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Related papers: Quantum Algorithms for Ground-State Preparation an…

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The logarithm-determinant is an widely-present operation in many areas of physics and computer science. Derivatives of the logarithm-determinant compute physically relevant quantities in statistical physics models, quantum field theories,…

Quantum Physics · Physics 2025-09-23 Thomas E. Baker , Jaimie A. Greasley

In the framework of the hybrid quantum-classical variational cluster approach (VCA) to strongly correlated electron systems one of the goals of a quantum subroutine is to find single-particle correlation functions of lattice fermions in…

Quantum Physics · Physics 2025-06-26 Gino Bishop , Dmitry Bagrets , Frank K. Wilhelm

Computing vacuum states of lattice gauge theories (LGTs) containing fermionic degrees of freedom can present significant challenges for classical computation using Monte-Carlo methods. Quantum algorithms may offer a pathway towards more…

Quantum Physics · Physics 2025-03-26 Lewis W. Anderson , Martin Kiffner , Tom O'Leary , Jason Crain , Dieter Jaksch

Many-body ground state preparation is an important subroutine used in the simulation of physical systems. In this paper, we introduce a flexible and efficient framework for obtaining a state preparation circuit for a large class of…

Quantum Physics · Physics 2024-11-05 Hyun-Soo Kim , Isaac H. Kim , Daniel Ranard

We propose a state-averaged orbital optimization scheme for improving the accuracy of excited states of the electronic structure Hamiltonian for use on near-term quantum computers. Instead of parameterizing the orbital rotation operator in…

Chemical Physics · Physics 2024-04-09 Joel Bierman , Yingzhou Li , Jianfeng Lu

Solving the Anderson impurity model typically involves a two-step process, where one first calculates the ground state of the Hamiltonian, and then computes its dynamical properties to obtain the Green's function. Here we propose a hybrid…

One of the main applications of future quantum computers will be the simulation of quantum models. While the evolution of a quantum state under a Hamiltonian is straightforward (if sometimes expensive), using quantum computers to determine…

Quantum systems have historically been formidable to simulate using classical computational methods, particularly as the system size grows. In recent years, advancements in quantum computing technology have offered new opportunities for…

Quantum Physics · Physics 2023-09-06 Jinao Wang , Rimika Jaiswal

Quantum computers are a highly promising tool for efficiently simulating quantum many-body systems. The preparation of their eigenstates is of particular interest and can be addressed, e.g., by quantum phase estimation algorithms. The…

Quantum Physics · Physics 2025-08-28 Xiaoyu Liu , Benjamin F. Schiffer , Jordi Tura

Drawing inspiration from the Lyapunov control technique for quantum systems, feedback-based quantum algorithms have been proposed for calculating the ground states of Hamiltonians. In this work, we consider extending these algorithms to…

Quantum Physics · Physics 2024-07-23 Salahuddin Abdul Rahman , Özkan Karabacak , Rafal Wisniewski

The task of estimating the ground state of Hamiltonians is an important problem in physics with numerous applications ranging from solid-state physics to combinatorial optimization. We provide a hybrid quantum-classical algorithm for…

Quantum Physics · Physics 2022-02-28 Kishor Bharti , Tobias Haug

In order to achieve fault-tolerant quantum computation, we need to repeat the following sequence of four steps: First, perform 1 or 2 qubit quantum gates (in parallel if possible). Second, do a syndrome measurement on a subset of the…

Quantum Physics · Physics 2024-12-11 Harry Buhrman , Marten Folkertsma , Bruno Loff , Niels M. P. Neumann

Quantum algorithms for ground-state energy estimation of chemical systems require a high-quality initial state. However, initial state preparation is commonly either neglected entirely, or assumed to be solved by a simple product state like…

Many-body Green's functions encode all the properties and excitations of interacting electrons. While these are challenging to be evaluated accurately on a classical computer, recent efforts have been directed towards finding quantum…

We present a recurrent neural network-based approach for ground state preparation utilizing mid-circuit measurement and feedback. Unlike previous methods that use machine learning solely as an optimizer, our approach dynamically adjusts…

Quantum Physics · Physics 2025-02-26 Chuanxin Wang , Yi-Zhuang You

We propose a variational approach for preparing entangled quantum states on quantum computers. The methodology involves training a unitary operation to match with a target unitary using the Fubini-Study distance as a cost function. We…

Quantum Physics · Physics 2023-07-03 Vu Tuan Hai , Nguyen Tan Viet , Le Bin Ho

We present a method that outputs a sequence of simple unitary operations to prepare a given quantum state that is a generalized coherent state. Our method takes as inputs the expectation values of some relevant observables on the state to…

Quantum Physics · Physics 2020-01-08 Rolando D. Somma

A common requirement of quantum simulations and algorithms is the preparation of complex states through sequences of 2-qubit gates. For a generic quantum state, the number of gates grows exponentially with the number of qubits, becoming…

Quantum Physics · Physics 2024-07-08 Matan Ben Dov , David Shnaiderov , Adi Makmal , Emanuele G. Dalla Torre

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

Calculating the energy spectrum of a quantum system is an important task, for example to analyse reaction rates in drug discovery and catalysis. There has been significant progress in developing algorithms to calculate the ground state…

Quantum Physics · Physics 2019-06-12 Suguru Endo , Tyson Jones , Sam McArdle , Xiao Yuan , Simon Benjamin