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Variational quantum eigensolver~(VQE) typically optimizes variational parameters in a quantum circuit to prepare eigenstates for a quantum system. Its applications to many problems may involve a group of Hamiltonians, e.g., Hamiltonian of a…

Quantum Physics · Physics 2021-01-19 Zhan-Hao Yuan , Tao Yin , Dan-Bo Zhang

For quantum systems with competing potentials, the conventional perturbation theory often yields an asymptotic series and the subsequent numerical outcome becomes uncertain. To tackle such kind of problems, we develop a general solution…

Quantum Physics · Physics 2015-06-05 H. Mineo , Sheng D. Chao

Solving partial differential equations for extremely large-scale systems within a feasible computation time serves in accelerating engineering developments. Quantum computing algorithms, particularly the Hamiltonian simulations, present a…

Quantum Physics · Physics 2024-09-10 Yuki Sato , Ruho Kondo , Ikko Hamamura , Tamiya Onodera , Naoki Yamamoto

Effective Hamiltonian methods are utilized to model the two-qubit cross-resonance gate for both the ideal two-qubit case and when higher levels are included. Analytic expressions are obtained in the qubit case and the higher-level model is…

Quantum Physics · Physics 2020-05-13 Easwar Magesan , Jay M. Gambetta

Some functorial and topological properties of vertical cohomologies and their application to completely integrable Hamiltonian systems are studied.

Symplectic Geometry · Mathematics 2007-05-23 Z. Tevdoradze

We present a numerical method to simulate the time evolution, according to a Hamiltonian made of local interactions, of quantum spin chains and systems alike. The efficiency of the scheme depends on the amount of the entanglement involved…

Quantum Physics · Physics 2009-11-10 G. Vidal

With the fast development of quantum technology, the sizes of both digital and analog quantum systems increase drastically. In order to have better control and understanding of the quantum hardware, an important task is to characterize the…

Quantum Physics · Physics 2023-07-05 Wenjun Yu , Jinzhao Sun , Zeyao Han , Xiao Yuan

As the size of quantum devices continues to grow, the development of scalable methods to characterise and diagnose noise is becoming an increasingly important problem. Recent methods have shown how to efficiently estimate Hamiltonians in…

Quantum Physics · Physics 2019-12-18 Tim J. Evans , Robin Harper , Steven T. Flammia

For a class of Hamiltonian systems naturally arising in the modern theory of separation of variables, we establish their maximal superintegrability by explicitly constructing the additional integrals of motion.

Exactly Solvable and Integrable Systems · Physics 2009-11-10 M. Blaszak , A. Sergyeyev

The support vector machines (SVM) algorithm is a popular classification technique in data mining and machine learning. In this paper, we propose a distributed SVM algorithm and demonstrate its use in a number of applications. The algorithm…

Machine Learning · Computer Science 2019-05-02 Taiping He , Tao Wang , Ralph Abbey , Joshua Griffin

A quantum thermodynamic system is described by a Hamiltonian and a list of conserved, non-commuting charges, and a fundamental goal is to determine the minimum energy of the system subject to constraints on the charges. Recently, [Liu et…

In this report, we explore the use of a quantum optimization algorithm for obtaining low energy conformations of protein models. We discuss mappings between protein models and optimization variables, which are in turn mapped to a system of…

The utility of effective model spaces in quantum simulations of non-relativistic quantum many-body systems is explored in the context of the Lipkin-Meshkov-Glick model of interacting fermions. We introduce an iterative…

Quantum Physics · Physics 2023-08-25 Caroline E. P. Robin , Martin J. Savage

We discuss how dynamical fermion computations may be made yet cheaper by using symplectic integrators that conserve energy much more accurately without decreasing the integration step size. We first explain why symplectic integrators…

High Energy Physics - Lattice · Physics 2008-11-26 M. A. Clark , A. D. Kennedy

We propose a finite element discretisation approach for the incompressible Euler equations which mimics their geometric structure and their variational derivation. In particular, we derive a finite element method that arises from a…

Numerical Analysis · Mathematics 2017-10-17 Andrea Natale , Colin J. Cotter

We propose the segmented iHMM (siHMM), a hierarchical infinite hidden Markov model (iHMM) that supports a simple, efficient inference scheme. The siHMM is well suited to segmentation problems, where the goal is to identify points at which a…

Machine Learning · Statistics 2016-02-23 Ardavan Saeedi , Matthew Hoffman , Matthew Johnson , Ryan Adams

This paper introduces equivariant hamiltonian flows, a method for learning expressive densities that are invariant with respect to a known Lie-algebra of local symmetry transformations while providing an equivariant representation of the…

Machine Learning · Statistics 2019-10-01 Danilo Jimenez Rezende , Sébastien Racanière , Irina Higgins , Peter Toth

A new exponentially fitted version of the Discrete Variational Derivative method for the efficient solution of oscillatory complex Hamiltonian Partial Differential Equations is proposed. When applied to the nonlinear Schroedinger equation,…

Numerical Analysis · Mathematics 2022-02-02 Dajana Conte , Gianluca Frasca-Caccia

Constrained Hamiltonian description of the classical limit is utilized in order to derive consistent dynamical equations for hybrid quantum-classical systems. Starting with a compound quantum system in the Hamiltonian formulation conditions…

Quantum Physics · Physics 2012-06-08 M. Radonjic , S. Prvanovic , N. Buric

We design a novel, exactly energy-conserving implicit non-symplectic integration method for an eight-dimensional Hamiltonian system with four degrees of freedom. In our algorithm, each partial derivative of the Hamiltonian with respect to…

General Relativity and Quantum Cosmology · Physics 2019-12-30 Shiyang Hu , Xin Wu , Guoqing Huang , Enwei Liang