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We study the fluctuations of the light emitted by two identical incoherent point sources in a disordered environment. The intensity-intensity correlation function and the speckle contrast, obtained after proper temporal and configurational…

Optics · Physics 2015-02-09 R. Carminati , G. Cwilich , L. S. Froufe-Pérez , J. J. Sáenz

In recent proposals for achieving optical super-resolution, variants of the Quantum Fisher Information (QFI) quantify the attainable precision. We find that claims about a strong enhancement of the resolution resulting from coherence…

Quantum Physics · Physics 2019-11-14 Zdeněk Hradil , Jaroslav Řeháček , Luis Sánchez-Soto , Berthold-Georg Englert

Various schemes have been proposed to overcome the drawback of the decoherence on quantum-enhanced parameter estimation. Here we suggest an alternative method, quantum feedback, to enhance the parameter precision of optimal quantum…

Quantum Physics · Physics 2015-06-24 Qiang Zheng , Li Ge , Yao Yao , Qi-jun Zhi

Transductive conformal prediction addresses the simultaneous prediction for multiple data points. Given a desired confidence level, the objective is to construct a prediction set that includes the true outcomes with the prescribed…

Machine Learning · Computer Science 2025-09-08 Arash Behboodi , Alvaro H. C. Correia , Fabio Valerio Massoli , Christos Louizos

This paper studies the tradeoff in privacy and utility in a single-trial multi-terminal guessing (estimation) framework using a system model that is inspired by index coding. There are $n$ independent discrete sources at a data curator.…

Information Theory · Computer Science 2020-06-19 Yucheng Liu , Ni Ding , Parastoo Sadeghi , Thierry Rakotoarivelo

Performance/security trade-off is widely noticed in CFI research, however, we observe that not every CFI scheme is subject to the trade-off. Motivated by the key observation, we ask three questions. Although the three questions probably…

Cryptography and Security · Computer Science 2021-01-12 Zhilong Wang , Peng Liu

In practical applications, data is used to make decisions in two steps: estimation and optimization. First, a machine learning model estimates parameters for a structural model relating decisions to outcomes. Second, a decision is chosen to…

Optimization and Control · Mathematics 2022-10-28 Samuel Tan , Peter I. Frazier

We investigate the tradeoff between the quality of an approximate version of a given measurement and the disturbance it induces in the measured quantum system. We prove that if the target measurement is a non-degenerate von Neumann…

Quantum Physics · Physics 2019-01-23 Anna-Lena K. Hashagen , Michael M. Wolf

The resolution of separation of two elementary signals forming a partially coherent superposition, defined by quantum Fisher information and normalised with respect to detection probabilities, is always limited by the resolution of…

Quantum Physics · Physics 2021-03-15 Zdeněk Hradil , Dominik Koutný , Jaroslav Řeháček

For decision making under uncertainty, min-max regret has been established as a popular methodology to find robust solutions. In this approach, we compare the performance of our solution against the best possible performance had we known…

Optimization and Control · Mathematics 2021-11-25 Marc Goerigk , Michael Hartisch

For sending unknown direction information, antiparallel spins contains more direction information than parallel spins(Gisin and Popescu, 1999, \textit{Phys. Rev. Lett.} 83, 432).In this paper, the optimal information-disturbance tradeoff…

Quantum Physics · Physics 2011-07-01 ShengLi Zhang , XuBo Zou , ChuanFeng Li , ChenHui Jin , GuangCan Guo

Precision measurements with quantum systems rely on our ability to trace the differences between experimental signals to variations in unknown physical parameters. In this Letter we derive the Fisher information and the ensuing Cramer-Rao…

Quantum Physics · Physics 2015-06-17 Søren Gammelmark , Klaus Mølmer

We study information-disturbance trade-off in generalized entanglement swapping protocols wherein starting from Bell pairs $\left(1,2\right)$ and $\left(3,4\right)$, one performs an arbitrary joint measurement on $\left(2,3\right)$, so that…

Quantum Physics · Physics 2020-11-25 Pratapaditya Bej , Arkaprabha Ghosal , Debarshi Das , Arup Roy , Somshubhro Bandyopadhyay

We study nonparametric change-point estimation from indirect noisy observations. Focusing on the white noise convolution model, we consider two classes of functions that are smooth apart from the change-point. We establish lower bounds on…

Statistics Theory · Mathematics 2007-06-13 A. Goldenshluger , A. Tsybakov , A. Zeevi

We study the prediction with expert advice setting, where the aim is to produce a decision by combining the decisions generated by a set of experts, e.g., independently running algorithms. We achieve the min-max optimal dynamic regret under…

Machine Learning · Computer Science 2022-08-09 Hakan Gokcesu , Suleyman S. Kozat

The thermodynamic uncertainty relation is an inequality stating that it is impossible to attain higher precision than the bound defined by entropy production. In statistical inference theory, information inequalities assert that it is…

Statistical Mechanics · Physics 2019-06-26 Yoshihiko Hasegawa , Tan Van Vu

Estimating entropy production from real observation data can be difficult due to finite resolution in both space and time and finite measurement statistics. We characterize the statistical error introduced by finite sample size and compare…

Statistical Mechanics · Physics 2025-04-09 Jonas H. Fritz , Benjamin Ertel , Udo Seifert

Incompatibility of certain measurements -- impossibility of obtaining deterministic outcomes simultaneously -- is a well known property of quantum mechanics. This feature can be utilized in many contexts, ranging from Bell inequalities to…

Quantum Physics · Physics 2018-03-14 Martin Plesch , Matej Pivoluska

While the accuracy-fairness trade-off has been frequently observed in the literature of fair machine learning, rigorous theoretical analyses have been scarce. To demystify this long-standing challenge, this work seeks to develop a…

Machine Learning · Computer Science 2023-10-20 Hua Tang , Lu Cheng , Ninghao Liu , Mengnan Du

We address the problem of maximizing Gain from Trade (GFT) in repeated buyer-seller exchanges subject to global budget balance constraints. While this problem is well-understood in purely adversarial and stochastic settings, these…

Computer Science and Game Theory · Computer Science 2026-05-12 Anna Lunghi , Matteo Castiglioni , Alberto Marchesi