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In this paper, we investigate finite-horizon optimal density steering problems for discrete-time stochastic linear dynamical systems whose state probability densities can be represented as Gaussian Mixture Models (GMMs). Our goal is to…

Optimization and Control · Mathematics 2025-01-07 Isin M Balci , Efstathios Bakolas

Non-Gaussian quantum states are a known necessary resource for reaching a quantum advantage and for violating Bell inequalities in continuous variable systems. As one kind of manifestation of quantum correlations, Einstein-Podolsky-Rosen…

Quantum Physics · Physics 2023-12-15 Mingsheng Tian , Zihang Zou , Da Zhang , David Barral , Kamel Bencheikh , Qiongyi He , Feng-Xiao Sun , Yu Xiang

We study tests of quantum steering in which the trusted party does not have perfect control of their measurements. We report on steering inequalities that remain unaffected when introducing up to a threshold magnitude of measurement…

Quantum Physics · Physics 2025-02-25 Elna Svegborn , Nicola d'Alessandro , Otfried Gühne , Armin Tavakoli

The term Einstein-Podolsky-Rosen steering refers to a quantum correlation intermediate between entanglement and Bell nonlocality, which has been connected to another fundamental quantum property: measurement incompatibility. In the…

Quantum Physics · Physics 2017-11-08 Jukka Kiukas , Costantino Budroni , Roope Uola , Juha-Pekka Pellonpää

Symmetry is a powerful tool for understanding phases of matter in equilibrium. Quantum circuits with measurements have recently emerged as a platform for novel states of matter intrinsically out of equilibrium. Can symmetry be used as an…

Quantum Physics · Physics 2025-06-18 Zhi Li , Zhu-Xi Luo

We derive a new steering inequality based on a fine-grained uncertainty relation to capture EPR-steering for bipartite systems. Our steering inequality improves over previously known ones since it can experimentally detect all steerable…

Quantum Physics · Physics 2014-11-25 Tanumoy Pramanik , Marc Kaplan , Archan S Majumdar

Quantum steering is one of the most intriguing phenomena in quantum mechanics and is essential for understanding correlations in multi-body systems. Despite its importance, analytical results for coupled three-body oscillators remain…

Quantum Physics · Physics 2026-01-06 Ayoub Ghaba , Radouan Hab Arrih , Elhoussine Atmani , Abdallah Slaoui

Einstein-Podolsky-Rosen steering refers to the quantum phenomenon whereby the state of a system held by one party can be "steered" into different states at the will of another, distant, party by performing different local measurements.…

Quantum Physics · Physics 2019-06-12 Travis J. Baker , Sabine Wollmann , Geoff J. Pryde , Howard M. Wiseman

Exploiting the geometric nature of statistical divergences, we devise a way to define associated induced uncertainty measures for discrete and finite probability distributions. We also report new uncertainty measures and discuss their…

Quantum Physics · Physics 2021-06-29 Gautam Sharma , Sk Sazim

In this work, we investigate measurement incompatibility in general probabilistic theories (GPTs). We show several equivalent characterizations of compatible measurements. The first is in terms of the positivity of associated maps. The…

Quantum Physics · Physics 2022-11-21 Andreas Bluhm , Anna Jenčová , Ion Nechita

EPR-steering refers to the ability of one observer to convince a distant observer that they share entanglement by making local measurements. Determining which states allow a demonstration of EPR-steering remains an open problem in general.…

Quantum Physics · Physics 2020-02-26 Travis J. Baker , Howard M. Wiseman

Steerability is a characteristic nonlocal trait of quantum states lying in between entanglement and Bell nonlocality. A given quantum state is considered to be steerable if it violates a suitably chosen steering inequality. A quantum state…

Quantum steering is the central resource for one-sided device-independent quantum information. It is manipulated via one-way local operations and classical communication, such as local filtering on the trusted party. Here, we provide a…

Quantum Physics · Physics 2022-08-26 Huan-Yu Ku , Chung-Yun Hsieh , Shin-Liang Chen , Yueh-Nan Chen , Costantino Budroni

We give an introduction to Gaussian states and operations. A discussion of the entanglement properties of bipartite Gaussian states in terms of its covariance matrix follows. It is explained how entanglement can be witnessed using feasible…

Quantum Physics · Physics 2007-05-23 Janet Anders

Singularity or negativity of Glauber P-function is a widespread notion of nonclassicality, with important implications in quantum optics and with the character of an irreducible resource. Here we explore how P-nonclassicality may be…

Quantum Physics · Physics 2020-05-08 Massimo Frigerio , Claudio Destri , Stefano Olivares , Matteo G. A. Paris

We generalize standard credal set models for imprecise probabilities to include higher order credal sets -- confidences about confidences. In doing so, we specify how an agent's higher order confidences (credal sets) update upon observing…

Statistics Theory · Mathematics 2021-07-20 Justus Hibshman , Tim Weninger

We study a generalized notion of a homogeneous skew-product extension of a probability-preserving system in which the homogeneous space fibres are allowed to vary over the ergodic decomposition of the base. The construction of such…

Dynamical Systems · Mathematics 2009-11-11 Tim Austin

Quantum steering is an asymmetric form of quantum nonlocality where one can detect whether a measurement on one system can steer or change another distant system. It is well-known that there are quantum states that are entangled but…

Quantum Physics · Physics 2026-04-03 Shubhayan Sarkar

Deep sequence models are receiving significant interest in current machine learning research. By representing probability distributions that are fit to data using maximum likelihood estimation, such models can model data on general…

Systems and Control · Electrical Eng. & Systems 2024-09-09 Kristian Løvland , Bjarne Grimstad , Lars Struen Imsland

Stacking is a general approach for combining multiple models toward greater predictive accuracy. It has found various application across different domains, ensuing from its meta-learning nature. Our understanding, nevertheless, on how and…

Machine Learning · Computer Science 2019-01-29 Nino Arsov , Martin Pavlovski , Ljupco Kocarev