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Quantum Filter Diagonalization with Compressed Double-Factorized Hamiltonians

delete2021-12-15
delete41
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OA
AI
J
Jeffrey Cohn *
M
Mário Motta
R
Robert M. Parrish
DOI:10.1103/PRXQuantum.2.040352delete
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摘要

摘要

En 中文
We demonstrate a method that merges the quantum filter diagonalization (QFD) approach for hybrid quantum-classical solution of the time-independent electronic Schrodinger equation with a low-rank double factorization (DF) approach for the representation of the electronic Hamiltonian. In particular, we explore the use of a novel sparse compressed double factorization (C-DF) truncation of the Hamiltonian within the time-propagation elements of QFD, while retaining a similarly compressed but numerically converged double-factorized representation of the Hamiltonian for the operator expectation values needed in the QFD quantum matrix elements. The new C-DF method is found to provide substantial additional compression at any given accuracy metric over the traditional explicit double factorization approach. Together with significant circuit reduction optimizations and number-preserving postselection and echosequencing error mitigation strategies, the method is found to provide accurate predictions for low-lying eigenspectra in a number of representative molecular systems, while requiring reasonably short circuit depths and modest measurement costs. The method is demonstrated by experiments on noise-free simulators, simulations including models of decoherence and shot-noise, and real quantum hardware.
Keyword:
APPROXIMATE INTEGRALS
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期刊

P
PRX Quantum
IF:
11
论文数:
919
被引数:
9.0K

机构

I
international business machines (ibm)
学者数:
5.7K
论文数: 4.5K
被引数: 4
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