Information Theory Research Articles

Horizon causality from holographic scattering in asymptotically dS3

In the AdS/CFT correspondence, a direct scattering in the bulk may not have a local boundary analog. A nonlocal implementation on the boundary requires O(1/GN) mutual information. This statement is formalized by the connected wedge theorem, which can be proven using general relativity within AdS3 but also argued for using quantum information theory on the boundary, suggesting that the theorem applies to any holographic duality. We examine scattering within the static patch of asymptotically dS3 spacetime, which is conjectured to be described by a quantum theory on the stretched horizon in static patch holography. We show that causality on the horizon induced from null infinities I± is consistent with the theorem. Specifically, signals propagating in the static patch are associated with local operators at I±. Our results suggest a novel connection between static patch holography and the dS/CFT correspondence.

Spatio-Temporal Analysis of Acute Myocardial Ischaemia Based on Entropy-Complexity Plane.

Myocardial ischaemia is a decompensation of the oxygen supply and demand ratio, often caused by coronary atherosclerosis. During the initial stage of ischaemia, the electrical activity of the heart is disrupted, increasing the risk of malignant arrhythmias. The aim of this study is to understand the differential behaviour of the ECG during occlusion of both the left anterior descending (LAD) and right anterior coronary artery (RCA), respectively, using spatio-temporal quantifiers from information theory. A standard 12-lead ECG was recorded for each patient in the database. The control condition was obtained initially. Then, a percutaneous transluminal coronary angioplasty procedure (PTCA), which encompassed the occlusion/reperfusion period, was performed. To evaluate information quantifiers, the Bandt and Pompe permutation method was used to estimate the probability distribution associated with the electrocardiographic vector modulus. Subsequently, we analysed the positioning in the H×C causal plane for the control and ischaemia. In LAD occlusion, decreased entropy and increased complexity can be seen, i.e., the behaviour is more predictable with an increase in the degree of complexity of the system. RCA occlusion had the opposite effects, i.e., the phenomenon is less predictable and exhibits a lower degree of organisation. Finally, both entropy and complexity decrease during the reperfusion phase in LAD and RCA cases.

Determinants of Dividend Payout Policy: More Evidence From Emerging Markets of G20 Bloc

ABSTRACTThe purpose of this article is to examine the key factors influencing dividend payout policy in emerging markets, using a quantitative approach with a sample of 938 firms and 19,698 firm‐year observations. The study considers dividends, and share repurchases as elements of payout, analysing the effect of earnings, taxes, debt, size and free cash flow on payout decisions through an OLS Panel Data regression model and a GMM‐AB model for robustness. Findings indicate that taxes, size and leverage positively influence payout, while free cash flow and earnings show negative associations. Notably, free cash flow exhibits the largest impact on payout variations, supporting asymmetric information theories like bird‐in‐hand, signalling and dividend life cycle theories, where payout responds to investor risk aversion. The paper's originality lies in its 21‐year analysis of 11 emerging economies, identifying that, unlike developed markets where payout is shaped by agency conflicts, emerging markets emphasise reducing investor risk aversion. The findings also challenge existing financial theories by demonstrating a complementary relationship between investment and debt policies, with a negative correlation between cash flow and dividends and a positive one between leverage and dividends.

Morphological analysis of Japanese food names

This study aims at analyzing the morphological construction of Japanese food names. There are many types of word formation used when creating food names in Japanese. Food names frequently have profound cultural meanings, reflecting the history, geography, social customs, and traditions of a society. The data of this study were collected from Japanese newspaper articles on the Asahi Shinbun website using observation methods and note-taking techniques. The data were analyzed using the identity method with distribution techniques. The forms of food names were analyzed using word formation theory. Based on the results, there are 5 types of word formation used in constructing Japanese food names namely affixation, compounding, reduplication, clipping, and borrowing. Japanese food names are constructed based on three main categories: 1) type of food, 2) cooking method, and 3) combination of foods.

Applications of Entropy in Data Analysis and Machine Learning: A Review.

