Category Archives: Quantum Computer

How a quantum computer could break 2048-bit RSA encryption …

But quantum computers change this thinking. These machines are far more powerful than classical computers and should be able to break these codes with ease.

That raises an important questionwhen will quantum computers be powerful enough to do this? After that date, any information protected by this form of encryption becomes insecure.

So computer scientists have attempted to calculate the resources such a quantum computer might need and then work out how long it will be until such a machine can be built. And the answer has always been decades.

Today, that thinking needs to be revised thanks to the work of Craig Gidney at Google in Santa Barbara and Martin Eker at the KTH Royal Institute of Technology in Stockholm, Sweden. These guys have found a more efficient way for quantum computers to perform the code-breaking calculations, reducing the resources they require by orders of magnitude.

Consequently, these machines are significantly closer to reality than anyone suspected. The result will make uncomfortable reading for governments, military and security organizations, banks, and anyone else who needs to secure data for 25 years or longer.

First some background. Back in 1994, the American mathematician Peter Shor discovered a quantum algorithm that outperformed its classical equivalent. Shors algorithm factors large numbers and is the crucial element in the process for cracking trapdoor-based codes.

Trapdoor functions are based on the process of multiplication, which is easy to perform in one direction but much harder to do in reverse. For example, it is trivial to multiply two numbers together: 593 times 829 is 491,597. But it is hard to start with the number 491,597 and work out which two prime numbers must be multiplied to produce it.

And it becomes increasingly difficult as the numbers get larger. Indeed, computer scientists consider it practically impossible for a classical computer to factor numbers that are longer than 2048 bits, which is the basis of the most commonly used form of RSA encryption.

Shor showed that a sufficiently powerful quantum computer could do this with ease, a result that sent shock waves through the security industry.

And since then, quantum computers have been increasing in power. In 2012, physicists used a four-qubit quantum computer to factor 143. Then in 2014 they used a similar device to factor 56,153.

Its easy to imagine that at this rate of progress, quantum computers should soon be able to outperform the best classical ones.

Not so. It turns out that quantum factoring is much harder in practice than might otherwise be expected. The reason is that noise becomes a significant problem for large quantum computers. And the best way currently to tackle noise is to use error-correcting codes that require significant extra qubits themselves.

Taking this into account dramatically increases the resources required to factor 2048-bit numbers. In 2015, researchers estimated that a quantum computer would need a billion qubits to do the job reliably. Thats significantly more than the 70 qubits in todays state-of-the-art quantum computers.

On that basis, security experts might well have been able to justify the idea that it would be decades before messages with 2048-bit RSA encryption could be broken by a quantum computer.

Now Gidney and Eker have shown how a quantum computer could do the calculation with just 20 million qubits. Indeed, they show that such a device would take just eight hours to complete the calculation. [As a result], the worst case estimate of how many qubits will be needed to factor 2048 bit RSA integers has dropped nearly two orders of magnitude, they say.

Their method focuses on a more efficient way to perform a mathematical process called modular exponentiation. This is the process of finding the remainder when a number is raised to a certain power and then divided by another number.

This process is the most computationally expensive operation in Shors algorithm. But Gidney and Eker have found various ways to optimize it, significantly reducing the resources needed to run the algorithm.

Thats interesting work that should have important implications for anyone storing information for the future. A 20-million-qubit quantum computer certainly seems a distant dream today. But the question these experts should be asking themselves is whether such a device could be possible within the 25 years they want to secure the information. If they think it is, then they need a new form of encryption.

Indeed, security experts have developed post-quantum codes that even a quantum computer will not be able to crack. So it is already possible to safeguard data today against future attack by quantum computers. But these codes are not yet used as standard.

For ordinary people, there is little risk. Most people use 2048-bit encryption, or something similar, for tasks like sending credit card details over the internet. If these transactions are recorded today and broken in 25 years, little will be lost.

But for governments, there is more at stake. The messages they send todaybetween embassies or the military, for examplemay well be significant in 20 years and so worth keeping secret. If such messages are still being sent via 2048-bit RSA encryption, or something similar, then these organizations should start worryingquickly.

Ref: : How To Factor 2048 Bit RSA Integers In 8 Hours Using 20 Million Noisy Qubits

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Atos confirms role as global leader in quantum hybridization technologies at its 8th Quantum Advisory Board – Yahoo Finance

Paris, France - December 3, 2021 - At the meeting of the 8th Atos Quantum Advisory Board, a group of international experts, mathematicians and physicists, authorities in their fields, Atos reaffirms its position as a global leader in quantum computing technologies. The quantum hybridization axis (convergence of high-performance computing (HPC) and quantum computing) in particular positions the company at the forefront of quantum research, converging its expertise. Atos has invested, along with partner start-ups Pasqal and IQM, in two major quantum hybridization projects in France and Germany.

Held at Atos' R&D centre, dedicated to research in quantum computing and high-performance computing, in Clayes-sous-Bois, in the presence of Atos next CEO, Rodolphe Belmer, and under the chairmanship of Pierre Barnab, Chair of the Quantum Advisory Board, Interim co-CEO and Head of Big Data and Cybersecurity, this meeting of the Quantum Advisory Board was an opportunity to review Atos recent work and to take stock of future prospects.

