Compositional Reversible Computation

被引:0
|
作者
Carette, Jacques [1 ]
Heunen, Chris [2 ]
Kaarsgaard, Robin [3 ]
Sabry, Amr [4 ]
机构
[1] McMaster Univ, Hamilton, ON, Canada
[2] Univ Edinburgh, Edinburgh, Midlothian, Scotland
[3] Univ Southern Denmark, Odense, Denmark
[4] Indiana Univ, Bloomington, IN 47405 USA
来源
关键词
Rig Categories; Information Effects; Quantum Computing; QUANTUM; INFORMATION;
D O I
10.1007/978-3-031-62076-8_2
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Reversible computing is motivated by both pragmatic and foundational considerations arising from a variety of disciplines. We take a particular path through the development of reversible computation, emphasizing compositional reversible computation. We start from a historical perspective, by reviewing those approaches that developed reversible extensions of lambda-calculi, Turing machines, and communicating process calculi. These approaches share a common challenge: computations made reversible in this way do not naturally compose locally. We then turn our attention to computational models that eschew the detour via existing irreversible models. Building on an original analysis by Landauer, the insights of Bennett, Fredkin, and Toffoli introduced a fresh approach to reversible computing in which reversibility is elevated to the status of the main design principle. These initial models are expressed using low-level bit manipulations, however. Abstracting from the low-level of the Bennett-Fredkin-Toffoli models and pursuing more intrinsic, typed, and algebraic models, naturally leads to rig categories as the canonical model for compositional reversible programming. The categorical model reveals connections to type isomorphisms, symmetries, permutations, groups, and univalent universes. This, in turn, paves the way for extensions to reversible programming based on monads and arrows. These extensions are shown to recover conventional irreversible programming, a variety of reversible computational effects, and more interestingly both pure (measurement-free) and measurement-based quantum programming.
引用
收藏
页码:10 / 27
页数:18
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