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The refined analytic torsion, defined by M. Braverman and T. Kappeler on closed manifolds, can be viewed as a refinement of the Ray-Singer torsion, since it is a canonical choice of an element with Ray-Singer norm one, in case of unitary…

Differential Geometry · Mathematics 2015-02-02 Boris Vertman

We study nonlinear effective field theories (EFTs) with factorially growing perturbative expansions, focusing on a class in which the relative entropy encodes an infinite tower of higher-dimensional operators. Using the resummed relative…

High Energy Physics - Theory · Physics 2026-04-28 Pietro Conzinu , Daiki Ueda

This paper studies chance-constrained stochastic optimization problems with finite support. It presents an iterative method that solves reduced-size chance-constrained models obtained by partitioning the scenario set. Each reduced problem…

Optimization and Control · Mathematics 2024-11-26 Marius Roland , Alexandre Forel , Thibaut Vidal

Efficient global optimization is a widely used method for optimizing expensive black-box functions such as tuning hyperparameter, and designing new material, etc. Despite its popularity, less attention has been paid to analyzing the…

Optimization and Control · Mathematics 2022-09-21 Wenjie Xu , Yuning Jiang , Emilio T. Maddalena , Colin N. Jones

We discuss how to consistently use Effective Field Theories (EFTs) to set universal bounds on heavy-mediator Dark Matter at colliders, without prejudice on the model underlying a given effective interaction. We illustrate the method for a…

High Energy Physics - Phenomenology · Physics 2015-05-18 Davide Racco , Andrea Wulzer , Fabio Zwirner

The present approach relies on the SM chiral symmetry breaking pattern $SU(2)_L\otimes SU(2)_R\to SU(2)_{L+R}$, with the EW Goldstone bosons given in a non-linear realization and the Higgs boson described by an EW singlet field. In…

High Energy Physics - Phenomenology · Physics 2019-09-04 Adolfo Guevara , Fernando Alvarado , Juan José Sanz Cillero

We compute the structure of a self-gravitating torus with polytropic equation-of-state (EOS) rotating in an imposed centrifugal potential. The Poisson-solver is based on isotropic multigrid with optimal covering factor (fluid…

Astrophysics of Galaxies · Physics 2016-12-07 J. -M. Huré , F. Hersant

Bond rating Transition Probability Matrices (TPMs) are built over a one-year time-frame and for many practical purposes, like the assessment of risk in portfolios or the computation of banking Capital Requirements (e.g. the new IFRS 9…

Risk Management · Quantitative Finance 2017-10-17 Greig Smith , Goncalo dos Reis

Imagine we want to split a group of agents into teams in the most \emph{efficient} way, considering that each agent has their own preferences about their teammates. This scenario is modeled by the extensively studied \textsc{Coalition…

Data Structures and Algorithms · Computer Science 2025-05-29 Foivos Fioravantes , Harmender Gahlawat , Nikolaos Melissinos

This paper considers the state estimation problem for nonlinear dynamic systems with unknown but bounded noises. Set membership filter (SMF) is a popular algorithm to solve this problem. In the set membership setting, we investigate the…

Optimization and Control · Mathematics 2022-11-10 Xiaowei Li , Xuqi Zhang , Zhiguo Wang , Xiaojing Shen

We present an extension of the summation-by-parts (SBP) framework to tensor-product spectral-element operators in collapsed coordinates. The proposed approach enables the construction of provably stable discretizations of arbitrary order…

Numerical Analysis · Mathematics 2025-04-29 Tristan Montoya , David W. Zingg

We develop the spacetime aspects of the computation of partition functions for string/M-theory on AdS(3) xM. Subleading corrections to the semi-classical result are included systematically, laying the groundwork for comparison with CFT…

High Energy Physics - Theory · Physics 2010-10-27 Per Kraus , Finn Larsen

We develop a highly scalable optimization method called "hierarchical group-thresholding" for solving a multi-task regression model with complex structured sparsity constraints on both input and output spaces. Despite the recent emergence…

Machine Learning · Statistics 2012-08-16 Seunghak Lee , Eric P. Xing

We propose a new algorithm to solve optimization problems of the form $\min f(X)$ for a smooth function $f$ under the constraints that $X$ is positive semidefinite and the diagonal blocks of $X$ are small identity matrices. Such problems…

Optimization and Control · Mathematics 2016-01-07 Nicolas Boumal

We construct a two-level weighted TQFT whose structure coefficents are equivariant intersection numbers on moduli spaces of admissible covers. Such a structure is parallel (and strictly related) to the local Gromov-Witten theory of curves…

Algebraic Geometry · Mathematics 2007-05-23 Renzo Cavalieri

We show that the refined analytic torsion is a holomorphic section of the determinant line bundle over the space of complex representations of the fundamental group of a closed oriented odd dimensional manifold. Further, we calculate the…

Differential Geometry · Mathematics 2007-05-23 Maxim Braverman , Thomas Kappeler

Group equivariant convolutional networks (GCNNs) endow classical convolutional networks with additional symmetry priors, which can lead to a considerably improved performance. Recent advances in the theoretical description of GCNNs revealed…

Machine Learning · Computer Science 2021-01-22 Leon Lang , Maurice Weiler

We formulate rational conformal field theory in terms of a symmetric special Frobenius algebra A and its representations. A is an algebra in the modular tensor category of Moore-Seiberg data of the underlying chiral CFT. The multiplication…

High Energy Physics - Theory · Physics 2008-11-26 Jürgen Fuchs , Ingo Runkel , Christoph Schweigert

Motivated by many application problems, we consider Markov decision processes (MDPs) with a general loss function and unknown parameters. To mitigate the epistemic uncertainty associated with unknown parameters, we take a Bayesian approach…

Machine Learning · Computer Science 2025-10-02 Xiaoshuang Wang , Yifan Lin , Enlu Zhou

We propose an algorithm to solve optimization problems constrained by partial (ordinary) differential equations under uncertainty, with almost sure constraints on the state variable. To alleviate the computational burden of high-dimensional…

Optimization and Control · Mathematics 2024-07-08 Harbir Antil , Sergey Dolgov , Akwum Onwunta