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Category Archives: Quantum Computing
Posted: March 26, 2020 at 6:43 am
Preamble: Intermittently, I will be introducing some columns which introduce some seemingly outlandish concepts. The purpose is a bit of humor, but also to provoke some thought. Enjoy.
atom orbit abstract
God does not play dice with the universe, Albert Einstein is reported to have said about the field of Quantum Physics. He was referring to the great divide at the time in the physics community between general relativity and quantum physics. General relativity was a theory which beautifully explained a great deal of physical phenomena in a deterministic fashion. Meanwhile, quantum physics grew out of a model which fundamentally had a probabilistic view of the world. Since Einstein made that statement in the mid 1950s, quantum physics has proven to be quite a durable theory, and in fact, it is used in a variety of applications such as semiconductors.
One might imagine a past leader in computer science such as Donald Knuth exclaiming, Algorithms should be deterministic. That is, given any input, the output should be exact and known. Indeed, since its formation, the field of computer science has focused on building elegant deterministic algorithms which have a clear view of the transformation between inputs and outputs. Even in the regime of non-determinism such as parallel processing, the objective of the overall algorithm is to be deterministic. That is, despite the fact that operations can run out-of-order, the outputs are still exact and known. Computer scientists work very hard to make that a reality.
As computer scientists have engaged with the real world, they frequently face very noisy inputs such as sensors or even worse, human beings. Computer algorithms continue to focus on faithfully and precisely translating input noise to output noise. This has given rise to the Junk In Junk Out (JIJO) paradigm. One of the key motivations for pursuing such a structure has been the notion of causality and diagnosability. After all, if the algorithms are noisy, how is one to know the issue is not a bug in the algorithm? Good point.
With machine learning, computer science has transitioned to a model where one trains a machine to build an algorithm, and this machine can then be used to transform inputs to outputs. Since the process of training is dynamic and often ongoing, the data and the algorithm are intertwined in a manner which is not easily unwound. Similar to quantum physics, there is a class of applications where this model seems to work. Recognizing patterns seems to be a good application. This is a key building block for autonomous vehicles, but the results are probabilistic in nature.
In quantum physics, there is an implicit understanding that the answers are often probabilistic Perhaps this is the key insight which can allow us to leverage the power of machine learning techniques and avoid the pitfalls. That is, if the requirements of the algorithm must be exact, perhaps machine learning methods are not appropriate. As an example, if your bank statement was correct with somewhat high probability, this may not be comforting. However, if machine learning algorithms can provide with high probability the instances of potential fraud, the job of a forensic CPA is made quite a bit more productive. Similar analogies exist in the area of autonomous vehicles.
Overall, machine learning seems to define the notion of probabilistic algorithms in computer science in a similar manner as quantum physics. The critical challenge for computing is to find the correct mechanisms to design and validate probabilistic results.
Research by University of Chicago PhD Student and EPiQC Wins IBM Q Best Paper – Quantaneo, the Quantum Computing Source
Posted: at 6:43 am
The interdisciplinary team of researchers from UChicago, University of California, Berkeley, Princeton University and Argonne National Laboratory won the $2,500 first-place award for Best Paper. Their research examined how the VQE quantum algorithm could improve the ability of current and near-term quantum computers to solve highly complex problems, such as finding the ground state energy of a molecule, an important and computationally difficult chemical calculation the authors refer to as a killer app for quantum computing.
Quantum computers are expected to perform complex calculations in chemistry, cryptography and other fields that are prohibitively slow or even impossible for classical computers. A significant gap remains, however, between the capabilities of todays quantum computers and the algorithms proposed by computational theorists.
VQE can perform some pretty complicated chemical simulations in just 1,000 or even 10,000 operations, which is good, Gokhale says. The downside is that VQE requires millions, even tens of millions, of measurements, which is what our research seeks to correct by exploring the possibility of doing multiple measurements simultaneously.
Gokhale explains the research in this video.
With their approach, the authors reduced the computational cost of running the VQE algorithm by 7-12 times. When they validated the approach on one of IBMs cloud-service 20-qubit quantum computers, they also found lower error as compared to traditional methods of solving the problem. The authors have shared their Python and Qiskit code for generating circuits for simultaneous measurement, and have already received numerous citations in the months since the paper was published.
For more on the research and the IBM Q Best Paper Award, see the IBM Research Blog. Additional authors on the paper include Professor Fred Chong and PhD student Yongshan Ding of UChicago CS, Kaiwen Gui and Martin Suchara of the Pritzker School of Molecular Engineering at UChicago, Olivia Angiuli of University of California, Berkeley, and Teague Tomesh and Margaret Martonosi of Princeton University.
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Posted: at 6:43 am
When an egg cell of almost any sexually reproducing species is fertilized, it sets off a series of waves that ripple across the egg's surface.
