TY - GEN
T1 - Quantum divide and compute
T2 - 19th IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2020
AU - Ayral, Thomas
AU - Le Regent, Francois Marie
AU - Saleem, Zain
AU - Alexeev, Yuri
AU - Suchara, Martin
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Noisy, intermediate-scale quantum computers comewith intrinsic limitations in terms of the number of qubits (circuit 'width') and decoherence time (circuit 'depth') they can have. Here, for the first time, we demonstrate a recently introduced method that breaks a circuit into smaller subcircuits or fragments, and thus makes it possible to run circuits that are either too wide or too deep for a given quantum processor. We investigate the behavior of the method on one of IBM's 20-qubit superconducting quantum processors with various numbers of qubits and fragments. We build noise models that capture decoherence, readout error, and gate imperfections for this particular processor. We then carry out noisy simulations of the method in order to account for the observed experimental results. We find an agreement within 20% between the experimental and the simulated success probabilities, and we observe that recombining noisy fragments yields overall results that can outperform the results without fragmentation.
AB - Noisy, intermediate-scale quantum computers comewith intrinsic limitations in terms of the number of qubits (circuit 'width') and decoherence time (circuit 'depth') they can have. Here, for the first time, we demonstrate a recently introduced method that breaks a circuit into smaller subcircuits or fragments, and thus makes it possible to run circuits that are either too wide or too deep for a given quantum processor. We investigate the behavior of the method on one of IBM's 20-qubit superconducting quantum processors with various numbers of qubits and fragments. We build noise models that capture decoherence, readout error, and gate imperfections for this particular processor. We then carry out noisy simulations of the method in order to account for the observed experimental results. We find an agreement within 20% between the experimental and the simulated success probabilities, and we observe that recombining noisy fragments yields overall results that can outperform the results without fragmentation.
KW - Fragmentation
KW - Noise models
KW - Noisy simulation
KW - Quantum algorithms
KW - Quantum computing
UR - https://www.scopus.com/pages/publications/85090400635
U2 - 10.1109/ISVLSI49217.2020.00034
DO - 10.1109/ISVLSI49217.2020.00034
M3 - Conference contribution
AN - SCOPUS:85090400635
T3 - Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI
SP - 138
EP - 140
BT - Proceedings - 2020 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2020
PB - IEEE Computer Society
Y2 - 6 July 2020 through 8 July 2020
ER -