Category Archives: Quantum Computer
Breakthroughs in quantum computing drive higher processing power – Digital Nation
Quantum computing has seen recent breakthroughs in driving higher processing power that can lead to solving more complex problems.
A process known as quantum entanglement is a key driver of the processing power of quantum computers, and higher quantum entanglement states allow quantum computers to increase the complexity of their algorithms.
The University of Melbournes IBM Quantum Hub claims to have created the largest entanglement state of its kind in the world.
Speaking at an IBM media round table, Dr Charles Hill, senior lecturer in quantum computing, and technical lead with the IBM Quantum Hub at the University of Melbourne said that the partnership has allowed for the generation and verification of entanglement in quantum devices, driving forward research in the space.
According to Hill, entanglement is a critical difference between quantum computers and classical computers.
If a quantum computer really wasn't able to demonstrate entanglement, it really wouldn't be a quantum computer it would just be a very, very expensive and very cold, multimillion dollar calculator, says Hill.
The ability to prepare these large, highly entangled states is an important benchmark. It really demonstrates the ability of a quantum device to perform genuinely quantum mechanical computations.
The Australian governments recent development of a national quantum strategy which includes a $70 million dollar investment for a quantum commercialisation hub, as well as the US/AU Quantum cooperation statement reveals the enormous perceived impacts of quantum computing, with the sector expected to grow to at least $86 billion by 2040.
According to Melissa Price, Minister for Science and Technology, Australia now has an important mission to commercialise our research, particularly given quantum technologies are increasingly vital for industries in key areas like defence and national security, as flagged in the recent AUKUS agreement.
Dr Jay Gambetta, IBM Fellow and Vice President, Quantum Computing at IBM says that research is now at the stage where it is looking at ways to connect quantum information to applications.
We're going into this new era where we can start to look at what can we do with these machines? I think they're starting to get to the point that they're beyond what is easy to simulate on a classical computer, says Gambetta.
If I was to say one thing that I hope we achieve in the next few years is when someone from a different field that hasn't particularly been in quantum information actually uses this to answer a question. I think that will be an exciting time.
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Breakthroughs in quantum computing drive higher processing power - Digital Nation
US blocks export of quantum computing tech to Chinese organizations – CNET
An ion chamber houses the brains of a Honeywell quantum computer.
The Commerce Department on Wednesdaybarred US firms from exporting quantum computing technology to eight Chinese companies and labs to try to keep the country from decrypting sensitive US communications and developing new military technology.
"Global trade and commerce should support peace, prosperity, and good-paying jobs, not national security risks," Commerce Secretary Gina Raimondo said in a statement.
Though still technologically immature, quantum computers eventually could crack conventional encryption. The US government also is leading an active program to develop post-quantum cryptography, but communications that are intercepted today could be exposed if quantum computers become powerful enough.
Quantum computers take advantage of the physics of the ultrasmall to perform a radically different type of computation than conventional computer chips in today's phones, laptops and supercomputers. But today they work only at small scales, are prone to errors that derail calculations and are finicky enough to require ultracold conditions.
The department also pointed to quantum computing military risks involving "counter-stealth and counter-submarine applications." It detailed in theFederal Registerthe Chinese organizations added to its entities list involving export controls.
Another market where quantum computers also have potential is simulating molecular structures that could lead to new materials. Military technology has benefited immensely from materials science in the past, so quantum computing could lead to new breakthroughs.
To capitalize on these breakthroughs, many US companies are investing billions of dollars in developing quantum computers. That includes Google, IBM, Microsoft, Honeywell, IonQ, Rigetti, D-Wave and Intel. Google Chief Executive Sundar Pichai said in November thatChinese researchers are tied with Google in the race to develop quantum computing technology.
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US blocks export of quantum computing tech to Chinese organizations - CNET
Why Blockchain isnt as secure as you think – Evening Standard
B
lockchain has rapidly become one of the most disruptive technologies of the 21st century, but with the continuous improvements in quantum computing, the foundations of the technology are starting to falter.
Blockchain, cryptocurrencies, NFTs and decentralised finance have become common terms, with blockchain now hailed as an extremely secure and much faster method of recording transactions due to the computational intensity of attempting to break it. Both companies and people have poured endless amounts of capital into the technology by buying cryptocurrencies or by developing their own currency or asset chains.
