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Category Archives: Quantum Computing
Posted: May 11, 2020 at 11:27 am
Tribune News Service
Chandigarh, May 10
There has been a massive spike in production of personal protection equipment (PPE) kits in the country following outbreak of the Covid-19 pandemic. From just 47,000 kits being produced annually, the output has gone up to about two lakh per day.
Stating this here today, Dr G Satheesh Reddy, Chairman, Defence Research and Development Organisation (DRDO), said Covid-19 has provided a lot of opportunity for research and development and industrial production, but cautioned that delays in development is of no use.
He was addressing scientists and staff at the Centre for Development of Advanced Computing (C-DAC), Mohali, via video-conferencing on the occasion of the centers 32nd foundation day. Directors and scientists from various laboratories of the DRDO, Council for Scientific and Industrial Research and other institutions also participated in the conference.
He also spoke about medical ventilators produced by the industry with assistance from the DRDO, which costs from Rs 1.5 to 4 lakh and have export potential.
Dr Reddy said the C-DAC, an autonomous body under the Ministry of Electronics and Information Technology, will be considered as an extended arm of the DRDO for undertaking applied research.
Lauding the role of the Mohali center in research and development in electronics and information technology, Dr Reddy said artificial intelligence tools developed by it would be required in all most every field.
Dr PK Khosla, Director, C-DAC, Mohali, gave an overview of the work done in the organisations four verticals healthcare technology, cyber security, e-governance and education and training. He also spoke about four new areas under focus, including artificial intelligence, augmented and virtual reality, robotics and quantum computing.
Dr Hemant Darbari, Director General, C-DAC, spoke on e-Sanjeevni OPD, a recently launched national level telemedicine project rolled out by the C-DAC, Mohali. It has been extended to 15 states within three weeks and provides access to over a thousand doctors.
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RAND report finds that, like fusion power and Half Life 3, quantum computing is still 15 years away – The Register
Posted: April 11, 2020 at 7:41 pm
Quantum computers pose an "urgent but manageable" threat to the security of modern communications systems, according to a report published Thursday by influential US RAND Corporation.
The non-profit think tank's report, "Securing Communications in the Quantum Computing Age: Managing the Risks to Encryption," urges the US government to act quickly because quantum code-breaking could be a thing in, say, 12-15 years.
If adequate implementation of new security measures has not taken place by the time capable quantum computers are developed, it may become impossible to ensure secure authentication and communication privacy without major, disruptive changes, said Michael Vermeer, a RAND scientist and lead author of the report in a statement.
Experts in the field of quantum computing like University of Texas at Austin computer scientist Scott Aaronson have proposed an even hazier timeline.
Noting that the quantum computers built by Google and IBM have been in the neighborhood of 50 to 100 quantum bits (qubits) and that running Shor's algorithm to break public key RSA cryptosystems would probably take several thousand logical qubits meaning millions of physical qubits due to error correction Aaronson recently opined, "I dont think anyone is close to that, and we have no idea how long it will take."
But other boffins, like University of Chicago computer science professor Diana Franklin, have suggested Shor's algorithm might be a possibility in a decade and a half.
So even though quantum computing poses a theoretical threat to most current public-key cryptography and less risk for lattice-based, symmetric, privacy key, post-quantum, and quantum cryptography there's not much consensus about how and when this threat might manifest itself.
Nonetheless, the National Institute of Standards and Technology, the US government agency overseeing tech standards, has been pushing the development of quantum-resistant cryptography since at least 2016. Last year it winnowed a list of proposed post-quantum crypto (PQC) algorithms down to a field of 26 contenders.
The RAND report anticipates quantum computers capable of crypto-cracking will be functional by 2033, with the caveat that experts propose dates both before and after that. PQC algorithm standards should gel within the next five years, with adoption not expected until the mid-to-late 2030s, or later.
But the amount of time required for the US and the rest of the world to fully implement those protocols to mitigate the risk of quantum crypto cracking may take longer still. Note that the US government is still running COBOL applications on ancient mainframes.
"If adequate implementation of PQC has not taken place by the time capable quantum computers are developed, it may become impossible to ensure secure authentication and communication privacy without major, disruptive changes to our infrastructure," the report says.
RAND's report further notes that consumer lack of awareness and indifference to the issue means there will be no civic demand for change.
Hence, the report urges federal leadership to protect consumers, perhaps unaware that Congress is considering the EARN-IT Act, which critics characterize as an "all-out assault on encryption."
"If we act in time with appropriate policies, risk reduction measures, and a collective urgency to prepare for the threat, then we have an opportunity for a future communications infrastructure that is as safe as or more safe than the current status quo, despite overlapping cyber threats from conventional and quantum computers," the report concludes.
It's worth recalling that a 2017 National Academy of Sciences, Engineering, and Medicine report, "Global Health and the Future Role of the United States," urged the US to maintain its focus on global health security and to prepare for infection disease threats.
