum computing more than ever - VentureBeat

CEO Jack Hidary on SandboxAQ’s Ambitions and Near-term Milestones – HPCwire

Spun out from Google last March, SandboxAQ is a fascinating, well-funded start-up targeting the intersection of AI and quantum technology. As the world enters the third quantum revolution, AI + Quantum software will address significant business and scientific challenges, is the companys broad self-described mission. Part software company, part investor, SandboxAQ foresees a blended classical computing-quantum computing landscape with AI infused throughout.

Its developing product portfolio comprises enterprise software for assessing and managing cryptography/data security in the so-called post-quantum era. NIST, of course, released its first official post-quantum algorithms in July and SandboxAQ is one of 12 companies selected to participate in its newproject Migration to Post Quantum Cryptography to build and commercialize tools. SandboxAQs AQ Analyzer product, says the company, is already available and being used by a few marquee customers.

Then theres SandboxAQs Strategic Investment Program, announced in August, which acquires or invests in technology companies of interest. So far, it has acquired one company (Cryptosense) and invested in two others (evolutionQ, and Qunnect).

Last week, HPCwire talked with SandboxAQ CEO Jack Hidary about the companys products and strategy. One has the sense that SandboxAQs aspirations are broad, and with nine figure funding, it has the wherewithal to pivot or expand. The A in the name stands for AI and the Q stands for quantum. One area not on the current agenda: building a quantum computer.

We want to sit above that layer. All these [qubit] technologies ion trap, and NV center (nitrogen vacancy center), neutral atoms, superconducting, photonic are very interesting and we encourage and mentor a lot of these companies who are quantum computing hardware companies. But we are not going to be building one because we really see our value as a layer on top of those computing [blocks], said Hidary. Google, of course, has another group working on quantum hardware.

Hidary joined Google in 2016 as Sandbox group director. A self-described serial entrepreneur, Hidarys varied experience includes founding EarthWeb, being a trustee of the XPrize Foundation, and running for Mayor in New York City in 2013. While at Google Sandbox, he wrote a textbook Quantum Computing: An Applied Approach.

I was recruited in to start a new division to focus on the use of AI and ultimately also quantum in solving really hard problems in the world. We realized that we needed to be multi-platform and focus on all the clouds and to do [other] kinds of stuff so we ended up spinning out earlier this year, said Hidary.

Eric Schmidt joined us about three and a half years ago as he wrapped up his chairmanship at Alphabet (Google parent company). He got really into what were doing, looking at the impact that scaled computation can have both on the AI side and the quantum side. He became chairman of SandboxAQ. I became CEO. Weve other backers like Marc Benioff from Salesforce and T. Rowe Price and Guggenheim, who are very long-term investors. What youll notice here thats interesting is we dont have short-term VCs. Wehave really long term investors who are here for 10 to 15 years.

The immediate focus is on post quantum cryptography tools delivered mostly by a SaaS model. By now were all familiar with the threat that fault-tolerant quantum computers will be able to crack conventionally encrypted (RSA) data using Shors algorithm. While fault-tolerant quantum computers are still many years away, the National Institute of Standards and Technology (NIST) and others, including SandboxAQ, have warned against Store Now/Decrypt Later attacks. (See HPCwire article, The Race to Ensure Post Quantum Data Security).

What adversaries are doing now is siphoning off information over VPNs. Theyre not cracking into your network. Theyre just doing it over VPNs, siphoning that information. They cant read it today, because its RSA protected, but theyll store it and read it in a number of years when they can, he said. The good news is you dont have to scrap your hardware. You could just upgrade the software. But thats still a monumental challenge. As you can imagine, for all the datacenters and the high-performance computing centers this is a non-trivial operation to do all that.

A big part of the problem is simply finding where encryption code is in existing infrastructure. That, in turn, has prompted calls for what is being called crypto-agility a comprehensive yet modular approach that allows easy swapping in-and-out cryptography code.

