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Related papers: Quantum Causal Unravelling

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Although the realization of useful quantum computers poses significant challenges, swift progress in emerging quantum technologies is making this goal realistically approachable. In this context, one of the essential resources is quantum…

Quantum Physics · Physics 2022-01-11 Valeria Saggio , Philip Walther

Perturbation theory is an important technique for reducing computational cost and providing physical insights in simulating quantum systems with classical computers. Here, we provide a quantum algorithm to obtain perturbative energies on…

Quantum Physics · Physics 2023-05-17 Kosuke Mitarai , Kiichiro Toyoizumi , Wataru Mizukami

We study the problem of deriving policies, or rules, that when enacted on a complex system, cause a desired outcome. Absent the ability to perform controlled experiments, such rules have to be inferred from past observations of the system's…

Machine Learning · Computer Science 2020-09-09 Kailash Budhathoki , Mario Boley , Jilles Vreeken

While spatial quantum correlations have been studied in great detail, much less is known about the genuine quantum correlations that can be exhibited by temporal processes. Employing the quantum comb formalism, processes in time can be…

Quantum Physics · Physics 2021-06-18 Simon Milz , Cornelia Spee , Zhen-Peng Xu , Felix A. Pollock , Kavan Modi , Otfried Gühne

Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means…

Quantum Physics · Physics 2018-04-04 Simon Milz , Felix A. Pollock , Thao P. Le , Giulio Chiribella , Kavan Modi

The capacity of distant parties to send signals to one another is a fundamental requirement in many information-processing tasks. Such ability is determined by the causal structure connecting the parties, and more generally, by the…

Quantum Physics · Physics 2022-08-31 Simon Milz , Jessica Bavaresco , Giulio Chiribella

Owing to the computational complexity of electronic structure algorithms running on classical digital computers, the range of molecular systems amenable to simulation remains tightly circumscribed even after many decades of work. Quantum…

Quantum Physics · Physics 2022-05-18 Alexis Ralli , Michael I. Williams , Peter V. Coveney

We discuss two qualities of quantum systems: various correlations existing between their subsystems and the distingushability of different quantum states. This is then applied to analysing quantum information processing. While quantum…

Quantum Physics · Physics 2015-05-13 Vlatko Vedral

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

We derive a general framework to identify genuinely multipartite entangled mixed quantum states in arbitrary-dimensional systems and show in exemplary cases that the constructed criteria are stronger than those previously known. Our…

Quantum Physics · Physics 2013-05-29 Marcus Huber , Florian Mintert , Andreas Gabriel , Beatrix C. Hiesmayr

Guided by the intuition of coherent superposition of causal relations, recent works presented quantum processes without classical common-cause and direct-cause explanation, that is, processes which cannot be written as probabilistic…

Emergence and causality are two fundamental concepts for understanding complex systems. They are interconnected. On one hand, emergence refers to the phenomenon where macroscopic properties cannot be solely attributed to the cause of…

Physics and Society · Physics 2024-02-27 Bing Yuan , Zhang Jiang , Aobo Lyu , Jiayun Wu , Zhipeng Wang , Mingzhe Yang , Kaiwei Liu , Muyun Mou , Peng Cui

Inference of causality in time series has been principally based on the prediction paradigm. Nonetheless, the predictive causality approach may overlook the simultaneous and reciprocal nature of causal interactions observed in real world…

Data Analysis, Statistics and Probability · Physics 2018-10-24 Albert C. Yang , Norden E. Huang , Chung-Kang Peng

Quantum mechanics has many counter-intuitive consequences which contradict our intuition which is based on classical physics. Here we discuss a special aspect of quantum mechanics, namely the possibility of entanglement between two or more…

Quantum Physics · Physics 2009-10-31 Martin B. Plenio , Vlatko Vedral

Quantum information processing is the emerging field that defines and realizes computing devices that make use of quantum mechanical principles, like the superposition principle, entanglement, and interference. In this review we study the…

Quantum Physics · Physics 2015-05-13 Harry Buhrman , Richard Cleve , Serge Massar , Ronald de Wolf

The future development of quantum technologies relies on creating and manipulating quantum systems of increasing complexity, with key applications in computation, simulation and sensing. This poses severe challenges in the efficient…

Entanglement is a fundamental aspect of quantum physics, both conceptually and for its many applications. Classifying an arbitrary multipartite state as entangled or separable -- a task referred to as the separability problem -- poses a…

Quantum computers provide an opportunity to efficiently sample from probability distributions that include non-trivial interference effects between amplitudes. Using a simple process wherein all possible state histories can be specified by…

Quantum Physics · Physics 2019-08-22 Davide Provasoli , Benjamin Nachman , Wibe A. de Jong , Christian W Bauer

Multipartite entanglement is the premier resource for quantum technologies. Yet, its exact quantification in the laboratory is notoriously challenging, typically requiring the full knowledge of high dimensional quantum states. Here, we…

Quantum Physics · Physics 2026-05-05 Francois Payn , Davide Girolami

Much of our experiments are designed to uncover the cause(s) and effect(s) behind a data generating mechanism (i.e., phenomenon) we happen to be interested in. Uncovering such relationships allows us to identify the true working of a…

Machine Learning · Computer Science 2023-07-11 M. Z. Naser
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