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We address the witnessing of quantum correlations beyond the limits imposed by an ensemble statistical average. By relying upon the continuous observation of a single quantum open system under the action of classical or quantum noise, we…

Quantum Physics · Physics 2016-08-14 Felipe Caycedo-Soler , Ferney J. Rodríguez , Luis Quiroga

We provide a new general theorem for multivariate normal approximation on convex sets. The theorem is formulated in terms of a multivariate extension of Stein couplings. We apply the results to a homogeneity test in dense random graphs and…

Probability · Mathematics 2016-08-14 Xiao Fang , Adrian Röllin

To our knowledge, the analysis of convergence rates for persistence diagrams estimation from noisy signals has predominantly relied on lifting signal estimation results through sup-norm (or other functional norm) stability theorems. We…

Statistics Theory · Mathematics 2025-06-03 Hugo Henneuse

Single-photon-sensitive cameras can now be used as massively parallel coincidence counters for entangled photon pairs. This enables measurement of biphoton joint probability distributions with orders-of-magnitude greater dimensionality and…

Instrumentation and Detectors · Physics 2018-08-01 Matthew Reichert , Hugo Defienne , Jason W. Fleischer

We consider audio decoding as an inverse problem and solve it through diffusion posterior sampling. Explicit conditioning functions are developed for input signal measurements provided by an example of a transform domain perceptual audio…

Audio and Speech Processing · Electrical Eng. & Systems 2024-09-13 Pedro J. Villasana T. , Lars Villemoes , Janusz Klejsa , Per Hedelin

Sampling theories lie at the heart of signal processing devices and communication systems. To accommodate high operating rates while retaining low computational cost, efficient analog-to digital (ADC) converters must be developed. Many of…

Information Theory · Computer Science 2010-10-12 Moslem Rashidi

In the present paper a counter-example to Bell's theorem is given which is based on common probability densities as standard normal (Gaussian) and uniform probability densities. The reason for violating the Bell inequalities lies in the…

General Physics · Physics 2007-05-23 J. F. Geurdes

The analytical expression for the signal-to-noise ratio of a slotted surface coil with an arbitrary number of slots was derived using the quasi-static approach. This surface coil based on the vane-type magnetron tube. To study the coil…

Medical Physics · Physics 2011-02-10 K. Ocegueda , S. S. Hidalgo , S. E. Solis , A. O. Rodriguez

We study connections between Natural Proofs, derandomization, and the problem of proving "weak" circuit lower bounds such as ${\sf NEXP} \not\subset {\sf TC^0}$. Natural Proofs have three properties: they are constructive (an efficient…

Computational Complexity · Computer Science 2015-07-23 Ryan Williams

Removal or cancellation of noise has wide-spread applications for imaging and acoustics. In every-day-life applications, denoising may even include generative aspects, which are unfaithful to the ground truth. For scientific use, however,…

In this paper we are interested to model quantum signal by statistical signal processing methods. The Gaussian distribution has been considered for the input quantum signal as Gaussian state have been proven to a type of important robust…

Quantum Physics · Physics 2023-02-17 Mouli Chakraborty , Harun Siljak , Indrakshi Dey , Nicola Marchetti

The paper investigates the distributed estimation problem under low bit rate communications. Based on the signal-comparison (SC) consensus protocol under binary-valued communications, a new consensus+innovations type distributed estimation…

Systems and Control · Electrical Eng. & Systems 2025-03-25 Jieming Ke , Xiaodong Lu , Yanlong Zhao , Ji-Feng Zhang

A continuous-time Wiener phase noise channel with an integrate-and-dump multi-sample receiver is studied. A lower bound to the capacity with an average input power constraint is derived, and a high signal-to-noise ratio (SNR) analysis is…

Information Theory · Computer Science 2015-03-12 Luca Barletta , Gerhard Kramer

In typical single-pixel detection multiplexing, an unknown object is sequentially illuminated with intensity patterns: the total signal is summed into a single-pixel detector and is then demultiplexed to retrieve the object. Because of…

Optics · Physics 2022-04-14 Camille Scotté , Frédéric Galland , Hervé Rigneault

We consider minimax signal detection in the sequence model. Working with certain ellipsoids in the space of square-summable sequences of real numbers, with a ball of positive radius removed, we obtain upper and lower bounds for the minimax…

Statistics Theory · Mathematics 2017-12-27 Clement Marteau , Theofanis Sapatinas

The possibility of a fundamental consistency between the basic quantum principles and reduction (so-called wave function reduction) is reexamined. The mathematical description of an organized macroscopic device is constructed explicitly as…

Quantum Physics · Physics 2010-02-15 Roland Omnes

For the additive white Gaussian noise channel with average power constraint, sparse superposition codes, proposed by Barron and Joseph in 2010, achieve the capacity. While the codewords of the original sparse superposition codes are made…

Information Theory · Computer Science 2018-01-10 Yoshinari Takeishi , Jun'ichi Takeuchi

Random constraint satisfaction problems (CSPs) are known to exhibit threshold phenomena: given a uniformly random instance of a CSP with $n$ variables and $m$ clauses, there is a value of $m = \Omega(n)$ beyond which the CSP will be…

Data Structures and Algorithms · Computer Science 2016-11-07 Prasad Raghavendra , Satish Rao , Tselil Schramm

The recovery of structured signals from a few linear measurements is a central point in both compressed sensing (CS) and discrete tomography. In CS the signal structure is described by means of a low complexity model e.g. co-/sparsity. The…

Optimization and Control · Mathematics 2018-12-31 Jan Kuske , Stefania Petra

A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribution and achieving accurate reconstruction on average, is…

Computer Vision and Pattern Recognition · Computer Science 2010-10-22 Guoshen Yu , Guillermo Sapiro
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