We want crypto-agility, and what we find is large corporations, large organizations, and large governments dont have crypto-agility. What were hoping is to develop tools to implement this idea. For example, as a first step to crypto-agility, were trying to see if people even have an MRI (discovery metaphor) machine for use on their own cybersecurity, and they really dont when it comes to encryption. Theres no diagnostic tools that these companies are using to find where their [encryption] footprint is or if they are encrypting everything appropriately. Maybe some stuff is not even being encrypted, said Hidary, who favors the MRI metaphor for a discovery tool.

No doubt, the need to modernize encryption/decryption methods and tools represents a huge problem and a huge market.

Without getting into technical details, Hidary said SandboxAQ is leveraging technology from its recent Cryptosense acquisition and internally developed technologies to develop a product portfolio planned to broadly encompass cryptography assessment, deployment and management. Its core current product is AQ Analyzer.

The idea, says Hidary returning to the MRI metaphor, is to take an MRI scan of inside the organization on-premise, cloud, private cloud, and so forth and this feeds into compliance vulnerabilities and post-quantum analysis. Its not just a quantum thing. Its about your general vulnerabilities on encryption. Overall, it happens to be that post quantum is helped by this, but this is a bigger issue. Then that feeds into your general sysops, network ops, and management tools that youre using.

AQ Analyzer, he says, is enterprise software that starts the process for organizations to become crypto-agile. Its now being used at large banks and telcos, and also by Mount Sinai Hospital. Healthcare replete with sensitive information is another early target for SandboxAQ. Long-term the idea is for Sandbox software tools to be able to automate much of the crypto management process from assessment to deployment through ongoing monitoring and management.

Thats the whole crypto-agility ballgame, says Hidary.

The business model, says Hidary, is carbon copy of Salesforce.coms SaaS model. Broadly, SandboxAQ uses a three-prong go-to-market via direct sales, global systems integrators in May it began programs with Ernst & Young (EY) and Deloitte and strategic partners/resellers. Vodafone and SoftBank are among the latter. Even though these are still early days for SandboxAQ as an independent entity, its moving fast, having benefitted from years of development inside Google. AQ Analyzer, said Hidary, is in general availability.

Were doing extremely well in banks and financial institutions. Theyre typically early adopters of cybersecurity because of the regulatory and compliance environment, and the trust they have with their customers, said Hidary.

Looking at near-term milestones, he said, Wed like to see a more global footprint of banks. Well be back in Europe soon now that we have Cryptosense (UK and Paris-based), and we have a local strong team in Europe. Weve had a lot of traction in the U.S. and the Canadian markets. So thats one key milestone over the next 18 months or so. Second, wed like to see [more adoption] into healthcare and telcos. We have Vodafone and Softbank mobile, on the telco side. We have Mount Sinai, wed like to see if that can be extended into additional players in those two spaces. The fourth vertical well probably go into is the energy grid. These are all critical infrastructure pieces of our society the financial structure of our society, energy, healthcare and the medical centers, the telecommunications grid.

While SandboxAQs AQ Analyzer is the companys first offering, its worth noting that the company aggressively looking for niches it can serve. For example, the company is keeping close tab on efforts to build a quantum internet.

Theres going to be a parallel quantum coherent internet to connect for distributed quantum computing, said Hidary. So nothing to do with cyber at all.

Our vision of the future that we share with I think everyone in the industry is that quantum does not take over classical, said Hidary. Its a mesh, a hybridization of CPU, GPU and quantum processing units. And the program, the code, in Python for example: part of it runs on CPUs, part of it on GPUs, and then yes, part of it will run on a QPU. In that mesh, youd want to have access both to the traditional Internet TCP IP today, but you also want to be able to connect over a quantum coherence intranet. So thats Qunnect.

Qunnect, of course, is one of the companies SandboxAQ has invested in and it is working on hardware (quantum memory and repeaters) to enable a quantum internet. Like dealing with post quantum cryptography, outfitting the quantum internet is likely to be as huge business. Looking at SandboxAQ, just seven months after being spun out from Google, the scope of its ambitions is hard to pin down.

