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We illustrate the use of the notion of derived recurrences introduced earlier to evaluate the algebraic entropy of self-maps of projective spaces. We in particular give an example, where a complete proof is still awaited, but where…

Dynamical Systems · Mathematics 2024-02-28 C. M. Viallet

In this review, we present some advanced algorithms and programs used in our scientific school with short description of types of astrophysical systems, which we study. However, we discuss mainly mathematical methods, which may be applied…

Instrumentation and Methods for Astrophysics · Physics 2020-11-11 Ivan L. Andronov , Vitalii V. Breus , Larysa S. Kudashkina

We study the design of efficient algorithms for combinatorial pattern matching. More concretely, we study algorithms for tree matching, string matching, and string matching in compressed texts.

Data Structures and Algorithms · Computer Science 2007-09-03 Philip Bille

A process model of quantum mechanics utilizes a combinatorial game to generate a discrete and finite causal space upon which can be defined a self-consistent quantum mechanics. An emergent space-time M and continuous wave function arise…

Mathematical Physics · Physics 2015-06-19 William Sulis

Symbolic regression plays a crucial role in modern scientific research thanks to its capability of discovering concise and interpretable mathematical expressions from data. A key challenge lies in the search for parsimonious and…

Machine Learning · Computer Science 2025-09-12 Kai Ruan , Yilong Xu , Ze-Feng Gao , Yike Guo , Hao Sun , Ji-Rong Wen , Yang Liu

Real-world experiments involve batched & delayed feedback, non-stationarity, multiple objectives & constraints, and (often some) personalization. Tailoring adaptive methods to address these challenges on a per-problem basis is infeasible,…

Machine Learning · Computer Science 2024-11-11 Ethan Che , Daniel R. Jiang , Hongseok Namkoong , Jimmy Wang

Neural Combinatorial Optimization attempts to learn good heuristics for solving a set of problems using Neural Network models and Reinforcement Learning. Recently, its good performance has encouraged many practitioners to develop neural…

Artificial Intelligence · Computer Science 2022-05-04 Andoni I. Garmendia , Josu Ceberio , Alexander Mendiburu

Our aim is to experimentally study the possibility of distinguishing between quantum sources of randomness--recently proved to be theoretically incomputable--and some well-known computable sources of pseudo-randomness. Incomputability is a…

Quantum Physics · Physics 2009-12-23 Cristian S. Calude , Michael J. Dinneen , Monica Dumitrescu , Karl Svozil

The Poisson compound decision problem is a long-standing problem in statistics, where empirical Bayes methodologies are commonly used to estimate Poisson's means in static or batch domains. In this paper, we study the Poisson compound…

Methodology · Statistics 2025-06-10 Stefano Favaro , Sandra Fortini

Statistical physics courses typically employ abstract language that describes objects too small to be seen, making the topic challenging for students to understand. In this work, we introduce a simple experiment that allows conceptualizing…

This survey is focused on certain sequential decision-making problems that involve optimizing over probability functions. We discuss the relevance of these problems for learning and control. The survey is organized around a framework that…

Optimization and Control · Mathematics 2023-01-13 Emiland Garrabe , Giovanni Russo

Development of several alternative mathematical models for the biological system in question and discrimination between such models using experimental data is the best way to robust conclusions. Models which challenge existing theories are…

Quantitative Methods · Quantitative Biology 2016-02-01 Vitaly V. Ganusov

In computer experiments, a mathematical model implemented on a computer is used to represent complex physical phenomena. These models, known as computer simulators, enable experimental study of a virtual representation of the complex…

Methodology · Statistics 2012-07-03 Hugh Chipman , Pritam Ranjan , Weiwei Wang

Computational models are quantitative representations of systems. By analyzing and comparing the outputs of such models, it is possible to gain a better understanding of the system itself. Though as the complexity of model outputs…

Machine Learning · Computer Science 2022-12-13 Colin G. Cess , Stacey D. Finley

We use Sidon sets to present an elementary method to study some combinatorial problems in finite fields, such as sum product estimates, solubility of some equations and distribution of sequences in small intervals. We obtain classic and…

Number Theory · Mathematics 2015-03-13 Javier Cilleruelo

We propose a computationally efficient method to solve the dynamics of operators of bosonic quantum systems coupled to their environments. The method maps the operator under interest to a set of complex-valued functions, and its adjoint…

A method is suggested for treating those complicated physical problems for which exact solutions are not known but a few approximation terms of a calculational algorithm can be derived. The method permits one to answer the following rather…

High Energy Physics - Phenomenology · Physics 2009-10-31 V. I. Yukalov , E. P. Yukalova

In this paper we discuss how teaching of mathematics for middle school and high school students can be improved dramatically when motivation of concepts and ideas is done through the classical problems and the history of mathematics. This…

History and Overview · Mathematics 2019-05-30 Bedri Shaska , Tanush Shaska

This paper presents a soundness and completeness proof for propositional intuitionistic calculus with respect to the semantics of computability logic. The latter interprets formulas as interactive computational problems, formalized as games…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

Multiphysics problems involving two or more coupled physical phenomena are ubiquitous in science and engineering. This work develops a new partitioned exponential approach for the time integration of multiphysics problems. After a possible…

Numerical Analysis · Mathematics 2019-09-09 Mahesh Narayanamurthi , Adrian Sandu