English

Picturing Indefinite Causal Structure

Other Computer Science 2017-01-04 v1

Abstract

Following on from the notion of (first-order) causality, which generalises the notion of being tracepreserving from CP-maps to abstract processes, we give a characterization for the most general kind of map which sends causal processes to causal processes. These new, second-order causal processes enable us to treat the input processes as 'local laboratories' whose causal ordering needs not be fixed in advance. Using this characterization, we give a fully-diagrammatic proof of a non-trivial theorem: namely that being causality-preserving on separable processes implies being 'completely' causality preserving. That is, causality is preserved even when the 'local laboratories' are allowed to have ancilla systems. An immediate consequence is that preserving causality is separable processes is equivalence to preserving causality for strongly non-signalling (a.k.a. localizable) processes.

Keywords

Cite

@article{arxiv.1701.00659,
  title  = {Picturing Indefinite Causal Structure},
  author = {Aleks Kissinger and Sander Uijlen},
  journal= {arXiv preprint arXiv:1701.00659},
  year   = {2017}
}

Comments

In Proceedings QPL 2016, arXiv:1701.00242

R2 v1 2026-06-22T17:39:54.564Z