English
Related papers

Related papers: Efficient impurity-bath trial states from superpos…

200 papers

A variational approach based on the multi-coherent-state ansatz with asymmetric parameters is employed to study the ground state of the spin-boson model. Without any artificial approximations except for the finite number of the coherent…

Quantum Gases · Physics 2014-12-22 Liwei Duan , Shu He , Qing-Hu Chen

We consider the task of approximating the ground state energy of two-local quantum Hamiltonians on bounded-degree graphs. Most existing algorithms optimize the energy over the set of product states. Here we describe a family of shallow…

Quantum Physics · Physics 2022-01-05 Anurag Anshu , David Gosset , Karen J. Morenz Korol , Mehdi Soleimanifar

Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct with high fidelity,…

Quantum Physics · Physics 2022-12-21 Rishabh Gupta , Manas Sajjan , Raphael D. Levine , Sabre Kais

Besides perturbation theory (which clearly requires the knowledge of the exact unperturbed solution), variational techniques represent the main tool for any investigation of the eigenvalue problem of some semibounded operator H in quantum…

High Energy Physics - Phenomenology · Physics 2009-10-31 Wolfgang Lucha , Franz F. Schoberl

The ground state correlations induced by a general pairing Hamiltonian in a finite system of like fermions are described in terms of four-body correlated structures (quartets). These are real superpositions of products of two pairs of…

Nuclear Theory · Physics 2015-06-15 M. Sambataro , N. Sandulescu

We propose a variational framework for solving ground-state problems of open quantum systems governed by quantum stochastic differential equations (QSDEs). This formulation naturally accommodates bosonic operators, as commonly encountered…

Quantum Physics · Physics 2025-12-17 Yunyan Lee , Ian R. Petersen , Daoyi Dong

We propose an algorithm to obtain the ground-state energy of a many-electron system using the variational wave function of a linear combination of antisymmetrized geminal powers. We optimized this algorithm to obtain the energy and the…

Chemical Physics · Physics 2019-06-07 Wataru Uemura , Takahito Nakajima

An important aspect of quantum simulation is the preparation of physically interesting states on a quantum computer, and this task can often be costly or challenging to implement. A digital, ``site-by-site'' scheme of state preparation was…

Quantum Physics · Physics 2022-07-06 Troy Sewell , Aniruddha Bapat , Stephen Jordan

Variational algorithms for strongly correlated chemical and materials systems are one of the most promising applications of near-term quantum computers. We present an extension to the variational quantum eigensolver that approximates the…

Quantum Physics · Physics 2020-08-26 William J. Huggins , Joonho Lee , Unpil Baek , Bryan O'Gorman , K. Birgitta Whaley

Understanding the structure of quantum correlations in a many-body system is key to its computational treatment. For fermionic systems, correlations can be defined as deviations from Slater determinant states. The link between fermionic…

Quantum Physics · Physics 2025-04-16 Mykola Semenyakin , Yevheniia Cheipesh , Yaroslav Herasymenko

Detecting when a quantum state leaves the efficiently simulable fermionic Gaussian regime is a central task for benchmarking quantum devices and certifying fermionic magic resources. We develop practical tests and witnesses based on…

Quantum Physics · Physics 2026-05-27 Tobias Haug , Xhek Turkeshi , Piotr Sierant

We study the ground states of lattice Hamiltonians that are invariant under permutations, in the limit where the number of lattice sites, N -> \infty. For spin systems, these are product states, a fact that follows directly from the quantum…

Quantum Physics · Physics 2013-09-24 Christina V. Kraus , Maciej Lewenstein , J. Ignacio Cirac

Variational mean field approximations tend to struggle with contemporary overparametrized deep neural networks. Where a Bayesian treatment is usually associated with high-quality predictions and uncertainties, the practical reality has been…

We derive families of optimal and near-optimal probe states for quantum estimation of the coupling constants of a general two-mode number-conserving bosonic Hamiltonian describing one-body and two-body dynamics. We find that the optimal…

Quantum Physics · Physics 2016-11-23 T. J. Volkoff

We develop a new perturbative method for studying any steady states of quantum impurities, in or out of equilibrium. We show that steady-state averages are completely fixed by basic properties of the steady-state (Hershfield's) density…

Strongly Correlated Electrons · Physics 2009-11-13 Benjamin Doyon

Preparing the ground state of a given Hamiltonian and estimating its ground energy are important but computationally hard tasks. However, given some additional information, these problems can be solved efficiently on a quantum computer. We…

Quantum Physics · Physics 2020-12-16 Lin Lin , Yu Tong

We study theoretically interspecies Cooper pairing in a fermionic system with SU(2)xSU(6) sym- metry. We show that, with suitable unitary transformations, the order parameter for the ground state can be reduced to only two non-vanishing…

Quantum Gases · Physics 2015-05-27 S. -K. Yip

We consider the optimization problem (ground energy search) for fermionic Hamiltonians with classical interactions. This QMA-hard problem is motivated by the Coulomb electron-electron interaction being diagonal in the position basis, a…

Quantum Physics · Physics 2026-02-24 Maarten Stroeks , Barbara M. Terhal , Yaroslav Herasymenko

Hybrid quantum-classical embedding methods for correlated materials simulations provide a path towards potential quantum advantage. However, the required quantum resources arising from the multi-band nature of $d$ and $f$ electron materials…

Quantum Physics · Physics 2023-01-09 Anirban Mukherjee , Noah F. Berthusen , João C. Getelina , Peter P. Orth , Yong-Xin Yao

This paper considers the problem of computing Bayesian estimates of both states and model parameters for nonlinear state-space models. Generally, this problem does not have a tractable solution and approximations must be utilised. In this…

Machine Learning · Statistics 2020-12-15 Jarrad Courts , Johannes Hendriks , Adrian Wills , Thomas Schön , Brett Ninness