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A complete solution to the multiplier version of the inverse problem of the calculus of variations is given for a class of hyperbolic systems of second-order partial differential equations in two independent variables. The necessary and…

Differential Geometry · Mathematics 2009-10-16 Matt Biesecker

We study numerical computation of conformal invariants of domains in the complex plane. In particular, we provide an algorithm for computing the conformal capacity of a condenser. The algorithm applies for wide kind of geometries: domains…

Complex Variables · Mathematics 2020-08-19 Mohamed M S Nasser , Matti Vuorinen

In this work, we present a novel algorithm design methodology that finds the optimal algorithm as a function of inequalities. Specifically, we restrict convergence analyses of algorithms to use a prespecified subset of inequalities, rather…

Optimization and Control · Mathematics 2024-03-25 Chanwoo Park , Ernest K. Ryu

It is proved that the first-order theory of the structure (N,mod) is undecidable. Here mod denotes the operation of computing the remainder for any division between positive integers; i.e. x mod y is the remainder obtained by the division x…

Logic · Mathematics 2025-06-05 Mihai Prunescu

Algorithmic differentiation (AD) has become increasingly capable and straightforward to use. However, AD is inefficient when applied directly to solvers, a feature of most engineering analyses. We can leverage implicit differentiation to…

Optimization and Control · Mathematics 2023-06-28 Andrew Ning , Taylor McDonnell

A gauge invariant partition function is defined for gauge theories which leads to the standard quantization. It is shown that the descent equations and consequently the consistent anomalies and Schwinger terms can be extracted from this…

High Energy Physics - Theory · Physics 2015-05-27 Amir Abbass Varshovi

Uncertainty quantification is a critical aspect of machine learning models, providing important insights into the reliability of predictions and aiding the decision-making process in real-world applications. This paper proposes a novel way…

Machine Learning · Computer Science 2024-01-02 Yusuf Sale , Paul Hofman , Lisa Wimmer , Eyke Hüllermeier , Thomas Nagler

The preceding paper constructed tangle machines as diagrammatic models, and illustrated their utility with a number of examples. The information content of a tangle machine is contained in characteristic quantities associated to equivalence…

Information Theory · Computer Science 2014-04-11 Avishy Y. Carmi , Daniel Moskovich

A differential calculus is set up on a deformation of the oscillator algebra. It is uniquely determined by the requirement of invariance under a seven-dimensional quantum group. The quantum space and its associated differential calculus are…

q-alg · Mathematics 2009-10-30 J. Bertrand , M. Irac-Astaud

Fundamentally, every static program analyser searches for a proof through a combination of heuristics providing candidate solutions and a candidate validation technique. Essentially, the heuristic reduces a second-order problem to a…

Logic in Computer Science · Computer Science 2015-01-20 Cristina David , Daniel Kroening , Matt Lewis

The question of defining unique, generally applicable constrained second, and higher-order, derivatives is investigated. It is shown that second-order constrained derivatives obtained via two successive constrained differentiations provide…

Mathematical Physics · Physics 2012-08-14 Tamas Gal

Linearization problem of ordinary differential equations by a new set of tangent transformations is considered in the paper. This set of transformations allows one to extend the set of transformations applied for the linearization problem.…

Classical Analysis and ODEs · Mathematics 2013-10-02 S. Suksern , S. V. Meleshko

Differentiable programming has recently received much interest as a paradigm that facilitates taking gradients of computer programs. While the corresponding flexible gradient-based optimization approaches so far have been used predominantly…

We prove decidability results on the existence of constant subsequences of uniformly recurrent morphic sequences along arithmetic progressions. We use spectral properties of the subshifts they generate to give a first algorithm deciding…

Dynamical Systems · Mathematics 2018-11-19 Fabien Durand , Valérie Goyheneche

We consider the decidability of the verification problem of programs \emph{modulo axioms} --- that is, verifying whether programs satisfy their assertions, when the functions and relations it uses are assumed to interpreted by arbitrary…

Programming Languages · Computer Science 2019-10-30 Umang Mathur , P. Madhusudan , Mahesh Viswanathan

In this paper we consider a fragment of the first-order theory of the real numbers that includes systems of equations of continuous functions in bounded domains, and for which all functions are computable in the sense that it is possible to…

Computational Complexity · Computer Science 2016-08-15 Peter Franek , Stefan Ratschan , Piotr Zgliczynski

This contribution deals with identification of fractional-order dynamical systems. We consider systems whose mathematical description is a three-member differential equation in which the orders of derivatives can be real numbers. We give a…

Optimization and Control · Mathematics 2007-05-23 L. Dorcak , V. Lesko , I. Kostial

Infinite-state systems such as distributed protocols are challenging to verify using interactive theorem provers or automatic verification tools. Of these techniques, deductive verification is highly expressive but requires the user to…

Programming Languages · Computer Science 2019-05-21 Yotam M. Y. Feldman , James R. Wilcox , Sharon Shoham , Mooly Sagiv

Algorithms are ways of mapping problems to solutions. An algorithm is invertible precisely when this mapping is injective, such that the initial problem can be uniquely inferred from its solution. While invertible algorithms can be…

Programming Languages · Computer Science 2022-12-08 Joachim Tilsted Kristensen , Robin Kaarsgaard , Michael Kirkedal Thomsen

Several quantities important in condensed matter physics, quantum information, and quantum chemistry, as well as quantities required in meta-optimization of machine learning algorithms, can be expressed as gradients of implicitly defined…

Quantum Physics · Physics 2022-11-28 Shahnawaz Ahmed , Nathan Killoran , Juan Felipe Carrasquilla Álvarez