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We propose an automatable data-driven methodology for robust nonlinear reduced-order modelling from time-resolved snapshot data. In the kinematical coarse-graining, the snapshots are clustered into few centroids representable for the whole…

Fluid Dynamics · Physics 2020-12-02 Hao Li , Daniel Fernex , Richard Semaan , Jianguo Tan , Marek Morzyński , Bernd R. Noack

Dynamic graphs are rife with higher-order interactions, such as co-authorship relationships and protein-protein interactions in biological networks, that naturally arise between more than two nodes at once. In spite of the ubiquitous…

Machine Learning · Computer Science 2021-02-09 Manohar Kaul , Masaaki Imaizumi

In static classical statistical systems the problem of information transport from a boundary to the bulk finds a simple description in terms of wave functions or density matrices. While the transfer matrix formalism is a type of Heisenberg…

Quantum Physics · Physics 2018-05-09 C. Wetterich

We study the problem of identifying macroscopic structures in networks, characterizing the impact of introducing link directions on the detectability phase transition. To this end, building on the stochastic block model, we construct a…

Physics and Society · Physics 2019-05-01 Mateusz Wilinski , Piero Mazzarisi , Daniele Tantari , Fabrizio Lillo

We investigate four different types of representations of deformed canonical variables leading to generalized versions of Heisenberg's uncertainty relations resulting from noncommutative spacetime structures. We demonstrate explicitly how…

Quantum Physics · Physics 2013-08-02 Sanjib Dey , Andreas Fring , Boubakeur Khantoul

Quantum collision models (CMs) provide advantageous case studies for investigating major issues in open quantum systems theory, and especially quantum non-Markovianity. After reviewing their general definition and distinctive features, we…

Quantum Physics · Physics 2018-03-09 Francesco Ciccarello

Kernel matrices are ubiquitous in computational mathematics, often arising from applications in machine learning and scientific computing. In two or three spatial or feature dimensions, such problems can be approximated efficiently by a…

Numerical Analysis · Mathematics 2025-11-07 Abraham Khan , Chao Chen , Vishwas Rao , Arvind K. Saibaba

Recently, a generalization of the standard optical multiport was proposed [Phys. Rev. A 93, 043845 (2016)]. These directionally unbiased multiports allow photons to reverse direction and exit backwards from the input port, providing a…

Quantum Physics · Physics 2017-04-12 David S. Simon , Casey A. Fitzpatrick , Shuto Osawa , Alexander V. Sergienko

We introduce a geometrical framework to construct a large class of time-dependent quantum systems, in which the position of a classical particle moving autonomously on a smooth connected manifold is used to steer a quantum Hamiltonian over…

Quantum Physics · Physics 2026-01-30 Jihong Wu , Chuan Liu , Daniel Bulmash , Wen Wei Ho

We study classical Hamiltonian systems in which the intrinsic proper time evolution parameter is related through a probability distribution to the physical time, which is assumed to be discrete. In this way, a physical clock with discrete…

Quantum Physics · Physics 2007-05-23 H. -T. Elze

A square matrix is nonderogatory if its Jordan blocks have distinct eigenvalues. We give canonical forms (i) for nonderogatory complex matrices up to unitary similarity and (ii) for pairs of complex matrices up to similarity, in which one…

Representation Theory · Mathematics 2011-12-19 Vyacheslav Futorny , Roger A. Horn , Vladimir V. Sergeichuk

A model of quantum computing is presented, based on properties of connections with a prescribed monodromy group on holomorphic vector bundles over bases with nontrivial topology. Such connections with required properties appear in the…

Quantum Physics · Physics 2007-05-23 Gia Giorgadze

While hidden class models of various types arise in many statistical applications, it is often difficult to establish the identifiability of their parameters. Focusing on models in which there is some structure of independence of some of…

Statistics Theory · Mathematics 2009-09-01 Elizabeth S. Allman , Catherine Matias , John A. Rhodes

We address the classical problem of hierarchical clustering, but in a framework where one does not have access to a representation of the objects or their pairwise similarities. Instead, we assume that only a set of comparisons between…

Machine Learning · Statistics 2019-06-13 Debarghya Ghoshdastidar , Michaël Perrot , Ulrike von Luxburg

We propose a scalable algorithmic framework for exact Bayesian variable selection and model averaging in linear models under the assumption that the Gram matrix is block-diagonal, and as a heuristic for exploring the model space for general…

Computation · Statistics 2017-01-04 Omiros Papaspiliopoulos , David Rossell

The formalism of the particle dynamics in the space-time, where motion of free particles is primordially stochastic, is considered. The conventional dynamic formalism, obtained for the space-time, where the motion of free particles is…

General Physics · Physics 2011-03-21 Yuri A. Rylov

Nonlinear optical cavities are crucial both in classical and quantum optics; in particular, nowadays optical parametric oscillators are one of the most versatile and tunable sources of coherent light, as well as the sources of the highest…

Quantum Physics · Physics 2016-03-22 Carlos Navarrete-Benlloch , Eugenio Roldán , Yue Chang , Tao Shi

A rank-three tensor model in canonical formalism has recently been proposed. The model describes consistent local-time evolutions of fuzzy spaces through a set of first-class constraints which form an on-shell closed algebra with structure…

High Energy Physics - Theory · Physics 2015-06-12 Naoki Sasakura

In this paper, we introduce the Wigner parametrization of unitary matrices and then apply it to the full description of canonical seesaw models, which extend the Standard Model with three right-handed neutrino singlets and account…

High Energy Physics - Phenomenology · Physics 2025-02-12 Shun Zhou

This paper introduces an innovative approach to open world recognition (OWR), where we leverage knowledge acquired from known objects to address the recognition of previously unseen objects. The traditional method of object modeling relies…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Paridhi Singh , Arun Kumar