These waves are produced by billions of activated proteins that surge through the egg's membrane like streams of tiny burrowing sentinels, signaling the egg to start dividing, folding, and dividing again, to form the first cellular seeds of an organism.
Now MIT scientists have taken a detailed look at the pattern of these waves, produced on the surface of starfish eggs. These eggs are large and therefore easy to observe, and scientists consider starfish eggs to be representative of the eggs of many other animal species.
In each egg, the team introduced a protein to mimic the onset of fertilization, and recorded the pattern of waves that rippled across their surfaces in response. They observed that each wave emerged in a spiral pattern, and that multiple spirals whirled across an egg's surface at a time. Some spirals spontaneously appeared and swirled away in opposite directions, while others collided head-on and immediately disappeared.
The behavior of these swirling waves, the researchers realized, is similar to the waves generated in other, seemingly unrelated systems, such as the vortices in quantum fluids, the circulations in the atmosphere and oceans, and the electrical signals that propagate through the heart and brain.
"Not much was known about the dynamics of these surface waves in eggs, and after we started analyzing and modeling these waves, we found these same patterns show up in all these other systems," says physicist Nikta Fakhri, the Thomas D. and Virginia W. Cabot Assistant Professor at MIT. "It's a manifestation of this very universal wave pattern."
"It opens a completely new perspective," adds Jrn Dunkel, associate professor of mathematics at MIT. "You can borrow a lot of techniques people have developed to study similar patterns in other systems, to learn something about biology."
Fakhri and Dunkel have published their results today in the journal Nature Physics. Their co-authors are Tzer Han Tan, Jinghui Liu, Pearson Miller, and Melis Tekant of MIT.
Previous studies have shown that the fertilization of an egg immediately activates Rho-GTP, a protein within the egg which normally floats around in the cell's cytoplasm in an inactive state. Once activated, billions of the protein rise up out of the cytoplasm's morass to attach to the egg's membrane, snaking along the wall in waves.
"Imagine if you have a very dirty aquarium, and once a fish swims close to the glass, you can see it," Dunkel explains. "In a similar way, the proteins are somewhere inside the cell, and when they become activated, they attach to the membrane, and you start to see them move."
Fakhri says the waves of proteins moving across the egg's membrane serve, in part, to organize cell division around the cell's core.
"The egg is a huge cell, and these proteins have to work together to find its center, so that the cell knows where to divide and fold, many times over, to form an organism," Fakhri says. "Without these proteins making waves, there would be no cell division."
MIT researchers observe ripples across a newly fertilized egg that are similar to other systems, from ocean and atmospheric circulations to quantum fluids. Courtesy of the researchers.
In their study, the team focused on the active form of Rho-GTP and the pattern of waves produced on an egg's surface when they altered the protein's concentration.
For their experiments, they obtained about 10 eggs from the ovaries of starfish through a minimally invasive surgical procedure. They introduced a hormone to stimulate maturation, and also injected fluorescent markers to attach to any active forms of Rho-GTP that rose up in response. They then observed each egg through a confocal microscope and watched as billions of the proteins activated and rippled across the egg's surface in response to varying concentrations of the artificial hormonal protein.
"In this way, we created a kaleidoscope of different patterns and looked at their resulting dynamics," Fakhri says.
The researchers first assembled black-and-white videos of each egg, showing the bright waves that traveled over its surface. The brighter a region in a wave, the higher the concentration of Rho-GTP in that particular region. For each video, they compared the brightness, or concentration of protein from pixel to pixel, and used these comparisons to generate an animation of the same wave patterns.
From their videos, the team observed that waves seemed to oscillate outward as tiny, hurricane-like spirals. The researchers traced the origin of each wave to the core of each spiral, which they refer to as a "topological defect." Out of curiosity, they tracked the movement of these defects themselves. They did some statistical analysis to determine how fast certain defects moved across an egg's surface, and how often, and in what configurations the spirals popped up, collided, and disappeared.
In a surprising twist, they found that their statistical results, and the behavior of waves in an egg's surface, were the same as the behavior of waves in other larger and seemingly unrelated systems.
"When you look at the statistics of these defects, it's essentially the same as vortices in a fluid, or waves in the brain, or systems on a larger scale," Dunkel says. "It's the same universal phenomenon, just scaled down to the level of a cell."
The researchers are particularly interested in the waves' similarity to ideas in quantum computing. Just as the pattern of waves in an egg convey specific signals, in this case of cell division, quantum computing is a field that aims to manipulate atoms in a fluid, in precise patterns, in order to translate information and perform calculations.
"Perhaps now we can borrow ideas from quantum fluids, to build minicomputers from biological cells," Fakhri says. "We expect some differences, but we will try to explore [biological signaling waves] further as a tool for computation."
This research was supported, in part, by the James S. McDonnell Foundation, the Alfred P. Sloan Foundation, and the National Science Foundation.