But in a dynamic cyber environment, is this $2.7 trillion dollar market really future-proof and secure?
With every innovation in quantum computing, the threat to blockchain increases.
There are two main issues that face the technology, the first being its reliance on a form of encryption known as public key cryptography; and second, its reliance on a type of algorithm called a hash function.
Public key cryptography is a method of encryption that publishes a key for the world to use so that they can encrypt information that only the holder of the private key can see.
A hash is generated by running a widely known and well-established algorithm on a piece of information to create a near unique digital representation of it. It is computationally impossible to construct the original information from a hashed representation, and they are said to be resistant to finding another piece of data that has the exact same digital representation. In both proof-of-work and proof-of-stake blockchains, digitally signed hashes are used in combination with random numbers to sign off a block.
The threat from quantum computing to public key encryption is a known issue and has been discussed at length by many experienced professionals. It is an issue that both governments and commercial entities have recognised. NIST, the US National Institute of Standards and Technology, is currently in the process of defining what the next phase of encryption (also known as post-quantum encryption) will be. Many experts will highlight that the types of quantum computers that are capable of cracking this are still far away, which is true, but various competing technologies alongside quantum are bringing this to the forefront of the cybersecurity threat vector.
Therefore, one can see that the main near-term issue facing the chain comes from the threat to the hashing algorithm from quantum computing or quantum accelerated hardware. There are a few issues with the hash-method, however, the main issue facing these chains is that a quantum computer will be able to solve for these hashes at a much faster rate than any computational-based approach, thereby taking ownership of a network. Significant progress has been made in the past two years on a type of quantum algorithm called Grovers algorithm, which poses the greatest risk to the network as a fully well error-corrected quantum computer is not needed.
Evaluating and understanding the risk only gets us part way, says David Worrall, co-founder of Secqai. It is now time to implement the solutions available to prepare us for the future.
This risk is further accentuated due to the decentralised nature of blockchain, where the latest cyber technology hasnt been built to integrate easily with, for example, new hardware based cryptography such as secure entropy sources or quantum random number generators.
Indeed, research has shown that the deployment of post quantum safe algorithms in todays blockchain architectures is not possible without a huge increase in transaction costs sometimes outweighing the value of the transaction.
Conversely, traditional banking infrastructure is relatively easy to update as the back-end software and hardware is managed centrally by each bank and each integrated party, i.e. the list of parties that need to be secure is well known.
Blockchain developers understand the challenge today, and as has been shown need to start the work of preparing their systems by integrating post-quantum methods into their infrastructure and adopt best practice techniques to ensure that they are prepared for a quantum world.
Rahul Tyagi is an ex-management consultant, inventor and co-founder of cyber security start-up Secqai
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Why Blockchain isnt as secure as you think - Evening Standard
Tech pioneers to headline Princeton conference on innovation and entrepreneurship – Princeton University
Engage 2021, Princetons second annual innovation and entrepreneurship conference, will be held online Dec. 1 and 2, offering opportunities to learn about the transformation of discoveries into innovations that benefit society from biomedicine and clean energy to wireless, cryptocurrency and quantum computing.
The two-day virtual gathering, hosted by Princeton Innovation, will include tips and case studies on successful new technologies and academic-industry partnerships, as well as guidance on funding opportunities for research and entrepreneurship, with a special focus on the growing innovation ecosystem in New Jersey and the tri-state area.
Faculty, researchers, students and alumni from Princeton and other institutions, entrepreneurs and those entrepreneurially-minded, industry representatives and government policymakers, are invited to register for the conference, which which is free and open to everyone,
By bringing people together from across the regional and global innovation ecosystems, Princeton is helping to grow a robust and inclusive environment that brings positive impacts to the broader community, the economy, and to daily life, said Vice Dean for Innovation Rodney Priestley, the Pomeroy and Betty Perry Smith Professor of Chemical and Biological Engineering.
Priestley leads Princeton Innovation, a University initiative that supports faculty, students and researchers as they transform discoveries emerging from science, engineering, social sciences and humanities into ventures and activities that can create a positive impact on society. Priestley will kick off Engage 2021 with updates on the initiative, which is part of Princetons Office of the Dean for Research.
