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July 29, 2021 Researchers at the University of Sydney and quantum control startup Q-CTRL today announced a way to identify sources of error in quantum computers through machine learning, providing hardware developers the ability to pinpoint performance degradation with unprecedented accuracy and accelerate paths to useful quantum computers.

A joint scientific paper detailing the research, titled Quantum Oscillator Noise Spectroscopy via Displaced Cat States, has been published in the Physical Review Letters, the worlds premier physical science research journal and flagship publication of the American Physical Society (APS Physics).

Focused on reducing errors caused by environmental noisethe Achilles heel of quantum computingthe University of Sydney team developed a technique to detect the tiniest deviations from the precise conditions needed to execute quantum algorithms using trapped ion and superconducting quantum computing hardware. These are the core technologies used by world-leading industrial quantum computing efforts at IBM, Google, Honeywell, IonQ, and others.

To pinpoint the source of the measured deviations, Q-CTRL scientists developed a new way to process the measurement results using custom machine-learning algorithms. In combination with Q-CTRLs existing quantum control techniques, the researchers were also able to minimize the impact of background interference in the process. This allowed easy discrimination between real noise sources that could be fixed and phantom artifacts of the measurements themselves.

Combining cutting-edge experimental techniques with machine learning has demonstrated huge advantages in the development of quantum computers, said Dr. Cornelius Hempel of ETH Zurich who conducted the research while at the University of Sydney. The Q-CTRL team was able to rapidly develop a professionally engineered machine learning solution that allowed us to make sense of our data and provide a new way to see the problems in the hardware and address them.

Q-CTRL CEO and University of Sydney professor Michael J. Biercuk said, The ability to identify and suppress sources of performance degradation in quantum hardware is critical to both basic research and industrial efforts building quantum sensors and quantum computers.

Quantum control, augmented by machine learning, has shown a pathway to make these systems practically useful and dramatically accelerate R&D timelines, he said.

The published results in a prestigious, peer-reviewed journal validate the benefit of ongoing cooperation between foundational scientific research in a university laboratory and deep-tech startups. Were thrilled to be pushing the field forward through our collaboration.

More information:

Alistair R. Milne et al, Quantum Oscillator Noise Spectroscopy via Displaced Cat States,Physical Review Letters(2021).DOI: 10.1103/PhysRevLett.126.250506

Journal information:

Source: University of Sydney

See original here:
Q-CTRL, University of Sydney Devise Machine Learning Technique Used to Pinpoint Quantum Errors - HPCwire

The US Department of Energy (DoE), the most influential body in the way the largest supercomputers are designed and built, has been looking beyond CMOS long before the introduction of exascale systems.

Agencies have made multiple bets that quantum computing will play an important role in the future of large-scale scientific computing, whether as an accelerator of some sort or as a more general-purpose system of the future. There is. With so many projects scattered around, its difficult to maintain current totals, but at current rates, DoE will invest well over $ 1 billion in future quantum technology by the end of 2022. Its possible, and its not unreasonable to think that this doesnt include millions of dollars. Reserved to build the quantum internet.

That gambling dollar figure continues to grow with an additional $ 73 million added today.

DoE has been strong in funding quantum computing for the past few years. Over the course of five years, it has pushed $ 115 million into this area from comprehensive programs like Q-Next, splitting its funding into the quantum application and domain areas (widely referred to by DoE as Quantum Information Science or QIS). increase). The system, even if the realization of that funding could be 10 years (or more) ahead and still might not replace traditional supercomputers.

In 2019, DoE awarded more than $ 60 million for quantum computing in communications, and in January 2020 announced $ 625 million for the new quantum computing center. $ 30 million for QIS in key application areas in March of this year. It will be added to the $ 115 million Q-Next program at Argonne National Laboratory. All of this does not include DoE funding that works with NSF and other institutions and programs, in addition to the $ 73 million announced today. So perhaps its already over a billion.

This week, DoE funds new thinking and experimental and theoretical efforts to promote understanding of the quantum phenomena of systems that can be used in Quantum Information Science (QIS) and the use of quantum computing in chemistry and materials science research. Announced $ 73 million to offer .. This influx of investment 29 projects Above all, more than 3 years to new materials, cryogenic systems and algorithms.

Very few winners have focused on the application, and the majority of the funding seems to support the quantum hardware effort. This includes projects focused on creating qubits (materials, enhanced stability, all-new qubit types), fault tolerance, and error correction. Some efforts focus on quantum simulation in traditional systems.

The award spans various universities and national laboratories. The Berkeley National Lab has two awards, one group focusing on the superconducting structure of scalable quantum systems, and the other team developing f-element qubits with controllable coherence and entanglement. I am. Argonne National Laboratory also has two groups, one focusing on entanglement issues and the other focusing on quantum spin coherence of photosynthetic proteins.

Other notable programs funded include work on applications such as quantum chemistry (Emory University) and molecular dynamics / materials science (University of Southern California). There are also some award-winning teams that focus on specific programming-related challenges.

The project was selected based on a peer review under the DOE Funding Opportunity Announcement Materials and Chemical Science Research for Quantum Information Science by the Department of Basic Energy Sciences (BES) of DOE. NS DOE Science Bureaus efforts in QIS It is notified by community input and applications focused on target missions such as quantum computing, quantum simulation, quantum communication, and quantum sensing. DOEs Science Department supports 5 National QIS Research Center A diverse portfolio of research projects, including recent awards for promoting QIS in areas related to nuclear physics and fusion energy science.

Quantum science represents the next technological revolution and frontier in the information age, and the United States is at the forefront, said Energy Secretary Jennifer M. Granholm. National Labs will strengthen resilience in the face of increasing cyber threats and climate disasters, paving the way for a cleaner and safer future.

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U.S. DoE sends another $ 73 million into the future of Quantum

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U.S. DoE sends another $ 73 million into the future of Quantum - Illinoisnewstoday.com