Reprinted with permission of MIT News. Read the original article.
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Posted: at 6:43 am
Fountech.Ventures, a next generation incubator for deep tech startups, has launched in the US and UK.
The subsidiary company ofFountech.ai, a four-year-old international AI think tank and parent company to a number of specialist AI and deep tech firms, is based in Austin, Texas, US and originated in London, UK.
Fountech.Ventures goes above and beyond a standard incubator it provides broader services over a longer timeframe so founders of deep tech startups can fast-track their businesses from ideation to commercial success.
Fountech.Ventures develops tailored programmes for members, sharing technical and commercial knowledge, along with the provision of interim CEOs, funding, business advice, office space and international networking opportunities.
Headed by Salvatore Minetti, a team of experienced tech experts will work with deep tech startups spanning artificial intelligence (AI), robotics, quantum computing and blockchain.
Based on progress and continuous assessments, Fountech.Ventures will invest its own funds into its portfolio companies, from pre-seed level right through to Series B.
Banking alternative fintech company Lanistar launches
Salvatore Minetti, CEO of Fountech.Ventures, said: The US and UK are home to a vast number of deep tech startups that have immense growth potential. However, reaching that potential is difficult tech experts and PhD graduates have incredible ideas for how to use new and advanced technologies but often lack the skills and experience to transform them into successful businesses.
Fountech.Ventures will change all this by delivering the commercial expertise and infrastructure that is sorely needed. Whats more, the fact that our members can also access vital funding and our international hubs means we have a unique ability to bring products and services grounded in leading edge technologies to huge markets.
It is this end-to-end offering that makes us more than a typical incubator Fountech.Ventures is a next generation incubator.
Fountech.Ventures already has six portfolio companies. These include Soffos, an AI TutorBot; Prospex, an AI-powered lead generation tool; and Dinabite, a restaurant app built on an AI platform.
Advanced acquires Tikit from BT Group
Rebecca Taylor and Joseph McCall have joined the Fountech.Ventures board as directors. The board is to be bolstered further with additional appointments in the coming weeks.
Nikolas Kairinos, CEO and founder of the parent company Fountech.ai, commented: We are delighted to unveil Fountech.Ventures today.
This next gen incubator is going to propel the growth of deep tech startups across both sides of the Atlantic. In doing so, we will enable innovative leading edge tech solutions to thrive and consequently improve the lives of consumers, businesses and societies.
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Recent PDF Report : Quantum Computing Market 2020: In-depth Industry Analysis By Size, Share, Competition, Opportunities And Growth By 2029 – Sound On…
Posted: at 6:43 am
MarketResearch.biz sets out the latest report on the Global Quantum Computing Market that includes an in-depth analysis of competition, segmentation, regional expansion, market dynamics and forecast 2020-2029.
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A basic outline of the competitive landscape:
The Quantum Computing market report includes a thorough analysis of the competitive landscape of this industry.
The report also encompasses a thorough analysis of the markets competitors scope based on the segmentation of the same into companies such as International Business Machines (IBM) Corporation, Google Inc, Microsoft Corporation, Qxbranch LLC, Cambridge Quantum Computing Ltd, 1QB Information Technologies Inc, QC Ware Corp., Magiq Technologies Inc, D-Wave Systems Inc, Rigetti Computing.
The study covers details on the individual market share of each industry contributor, the region served and more.
Key players Profiles covered in the report alongside facts concerning its futuristic strategies, financials, technological developments, supply chain study, collaboration & mergers, gross margins and price models.
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A complete outline of the regional spectrum:
A crisp outline of the market segmentation:
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Segmentation by Component:
GeneratorConversion DevicesDistribution DevicesBattery Management SystemsOthers (Alternators, etc.)Segmentation by System:
Power GenerationPower DistributionPower ConversionEnergy StorageSegmentation by Platform:
Military AviationCommercial AviationBusiness & General AviationSegmentation by Application:
Cabin SystemFlight Control & OperationConfiguration ManagementPower Generation ManagementAir Pressurization & Conditioning
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Different questions addressed through this research report:
What are the affecting factors for the growth of the market?
What are the major restraints and drivers of market?
What will be the market size in 2029?
Which are the most demanding regions in terms of consumption and production?
key outcomes of industry analysis techniques?
What are the successful key players in market?