Artur Ekert, Professor of Quantum Physics at the Mathematical Institute, University of Oxford, Founding Director of the Centre for Quantum Technologies in Singapore and member of the Quantum Advisory Board said We are truly impressed by the work and the progress that Atos has made over the past year. The company takes quantum computing seriously and it gives us great pleasure to see it becoming one of the key players in the field. It is a natural progression for Atos. As a world leader in High Performance Computing (HPC), Atos is in a unique position to combine its existing, extensive, expertise in HPC with quantum technology and take both fields to new heights. We are confident that Atos will shape the quantum landscape in years to come, both with research and applications that have long-lasting impact.

In the field of quantum hybridization Atos is the only player and the company is already enabling several applications - in the areas of chemistry, such as catalysis design for nitrogen fixation, and for the optimization of smart grids. Atos is also involved in two additional quantum hybridization projects, which are currently being launched:

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The European HPC-QS (Quantum Simulation) project, which starts this December 2021, aims to build the first European hybrid supercomputer with an integrated quantum accelerator by the end of 2023. It is intended to be a first major brick of the French quantum plan. Atos is involved in this project alongside national partners including the CEA, GENCI, Pasqal and the Julich Supercomputing Centre. Pasqal will provide its analog quantum accelerator and Atos, with its quantum simulator, the Quantum Learning Machine (QLM), will ensure the hybridization with the HPCs at the two datacenters at GENCI and Julich.

The Q-EXA project, part of the German Government quantum plan, will see a consortium of partners, including Atos, work together to integrate a German quantum computer into an HPC supercomputer for the first time. Atos QLM will be instrumental in connecting the quantum computer, from start-up IQM (also part of the Atos Scaler program) to the Leibniz Supercomputing-LRZ centre.

The European Organization for Nuclear Research (CERN), one of the worlds largest and most respected research centres, based in Geneva, has recently acquired an Atos Quantum Learning Machine (QLM) appliance and joined the Atos User Club. The Atos QLM, delivered to CERN in October, will be made available to the CERN scientific community to support research activities in the framework of the CERN Quantum Technology Initiative (CERN QTI), thus accelerating the investigation of quantum advantage for high-energy physics (HEP) and beyond.

Building on CERNs unique expertise and strong collaborative culture, co-development efforts are at the core of CERN QTI. As we explore the fast-evolving field of quantum technologies, access to the Atos Quantum Learning Machine and Atos expertise can play an important role in our quantum developments roadmap in support of the high-energy physics community and beyond, says Alberto Di Meglio, Coordinator of the CERN Quantum Technology Initiative. A dedicated training workshop is being organized with Atos to investigate the full functionality and potential of the quantum appliance, as well as its future application for some of the CERN QTI activities.

"Atos is the world leader in the convergence of supercomputing and quantum computing, as shown by these two major and strategic projects we are involved in in France and Germany. At a time when the French government is expected to announce its plan for quantum computing, the durability of our Quantum Board, the quality of the work carried out and the concrete applications of this research in major projects reinforce this position," comments Pierre Barnab, interim co-CEO and head of Big Data and Cybersecurity at Atos.

The Quantum Advisory Board is made up of universally recognized quantum physicists and includes:

Alain Aspect, Professor at the Institut dOptique Graduate School, Universit Paris-Saclay and at Ecole Polytechnique, Institut Polytechnique de Paris

David DiVincenzo, Alexander von Humboldt Professor, Director of the Institute for Quantum Information at RWTH Aachen University, Director of the Institute for Theoretical Nanoelectronics at the Juelich Research Center;

Artur Ekert, Professor of Quantum Physics at the Mathematical Institute, University of Oxford and Founding Director of the Centre for Quantum Technologies in Singapore;

Daniel Esteve, Research Director, CEA Saclay, Head of Quantronics;

Serge Haroche, Professor emeritus at the Collge de France, Nobel laureate in Physics.

As a result of Atos ambitious program to anticipate the future of quantum computing and to be prepared for the opportunities and challenges that come with it - Atos Quantum - Atos was the first organization to offer a quantum noisy simulation module which can simulate real Qubits, the Atos QLM and to propose Q-score, the only universal metrics to assess quantum performance and superiority. Atos is also the first European patent holder in quantum computing.


About Atos

Atos is a global leader in digital transformation with 107,000 employees and annual revenue of over 11 billion. European number one in cybersecurity, cloud and high performance computing, the Group provides tailored end-to-end solutions for all industries in 71 countries. A pioneer in decarbonization services and products, Atos is committed to a secure and decarbonized digital for its clients. Atos is a SE (Societas Europaea), listed on Euronext Paris and included in the CAC 40 ESG and Next 20 Paris Stock indexes.

The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.

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Laura Fau | | +33 6 73 64 04 18 |



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Atos confirms role as global leader in quantum hybridization technologies at its 8th Quantum Advisory Board - Yahoo Finance

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


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,

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


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