Stay tuned.

Here is the original post:

CEO Jack Hidary on SandboxAQ's Ambitions and Near-term Milestones - HPCwire

Cleveland Clinic and IBM Begin Installation of IBM Quantum System One – Cleveland Clinic Newsroom

Cleveland Clinicand IBM have begundeployment of the first private sector onsite,IBM-managedquantum computer in the United States.The IBM Quantum Systemis to be located on Cleveland Clinics main campus in Cleveland.

The first quantum computer in healthcare, anticipated to be completed in early 2023, is a key part of the two organizations10-year partnership aimed at fundamentally advancing the pace of biomedical research through high-performance computing. Announced in 2021, the Cleveland Clinic-IBM Discovery Accelerator is a joint center that leverages Cleveland Clinics medical expertise with the technology expertise of IBM, including its leadership in quantum computing.

The current pace of scientific discovery is unacceptably slow, while our research needs are growing exponentially, said Lara Jehi, M.D., Cleveland Clinics Chief Research Information Officer. We cannot afford to continue to spend a decade or more going from a research idea in a lab to therapies on the market. Quantum offers a future to transform this pace, particularly in drug discovery and machine learning.

A step change in the way we solve scientific problems is on the horizon, said Ruoyi Zhou, Director, Ph.D., IBM Research Cleveland Clinic Partnership. At IBM, were more motivated than ever to create with Cleveland Clinic and others lasting communities of discovery and harness the power of quantum computing, AI and hybrid cloud to usher in a new era of accelerated discovery in healthcare and life sciences.

The Discovery Accelerator at Cleveland Clinic draws upon a variety of IBMs latest advancements in high performance computing, including:

Lara Jehi, M.D., and Ruoyi Zhou, Ph.D., at the site of the IBM Quantum System One on Cleveland Clinics main campus. (Courtesy: Cleveland Clinic/IBM)

The Discovery Accelerator also serves as the technology foundation for Cleveland Clinics Global Center for Pathogen Research & Human Health, part of the Cleveland Innovation District. The center, supported by a $500 million investment from the State of Ohio, Jobs Ohio and Cleveland Clinic, brings together a team focused on studying, preparing and protecting against emerging pathogens and virus-related diseases. Through Discovery Accelerator, researchers are leveraging advanced computational technology to expedite critical research into treatments and vaccines.

Together, the teams have already begun several collaborative projects that benefit from the new computational power. The Discovery Accelerator projects include a research study developing a quantum computing method to screen and optimize drugs targeted to specific proteins; improving a prediction model for cardiovascular risk following non-cardiac surgery; and using artificial intelligence to search genome sequencing findings and large drug-target databases to find effective, existing drugs that could help patients with Alzheimers and other diseases.

A significant part of the collaboration is a focus on educating the workforce of the future and creating jobs to grow the economy. An innovative educational curriculum has been designed for participants from high school to professional level, offering training and certification programs in data science, machine learning and quantum computing to build the skilled workforce needed for cutting-edge computational research of the future.

Read more from the original source:

Cleveland Clinic and IBM Begin Installation of IBM Quantum System One - Cleveland Clinic Newsroom

New laboratory to explore the quantum mysteries of nuclear materials – EurekAlert

Replete with tunneling particles, electron wells, charmed quarks and zombie cats, quantum mechanics takes everything Sir Isaac Newton taught about physics and throws it out the window.

Every day, researchers discover new details about the laws that govern the tiniest building blocks of the universe. These details not only increase scientific understanding of quantum physics, but they also hold the potential to unlock a host of technologies, from quantum computers to lasers to next-generation solar cells.

But theres one area that remains a mystery even in this most mysterious of sciences: the quantum mechanics of nuclear fuels.

Until now, most fundamental scientific research of quantum mechanics has focused on elements such as silicon because these materials are relatively inexpensive, easy to obtain and easy to work with.