Table of Content
1 Introduction of Quantum Computing Market
1.1 Overview of the Market
1.2 Scope of Report
2 Executive Summary
3 Research Methodology of MarketResearch.biz
3.1 Data Mining
3.3 Primary Interviews
3.4 List of Data Sources
4 Quantum Computing Market Outlook
4.2 Market Dynamics
4.3 Porters Five Force Model
4.4 Value Chain Analysis
5 Quantum Computing Market , Segmentation
6 Quantum Computing Market , By Geography
6.2 North America
6.3.4 Rest of Europe
6.4 Asia Pacific
6.4.4 Rest of Asia Pacific
6.5 Rest of the World
6.5.1 Latin America
6.5.2 Middle East
7 Quantum Computing Market Competitive Landscape
7.2 Company Market Ranking
7.3 Key Development Strategies
8 Company Profiles
8.1.2 Financial Performance
8.1.3 Product Outlook
8.1.4 Key Developments
9.1 Related Research
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Originally posted here:
Posted: March 24, 2020 at 6:21 am
When you first stumble across the term quantum computer, you might pass it off as some far-flung science fiction concept rather than a serious current news item.
But with the phrase being thrown around with increasing frequency, its understandable to wonder exactly what quantum computers are, and just as understandable to be at a loss as to where to dive in. Heres the rundown on what quantum computers are, why theres so much buzz around them, and what they might mean for you.
All computing relies on bits, the smallest unit of information that is encoded as an on state or an off state, more commonly referred to as a 1 or a 0, in some physical medium or another.
Most of the time, a bit takes the physical form of an electrical signal traveling over the circuits in the computers motherboard. By stringing multiple bits together, we can represent more complex and useful things like text, music, and more.
The two key differences between quantum bits and classical bits (from the computers we use today) are the physical form the bits take and, correspondingly, the nature of data encoded in them. The electrical bits of a classical computer can only exist in one state at a time, either 1 or 0.
Quantum bits (or qubits) are made of subatomic particles, namely individual photons or electrons. Because these subatomic particles conform more to the rules of quantum mechanics than classical mechanics, they exhibit the bizarre properties of quantum particles. The most salient of these properties for computer scientists is superposition. This is the idea that a particle can exist in multiple states simultaneously, at least until that state is measured and collapses into a single state. By harnessing this superposition property, computer scientists can make qubits encode a 1 and a 0 at the same time.
The other quantum mechanical quirk that makes quantum computers tick is entanglement, a linking of two quantum particles or, in this case, two qubits. When the two particles are entangled, the change in state of one particle will alter the state of its partner in a predictable way, which comes in handy when it comes time to get a quantum computer to calculate the answer to the problem you feed it.
A quantum computers qubits start in their 1-and-0 hybrid state as the computer initially starts crunching through a problem. When the solution is found, the qubits in superposition collapse to the correct orientation of stable 1s and 0s for returning the solution.
Aside from the fact that they are far beyond the reach of all but the most elite research teams (and will likely stay that way for a while), most of us dont have much use for quantum computers. They dont offer any real advantage over classical computers for the kinds of tasks we do most of the time.
However, even the most formidable classical supercomputers have a hard time cracking certain problems due to their inherent computational complexity. This is because some calculations can only be achieved by brute force, guessing until the answer is found. They end up with so many possible solutions that it would take thousands of years for all the worlds supercomputers combined to find the correct one.
The superposition property exhibited by qubits can allow supercomputers to cut this guessing time down precipitously. Classical computings laborious trial-and-error computations can only ever make one guess at a time, while the dual 1-and-0 state of a quantum computers qubits lets it make multiple guesses at the same time.
So, what kind of problems require all this time-consuming guesswork calculation? One example is simulating atomic structures, especially when they interact chemically with those of other atoms. With a quantum computer powering the atomic modeling, researchers in material science could create new compounds for use in engineering and manufacturing. Quantum computers are well suited to simulating similarly intricate systems like economic market forces, astrophysical dynamics, or genetic mutation patterns in organisms, to name only a few.
Amidst all these generally inoffensive applications of this emerging technology, though, there are also some uses of quantum computers that raise serious concerns. By far the most frequently cited harm is the potential for quantum computers to break some of the strongest encryption algorithms currently in use.
In the hands of an aggressive foreign government adversary, quantum computers could compromise a broad swath of otherwise secure internet traffic, leaving sensitive communications susceptible to widespread surveillance. Work is currently being undertaken to mature encryption ciphers based on calculations that are still hard for even quantum computers to do, but they are not all ready for prime-time, or widely adopted at present.
A little over a decade ago, actual fabrication of quantum computers was barely in its incipient stages. Starting in the 2010s, though, development of functioning prototype quantum computers took off. A number of companies have assembled working quantum computers as of a few years ago, with IBM going so far as to allow researchers and hobbyists to run their own programs on it via the cloud.
Despite the strides that companies like IBM have undoubtedly made to build functioning prototypes, quantum computers are still in their infancy. Currently, the quantum computers that research teams have constructed so far require a lot of overhead for executing error correction. For every qubit that actually performs a calculation, there are several dozen whose job it is to compensate for the ones mistake. The aggregate of all these qubits make what is called a logical qubit.
Long story short, industry and academic titans have gotten quantum computers to work, but they do so very inefficiently.
