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Quantum annealing is a generic solver of the optimization problem that uses fictitious quantum fluctuation. Its simulation in classical computing is often performed using the quantum Monte Carlo simulation via the Suzuki--Trotter…

Quantum Physics · Physics 2016-12-15 Masayuki Ohzeki

Simulated quantum annealing is a generic classical protocol to simulate some aspects of quantum annealing and is sometimes regarded as a classical alternative to quantum annealing in finding the ground state of a classical Ising model. We…

Quantum Physics · Physics 2022-12-21 Yusuke Kimura , Hidetoshi Nishimori

Non-stoquastic Hamiltonians have both positive and negative signs in off-diagonal elements in their matrix representation in the standard computational basis and thus cannot be simulated efficiently by the standard quantum Monte Carlo…

Quantum Physics · Physics 2017-02-21 Hidetoshi Nishimori , Kabuki Takada

Convergence conditions for quantum annealing are derived for optimization problems represented by the Ising model of a general form. Quantum fluctuations are introduced as a transverse field and/or transverse ferromagnetic interactions, and…

Quantum Physics · Physics 2007-05-25 Satoshi Morita , Hidetoshi Nishimori

We establish a set of nonequilibrium quantum phase transitions in the Ising model driven under monochromatic nonadiabatic modulation of the transverse field. We show that besides the Ising-like critical behavior, the system exhibits an…

Quantum Physics · Physics 2013-01-03 V. M. Bastidas , C. Emary , G. Schaller , T. Brandes

We introduce quantum fluctuations into the simulated annealing process of optimization problems, aiming at faster convergence to the optimal state. Quantum fluctuations cause transitions between states and thus play the same role as thermal…

Statistical Mechanics · Physics 2009-10-31 Tadashi Kadowaki , Hidetoshi Nishimori

Stoquastic Hamiltonians are characterized by the property that their off-diagonal matrix elements in the standard product basis are real and non-positive. Many interesting quantum models fall into this class including the Transverse field…

Quantum Physics · Physics 2017-01-13 Sergey Bravyi

We propose a two qubit experiment for validating tunable antiferromagnetic $XX$ interactions in quantum annealing. Such interactions allow the time-dependent Hamiltonian to be non-stoquastic, and the instantaneous ground state can have…

Quantum Physics · Physics 2020-01-10 Tameem Albash

We solve the mean-field-like $p$-spin Ising model under a spatio-temporal inhomogeneous transverse field to study the effects of inhomogeneity on the performance of quantum annealing. We find that the problematic first-order quantum phase…

Quantum Physics · Physics 2018-10-23 Yuki Susa , Yu Yamashiro , Masayuki Yamamoto , Itay Hen , Daniel A. Lidar , Hidetoshi Nishimori

We study the performance of quantum annealing for two sets of problems, namely, 2-satisfiability (2-SAT) problems represented by Ising-type Hamiltonians, and nonstoquastic problems which are obtained by adding extra couplings to the 2-SAT…

Quantum Physics · Physics 2021-10-04 Vrinda Mehta , Fengping Jin , Hans De Raedt , Kristel Michielsen

The rotational and fine structure of open-shell molecules in a $\Sigma$ electronic state gives rise to crossings between Zeeman states of different parity. These crossings become avoided in the presence of an electric field. We propose an…

Quantum Physics · Physics 2022-08-15 K. Asnaashari , R. V. Krems

The role of nonstoquasticity in the field of quantum annealing and adiabatic quantum computing is an actively debated topic. We study a strongly-frustrated quasi-one-dimensional quantum Ising model on a two-leg ladder to elucidate how a…

Non-equilibrium dynamics of the Ising model is a classical stochastic process whereas quantum mechanics has no stochastic elements in the classical sense. Nevertheless, it has been known that there exists a close formal relationship between…

Quantum Physics · Physics 2015-09-30 Hidetosni Nishimori

Relations of simulated annealing and quantum annealing are studied by a mapping from the transition matrix of classical Markovian dynamics of the Ising model to a quantum Hamiltonian and vice versa. It is shown that these two operators, the…

Quantum Physics · Physics 2015-01-08 Hidetoshi Nishimori , Junichi Tsuda , Sergey Knysh

Traditional simulated annealing utilizes thermal fluctuations for convergence in optimization problems. Quantum tunneling provides a different mechanism for moving between states, with the potential for reduced time scales. We compare…

Condensed Matter · Physics 2007-05-23 J. Brooke , D. Bitko , T. F. Rosenbaum , G. Aeppli

A quantum simulator is a well controlled quantum system that can simulate the behavior of another quantum system which may require exponentially large classical computing resources to understand otherwise. In the 1980s, Feynman proposed the…

We introduce transverse ferromagnetic interactions, in addition to a simple transverse field, to quantum annealing of the random-field Ising model to accelerate convergence toward the target ground state. The conventional approach using…

Quantum Physics · Physics 2007-06-13 Sei Suzuki , Hidetoshi Nishimori , Masuo Suzuki

We describe a new algorithm for the numerical simulation of quantum spin and boson systems. The method is based on the Trotter decomposition in imaginary time and a decoupling by auxiliary Ising spins. It can be applied, in principle, to…

Disordered Systems and Neural Networks · Physics 2009-10-31 M. Ulmke , R. T. Scalettar

Quantum annealing (QA) is a generic method for solving optimization problems using fictitious quantum fluctuation. The current device performing QA involves controlling the transverse field; it is classically simulatable by using the…

Disordered Systems and Neural Networks · Physics 2019-05-01 Masayuki Ohzeki

We introduce the transverse Ising model as a prototype for discussing quantum phase transition. Next we introduce Suzuki-Trotter formalism to show the correspondence between $d$-dimensional quantum system with a $(d+1)$-dimensional…

Disordered Systems and Neural Networks · Physics 2007-05-23 Bikas K. Chakrabarti , Arnab Das
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