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Reduction-based interpreters are traditionally defined in terms of a one-step reduction function which systematically decomposes a term into a potential redex and context, contracts the redex, and recomposes it to construct the new term to…

Programming Languages · Computer Science 2025-08-18 Casper Bach

In this paper a thermodynamical derivation of the quantum potential is pro- posed. Within the framework of Bohmian mechanics we show how the quantum potential can be derived, by adding an additional informational degree of freedom to the…

Quantum Physics · Physics 2019-06-04 Luca Curcuraci , Mehdi Ramezani

In a recent paper by Ibragimov [N. H. Ibragimov, Invariant Lagrangians and a new method of integration of nonlinear equations, J. Math. Anal. Appl. 304 (2005) 212--235] a method was presented in order to find Lagrangians of certain…

Exactly Solvable and Integrable Systems · Physics 2015-05-13 M. C. Nucci , P. G. L. Leach

The effects of dissipation on the thermodynamic properties of nonlinear quantum systems are approached by the path-integral method in order to construct approximate classical-like formulas for evaluating thermal averages of thermodynamic…

Statistical Mechanics · Physics 2016-11-23 Alessandro Cuccoli , Andrea Fubini , Valerio Tognetti , Ruggero Vaia

The paradigm of differentiable programming has significantly enhanced the scope of machine learning via the judicious use of gradient-based optimization. However, standard differentiable programming methods (such as autodiff) typically…

In this paper, we realize high-level versions of Jacobi's derivative formula to all the rational characteristics corresponding to level $k \,\,(k=3,4,5,6).$ For this purpose, we propose the method to obtain derivative formulas by means of…

Classical Analysis and ODEs · Mathematics 2017-04-03 Kazuhide Matsuda

We aim at computing the derivative of the solution to a parametric optimization problem with respect to the involved parameters. For a class broader than that of strongly convex functions, this can be achieved by automatic differentiation…

Optimization and Control · Mathematics 2019-10-15 Sheheryar Mehmood , Peter Ochs

In this paper, we investigate the numerical approximation of Hamilton-Jacobi equations with the Caputo time-fractional derivative. We introduce an explicit in time discretization of the Caputo derivative and a finite difference scheme for…

Numerical Analysis · Mathematics 2019-12-20 Fabio Camilli , Serikbolsyn Duisembay

We have been working in many aspects of the problem of analyzing, understanding and solving ordinary differential equations (first and second order). As we have extensively mentioned, while working in the Darboux type methods, the most…

Mathematical Physics · Physics 2011-04-27 L. G. S. Duarte , L. A. C. P. da Mota

Before we proposed an algebraic technics for the Hamiltonian approach to the evolution systems of partial differential equations, including systems with constraints. Here we further develop this approach and present the defining system of…

Mathematical Physics · Physics 2018-03-13 Victor Zharinov

We present a quantum algorithm for the microcanonical thermal pure quantum (TPQ) method, which has an advantage in evaluating thermodynamic quantities at finite temperatures, by combining with some recently developed techniques derived from…

Quantum Physics · Physics 2023-08-16 Kaito Mizukami , Akihisa Koga

We present here a new method for evaluating determinants -- the reduction method. Firstly, in the section 2, we apply it to third-order determinants and after, in the section 3, we generalize it to higher-order determinants. In the section…

Combinatorics · Mathematics 2011-09-06 Ricardo S. Vieira

Digital computers implement computations using circuits, as do many naturally occurring systems (e.g., gene regulatory networks). The topology of any such circuit restricts which variables may be physically coupled during the operation of a…

Statistical Mechanics · Physics 2023-07-26 David Hilton Wolpert , Artemy Kolchinsky

It is shown how the dimension of any arbitrary over-determined system of differential equations can be reduced, which makes the system suitable for numerical solution modeling. Specifically, over-determined equations of hydrodynamics are…

Mathematical Physics · Physics 2013-02-26 Maxim Zaytsev , Vyacheslav Akkerman

The thermal dynamics in thermo-mechanical systems exhibits a much slower time scale compared to the structural dynamics. In this work, we use the method of multiple scales to reduce the thermo-mechanical structural models with a…

Computational Engineering, Finance, and Science · Computer Science 2019-10-25 Shobhit Jain , Paolo Tiso

A computer-algebra aided method is carried out, for determining geometric objects associated to differential operators that satisfy the elliptic ansatz. This results in examples of Lame curves with double reduction and in the explicit…

Mathematical Physics · Physics 2008-04-24 J. Chris Eilbeck , Victor Z. Enolski , Emma Previato

In this work a rationalized algorithm for calculating the quotient of two complex numbers is presented which reduces the number of underlying real multiplications. The performing of a complex number division using the naive method takes 4…

Data Structures and Algorithms · Computer Science 2016-08-31 Aleksandr Cariow

This paper introduces a novel general-purpose algorithm for Pauli decomposition that employs matrix slicing and addition rather than expensive matrix multiplication, significantly accelerating the decomposition of multi-qubit matrices. In a…

Quantum Physics · Physics 2024-09-25 Lukas Hantzko , Lennart Binkowski , Sabhyata Gupta

This paper presents a method for the accurate and efficient computations on scalar, vector and tensor fields in three-dimensional spherical polar coordinates. The methods uses spin-weighted spherical harmonics in the angular directions and…

Numerical Analysis · Mathematics 2018-04-30 Geoff Vasil , Daniel Lecoanet , Keaton Burns , Jeff Oishi , Ben Brown

Derivative-based algorithms are ubiquitous in statistics, machine learning, and applied mathematics. Automatic differentiation offers an algorithmic way to efficiently evaluate these derivatives from computer programs that execute relevant…

Computation · Statistics 2022-03-01 Charles C. Margossian , Michael Betancourt
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