Walking through Hilbert Space with Quantum Computers DOI
Tong Jiang, Jinghong Zhang, Moritz K. A. Baumgarten

et al.

Chemical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

Computations of chemical systems' equilibrium properties and nonequilibrium dynamics have been suspected being a "killer app" for quantum computers. This review highlights the recent advancements algorithms tackling complex sampling tasks in key areas computational chemistry: ground state, thermal state properties, calculations. We broad range algorithms, from hybrid quantum-classical to fully quantum, focusing on traditional Monte Carlo family, including Markov chain Carlo, variational projector path integral etc. also cover other relevant techniques involving tasks, such as quantum-selected configuration interaction, minimally entangled typical states, entanglement forging, Carlo-flavored Lindbladian dynamics. provide comprehensive overview these algorithms' classical counterparts, detailing their theoretical frameworks discussing potentials challenges achieving advantages.

Language: Английский

Unbiasing fermionic auxiliary-field quantum Monte Carlo with matrix product state trial wavefunctions DOI
Tong Jiang, Bryan O’Gorman, Ankit Mahajan

et al.

Physical Review Research, Journal Year: 2025, Volume and Issue: 7(1)

Published: Jan. 10, 2025

In this work, we report, for the first time, an implementation of fermionic auxiliary-field quantum Monte Carlo (AFQMC) using matrix product state (MPS) trial wavefunctions, dubbed MPS-AFQMC. Calculating overlaps between MPS and arbitrary Slater determinants up to a multiplicative error, crucial subroutine in MPS-AFQMC, is proven be #P-hard. Nonetheless, tested several promising heuristics successfully improving phaseless AFQMC energies. We also proposed way evaluate local energy force bias evaluations free operators. This allows larger basis set calculations without significant overhead. showcase utility our approach on one- two-dimensional hydrogen lattices, even when itself struggles obtain high accuracy. Our work offers new tools that can solve currently challenging electronic structure problems with future improvements. Published by American Physical Society 2025

Language: Английский

Citations

3
Beyond CCSD(T) Accuracy at Lower Scaling with Auxiliary Field Quantum Monte Carlo DOI
Ankit Mahajan, James H. Thorpe, Jo S. Kurian

et al.

Journal of Chemical Theory and Computation, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

We introduce a black-box auxiliary field quantum Monte Carlo (AFQMC) approach to perform highly accurate electronic structure calculations using configuration interaction singles and doubles (CISD) trial states. This method consistently provides more energy estimates than coupled cluster with perturbative triples (CCSD(T)), often regarded as the gold standard in chemistry. level of precision is achieved at lower asymptotic computational cost, scaling O(N6) compared O(N7) CCSD(T). provide numerical evidence supporting these findings through results for challenging main group transition metal-containing molecules.

Language: Английский

Citations

1
Walking through Hilbert Space with Quantum Computers DOI
Tong Jiang, Jinghong Zhang, Moritz K. A. Baumgarten

et al.

Chemical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

Computations of chemical systems' equilibrium properties and nonequilibrium dynamics have been suspected being a "killer app" for quantum computers. This review highlights the recent advancements algorithms tackling complex sampling tasks in key areas computational chemistry: ground state, thermal state properties, calculations. We broad range algorithms, from hybrid quantum-classical to fully quantum, focusing on traditional Monte Carlo family, including Markov chain Carlo, variational projector path integral etc. also cover other relevant techniques involving tasks, such as quantum-selected configuration interaction, minimally entangled typical states, entanglement forging, Carlo-flavored Lindbladian dynamics. provide comprehensive overview these algorithms' classical counterparts, detailing their theoretical frameworks discussing potentials challenges achieving advantages.

Language: Английский

Citations

0