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Cornell researchers discovered a quantum spin-glass state in quantum computing, offering insights into error correction and revealing hidden orders in quantum algorithms, potentially leading to new quantum state classifications and advances in quantum computing.

At the microscopic level, window glass exhibits a curious blend of properties. Its atoms are disordered like a liquid, yet they possess the rigidity of a solid; when a force is applied to one atom, it affects all others.

Its an analogy physicists use to describe a quantum state called a quantum spin-glass, in which quantum mechanical bits (qubits) in a quantum computer demonstrate both disorder (taking on seemingly random values) and rigidity (when one qubit flips, so do all the others). A team of Cornell researchers unexpectedly discovered the presence of this quantum state while conducting a research project designed to learn more about quantum algorithms and, relatedly, new strategies for error correction in quantum computing.

Measuring the position of a quantum particle changes its momentum and vice versa. Similarly, for qubits, there are quantities that change one another when they are measured. We find that certain random sequences of these incompatible measurements lead to the formation of a quantum spin-glass, said Erich Mueller, professor of physics in the College of Arts and Sciences (A&S). One implication of our work is that some types of information are automatically protected in quantum algorithms whichshare the features of our model.

The study was recently published in Physical Review B. The lead author is Vaibhav Sharma, a doctoral student in physics.

Assistant professor of physicsChao-Ming Jian(A&S) is a co-author along with Mueller. All three conduct their research at CornellsLaboratory of Atomic and Solid State Physics(LASSP). The research received funding from a College of Arts and SciencesNew Frontier Grant.

We are trying to understand generic features of quantum algorithms features which transcend any particular algorithm, Sharma said. Our strategy for revealing these universal features was to study random algorithms.We discovered that certain classes of algorithms lead to hidden spin-glass order. We are now searching for other forms of hidden order and think that this will lead us to a new taxonomy of quantum states.

Random algorithms are those that incorporate a degree of randomness as part of the algorithm e.g., random numbers to decide what to do next.

Muellers proposal for the2021 New Frontier GrantAutonomous Quantum Subsystem Error Correction aimed to simplify quantum computer architectures by developing a new strategy to correct for quantum processor errors caused by environmental noise that is, any factor, such as cosmic rays or magnetic fields, that would interfere with a quantum computers qubits, corrupting information.

The bits of classical computer systems are protected by error-correcting codes, Mueller said; information is replicated so that if one bit flips, you can detect it and fix the error. For quantum computing to be workable now and in the future, we need to come up with ways to protect qubits in the same way.

The key to error correction is redundancy, Mueller said. If I send three copies of a bit, you can tell if there is an error by comparing the bits with one another. We borrow language from cryptography for talking about such strategies and refer to the repeated set of bits as a codeword.

When they made their discovery about spin-glass order, Mueller and his team were looking into a generalization, where multiple codewords are used to represent the same information. For example, in a subsystem code, the bit 1 might be stored in 4 different ways: 111; 100; 101; and 001.

The extra freedom that one has in quantum subsystem codes simplifies the process of detecting and correcting errors, Mueller said.

The researchers emphasized that they werent simply trying to generate a better error protection scheme when they began this research. Rather, they were studying random algorithms to learn general properties of all such algorithms.

Interestingly, we found nontrivial structure, Mueller said. The most dramatic was the existence of this spin-glass order, which points toward there being some extra hidden information floating around, which should be useable in some way for computing, though we dont know how yet.

Reference: Subsystem symmetry, spin-glass order, and criticality from random measurements in a two-dimensional Bacon-Shor circuit by Vaibhav Sharma, Chao-Ming Jian and Erich J. Mueller, 31 July 2023,Physical Review B. DOI: 10.1103/PhysRevB.108.024205

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Cornell Scientists Have Discovered a Hidden Quantum State - SciTechDaily

Santa Clara (CA), 6 December 2023 - Airbus and BMW Group launch a global Quantum Computing Challenge entitled The Quantum Mobility Quest to tackle the most pressing challenges in aviation and automotive that have remained insurmountable for classical computers.

This challenge is the first-of-its-kind, bringing together two global industry leaders to harness quantum technologies for real-world industrial applications, unlocking the potential to forge more efficient, sustainable and safer solutions for the future of transportation.

"This is the perfect time to shine a spotlight on quantum technology and its potential impact on our society. Partnering with an industry leader like BMW Group enables us to mature the technology as we need to bridge the gap between scientific exploration and its potential applications. Were seeking the best-in-class students, PhDs, academics, researchers, start-ups, companies, or professionals in the field, worldwide to join our challenge to create a massive paradigm shift in the way aircraft are built and flown." says Isabell Gradert, Vice President Central Research and Technology at Airbus.

Following the success of previous editions of Quantum Computing Challenges by BMW Group and Airbus, we are gearing up for a new wave of innovation, exploring the technology capabilities for sustainability and operational excellence. said Dr. Peter Lehnert, Vice-President, Research Technologies at BMW Group. The BMW Group is clearly aiming at positioning itself at the crossroads of quantum technology, the global ecosystem, and cutting-edge solutions. By doing so, we strongly believe in major advances when it comes to sustainable materials for batteries and fuel cells, to generate unique and efficient designs, or to enhance the overall user experience in the BMW Group Products.

