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Similarity and metric learning provides a principled approach to construct a task-specific similarity from weakly supervised data. However, these methods are subject to the curse of dimensionality: as the number of features grows large,…

Machine Learning · Statistics 2019-09-10 Kuan Liu , Aurélien Bellet

In the case of multi-parameter full-waveform inversion, the computation of the additional Hessian terms that contain derivatives with respect to more than one type of parameter is necessary. If a simple gradient-based minimization is used,…

Geophysics · Physics 2018-04-05 Pawan Bharadwaj , Wim Mulder , Guy Drijkoningen

We investigate an approach for studying the ground state of a quantum many-body Hamiltonian that is based on treating the correlation functions as variational parameters. In this approach, the challenge set by the exponentially-large…

Strongly Correlated Electrons · Physics 2020-01-22 Arbel Haim , Richard Kueng , Gil Refael

In contrast to the standard quantum state tomography, the direct tomography seeks the direct access to the complex values of the wave function at particular positions (i.e., the expansion coefficient in a fixed basis). Originally put…

Quantum Physics · Physics 2021-11-18 Xuan-Hoai Thi Nguyen , Mahn-Soo Choi

We propose a variational scheme to represent composite quantum systems using multiple parameterized functions of varying accuracies on both classical and quantum hardware. The approach follows the variational principle over the entire…

Quantum Physics · Physics 2024-06-21 Stefano Barison , Filippo Vicentini , Giuseppe Carleo

An expansion for quantum statistical mechanics is derived that gives classical statistical mechanics as the leading term. Each quantum correction comes from successively larger permutation loops, which arise from the factorization of the…

Statistical Mechanics · Physics 2016-05-12 Phil Attard

Bayesian experimental design is a technique that allows to efficiently select measurements to characterize a physical system by maximizing the expected information gain. Recent developments in deep neural networks and normalizing flows…

Quantum Physics · Physics 2023-06-27 Leopoldo Sarra , Florian Marquardt

Recently developed tensor network methods demonstrate great potential for addressing the quantum many-body problem, by constructing variational spaces with polynomially, instead of exponentially, scaled parameters. Constructing such an…

Strongly Correlated Electrons · Physics 2015-06-15 Zhen Wang , Yongjian Han , Guang-Can Guo , Lixin He

We derive a closed equation of motion for the current density of an inhomogeneous quantum many-body system under the assumption that the time-dependent wave function can be described as a geometric deformation of the ground-state wave…

Other Condensed Matter · Physics 2015-05-14 Xianlong Gao , Jianmin Tao , G. Vignale , I. V. Tokatly

The act of measurement on a quantum state is supposed to "collapse" the state into one of several eigenstates of the operator corresponding to the observable being measured. This measurement process is sometimes described as outside…

Quantum Physics · Physics 2021-10-26 Satish Ramakrishna

A practical search technique for finding the complex saddle points used in wave packet or coherent state propagation is developed which works for a large class of Hamiltonian dynamical systems with many degrees of freedom. The method can be…

Statistical Mechanics · Physics 2018-08-08 Steven Tomsovic

The method used earlier for analysis of correlated nanoscopic systems is extended to infinite (periodic) s-band like systems described by the Hubbard model and its extensions. The optimized single-particle wave functions contained in the…

Strongly Correlated Electrons · Physics 2009-02-18 Jan Kurzyk , Włodzimierz Wójcik , Jozef Spałek

We suggest that low-lying eigenvalues of realistic quantum many-body hamiltonians, given, as in the nuclear shell model, by large matrices, can be calculated, instead of the full diagonalization, by the diagonalization of small truncated…

Nuclear Theory · Physics 2009-10-31 Mihai Horoi , Alexander Volya , Vladimir Zelevinsky

The concept of the macroscopic wave function is a key for understanding macroscopic quantum phenomena. The existence of this object reflects a certain order, as is present in a Bose-Einstein condensate when a single-particle orbital is…

Quantum Gases · Physics 2015-08-25 Bettina Gertjerenken , Martin Holthaus

We are interested in how quantum data can allow for practical solutions to otherwise difficult computational problems. A notoriously difficult phenomenon from quantum many-body physics is the emergence of many-body localization (MBL). So…

Disordered Systems and Neural Networks · Physics 2022-02-21 Alexander Gresch , Lennart Bittel , Martin Kliesch

A powerful approach to solve the Coulombic quantum three-body problem is proposed. The approach is exponentially convergent and more efficient than the Hyperspherical Coordinate(HC) method and the Correlation Function Hyperspherical…

Atomic Physics · Physics 2007-05-23 Shi-Na Tan

In this work we derive a systematic short-range expansion of the many-body wave function. At leading order, the wave function is factorized to a zero-energy $s$-wave correlated pair and spectator particles, while terms that include energy…

Nuclear Theory · Physics 2023-07-13 Ronen Weiss , Diego Lonardoni , Stefano Gandolfi

We investigate in a simple model whether a Jastrow-based approach for a many-body system containing two-body interactions can be exact. By comparison with recent assertions to the contrary, we find that in general the exact wave function is…

Chemical Physics · Physics 2007-05-23 Niels R. Walet , R. F. Bishop

High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random-walk Metropolis algorithms. The assumptions under which weak convergence results are proved are however restrictive: the…

Methodology · Statistics 2022-02-16 Sebastian M Schmon , Philippe Gagnon

The Wave Based Method (WBM) is a Trefftz method for the simulation of wave problems in vibroacoustics. Like other Trefftz methods, it employs a non-standard discretisation basis consisting of solutions of the partial differential equation…

Numerical Analysis · Mathematics 2018-02-06 Daan Huybrechs , Anda-Elena Olteanu