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Machine learning techniques, notably various deep neural network methods, are instrumental in processing extensive and intricate data sets in engineering and scientific fields. This paper shows how deep neural networks can inversely design…

Optics · Physics 2026-05-05 Ali Mohajer Hejazi , Vincent Ginis

This paper investigates some issues arising in categorical models of reversible logic and computation. Our claim is that the structural (coherence) isomorphisms of these categorical models, although generally overlooked, have decidedly…

Category Theory · Mathematics 2013-04-29 Peter Hines

Petri nets are a mathematical language for modeling and reasoning about distributed systems. In this paper we propose an approach to Petri nets for embedding reversibility, i.e., the ability of reversing an executed sequence of operations…

Logic in Computer Science · Computer Science 2020-10-09 Anna Philippou , Kyriaki Psara

Uncovering the origin of the arrow of time remains a fundamental scientific challenge. Within the framework of statistical physics, this problem was inextricably associated with the second law of thermodynamics, which declares that entropy…

Quantum Physics · Physics 2018-02-27 G. B. Lesovik , I. A. Sadovskyy , M. V. Suslov , A. V. Lebedev , V. M. Vinokur

Quantum models of computation are widely believed to be more powerful than classical ones. Efforts center on proving that, for a given problem, quantum algorithms are more resource efficient than any classical one. All this, however,…

Quantum Physics · Physics 2022-05-16 Jacques Carette , Gerardo Ortiz , Amr Sabry

Retroreflectors are optical devices that reverse the direction of incident beams of light. Here we present a collection of billiard type retroreflectors consisting of four objects; three of them are asymptotically perfect retroreflectors,…

Dynamical Systems · Mathematics 2010-05-20 Alexander Plakhov

This paper presents an efficient reversible algorithm for linear regression, both with and without ridge regression. Our reversible algorithm matches the asymptotic time and space complexity of standard irreversible algorithms for this…

Data Structures and Algorithms · Computer Science 2021-12-01 Erik D. Demaine , Jayson Lynch , Jiaying Sun

This article provides an alternate characterization of dagger categories, which are central to the study of categorical quantum mechanics, in terms of inner product categories. An inner product category is an "achiral involutive" category…

Category Theory · Mathematics 2026-03-31 Robin Cockett , Durgesh Kumar , Priyaa Varshinee Srinivasan

We study inverse optimization (IO), where the goal is to use a parametric optimization program as the hypothesis class to infer relationships between input-decision pairs. Most of the literature focuses on learning only the objective…

Optimization and Control · Mathematics 2025-05-22 Ke Ren , Peyman Mohajerin Esfahani , Angelos Georghiou

We examine the optical properties of a system of nano and micro particles of varying size, shape, and material (including metals and dielectrics, and sub-wavelength and super-wavelength regimes). Training data is generated by numerically…

Quantum computer requires quantum arithmetic. The sophisticated design of a reversible arithmetic logic unit (reversible ALU) for quantum arithmetic has been investigated in this letter. We provide explicit construction of reversible ALU…

Hardware Architecture · Computer Science 2011-07-21 Rigui zhou , Yang shi , Manqun Zhang

Inverse design refers to the problem of optimizing the input of an objective function in order to enact a target outcome. For many real-world engineering problems, the objective function takes the form of a simulator that predicts how the…

Reversible computing is a concept reflecting physical reversibility. Until now several reversible systems have been investigated. In a series of papers Kenichi Morita defines the rotary element RE, that is a reversible logic element. By…

Other Computer Science · Computer Science 2015-03-17 Serban E. Vlad

We consider the problem of training generative models with deep neural networks as generators, i.e. to map latent codes to data points. Whereas the dominant paradigm combines simple priors over codes with complex deterministic models, we…

Machine Learning · Statistics 2017-07-31 Yannic Kilcher , Aurélien Lucchi , Thomas Hofmann

One of the well-known results in concurrency theory concerns the relationship between event structures and occurrence nets: an occurrence net can be associated with a prime event structure, and vice versa. More generally, the relationships…

Logic in Computer Science · Computer Science 2019-10-25 Hernán Melgratti , Claudio Antares Mezzina , Iain Phillips , G. Michele Pinna , Irek Ulidowski

Reversible computation opens up the possibility of overcoming some of the hardware's current physical limitations. It also offers theoretical insights, as it enriches multiple paradigms and models of computation, and sometimes…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-15 Clément Aubert , Ioana Cristescu

The spread of the time arrows from the environment to an observed subsystem is followed within a harmonic model. A similarity is pointed out between irreversibility and a phase with spontaneously broken symmetry. The causal structure of…

High Energy Physics - Theory · Physics 2012-06-26 Janos Polonyi

We study a class of realistic computer vision settings wherein one can influence the design of the objects being recognized. We develop a framework that leverages this capability to significantly improve vision models' performance and…

Computer Vision and Pattern Recognition · Computer Science 2020-12-23 Hadi Salman , Andrew Ilyas , Logan Engstrom , Sai Vemprala , Aleksander Madry , Ashish Kapoor

Using simultaneously two operator identities, we consider the inversion of the convolution operators on a rectangular. The structure of the inverse operators and of some corresponding forms, which are important in signal processing, is…

Classical Analysis and ODEs · Mathematics 2017-01-31 Alexander Sakhnovich

Functional soft materials, comprising colloidal and molecular building blocks that self-organize into complex structures as a result of their tunable interactions, enable a wide array of technological applications. Inverse methods provide…

Soft Condensed Matter · Physics 2020-04-13 Zachary M. Sherman , Michael P. Howard , Beth A. Lindquist , Ryan B. Jadrich , Thomas M. Truskett