Quantum computing has the potential to significantly enhance computational power and to enable the most complex operations that challenge even todays best computers. In particular, for data-driven industries like the transportation sector, this emerging technology could play a crucial role in simulating various industrial and operational processes, opening up opportunities to shape future mobility products and services.

Challenge candidates are invited to select one or more problem statements: improved aerodynamics design with quantum solvers, future automated mobility with quantum machine learning, more sustainable supply chain with quantum optimisation, and enhanced corrosion inhibition with quantum simulation. Additionally, candidates can put forward their own quantum technologies with the potential to develop native apps yet to be explored in the transportation sector.

The challenge is hosted by The Quantum Insider (TQI) and divided into two parts, a four-month phase where participants will develop a theoretical framework for one of the given statements, and a second phase during which selected finalists will implement and benchmark their solutions. Amazon Web Services (AWS) provides candidates with an opportunity to run their algorithms on their Amazon Braket quantum computing service.

A jury composed of world-leading quantum experts will team up with experts from Airbus, BMW Group, and AWS to evaluate submitted proposals and award one winning-team with a 30,000 prize in each of the five challenges, by the end of 2024.

Registration opens today, and submissions will be accepted from mid-January through April 30, 2024 here: http://www.thequantuminsider.com/quantum-challenge.

If you have any questions, please contact:

Press and Public Relations Janina LatzaSpokesperson BMW Group IT Tel.: +49 (0)151 601 12650 E-Mail: Janina.Latza@bmw.de

Christophe Koenig Leiter BMW Group IT, Digital and Driving Experience Communications, BMW Group Design, Innovations and Digital Car Communications Telefon: +49-89-382-56097 E-Mail: Christophe.Koenig@bmwgroup.com

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Airbus and BMW Group launch Quantum Computing Competition to tackle their most pressing mobility challenges. - BMW Press

In classical control theory, both open-loop and closed-loop control systems are commonly used. These systems are well understood and rather straightforward, controlling everything from washing machines to industrial equipment to the classical computing devices that make todays society work. When trying to transfer this knowledge to the world of quantum control theory, however, many issues arise. The most pertinent ones involve closed-loop quantum control and the clocking of quantum computations. With physical limitations on the accuracy and resolution of clocks, this would set hard limits on the accuracy and speed of quantum computing.

The entire argument is covered in two letters to Physical Review Letters, by Florian Meier et al. titled Fundamental Accuracy-Resolution Trade-Off for Timekeeping Devices (Arxiv preprint), and by Jake Xuereb et al. titled Impact of Imperfect Timekeeping on Quantum Control(Arxiv preprint). The simple version is that by simply increasing the clock rate, accuracy suffers, with dephasing and other issues becoming more frequent.

Solving the riddle of closed-loop quantum control theory is a hard one, as noted by Daoyi Dong and Ian R Peterson in 2011. In their paper titled Quantum control theory and applications: A survey, the most fundamental problem with such a closed-loop quantum control system lies with aspects such as the uncertainty principle, which limits the accuracy with which properties of the system can be known.

In this regard, an accurately clocked open-loop system could work better, except that here we run into other fundamental issues. Even though this shouldnt phase us, as with time solutions may be found to the timekeeping and other issues, its nonetheless part of the uncertainties that keep causing waves in quantum physics.

Top image: Impact of timekeeping error on quantum gate fidelity & independent clock dephasing (Xuereb et al., 2023)

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Impact Of Imperfect Timekeeping On Quantum Control And Computing - Hackaday

Using a classical cryptographic algorithm alongside its quantum safe equivalent.

Once quantum computers, more specifically Cryptographically Relevant Quantum Computers (CRQCs), have become powerful and reliable enough, they will enable adversaries to break current asymmetric encryption, placing important data and assets at risk. New digital signatures and key encapsulation mechanisms (KEMs) are needed, and while considerable progress has been made in recent years to develop new quantum-resistant algorithms, there is still ongoing discussions in the industry about the best way to implement them in the various security protocols that the industry requires.

The concept of hybrid cryptography is to use two or more fundamentally different algorithms that offer similar cryptographic functionality. In the context of Quantum Safe Cryptography more specifically, it refers to using a combination of classical cryptographic algorithms, for example, X25519 elliptic curve key exchange or ECDSA, in combination with Quantum Safe equivalents such as ML-KEM / FIPS 203 and ML-DSA / FIPS 204.

Hybrid cryptography comes in two flavors, which are sometimes referred to as AND hybrid and OR hybrid. The latter, as the name suggests, means that both algorithms are supported, and protocols can choose which of the two algorithms they prefer. This minimizes performance impact and is important to ensure mission continuity during the transition to Quantum Safe algorithms in heterogenous systems where not all components can transition at the same time.

On the other hand, it also means that communications protected only by classical ECC / RSA cryptography are vulnerable to CRQCs, and communications protected by Quantum Safe algorithms suffer from the much newer, less tested code base for these algorithms. On top of that, OR hybrid applications need to be designed specifically to prevent downgrade attacks. OR hybrid is more often simply subsumed within crypto agility discussions.

