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

Springer proceedings in physics

Finite Temperature Simulation Based on Lanczos Algorithm for Low-Dimensional Quantum Systems

Tôru Sakai

Published Jan 1, 2004• 0 citations
Publisher
DOI
10.1007/978-3-642-59293-5_7

Related papers

Advanced finite-temperature Lanczos method for anisotropic spin systems

Oliver Hanebaum, Jürgen Schnack

•Jan 1, 2014•17 citations

Finite Temperature Simulations of Strongly Correlated Systems

Chong Sun

This thesis describes several topics related to finite temperature studies of strongly correlated systems: finite temperature density matrix embedding theory (FT-DMET), finite temperature metal-insulator transition, and quantum algorithms including quantum imaginary time evolution (QITE), quantum Lanczos (QLanczos), and quantum minimally entangled typical thermal states (QMETTS) algorithms. While the absolute zero temperature is not reachable, studies of physical and chemical problems at finite temperatures, especially at low temperature, is essential for understanding the quantum behaviors of materials in realistic conditions. Here we define low temperature as the temperature regime where the quantum effect is not largely dissipated due to thermal fluctuation. Treatment of systems at low temperature is specially difficult compared to both high temperature - where classical approximation can be applied - and zero temperature where only the ground state is required to describe the system of interest. FT-DMET is a wavefunction-based embedding scheme which can handle finite temperature simulations of a variety of strongly correlated problems. The "high-level in low-level" framework enables FT-DMET to tackle large bulk sizes and capture the majority of the entanglement at the same time. FT-DMET formulations and implementation details for both model systems and ab initio problems are provided in Chapter 2 and Chapter 3. Metal-insulator transition is a common but important phase transition in many strongly correlated materials. The widely accepted scheme to distinguish an insulator from a metal is band structure theory based on a single-particle picture. However, insulating phases caused by disorder or strong correlation cannot be explained merely with the band structure. In Chapter 4, we demonstrate that electron locality/mobility is a more general criteria to detect metal-insulator transition. We further introduce complex polarization as the order parameter to reflect the electron locality/mobility and provide a formalism based on thermofield theory to evaluate the complex polarization at finite temperature. Quantum algorithms are designed to perform simulations on a quantum device. The infrastructure of a quantum processing unit (QPU) utilizes the superposition property of quantum bits (qubits), and thus can potentially outplay the classical simulations in computational scaling for certain problems. In Chapter 5, we introduce the QITE algorithm, which can be applied to quantum simulations of both ground state and finite temperature problems. We further introduce a subspace method, QLanczos algorithm, and a a finite temperature quantum algorithm, QMETTS, where QITE is used as a building block for the two algorithms. We demonstrate above quantum algorithms with simulations on both classical computers and quantum computers.

arXiv:2302.14313•Dec 18, 2020•1 citation

Numerical study of low-dimensional quantum systems

Tôru Sakai

•Jan 1, 1999•0 citations

Ground State and Finite Temperature Lanczos Methods

Peter Prelovšek, J. Bonča

The present review will focus on recent development of exact-diagonali- zation (ED) methods that use Lanczos algorithm to transform large sparse matrices onto the tridiagonal form. We begin with a review of basic principles of the Lanczos method for computing ground-state static as well as dynamical properties. Next, generalization to finite-temperatures in the form of well established finite-temperature Lanczos method is described. The latter allows for the evaluation of temperatures T>0 static and dynamic quantities within various correlated models. Several extensions and modification of the latter method introduced more recently are analysed. In particular, the low-temperature Lanczos method and the microcanonical Lanczos method, especially applicable within the high-T regime. In order to overcome the problems of exponentially growing Hilbert spaces that prevent ED calculations on larger lattices, different approaches based on Lanczos diagonalization within the reduced basis have been developed. In this context, recently developed method based on ED within a limited functional space is reviewed. Finally, we briefly discuss the real-time evolution of correlated systems far from equilibrium, which can be simulated using the ED and Lanczos-based methods, as well as approaches based on the diagonalization in a reduced basis.

arXiv:1111.5931•Nov 25, 2011•17 citations

Numerical simulation of low-dimensional quantum many-body systems

Shoji Yamamoto, 山本 昌司

•Jan 1, 1995•0 citations

Quantum Finite Temperature Lanczos Method

Gian Gentinetta, Friederike Metz, William Kirby +1 more

The computation of thermal properties of quantum many-body systems is a central challenge in our understanding of quantum mechanics. We introduce the Quantum Finite Temperature Lanczos Method (QFTLM), which extends the finite-temperature Lanczos method to quantum computers by combining real-time quantum Krylov methods with efficient preparation of typical states for trace estimation. This approach enables the computation of thermal expectation values while avoiding the exponential scaling inherent to classical exact simulation techniques. Numerical experiments on the transverse-field Ising model show that QFTLM can reproduce thermal observables over a wide temperature range. We further analyze the influence of Krylov dimension, number of trace-estimator states, and Trotter error, and show that suitable regularization is essential for robustness in noisy settings. These results establish QFTLM as a promising framework for finite-temperature quantum simulation.

