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We introduce a Poissonization method to study the coalescent structure of uniform samples from branching processes. This method relies on the simple observation that a uniform sample of size $k$ taken from a random set with positive…

Probability · Mathematics 2021-06-24 Samuel G. G. Johnston , Amaury Lambert

Boson sampling stands out as a promising approach toward experimental demonstration of quantum computational advantage. However, the presence of physical noise in near-term experiments hinders the realization of the quantum computational…

Quantum Physics · Physics 2025-09-30 Byeongseon Go , Changhun Oh , Hyunseok Jeong

Analyzing the properties of complex quantum systems is crucial for further development of quantum devices, yet this task is typically challenging and demanding with respect to required amount of measurements. A special attention to this…

Systems switching between different dynamical phases is an ubiquitous phenomenon. The general understanding of such a process is limited. To this end, we present a general expression that captures fluctuations of a system exhibiting a…

Statistical Mechanics · Physics 2024-12-05 Ion Santra , Kristian Stølevik Olsen , Deepak Gupta

In Bayesian nonparametric inference, random discrete probability measures are commonly used as priors within hierarchical mixture models for density estimation and for inference on the clustering of the data. Recently, it has been shown…

Statistics Theory · Mathematics 2012-11-26 Stefano Favaro , Antonio Lijoi , Igor Prünster

The photon-number distribution between two parts of a given volume is found for an arbitrary photon statistics. This problem is related to the interaction of a light beam with a macroscopic device, for example a diaphragm, that separates…

Quantum Physics · Physics 2016-08-09 Aleksey V. Ilyin

We study the dynamics of a class of two dimensional stochastic processes, depending on two parameters, which may be interpreted as two different temperatures, respectively associated to interfacial and to bulk noise. Special lines in the…

Statistical Mechanics · Physics 2009-10-31 J-M Drouffe , C Godreche

Bayesian inference provides a principled way of estimating the parameters of a stochastic process that is observed discretely in time. The overdamped Brownian motion of a particle confined in an optical trap is generally modelled by the…

Data Analysis, Statistics and Probability · Physics 2017-02-01 Sudipta Bera , Shuvojit Paul , Rajesh Singh , Dipanjan Ghosh , Avijit Kundu , Ayan Banerjee , R. Adhikari

Multiphoton interference is at the very heart of quantum foundations and applications in quantum sensing and information processing. In particular, boson sampling experiments have the potential to demonstrate quantum computational supremacy…

Quantum Physics · Physics 2021-09-15 Vincenzo Tamma , Simon Laibacher

Mutually unbiased measurements (MUMs) are generalized from the concept of mutually unbiased bases (MUBs) and include the complete set of MUBs as a special case, but they are superior to MUBs as they do not need to be rank one projectors. We…

Quantum Physics · Physics 2015-08-25 Lu Liu , Ting Gao , Fengli Yan

We propose a simple abstract formalisation of the act of observation, in which the system and the observer are assumed to be in a pure state and their interaction deterministically changes the states such that the outcome can be read from…

Quantum Physics · Physics 2007-05-23 Sven Aerts

Mistakes/uncertainties in object detection could lead to catastrophes when deploying robots in the real world. In this paper, we measure the uncertainties of object localization to minimize this kind of risk. Uncertainties emerge upon…

Computer Vision and Pattern Recognition · Computer Science 2020-07-03 Yihui He , Jianren Wang

It is well known that bosons and fermions exhibit opposite behaviors when experiencing interference, in the sense that bosons have a tendency to bunch whereas fermions have a tendency to antibunch. Recently, this complementarity was…

Quantum Physics · Physics 2026-04-28 Marco Robbio , Michael G. Jabbour , Nicolas J. Cerf

Since the development of Boson sampling, there has been a quest to construct more efficient and experimentally feasible protocols to test the computational complexity of sampling from photonic states. In this paper we interpret and extend…

We investigate the stabilization of unstable multidimensional partially observed single-sensor and multi-sensor linear systems driven by unbounded noise and controlled over discrete noiseless channels under fixed-rate information…

Optimization and Control · Mathematics 2012-09-21 Andrew P. Johnston , Serdar Yüksel

Using new results on the separability properties of bosonic systems, we provide a new complete criterion for separability. This criterion aims at characterizing the set of separable states from the inside by means of a sequence of…

Quantum Physics · Physics 2013-05-29 Miguel Navascues , Masaki Owari , Martin B. Plenio

Coulomb repulsion is taken into account to derive the thermodynamics of charged bosons in a random external potential. A simple analytical form of the partition function is proposed for the case of non-overlapping localised states (i.e. a…

Superconductivity · Physics 2008-02-03 A. S. Alexandrov , R. T. Giles

The uncanny ability of multiple particles to interfere with one another is one of the core principles of quantum mechanics, and serves as foundation for quantum information processing. In particular, the interplay of constructive and…

Quantum Physics · Physics 2022-03-23 Max Ehrhardt , Matthias Heinrich , Alexander Szameit

Computing the state of a quantum mechanical many-body system composed of indistinguishable particles distributed over a multitude of modes is one of the paradigmatic test cases of computational complexity theory: Beyond well-understood…

Boson-Sampling is a classically computationally hard problem that can - in principle - be efficiently solved with quantum linear optical networks. Very recently, a rush of experimental activity has ignited with the aim of developing such…

Quantum Physics · Physics 2020-05-15 C. Gogolin , M. Kliesch , L. Aolita , J. Eisert