Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:1612.05260 · Physical review. B./Physical review. B

Finite-temperature properties of strongly correlated systems via variational Monte Carlo

Jahan Claes, Bryan K. Clark

Published May 8, 2017• 22 citations
arXivHTMLPDF

Abstract

Variational methods are a common approach for computing properties of ground states but have not yet found analogous success in finite-temperature calculations. In this work, we develop a new variational finite-temperature algorithm (VAFT), which combines ideas from minimally entangled typical thermal states (METTS), variational Monte Carlo (VMC) optimization, and path integral Monte Carlo (PIMC). This allows us to define an implicit variational density matrix to estimate finite-temperature properties in two and three dimensions. We benchmark the algorithm on the bipartite Heisenberg model and compare to exact results.

DOI
10.1103/physrevb.95.205109

Related papers

Finite-Temperature Variational Monte Carlo Method for Strongly Correlated Electron Systems

Kensaku Takai, Kota Ido, Takahiro Misawa +2 more

A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in the imaginary-time formulation, starting from the infinite-temperature state that is well approximated by a small number of certain random initial states. Lower temperatures are progressively reached by the imaginary-time evolution. The algorithm follows the framework of the quantum transfer matrix and finite-temperature Lanczos methods, but we extends them to treat much larger system sizes without the negative sign problem by optimizing the truncated Hilbert space on the basis of the time-dependent variational principle (TDVP). This optimization algorithm is equivalent to the stochastic reconfiguration (SR) method that has been frequently used for the ground state to optimally truncate the Hilbert space. The obtained finite-temperature states allow an interpretation based on the thermal pure quantum (TPQ) state instead of the conventional canonical-ensemble average. Our method is tested for the one- and two-dimensional Hubbard models and its accuracy and efficiency are demonstrated.

arXiv:1510.05352•Journal of the Physical Society of Japan•Feb 18, 2016•21 citations

Adaptive variational quantum minimally entangled typical thermal states for finite temperature simulations

João C. Getelina, Niladri Gomes, Thomas Iadecola +2 more

Scalable quantum algorithms for the simulation of quantum many-body systems in thermal equilibrium are important for predicting properties of quantum matter at finite temperatures. Here we describe and benchmark a quantum computing version of the minimally entangled typical thermal states (METTS) algorithm for which we adopt an adaptive variational approach to perform the required quantum imaginary time evolution. The algorithm, which we name AVQMETTS, dynamically generates compact and problem-specific quantum circuits, which are suitable for noisy intermediate-scale quantum (NISQ) hardware. We benchmark AVQMETTS on statevector simulators and perform thermal energy calculations of integrable and nonintegrable quantum spin models in one and two dimensions and demonstrate an approximately linear system-size scaling of the circuit complexity. We further map out the finite-temperature phase transition line of the two-dimensional transverse field Ising model. Finally, we study the impact of noise on AVQMETTS calculations using a phenomenological noise model.

arXiv:2301.02592•SciPost Physics•Sep 19, 2023•21 citations

Matrix product state techniques for two-dimensional systems at finite temperature

Benedikt Bruognolo, Zhenyue Zhu, Steven R. White +1 more

The density matrix renormalization group is one of the most powerful numerical methods for computing ground-state properties of two-dimensional (2D) quantum lattice systems. Here we show its finite-temperature extensions are also viable for 2D, using the following strategy: At high temperatures, we combine density-matrix purification and numerical linked-cluster expansions to extract static observables directly in the thermodynamic limit. At low temperatures inaccessible to purification, we use the minimally entangled typical thermal state (METTS) algorithm on cylinders. We consider the triangular Heisenberg antiferromagnet as a first application, finding excellent agreement with other state of the art methods. In addition, we present a METTS-based approach that successfully extracts critical temperatures, and apply it to a frustrated lattice model. On a technical level, we compare two different schemes for performing imaginary-time evolution of 2D clusters, finding that a Suzuki-Trotter decomposition with swap gates is currently the most accurate and efficient.

arXiv:1705.05578•May 16, 2017•28 citations

Minimally entangled typical thermal states with auxiliary matrix-product-state bases

