Consistent circuits for indefinite causal order
- URL: http://arxiv.org/abs/2206.10042v2
- Date: Mon, 6 Feb 2023 17:10:24 GMT
- Title: Consistent circuits for indefinite causal order
- Authors: Augustin Vanrietvelde, Nick Ormrod, Hl\'er Kristj\'ansson, Jonathan
Barrett
- Abstract summary: A number of quantum processes have been proposed which are logically consistent, yet feature a cyclic causal structure.
Here we provide a method to construct a process with an exotic causal structure in a way that ensures, and makes clear why, it is consistent.
We show how several standard examples of exotic processes, including ones that violate causal inequalities, are among the class of processes that can be generated in this way.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Over the past decade, a number of quantum processes have been proposed which
are logically consistent, yet feature a cyclic causal structure. However, there
is no general formal method to construct a process with an exotic causal
structure in a way that ensures, and makes clear why, it is consistent. Here we
provide such a method, given by an extended circuit formalism. This only
requires directed graphs endowed with Boolean matrices, which encode basic
constraints on operations. Our framework (a) defines a set of elementary rules
for checking the validity of any such graph, (b) provides a way of constructing
consistent processes as a circuit from valid graphs, and (c) yields an
intuitive interpretation of the causal relations within a process and an
explanation of why they do not lead to inconsistencies. We display how several
standard examples of exotic processes, including ones that violate causal
inequalities, are among the class of processes that can be generated in this
way; we conjecture that this class in fact includes all unitarily extendible
processes.
Related papers
- Flow of dynamical causal structures with an application to correlations [0.9208007322096533]
Causal models capture cause-effect relations both qualitatively - via the graphical causal structure - and quantitatively.
Here, we introduce a tool - the flow of causal structures - to visualize and explore the dynamical aspect of classical-deterministic processes.
arXiv Detail & Related papers (2024-10-24T13:40:02Z) - A Canonicalization Perspective on Invariant and Equivariant Learning [54.44572887716977]
We introduce a canonicalization perspective that provides an essential and complete view of the design of frames.
We show that there exists an inherent connection between frames and canonical forms.
We design novel frames for eigenvectors that are strictly superior to existing methods.
arXiv Detail & Related papers (2024-05-28T17:22:15Z) - A complete logic for causal consistency [0.0]
We introduce graph types as a tool to examine causal structures over graphs in this model.
The properties of graph types are then used to prove completeness for causal consistency of a new causal logic that conservatively extends pomset logic.
Using the fact that causal logic conservatively extends pomset logic, we finish by giving a physically-meaningful interpretation of a separating statement between pomset and BV.
arXiv Detail & Related papers (2024-03-14T11:36:53Z) - Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse
Actions, Interventions and Sparse Temporal Dependencies [58.179981892921056]
This work introduces a novel principle for disentanglement we call mechanism sparsity regularization.
We propose a representation learning method that induces disentanglement by simultaneously learning the latent factors.
We show that the latent factors can be recovered by regularizing the learned causal graph to be sparse.
arXiv Detail & Related papers (2024-01-10T02:38:21Z) - Tractable Bounding of Counterfactual Queries by Knowledge Compilation [51.47174989680976]
We discuss the problem of bounding partially identifiable queries, such as counterfactuals, in Pearlian structural causal models.
A recently proposed iterated EM scheme yields an inner approximation of those bounds by sampling the initialisation parameters.
We show how a single symbolic knowledge compilation allows us to obtain the circuit structure with symbolic parameters to be replaced by their actual values.
arXiv Detail & Related papers (2023-10-05T07:10:40Z) - A Hybrid System for Systematic Generalization in Simple Arithmetic
Problems [70.91780996370326]
We propose a hybrid system capable of solving arithmetic problems that require compositional and systematic reasoning over sequences of symbols.
We show that the proposed system can accurately solve nested arithmetical expressions even when trained only on a subset including the simplest cases.
arXiv Detail & Related papers (2023-06-29T18:35:41Z) - Isotropic Gaussian Processes on Finite Spaces of Graphs [71.26737403006778]
We propose a principled way to define Gaussian process priors on various sets of unweighted graphs.
We go further to consider sets of equivalence classes of unweighted graphs and define the appropriate versions of priors thereon.
Inspired by applications in chemistry, we illustrate the proposed techniques on a real molecular property prediction task in the small data regime.
arXiv Detail & Related papers (2022-11-03T10:18:17Z) - Existence of processes violating causal inequalities on time-delocalised
subsystems [0.0]
It is possible to exist quantum and classical processes in which the operations performed by separate parties do not occur in a well-defined causal order.
We show that realisations on time-delocalised subsystems exist for all unitary extensions of tripartite processes.
arXiv Detail & Related papers (2022-01-27T22:34:02Z) - Ordering the processes with indefinite causal order [0.0]
We show a method of describing processes with indefinite causal order (ICO) by a definite causal order.
We do so by relabeling the processes that take place in the circuit in accordance with the basis of measurement of control qubit.
arXiv Detail & Related papers (2021-06-16T17:17:05Z) - Causal Expectation-Maximisation [70.45873402967297]
We show that causal inference is NP-hard even in models characterised by polytree-shaped graphs.
We introduce the causal EM algorithm to reconstruct the uncertainty about the latent variables from data about categorical manifest variables.
We argue that there appears to be an unnoticed limitation to the trending idea that counterfactual bounds can often be computed without knowledge of the structural equations.
arXiv Detail & Related papers (2020-11-04T10:25:13Z) - Quantum chicken-egg dilemmas: Delayed-choice causal order and the
reality of causal non-separability [0.0]
We show that causally indefinite processes can be realised with schemes where C serves only as a classical flag.
We demonstrate that quantum mechanics allows for phenomena where C can deterministically decide whether A comes before B or vice versa.
arXiv Detail & Related papers (2020-08-18T12:03:31Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.