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Related papers: Randomness from causally independent processes

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We develop an extension of the process matrix (PM) framework for correlations between quantum operations with no causal order that allows multiple rounds of information exchange for each party compatibly with the assumption of well-defined…

Quantum Physics · Physics 2021-01-27 Timothée Hoffreumon , Ognyan Oreshkov

The causal effects activated by a quantum interaction are studied, modelling the last one as a bipartite unitary channel. The two parties, say Alice and Bob, can use the channel to exchange messages -- i.e. to signal. On the other hand, the…

Quantum Physics · Physics 2025-05-21 Kathleen Barsse , Paolo Perinotti , Alessandro Tosini , Leonardo Vaglini

Quantum mechanics allows the occurrence of events without having any definite causal order. Here, it is shown that the application of two different thermal channels in the causally inseparable order can enhance the potential to extract…

Quantum Physics · Physics 2020-09-23 Tamal Guha , Mir Alimuddin , Preeti Parashar

The capability of a given channel to communicate information is, a priori, distinct from its capability to distribute shared randomness. In this article we define randomness distribution capacities of quantum channels assisted by forward,…

Quantum Physics · Physics 2018-05-22 Raul Garcia-Patron , William Matthews , Andreas Winter

Randomness can help one to implement quantum maps that cannot be realized in a deterministic fashion. Recently, it was discovered that explicitly treating a randomness source as a quantum system could double the efficiency as a catalyst for…

Quantum Physics · Physics 2021-03-12 Seok Hyung Lie , Hyunseok Jeong

We develop the resource theory of private randomness extraction in the distributed and device-dependent scenario. We begin by introducing the notion of independent random bits, which are bipartite states containing ideal private randomness…

Quantum Physics · Physics 2019-10-24 Dong Yang , Karol Horodecki , Andreas Winter

Bell non-local correlations cannot be naturally explained in a fixed causal structure. This serves as a motivation for considering models where no global assumption is made beyond logical consistency. The assumption of a fixed causal order…

Quantum Physics · Physics 2016-04-06 Ämin Baumeler , Stefan Wolf

Quantum theory features several phenomena which can be considered as resources for information processing tasks. Some of these effects, such as entanglement, arise in a nonlocal scenario, where a quantum state is distributed between…

Quantum Physics · Physics 2024-07-22 Martin Plávala , Otfried Gühne

Causality is omnipresent in scientists' verbalisations of their understanding, even though we have no formal consensual scientific definition for it. In Automata Networks, it suffices to say that automata "influence" one another to…

Other Computer Science · Computer Science 2016-10-28 Mathilde Noual

In a Bell experiment, it is natural to seek a causal account of correlations wherein only a common cause acts on the outcomes. For this causal structure, Bell inequality violations can be explained only if causal dependencies are modelled…

In a recent series of works [Ebler et al. Phys. Rev. Lett. 120, 120502 (2018); arXiv:1809.06655v2; arXiv:1810.10457v2], it has been proposed that the quantum superposition of causal order -- the quantum switch -- may offer an enhancement of…

Quantum Physics · Physics 2019-06-24 Philippe Allard Guérin , Giulia Rubino , Časlav Brukner

We introduce probability estimation, a broadly applicable framework to certify randomness in a finite sequence of measurement results without assuming that these results are independent and identically distributed. Probability estimation…

Quantum Physics · Physics 2018-11-30 Yanbao Zhang , Emanuel Knill , Peter Bierhorst

Randomness in Bell test data can be device-independently certified by Bell's theorem without placing assumptions about the experimental devices. The device-independent randomness has very demanding requirement about the experimental devices…

Quantum Physics · Physics 2021-04-21 Xing Chen , Kai Redeker , Robert Garthoff , Wenjamin Rosenfeld , Jörg Wrachtrup , Ilja Gerhardt

An operational probabilistic theory where all systems are classical, and all pure states of composite systems are entangled, is constructed. The theory is endowed with a rule for composing an arbitrary number of systems, and with a…

Quantum Physics · Physics 2022-01-24 Giacomo Mauro D'Ariano , Marco Erba , Paolo Perinotti

Causal inference uses observations to infer the causal structure of the data generating system. We study a class of functional models that we call Time Series Models with Independent Noise (TiMINo). These models require independent residual…

Machine Learning · Statistics 2016-08-18 Jonas Peters , Dominik Janzing , Bernhard Schölkopf

We identify general conditions under which regenerative processes with dependent cycles and cycle lengths are asymptotically independent. The result is applied to various models. In particular, independent L\'evy processes with dependent…

Probability · Mathematics 2017-11-22 Royi Jacobovic , Offer Kella

We present an end-to-end and practical randomness amplification and privatisation protocol based on Bell tests. This allows the building of device-independent random number generators which output (near-)perfectly unbiased and private…

Quantum Physics · Physics 2023-04-05 Cameron Foreman , Sherilyn Wright , Alec Edgington , Mario Berta , Florian J. Curchod

In this paper we investigate properties of several randomness generation protocols in the device independent framework. Using Bell-type inequalities it is possible to certify that the numbers generated by an untrusted device are indeed…

Quantum Physics · Physics 2013-09-25 Piotr Mironowicz , Marcin Pawłowski

It is shown that a random binary process with impulse-like autocorrelation can be generated by randomizing the length of symbols occurring in a random Bernoulli process. Such randomization is achieved by random (or judiciously designed…

Signal Processing · Electrical Eng. & Systems 2020-06-30 W. J. Szajnowski

We introduce a method to rigorously draw causal inferences---inferences immune to all possible confounding---from genetic data that include parents and offspring. Causal conclusions are possible with these data because the natural…

Methodology · Statistics 2024-03-12 Stephen Bates , Matteo Sesia , Chiara Sabatti , Emmanuel Candes
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