Now, Idaho National Laboratory researchers are planning to explore the frontiers of quantum mechanics with a new synthesis laboratory that can work with radioactive elements such as uranium and thorium.

An announcement about the new laboratory appears online in the journalNature Communications.

Uranium and thorium, which are part of a larger group of elements called actinides, are used as fuels in nuclear power reactors because they can undergo nuclear fission under certain conditions.

However, the unique properties of these elements, especially the arrangement of their electrons, also means they could exhibit interesting quantum mechanical properties.

In particular, the behavior of particles in special, extremely thin materials made from actinides could increase our understanding of phenomena such as quantum wells and quantum tunneling (see sidebar).

To study these properties, a team of researchers has built a laboratory around molecular beam epitaxy (MBE), a process that creates ultra-thin layers of materials with a high degree of purity and control.

The MBE technique itself is not new, said Krzysztof Gofryk, a scientist at INL. Its widely used. Whats new is that were applying this method to actinide materials uranium and thorium. Right now, this capability doesnt exist anywhere else in the world that we know of.

The INL team is conducting fundamental research science for the sake of knowledge but the practical applications of these materials could make for some important technological breakthroughs.

At this point, we are not interested in building a new qubit [the basis of quantum computing], but we are thinking about which materials might be useful for that, Gofryk said. Some of these materials could be potentially interesting for new memory banks and spin-based transistors, for instance.

Memory banks and transistors are both important components of computers.

To understand how researchers make these very thin materials, imagine an empty ball pit at a fast-food restaurant. Blue and red balls are thrown in the pit one at a time until they make a single layer on the floor. But that layer isnt a random assortment of balls. Instead, they arrange themselves into a pattern.

During the MBE process, the empty ball pit is a vacuum chamber, and the balls are highly pure elements, such as nitrogen and uranium, that are heated until individual atoms can escape into the chamber.

The floor of our imaginary ball pit is, in reality, a charged substrate that attracts the individual atoms. On the substrate, atoms order themselves to create a wafer of very thin material in this case, uranium nitride.

Back in the ball pit, weve created layer of blue and red balls arranged in a pattern. Now we make another layer of green and orange balls on top of the first layer.

To study the quantum properties of these materials, Gofryk and his team will join two dissimilar wafers of material into a sandwich called a heterostructure. For instance, the thin layer of uranium nitride might be joined to a thin layer of another material such as gallium arsenide, a semiconductor. At the junction between the two different materials, interesting quantum mechanical properties can be observed.

We can make sandwiches of these materials from a variety of elements, Gofryk said. We have lots of flexibility. We are trying to think about the novel structures we can create with maybe some predicted quantum properties.

We want to look at electronic properties, structural properties, thermal properties and how electrons are transported through the layers, he continued. What will happen if you lower the temperature and apply a magnetic field? Will it cause electrons to behave in certain way?

INL is one of the few places where researchers can work with uranium and thorium for this type of science. The amounts of the radioactive materials and the consequent safety concerns will be comparable to the radioactivity found in an everyday smoke alarm.

INL is the perfect place for this research because were interested in this kind of physics and chemistry, Gofryk said.

In the end, Gofryk hopes the laboratory will result in breakthroughs that help attract attention from potential collaborators as well as recruit new employees to the laboratory.

These actinides have such special properties, he said. Were hoping we can discover some new phenomena or new physics that hasnt been found before.

In 1900, German physicist Max Planck first described how light emitted from heated objects, such as the filament in a light bulb, behaved like particles.

Since then, numerous scientists including Albert Einstein and Niels Bohr have explored and expanded upon Plancks discovery to develop the field of physics known as quantum mechanics. In short, quantum mechanics describes the behavior of atoms and subatomic particles.

Quantum mechanics is different than regular physics, in part, because subatomic particles simultaneously have characteristics of both particles and waves, and their energy and movement occur in discrete amounts called quanta.