Marian Croak, Class of 1977 and vice president of engineering at Google
Headlining the conference will be Marian Croak, Class of 1977 and vice president of engineering at Google, in a conversation with chair of computer science Jennifer Rexford about the contributions of women in STEM fields, the importance of mentorship, and being an intrapreneur andinnovator at a large company. This year, Croak became one of the first two Black women inducted into the National Inventors Hall of Fame, in recognition of her work on advancing Voice over Internet Protocol (VoIP) technologies, a key development in audio and video conferencing.
Another keynote session will feature a conversation between Andrea Goldsmith, dean of Princetons School of Engineering and Applied Science, and Naveen Verma, director of the Keller Center for Innovation in Engineering Education. They will discuss developments and opportunities for innovation in the New Jersey region, and connections between entrepreneurship, research and teaching at Princeton.
This conference will help enable all of us seeking to make a positive difference engineers, scientists, humanists, social scientists, business leaders and startup enablers to engage with each other in fostering innovation that strengthens society, said Goldsmith, the Arthur LeGrand Doty Professor of Electrical and Computer Engineering, who has founded two companies around her expertise in wireless technology.
As part of the conference, the 13th annual Celebrate Princeton Innovation showcase will honor Princeton faculty-led discoveries in life sciences and technology that have the potential to become everyday innovations.
The showcase features 10 Princeton faculty experts discussing their discoveries on topics including a new technology to prevent smartphone theft, new anticancer therapeutic strategies, early detection of autism and other neurobehavioral conditions, clean and inexpensive lithium-ion battery recycling, electric bandages, and more. The keynote address will feature blockchain-technology startup Offchain Labs cofounder Edward Felten, the Robert E. Kahn Professor of Computer Science and Public Affairs, Emeritus.
Mohammad Seyedsayamdost, professor of chemistry, has been selected to receive Princetons second annual prize for innovative faculty, the Dean for Research Award for Distinguished Innovation, for the creation of a method for discovering new anti-infective agents, including drugs that treat bacterial, viral and fungal infections. Seyedsayamdost, who has cofounded the startup Cryptyx Bioscience, will receive the award and give a talk about his technology.
Engage 2021 will also feature a New Jersey startup showcase of academic scientists and engineers raising venture funds for companies based on their research, including Marcus Hultmark, an associate professor of mechanical and aerospace engineering at Princeton. Hultmark and his team recently received an Edison Patent Award from the Research and Development Council of New Jersey for their low-cost, nanotechnology-based industrial velocity sensors.
Hultmarks company, Tendo Technologies, was launched in 2018 with support from the National Science Foundation Innovation Corps (I-Corps) program and the eLab Summer Accelerator at Princetons Keller Center. Princeton is now the leading institution of the I-Corps Northeast Hub, which was announced earlier this year with a $15 million grant to accelerate the impact of federally funded research and advance diversity in entrepreneurship. I-Corps Northeast Hub leaders from Rutgers, Rowan and Drexel Universities will discuss the hubs activities and opportunities in a panel discussion.
Another panel discussion will cover the benefits of joining a startup accelerator, and how to choose the right accelerator and create a strong application. Representatives from the accelerators QED, VentureWell and FedTech will join the conversation, as will Garrett Winther of the HAX accelerator. HAX recently announced it would establish its U.S. headquarters in Newark, New Jersey, after a persuasive State of New Jersey pitch supported by Princeton Engineering dean Goldsmith on behalf of Princeton. HAX aims to invest $25 million in 100 new technology companies over the next five years with a focus on re-industrialization and decarbonization of the U.S.
Engage 2021 sessions will feature many Princeton science and engineering faculty members, along with panelists from industry and other universities, discussing emerging technologies in decarbonized transportation, cancer research, quantum computing, wireless communications, and artificial intelligence in bioengineering.
Our vision is for Princeton to be a catalyst for a diverse, inclusive and human-centered high-tech hub for the entire tri-state region, said Goldsmith. We have much exciting progress, but we need to keep building partnerships. I encourage anyone with a passion for building new ventures and harnessing technology for the good of humanity to join us.