That was the same year nonprofit PATH issued a pandemic prevention report urging the US government to "maintain its leadership position backed up by the necessary resources to ensure continued vigilance against emerging pandemic threats, both at home and abroad."
The federal government's reaction to COVID-19 is a testament to the impact of reports from external organizations. We can only hope that the threat of crypto-cracking quantum computers elicits a response that's at least as vigorous.
Sponsored: Practical tips for Office 365 tenant-to-tenant migration
Posted: at 7:41 pm
ELMSFORD, N.Y., April 10, 2020 Seeqcannounced funding of $5 Million from M Ventures, the strategic corporate venture capital arm of Merck KGaA, Darmstadt, Germany to develop commercially viable quantum computing systems for problem-specific applications.
The M Ventures funding follows a $6.8 million seed round from investors including BlueYard Capital, Cambium, NewLab and the Partnership Fund for New York City.
Seeqc is developing a new approach to making quantum computing useful, via fully Digital Quantum Computing. The solution combines classical and quantum computing to form an all-digital architecture through a system-on-a-chip design that utilizes 10-40 GHz superconductive classical co-processing to address the efficiency, stability and cost issues endemic to quantum computing systems. Seeqc recently spun out of HYPRES, Inc., the worlds leading developer of superconductor electronics, to pursue a vision of making quantum computing useful, commercially and at scale.
Through the spin-out, Seeqc acquired significant infrastructure and intellectual property from HYPRES. HYPRES had garnered over $100 million from public and private investments to develop a multi-layer commercial superconductor chip foundry and intellectual property. This investment was in support of creating commercial superconductive computing solutions, much of which is now part of Seeqc.
These assets give Seeqc the advantage of having sophisticated tools, facilities and IP for the design, testing and manufacturing of quantum-ready superconductor chips and wafers.
Merck KGaA, Darmstadt, Germany, will be a strategic partner for Seeqc supporting its research and development towards useful, application-specific quantum computers both as semiconductor materials solutions provider as well as an end user for high performance quantum computing.
The team of executives and scientists at Seeqc has deep expertise and experience in commercial superconductive computing solutions and quantum computing. The companys executive leadership team consists of John Levy, co-CEO, chair, and co-founder; Oleg Mukhanov, PhD, co-CEO, CTO, and co-founder; and Matthew Hutchings, PhD, chief product officer, co-founder.
Seeqc enters the quantum computing market as the world leader in superconductive electronics and is one of the only companies to ever design, manufacture and deliver multi-layer superconductive digital chips operating at tens of GHz into complex cryogenic systems.
Quantum Computing is Approaching Its Next Phase
While major advancements have been made recently with early generation quantum computing systems, such systems and architectures are inherently unstable and unscalable. The industry continues to struggle with cost, readout and control challenges, excessive input/output connection count as well as the complexities of managing microwave pulses used to control and readout qubits.
Leading state-of-the-art qubits need to be kept at near absolute zero temperatures to function, so as solutions require hundreds, even thousands of qubits and maybe even more cost, control/readout, complexity and heat management greatly impact scale.
Seeqcs digital classical-quantum hybrid approach mitigates many of these challenges:
The brute force or labware approach to quantum computing contemplates building machines with thousands or even millions of qubits requiring multiple analog cables and, in some cases, complex CMOS readout/control for each qubit, but that doesnt scale effectively as the industry strives to deliver business-applicable solutions, said John Levy, co-chief executive officer at Seeqc. With Seeqcs hybrid approach, we utilize the power of quantum computers in a digital system-on-a-chip environment, offering greater control, cost reduction and with a massive reduction in energy, introducing a more viable path to commercial scalability.
We believe that the best way to make quantum computing commercially viable is to ensure that early engagement with customers is ultra-focused and problem-specific, with the goal to solve previously insurmountable challenges with a targeted application specific hardware and software solution, continued Levy. A close partnership with customers, academic experts and application developers to work through the early use cases of quantum computing is critical to extracting its novel and potentially world-changing value.
Were excited to be working with a world leading team and fab on one of the most pressing issues in modern quantum computing, says Owen Lozman, Vice President at M Ventures. We recognize that scaling the current generations of superconducting quantum computers beyond the noisy intermediate scale quantum era will require fundamental changes in qubit control and wiring. Building on deep expertise in single flux quantum technologies, Seeqc has a clear, and importantly cost-efficient, pathway towards addressing existing challenges and disrupting analog, microwave-controlled architectures.
As a leading science and technology company, it is one of our key missions to stay on top of emerging trends. In quantum computing, we see a huge potential to advance major parts of our existing business, says John Langan, Chief Technology Officer, Performance Materials at Merck, KGaA, Darmstadt Germany. Were therefore excited to be embarking on a close partnership with Seeqc to develop the next generation of quantum machines. For one, our Semiconductor Solutions business unit will be working with Seeqc to develop and optimize semiconductor materials and processes utilized in the manufacturing of quantum technologies. In parallel, our Quantum Computing Task Force will support Seeqc in developing application-specific quantum co-processors to expedite the advent of industrially viable quantum computers that can be used by our Digital Organization and by our computational researcher across our three main business units.
