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We use a Jastrow-Slater wave function with an elliptical Fermi sea to describe the nematic state of the two-dimensional electron gas in a magnetic field and the Monte Carlo method to calculate a variational energy upper bound. These energy…

Mesoscale and Nanoscale Physics · Physics 2008-08-18 Quoc M. Doan , Efstratios Manousakis

In this Ph.D. thesis quantum Monte Carlo methods are applied to investigate the properties of a number of ultracold quantum systems. In Chapter 1 we discuss the analytical approaches and approximations used in the subsequent Chapters; also…

Quantum Gases · Physics 2013-01-10 Oleg N. Osychenko

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be…

Nuclear Theory · Physics 2010-04-06 G. Hupin , D. Lacroix

In this paper, we solve quantum many-body problem by propagating ensembles of trajectories and guiding waves in physical space. We introduce the 'effective potential' correction within the recently proposed time-dependent quantum Monte…

Quantum Physics · Physics 2025-02-05 Ivan P. Christov

Recently, it has been shown that the ground-state energy of a quantum many-body system can be written in terms of cumulants. In this paper we show that the energies of excited states can be expressed similarly. These representations are…

Condensed Matter · Physics 2007-05-23 T. Schork , P. Fulde

Variational methods are used to calculate structural and thermodynamical properties of a titrating polyelectrolyte in a discrete representation. The Coulomb interactions are emulated by harmonic repulsive forces, the force constants being…

chem-ph · Physics 2008-02-03 B. Jönsson , M. Ullner , C. Peterson , O. Sommelius , B. Söderberg

The construction of trial wave functions based on neural networks combined with the variational Monte Carlo method is discussed. The mathematical formulation for representing quantum states as artificial neural networks is introduced. The…

Computational Physics · Physics 2026-05-19 William Freitas

The diffusion quantum Monte Carlo method is extended to solve the old theoretical physics problem of many-electron atoms and ions in intense magnetic fields. The feature of our approach is the use of adiabatic approximation wave functions…

Quantum Physics · Physics 2009-11-13 S. Bucheler , D. Engel , J. Main , G. Wunner

Variational minimization of tensor network states enables the exploration of low energy states of lattice gauge theories. However, the exact numerical evaluation of high-dimensional tensor network states remains challenging in general. In…

Quantum Physics · Physics 2020-10-12 Patrick Emonts , Mari Carmen Bañuls , J. Ignacio Cirac , Erez Zohar

We present \emph{multi-qubit correction} (MQC) as a novel postprocessing method for quantum annealers that views the evolution in an open-system as a Gibbs sampler and reduces a set of excited states to a new synthetic state with lower…

Quantum Physics · Physics 2021-07-13 Ramin Ayanzadeh , John Dorband , Milton Halem , Tim Finin

We present an elementary and self-contained account of the analogies existing between classical diffusion and the imaginary-time evolution of quantum systems. These analogies are used to develop a new quantum simulation method which allows…

Condensed Matter · Physics 2007-05-23 S. Baroni , S. Moroni

The two-dimensional Wigner crystals are studied with the variational quantum Monte Carlo method. The close relationship between the ground-state wavefunction and the collective excitations in the system is illustrated, and used to guide the…

Condensed Matter · Physics 2009-10-28 Xuejun Zhu , Steven G. Louie

The variational quantum eigensolver (VQE) is an algorithm to compute ground and excited state energy of quantum many-body systems. A key component of the algorithm and an active research area is the construction of a parametrized trial…

A variational ansatz for momentum eigenstates of translation invariant quantum spin chains is formulated. The matrix product state ansatz works directly in the thermodynamic limit and allows for an efficient implementation (cubic scaling in…

In this work, we consider the problem of estimating the probability distribution, the quantile or the conditional expectation above the quantile, the so called conditional-value-at-risk, of output quantities of complex random differential…

Computation · Statistics 2023-05-23 Quentin Ayoul-Guilmard , Sundar Ganesh , Sebastian Krumscheid , Fabio Nobile

We present and analyze large-scale simulation results of a hybrid quantum-classical variational method to calculate the ground state energy of the anti-ferromagnetic Heisenberg model. Using a massively parallel universal quantum computer…

Quantum Physics · Physics 2022-06-20 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

We propose a quantum Monte Carlo approach to solve the ground state many-body Schrodinger equation for the electronic ground state. The method combines optimization from variational Monte Carlo and propagation from auxiliary field quantum…

Computational Physics · Physics 2023-04-21 Yixiao Chen , Linfeng Zhang , Weinan E , Roberto Car

We formulate a quantum Monte Carlo (QMC) method for calculating the ground state of many-boson systems. The method is based on a field-theoretical approach, and is closely related to existing fermion auxiliary-field QMC methods which are…

Computational Physics · Physics 2009-11-10 Wirawan Purwanto , Shiwei Zhang

We introduce a variational wavefunction for many-body ground states that involves imaginary time evolution with two different Hamiltonians in an alternating fashion with variable time intervals. We successfully apply the ansatz on the one-…

Strongly Correlated Electrons · Physics 2019-09-25 Matthew J. S. Beach , Roger G. Melko , Tarun Grover , Timothy H. Hsieh

Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have…

Computational Physics · Physics 2007-05-23 David Ceperley , Mark Dewing , Carlo Pierleoni
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