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Tech pioneers to headline Princeton conference on innovation and entrepreneurship - Princeton University
Quantum Turing machine – Wikipedia
Model of quantum computation
A quantum Turing machine (QTM) or universal quantum computer is an abstract machine used to model the effects of a quantum computer. It provides a simple model that captures all of the power of quantum computationthat is, any quantum algorithm can be expressed formally as a particular quantum Turing machine. However, the computationally equivalent quantum circuit is a more common model.[1][2]:2
Quantum Turing machines can be related to classical and probabilistic Turing machines in a framework based on transition matrices. That is, a matrix can be specified whose product with the matrix representing a classical or probabilistic machine provides the quantum probability matrix representing the quantum machine. This was shown by Lance Fortnow.[3]
A way of understanding the quantum Turing machine (QTM) is that it generalizes the classical Turing machine (TM) in the same way that the quantum finite automaton (QFA) generalizes the deterministic finite automaton (DFA). In essence, the internal states of a classical TM are replaced by pure or mixed states in a Hilbert space; the transition function is replaced by a collection of unitary matrices that map the Hilbert space to itself.[4]
That is, a classical Turing machine is described by a 7-tuple M = Q , , b , , , q 0 , F {displaystyle M=langle Q,Gamma ,b,Sigma ,delta ,q_{0},Frangle } .
For a three-tape quantum Turing machine (one tape holding the input, a second tape holding intermediate calculation results, and a third tape holding output):
The above is merely a sketch of a quantum Turing machine, rather than its formal definition, as it leaves vague several important details: for example, how often a measurement is performed; see for example, the difference between a measure-once and a measure-many QFA. This question of measurement affects the way in which writes to the output tape are defined.
In 1980 and 1982, physicist Paul Benioff published papers[5][6] that first described a quantum mechanical model of Turing machines. A 1985 article written by Oxford University physicist David Deutsch further developed the idea of quantum computers by suggesting quantum gates could function in a similar fashion to traditional digital computing binary logic gates.[4]
Iriyama, Ohya, and Volovich have developed a model of a linear quantum Turing machine (LQTM). This is a generalization of a classical QTM that has mixed states and that allows irreversible transition functions. These allow the representation of quantum measurements without classical outcomes.[7]
A quantum Turing machine with postselection was defined by Scott Aaronson, who showed that the class of polynomial time on such a machine (PostBQP) is equal to the classical complexity class PP.[8]
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Quantum Turing machine - Wikipedia
Multiverse Computing Partners with IonQ to Bring Quantum Computing to Global Finance – HPCwire
SAN SEBASTIN, Spain, Nov. 11, 2021 Multiverse Computing today announced a partnership with IonQ, the leader in trapped-ion quantum computing, which will enable financial services organizations to model risk more accurately and quickly than ever before using the IonQ Quantum Cloud platform within Singularity, Multiverses financial solution.
The partnership combines IonQ, offering the worlds most advanced quantum hardware architecture, with the simplicity and ease-of-use that Multiverse Computing customers have come to rely upon for complex financial modeling. Using this integrated system, financial institutions can model real-life financial problems such as Fair Price calculations, portfolio creation and optimization, ETF replication, risk valuation, and many other simulations with unprecedented speed and accuracy.
Singularity already allows analysts and other users to model problems directly within spreadsheets and other familiar tools. With the new integration, financial institutions can now take advantage of IonQs industry-leading hardware without ever writing a line of code allowing them to leverage the power of quantum computing in everyday financial simulations.
The integration will dramatically increase the accessibility of quantum computing for financial professionals, including those without technical backgrounds or understanding of how quantum computers operate.
We are excited to announce IonQ as a preferred quantum compute partner for our Singularity platform, said Enrique Lizaso, CEO of Multiverse Computing. Together, our two platforms will allow us to develop joint solutions to interesting, real-life problems in finance. Singularity will put the power of cutting-edge quantum computing in the hands of financial professionals quickly and easily, without the need for them to learn quantum mechanics. Contrary to conventional wisdom that beneficial applications are years away, quantum computing in finance is here, and it means business.
Financial simulations are central to the global economy, and spreadsheets are the de facto tool for these analyses, said Peter Chapman, CEO of IonQ. This integration with Multiverse brings the worlds most powerful quantum hardware to the native application for finance professionals so that they dont need to be technical to leverage our computers. It is an important early step towards bringing quantum computing into everyday workflows.
The application of quantum computing in the financial industry is accelerating rapidly, driven by the potential for quantum to deliver competitive advantages and significant value. Together, IonQ and Multiverse Computing will help their clients to use quantum solutions specifically designed to address critical problems whose solutions were previously out of reach.
