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Two observations are given on the fidelity of schemes for quantum information processing. In the first one, we show that the fidelity of a symplectic (stabilizer) code, if properly defined, exactly equals the `probability' of the…

Quantum Physics · Physics 2007-05-23 Mitsuru Hamada

An algorithm of searching a zero of an unknown undimensional function is considered, measured at a point x with some error. The step sizes are random positive values and are calculated according to the rule: if two consecutive iterations…

Statistics Theory · Mathematics 2007-06-13 Alexander Plakhov , Pedro Cruz

It is common to reject undesired outputs of Large Language Models (LLMs); however, current methods to do so require an excessive amount of computation to re-sample after a rejection, or distort the distribution of outputs by constraining…

Computation and Language · Computer Science 2025-10-09 Daniel Melcer , Sujan Gonugondla , Pramuditha Perera , Haifeng Qian , Wen-Hao Chiang , Yanjun Wang , Nihal Jain , Pranav Garg , Xiaofei Ma , Anoop Deoras

We consider the task of performing probabilistic inference with probabilistic logical models. Many algorithms for approximate inference with such models are based on sampling. From a logic programming perspective, sampling boils down to…

Artificial Intelligence · Computer Science 2015-03-19 Daan Fierens

A theoretical framework is developed to describe the transformation that distributes probability density functions uniformly over space. In one dimension, the cumulative distribution can be used, but does not generalize to higher…

Neural and Evolutionary Computing · Computer Science 2016-09-08 Eric Kee

We present a method for approximating solutions of Stochastic Differential Equations (SDEs) with arbitrary rates. This approximation is derived for bounded and measurable test functions. Specifically, we demonstrate that, leveraging the…

Probability · Mathematics 2024-03-27 Clément Rey

For $q$-ary $n$-sequences, we develop the concept of similarity functions that can be used (for $q=4$) to model a thermodynamic similarity on DNA sequences. A similarity function is identified by the length of a longest common subsequence…

Information Theory · Computer Science 2014-01-30 A. Dyachkov

The problem of neural coding is to understand how sequences of action potentials (spikes) are related to sensory stimuli, motor outputs, or (ultimately) thoughts and intentions. One clear question is whether the same coding rules are used…

We study the theoretical performance of a combined approach to demodulation and decoding of binary continuous-phase modulated signals under repetition-like codes. This technique is motivated by a need to transmit packetized or framed data…

Information Theory · Computer Science 2014-04-28 Gaurav Thakur

This paper presents a new supervised representation learning framework, namely structured probabilistic coding (SPC), to learn compact and informative representations from input related to the target task. SPC is an encoder-only…

Computation and Language · Computer Science 2024-05-03 Dou Hu , Lingwei Wei , Yaxin Liu , Wei Zhou , Songlin Hu

To perform recognition, molecules must locate and specifically bind their targets within a noisy biochemical environment with many look-alikes. Molecular recognition processes, especially the induced-fit mechanism, are known to involve…

Biomolecules · Quantitative Biology 2010-07-27 Yonatan Savir , Tsvi Tlusty

We consider uniquely-decodable coding for zero-error network function computation, where in a directed acyclic graph, the single sink node is required to compute with zero error a target function multiple times, whose arguments are the…

Information Theory · Computer Science 2025-09-16 Xuan Guang , Jihang Yang , Ruze Zhang

Recent advancements in deep learning techniques have transformed the area of semantic text matching. However, most state-of-the-art models are designed to operate with short documents such as tweets, user reviews, comments, etc. These…

Information Retrieval · Computer Science 2022-06-03 Akshita Jha , Vineeth Rakesh , Jaideep Chandrashekar , Adithya Samavedhi , Chandan K. Reddy

Unary coding is useful but it is redundant in its standard form. Unary coding can also be seen as spatial coding where the value of the number is determined by its place in an array. Motivated by biological finding that several neurons in…

Neural and Evolutionary Computing · Computer Science 2014-12-22 Subhash Kak

This work constructs codes that are efficiently decodable from a constant fraction of \emph{worst-case} insertion and deletion errors in three parameter settings: (i) Binary codes with rate approaching 1; (ii) Codes with constant rate for…

Information Theory · Computer Science 2016-05-17 Venkatesan Guruswami , Ray Li

Field experiments are often difficult and expensive to make. To bypass these issues, industrial companies have developed computational codes. These codes intend to be representative of the physical system, but come with a certain amount of…

Computation · Statistics 2019-03-26 Mathieu Carmassi , Pierre Barbillon , Merlin Keller , Eric Parent , Matthieu Chiodetti

Computational spectral imaging is drawing increasing attention owing to the snapshot advantage, and amplitude, phase, and wavelength encoding systems are three types of representative implementations. Fairly comparing and understanding the…

Image and Video Processing · Electrical Eng. & Systems 2023-12-22 Xinyuan Liu , Lizhi Wang , Lingen Li , Chang Chen , Xue Hu , Fenglong Song , Youliang Yan

Analytic and numeric approximations are studied in detail for a hydrodynamic parameterization of single-particle spectra and two-particle correlation functions in high energy hadron-proton and heavy ion reactions. Two very different sets of…

High Energy Physics - Phenomenology · Physics 2009-09-25 A. Ster , T. Csorgo , B. Lorstad

Low-density parity-check codes with irregular constructions have been recently shown to outperform the most advanced error-correcting codes to date. In this paper we apply methods of statistical physics to study the typical properties of…

Disordered Systems and Neural Networks · Physics 2016-08-31 Renato Vicente , David Saad , Yoshiyuki Kabashima
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