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The correlation matrices or tensors in the Bloch representation of density matrices are encoded with entanglement properties. In this paper, based on the Bloch representation of density matrices, we give some new separability criteria for…

Quantum Physics · Physics 2016-08-09 Shu-Qian Shen , Juan Yu , Ming Li , Shao-Ming Fei

A hierarchy of multimode uncertainty relations on the second moments of n pairs of canonical operators is derived in terms of quantities invariant under linear canonical (i.e. symplectic) transformations. Conditions for the separability of…

Quantum Physics · Physics 2013-05-29 Alessio Serafini

This paper considers a challenging problem of identifying a causal graphical model under the presence of latent variables. While various identifiability conditions have been proposed in the literature, they often require multiple pure…

Machine Learning · Statistics 2026-02-03 Seunghyun Lee , Yuqi Gu

Entanglement is fundamental inasmuch because it rephrases the quest for the classical-quantum demarcation line, and it also has potentially enormous practical applications in modern information technology. In this work, employing the…

Quantum Physics · Physics 2024-06-26 Xiaofen Huang , Tinggui Zhang , Naihuan Jing

Causal disentanglement aims to learn about latent causal factors behind data, holding the promise to augment existing representation learning methods in terms of interpretability and extrapolation. Recent advances establish identifiability…

Machine Learning · Computer Science 2024-12-25 Ryan Welch , Jiaqi Zhang , Caroline Uhler

We generalize entanglement detection with covariance matrices for an arbitrary set of observables. A generalized uncertainty relation is constructed using the covariance and commutation matrices, then a criterion is established by…

Quantum Physics · Physics 2018-06-12 Vinay Tripathi , Chandrashekar Radhakrishnan , Tim Byrnes

We present a novel approach for explaining Gaussian processes (GPs) that can utilize the full analytical covariance structure present in GPs. Our method is based on the popular solution concept of Shapley values extended to stochastic…

Machine Learning · Statistics 2023-05-25 Siu Lun Chau , Krikamol Muandet , Dino Sejdinovic

In this paper, we discuss the partial separability and its criteria problems of multipartite qubit mixed-states. First we strictly define what is the partial separability of a multipartite qubit system. Next we give a reduction way from…

Quantum Physics · Physics 2007-05-23 Zai-Zhe Zhong

Lower bounds for persistence probabilities of stationary Gaussian processes in discrete time are obtained under various conditions on the spectral measure of the process. Examples are given to show that the persistence probability can decay…

Probability · Mathematics 2016-02-02 Krishna M. , Manjunath Krishnapur

The persistent separability of certain quantum states, known as symmetric absolutely separable (SAS), under symmetry-preserving global unitary transformations is of key significance in the context of quantum resources for bosonic systems.…

Quantum Physics · Physics 2024-02-27 Eduardo Serrano-Ensástiga , Jérôme Denis , John Martin

A smooth function of the second moments of $N$ continuous variables gives rise to an uncertainty relation if it is bounded from below. We present a method to systematically derive such bounds by generalizing an approach applied previously…

Quantum Physics · Physics 2016-10-18 Spiros Kechrimparis , Stefan Weigert

This paper propose a novel decomposable graphical model to accommodate skew Gaussian graphical models. We encode conditional independence structure among the components of the multivariate closed skew normal random vector by means of a…

Methodology · Statistics 2013-09-23 Hamid Zareifard , Havard Rue , Majid Jafari Khaledi , Finn Lindgren

We revisit the application of different separability criteria by recourse to an exhaustive Monte Carlo exploration involving the pertinent state-space of pure and mixed states. The corresponding chain of implications of different criteria…

Quantum Physics · Physics 2009-11-10 J. Batle , A. R. Plastino , M. Casas , A. Plastino

The Schr{\"o}dinger-Robertson inequality generally provides a stronger bound on the product of uncertainties for two noncommuting observables than the Heisenberg uncertainty relation, and as such, it can yield a stricter separability…

Quantum Physics · Physics 2009-11-13 Hyunchul Nha

A necessary and sufficient condition for characterization and quantification of entanglement of any bipartite Gaussian state belonging to a special symmetry class is given in terms of classicality measures of one-party states. For Gaussian…

Quantum Physics · Physics 2009-11-10 M. C. de Oliveira

We present an encoding of a polynomial system into vanishing and non-vanishing constraints on almost-principal minors of a symmetric, principally regular matrix, such that the solvability of the system over some field is equivalent to the…

Statistics Theory · Mathematics 2021-03-04 Tobias Boege

We derive a fine-grained uncertainty relation for the measurement of two incompatible observables on a single quantum system of continuous variables, and show that continuous variable systems are more uncertain than discrete variable…

Quantum Physics · Physics 2015-10-19 Priyanka Chowdhury , Tanumoy Pramanik , Archan S. Majumdar

Based on the mutually unbiased bases, the mutually unbiased measurements and the general symmetric informationally complete positive-operator-valued measures, we propose three separability criteria for $d$-dimensional bipartite quantum…

Quantum Physics · Physics 2015-09-02 Shu-Qian Shen , Ming Li , Xue-Feng Duan

We formulate the necessary and sufficient conditions for the existence of a pair of maximally incompatible two-outcome measurements in a finite dimensional General Probabilistic Theory. The conditions are on the geometry of the state space,…

Quantum Physics · Physics 2017-08-16 Anna Jenčová , Martin Plávala

We extend the theory of d-separation to cases in which data instances are not independent and identically distributed. We show that applying the rules of d-separation directly to the structure of probabilistic models of relational data…

Artificial Intelligence · Computer Science 2014-01-07 Marc Maier , Katerina Marazopoulou , David Jensen
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