About Multiverse Computing
Multiverse Computingis a leading quantum software company that applies quantum and quantum-inspired solutions to tackle complex problems in finance to deliver value today and enable a more resilient and prosperous economy. The companys expertise in quantum control and computational methods as well as finance means it can secure maximum results from current quantum devices. Its flagship product, Singularity, allows financial professionals to leverage quantum computing with common software tools. The company is headquartered in San Sebastian, Spain with offices in Toronto, Canada and Paris.
About IonQ
IonQ, Inc. is a leader in quantum computing, with a proven track record of innovation and deployment. IonQs next-generation quantum computer is the worlds most powerful trapped-ion quantum computer, and IonQ has defined what it believes is the best path forward to scale. IonQ is the only company with its quantum systems available through the cloud on Amazon Braket, Microsoft Azure, and Google Cloud, as well as through direct API access. IonQ was founded in 2015 byChristopher MonroeandJungsang Kimbased on 25 years of pioneering research. To learn more, visitwww.ionq.com.
Source: Multiverse Computing
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Multiverse Computing Partners with IonQ to Bring Quantum Computing to Global Finance - HPCwire
Is Quantum Computing the Future of AI? – Datanami
(metamorworks/Shutterstock)
Quantum computing has grabbed the imagination of computer scientists as one possible future of the discipline after weve reached the limits of digital binary computers. Thanks to its capability to hold many different possible outcomes in the quantum state, quantum computing could potentially deliver a big computational upgrade for machine learning and AI problems. However, there are still a lot of unanswered questions around quantum computing, and its unclear if the devices will help with the building wave of investment in enterprise AI.
Weve done quite well with the line of binary computers that first appeared in the 1950s and have evolved into the basis of todays multi-trillion-dollar IT sector. With just two bits and three Boolean algebraic operators, we created tremendous data-crunching machines that have automated many manual tasks and had a large impact on the world around us. From basic accounting and supply chain routing to flight control computers and understanding the genome, its tough to overstate the impact that computers have had on our modern lives.
But as we approach the limits of what classical binary computers can do, quantum computers have emerged with the (as yet unfulfilled) promise of a tremendous upgrade in computational power. Instead of being restricted to Boolean linear algebraic functions on 1s and 0s, quantum computing allows us to use linear algebra upon quantum bits, or qubits, that are composed of numbers, vectors, and matrices interacting in quantum states, including superposition, entanglement, and interference.
Quantum computing opens the door potentially solving very large and complex computational problems that are basically impossible to solve on traditional computers. This includes things like using brute-force methods to guess the passcode used to encrypt a piece of data using a 256-bit algorithm. Data encrypted with AES-256 is considered secure precisely because it cant be cracked with a brute-force attack (its possible, but it would take many thousands of years with current technology, which makes it practically impossible). But with quantum computers ability to compute with multiple possible states, solving such problems will now be within practical reach.
The Google Sycamore quantum processor (Image source: Google)
Another example is the traveling salesman problem. Given a number of geographic locations, figuring out the most efficient path among them is actually an extremely compute-intensive problem. UPS, which spends billions on fuel for its delivery trucks, has gone so far as to limit the number of left turns its drivers make in an attempt to maximize delivery time and minimize fuel use, making it an interesting twist on the old traveling salesman problem.
Which brings us to machine learning and AI. The latest incarnation of machine learning, deep learning, is pushing the limits of what traditional computers can handle. Large transformer models, such as OpenAIs GPT-3, which has 175 billion parameters, take months to train on classical computers. As future models grow into the trillions of parameters, they will take even longer to train. That is one reason why users are adopting novel microprocessor architectures that deliver better performance than what traditional CPUs and even GPUs can deliver.
But at the end of the day, CPUs and GPUs are tied to classical binary computers, and the limitations they entail. Quantum computers offer the possibility of a quantum leap in performance and capability for a range of use cases, and AI is definitely one of them.
Cem Dilmegani, who is an industry analyst at AIMultiple, defines quantum AI as the use of quantum computing for running machine learning algorithms. Thanks to computational advantages of quantum computing, quantum AI can help achieve results that are not possible to achieve with classical computers, Dilmegani writes.
