
Photo shows Dr. Alexeev with a model of an IBM Q quantum computer. (Image by Argonne National Laboratory.)
Argonne combines quantum and classical approaches to overcome limitations in current quantum computing hardware
In recent years, quantum devices have become available that enable researchers — for the first time — to use real quantum hardware to begin to solve scientific problems. However, in the near term, the number and quality of qubits (the basic unit of quantum information) for quantum computers are expected to remain limited, making it difficult to use these machines for practical applications.
A hybrid quantum and classical approach may be the answer to tackling this problem with existing quantum hardware. Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and Los Alamos National Laboratory, along with researchers at Clemson University and Fujitsu Laboratories of America, have developed hybrid algorithms to run on quantum machines and have demonstrated them for practical applications using IBM quantum computers (see right rail for description of Argonne’s role in the IBMQ Hub at Oak Ridge National Laboratory [ORNL]) and a D-Wave quantum computer.
“This approach will enable researchers to use near-term quantum computers to solve applications that support the DOE mission. For example, it can be applied to find community structures in metabolic networks or a microbiome.” — Yuri Alexeev, principal project specialist, Computational Science division
The team’s work is presented in an article entitled ?“A Hybrid Approach for Solving Optimization Problems on Small Quantum Computers” that appears in the June 2019 issue of the Institute of Electrical and Electronics Engineers (IEEE) Computer Magazine.
Concerns about qubit connectivity, high noise levels, the effort required to correct errors, and the scalability of quantum hardware have limited researchers’ ability to deliver the solutions that future quantum computing promises.
The hybrid algorithms that the team developed employ the best features and capabilities of both classical and quantum computers to address these limitations. For example, classical computers have large memories capable of storing huge datasets — a challenge for quantum devices that have only a small number of qubits. On the other hand, quantum algorithms perform better for certain problems than classical algorithms.
To distinguish between the types of computation performed on two completely different types of hardware, the team referred to the classical and quantum stages of hybrid algorithms as central processing units (CPUs) for classical computers and quantum processing units (QPUs) for quantum computers.
The team seized on graph partitioning and clustering as examples of practical and important optimization problems that can already be solved using quantum computers: a small graph problem can be solved directly on a QPU, while larger graph problems require hybrid quantum-classical approaches.
As a problem became too large to run directly on quantum computers, the researchers used decomposition methods to break the problem down into smaller pieces that the QPU could manage — an idea they borrowed from high-performance computing and classical numerical methods.
All the pieces were then assembled into a final solution on the CPU, which not only found better parameters, but also identified the best sub-problem size to solve on a quantum computer.
Such hybrid approaches are not a silver bullet; they do not allow for quantum speedup because using decomposition schemes limits speed as the size of the problem increases. In the next 10 years, though, expected improvements in qubits (quality, count, and connectivity), error correction, and quantum algorithms will decrease runtime and enable more advanced computation.
“In the meantime,” according to Yuri Alexeev, principal project specialist in the Computational Science division, ?“this approach will enable researchers to use near-term quantum computers to solve applications that support the DOE mission. For example, it can be applied to find community structures in metabolic networks or a microbiome.”
Learn more: The best of both worlds: how to solve real problems on modern quantum computers
The Latest on: Quantum computing
via Google News
The Latest on: Quantum computing
- UChicago Certificate Supports Transition to Quantum Careerson January 26, 2021 at 9:15 am
Last fall, the Chicago Quantum Exchange launched the inaugural session of a new Certificate Program in Quantum Engineering and ...
- Physicists use 'hyperchaos' to model complex quantum systems at a fraction of the computing poweron January 26, 2021 at 6:40 am
Physicists have discovered a potentially game-changing feature of quantum bit behavior which would allow scientists to simulate complex quantum systems without the need for enormous computing power.
- QCI QikStart™ Program Accelerates Business Adoption of Quantum Computingon January 26, 2021 at 5:41 am
Quantum Computing Inc. (OTCQB: QUBT) (QCI), the leader in bridging the power of classic and quantum computing, today unveiled its QikStart™ Program. The program partners QCI with selected participants ...
- Simulating black holes, building better drugs: Expanded quantum computing project brings new research possibilitieson January 25, 2021 at 9:32 pm
Armed with shiny new technology and a major building expansion, Duke is betting big on quantum computing. Since November 2020, construction has been underway to expand Duke’s existing quantum ...
- Quantum Computing Software Specialist Riverlane Secures $20M in Series A Fundingon January 25, 2021 at 8:09 am
Riverlane, a quantum software company, today announces that it has raised $20m in Series A funding to build Deltaflow, its operating system for quantum computers. Over the past year, Riverlane has ...
- Quantum hyperchaos could help build better quantum computerson January 25, 2021 at 4:59 am
When quantum computers get too complex, they can display hyperchaotic behaviour – like chaos, but more chaotic – and understanding it could help improve computer designs ...
- Cambridge quantum computing start-up targets global expansionon January 24, 2021 at 8:04 pm
A quantum computing start-up spun out of Cambridge university has completed its first significant fundraising to help accelerate its global growth. Riverlane is part of the vanguard of British ...
- Quantum computing research helps IBM win top spot in patent raceon January 24, 2021 at 7:23 pm
Quantum computing research helps IBM win top spot in patent race. An IBM patent shows a hexagonal array of qubits in a quantum computer, ...
- New blueprint for more stable quantum computerson January 22, 2021 at 9:44 am
Researchers at the Paul Scherrer Institute (PSI) have put forward a detailed plan of how faster and better defined quantum bits—qubits—can be created. The central elements are magnetic atoms from the ...
- Less is more: IBM achieves quantum computing simulation for new materials with fewer qubitson January 20, 2021 at 11:11 pm
IBM researchers achieved better simulation of molecules that could be used to design new materials, without the need for more qubits.
via Bing News