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Related papers: Quantum Thermal State Preparation

200 papers

We present an efficient method to prepare states of a many-body system on quantum hardware, first isolating individual quantum numbers and then using time evolution to isolate the energy. Our method in its simplest form requires only one…

Quantum Physics · Physics 2023-10-03 I. Stetcu , A. Baroni , J. Carlson

We provide a quantum protocol to perform topological data analysis (TDA) via the distillation of quantum thermal states. Recent developments of quantum thermal state preparation algorithms reveal their characteristic scaling defined by…

Quantum Physics · Physics 2024-07-15 Stefano Scali , Chukwudubem Umeano , Oleksandr Kyriienko

We present a new approach to study the thermodynamic properties of $d$-dimensional classical systems by reducing the problem to the computation of ground state properties of a $d$-dimensional quantum model. This classical-to-quantum mapping…

Quantum Physics · Physics 2009-11-13 Rolando D. Somma , Cristian D. Batista , Gerardo Ortiz

This is the documentation for generating random samples from the quantum state space in accordance with a specified distribution, associated with this webpage: http://tinyurl.com/QSampling . Ready-made samples (each with at least a million…

We present a cooling algorithm for ground state preparation of fermionic Hamiltonians. Our algorithm makes use of the Hamiltonian simulation of the considered system coupled to an ancillary fridge, which is regularly reset to its known…

Quantum Physics · Physics 2025-02-19 Lucas Marti , Refik Mansuroglu , Michael J. Hartmann

Quantum state preparation is a task to prepare a state with a specific function encoded in the amplitude, which is an essential subroutine in many quantum algorithms. In this paper, we focus on multivariate state preparation, as it is an…

Quantum Physics · Physics 2024-09-12 Hitomi Mori , Kosuke Mitarai , Keisuke Fujii

State preparation is a necessary component of many quantum algorithms. In this work, we combine a method for efficiently representing smooth differentiable probability distributions using matrix product states with recently discovered…

Quantum Physics · Physics 2024-02-19 Jason Iaconis , Sonika Johri , Elton Yechao Zhu

We introduce a classical algorithm to approximate the free energy of local, translation-invariant, one-dimensional quantum systems in the thermodynamic limit of infinite chain size. While the ground state problem (i.e., the free energy at…

Quantum Physics · Physics 2024-07-04 Hamza Fawzi , Omar Fawzi , Samuel O. Scalet

A candidate application for quantum computers is to simulate the low-temperature properties of quantum systems. For this task, there is a well-studied quantum algorithm that performs quantum phase estimation on an initial trial state that…

Quantum Physics · Physics 2024-11-04 Chi-Fang , Chen , Alexander M. Dalzell , Mario Berta , Fernando G. S. L. Brandão , Joel A. Tropp

Quantum cooling, a deterministic process that drives any state to the lowest eigenstate, has been widely used from studying ground state properties of chemistry and condensed matter quantum physics, to general optimization problems.…

Quantum Physics · Physics 2022-06-06 Pei Zeng , Jinzhao Sun , Xiao Yuan

Nonequilibrium dynamics of quantum many-body systems is challenging for classical computing, providing opportunities for demonstrating practical quantum computational advantage with analogue quantum simulators. Owing to the intimate…

The simulation of electronic properties is a pivotal issue in modern electronic structure theory, driving significant efforts over the past decades to develop protocols for computing energy derivatives. In this work, we address this problem…

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…

Quantum Physics · Physics 2026-05-15 Gian Gentinetta , Friederike Metz , William Kirby , Giuseppe Carleo

We introduce a tensor network method for approximating thermal equilibrium states of quantum many-body systems at low temperatures. Whereas the usual approach starts from infinite temperature and evolves the state in imaginary time (toward…

Quantum Physics · Physics 2025-10-23 Denise Cocchiarella , Mari Carmen Bañuls

The combination of quantum many-body and machine learning techniques has recently proved to be a fertile ground for new developments in quantum computing. Several works have shown that it is possible to classically efficiently predict the…

Quantum Physics · Physics 2023-11-14 Emilio Onorati , Cambyse Rouzé , Daniel Stilck França , James D. Watson

Gibbs sampling is fundamental to a wide range of computer algorithms. Such algorithms are set to be replaced by physics based processors$-$be it quantum or stochastic annealing devices$-$which embed problem instances and evolve a physical…

Quantum Physics · Physics 2019-06-27 H. Philathong , V. Akshay , I. Zacharov , J. Biamonte

Thermal equilibrium states of many-body Hamiltonians are essential for probing quantum chaos, finite-temperature phases of matter, and training quantum machine learning models, yet generating large collections of such states across…

Quantum Physics · Physics 2026-03-20 Jiyu Jiang , Mingrui Jing , Jizhe Lai , Xin Wang , Lei Zhang

The Lindblad form guarantees complete positivity of a Markovian quantum master equation (QME). However, its microscopic derivation for a quantum system weakly interacting with a thermal bath requires several approximations, which may result…

Quantum Physics · Physics 2022-11-23 Jae Sung Lee , Joonhyun Yeo

$W$ states are quantum correlated states possessing both bipartite and multipartite entanglement, which makes them useful for several quantum algorithms. We propose a protocol to generate these states by exploiting {\it topological ring…

We present classical and quantum algorithms for approximating partition functions of classical Hamiltonians at a given temperature. Our work has two main contributions: first, we modify the classical algorithm of \v{S}tefankovi\v{c},…