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Persistence diagrams (PDs) are now routinely used to summarize the underlying topology of complex data. Despite several appealing properties, incorporating PDs in learning pipelines can be challenging because their natural geometry is not…

Machine Learning · Statistics 2018-11-14 Théo Lacombe , Marco Cuturi , Steve Oudot

We provide a novel transcription of monotone operator theory to the non-Euclidean finite-dimensional spaces $\ell_1$ and $\ell_{\infty}$. We first establish properties of mappings which are monotone with respect to the non-Euclidean norms…

Optimization and Control · Mathematics 2023-03-21 Alexander Davydov , Saber Jafarpour , Anton V. Proskurnikov , Francesco Bullo

We present an algorithm for the rapid numerical integration of smooth, time-periodic differential equations with small nonlinearity, particularly suited to problems with small dissipation. The emphasis is on speed without compromising…

Numerical Analysis · Mathematics 2015-06-23 Michele V. Bartuccelli , Jonathan H. B. Deane , Guido Gentile

We compute the holographic Euclidean two-point function of scalar operators in a thermal state. We work directly using the Fourier series on the thermal circle. The Fourier series does not converge as a function, but instead converges as a…

High Energy Physics - Theory · Physics 2026-03-31 Paolo Arnaudo , Benjamin Withers

We will consider the resolution of the 3D non linear wave equation under the assumption of spherical symmetry on the euclidian space. For this purpose, we will build a non trivial measure on distributions such that there exists a set of…

Analysis of PDEs · Mathematics 2013-02-14 Anne-Sophie de Suzzoni

We develop a technique of multiple scale asymptotic expansions along mean flows and a corresponding notion of weak multiple scale convergence. These are applied to homogenize convection dominated parabolic equations with rapidly…

Analysis of PDEs · Mathematics 2016-09-29 Thomas Holding , Harsha Hutridurga , Jeffrey Rauch

Determining the representativeness of a point within a data cloud has recently become a desirable task in multivariate analysis. The concept of statistical depth function, which reflects centrality of an arbitrary point, appears to be…

Computation · Statistics 2016-03-02 Pavlo Mozharovskyi

Continuous time branching models are used to create random fractals in a Euclidean space, whose Hausdorff dimension is controlled by an input parameter. Finite realizations are applied in modelling the set of sites visited in models of…

Probability · Mathematics 2018-05-25 R. W. R. Darling , Robin Pemantle

We consider manifestly crossing symmetric dispersion relations for Mellin amplitudes of scalar four point correlators in conformal field theories (CFTs). This allows us to set up the non-perturbative Polyakov bootstrap for CFTs in Mellin…

High Energy Physics - Theory · Physics 2021-05-31 Rajesh Gopakumar , Aninda Sinha , Ahmadullah Zahed

Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in…

High Energy Physics - Theory · Physics 2016-08-05 Thomas Hartman , Sachin Jain , Sandipan Kundu

We present a Bayesian data fusion method to approximate a posterior distribution from an ensemble of particle estimates that only have access to subsets of the data. Our approach relies on approximate probabilistic inference of model…

Computation · Statistics 2020-10-28 Caleb Miller , Michael D. Schneider , Jem N. Corcoran , Jason Bernstein

We introduce a generalization of the Euclidean algorithm for rings equipped with an involution, and completely enumerate all isomorphism classes of orders over definite, rational quaternion algebras equipped with an orthogonal involution…

Number Theory · Mathematics 2020-06-15 Arseniy , Sheydvasser

Integral and derivative dispersion relations (DR) are considered for the forward scattering $pp$ and $\bar pp$ amplitudes. A new representation for the derivative DR, valid not only at high energy, is obtained. The data on the total cross…

High Energy Physics - Phenomenology · Physics 2011-09-13 E. Martynov , J. R. Cudell , O. V. Selyugin

Wave propagation and acoustic scattering problems require vast computational resources to be solved accurately at high frequencies. Asymptotic methods can make this cost potentially frequency independent by explicitly extracting the…

Numerical Analysis · Mathematics 2018-01-16 Daan Huybrechs , Peter Opsomer

Group theoretical methods are used to study the equations describing \chi^{(2)}:\chi^{(2)} cascading. The equations are shown not to be integrable by inverse scattering techniques. On the other hand, these equations do share some of the…

solv-int · Physics 2009-10-31 S. Lafortune , P. Winternitz , C. R. Menyuk

The elastic neutron-${}^3\mathrm{H}$ scattering at intermediate energies is studied using rigorous integral equations solved in the momentum-space partial-wave basis. The four-particle transition operators are expanded into…

Nuclear Theory · Physics 2025-02-24 A. Deltuva

We consider correlators for the flux of energy and charge in the background of operators with large global $U(1)$ charge in conformal field theory (CFT). It has recently been shown that the corresponding Euclidean correlators generically…

High Energy Physics - Theory · Physics 2023-09-27 Eren Firat , Alexander Monin , Riccardo Rattazzi , Matthew T. Walters

The important role of geometric phases in searches for a permanent electric dipole moment of the neutron, using Ramsey separated oscillatory field nuclear magnetic resonance, was first noted by Commins and investigated in detail by…

Nuclear Experiment · Physics 2015-12-18 R. Golub , A. Steyerl , C. Kaufman , G. Müller

A model of a finite cylindrical ion channel through a phospholipid membrane of width $L$ separating two electrolyte reservoirs is studied. Analytical solution of the Poisson equation is obtained for an arbitrary distribution of ions inside…

Soft Condensed Matter · Physics 2009-11-11 Yan Levin

The matching problem is a notorious combinatorial optimization problem that has attracted for many years the attention of the statistical physics community. Here we analyze the Euclidean version of the problem, i.e. the optimal matching…

Disordered Systems and Neural Networks · Physics 2017-01-11 Carlo Lucibello , Giorgio Parisi , Gabriele Sicuro