quant-pharXiv:2603.25394•Physical Review Research•Mar 27, 2026•0 citations
This thesis describes several topics related to finite temperature studies of strongly correlated systems: finite temperature density matrix embedding theory (FT-DMET), finite temperature metal-insulator transition, and quantum algorithms including quantum imaginary time evolution (QITE), quantum Lanczos (QLanczos), and quantum minimally entangled typical thermal states (QMETTS) algorithms. While the absolute zero temperature is not reachable, studies of physical and chemical problems at finite temperatures, especially at low temperature, is essential for understanding the quantum behaviors of materials in realistic conditions. Here we define low temperature as the temperature regime where the quantum effect is not largely dissipated due to thermal fluctuation. Treatment of systems at low temperature is specially difficult compared to both high temperature - where classical approximation can be applied - and zero temperature where only the ground state is required to describe the system of interest. FT-DMET is a wavefunction-based embedding scheme which can handle finite temperature simulations of a variety of strongly correlated problems. The "high-level in low-level" framework enables FT-DMET to tackle large bulk sizes and capture the majority of the entanglement at the same time. FT-DMET formulations and implementation details for both model systems and ab initio problems are provided in Chapter 2 and Chapter 3. Metal-insulator transition is a common but important phase transition in many strongly correlated materials. The widely accepted scheme to distinguish an insulator from a metal is band structure theory based on a single-particle picture. However, insulating phases caused by disorder or strong correlation cannot be explained merely with the band structure. In Chapter 4, we demonstrate that electron locality/mobility is a more general criteria to detect metal-insulator transition. We further introduce complex polarization as the order parameter to reflect the electron locality/mobility and provide a formalism based on thermofield theory to evaluate the complex polarization at finite temperature. Quantum algorithms are designed to perform simulations on a quantum device. The infrastructure of a quantum processing unit (QPU) utilizes the superposition property of quantum bits (qubits), and thus can potentially outplay the classical simulations in computational scaling for certain problems. In Chapter 5, we introduce the QITE algorithm, which can be applied to quantum simulations of both ground state and finite temperature problems. We further introduce a subspace method, QLanczos algorithm, and a a finite temperature quantum algorithm, QMETTS, where QITE is used as a building block for the two algorithms. We demonstrate above quantum algorithms with simulations on both classical computers and quantum computers.
The present review will focus on recent development of exact-diagonali- zation (ED) methods that use Lanczos algorithm to transform large sparse matrices onto the tridiagonal form. We begin with a review of basic principles of the Lanczos method for computing ground-state static as well as dynamical properties. Next, generalization to finite-temperatures in the form of well established finite-temperature Lanczos method is described. The latter allows for the evaluation of temperatures T>0 static and dynamic quantities within various correlated models. Several extensions and modification of the latter method introduced more recently are analysed. In particular, the low-temperature Lanczos method and the microcanonical Lanczos method, especially applicable within the high-T regime. In order to overcome the problems of exponentially growing Hilbert spaces that prevent ED calculations on larger lattices, different approaches based on Lanczos diagonalization within the reduced basis have been developed. In this context, recently developed method based on ED within a limited functional space is reviewed. Finally, we briefly discuss the real-time evolution of correlated systems far from equilibrium, which can be simulated using the ED and Lanczos-based methods, as well as approaches based on the diagonalization in a reduced basis.
The computation of thermal properties of quantum many-body systems is a central challenge in our understanding of quantum mechanics. We introduce the Quantum Finite Temperature Lanczos Method (QFTLM), which extends the finite-temperature Lanczos method to quantum computers by combining real-time quantum Krylov methods with efficient preparation of typical states for trace estimation. This approach enables the computation of thermal expectation values while avoiding the exponential scaling inherent to classical exact simulation techniques. Numerical experiments on the transverse-field Ising model show that QFTLM can reproduce thermal observables over a wide temperature range. We further analyze the influence of Krylov dimension, number of trace-estimator states, and Trotter error, and show that suitable regularization is essential for robustness in noisy settings. These results establish QFTLM as a promising framework for finite-temperature quantum simulation.