Chia-Min Chung, Ulrich Schollwöck

Finite temperature problems in the strong correlated systems are important but challenging tasks. Minimally entangled typical thermal states (METTS) are a powerful method in the framework of tensor network methods to simulate finite temperature systems, including Fermions and frustrated spins which introduce a sign problem in the typical Monte Carlo methods. In this work, we introduce an extension of the METTS algorithm by using a new basis, the auxiliary matrix product state. This new basis achieves the pre-summation process in the partition function, and thus improve the convergence in the Monte Carlo samplings. The method also has the advantage of simulating the grand canonical ensemble in a computationally efficient way by employing good quantum numbers. We benchmark our method on the spin-$1/2$ XXZ model on the triangular lattice, and show that the new method outperforms the original METTS as well as the purification methods at sufficiently low temperature, the usual range of applications of METTS. The new method also naturally connects the METTS method to the purification method.

arXiv:1910.03329•Oct 8, 2019•2 citations

Pairing and entanglement: quantum Monte Carlo studies

David ChangMo Yang

Described in this dissertation is the use of quantum Monte Carlo methods to study two ideas in quantum many-body problems: superfluidity and entanglement. Density matrices are presented a central tool in the analysis, as are discussed in the review of path integral Monte Carlo (PIMC) and variational Monte Carlo (VMC) methods. PIMC is used to model a one-dimensional system of fermionic lithium atoms according to existing experiments, including a realistic temperature. New estimators of the pair momentum distribution are implemented, yielding in a clear in-situ signature of a pairing mechanism (dubbed FFLO after its first proposers) which implies a microscopic phase fluctuation in space between a normal fluid and a superfluid. VMC is used to model homonuclear diatomic molecules of period-2 elements. The degree of entanglement and the responsible electronic configurations in real space are quantified in terms of the entanglement spectra. Calculating the reduced denstity matrix as an intermediate step reveals a novel way of understanding chemical bonds, as exemplified by Be2 and C2 . Possible implications of these results in integrable many-body models and in quantum chemistry are discussed, as well as direction for future investigation.

•Apr 7, 2016•0 citations

Variational Monte Carlo method for electron-phonon coupled systems

Takahiro Ohgoe, Masatoshi Imada

We develop a variational Monte Carlo (VMC) method for electron-phonon coupled systems. The VMC method has been extensively used for investigating strongly correlated electrons over the last decades. However, its applications to electron-phonon coupled systems have been severely restricted because of its large Hilbert space. Here, we propose a variational wave function with a large number of variational parameters, which is suitable and tractable for systems with electron-phonon coupling. In the proposed wave function, we implement an unexplored electron-phonon correlation factor, which takes into account the effect of the entanglement between electrons and phonons. The method is applied to systems with diagonal electron-phonon interactions, i.e., interactions between charge densities and lattice displacements (phonons). As benchmarks, we compare VMC results with previous results obtained by the exact diagonalization, the Green function Monte Carlo method and the density matrix renormalization group for the Holstein and Holstein-Hubbard model. From these benchmarks, we show that the present method offers an efficient way to treat strongly coupled electron-phonon systems.

