23 papers · ranked by Valyu relevance
Henry Pinkard, Laura Waller
Though originally developed for communications engineering, information theory contains mathematical tools with numerous applications in science and engineering. These tools can be used to characterize the fundamental limits of data compression and transmission in the presence of noise. Here, we present a practical…
Jordão Natal, Ivonete Ávila, Victor Batista Tsukahara, Marcelo Pinheiro + 3 more
'Marcelo Pinheiro' 'Carlos Dias Maciel' 'José A. Tenreiro Machado' 'Leonid M. Martyushev'] Entropy is a concept that emerged in the 19th century. It used to be associated with heat harnessed by a thermal machine to perform work during the Industrial Revolution. However, there was an unprecedented scientific revolution…
Yair Lapin
The Turing machine halting problem can be explained by several factors, including arithmetic logic irreversibility and memory erasure, which contribute to computational uncertainty due to information loss during computation. Essentially, this means that an algorithm can only preserve information about an input, rather…
El Mahdi Mouloua, Essaid Mohamed
Information theory is introduced in this lecture note with a particular emphasis on its relevance to algebraic coding theory. The document develops the mathematical foundations for quantifying uncertainty and information transmission by building upon Shannon's pioneering formulation of information, entropy, and channel…
Thomas F. Varley
In the 21st century, many of the crucial scientific and technical issues facing humanity can be understood as problems associated with understanding, modelling, and ultimately controlling complex systems: systems comprised of a large number of non-trivially interacting components whose collective behaviour can be…
Myongin Oh, Donald F. Weaver
The human brain is a dynamic multiplex of information, both neural (neurotransmitter-to-neuron, involving 1.5×1015 action potentials per minute) and immunological (cytokine-to-microglia, providing continuous immune surveillance via 1.5×1010 immunocompetent cells). This conceptualization highlights the opportunity of…
Roberto Maffulli, Miguel A. Casal, Marco Celotto, Stefano Zucca + 3 more
Information theory provides a popular and principled framework for the analysis of neural data. It allows to uncover in an assumption-free way how neurons encode and transmit information, capturing both linear and non-linear coding mechanisms and including the information carried by interactions of any order. To…
Riccardo Manzotti, Kyumin Moon, José F.F. Mendes
In this paper, I argue that information is nothing more than an abstract object; therefore, it does not exist fundamentally. It is neither a concrete physical entity nor a form of “stuff” that “flows” through communication channels or that is “carried” by vehicles or that is stored in memories, messages, books, or…
Aida Koch, Alix Petit
In this article, we will analyze in detail the coding limit of an individual sequence by introducing the latest developments brought by the Set Shaping Theory. This new theory made us realize that there is a huge difference between source entropy and zero order empirical entropy. Understanding the differences between…
Jeroen Schoenmaker, George Ruppeiner
This manuscript gives a solution to the black hole information paradox by bringing to the debate a fundamental aspect of information science: the process of measurement by a receiver. Bekenstein and Hawking established the foundations of black hole thermodynamics based on previous works of Brillouin and Szilard on…
Hiqmet Kamberaj
Using a notably large amount of data in investigating physical and chemical phenomena demands new statistical and computational approaches; besides, the cross-validations require wellestablished theoretical frameworks. This study aims to validate the statistical efficiency of alternative definitions for the…
Antonio Carvajal-Rodríguez
Population genetics describes evolutionary processes, focusing on the variation within and between species and the forces shaping this diversity. Evolution reflects information accumulated in genomes, enhancing organisms’ adaptation to their environment. In this paper, we propose a model that begins with the…
John Tower
Biological information is generally thought to be subject to selection for faithful maintenance. However, accurate preservation is often combined with regulated mechanisms that generate state change. Selectively advantageous instability (SAI) is modeled here as instability that is favored because useful alternatives…
Mario Martinelli, Armin Feldhoff, Christophe Goupil, Pascal Boulet + 4 more
'Marie-Christine Record' 'Eric Herbert' 'Gaël Giraud' 'Mathieu Arnoux'] This second part of this companion paper the Carnot cycle is analyzed trying to investigate the similarities and differences between a framework related to thermodynamics and one related to information theory. The parametric Schrodinger equations…
Qian Zeng, Ran Li, Jin Wang, Lamberto Rondoni
We investigated the impact of nonequilibrium conditions on the transmission and recovery of information through noisy channels. By measuring the recoverability of messages from an information source, we demonstrate that the ability to recover information is connected to the nonequilibrium behavior of the information…
Michal Hledík, Nick Barton, Gašper Tkačik
Selection accumulates information in the genome — it guides stochastically evolving populations towards states (genotype frequencies) that would be unlikely under neutrality. This can be quantified as the Kullback-Leibler (KL) divergence between the actual distribution of genotype frequencies and the corresponding…
Authors not listed
Quantum state tomography has been widely used to reconstruct the quantum state of a system from a set of informationally-complete measurements. Obtaining enough information about, e.g., the wavefunction of a molecule allows its complete characterization. On the other hand, deep learning models for molecular property…
Jia Lu, Ryan Tsoi, Nan Luo, Yuanchi Ha + 8 more
Dynamical systems often generate distinct outputs according to different initial conditions, and one can infer the corresponding input configuration given an output. This property captures the essence of information encoding and decoding. Here, we demonstrate the use of self-organized patterns, combined with machine…
Authors not listed
A framework for catalysis based on categorical aperture selection rather than temporal acceleration is presented. Traditional catalysis theory describes catalysts as agents that accelerate reactions by lowering activation energies, implicitly treating time as the fundamental variable and reaction rate enhancement as…
Authors not listed
Chemical bonding, despite being fundamental to chemistry, lacks a universally agreed-upon quantum mechanical definition that captures all its facets across diverse molecular systems. Traditional models—Lewis structures, Valence Bond theory, Molecular Orbital theory, and the Quantum Theory of Atoms in Molecules…
Authors not listed
We present a theoretical and computational framework for virtual mass spectrometry based on Molecular Maxwell Demons (MMDs) operating as information catalysts. Building on the biological Maxwell demon framework, we demonstrate that mass spectrometry data contain categorical state information that is fundamentally…
Mohsen Farshad
Providing a simple description of entropy as the foundation of thermodynamics is necessary for researchers in explaining physical phenomena in the universe. Here we dive deep into the meaning of entropy starting from the basics and ending with the Newton's second law of motion which may be rooted in a hidden dimension…
Authors not listed
Gibbs’ paradox—the apparent discontinuity in mixing entropy for gases of varying similarity and the seeming reversibility of mixing-separation cycles—has resisted fully satisfactory resolution for 150 years. We present a solution based on categorical state theory, which posits that physical con f igurations are…