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This paper presents a technique to drive the state of a constrained nonlinear system to a specified target state in finite time, when the system suffers a partial loss in control authority. Our technique builds on a recent method to control…

Optimization and Control · Mathematics 2026-04-10 Ram Padmanabhan , Melkior Ornik

Particle-In-Cell codes are widely used for plasma physics simulations. It is often the case that particles within a computational cell need to be split to improve the statistics or, in the case of non-uniform meshes, to avoid the…

Computational Physics · Physics 2021-04-22 Roch Smets , Nicolas Aunais , ANdrea Ciardi , Matthieu Drouin , Martin Campos-Pino , Philip Deegan

Spherical particles confined to a sphere surface cannot pack densely into a hexagonal lattice without defects. In this study, we use hard particle Monte Carlo simulations to determine the effects of continuously deformable shape anisotropy…

Soft Condensed Matter · Physics 2026-01-01 Gabrielle N. Jones , Philipp W. A. Schönhöfer , Sharon C. Glotzer

In this paper, we study a discrete system of entities residing on a two-dimensional square grid. Each entity is modelled as a node occupying a distinct cell of the grid. The set of all $n$ nodes forms initially a connected shape $A$.…

Data Structures and Algorithms · Computer Science 2019-04-30 Abdullah Almethen , Othon Michail , Igor Potapov

This paper addresses the inverse obstacle scattering problem of simultaneously reconstructing the obstacle geometry and boundary conditions from multi-frequency near-field backscattering data. We first establish rigorous high-frequency…

Analysis of PDEs · Mathematics 2026-04-14 Jialei Li , Xiaodong Liu

The inverse problem we consider is to reconstruct the location and shape of buried obstacles in the lower half-space of an unbounded two-layered medium in two dimensions from phaseless far-field data. A main difficulty of this problem is…

Numerical Analysis · Mathematics 2021-05-26 Long Li , Jiansheng Yang , Bo Zhang , Haiwen Zhang

Shapes do not define a linear space. This paper explores the linear structure of deformations as a representation of shapes. This transforms shape optimization to a variant of optimal control. The numerical challenges of this point of view…

Optimization and Control · Mathematics 2022-03-15 Stephan Schmidt , Volker H. Schulz

In this paper, we consider the planted partition model, in which $n = ks$ vertices of a random graph are partitioned into $k$ "clusters," each of size $s$. Edges between vertices in the same cluster and different clusters are included with…

Data Structures and Algorithms · Computer Science 2017-08-28 Sam Cole , Shmuel Friedland , Lev Reyzin

If the phase retrieval problem can be solved by a method similar to that of solving a system of linear equations under the context of FFT, the time complexity of computer based phase retrieval algorithm would be reduced. Here I present such…

Numerical Analysis · Mathematics 2013-05-20 Yuan Sun

We consider the problem of recovering a signal from nonlinear transformations, under convex constraints modeling a priori information. Standard feasibility and optimization methods are ill-suited to tackle this problem due to the…

Optimization and Control · Mathematics 2020-06-16 Patrick L. Combettes , Zev. C. Woodstock

In typical microscopic approaches, particularly when pairing correlations are present, nuclei and nuclear fragments do not have well defined quantum numbers and symmetries should be restored. I present here a formalism for the simultaneous…

Nuclear Theory · Physics 2021-11-03 Aurel Bulgac

Topological defects, such as disclination lines in nematic liquid crystals, are fundamental to many physical systems and applications. In this work, we study the behavior of nematic disclinations in thin parallel-plate geometries with…

Soft Condensed Matter · Physics 2025-08-05 Yehonatan Tsubery , Hillel Aharoni

One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction. Its main part is the track reconstruction procedure which consists in looking for all tracks that elementary particles…

Machine Learning · Computer Science 2019-10-02 Dmitriy Baranov , Sergey Mitsyn , Pavel Goncharov , Gennady Ososkov

We numerically implement the variational approach for reconstruction in the inverse crack and cavity problems developed by one of the authors. The method is based on a suitably adapted free-discontinuity problem. Its main features are the…

Analysis of PDEs · Mathematics 2017-02-14 Wolfgang Ring , Luca Rondi

Noise is typically treated as the adversary of quantum information processing. For open quantum dynamics, however, dissipation is part of the target physics, creating a tension with fault-tolerant architectures designed to suppress…

Quantum Physics · Physics 2026-05-29 Sameer Dambal , Michael AD Taylor , Yu Zhang

The topic of this paper are integer programming models in which a subset of 0/1-variables encode a partitioning of a set of objects into disjoint subsets. Such models can be surprisingly hard to solve by branch-and-cut algorithms if the…

Optimization and Control · Mathematics 2011-10-18 Volker Kaibel , Matthias Peinhardt , Marc E. Pfetsch

We propose a path-based approach to program repair for imperative programs. Our repair framework takes as input a faulty program, a logic specification that is refuted, and a hint where the fault may be located. An iterative abstraction…

Programming Languages · Computer Science 2015-03-18 Heinz Riener , Rüdiger Ehlers , Görschwin Fey

Solving nesting problems or irregular strip packing problems is to position polygons in a fixed width and unlimited length strip, obeying polygon integrity containment constraints and non-overlapping constraints, in order to minimize the…

Optimization and Control · Mathematics 2017-07-25 Jeinny Peralta , Marina Andretta , José Fernando Oliveira

In this paper, we introduce the following problem in the theory of algorithmic self-assembly: given an input shape as the seed of a tile-based self-assembly system, design a finite tile set that can, in some sense, uniquely identify whether…

Computational Complexity · Computer Science 2010-06-16 Matthew J. Patitz , Scott M. Summers

Physics-informed neural networks have emerged as an alternative method for solving partial differential equations. However, for complex problems, the training of such networks can still require high-fidelity data which can be expensive to…

Machine Learning · Computer Science 2023-03-28 Wenqian Chen , Panos Stinis