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We introduce a general scheme to realize perfect quantum state reconstruction and storage in systems of interacting qubits. This novel approach is based on the idea of controlling the residual interactions by suitable external controls…

Quantum Physics · Physics 2007-05-23 S. M. Giampaolo , F. Illuminati , A. Di Lisi , G. Mazzarella

The main goal of this paper is to propose a new quaternion total variation regularization model for solving linear ill-posed quaternion inverse problems, which arise from three-dimensional signal filtering or color image processing. The…

Numerical Analysis · Mathematics 2024-08-07 Xuan Liu , Zhigang Jia , Xiaoqing Jin

In simulations of partial differential equations using particle-in-cell (PIC) methods, it is often advantageous to resample the particle distribution function to increase simulation accuracy, reduce compute cost, and/or avoid numerical…

Finite difference schemes that preserve two conservation laws of a given partial differential equation can be found directly by a recently-developed symbolic approach. Until now, this has been used only for equations with quadratic…

Numerical Analysis · Mathematics 2019-07-31 Gianluca Frasca-Caccia , Peter E. Hydon

Quiver representations arise naturally in many areas across mathematics. Here we describe an algorithm for calculating the vector space of sections, or compatible assignments of vectors to vertices, of any finite-dimensional representation…

Representation Theory · Mathematics 2021-11-25 Anna Seigal , Heather A. Harrington , Vidit Nanda

Many differential equations with physical backgrounds are described as gradient systems, which are evolution equations driven by the gradient of some functionals, and such problems have energy conservation or dissipation properties. For…

Numerical Analysis · Mathematics 2023-08-07 Tomoya Kemmochi

DNA sequences encode critical genetic information, yet their variable length and discrete nature impede direct utilization in deep learning models. Existing DNA representation schemes convert sequences into numerical vectors but fail to…

Genomics · Quantitative Biology 2025-12-16 Zhiyuan Peng , Naifan Zhang , Yuanbo Tang , Yang Li

Recent sequential pattern mining methods have used the minimum description length (MDL) principle to define an encoding scheme which describes an algorithm for mining the most compressing patterns in a database. We present a novel…

Machine Learning · Statistics 2016-11-14 Jaroslav Fowkes , Charles Sutton

In this paper, we construct a semi-implicit finite difference method for the time dependent Poisson-Nernst-Planck system. Although the Poisson-Nernst-Planck system is a nonlinear system, the numerical method presented in this paper only…

Numerical Analysis · Mathematics 2019-01-17 Dongdong He , Kejia Pan

Random graphs with prescribed degree sequences have been widely used as a model of complex networks. Comparing an observed network to an ensemble of such graphs allows one to detect deviations from randomness in network properties. Here we…

Statistical Mechanics · Physics 2007-05-23 R. Milo , N. Kashtan , S. Itzkovitz , M. E. J. Newman , U. Alon

A new high-order conservative finite element method for Darcy flow is presented. The key ingredient in the formulation is a volumetric, residual-based, based on Lagrange multipliers in order to impose conservation of mass that does not…

Numerical Analysis · Mathematics 2017-07-03 Eduardo Abreu , Ciro Diaz , Juan Galvis , Marcus Sarkis

In this paper, we study a maximization problem on real sequences. More precisely, for a given sequence, we are interested in computing the supremum of the sequence and an index for which the associated term is maximal. We propose a general…

Optimization and Control · Mathematics 2026-03-03 Assalé Adjé

We consider a class of finite element approximations for fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. In our approach, we first solve a variational problem…

Numerical Analysis · Mathematics 2021-06-30 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

Conservation laws are key theoretical and practical tools for understanding, characterizing, and modeling nonlinear dynamical systems. However, for many complex systems, the corresponding conserved quantities are difficult to identify,…

Computational Physics · Physics 2023-08-23 Peter Y. Lu , Rumen Dangovski , Marin Soljačić

Traditional Quartet Puzzling algorithms use maximum likelihood methods to reconstruct quartet trees, and a puzzling algorithm to combine these quartets into a tree for the full collection of $n$ taxa. We propose a variation of Quartet…

Populations and Evolution · Quantitative Biology 2011-10-31 Joe Rusinko , Brian Hipp

The magnetic inverse source problem of reconstructing the positions and currents of very long parallel conductors is considered in a two-dimensional situation, with applications to power line measurements. The input data is the magnetic…

Mathematical Physics · Physics 2013-02-27 Martin Norgren

In conservation biology, phylogenetic diversity (PD) provides a way to quantify the impact of the current rapid extinction of species on the evolutionary `Tree of Life'. This approach recognises that extinction not only removes species but…

Populations and Evolution · Quantitative Biology 2022-04-13 Kerry Manson , Charles Semple , Mike Steel

The efficiency of locally generating unitary designs, which capture statistical notions of quantum pseudorandomness, lies at the heart of wide-ranging areas in physics and quantum information technologies. While there are extensive potent…

Quantum Physics · Physics 2024-12-30 Zimu Li , Han Zheng , Zi-Wen Liu

This paper examines several applications of principal component analysis (PCA) to physical systems. The first of these demonstrates that the principal components in a basis of appropriate system variables can be employed to identify…

Data Analysis, Statistics and Probability · Physics 2021-02-24 David Yevick

We develop the theory of Energy Conserving Descent (ECD) and introduce ECDSep, a gradient-based optimization algorithm able to tackle convex and non-convex optimization problems. The method is based on the novel ECD framework of…

Machine Learning · Computer Science 2023-06-02 G. Bruno De Luca , Alice Gatti , Eva Silverstein