A quantum computer from Oxford-Quantum-Circuits (Image courtesy of the company)
One of the early quantum computer manufacturers thats making moves in this area is Google. In March 2020, Google launched TensorFlow Quantum, a which brings the TensorFlow machine learning development library to the world of quantum computers. With TensorFlow Quantum, developers will be able to develop quantum neural network models that run on quantum computers.
While running AI applications on quantum computers is still in its very earliest stages, there are many organizations working to develop it. NASA has been working with Google for some time, and there is also work going on in the national labs.
For instance, last month, researchers at Los Alamos National Laboratory published a paper called Absence of Barren Plateaus in Quantum Convolutional Neural Networks, which essentially shows that convolutional neural networks (the type commonly used for computer vision problems) can run on quantum computers.
We proved the absence of barren plateaus for a special type of quantum neural network, Marco Cerezo, a LANL researcher who co-authored the paper, said in a LANL press release. Our work provides trainability guarantees for this architecture, meaning that one can generically train its parameters.
LANL researchers are bullish on the potential for quantum AI algorithms to provide the next breakthrough in computational capability. Patrick Coles, a quantum physicist at LANL and a co-author of the paper, said this approach will yield new approaches for crunching large amounts of data.
The field of quantum machine learning is still young, Coles said in the LANL press release. Theres a famous quote about lasers, when they were first discovered, that said they were a solution in search of a problem. Now lasers are used everywhere. Similarly, a number of us suspect that quantum data will become highly available, and then quantum machine learning will take off.
Earlier this year, IBM Research announced that it found mathematical proof of a quantum advantage for quantum machine learning. The proof came in the form of a classification algorithm that, provided access to classical data, provided a provable exponential speedup over classic ML methods. While there are plenty of caveats to go along with that statement, it provides a glimpse into one potential future where quantum AI is feasible.
IBM quantum computer (Source: IBM)
To be sure, there is plenty of doubt whenever two highly hyped technologiesAI and quantum computingcome together. In its July 2021 blog, IBM stated: Few concepts in computer science cause as much excitementand perhaps as much potential for hype and misinformationas quantum machine learning.
While there appears to be potential with quantum AI, that potential is, as yet, unrealized. On the bright side, there appears to be at least cause for some optimism that a real breakthrough could be in our future.
Sceptics are correct in that quantum computing is still a field of research and it is a long way from being applied to neural networks, Dilmegani writes. However, in a decade, AI could run into another plateau due to insufficient computing power and quantum computing could rise to help the advance of AI.
Its still too soon to tell whether the field of quantum computing will have a major impact on the development of AI. Were still in the midst of what those in the quantum computing field call Noisy Intermediate-Stage Quantum, or NISQ. There definitely are many promising developments, but there are too many unanswered questions still.
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Leading Technology Executive Max Schireson Joins Quantum Machines’ Board of Directors – HPCwire
TEL AVIV, Israel,Nov. 11, 2021 Quantum Machines, creator of the Quantum Orchestration Platform, announced today thatMax Schiresonhas joined the companys Board of Directors.
Max is most well known as the former CEO of open-source database company MongoDB, where grew the companys sales from$1Mto$50Mand positioned it as the most popular NoSQL database in terms of users. Moreover, Max served on the board of supercomputer manufacturer Cray until it was acquired by Hewlett Packard in 2019. Today Max serves as Executive in Residence at Battery Ventures where he advises Battery and its cloud and big-data portfolio companies, and will be joining Quantum Machines board on the companys behalf.
We are very fortunate to add Max to our Board of Directors, said Dr.Itamar Sivan, CEO of Quantum Machines. With the rapid advances being made in the quantum computing industry, Max experience as both a business leader, building MongoDB into an industry leader in databases, coupled with his deep knowledge and experience in the high-performance computing industry will be an invaluable resource to Quantum Machines as we build towards the future of quantum computers.
As the quantum computing industry emerges, one of its most pressing challenges is to develop a viable and sustainable value-chain and technology stack. With different companies focused on different layers of the computer, from the qubits to the applications, there is a lot of strategizing for the leading companies to be made, beyond the deep and complex technology to be developed. Max is joining Quantum Machines to help craft the companys strategy and offerings for it to continue leading the quantum race.
Quantum computing has the potential to fundamentally change all aspects of our technology, saidMax Schireson, Executive in Residence at Battery Ventures. Im excited to work with Quantum Machines to continue to advance its business and its products and help realize the potential of quantum computers.
