Argonne National Laboratory Using Hybrid Computing to Boost Quantum Computing Power

The best of both worlds: how to solve real problems on modern quantum computers

Excerpts and salient points ~

+  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.

“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

+  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 IBM Q Hub at Oak Ridge National Laboratory [ORNL]) and a D-Wave quantum computer.

+  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.

Source:  Argonne National Laboratory.  Mary Fitzpatrick,  The best of both worlds: how to solve real problems on modern quantum computers…

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