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We show that any Petz $f$-divergence (where $f$ is operator convex) between quantum states admits a universal $\chi^2$-mixture representation: the distinguishability of $\rho$ from $\sigma$ is obtained as a positive superposition of…

Quantum Physics · Physics 2025-12-23 Domingos S. P. Salazar

Inverse problems and, in particular, inferring unknown or latent parameters from data are ubiquitous in engineering simulations. A predominant viewpoint in identifying unknown parameters is Bayesian inference where both prior information…

Computation · Statistics 2022-08-31 Vahid Keshavarzzadeh , Robert M. Kirby , Akil Narayan

Quantum Fourier transformation is important in many quantum algorithms. In this paper, we generalize quantum Fourier transformation over the Abelian group $\mathbb{Z}_N$ from two different points to get more efficient unitary…

Quantum Physics · Physics 2017-12-06 Changpeng Shao

Quantum measurements are inherently probabilistic and quantum theory often forbids to precisely predict the outcomes of simultaneous measurements. This phenomenon is captured and quantified through uncertainty relations. Although studied…

Quantum Physics · Physics 2023-10-30 Carlos de Gois , Kiara Hansenne , Otfried Gühne

The Thermodynamic Uncertainty Relation (TUR) is a lower bound for the variance of a current as a function of the average entropy production and average current. Depending on the assumptions, one obtains different versions of the TUR. For…

Statistical Mechanics · Physics 2023-01-04 Domingos S. P. Salazar

In our earlier work math.QA/9808015 some results on integral representations of functions in quantum disc were announced. It was then shown in math.QA/9808037 that the validity of those results is related to the invariance of kernels of…

Quantum Algebra · Mathematics 2007-05-23 D. Shklyarov , S. Sinel'shchikov , L. Vaksman

Uncertainty relation lies at the heart of quantum mechanics, characterizing the incompatibility of non-commuting observables in the preparation of quantum states. An important question is how to improve the lower bound of uncertainty…

Quantum Physics · Physics 2017-05-25 Qiu-Cheng Song , Jun-Li Li , Guang-Xiong Peng , Cong-Feng Qiao

Quantum uncertainty relations have deep-rooted significance on the formalism of quantum mechanics. Heisenberg's uncertainty relations attracted a renewed interest for its applications in quantum information science. Robertson derived a…

Quantum Physics · Physics 2023-02-16 Md. Manirul Ali

Reliable predictions of nuclear properties are needed as much to answer fundamental science questions as in applications such as reactor physics or data evaluation. Nuclear density functional theory is currently the only microscopic, global…

Nuclear Theory · Physics 2015-01-23 N. Schunck , J. D. McDonnell , D. Higdon , J. Sarich , S. Wild

Textbook quantum mechanics treats time as a classical parameter, and not as a quantum observable with an associated Hermitian operator. For this reason, to make sense of usual time-energy uncertainty relations such as $\Delta {t}\Delta…

Quantum Physics · Physics 2021-12-08 Matteo Fadel , Lorenzo Maccone

Quantum measurement and quantum operation theory is developed here by taking the relational properties among quantum systems, instead of the independent properties of a quantum system, as the most fundamental elements. By studying how the…

Quantum Physics · Physics 2021-04-20 Jianhao M. Yang

The uncertainty principle sets limit on our ability to predict the values of two incompatible observables measured on a quantum particle simultaneously. This principle can be stated in various forms. In quantum information theory, it is…

Quantum Physics · Physics 2018-09-27 H. Dolatkhah , S. Haseli , S. Salimi , S. A. Khorashad

We present a new uncertainty relation by defining a measure of uncertainty based on skew information. For bipartite systems, we establish uncertainty relations with the existence of a quantum memory. A general relation between quantum…

Quantum Physics · Physics 2017-01-10 Zhihao Ma , Zhihua Chen , Shaoming Fei

This study investigates pseudo-Hermitian quantum mechanics, where the Hamiltonian satisfies a modified Hermiticity condition. We extend the uncertainty relation for such systems, demonstrating its equivalence to the standard Hermitian case…

Quantum Physics · Physics 2025-08-11 Boubakeur Khantoul , Bilel Hamil , Amar Benchikha

Covariate shift occurs prevalently in practice, where the input distributions of the source and target data are substantially different. Despite its practical importance in various learning problems, most of the existing methods only focus…

Machine Learning · Statistics 2023-10-20 Xingdong Feng , Xin He , Caixing Wang , Chao Wang , Jingnan Zhang

We introduce a novel time-energy uncertainty relation within the context of restarts in monitored quantum dynamics. Initially, we investigate the concept of ``first hitting time'' in quantum systems using an IBM quantum computer and a…

Statistical Mechanics · Physics 2025-01-07 Ruoyu Yin , Qingyuan Wang , Sabine Tornow , Eli Barkai

Uncertainty quantification (UQ) is an important component of molecular property prediction, particularly for drug discovery applications where model predictions direct experimental design and where unanticipated imprecision wastes valuable…

Machine Learning · Computer Science 2020-05-21 Lior Hirschfeld , Kyle Swanson , Kevin Yang , Regina Barzilay , Connor W. Coley

The quantum-mechanical framework in which observables are associated with Hermitian operators is too narrow to discuss measurements of such important physical quantities as elapsed time or harmonic-oscillator phase. We introduce a broader…

Quantum Physics · Physics 2009-10-28 Samuel L. Braunstein , Carlton M. Caves , G. J. Milburn

In this paper, we have given a new definition of continuous fractional wavelet transform in $\mathbb{R}^N$, namely the multidimensional fractional wavelet transform (MFrWT) and studied some of the basic properties along with the inner…

Functional Analysis · Mathematics 2022-03-02 Navneet Kaur , Bivek Gupta , Amit K. Verma

Lecture notes from the course given by Professor Julia Kempe at the summer school "Statistical physics of Machine Learning" in Les Houches. The notes discuss the so-called NTK approach to problems in machine learning, which consists of…

Machine Learning · Computer Science 2023-07-07 Francesco Cagnetta , Deborah Oliveira , Mahalakshmi Sabanayagam , Nikolaos Tsilivis , Julia Kempe
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