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Metric data plays an important role in various settings such as metric-based indexing, clustering, classification, and approximation algorithms in general. Due to measurement error, noise, or an inability to completely gather all the data,…

Computational Geometry · Computer Science 2018-07-24 Chenglin Fan , Benjamin Raichel , Gregory Van Buskirk

A shortcoming of existing reachability approaches for nonlinear systems is the poor scalability with the number of continuous state variables. To mitigate this problem we present a simulation-based approach where we first sample a number of…

Systems and Control · Computer Science 2017-09-21 Murat Arcak , John Maidens

In three spatial dimensions, in the unitary limit of a non-relativistic quantum Bose or Fermi gas, the scattering length diverges. This occurs at a renormalization group fixed point, thus these systems present interesting examples of…

Quantum Gases · Physics 2011-02-16 Pye-Ton How , Andre LeClair

Backward reachability analysis computes the set of states that reach a target set under the competing influence of control input and disturbances. Depending on their interplay, the backward reachable set either represents all states that…

Numerical Analysis · Mathematics 2025-09-19 Mark Wetzlinger , Matthias Althoff

The Bouncy Particle Sampler (BPS) is a Monte Carlo Markov Chain algorithm to sample from a target density known up to a multiplicative constant. This method is based on a kinetic piecewise deterministic Markov process for which the target…

Probability · Mathematics 2019-11-18 Alain Durmus , Arnaud Guillin , Pierre Monmarché

Extendibility of bosonic Gaussian states is a key issue in continuous-variable quantum information. We show that a bosonic Gaussian state is $k$-extendible if and only if it has a Gaussian $k$-extension, and we derive a simple semidefinite…

Quantum Physics · Physics 2019-08-13 Ludovico Lami , Sumeet Khatri , Gerardo Adesso , Mark M. Wilde

Metric embeddings are a widely used method in algorithm design, where generally a ``complex'' metric is embedded into a simpler, lower-dimensional one. Historically, the theoretical computer science community has focused on bi-Lipschitz…

Data Structures and Algorithms · Computer Science 2025-05-19 Ainesh Bakshi , Vincent Cohen-Addad , Samuel B. Hopkins , Rajesh Jayaram , Silvio Lattanzi

We propose a new way to generate an observable geometric phase by means of a completely incoherent phenomenon. We show how to imprint a geometric phase to a system by "adiabatically" manipulating the environment with which it interacts. As…

Quantum Physics · Physics 2009-11-11 Angelo Carollo , G. Massimo Palma , Artur Lozinski , Marcelo Franca Santos , Vlatko Vedral

We discuss and calculate parity conserving (PC) and parity violating (PV) geometric phases for the metastable 2S states of hydrogen and deuterium. The atoms are supposed to be subjected to slowly varying electric and magnetic fields which…

Atomic Physics · Physics 2008-11-26 Timo Bergmann , Thomas Gasenzer , Otto Nachtmann

The past few years have seen a revived interest in quantum geometrical characterizations of band structures due to the rapid development of topological insulators and semi-metals. Although the metric tensor has been connected to many…

Mesoscale and Nanoscale Physics · Physics 2023-03-07 Adrien Bouhon , Abigail Timmel , Robert-Jan Slager

Complex systems have motivated continuing interest from the scientific community, leading to new concepts and methods. Growing systems represent a case of particular interest, as their topological, geometrical, and also dynamical properties…

Social and Information Networks · Computer Science 2024-05-27 Alexandre Benatti , Roberto M. Cesar , Luciano da F. Costa

The Vapnik-Chervonenkis dimension is a combinatorial parameter that reflects the "complexity" of a set of sets (a.k.a. concept classes). It has been introduced by Vapnik and Chervonenkis in their seminal 1971 paper and has since found many…

Machine Learning · Computer Science 2015-07-21 Shai Ben-David

We study the discrepancy between the distribution of a vector-valued functional of i.i.d. random elements and that of a Gaussian vector. Our main contribution is an explicit bound on the convex distance between the two distributions,…

Probability · Mathematics 2022-03-25 Mikołaj J. Kasprzak , Giovanni Peccati

The projective space of order $n$ over the finite field $\Fq$, denoted here as $\Ps$, is the set of all subspaces of the vector space $\Fqn$. The projective space can be endowed with distance function $d_S(X,Y) = \dim(X) + \dim(Y) -…

Information Theory · Computer Science 2015-03-19 Michael Braun , Tuvi Etzion , Alexander Vardy

Multi-stack pushdown systems are a well-studied model of concurrent computation using threads with first-order procedure calls. While, in general, reachability is undecidable, there are numerous restrictions on stack behaviour that lead to…

Formal Languages and Automata Theory · Computer Science 2013-10-11 Matthew Hague

This paper presents a reachability-based approach to finite-time transition problem of nonlinear systems between two stationary points (i.e., the point-to-point steering problem). When the target state is reachable, we prove that a solution…

Optimization and Control · Mathematics 2025-09-23 Juho Bae , Han-Lim Choi

We study, via the replica method of disordered systems, the packing problem of hard-spheres with a square-well attractive potential when the space dimensionality, d, becomes infinitely large. The phase diagram of the system exhibits…

Disordered Systems and Neural Networks · Physics 2013-12-17 Mauro Sellitto , Francesco Zamponi

Genetic sequencing has become an increasingly affordable and accessible source of genomic data in computational biology. This data is often represented as $k$-mers, i.e., strings of some fixed length $k$ with symbols chosen from a reference…

Combinatorics · Mathematics 2020-07-06 Lucas Laird

Vector Symbolic Architectures (VSAs) give a way to represent a complex object as a single fixed-length vector, so that similar objects have similar vector representations. These vector representations then become easy to use for machine…

Machine Learning · Computer Science 2022-02-11 Stephen I. Gallant

Multidimensional Scaling (MDS) is a classic technique that seeks vectorial representations for data points, given the pairwise distances between them. However, in recent years, data are usually collected from diverse sources or have…

Computer Vision and Pattern Recognition · Computer Science 2017-08-29 Song Bai , Xiang Bai , Longin Jan Latecki , Qi Tian
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