scispace - formally typeset
Search or ask a question
Author

Robin Kaarsgaard

Other affiliations: University of Copenhagen
Bio: Robin Kaarsgaard is an academic researcher from University of Edinburgh. The author has contributed to research in topics: Computer science & Semantics (computer science). The author has an hindex of 6, co-authored 20 publications receiving 103 citations. Previous affiliations of Robin Kaarsgaard include University of Copenhagen.

Papers
More filters
Journal ArticleDOI
TL;DR: It is shown how additionally assuming the existence of countable joins on such inverse categories leads to a number of properties that are desirable when modeling reversible functional programming, notably morphism schemes for reversible recursion, a †-trace, and algebraic ω -compactness.

27 citations

Journal ArticleDOI
TL;DR: A categorical foundation for this class of languages based on inverse categories with joins is developed, which leads to a categorical semantics for structured reversible flowcharts, from which it is shown that a program inverter can be extracted.

17 citations

Journal Article
TL;DR: Structured reversible flowchart languages as discussed by the authors are a class of imperative reversible programming languages allowing for a simple diagrammatic representation of control flow built from a limited set of controlflow structures.
Abstract: Structured reversible flowchart languages is a class of imperative reversible programming languages allowing for a simple diagrammatic representation of control flow built from a limited set of control flow structures. This class includes the reversible programming language Janus (without recursion), as well as more recently developed reversible programming languages such as R-CORE and R-WHILE. In the present paper, we develop a categorical foundation for this class of languages based on inverse categories with joins. We generalize the notion of extensivity of restriction categories to one that may be accommodated by inverse categories, and use the resulting decisions to give a reversible representation of predicates and assertions. This leads to a categorical semantics for structured reversible flowcharts, which we show to be computationally sound and adequate, as well as equationally fully abstract with respect to the operational semantics under certain conditions.

14 citations

Book ChapterDOI
09 Jul 2020
TL;DR: Many threads of research in the area of foundations of reversible computing are reported below, giving particular emphasis to the results obtained in the framework of the European COST Action IC1405, entitled “Reversible Computation - Extending Horizons of Computing”, which took place in the years 2015–2019.
Abstract: Reversible computation allows computation to proceed not only in the standard, forward direction, but also backward, recovering past states. While reversible computation has attracted interest for its multiple applications, covering areas as different as low-power computing, simulation, robotics and debugging, such applications need to be supported by a clear understanding of the foundations of reversible computation. We report below on many threads of research in the area of foundations of reversible computing, giving particular emphasis to the results obtained in the framework of the European COST Action IC1405, entitled “Reversible Computation - Extending Horizons of Computing”, which took place in the years 2015–2019.

13 citations

Book ChapterDOI
16 Jul 2015
TL;DR: Previously, Soeken and Thomsen presented six basic semantics-preserving rules for rewriting reversible logic circuits, defined using the well-known diagrammatic notation of Feynman.
Abstract: Previously, Soeken and Thomsen presented six basic semantics-preserving rules for rewriting reversible logic circuits, defined using the well-known diagrammatic notation of Feynman. While this notation is both useful and intuitive for describing reversible circuits, its shortcomings in generality complicates the specification of more sophisticated and abstract rewriting rules.

9 citations


Cited by
More filters
Book ChapterDOI
01 Jan 1985
TL;DR: The first group of results in fixed point theory were derived from Banach's fixed point theorem as discussed by the authors, which is a nice result since it contains only one simple condition on the map F, since it is easy to prove and since it nevertheless allows a variety of applications.
Abstract: Formally we have arrived at the middle of the book. So you may need a pause for recovering, a pause which we want to fill up by some fixed point theorems supplementing those which you already met or which you will meet in later chapters. The first group of results centres around Banach’s fixed point theorem. The latter is certainly a nice result since it contains only one simple condition on the map F, since it is so easy to prove and since it nevertheless allows a variety of applications. Therefore it is not astonishing that many mathematicians have been attracted by the question to which extent the conditions on F and the space Ω can be changed so that one still gets the existence of a unique or of at least one fixed point. The number of results produced this way is still finite, but of a statistical magnitude, suggesting at a first glance that only a random sample can be covered by a chapter or even a book of the present size. Fortunately (or unfortunately?) most of the modifications have not found applications up to now, so that there is no reason to write a cookery book about conditions but to write at least a short outline of some ideas indicating that this field can be as interesting as other chapters. A systematic account of more recent ideas and examples in fixed point theory should however be written by one of the true experts. Strange as it is, such a book does not seem to exist though so many people are puzzling out so many results.

994 citations

BookDOI
01 Jan 2013
TL;DR: This research presents a meta-anatomy of decision-making in the context of knowledge representation, which aims to provide a scaffolding for future generations of scientists to understand and act on the structure of knowledge.
Abstract: David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen TU Dortmund University, Germany Madhu Sudan Microsoft Research, Cambridge, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max Planck Institute for Informatics, Saarbruecken, Germany

71 citations

Book ChapterDOI
01 Jan 2004

56 citations

Book ChapterDOI
06 Jul 2017
TL;DR: A rigorous quantitative formulation of Landauer’s Principle is used to develop the theory of Generalized Reversible Computing (GRC), which precisely characterizes the minimum requirements for a computation to avoid information loss and the consequent energy dissipation, showing that a much broader range of computations are, in fact, reversible than is acknowledged by traditional reversible computing theory.
Abstract: Information loss from a computation implies energy dissipation due to Landauer’s Principle Thus, increasing the amount of useful computational work that can be accomplished within a given energy budget will eventually require increasing the degree to which our computing technologies avoid information loss, ie, are logically reversible But the traditional definition of logical reversibility is actually more restrictive than is necessary to avoid information loss and energy dissipation due to Landauer’s Principle As a result, the operations that have traditionally been viewed as the atomic elements of reversible logic, such as Toffoli gates, are not really the simplest primitives that one can use for the design of reversible hardware Arguably, a complete theoretical framework for reversible computing should provide a more general, parsimonious foundation for practical engineering To this end, we use a rigorous quantitative formulation of Landauer’s Principle to develop the theory of Generalized Reversible Computing (GRC), which precisely characterizes the minimum requirements for a computation to avoid information loss and the consequent energy dissipation, showing that a much broader range of computations are, in fact, reversible than is acknowledged by traditional reversible computing theory This paper summarizes the foundations of GRC theory and briefly presents a few of its applications

36 citations

Book ChapterDOI
16 Apr 2018
TL;DR: One perspective on quantum algorithms is that they are classical algorithms having access to a special kind of memory with exotic properties, and the control flow notions of sequencing, conditionals, loops, and recursion are entirely classical.
Abstract: One perspective on quantum algorithms is that they are classical algorithms having access to a special kind of memory with exotic properties. This perspective suggests that, even in the case of quantum algorithms, the control flow notions of sequencing, conditionals, loops, and recursion are entirely classical. There is however, another notion of control flow, that is itself quantum. The notion of quantum conditional expression is reasonably well-understood: the execution of the two expressions becomes itself a superposition of executions. The quantum counterpart of loops and recursion is however not believed to be meaningful in its most general form.

33 citations