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A variational method for computing conformational properties of molecules with Lennard-Jones potentials for the monomer-monomer interactions is presented. The approach is tailored to deal with angular degrees of freedom, {\it rotors}, and…

chem-ph · Physics 2016-08-31 Carsten Peterson , Ola Sommelius , Bo Söderberg

The adaptive variational quantum dynamics simulation (AVQDS) method performs real-time evolution of quantum states using automatically generated parameterized quantum circuits that often contain substantially fewer gates than Trotter…

Quantum Physics · Physics 2025-06-23 Feng Zhang , Cai-Zhuang Wang , Thomas Iadecola , Peter P. Orth , Yong-Xin Yao

Variational quantum algorithms are proposed to solve relevant computational problems on near term quantum devices. Popular versions are variational quantum eigensolvers and quantum ap- proximate optimization algorithms that solve ground…

Quantum Physics · Physics 2022-04-15 Lennart Bittel , Martin Kliesch

Determining quantum excited states is crucial across physics and chemistry but presents significant challenges for variational methods, primarily due to the need to enforce orthogonality to lower-energy states, often requiring…

Quantum Physics · Physics 2025-05-01 Shi-Xin Zhang , Lei Wang

Variational methods are highly valuable computational tools for solving high-dimensional quantum systems. In this paper, we explore the effectiveness of three variational methods: the density matrix renormalization group (DMRG), Boltzmann…

Quantum Physics · Physics 2024-04-18 Daming Li

Variational Quantum Algorithms (VQAs) have emerged as promising methods for tackling complex problems on near-term quantum devices. Among these algorithms, the Variational Quantum Linear Solver (VQLS) addresses linear systems of the form…

Quantum Physics · Physics 2024-09-11 Gloria Turati , Alessia Marruzzo , Maurizio Ferrari Dacrema , Paolo Cremonesi

We compare the performance of different methodologies for finding the ground state of the molecule BeH2. We implement adaptive, tetris-adaptive variational quantum eigensolver (VQE), and entanglement forging to reduce computational resource…

Quantum Physics · Physics 2024-07-24 Tushar Pandey , Jason Saroni , Abdullah Kazi , Kartik Sharma

This work introduces a novel approach to quantum simulation by leveraging continuous-variable systems within a photonic hardware-inspired framework. The primary focus is on simulating static properties of the ground state of Hamiltonians…

The variational quantum eigensolver (VQE) is one of the most promising algorithms for low-lying eigenstates calculation on Noisy Intermediate-Scale Quantum (NISQ) computers. Specifically, VQE has achieved great success for ground state…

Numerical Analysis · Mathematics 2025-12-19 Hengzhun Chen , Yingzhou Li , Bichen Lu , Jianfeng Lu

The Variational Method is applied within the context of Supersymmetric Quantum Mechanics to provide information about the energy and eigenfunction of the lowest levels of a Hamiltonian. The approach is illustrated by the case of the Morse…

High Energy Physics - Theory · Physics 2009-10-31 Elso Drigo Filho , Regina Maria Ricotta

Variational quantum algorithms on bosonic quantum processors are an emerging paradigm for quantum chemistry calculations, exploiting the natural alignment between molecular structure and harmonic oscillator-based hardware. We introduce the…

Quantum Physics · Physics 2026-04-21 Marlon F. Jost , Sijia S. Dong

Quantum chemistry applications on quantum computers currently rely heavily on the variational quantum eigensolver (VQE) algorithm. This hybrid quantum-classical algorithm aims at finding ground state solutions of molecular systems based on…

To compute approximate solutions for combinatorial optimization problems, we describe variational methods based on the product state (PS) and matrix product state (MPS) ansatzes. We perform variational energy minimization with respect to a…

Quantum Physics · Physics 2025-12-24 Guillermo Preisser , Conor Mc Keever , Michael Lubasch

Variational quantum eigensolvers (VQEs) combine classical optimization with efficient cost function evaluations on quantum computers. We propose a new approach to VQEs using the principles of measurement-based quantum computation. This…

Extracting eigenvalues and eigenvectors of exponentially large matrices will be an important application of near-term quantum computers. The Variational Quantum Eigensolver (VQE) treats the case when the matrix is a Hamiltonian. Here, we…

Quantum Physics · Physics 2022-09-28 M. Cerezo , Kunal Sharma , Andrew Arrasmith , Patrick J. Coles

We present and analyze large-scale simulation results of a hybrid quantum-classical variational method to calculate the ground state energy of the anti-ferromagnetic Heisenberg model. Using a massively parallel universal quantum computer…

Quantum Physics · Physics 2022-06-20 Manpreet Singh Jattana , Fengping Jin , Hans De Raedt , Kristel Michielsen

It is well-known that the {\it Gross-Pitaevskii} variational formula describes the the ground state energy of of $N$-indistinguishable trapped particles (bosons) in a dilute state in the large system size $N\to\infty$. The goal of the…

Probability · Mathematics 2019-11-22 Stefan Adams , Chiranjib Mukherjee

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

One of the central difficulties in the quantization of the gravitational interactions is that they are described by a set of constraints. The standard strategy for dealing with the problem is the Dirac quantization procedure, which leads to…

General Relativity and Quantum Cosmology · Physics 2022-06-15 Grzegorz Czelusta , Jakub Mielczarek

Different hybrid quantum-classical algorithms have recently been developed as a near-term way to solve linear systems of equations on quantum devices. However, the focus has so far been mostly on the methods, rather than the problems that…

Computational Engineering, Finance, and Science · Computer Science 2024-12-09 Giorgio Tosti Balducci , Boyang Chen , Matthias Möller , Roeland De Breuker