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We develop a rigorous and implementable framework for Gibbs sampling of infinite-dimensional quantum systems governed by unbounded Hamiltonians. Extending dissipative Gibbs samplers beyond finite dimensions raises fundamental obstacles,…

Quantum Physics · Physics 2026-04-02 Simon Becker , Cambyse Rouzé , Robert Salzmann

We present quantum algorithms for solving two problems regarding stochastic processes. The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time almost linear in $\sqrt{N \beta/{\cal Z}}$ and polynomial in…

Quantum Physics · Physics 2017-01-11 Anirban Narayan Chowdhury , Rolando D. Somma

The presence of energy barriers in the state space of a physical system can lead to exponentially slow convergence for sampling algorithms like Markov chain Monte Carlo (MCMC). In the classical setting, replica exchange (or parallel…

Quantum Physics · Physics 2025-12-01 Zherui Chen , Joao Basso , Zhiyan Ding , Lin Lin

In this work, we study the Hamiltonian Decoded Quantum Interferometry (HDQI) for the general Hamiltonians $H=\sum_ic_iP_i$ on an $n$-qubit system, where the coefficients $c_i\in \mathbb{R}$ and $P_i$ are Pauli operators. We show that, given…

Quantum Physics · Physics 2026-01-27 Kaifeng Bu , Weichen Gu , Xiang Li

Gibbs sampling from continuous real-valued functions is a challenging problem of interest in machine learning. Here we leverage quantum Fourier transforms to build a quantum algorithm for this task when the function is periodic. We use the…

Quantum Physics · Physics 2024-07-23 Arsalan Motamedi , Pooya Ronagh

We give an improved algorithm for learning a quantum Hamiltonian given copies of its Gibbs state, that can succeed at any temperature. Specifically, we improve over the work of Bakshi, Liu, Moitra, and Tang [BLMT24], by reducing the sample…

Quantum Physics · Physics 2024-07-08 Shyam Narayanan

We present an algorithm for doing Gibbs sampling on a quantum computer. The algorithm combines phase estimation for a Szegedy operator, and Grover's algorithm. For any $\epsilon>0$, the algorithm will sample a probability distribution in…

Quantum Physics · Physics 2010-01-14 Robert R. Tucci

In this paper, we study a class of multilinear Gibbs measures with Hamiltonian given by a generalized $\mathrm{U}$-statistic and with a general base measure. Expressing the asymptotic free energy as an optimization problem over a space of…

Probability · Mathematics 2026-03-31 Sohom Bhattacharya , Nabarun Deb , Sumit Mukherjee

We present a Gibbs sampling solution to the map-making problem for CMB measurements, building on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps; noise filtering…

Quantum computation can be achieved by preparing an appropriate initial product state of qudits and then letting it evolve under a fixed Hamiltonian. The readout is made by measurement on individual qudits at some later time. This approach…

Quantum Physics · Physics 2015-12-22 Tzu-Chieh Wei , John C. Liang

We propose a framework for the connection between local symmetries of discrete Hamiltonians and the design of compact localized states. Such compact localized states are used for the creation of tunable, local symmetry-induced bound states…

Quantum Physics · Physics 2018-02-09 M. Röntgen , C. V. Morfonios , P. Schmelcher

We derive an explicit Hamiltonian for copying the basis up and down states of a quantum two-state system - a qubit - onto n "copy" qubits initially all prepared in the down state. In terms of spin components, for spin-1/2 particle spin…

Quantum Physics · Physics 2014-11-18 Dima Mozyrsky , Vladimir Privman , Mark Hillery

This paper provides a stabilizing preparation method for quantum Gaussian states by utilizing continuous measurement. The stochastic evolution of the open quantum system is described in terms of the quantum stochastic master equation. We…

Quantum Physics · Physics 2021-09-28 Liying Bao , Bo Qi , Daoyi Dong

The direct compilation of algorithm-specific graph states in measurement-based quantum computation (MBQC) can lead to resource reductions in terms of circuit depth, entangling gates, and even the number of physical qubits. In this work, we…

While quantum simulation is one of the most promising applications of modern quantum devices, accessible simulation times are fundamentally limited by finite coherence times due to omnipresent noise. Based on the ideas of relational…

Quantum Physics · Physics 2025-09-03 Sebastian Gemsheim , Felix Fritzsch

Counterdiabatic (CD) protocols enable fast driving of quantum states by invoking an auxiliary adiabatic gauge potential (AGP) that suppresses transitions to excited states throughout the driving process. Usually, the full spectrum of the…

Strongly Correlated Electrons · Physics 2022-11-09 Q Xie , Kazuhiro Seki , Seiji Yunoki

The preparation of quantum states using short quantum circuits is one of the most promising near-term applications of small quantum computers, especially if the circuit is short enough and the fidelity of gates high enough that it can be…

Quantum Physics · Physics 2015-10-07 D. Wecker , M. B. Hastings , M. Troyer

Given a uniform, frustration-free family of local Lindbladians defined on a quantum lattice spin system in any spatial dimension, we prove a strong exponential convergence in relative entropy of the system to equilibrium under a condition…

Quantum Physics · Physics 2021-06-04 Ángela Capel , Cambyse Rouzé , Daniel Stilck França

If a quantum system interacts with the environment, then the Hamiltonian acquires a correction known as the Lamb-shift term. There are two other corrections to the Hamiltonian, related to the stationary state. Namely, the stationary state…

Quantum Physics · Physics 2025-01-28 Marcin Łobejko , Marek Winczewski , Gerardo Suárez , Robert Alicki , Michał Horodecki

The particle Gibbs sampler is a Markov chain Monte Carlo (MCMC) algorithm to sample from the full posterior distribution of a state-space model. It does so by executing Gibbs sampling steps on an extended target distribution defined on the…

Computation · Statistics 2015-07-29 Nicolas Chopin , Sumeetpal S. Singh
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