More than 120 years later, quantum mechanics plays a key role in numerous practical applications, especially lasers and transistors a key component of modern electronic devices. Quantum mechanics also promises to serve as the basis for the next generation of computers, known as quantum computers, which will be much more powerful at solving certain types of calculations.

Uranium, thorium and the other actinides have something in common that makes them interesting for quantum mechanics: the arrangement of their electrons.

Electrons do not orbit around the nucleus the way the earth orbits the sun. Rather, they zip around somewhat randomly. But we can define areas where there is a high probability of finding electrons. These clouds of probability are called orbitals.

For the smallest atoms, these orbitals are simple spheres surrounding the nucleus. However, as the atoms get larger and contain more electrons, orbitals begin to take on strange and complex shapes.

In very large atoms like uranium and thorium (92 and 90 electrons respectively), the outermost orbitals are a complex assortment of party balloon, jelly bean, dumbbell and hula hoop shapes. The electrons in these orbitals are high energy. While scientists can guess at their quantum properties, nobody knows for sure how they will behave in the real world.

Quantum tunneling is a key part of any number of phenomena, including nuclear fusion in stars, mutations in DNA and diodes in electronic devices.

To understand quantum tunneling, imagine a toddler rolling a ball at a mountain. In this analogy, the ball is a particle. The mountain is a barrier, most likely a semiconductor material. In classical physics, theres no chance the ball has enough energy to pass over the mountain.

But in the quantum realm, subatomic particles have properties of both particles and waves. The waves peak represents the highest probability of finding the particle. Thanks to a quirk of quantum mechanics, while most of the wave bounces off the barrier, a small part of that wave travels through if the barrier is thin enough.

For a single particle, the small amplitude of this wave means there is a very small chance of the particle making it to the other side of the barrier.

However, when large numbers of waves are travelling at a barrier, the probability increases, and sometimes a particle makes it through. This is quantum tunneling.

Quantum wells are also important, especially for devices such as light emitting diodes (LEDs) and lasers.

Like quantum tunneling, to build quantum wells, you need alternating layers of very thin (10 nanometers) material where one layer is a barrier.

While electrons normally travel in three dimensions, quantum wells trap electrons in two dimensions within a barrier that is, for practical purposes, impossible to overcome. These electrons exist at specific energies say the precise energies needed to generate specific wavelengths of light.

About Idaho National LaboratoryBattelle Energy Alliance manages INL for the U.S. Department of Energys Office of Nuclear Energy. INL is the nations center for nuclear energy research and development,and alsoperforms research in each of DOEs strategic goal areas: energy, national security, science and the environment. For more information, visitwww.inl.gov.Follow us on social media:Twitter,Facebook,InstagramandLinkedIn.

View post:

New laboratory to explore the quantum mysteries of nuclear materials - EurekAlert

Cancer to Be Treated as Easily as Common Cold When Humans Crack Quantum Computing – Business Wire

DUBAI, United Arab of Emirates--(BUSINESS WIRE)--Breakthroughs in quantum computing will enable humans to cure diseases like cancer, Alzheimers, and Parkinsons as easily as we treat the common cold.

That was one of the major insights to emerge from the Dubai Future Forum, with renowned theoretical physicist Dr. Michio Kaku telling the worlds largest gathering of futurists that humanity should brace itself for major transformations in healthcare.

The forum concluded with a call for governments to institutionalize foresight and engrain it within decision making.

Taking place in Dubai, UAE at the Museum of the Future, Amy Webb, CEO of Future Today Institute, criticized nations for being too pre-occupied with the present and too focused on creating white papers, reports and policy recommendations instead of action.

Nowism is a virus. Corporations and governments are infected, she said.

One panel session heard how humans could be ready to test life on the Moon in just 15 years and be ready for life on Mars in another decade. Sharing his predictions for the future, Dr. Kaku also said there is a very good chance humans will pick up a signal from another intelligent life form this century.