More often, when people talk about hybrid cryptography in the context of Quantum Safe algorithms, they refer to the AND hybrid model where both a classical and a Quantum Safe algorithm are combined to ensure security even if one of the algorithms or its implementation are broken. In the case of a key exchange, for example, this means that the session key will be derived in equal parts from a classical method such as X25119 and a Quantum Safe algorithm such as ML-KEM / FIPS 203. One example of this can be found in the provision of NIST SP800-56C Rev 2 that allows concatenation of two session secrets into a combined session secret from which the session key is derived. Also, there are various RFC proposals such as, for example, draft-tls-westerbaan-xyber768d00-0314 that are actively being worked on to support AND hybrid key exchanges for use in TLS. In terms of signatures, an AND hybrid scheme would only return valid if both classical and Quantum Safe signatures are successfully verified.

The Rambus Quantum Safe IP Portfolio allows for the implementation of hybrid cryptography. The Rambus QSE-IP-86 Quantum Safe Engine is a standalone cryptographic core that supports the NIST draft standards FIPS 203 ML-KEM and FIPS 204 ML-DSA and provides SHAKE-128 and SHAKE-256 acceleration. It can be combined with an accelerator for traditional asymmetric cryptography such as the Rambus PKE-IP-85 core that accelerates classic public key cryptography and a TRNG-IP-76 core that generates true random numbers. The Rambus RT-600 family of Root of Trust cores provides a robust integrated solution embedding engines and firmware that support both the full suite of CNSA 1.0 classic and CNSA 2.0 Quantum Safe algorithms (including NIST SP 800-208 XMSS/LMS hash-based verification) that can be used to implement AND hybrid solutions, offering system security management for use cases like secure boot, secure debug, secure firmware upgrade, lifecycle and SKU management, platform attestation and authentication.

Join me for my webinar Protecting Devices and Data in the Quantum Era on January 10, 2024 to learn about all the latest developments in Quantum Safe Cryptography and how you can protect your past, current, and future data in the quantum computing era.

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Getting Ready For The Quantum Computing Era: Thoughts On Hybrid Cryptography - SemiEngineering

The primary challenge for practical quantum computing is error suppression, necessitating quantum error correction for extensive processing. However, implementing error-corrected logical qubits, where information is redundantly encoded across multiple physical qubits, presents significant challenges for achieving large-scale logical quantum computing.

A new study by Harvard scientists reports realizing a programmable quantum processor based on encoded logical qubits operating with up to 280 physical qubits. This is a critical milestone in the quest for stable, scalable quantum computing.

This new quantum processor can encode up to 48 logical qubits and execute hundreds of logical gate operations, a vast improvement over prior efforts. This system marks the initial showcase of running large-scale algorithms on an error-corrected quantum computer, signaling the arrival of early fault-tolerant quantum computation that operates reliably without interruption.

Denise Caldwell of the National Science Foundation said,This breakthrough is a tour de force of quantum engineering and design. The team has not only accelerated the development of quantum information processing by using neutral atoms but opened a new door to explorations of large-scale logical qubit devices, which could enable transformative benefits for science and society as a whole.

A quantum bit or qubit is one unit of information in quantum computing. In the world of quantum computing, in principle, it is possible to create physical qubits by manipulating quantum particles be they atoms, ions, or photons.

Harnessing the peculiarities of quantum mechanics for computation is more intricate than merely accumulating a sufficient number of qubits. Qubits are inherently unstable and susceptible to collapsing out of their quantum states.

The accurate measure of success lies in logical qubits, known as the coins of the realm. These are bundles of redundant, error-corrected physical qubits capable of storing information for quantum algorithms. Creating controllable logical qubits, akin to classical bits poses a significant challenge for the field. It is widely acknowledged that until quantum computers can operate reliably on logical qubits, the technology cannot truly advance.

Current computing systems have demonstrated only one or two logical qubits and a single quantum gate operationa unit of codebetween them.

The breakthrough by the Harvard team is built upon years of research on a quantum computing architecture called a neutral atom array, pioneered in Lukins lab. QuEra, a company commercializing this technology, recently entered into a licensing agreement with Harvards Office of Technology Development for a patent portfolio based on Lukins groups innovations.

A block of ultra-cold, suspended rubidium atoms is at the heart of the system. These atoms, serving as the systems physical qubits, can move around and form pairs or become entangled during computations.

Entangled pairs of atoms come together to form gates, representing units of computing power. The team had previously showcased low error rates in their entangling operations, establishing the reliability of their neutral atom array system.

In their logical quantum processor, the scientists have now demonstrated parallel, multiplexed control over an entire section of logical qubits using lasers. This approach is more efficient and scalable compared to individually controlling physical qubits.

Paper first author Dolev Bluvstein, a Griffin School of Arts and Sciences Ph.D. student in Lukins lab, said,We are trying to mark a transition in the field, toward starting to test algorithms with error-corrected qubits instead of physical ones, and enabling a path toward larger devices.

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Scientists created the first programmable, logical quantum processor - Tech Explorist