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Computing the excited states of a given Hamiltonian is computationally hard for large systems, but methods that do so using quantum computers scale tractably. This problem is equivalent to the PCA problem where we are interested in…

Quantum Physics · Physics 2025-03-19 David Quiroga , Jason Han , Anastasios Kyrillidis

Numerically solving partial differential equations is a ubiquitous computational task with broad applications in many fields of science. Quantum computers can potentially provide high-degree polynomial speed-ups for solving PDEs, however…

Quantum Physics · Physics 2026-01-09 Gumaro Rendon , Stepan Smid

Current quantum computers are limited in the number of qubits and coherence time, constraining the algorithms executable with sufficient fidelity. The variational quantum eigensolver (VQE) is an algorithm to find an approximate ground state…

Quantum Physics · Physics 2023-01-24 Luca Erhart , Kosuke Mitarai , Wataru Mizukami , Keisuke Fujii

Automatic differentiation frameworks are optimized for exactly one thing: computing the average mini-batch gradient. Yet, other quantities such as the variance of the mini-batch gradients or many approximations to the Hessian can, in…

Machine Learning · Computer Science 2020-02-18 Felix Dangel , Frederik Kunstner , Philipp Hennig

While most work on the quantum simulation of chemistry has focused on computing energy surfaces, a similarly important application requiring subtly different algorithms is the computation of energy derivatives. Almost all molecular…

We investigate the $t$-$W$ scheme for the anti-ferromagnetic XXX spin chain under both periodic and open boundary conditions. We propose a new parametrization of the eigenvalues of transfer matrix. Based on it, we obtain the exact solution…

Mathematical Physics · Physics 2023-12-08 Yi Qiao , Junpeng Cao , Wen-Li Yang , Kangjie Shi , Yupeng Wang

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

This thesis presents an efficient quantum algorithm and explicit circuits for generating eigenstates of arbitrary SU(2) and SU(3) representations. These include a wide variety of highly entangled states. The algorithm uses Schur transform…

Quantum Physics · Physics 2013-09-12 Satya Sainadh U

The characterization of observables, expressed via Hermitian operators, is a crucial task in quantum mechanics. For this reason, an eigensolver is a fundamental algorithm for any quantum technology. In this work, we implement a…

Quantum Physics · Physics 2021-06-15 C. -Y. Pan , M. Hao , N. Barraza , E. Solano , F. Albarran-Arriagada

We numerically benchmark 30 optimisers on 372 instances of the variational quantum eigensolver for solving the Fermi-Hubbard system with the Hamiltonian variational ansatz. We rank the optimisers with respect to metrics such as final energy…

Quantum Physics · Physics 2025-01-22 Benjamin D. M. Jones , Lana Mineh , Ashley Montanaro

We adapt the robust phase estimation algorithm to the evaluation of energy differences between two eigenstates using a quantum computer. This approach does not require controlled unitaries between auxiliary and system registers or even a…

Quantum Physics · Physics 2021-06-02 A. E. Russo , K. M. Rudinger , B. C. A. Morrison , A. D. Baczewski

We study the performance of the D-Wave 2X quantum annealing machine on systems with well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass benchmark instance represents a difficult task, the gold standard…

Quantum Physics · Physics 2017-02-21 Salvatore Mandrà , Zheng Zhu , Helmut G. Katzgraber

In this work, we consider a fundamental task in quantum many-body physics - finding and learning ground states of quantum Hamiltonians and their properties. Recent works have studied the task of predicting the ground state expectation value…

Quantum Physics · Physics 2025-01-16 Štěpán Šmíd , Roberto Bondesan

Differential equations are ubiquitous in models of physical phenomena. Applications like steady-state analysis of heat flow and deflection in elastic bars often admit to a second order differential equation. In this paper, we discuss the…

Quantum Physics · Physics 2019-06-12 Siddhartha Srivastava , Veera Sundararaghavan

Automatic differentiation plays a prominent role in scientific computing and in modern machine learning, often in the context of powerful programming systems. The relation of the various embodiments of automatic differentiation to the…

Programming Languages · Computer Science 2020-02-04 Martin Abadi , Gordon D. Plotkin

Adiabatic quantum computing enables the preparation of many-body ground states. This is key for applications in chemistry, materials science, and beyond. Realisation poses major experimental challenges: Direct analog implementation requires…

Linear dissipative differential equation is a fundamental model for a large number of physical systems, such as quantum dynamics with non-Hermitian Hamiltonian, open quantum system dynamics, diffusion process and damped system. In this…

Quantum Physics · Physics 2025-08-22 Gengzhi Yang , Akwum Onwunta , Dong An

Quantum supremacy is the ability of quantum processors to outperform classical computers at certain tasks. In digital random quantum circuit approaches for supremacy, the output distribution produced is described by the Porter-Thomas (PT)…

We study the eigenlevel spectrum of quantum adiabatic algorithm for 3-satisfiability problem, focusing on single-solution instances. The properties of the ground state and the associated gap, crucial for determining the running time of the…

Quantum Physics · Physics 2009-11-11 Marko Znidaric

The theory of open quantum systems lays the foundations for a substantial part of modern research in quantum science and engineering. Rooted in the dimensionality of their extended Hilbert spaces, the high computational complexity of…

Strongly Correlated Electrons · Physics 2024-06-10 Di Luo , Zhuo Chen , Juan Carrasquilla , Bryan K. Clark
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