Fierce competition between quantum computer researchers is still raging, between big and small players alike. Among those who have working quantum computers are the traditionally dominant tech companies one would expect: IBM, Intel, Microsoft, and Google.
As exacting and costly of a venture as creating a quantum computer is, there are a surprising number of smaller companies and even startups that are rising to the challenge.
The comparatively lean D-Wave Systems has spurred many advances in the fieldand proved it was not out of contention by answering Googles momentous announcement with news of a huge deal with Los Alamos National Labs. Still, smaller competitors like Rigetti Computing are also in the running for establishing themselves as quantum computing innovators.
Depending on who you ask, youll get a different frontrunner for the most powerful quantum computer. Google certainly made its case recently with its achievement of quantum supremacy, a metric that itself Google more or less devised. Quantum supremacy is the point at which a quantum computer is first able to outperform a classical computer at some computation. Googles Sycamore prototype equipped with 54 qubits was able to break that barrier by zipping through a problem in just under three-and-a-half minutes that would take the mightiest classical supercomputer 10,000 years to churn through.
Not to be outdone, D-Wave boasts that the devices it will soon be supplying to Los Alamos weigh in at 5000 qubits apiece, although it should be noted that the quality of D-Waves qubits has been called into question before. IBM hasnt made the same kind of splash as Google and D-Wave in the last couple of years, but they shouldnt be counted out yet, either, especially considering their track record of slow and steady accomplishments.
Put simply, the race for the worlds most powerful quantum computer is as wide open as it ever was.
The short answer to this is not really, at least for the near-term future. Quantum computers require an immense volume of equipment, and finely tuned environments to operate. The leading architecture requires cooling to mere degrees above absolute zero, meaning they are nowhere near practical for ordinary consumers to ever own.
But as the explosion of cloud computing has proven, you dont need to own a specialized computer to harness its capabilities. As mentioned above, IBM is already offering daring technophiles the chance to run programs on a small subset of its Q System Ones qubits. In time, IBM and its competitors will likely sell compute time on more robust quantum computers for those interested in applying them to otherwise inscrutable problems.
But if you arent researching the kinds of exceptionally tricky problems that quantum computers aim to solve, you probably wont interact with them much. In fact, quantum computers are in some cases worse at the sort of tasks we use computers for every day, purely because quantum computers are so hyper-specialized. Unless you are an academic running the kind of modeling where quantum computing thrives, youll likely never get your hands on one, and never need to.
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Posted: at 6:21 am
This is the first in a series of explainers on quantum technology. The other two are on quantum communication and post-quantum cryptography.
A quantum computer harnesses some of the almost-mystical phenomena of quantum mechanics to deliver huge leaps forward in processing power. Quantum machines promise to outstrip even the most capable of todaysand tomorrowssupercomputers.
They wont wipe out conventional computers, though. Using a classical machine will still be the easiest and most economical solution for tackling most problems. But quantum computers promise to power exciting advances in various fields, from materials science to pharmaceuticals research. Companies are already experimenting with them to develop things like lighter and more powerful batteries for electric cars, and to help create novel drugs.
The secret to a quantum computers power lies in its ability to generate and manipulate quantum bits, or qubits.
What is a qubit?
Today's computers use bitsa stream of electrical or optical pulses representing1s or0s. Everything from your tweets and e-mails to your iTunes songs and YouTube videos are essentially long strings of these binary digits.
Quantum computers, on the other hand, usequbits, whichare typically subatomic particles such as electrons or photons. Generating and managing qubits is a scientific and engineering challenge. Some companies, such as IBM, Google, and Rigetti Computing, use superconducting circuits cooled to temperatures colder than deep space. Others, like IonQ, trap individual atoms in electromagnetic fields on a silicon chip in ultra-high-vacuum chambers. In both cases, the goal is to isolate the qubits in a controlled quantum state.
Qubits have some quirky quantum properties that mean a connected group of them can provide way more processing power than the same number of binary bits. One of those properties is known as superposition and another is called entanglement.
Qubits can represent numerous possible combinations of 1and 0 at the same time. This ability to simultaneously be in multiple states is called superposition. To put qubits into superposition, researchers manipulate them using precision lasers or microwave beams.
Thanks to this counterintuitive phenomenon, a quantum computer with several qubits in superposition can crunch through a vast number of potential outcomes simultaneously. The final result of a calculation emerges only once the qubits are measured, which immediately causes their quantum state to collapse to either 1or 0.
Researchers can generate pairs of qubits that are entangled, which means the two members of a pair exist in a single quantum state. Changing the state of one of the qubits will instantaneously change the state of the other one in a predictable way. This happens even if they are separated by very long distances.
