Thermal pure states for systems with antiunitary symmetries and their tensor network representations

Thermal pure state algorithms, which employ pure quantum states representing thermal equilibrium states instead of statistical ensembles, are useful both for numerical simulations and for theoretical analysis of thermal states. However, their inherently large entanglement makes it difficult to represent efficiently and limits their use in analyzing large systems. Here we propose a tensor network algorithm for constructing thermal pure states for systems with certain antiunitary symmetries, such as time-reversal or complex-conjugate symmetry. Our method utilizes thermal pure states that, while exhibiting volume-law entanglement, can be mapped to tensor network states through simple transformations. Furthermore, our approach does not rely on random sampling and thus avoids statistical uncertainty. Moreover, we can compute not only thermal expectation values of local observables but also thermodynamic quantities. We demonstrate the validity and utility of our method by applying it to the one-dimensional <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mi>X</a:mi><a:mi>Y</a:mi></a:mrow></a:math> model and the two-dimensional Ising model on a triangular lattice. Our results suggest a class of variational wave functions for volume-law states that are not limited to thermal equilibrium states. Published by the American Physical Society 2024

Authors

Institutions

Publication Details

Journal
Physical Review Research
Published
2024-12-13
DOI
https://doi.org/10.1103/physrevresearch.6.l042062
Citations
5
Primary Topic
Quantum many-body systems
Type
article
Field-Weighted Citation Impact
1.69

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Thermal pure states for systems with antiunitary symmetries and their tensor network representations

Yasushi Yoneta
5 citations
Physical Review Research
Quantum many-body systems
1.69
article

Thermal pure states for systems with antiunitary symmetries and their tensor network representations

Yasushi Yoneta
article en
5 citations

Abstract

Thermal pure state algorithms, which employ pure quantum states representing thermal equilibrium states instead of statistical ensembles, are useful both for numerical simulations and for theoretical analysis of thermal states. However, their inherently large entanglement makes it difficult to represent efficiently and limits their use in analyzing large systems. Here we propose a tensor network algorithm for constructing thermal pure states for systems with certain antiunitary symmetries, such as time-reversal or complex-conjugate symmetry. Our method utilizes thermal pure states that, while exhibiting volume-law entanglement, can be mapped to tensor network states through simple transformations. Furthermore, our approach does not rely on random sampling and thus avoids statistical uncertainty. Moreover, we can compute not only thermal expectation values of local observables but also thermodynamic quantities. We demonstrate the validity and utility of our method by applying it to the one-dimensional <a:math xmlns:a="http://www.w3.org/1998/Math/MathML"><a:mrow><a:mi>X</a:mi><a:mi>Y</a:mi></a:mrow></a:math> model and the two-dimensional Ising model on a triangular lattice. Our results suggest a class of variational wave functions for volume-law states that are not limited to thermal equilibrium states. Published by the American Physical Society 2024

Physical Review ResearchVol. 6(4)
Computing Center (RU), RIKEN Center for Advanced Photonics (JP)
RIKEN
Peace, Justice and strong institutions
Openalex Percentile: Top 15%
Quantum many-body systems
1.69
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.