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We design a quantum algorithm for ground state preparation in the early fault tolerant regime. As a Monte Carlo-style quantum algorithm, our method features a Lindbladian where the target state is stationary. The construction of this…

Quantum Physics · Physics 2024-08-27 Zhiyan Ding , Chi-Fang Chen , Lin Lin

Preparing the ground states of a many-body system is essential for evaluating physical quantities and determining the properties of materials. This work provides a quantum ground state preparation scheme with shallow variational warm-start…

Quantum Physics · Physics 2023-03-21 Youle Wang , Chenghong Zhu , Mingrui Jing , Xin Wang

Electronic excited states are central to a vast array of physical and chemical phenomena, yet accurate and efficient methods for preparing them on quantum devices remain challenging and comparatively underexplored. We introduce a general…

Quantum Physics · Physics 2026-02-02 Hao-En Li , Lin Lin

The assumption that quantum systems relax to a stationary state in the long-time limit underpins statistical physics and much of our intuitive understanding of scientific phenomena. For isolated systems this follows from the eigenstate…

Quantum Physics · Physics 2019-04-16 Berislav Buca , Joseph Tindall , Dieter Jaksch

We utilize neural network quantum states (NQS) to investigate the ground state properties of the Heisenberg model on a Shastry-Sutherland lattice using the variational Monte Carlo method. We show that already relatively simple NQSs can be…

Disordered Systems and Neural Networks · Physics 2024-02-07 Matěj Mezera , Jana Menšíková , Pavel Baláž , Martin Žonda

Critical ground states of quantum many-body systems have emerged as vital resources for quantum-enhanced sensing. Traditional methods to prepare these states often rely on adiabatic evolution, which may diminish the quantum sensing…

Quantum Physics · Physics 2025-03-05 Hang Xu , Tailong Xiao , Jingzheng Huang , Ming He , Jianping Fan , Guihua Zeng

Quantum Mechanical ground states of many-body systems can be important resources for various investigations: for quantum sensing, as the initial state for nonequilibrium quantum dynamics following quenches, and the simulation of quantum…

Quantum Physics · Physics 2025-11-18 Prashasti Tiwari , Dylan Lewis , Sougato Bose

Preparing the ground state of a local Hamiltonian is a crucial problem in understanding quantum many-body systems, with applications in a variety of physics fields and connections to combinatorial optimization. While various quantum…

Quantum Physics · Physics 2025-02-06 Benjamin F. Schiffer , Jordi Tura

State preparation is of fundamental importance in quantum physics, which can be realized by constructing the quantum circuit as a unitary that transforms the initial state to the target, or implementing a quantum control protocol to evolve…

Quantum Physics · Physics 2021-11-23 Ying Lu , Yue-Min Li , Peng-Fei Zhou , Shi-Ju Ran

The ground state of the bilayer Kitaev model with the Heisenberg-type interlayer exchange interaction is investigated by means of the exact diagonalization. Calculating the ground-state energy, local quantity defined on each plaquette, and…

Strongly Correlated Electrons · Physics 2019-05-24 Hiroyuki Tomishige , Joji Nasu , Akihisa Koga

Controlled quantum mechanical devices provide a means of simulating more complex quantum systems exponentially faster than classical computers. Such "quantum simulators" rely heavily upon being able to prepare the ground state of…

Quantum Physics · Physics 2012-08-01 Dvir Kafri , Jacob M. Taylor

The preparation of the ground state of a Hamiltonian $H$ with a large spectral radius has applications in many areas such as electronic structure theory and quantum field theory. Given an initial state with a constant overlap with the…

Quantum Physics · Physics 2024-06-05 Yulong Dong , Lin Lin

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by…

Quantum Physics · Physics 2023-08-30 Clemens Giuliani , Filippo Vicentini , Riccardo Rossi , Giuseppe Carleo

We derive a microscopic model for dissipative dynamics in a system of mutually interacting qubits coupled to a thermal bath that generalises the dissipative model of Landau-Lifschitz-Gilbert to the case of anisotropic bath couplings. We…

Mesoscale and Nanoscale Physics · Physics 2016-12-14 Philip J D Crowley , A G Green

Quantum ground-state problems are computationally hard problems; for general many-body Hamiltonians, there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating…

The ground-state and low-energy excitations of quantum Hall systems are studied by the density matrix renormalization group (DMRG) method. From the ground-state pair correlation functions and low-energy excitions, the ground-state phase…

Strongly Correlated Electrons · Physics 2009-06-08 Naokazu Shibata

Quantum circuit partitioning (QCP) is a hybrid quantum-classical approach that aims to simulate large quantum systems on smaller quantum computers. A quantum computation is divided into smaller subsystems and results of measurements on…

Quantum Physics · Physics 2024-09-20 Stian Bilek

We present a technique to coarse-grain quantum states in a finite-dimensional Hilbert space. Our method is distinguished from other approaches by not relying on structures such as a preferred factorization of Hilbert space or a preferred…

Quantum Physics · Physics 2018-03-16 Ashmeet Singh , Sean M. Carroll

We describe a protocol for preparing the ground state of a Hamiltonian $H$ on a quantum computer. This is done by designing a quantum algorithm that implements the imaginary time evolution operator: $e^{-\tau H}$. The method relies on the…

Quantum Physics · Physics 2023-06-28 Charles Marteau

Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations --- alongside impressive results using machine learning techniques for computation --- hybridizing…

Quantum Physics · Physics 2018-10-24 Rongxin Xia , Sabre Kais