Dr. Jamie Metzl, Founder and Chair, OneShared.World, urged people to eat more lab-grown meat to combat global warming and food insecurity.

If we are treating them like a means to an end of our nutrition, wouldnt it be better instead of growing the animal, to grow the meat? he said.

Among the 70 speakers participating in sessions were several UAE ministers. HE Mohammad Al Gergawi, UAE Minister of Cabinet Affairs, Vice Chairman, Board of Trustees and Managing Director of the Dubai Future Foundation, said ministers around the world should think of themselves as designers of the future. Our stakeholders are 7.98 billion people around the world, he noted.

Dubais approach to foresight was lauded by delegates, including HE Omar Sultan Al Olama, UAE Minister of State for Artificial Intelligence, Digital Economy, and Remote Work Applications, who said: What makes our city and nation successful is not natural resources, but a unique ability to embrace all ideas and individuals.

More than 30 sessions covered topics including immortality, AI sentience, climate change, terraforming, genome sequencing, legislation, and the energy transition.

*Source: AETOSWire

Follow this link:

Cancer to Be Treated as Easily as Common Cold When Humans Crack Quantum Computing - Business Wire

What is quantum computing? – TechTarget

Quantum computing is an area of study focused on the development of computer based technologies centered around the principles ofquantum theory. Quantum theory explains the nature and behavior of energy and matter on thequantum(atomic and subatomic) level. Quantum computing uses a combination ofbitsto perform specific computational tasks. All at a much higher efficiency than their classical counterparts. Development ofquantum computersmark a leap forward in computing capability, with massive performance gains for specific use cases. For example quantum computing excels at like simulations.

The quantum computer gains much of its processing power through the ability for bits to be in multiple states at one time. They can perform tasks using a combination of 1s, 0s and both a 1 and 0 simultaneously. Current research centers in quantum computing include MIT, IBM, Oxford University, and the Los Alamos National Laboratory. In addition, developers have begun gaining access toquantum computers through cloud services.

Quantum computing began with finding its essential elements. In 1981, Paul Benioff at Argonne National Labs came up with the idea of a computer that operated with quantum mechanical principles. It is generally accepted that David Deutsch of Oxford University provided the critical idea behind quantum computing research. In 1984, he began to wonder about the possibility of designing a computer that was based exclusively on quantum rules, publishing a breakthrough paper a few months later.

Quantum Theory

Quantum theory's development began in 1900 with a presentation by Max Planck. The presentation was to the German Physical Society, in which Planck introduced the idea that energy and matter exists in individual units. Further developments by a number of scientists over the following thirty years led to the modern understanding of quantum theory.

Quantum Theory

Quantum theory's development began in 1900 with a presentation by Max Planck. The presentation was to the German Physical Society, in which Planck introduced the idea that energy and matter exists in individual units. Further developments by a number of scientists over the following thirty years led to the modern understanding of quantum theory.

The Essential Elements of Quantum Theory:

Further Developments of Quantum Theory

Niels Bohr proposed the Copenhagen interpretation of quantum theory. This theory asserts that a particle is whatever it is measured to be, but that it cannot be assumed to have specific properties, or even to exist, until it is measured. This relates to a principle called superposition. Superposition claims when we do not know what the state of a given object is, it is actually in all possible states simultaneously -- as long as we don't look to check.

To illustrate this theory, we can use the famous analogy of Schrodinger's Cat. First, we have a living cat and place it in a lead box. At this stage, there is no question that the cat is alive. Then throw in a vial of cyanide and seal the box. We do not know if the cat is alive or if it has broken the cyanide capsule and died. Since we do not know, the cat is both alive and dead, according to quantum law -- in a superposition of states. It is only when we break open the box and see what condition the cat is in that the superposition is lost, and the cat must be either alive or dead.

The principle that, in some way, one particle can exist in numerous states opens up profound implications for computing.

