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Understanding quantum tunneling using diffusion Monte Carlo simulations

Inack, E. M.
•
Giudici, G.
•
Parolini, Tommaso
altro
Pilati, Sebastiano
2018
  • journal article

Periodico
PHYSICAL REVIEW A
Abstract
In simple ferromagnetic quantum Ising models characterized by an effective double-well energy landscape the characteristic tunneling time of path-integral Monte Carlo (PIMC) simulations has been shown to scale as the incoherent quantum-tunneling time, i.e., as 1/Δ2, where Δ is the tunneling gap. Since incoherent quantum tunneling is employed by quantum annealers (QAs) to solve optimization problems, this result suggests that there is no quantum advantage in using QAs with respect to quantum Monte Carlo (QMC) simulations. A counterexample is the recently introduced shamrock model (Andriyash and Amin, arXiv:1703.09277), where topological obstructions cause an exponential slowdown of the PIMC tunneling dynamics with respect to incoherent quantum tunneling, leaving open the possibility for potential quantum speedup, even for stoquastic models. In this work we investigate the tunneling time of projective QMC simulations based on the diffusion Monte Carlo (DMC) algorithm without guiding functions, showing that it scales as 1/Δ, i.e., even more favorably than the incoherent quantum-tunneling time, both in a simple ferromagnetic system and in the more challenging shamrock model. However, a careful comparison between the DMC ground-state energies and the exact solution available for the transverse-field Ising chain indicates an exponential scaling of the computational cost required to keep a fixed relative error as the system size increases.
DOI
10.1103/PhysRevA.97.032307
WOS
WOS:000426900500005
Archivio
http://hdl.handle.net/20.500.11767/87931
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85043999521
https://journals.aps.org/pra/abstract/10.1103/PhysRevA.97.032307
https://arxiv.org/abs/1711.08027
Diritti
closed access
Soggetti
  • Atomic and Molecular ...

  • Settore FIS/03 - Fisi...

Scopus© citazioni
10
Data di acquisizione
Jun 14, 2022
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Web of Science© citazioni
13
Data di acquisizione
Mar 15, 2024
Visualizzazioni
7
Data di acquisizione
Apr 19, 2024
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