arXiv:1403.4150•Physical Review B•May 29, 2014•28 citations
Variational methods are a common approach for computing properties of ground states but have not yet found analogous success in finite-temperature calculations. In this work, we develop a new variational finite-temperature algorithm (VAFT), which combines ideas from minimally entangled typical thermal states (METTS), variational Monte Carlo (VMC) optimization, and path integral Monte Carlo (PIMC). This allows us to define an implicit variational density matrix to estimate finite-temperature properties in two and three dimensions. We benchmark the algorithm on the bipartite Heisenberg model and compare to exact results.
A new computational method for finite-temperature properties of strongly correlated electrons is proposed by extending the variational Monte Carlo method originally developed for the ground state. The method is based on the path integral in the imaginary-time formulation, starting from the infinite-temperature state that is well approximated by a small number of certain random initial states. Lower temperatures are progressively reached by the imaginary-time evolution. The algorithm follows the framework of the quantum transfer matrix and finite-temperature Lanczos methods, but we extends them to treat much larger system sizes without the negative sign problem by optimizing the truncated Hilbert space on the basis of the time-dependent variational principle (TDVP). This optimization algorithm is equivalent to the stochastic reconfiguration (SR) method that has been frequently used for the ground state to optimally truncate the Hilbert space. The obtained finite-temperature states allow an interpretation based on the thermal pure quantum (TPQ) state instead of the conventional canonical-ensemble average. Our method is tested for the one- and two-dimensional Hubbard models and its accuracy and efficiency are demonstrated.
Scalable quantum algorithms for the simulation of quantum many-body systems in thermal equilibrium are important for predicting properties of quantum matter at finite temperatures. Here we describe and benchmark a quantum computing version of the minimally entangled typical thermal states (METTS) algorithm for which we adopt an adaptive variational approach to perform the required quantum imaginary time evolution. The algorithm, which we name AVQMETTS, dynamically generates compact and problem-specific quantum circuits, which are suitable for noisy intermediate-scale quantum (NISQ) hardware. We benchmark AVQMETTS on statevector simulators and perform thermal energy calculations of integrable and nonintegrable quantum spin models in one and two dimensions and demonstrate an approximately linear system-size scaling of the circuit complexity. We further map out the finite-temperature phase transition line of the two-dimensional transverse field Ising model. Finally, we study the impact of noise on AVQMETTS calculations using a phenomenological noise model.
The density matrix renormalization group is one of the most powerful numerical methods for computing ground-state properties of two-dimensional (2D) quantum lattice systems. Here we show its finite-temperature extensions are also viable for 2D, using the following strategy: At high temperatures, we combine density-matrix purification and numerical linked-cluster expansions to extract static observables directly in the thermodynamic limit. At low temperatures inaccessible to purification, we use the minimally entangled typical thermal state (METTS) algorithm on cylinders. We consider the triangular Heisenberg antiferromagnet as a first application, finding excellent agreement with other state of the art methods. In addition, we present a METTS-based approach that successfully extracts critical temperatures, and apply it to a frustrated lattice model. On a technical level, we compare two different schemes for performing imaginary-time evolution of 2D clusters, finding that a Suzuki-Trotter decomposition with swap gates is currently the most accurate and efficient.
Finite temperature problems in the strong correlated systems are important but challenging tasks. Minimally entangled typical thermal states (METTS) are a powerful method in the framework of tensor network methods to simulate finite temperature systems, including Fermions and frustrated spins which introduce a sign problem in the typical Monte Carlo methods. In this work, we introduce an extension of the METTS algorithm by using a new basis, the auxiliary matrix product state. This new basis achieves the pre-summation process in the partition function, and thus improve the convergence in the Monte Carlo samplings. The method also has the advantage of simulating the grand canonical ensemble in a computationally efficient way by employing good quantum numbers. We benchmark our method on the spin-1/21/21/2 XXZ model on the triangular lattice, and show that the new method outperforms the original METTS as well as the purification methods at sufficiently low temperature, the usual range of applications of METTS. The new method also naturally connects the METTS method to the purification method.
Described in this dissertation is the use of quantum Monte Carlo methods to study two ideas in quantum many-body problems: superfluidity and entanglement. Density matrices are presented a central tool in the analysis, as are discussed in the review of path integral Monte Carlo (PIMC) and variational Monte Carlo (VMC) methods. PIMC is used to model a one-dimensional system of fermionic lithium atoms according to existing experiments, including a realistic temperature. New estimators of the pair momentum distribution are implemented, yielding in a clear in-situ signature of a pairing mechanism (dubbed FFLO after its first proposers) which implies a microscopic phase fluctuation in space between a normal fluid and a superfluid. VMC is used to model homonuclear diatomic molecules of period-2 elements. The degree of entanglement and the responsible electronic configurations in real space are quantified in terms of the entanglement spectra. Calculating the reduced denstity matrix as an intermediate step reveals a novel way of understanding chemical bonds, as exemplified by Be2 and C2 . Possible implications of these results in integrable many-body models and in quantum chemistry are discussed, as well as direction for future investigation.
We develop a variational Monte Carlo (VMC) method for electron-phonon coupled systems. The VMC method has been extensively used for investigating strongly correlated electrons over the last decades. However, its applications to electron-phonon coupled systems have been severely restricted because of its large Hilbert space. Here, we propose a variational wave function with a large number of variational parameters, which is suitable and tractable for systems with electron-phonon coupling. In the proposed wave function, we implement an unexplored electron-phonon correlation factor, which takes into account the effect of the entanglement between electrons and phonons. The method is applied to systems with diagonal electron-phonon interactions, i.e., interactions between charge densities and lattice displacements (phonons). As benchmarks, we compare VMC results with previous results obtained by the exact diagonalization, the Green function Monte Carlo method and the density matrix renormalization group for the Holstein and Holstein-Hubbard model. From these benchmarks, we show that the present method offers an efficient way to treat strongly coupled electron-phonon systems.