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Related papers: Near-optimal ground state preparation

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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

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

We describe an algorithm that computes the ground state energy and correlation functions for 2-local Hamiltonians in which interactions between qubits are weak compared to single-qubit terms. The running time of the algorithm is polynomial…

Quantum Physics · Physics 2009-11-13 Sergey Bravyi , David DiVincenzo , Daniel Loss

Quantum Phase Estimation (QPE), the quantum algorithm for estimating eigenvalues of a given Hermitian matrix and preparing its eigenvectors, is considered the most promising approach to finding the ground states and their energies of…

Several approximations are tested by calculating the ground-state energy and the energy of the first excited $0^{+}$ state using an exactly solvable model with two symmetric levels interacting via a pairing force. They are the BCS…

Nuclear Theory · Physics 2009-09-29 Nguyen Dinh Dang

We propose quantum-selected configuration interaction (QSCI), a class of hybrid quantum-classical algorithms for calculating the ground- and excited-state energies of many-electron Hamiltonians on noisy quantum devices. Suppose that an…

Quantum Physics · Physics 2023-02-23 Keita Kanno , Masaya Kohda , Ryosuke Imai , Sho Koh , Kosuke Mitarai , Wataru Mizukami , Yuya O. Nakagawa

We describe an efficient approximation algorithm for evaluating the ground-state energy of the classical Ising Hamiltonian with linear terms on an arbitrary planar graph. The running time of the algorithm grows linearly with the number of…

Quantum Physics · Physics 2009-09-16 Nikhil Bansal , Sergey Bravyi , Barbara M. Terhal

We develop an adaptive method for quantum state preparation that utilizes randomness as an essential component and that does not require classical optimization. Instead, a cost function is minimized to prepare a desired quantum state…

Quantum Physics · Physics 2023-10-10 Alicia B. Magann , Sophia E. Economou , Christian Arenz

Estimating observable expectation values in eigenstates of quantum systems has a broad range of applications and is an area where early fault-tolerant quantum computers may provide practical quantum advantage. We develop a hybrid…

Quantum Physics · Physics 2026-03-03 Bence Bakó , Tenzan Araki , Bálint Koczor

We describe a quantum algorithm to prepare an arbitrary pure state of a register of a quantum computer with fidelity arbitrarily close to 1. Our algorithm is based on Grover's quantum search algorithm. For sequences of states with suitably…

Quantum Physics · Physics 2007-05-23 Andrei N. Soklakov , Ruediger Schack

Generating large, non-trivial quantum chemistry test problems with known ground-state solutions remains a core challenge for benchmarking electronic structure methods. Inspired by planted-solution techniques from combinatorial optimization,…

Quantum Physics · Physics 2025-09-23 Linjun Wang , Joshua T. Cantin , Smik Patel , Ignacio Loaiza , Rick Huang , Artur F. Izmaylov

We investigate the possibility to calculate the ground-state energy of the atomic systems on a quantum computer. For this purpose we evaluate the lowest binding energy of the moscovium atom with the use of the iterative phase estimation and…

Quantum Physics · Physics 2023-09-26 V. A. Zaytsev , M. E. Groshev , I. A. Maltsev , A. V. Durova , V. M. Shabaev

The performance of quantum algorithms for ground-state energy estimation is directly impacted by the quality of the initial state, where quality is traditionally defined in terms of the overlap of the input state with the target state. An…

Hamiltonian simulation is a domain where quantum computers have the potential to outperform their classical counterparts. One of the main challenges of such quantum algorithms is increasing the system size, which is necessary to achieve…

Quantum Physics · Physics 2025-02-07 Erenay Karacan , Yanbin Chen , Christian B. Mendl

A fundamental problem in quantum many-body physics is that of finding ground states of local Hamiltonians. A number of recent works gave provably efficient machine learning (ML) algorithms for learning ground states. Specifically, [Huang et…

The variational approach is a cornerstone of computational physics, considering both conventional and quantum computing computational platforms. The variational quantum eigensolver (VQE) algorithm aims to prepare the ground state of a…

Quantum Physics · Physics 2022-12-16 Nikita Astrakhantsev , Guglielmo Mazzola , Ivano Tavernelli , Giuseppe Carleo

We use matrix product techniques to investigate the performance of two algorithms for obtaining the ground state of a quantum many-body Hamiltonian $H = H_A + H_B$ in infinite systems. The first algorithm is a generalization of the quantum…

Strongly Correlated Electrons · Physics 2022-11-30 Ruoshui Wang , Timothy H. Hsieh , Guifre Vidal

We develop a phase estimation method with a distinct feature: its maximal runtime (which determines the circuit depth) is $\delta/\epsilon$, where $\epsilon$ is the target precision, and the preconstant $\delta$ can be arbitrarily close to…

Quantum Physics · Physics 2024-03-12 Zhiyan Ding , Lin Lin

Accurately determining ground-state properties of quantum many-body systems remains one of the major challenges of quantum simulation. In this work, we present a protocol for estimating the ground-state energy using only global time…

A variety of quantum computing algorithms exist for the preparation of approximate Hamiltonian ground states. A natural and important question is how these ground-state approximations can be further improved using adiabatic state…

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