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Quantum phase is not a direct observable and is usually determined by interferometric methods. We present a method to map complete electron wave functions, including internal quantum phase information, from measured single-state probability…

Mesoscale and Nanoscale Physics · Physics 2008-03-19 Christopher R. Moon , Laila S. Mattos , Brian K. Foster , Gabriel Zeltzer , Wonhee Ko , Hari C. Manoharan

Determinantal Point Processes (DPPs) are elegant probabilistic models of repulsion and diversity over discrete sets of items. But their applicability to large sets is hindered by expensive cubic-complexity matrix operations for basic tasks…

Machine Learning · Computer Science 2016-05-31 Chengtao Li , Stefanie Jegelka , Suvrit Sra

The problem of classification in machine learning has often been approached in terms of function approximation. In this paper, we propose an alternative approach for classification in arbitrary compact metric spaces which, in theory, yields…

Machine Learning · Computer Science 2026-03-26 H. N. Mhaskar , Ryan O'Dowd

We show that the spectrum of a flow field can be extracted within a local region by straightforward filtering in physical space. We find that for a flow with a certain level of regularity, the filtering kernel must have a sufficient number…

Fluid Dynamics · Physics 2018-12-04 Mahmoud Sadek , Hussein Aluie

Squeezed number states for a single mode Hamiltonian are investigated from two complementary points of view. Firstly the more relevant features of their photon distribution are discussed using the WKB wave functions. In particular the…

Quantum Physics · Physics 2009-11-10 D. F. Mundarain , J. Stephany

Model misspecification can create significant challenges for the implementation of probabilistic models, and this has led to development of a range of robust methods which directly account for this issue. However, whether these more…

Machine Learning · Statistics 2025-04-22 Oscar Key , Arthur Gretton , François-Xavier Briol , Tamara Fernandez

The effect of the Coulomb interaction on the phase diagram of finite nuclei is studied within the Canonical Thermodynamic Model. If Coulomb effects are artificially switched off, this model shows a phenomenology consistent with the…

Nuclear Theory · Physics 2008-12-18 G. Chaudhuri , S. Das Gupta , F. Gulminelli

We propose a class of kernel-based two-sample tests, which aim to determine whether two sets of samples are drawn from the same distribution. Our tests are constructed from kernels parameterized by deep neural nets, trained to maximize test…

Machine Learning · Statistics 2021-01-15 Feng Liu , Wenkai Xu , Jie Lu , Guangquan Zhang , Arthur Gretton , Danica J. Sutherland

The phase-space of a simple synchronization model is thoroughly investigated. The model considers two-mode stochastic oscillators, coupled through a pulse-like interaction controlled by simple optimization rules. A complex phase space is…

Adaptation and Self-Organizing Systems · Physics 2020-12-03 Szabolcs Horvát , Zoltán Néda

Phase measurement constitutes a key task in many fields of science, both in the classical and quantum regime. The higher precision of such measurement offers significant advances, and can also be utilised to achieve finer estimates for…

The first quantum technologies to solve computational problems that are beyond the capabilities of classical computers are likely to be devices that exploit characteristics inherent to a particular physical system, to tackle a bespoke…

We study the wave function of a tensor model in the canonical formalism by Hamiltonian Monte Carlo method for Lie group symmetric or nearby values for the argument of the wave function, and show that there emerge Lie-group symmetric…

High Energy Physics - Theory · Physics 2022-03-31 Naoki Sasakura

In this paper, we discuss some numerical realizations of Shannon's sampling theorem. First we show the poor convergence of classical Shannon sampling sums by presenting sharp upper and lower bounds of the norm of the Shannon sampling…

Numerical Analysis · Mathematics 2025-04-17 Melanie Kircheis , Daniel Potts , Manfred Tasche

We present a method to identify spurious signals generated by finite-width pulses in quantum sensing experiments and apply it to recently proposed dynamical decoupling sequences for accurate spectral interpretation. We first study the…

Quantum Physics · Physics 2016-09-28 J. F. Haase , Z. -Y. Wang , J. Casanova , M. B. Plenio

Quantum Signal Processing (QSP) is a technique that can be used to implement a polynomial transformation $P(x)$ applied to the eigenvalues of a unitary $U$, essentially implementing the operation $P(U)$, provided that $P$ satisfies some…

Quantum Physics · Physics 2023-03-21 Lorenzo Laneve

A central feature of quantum metrology is the possibility of Heisenberg scaling, a quadratic improvement over the limits of classical statistics. This scaling, however, is notoriously fragile to noise. While for some noise types it can be…

Quantum Physics · Physics 2022-06-08 Giulio Chiribella , Xiaobin Zhao

We are interested in the large time behavior of the solutions to the growth-fragmentation equation. We work in the space of integrable functions weighted with the principal dual eigenfunction of the growth-fragmentation operator. This space…

Analysis of PDEs · Mathematics 2019-02-28 Etienne Bernard , Pierre Gabriel

Phase imaging techniques extract the optical path-length information of a scene, whereas wavefront sensors provide the shape of an optical wavefront. Since these two applications have different technical requirements, they have developed…

Optics · Physics 2018-02-28 F. Soldevila , V. Durán , P. Clemente , J. Lancis , E. Tajahuerce

Achieving a quantum computational advantage regime, and thus providing evidence against the extended Church-Turing thesis, remains one of the key challenges of modern science. Boson sampling seems to be a very promising platform in this…

Quantum Physics · Physics 2024-11-22 A. A. Mazanik , A. N. Rubtsov

We prove that a classical computer can efficiently sample from the photon-number probability distribution of a Gaussian state prepared by using an optical circuit that is shallow and local. Our work generalizes previous known results for…