Searcharxiv⌕ Search

arXiv · physics/0403146

Quantum Monte Carlo method for the ground state of many-boson systems

Abstract

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 applied in several fields of physics. The ground-state projection is implemented as a branching random walk in the space of permanents consisting of identical single-particle orbitals. The method is in principle exact. We illustrate this method with a trapped atomic boson gas, where the atoms interact via an attractive or repulsive contact two-body potential. We choose as the single-particle basis a real-space grid. We compare with exact results in small systems, and arbitrarily-sized systems of untrapped bosons with attractive interactions in one dimension, where analytical solutions exist. We also compare with the corresponding Gross-Pitaevskii (GP) mean-field calculations for trapped atoms, and discuss the close formal relation between our method and the GP approach. Our method provides a way to systematically improve upon GP while using the same framework, capturing interaction and correlation effects with a stochastic, coherent ensemble of non-interacting solutions. We discuss various algorithmic issues, including importance sampling and the back-propagation technique for computing observables, and illustrate them with numerical studies. We show results for systems with up to N ~ 400 bosons.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Wirawan Purwanto, Shiwei Zhang. 2004-03-31. Quantum Monte Carlo method for the ground state of many-boson systems. https://doi.org/10.1103/physreve.70.056702

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Advanced computational methods for simulating the classical hydrogen atom in stochastic electrodynamics

Stochastic electrodynamics (SED) is a theory of nature seeking to derive key aspects of quantum mechanics and quantum electrodynamics from a purely classical physics perspective. While SED has been successful in many areas, it has had mixed success when addressing the classical hydrogen atom bathed in classical electromagnetic zero-point radiation. Because analytical approaches are largely intractable, advanced numerical simulation methods are required. To address this, we develop a pseudo-wave formulation that integrates the solid angle in k-space utilizing symmetry, resulting in a significantly reduced memory footprint and lower computational overhead for generating the zero-point radiation spectrum. This optimization is paired with a logarithmic frequency grid, a sliding window tracking the instantaneous Keplerian frequency, and a Tukey smoothing function to eliminate discrete force discontinuities. Integrated via an adaptive RK4 algorithm with step-doubling across highly dense grids of up to 100-million bins, these techniques demonstrate the asymptotic convergence of ensemble stability. We show that increasing grid resolution in the high-frequency domain systematically mitigates artificial electron decay, yielding a simulated probability density function that closely aligns with the quantum mechanical ground state P(r). Crucially, the simulations exhibit stable, low-eccentricity orbits without any observed atomic ionization events.

physics.comp-ph↗

Quantum simulation of dissipative acoustic and elastic waves by Schrödingerisation: absorbing boundaries and explicit polynomial-size circuits

Explicit quantum circuits for the acoustic and elastic wave equations, obtained by Hamiltonian simulation of their first-order forms, conserve energy and therefore describe closed domains: an outgoing wave reflects off the edge of the computational region or, with periodic boundaries, wraps around and re-enters from the opposite side. We open the domain with the simplest physical absorber, a graded sponge layer in which every wave field is damped at a rate that grows towards the outer edge, and implement the resulting dissipative dynamics on a quantum simulator by Schrödingerisation, which turns a non-unitary linear evolution into a family of unitary ones by means of a single auxiliary variable. We derive the whole chain from the partial differential equation to the circuit, in one, two and three dimensions. An independent finite-difference solver confirms that damping all wave fields absorbs far better than the common velocity-only damping mask. For the sponge the quantum analysis is sharp: recovery is exact on the whole non- negative half of the auxiliary axis at every time; that axis can be truncated periodically at a length set by the largest damping rate and the simulated time; and the success probability is a fixed constant, about 0.4, times the fraction of the energy not yet absorbed, with only one or two auxiliary qubits measured. On the circuit side, the damping step, which generic synthesis compiles into a number of controlled-NOT gates exponential in the number of qubits, factorises exactly into polynomially many multi-controlled phase gates. Gate-level simulations on up to 25 qubits agree with the classical solutions of the damped wave equations.

physics.comp-ph↗

Maximal correlation and optimal transformations of probability distributions in tensor-train format: a variational algorithm

The correlation between two subsystems $A$ and $B$ of a many-body system is usually measured through a pair of observables chosen in advance. The Hirschfeld-Gebelein-Rényi maximal correlation removes the choice: it is the largest correlation coefficient between any function of the configuration of $A$ and any function of the configuration of $B$, and the two functions that reach it, the optimal transformations, are the observables that carry the correlation. Both follow from a singular value decomposition (SVD) of the joint distribution normalized by its marginals, a matrix whose dimension is the number of configurations. We show that this SVD can be computed variationally for a classical distribution of discrete variables, such as the Boltzmann distribution of a spin model, given in the tensor-train (matrix-product) format, without ever forming the matrix. The optimal transformations are sought as tensor trains; each step updates a single core in closed form, and the inverse of a small matrix contracted from the distribution and the remaining cores performs the division by the marginals core by core. Every iterate is a feasible pair, so the objective is a lower bound on the maximal correlation that increases monotonically, and the cost grows linearly with the number of variables. The algorithm reproduces the exact SVD on small systems, recovers the known nonlinear optimal transformations of synthetic distributions of up to ten angular variables ($10^{15}$ configurations), and, for the bipartite antiferromagnetic model with $2^{32}$ configurations, returns an optimal transformation that is a function of the group magnetization, linear above the transition and sign-like below it: the staggered order parameter is read off from the distribution instead of being postulated.

physics.comp-ph↗