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Simulated Quantum Annealing (SQA), that is emulating a Quantum Annealing (QA) dynamics on a classical computer by a Quantum Monte Carlo whose parameters are changed during the simulation, is a well established computational strategy to cope…

Quantum Physics · Physics 2019-02-06 Glen Bigan Mbeng , Lorenzo Privitera , Luca Arceci , Giuseppe E. Santoro

We investigate the tunneling process between two symmetric stable islands of a forced pendulum Hamiltonian in the weak chaos regime. We show that when the tunneling doublet is quantized over a classical non-linear resonance the tunneling…

chao-dyn · Physics 2009-10-31 Luca Bonci , Andrea Farusi , Paolo Grigolini , Roberto Roncaglia

It is not widely appreciated that an acoustic wave can "jump" or "tunnel" across a vacuum gap between two piezoelectric solids, nor has the general case been formulated or studied in detail. Here, we remedy that situation, by presenting a…

Mesoscale and Nanoscale Physics · Physics 2022-05-17 Zhuoran Geng , Ilari J. Maasilta

A simple model of a quantum clock is applied to the old and controversial problem of how long a particle takes to tunnel through a quantum barrier. The model I employ has the advantage of yielding sensible results for energy eigenstates,…

Quantum Physics · Physics 2009-11-10 P. C. W. Davies

The Path Integral Monte Carlo simulated Quantum Annealing algorithm is applied to the optimization of a large hard instance of the Random 3-SAT Problem (N=10000). The dynamical behavior of the quantum and the classical annealing are…

Disordered Systems and Neural Networks · Physics 2009-11-11 Demian Battaglia , Giuseppe Santoro , Erio Tosatti

We have studied dynamical properties and quantum tunneling in asymmetric double-well (DW) systems, by solving Schr\"{o}dinger equation with the use of two kinds of spectral methods for initially squeezed Gaussian wavepackets. Time…

Quantum Physics · Physics 2015-06-15 Hideo Hasegawa

Quantum annealing is an innovative idea and method for avoiding the increase of the calculation cost of the combinatorial optimization problem. Since the combinatorial optimization problems are ubiquitous, quantum annealing machine with…

Statistical Mechanics · Physics 2020-01-13 Shohei Watabe , Yuya Seki , Shiro Kawabata

Quantum computing and quantum Monte Carlo (QMC) are respectively the state-of-the-art quantum and classical computing methods for understanding many-body quantum systems. Here, we propose a hybrid quantum-classical algorithm that integrates…

Quantum Physics · Physics 2025-11-17 Yukun Zhang , Yifei Huang , Jinzhao Sun , Dingshun Lv , Xiao Yuan

By including elements of the density matrix formalism, the semiclassical ensemble Monte Carlo method for carrier transport is extended to incorporate incoherent tunneling, known to play an important role in quantum cascade lasers (QCLs). In…

Mesoscale and Nanoscale Physics · Physics 2017-11-17 Christian Jirauschek

Quantum mechanical real-time tunneling through general scattering potentials is studied in the semiclassical limit. It is shown that the exact path integral of the real-time propagator is dominated in the long time sector by…

Quantum Physics · Physics 2016-08-16 Joachim Ankerhold , Markus Saltzer

We have reformulated the quantum Monte Carlo (QMC) technique so that a large part of the calculation scales linearly with the number of atoms. The reformulation is related to a recent alternative proposal for achieving linear-scaling QMC,…

Other Condensed Matter · Physics 2016-08-31 D. Alfe` , M. J. Gillan

Singularity of the potential function makes quantum tunneling problem mathematically underdetermined. To circumvent the difficulties it introduced in physics, a potential singularity cutoff is often used, followed by a reverse limit…

Quantum Physics · Physics 2021-07-07 A. Zh. Muradyan

Computational methods both open the frontiers of economic analysis and serve as a bottleneck in what can be achieved. We are the first to study whether Quantum Monte Carlo (QMC) algorithm can improve the runtime of economic applications and…

Quantum Physics · Physics 2024-09-24 Vladimir Skavysh , Sofia Priazhkina , Diego Guala , Thomas R. Bromley

Neural-network quantum states (NQS) offer a versatile and expressive alternative to traditional variational ans\"atze for simulating physical systems. Energy-based frameworks, like Hopfield networks and Restricted Boltzmann Machines,…

Quantum Physics · Physics 2024-12-18 Manas Sajjan , Vinit Singh , Sabre Kais

We consider in detail the quantum-mechanical problem associated with the motion of a one-dimensional particle under the action of the double-well potential. Our main tool will be the euclidean (imaginary time) version of the path-integral…

Quantum Physics · Physics 2015-06-26 J. Casahorran

Quantum Monte Carlo (QMC) is a family of powerful tools for addressing quantum many-body problems. However, its applications are often plagued by the fermionic sign problem. A promising strategy is to simulate an interaction without sign…

Nuclear Theory · Physics 2025-05-01 Jun Liu , Teng Wang , Bing-Nan Lu

Quantum tunneling in a two-dimensional integrable map is studied. The orbits of the map are all confined to the curves specified by the one-dimensional Hamiltonian. It is found that the behavior of tunneling splitting for the integrable map…

Chaotic Dynamics · Physics 2024-04-01 Yasutaka Hanada , Akira Shudo

It is well known that quantum tunneling can be described by instantons in the imaginary-time path integral formalism. However, its description in the real-time path integral formalism has been elusive. Here we establish a statement that…

High Energy Physics - Theory · Physics 2023-08-03 Jun Nishimura , Katsuta Sakai , Atis Yosprakob

Using Monte Carlo simulations, we investigate the electrical conductivity of networks of hard rods as a function of the volume fraction for two tunneling conductance models. For a simple, orientationally independent tunneling model, we…

Soft Condensed Matter · Physics 2018-12-26 Arshia Atashpendar , Sarthak Arora , Alexander D. Rahm , Tanja Schilling

Optimizing the training of a machine learning pipeline helps in reducing training costs and improving model performance. One such optimizing strategy is quantum annealing, which is an emerging computing paradigm that has shown potential in…

Quantum Physics · Physics 2021-06-08 Rajdeep Kumar Nath , Himanshu Thapliyal , Travis S. Humble
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