Quantum Machines Quantum Orchestration Platform (QOP) is the leading scalable cloud-ready solution for the control and operation of quantum computers. The combined software and hardware solution enables R&D teams to execute the highly complex algorithms necessary for tackling the most advanced challenges facing quantum computing.
About Quantum Machines
QMs full-stack Quantum Orchestration Platform enables an entirely new approach to controlling and operating quantum processors. Capable of running even the most complex algorithms from near-term applications of quantum computers to challenges of quantum-error-correction the Quantum Orchestration Platform allows users to realize the potential of all quantum processors right out of the box via its powerful, yet intuitive, programming language QUA.
Source: Quantum Machines
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Leading Technology Executive Max Schireson Joins Quantum Machines' Board of Directors - HPCwire
Andrew Chi-Chih Yao receives the 2021 Kyoto Prize in Advanced Technology: Commemorative Lecture on his wonderful journey in computer science to be…
video:Andrew Chi-Chih Yao (The 2021 Kyoto Prize laureate in Advanced Technology): One-minute digest introduction view more
Credit: Courtesy of Inamori Foundation
Andrew Chi-Chih Yao, Dean of Institute for Interdisciplinary Information Sciences at Tsinghua University, received the 2021 Kyoto Prize in Advanced Technology for his pioneering contributions to a new theory of computation and communication and a fundamental theory for its security. Yaos Commemorative Lecture A Journey Through Computer Science will be published on November 10, 2021, 10:00 AM JST at the 2021 Kyoto Prize Special Website. In his lecture, Yao shares episodes from his youth and research career as well as insights he gained from his achievements in physics and computer science. In science, the paradigm is the search for truth. In this process, we sometimes discover patterns and beauty which can lift the human spirit. It also leads to innovations that can improve human conditions and prepare us for future human challenges, says Yao, looking back at the journey of his research life.
In his lecture, Yao shares episodes from his youth and research career as well as insights he gained from his achievements in physics and computer science. In science, the paradigm is the search for truth. In this process, we sometimes discover patterns and beauty which can lift the human spirit. It also leads to innovations that can improve human conditions and prepare us for future human challenges, says Yao, looking back at the journey of his research life.
Andrew Chi-Chih Yao created new trends in computer science and made a great contribution to cutting-edge research in various areas, especially in security, secure computing, and quantum computation through establishing innovative fundamental theories for computation and communication. His achievements are continuing to influence current real-world problems such as security, secure computing, and big data processing.
Yao and the other two 2021 Kyoto Prize laureates are introduced on the 2021 Kyoto Prize Special Website with information about their work, profiles, and three-minute introduction videos. The Kyoto Prize in Basic Sciences for this year went to Robert G. Roeder, Arnold and Mabel Beckman Professor of Biochemistry and Molecular Biology at The Rockefeller University; Arts and Philosophy to Bruno Latour, Professor Emeritus of the Paris Institute of Political Studies (Sciences Po).
About Kyoto Prize
The Kyoto Prize is an international award of Japanese origin, presented to individuals who have made significant contributions to the progress of science, the advancement of civilization, and the enrichment and elevation of the human spirit. The Prize is granted in the three categories of Advanced Technology, Basic Sciences, and Arts and Philosophy, each of which comprises four fields, making a total of 12 fields. Every year, one Prize for each of the three categories is awarded with prize money of 100 million yen per category.
One of the distinctive features of the Kyoto Prize is that it recognizes both science and arts and philosophy fields. This is because of its founder Kazuo Inamoris conviction that the future of humanity can be assured only when there is a balance between scientific development and the enrichment of the human spirit.
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.
Clever Combination of Quantum Physics and Molecular Biology – SciTechDaily
Illustration of a quantum wave packet in close vicinity of a conical intersection between two potential energy surfaces. The wave packet represents the collective motion of multiple atoms in the photoactive yellow protein. A part of the wave packet moves through the intersection from one potential energy surface to the other, while another part remains on the top surface, leading to a superposition of quantum states. Credit: DESY, Niels Breckwoldt
A new analytical technique is able to provide hitherto unattainable insights into the extremely rapid dynamics of biomolecules. The team of developers, led by Abbas Ourmazd from the University of WisconsinMilwaukee and Robin Santra from DESY, is presenting its clever combination of quantum physics and molecular biology in the scientific journal Nature. The scientists used the technique to track the way in which the photoactive yellow protein (PYP) undergoes changes in its structure in less than a trillionth of a second after being excited by light.
