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Sequential quantum information processing may lie in the peaceful coexistence of no-go theorems on quantum operations, such as the no-cloning theorem, the monogamy of correlations, and the no-signalling principle. In this work, we…

Quantum Physics · Physics 2024-11-25 Hanwool Lee , Kieran Flatt , Joonwoo Bae

This work presents a comparison for the performance of sequential sorting algorithms under four different modes of execution, the sequential processing mode, a conventional multi-threading implementation, multi-threading with OpenMP Library…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-09-07 Mohammad Fasha

We study quantum causal inference in a set-up proposed by Ried et al. [Nat. Phys. 11, 414 (2015)] in which a common-cause scenario can be mixed with a cause-effect scenario, and for which it was found that quantum mechanics can bring an…

Quantum Physics · Physics 2019-12-24 Jonas Kübler , Daniel Braun

Requiring that the causal structure between different parties is well-defined imposes constraints on the correlations they can establish, which define so-called causal correlations. Some of these are known to have a "dynamical" causal order…

Quantum Physics · Physics 2025-11-13 Raphaël Mothe , Alastair A. Abbott , Cyril Branciard

Methods to find counterfactual explanations have predominantly focused on one step decision making processes. In this work, we initiate the development of methods to find counterfactual explanations for decision making processes in which…

Machine Learning · Computer Science 2021-10-28 Stratis Tsirtsis , Abir De , Manuel Gomez-Rodriguez

We consider the problem of optimally discriminating two Pauli channels in the minimax strategy, maximizing the smallest of the probabilities of correct identification of the channel. We find the optimal input state at the channel and show…

Quantum Physics · Physics 2009-11-11 G. Mauro D'Ariano , Massimiliano F. Sacchi , Jonas Kahn

To make good decisions in the real world people need efficient planning strategies because their computational resources are limited. Knowing which planning strategies would work best for people in different situations would be very useful…

Artificial Intelligence · Computer Science 2021-02-02 Saksham Consul , Lovis Heindrich , Jugoslav Stojcheski , Falk Lieder

We present an efficient tensor-network based algorithm for finding the optimal adaptive quantum channel discrimination strategies inspired by recently developed numerical methods in quantum metrology to find the optimal adaptive channel…

Quantum Physics · Physics 2026-02-11 Stanisław Sieniawski , Rafał Demkowicz-Dobrzański

Quantum channels breaking entanglement, incompatibility, or nonlocality are defined as such because they are not useful for entanglement-based, one-sided device-independent, or device-independent quantum information processing,…

We consider causal models with two observed variables and one latent variables, each variable being discrete, with the goal of characterizing the possible distributions on outcomes that can result from controlling one of the observed…

Information Theory · Computer Science 2021-03-05 Kevin Shu

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. Causal…

Quantum Physics · Physics 2022-03-04 Stanislav Filatov , Marcis Auzinsh

We develop a semidefinite programming method for the optimization of quantum networks, including both causal networks and networks with indefinite causal structure. Our method applies to a broad class of performance measures, defined…

Quantum Physics · Physics 2018-05-01 Giulio Chiribella , Daniel Ebler

A central problem in cognitive science and behavioural neuroscience as well as in machine learning and artificial intelligence research is to ascertain whether two or more decision makers (be they brains or algorithms) use the same…

Computer Vision and Pattern Recognition · Computer Science 2020-12-21 Robert Geirhos , Kristof Meding , Felix A. Wichmann

The accurate and reliable characterization of quantum dynamical processes underlies efforts to validate quantum technologies, where discrimination between competing models of observed behaviors inform efforts to fabricate and operate qubit…

Quantum Physics · Physics 2016-10-31 Eugene Dumitrescu , Travis S. Humble

A group of transition probability functions form a Shannon's channel whereas a group of truth functions form a semantic channel. Label learning is to let semantic channels match Shannon's channels and label selection is to let Shannon's…

Machine Learning · Computer Science 2018-05-04 Chenguang Lu

Bidirectional devices are devices for which the roles of the input and output ports can be exchanged. Mathematically, these devices are described by bistochastic quantum channels, namely completely positive linear maps that are both…

Quantum Physics · Physics 2026-02-03 Luca Apadula , Alessandro Bisio , Giulio Chiribella , Paolo Perinotti , Kyrylo Simonov

Dynamics of many-qubit systems, that may correspond to computational processing with quantum systems, can be efficiently and generally approximated by a sequence of two- and single-qubit gates. In practical applications, however, a quantum…

Quantum Physics · Physics 2018-12-06 Joonwoo Bae , Tanmay Singal

Making judicious channel access and transmission scheduling decisions is essential for improving performance as well as energy and spectral efficiency in multichannel wireless systems. This problem has been a subject of extensive study in…

Machine Learning · Computer Science 2015-04-07 Yang Liu , Mingyan Liu

We consider conditions that allow us to find an optimal strategy for sequential decisions from a given data situation. For the case where all interventions are unconditional (atomic), identifiability has been discussed by Pearl & Robins…

Artificial Intelligence · Computer Science 2020-04-28 Philip Dawid , Vanessa Didelez

A sequential training method for large-scale feedforward neural networks is presented. Each layer of the neural network is decoupled and trained separately. After the training is completed for each layer, they are combined together. The…

Machine Learning · Computer Science 2019-05-21 Jongrae Kim