Nobody really knows quite how or why entanglement works. It even baffled Einstein, who famously described it as spooky action at a distance. But its key to the power of quantum computers. In a conventional computer, doubling the number of bits doubles its processing power. But thanks to entanglement, adding extra qubits to a quantum machine produces an exponential increase in its number-crunching ability.
Quantum computers harness entangled qubits in a kind of quantum daisy chain to work their magic. The machines ability to speed up calculations using specially designed quantum algorithms is why theres so much buzz about their potential.
Thats the good news. The bad news is that quantum machines are way more error-prone than classical computers because of decoherence.
The interaction of qubits with their environment in ways that cause their quantum behavior to decay and ultimately disappear is called decoherence. Their quantum state is extremely fragile. The slightest vibration or change in temperaturedisturbances known as noise in quantum-speakcan cause them to tumble out of superposition before their job has been properly done. Thats why researchers do their best to protect qubits from the outside world in those supercooled fridges and vacuum chambers.
But despite their efforts, noise still causes lots of errors to creep into calculations. Smart quantum algorithmscan compensate for some of these, and adding more qubits also helps. However, it will likely take thousands of standard qubits to create a single, highly reliable one, known as a logical qubit. This will sap a lot of a quantum computers computational capacity.
And theres the rub: so far, researchers havent been able to generate more than 128 standard qubits (see our qubit counter here). So were still many years away from getting quantum computers that will be broadly useful.
That hasnt dented pioneers hopes of being the first to demonstrate quantum supremacy.
What is quantum supremacy?
Its the point at which a quantum computer can complete a mathematical calculation that is demonstrably beyond the reach of even the most powerful supercomputer.
Its still unclear exactly how many qubits will be needed to achieve this because researchers keep finding new algorithms to boost the performance of classical machines, and supercomputing hardware keeps getting better. But researchers and companies are working hard to claim the title, running testsagainst some of the worlds most powerful supercomputers.
Theres plenty of debate in the research world about just how significant achieving this milestone will be. Rather than wait for supremacy to be declared, companies are already starting to experiment with quantum computers made by companies like IBM, Rigetti, and D-Wave, a Canadian firm. Chinese firms like Alibaba are also offering access to quantum machines. Some businesses are buying quantum computers, while others are using ones made available through cloud computing services.
Where is a quantum computer likely to be most useful first?
One of the most promising applications of quantum computers is for simulating the behavior of matterdown to the molecular level. Auto manufacturers like Volkswagen and Daimler are using quantum computers to simulate the chemical composition of electrical-vehicle batteries to help find new ways to improve their performance. And pharmaceutical companies are leveraging them to analyze and compare compounds that could lead to the creation of new drugs.
The machines are also great for optimization problems because they can crunch through vast numbers of potential solutions extremely fast. Airbus, for instance, is using them to help calculate the most fuel-efficient ascent and descent paths for aircraft. And Volkswagen has unveiled a service that calculates the optimal routes for buses and taxis in cities in order to minimize congestion. Some researchers also think the machines could be used to accelerate artificial intelligence.
It could take quite a few years for quantum computers to achieve their full potential. Universities and businesses working on them are facing a shortage of skilled researchersin the fieldand a lack of suppliersof some key components. But if these exotic new computing machines live up to their promise, they could transform entire industries and turbocharge global innovation.
Posted: at 6:21 am
Its fascinating to think about the power in our pockettodays smartphones have the computing power of a military computer from 50 years ago that was the size of an entire room. However, even with the phenomenal strides we made in technology and classical computers since the onset of the computer revolution, there remain problems that classical computers just cant solve. Many believe quantum computers are the answer.
The Limits of Classical Computers
Now that we have made the switching and memory units of computers, known as transistors, almost as small as an atom, we need to find an entirely new way of thinking about and building computers. Even though a classical computer helps us do many amazing things, under the hood its really just a calculator that uses a sequence of bitsvalues of 0 and 1 to represent two states (think on and off switch) to makes sense of and decisions about the data we input following a prearranged set of instructions. Quantum computers are not intended to replace classical computers, they are expected to be a different tool we will use to solve complex problems that are beyond the capabilities of a classical computer.
Basically, as we are entering a big data world in which the information we need to store grows, there is a need for more ones and zeros and transistors to process it. For the most part classical computers are limited to doing one thing at a time, so the more complex the problem, the longer it takes. A problem that requires more power and time than todays computers can accommodate is called an intractable problem. These are the problems that quantum computers are predicted to solve.
The Power of Quantum Computers
When you enter the world of atomic and subatomic particles, things begin to behave in unexpected ways. In fact, these particles can exist in more than one state at a time. Its this ability that quantum computers take advantage of.