The company holds 36 patents and is comprised of 16 PhDs with senior leadership experience from HYPRES.
Seeqc is developing the first fully digital quantum computing platform for global businesses. Seeqc combines classical and quantum technologies to address the efficiency, stability and cost issues endemic to quantum computing systems. The company applies classical and quantum technology through digital readout and control technology and a unique chip-scale architecture. Seeqcs quantum system provides the energy- and cost-efficiency, speed and digital control required to make quantum computing useful and bring the first commercially-scalable, problem-specific quantum computing applications to market.
About M Ventures
M Ventures is the strategic, corporate venture capital arm of Merck KGaA, Darmstadt,Germany. Its mandate is to invest in innovative technologies and products with the potential to significantly impact the companys core business areas. From its headquarters in Amsterdam and offices in the US and Israel, M Ventures invests globally in transformational ideas driven by great entrepreneurs. M Ventures takes an active role in its portfolio companies and teams up with entrepreneurs and coinvestors to translate innovation towards commercial success. For more information, visitwww.m-ventures.com
About Merck KGaA, Darmstadt, Germany
Merck KGaA, Darmstadt, Germany, a leading science and technology company, operates across healthcare, life science and performance materials. Around 52,000 employees work to make a positive difference to millions of peoples lives every day by creating more joyful and sustainable ways to live. From advancing gene editing technologies and discovering unique ways to treat the most challenging diseases to enabling the intelligence of devices the company is everywhere. In 2019, Merck KGaA, Darmstadt, Germany, generated sales of 16.2 billion in 66 countries. The company holds the global rights to the name and trademark Merck internationally. The only exceptions are the United States and Canada, where the business sectors of Merck KGaA, Darmstadt, Germany operate as EMD Serono in healthcare, MilliporeSigma in life science, and EMD Performance Materials. Since its founding 1668, scientific exploration and responsible entrepreneurship have been key to the companys technological and scientific advances. To this day, the founding family remains the majority owner of the publicly listed company.
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Posted: at 7:41 pm
Astronomers believe that many planets including our own solar system emerged from giant disks of gas and dust spinning around stars. To understand these cosmic mechanisms, researchers have typically used simulations to separately examine planetary development and magnetic field formation. Now, new work by researchers from the University of Zurich and the University of Cambridge has unified these fields of study in a single simulation for the first time ever.
Researchers knew that planets likely formed as a result of gravitational instabilities in the disks that allowed particles to congeal together, slowly forming planets over hundreds of thousands of years. With the new study, the research team aimed to examine the effects that magnetic fields have on planet formation in the context of those gravitational instabilities.
To do that, they modified a hybrid mesh-particle method that calculated the mass and gravity using particles, creating a virtual adaptive mesh that allowed the researchers to simultaneously incorporate magnetic fields, fluid dynamics and gravity.
Applying that method required supercomputing power. The researchers turned to Piz Daint, the in-house Cray supercomputer of the Swiss National Supercomputing Centre (CSCS). Piz Daints 5,704 XC50 nodes each pack an Intel Xeon E5-2690 v3 CPU and an Nvidia Tesla P100 GPU, and its 1,813 XC40 nodes each carry two Intel Xeon E5-2695 v4 CPUs. The two sections stack up at 21.2 Linpack petaflops and 1.9 Linpack petaflops respectively, placing 6th and 185th on the most recent Top500 list of the worlds most powerful supercomputers.
After running the simulations on Piz Daint, the researchers got some very interesting results. For some time, the astronomy community has puzzled over why planets spin slower than the disks from which they were born. But now, it seems, they might have their answer.
Our new mechanism seems to be able to solve and explain this very general problem, said Lucio Mayer, professor of computational astrophysics at the University of Zurich and project manager at the National Centre of Competence in Research PlanetS.
The simulation shows that the energy generated by the interaction of the forming magnetic field with gravity acts outwards and drives a wind that throws matter out of the disk, Mayer said. If this is true, this would be a desirable prediction, because many of the protoplanetary disks studied with telescopes that are a million years old have about 90 percent less mass than predicted by the simulations of disks formation so far.
The researchers believe that that matter-ejecting mechanism is the culprit behind the loss of angular momentum in the disks and, ultimately, the planets they birth. The discovery of this mechanism, of course, was only made possible by conducting their unified simulation on Piz Daint.
To read CSCS Simone Ulmers article discussing this research, click here.
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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
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.
Go here to read the rest:
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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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
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6.5.2 Middle East
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7.2 Company Market Ranking
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8.1.2 Financial Performance
8.1.3 Product Outlook
8.1.4 Key Developments
9.1 Related Research
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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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