In order to precisely understand biochemical processes in nature, such as photosynthesis in certain bacteria, it is important to know the detailed sequence of events, Santra explains their underlying motivation. When light strikes photoactive proteins, their spatial structure is altered, and this structural change determines what role a protein takes on in nature. Until now, however, it has been almost impossible to track the exact sequence in which structural changes occur. Only the initial and final states of a molecule before and after a reaction can be determined and interpreted in theoretical terms. But we dont know exactly how the energy and shape changes in between the two, says Santra. Its like seeing that someone has folded their hands, but you cant see them interlacing their fingers to do so.
Whereas a hand is large enough and the movement is slow enough for us to follow it with our eyes, things are not that easy when looking at molecules. The energy state of a molecule can be determined with great precision using spectroscopy; and bright X-rays for example from an X-ray laser can be used to analyze the shape of a molecule. The extremely short wavelength of X-rays means that they can resolve very small spatial structures, such as the positions of the atoms within a molecule. However, the result is not an image like a photograph, but instead a characteristic interference pattern, which can be used to deduce the spatial structure that created it.
Since the movements are extremely rapid at the molecular level, the scientists have to use extremely short X-ray pulses to prevent the image from being blurred. It was only with the advent of X-ray lasers that it became possible to produce sufficiently bright and short X-ray pulses to capture these dynamics. However, since molecular dynamics takes place in the realm of quantum physics where the laws of physics deviate from our everyday experience, the measurements can only be interpreted with the help of a quantum-physical analysis.
A peculiar feature of photoactive proteins needs to be taken into consideration: the incident light excites their electron shell to enter a higher quantum state, and this causes an initial change in the shape of the molecule. This change in shape can in turn result in the excited and ground quantum states overlapping each other. In the resulting quantum jump, the excited state reverts to the ground state, whereby the shape of the molecule initially remains unchanged. The conical intersection between the quantum states therefore opens a pathway to a new spatial structure of the protein in the quantum mechanical ground state.
The team led by Santra and Ourmazd has now succeeded for the first time in unraveling the structural dynamics of a photoactive protein at such a conical intersection. They did so by drawing on machine learning because a full description of the dynamics would in fact require every possible movement of all the particles involved to be considered. This quickly leads to unmanageable equations that cannot be solved.
The photoactive yellow protein we studied consists of some 2000 atoms, explains Santra, who is a Lead Scientist at DESY and a professor of physics at Universitt Hamburg. Since every atom is basically free to move in all three spatial dimensions, there are a total of 6000 options for movement. That leads to a quantum mechanical equation with 6000 dimensions which even the most powerful computers today are unable to solve.
However, computer analyses based on machine learning were able to identify patterns in the collective movement of the atoms in the complex molecule. Its like when a hand moves: there, too, we dont look at each atom individually, but at their collective movement, explains Santra. Unlike a hand, where the possibilities for collective movement are obvious, these options are not as easy to identify in the atoms of a molecule. However, using this technique, the computer was able to reduce the approximately 6000 dimensions to four. By demonstrating this new method, Santras team was also able to characterize a conical intersection of quantum states in a complex molecule made up of thousands of atoms for the first time.
The detailed calculation shows how this conical intersection forms in four-dimensional space and how the photoactive yellow protein drops through it back to its initial state after being excited by light. The scientists can now describe this process in steps of a few dozen femtoseconds (quadrillionths of a second) and thus advance the understanding of photoactive processes. As a result, quantum physics is providing new insights into a biological system, and biology is providing new ideas for quantum mechanical methodology, says Santra, who is also a member of the Hamburg Cluster of Excellence CUI: Advanced Imaging of Matter. The two fields are cross-fertilizing each other in the process.
Reference: Few-fs resolution of a photoactive protein traversing a conical intersection by A. Hosseinizadeh, N. Breckwoldt, R. Fung, R. Sepehr, M. Schmidt, P. Schwander, R. Santra and A. Ourmazd, 3 November 2021, Nature.DOI: 10.1038/s41586-021-04050-9
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Clever Combination of Quantum Physics and Molecular Biology - SciTechDaily