Instead of bits, which conventional computers use, a quantum computer uses quantum bitsknown as qubits. To illustrate the difference, imagine a sphere. A bit can be at either of the two poles of the sphere, but a qubit can exist at any point on the sphere. So, this means that a computer using qubits can store an enormous amount of information and uses less energy doing so than a classical computer. By entering into this quantum area of computing where the traditional laws of physics no longer apply, we will be able to create processors that are significantly faster (a million or more times) than the ones we use today. Sounds fantastic, but the challenge is that quantum computing is also incredibly complex.
The pressure is on the computer industry to find ways to make computing more efficient, since we reached the limits of energy efficiency using classical methods. By 2040, according to a report by the Semiconductor Industry Association, we will no longer have the capability to power all of the machines around the world. Thats precisely why the computer industry is racing to make quantum computers work on a commercial scale. No small feat, but one that will pay extraordinary dividends.
How our world will change with quantum computing
Its difficult to predict how quantum computing will change our world simply because there will be applications in all industries. Were venturing into an entirely new realm of physics and there will be solutions and uses we have never even thought of yet. But when you consider how much classical computers revolutionized our world with a relatively simple use of bits and two options of 0 or 1, you can imagine the extraordinary possibilities when you have the processing power of qubits that can perform millions of calculations at the same moment.
What we do know is that it will be game-changing for every industry and will have a huge impact in the way we do business, invent new medicine and materials, safeguard our data, explore space, and predict weather events and climate change. Its no coincidence that some of the worlds most influential companies such as IBM and Google and the worlds governments are investing in quantum computing technology. They are expecting quantum computing to change our world because it will allow us to solve problems and experience efficiencies that arent possible today. In another post, I dig deeper into how quantum computing will change our world.
Quantum Computing Market Increase In Analysis & Development Activities Is More Boosting Demands – Daily Science
Posted: at 5:41 am
Quantum Computing Market report covers the worldwide top manufacturers like (D-Wave Systems, Google, IBM, Intel, Microsoft, 1QB Information Technologies, Anyon Systems, Cambridge Quantum Computing, ID Quantique, IonQ, QbitLogic, QC Ware, Quantum Circuits, Qubitekk, QxBranch, Rigetti Computing) which including information such as: Capacity, Production, Price, Revenue, Cost, Shipment,Gross, Gross Profit, Interview Record, Business Distribution etc., these data help the consumer know about the competitors better. This Quantum Computing Marketreport includes (6 Year Forecast 2020-2026)Overview, Classification, Industry Value, Price, Cost and Gross Profit.This Quantum Computing industry report also covers all the regions and countries of the world, which shows a regional development status, including market size, volume and value, as well as price data.
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Target Audience of the Global Quantum Computing Market in Market Study: Key Consulting Companies & Advisors, Large, medium-sized, and small enterprises, Venture capitalists, Value-Added Resellers (VARs), Manufacturers, Third-party knowledge providers, Equipment Suppliers/ Buyers, Industry Investors/Investment Bankers, Research Professionals, Emerging Companies, Service Providers.
Scope of Quantum Computing Market: Quantum computing is a technology that applies the laws of quantum mechanics to computational ability. It includes three states, namely 1, 0 as well as the superposition of 1 and 0. Superposition indicates that two states exist at the same time. These bits are known as quantum bits or qubits. The global quantum computing market consists of the hardware that is required to develop quantum computers and its peripherals.
North America accounted for the largest share of the overall quantum computing market in 2017. On the other hand, Asia Pacific (APAC) would be the fastest growing region for quantum computing during the forecast period. This growth can be attributed to the increasing demand for quantum technology to solve the most tedious and complex problems in the defense and banking & finance industry.
On the basis of product type, this report displays the shipments, revenue (Million USD), price, and market share and growth rate of each type.
Hardware Software Services
On the basis on the end users/applications,this report focuses on the status and outlook for major applications/end users, shipments, revenue (Million USD), price, and market share and growth rate foreach application.
Defense Healthcare & pharmaceuticals Chemicals Banking & finance Energy & power
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Geographically, the report includes the research on production, consumption, revenue, Quantum Computing market share and growth rate, and forecast (2020-2026) of the following regions:
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Quantum computing is right around the corner, but cooling is a problem. What are the options? – Diginomica
Posted: March 22, 2020 at 1:47 am
Why would you be thinking about quantum computing? Yes, it may be two years or more before quantum computing will be widely available, but there are already quite a few organizations that are pressing ahead. I'll get into those use cases, but first - Lets start with the basics:
Classical computers require built-in fans and other ways to dissipate heat, and quantum computers are no different. Instead of working with bits of information that can be either 0 or 1, as in a classical machine, a quantum computer relies on "qubits," which can be in both states simultaneously called a superposition thanks to the quirks of quantum mechanics. Those qubits must be shielded from all external noise, since the slightest interference will destroy the superposition, resulting in calculation errors. Well-isolated qubits heat up quickly, so keeping them cool is a challenge.