A Comparison of Classical and Quantum Computing

Classical computing relies on principles expressed by Boolean algebra; usually Operating with a 3 or 7-modelogic gateprinciple. Data must be processed in an exclusive binary state at any point in time; either 0 (off / false) or 1 (on / true). These values are binary digits, or bits. The millions of transistors and capacitors at the heart of computers can only be in one state at any point. In addition, there is still a limit as to how quickly these devices can be made to switch states. As we progress to smaller and faster circuits, we begin to reach the physical limits of materials and the threshold for classical laws of physics to apply.

The quantum computer operates with a two-mode logic gate:XORand a mode called QO1 (the ability to change 0 into a superposition of 0 and 1). In a quantum computer, a number of elemental particles such as electrons or photons can be used. Each particle is given a charge, or polarization, acting as a representation of 0 and/or 1. Each particle is called a quantum bit, or qubit. The nature and behavior of these particles form the basis of quantum computing and quantum supremacy. The two most relevant aspects of quantum physics are the principles of superposition andentanglement.

Superposition

Think of a qubit as an electron in a magnetic field. The electron's spin may be either in alignment with the field, which is known as aspin-upstate, or opposite to the field, which is known as aspin-downstate. Changing the electron's spin from one state to another is achieved by using a pulse of energy, such as from alaser. If only half a unit of laser energy is used, and the particle is isolated the particle from all external influences, the particle then enters a superposition of states. Behaving as if it were in both states simultaneously.

Each qubit utilized could take a superposition of both 0 and 1. Meaning, the number of computations a quantum computer could take is 2^n, where n is the number of qubits used. A quantum computer comprised of 500 qubits would have a potential to do 2^500 calculations in a single step. For reference, 2^500 is infinitely more atoms than there are in the known universe. These particles all interact with each other via quantum entanglement.

In comparison to classical, quantum computing counts as trueparallel processing. Classical computers today still only truly do one thing at a time. In classical computing, there are just two or more processors to constitute parallel processing.EntanglementParticles (like qubits) that have interacted at some point retain a type can be entangled with each other in pairs, in a process known ascorrelation. Knowing the spin state of one entangled particle - up or down -- gives away the spin of the other in the opposite direction. In addition, due to the superposition, the measured particle has no single spin direction before being measured. The spin state of the particle being measured is determined at the time of measurement and communicated to the correlated particle, which simultaneously assumes the opposite spin direction. The reason behind why is not yet explained.

Quantum entanglement allows qubits that are separated by large distances to interact with each other instantaneously (not limited to the speed of light). No matter how great the distance between the correlated particles, they will remain entangled as long as they are isolated.

Taken together, quantum superposition and entanglement create an enormously enhanced computing power. Where a 2-bit register in an ordinary computer can store only one of four binary configurations (00, 01, 10, or 11) at any given time, a 2-qubit register in a quantum computer can store all four numbers simultaneously. This is because each qubit represents two values. If more qubits are added, the increased capacity is expanded exponentially.

Quantum Programming

Quantum computing offers an ability to write programs in a completely new way. For example, a quantum computer could incorporate a programming sequence that would be along the lines of "take all the superpositions of all the prior computations." This would permit extremely fast ways of solving certain mathematical problems, such as factorization of large numbers.

The first quantum computing program appeared in 1994 by Peter Shor, who developed a quantum algorithm that could efficiently factorize large numbers.

The Problems - And Some Solutions

The benefits of quantum computing are promising, but there are huge obstacles to overcome still. Some problems with quantum computing are:

There are many problems to overcome, such as how to handle security and quantum cryptography. Long time quantum information storage has been a problem in the past too. However, breakthroughs in the last 15 years and in the recent past have made some form of quantum computing practical. There is still much debate as to whether this is less than a decade away or a hundred years into the future. However, the potential that this technology offers is attracting tremendous interest from both the government and the private sector. Military applications include the ability to break encryptions keys via brute force searches, while civilian applications range from DNA modeling to complex material science analysis.

See the article here:

What is quantum computing? - TechTarget