The current operating temperature of quantum computers is 0.015 Kelvin or -273C or -460F. That is the only way to slow down the movement of atoms, so a "qubit" can hold a value.
There have been some creative solutions proposed for this problem, such as the nanofridge," which builds a circuit with an energy gap dividing two channels: a superconducting fast lane, where electrons can zip along with zero resistance, and a slow resistive (non-superconducting) lane. Only electrons with sufficient energy to jump across that gap can get to the superconductor highway; the rest are stuck in the slow lane. This has a cooling effect.
Just one problem though: The inventor, MikkoMttnen, is confident enough in the eventual success that he has applied for a patent for the device. However, "Maybe in 10 to 15 years, this might be commercially useful, he said. Its going to take some time, but Im pretty sure well get there."
Ten to fifteen years? It may be two years or more before quantum computing will be widely available, but there are already quite a few organizations that are pressing ahead in the following sectors:
An excellent, detailed report on the quantum computing ecosystem is: The Next Decade in Quantum Computingand How to Play.
But the cooling problem must get sorted. It may be diamonds that finally solve some of the commercial and operational/cost issues in quantum computing: synthetic, also known as lab-grown diamonds.
The first synthetic diamond was grown by GE in 1954. It was an ugly little brown thing. By the '70s, GE and others were growing up to 1-carat off-color diamonds for industrial use. By the '90s, a company called Gemesis (renamed Pure Grown Diamonds) successfully created one-carat flawless diamonds graded ILA, meaning perfect. Today designer diamonds come in all sizes and colors: adding Boron to make them pink or nitrogen to make them yellow.
Diamonds have unique properties. They have high thermal conductivity (meaning they don't melt like silicon). The thermal conductivity of a pure diamond is the highest of any known solid. They are also an excellent electrical insulator. In its center, it has an impurity called an N-V center, where a carbon atom is replaced by a nitrogen atom leaving a gap where an unpaired electron circles the nitrogen gap and can be excited or polarized by a laser. When excited, the electron gives off a single photon leaving it in a reduced energy state. Somehow, and I admit I dont completely understand this, the particle is placed into a quantum superposition. In quantum-speak, that means it can be two things, two values, two places at once, where it has both spin up and spin down. That is the essence of quantum computing, the creation of a "qubit," something that can be both 0 and 1 at the same time.
If that isnt weird enough, there is the issue of entanglement. A microwave pulse can be directed at a pair of qubits, placing them both in the same state. But you can "entangle" them so that they are always in the same state. In other words, if you change the state of one of them, the other also changes, even if great distances separate them, a phenomenon Einstein dubbed, spooky action at a distance. Entangled photons don't need bulky equipment to keep them in their quantum state, and they can transmit quantum information across long distances.
At least in the theory of the predictive nature of entanglement, adding qubits explodes a quantum computer's computing power. In telecommunications, for example, entangled photons that span the traditional telecommunications spectrum have enormous potential for multi-channel quantum communication.
News Flash: Physicists have just demonstrated a 3-particle entanglement. This increases the capacity of quantum computing geometrically.
The cooling of qubits is the stumbling block. Diamonds seem to offer a solution, one that could quantum computing into the mainstream. The impurities in synthetic diamonds can be manipulated, and the state of od qubit can held at room temperature, unlike other potential quantum computing systems, and NV-center qubits (described above) are long-lived. There are still many issues to unravel to make quantum computers feasible, but today, unless you have a refrigerator at home that can operate at near absolute-zero, hang on to that laptop.
But doesnt diamonds in computers sound expensive, flagrant, excessive? It begs the question, What is anything worth? Synthetic diamonds for jewelry are not as expensive as mined gems, but the price one pays at retail s burdened by the effect of monopoly, and so many intermediaries, distributors, jewelry companies, and retailers.
A recent book explored the value of fine things and explains the perceived value which only has a psychological basis.In the 1930s, De Beers, which had a monopoly on the world diamond market and too many for the weak demand, engaged the N. W. Ayers advertising agency realizing that diamonds were only sold to the very rich, while everyone else was buying cars and appliances. They created a market for diamond engagement rings and introduced the idea that a man should spend at least three months salary on a diamond for his betrothed.
And in classic selling of an idea, not a brand, they used their earworm taglines like diamonds are forever. These four iconic words have appeared in every single De Beers advertisement since 1948, and AdAge named it the #1 slogan of the century in 1999. Incidentally, diamonds arent forever. That diamond on your finger is slowly evaporating.
The worldwide outrage over the Blood Diamond scandal is increasing supply and demand for fine jewelry applications of synthetic diamonds. If quantum computers take off, and a diamond-based architecture becomes a standard, it will spawn a synthetic diamond production boom, increasing supply and drastically lowering the cost, making it feasible.
Many thanks to my daughter, Aja Raden, an author, jeweler, and behavioral economist for her insights about the diamond trade.
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