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory, Ergodic Theory and the Theory of Dynamical Systems. Specifically, we are referring to the classical entropies: the Boltzmann-Gibbs, von Neumann, Shannon, Kolmogorov-Sinai and topological entropies. In addition to their common name, which is historically justified (as we briefly describe in this review), another commonality of the classical entropies is the important role that they have played and are still playing in the theory and applications of their respective fields and beyond. Therefore, it is not surprising that, in the course of time, many other instances of the overarching concept of entropy have been proposed, most of them tailored to specific purposes. Following the current usage, we will refer to all of them, whether classical or new, simply as entropies. In particular, the subject of this review is their applications in data analysis and machine learning. The reason for these particular applications is that entropies are very well suited to characterize probability mass distributions, typically generated by finite-state processes or symbolized signals. Therefore, we will focus on entropies defined as positive functionals on probability mass distributions and provide an axiomatic characterization that goes back to Shannon and Khinchin. Given the plethora of entropies in the literature, we have selected a representative group, including the classical ones. The applications summarized in this review nicely illustrate the power and versatility of entropy in data analysis and machine learning.

Globular Cluster Counts around 700 Nearby Galaxies

Abstract Empirically, the total number (or total mass) of globular clusters (GCs) bound in a single galactic system correlates with the virial mass of the system. The form of this relation and its intrinsic scatter are potentially valuable constraints on theories of GC formation and galaxy evolution. In this work, we use the DESI Legacy Imaging Survey (DESI-LS) to make a large-scale, homogeneous estimate of GC abundance around 707 galaxies at distances ≲30 Mpc with luminosities 8 ≤ log 10 L / L ⊙ ≤ 11.5 . The combination of depth and sky coverage in DESI-LS allow us to extend the techniques used by previous ground-based photometric GC surveys to a larger and potentially more representative sample of galaxies. We find average GC counts and radial profiles that are broadly consistent with the literature on individual galaxies, including good agreement with the distribution of GCs in the Milky Way, demonstrating the viability of DESI-LS images for this purpose. We find a relation between GC counts and virial mass in agreement with previous estimates based on heterogenous data sets, except at the lowest masses we probe, where we find a larger scatter in the number of cluster candidates and a slightly higher average count.

Shannon Entropy Analysis of a Nuclear Fuel Pin Under Deep Burnup.

This paper analyzes the behavior of the entropy of a nuclear fuel rod under deep burnup conditions, beyond standard operational ranges, reaching up to 60 years. The evolution of the neutron source distribution in a pressurized water reactor (PWR) fuel pin was analyzed using the Monte Carlo method and Shannon information entropy. To maintain proper statistics, a novel scaling method was developed, adjusting the neutron population based on the fission rate. By integrating reactor physics with information theory, this work aimed at the deeper understanding of nuclear fuel behavior under extreme burnup conditions. The results show a "U-shaped" entropy evolution: an initial decrease due to self-organization, followed by stabilization and eventual increase due to degradation. A minimum entropy state is reached after approximately 45 years of pin operation, showing a steady-state condition with no entropy change. This point may indicate a physical limit for fuel utilization. Beyond this point, entropy rises, reflecting system degradation and lower energy efficiency. The results show that entropy analysis can provide valuable insights into fuel behavior and operational limits. The proposed scaling method may also serve to control a Monte Carlo simulation, especially for the analysis of long-life reactors.

Sipping and sharing: impact of emotions and topics on the usefulness of travelers’ wine festival forum posts

PurposeAficionados of wine festivals, a component of wine tourism experience, engage in vigorous online discussions that influence fellow travelers’ purchase behaviors. This study aims to delve into these overlooked discussions, identifying emotions, topics and assessing their usefulness in TripAdvisor’s Travel Forums for two US wine festivals: Taste of Yountville and Epcot International Food and Wine Festival, located in traditional and nontraditional wine tourism destinations.Design/methodology/approachThe study uses state-of-art sentiment analysis and topic modeling methods to extract emotions and underlying latent topics in travel forum discussions. Drawing from information theory, two regression analyses are performed on 10,677 forum posts to examine how the extracted Ekman’s emotions and key underlying topics influence the helpfulness of wine forum posts for each festival.FindingsWhile three topics were identified in Epcot and four in Yountville, both festival platforms highlight travelers’ common preferences for “culinary experience” and “planning” attributes but reveal notable differences in their utility. Other shared novel findings include the importance of “anger” and “surprise” emotions on the helpfulness of forum posts.Practical implicationsThese findings enhance wine festival managers’ and destination planners’ understanding of online travelers’ preferences and cognitive evaluation of user-generated contents’ usefulness. This marketing intelligence informs strategies for boosting the wine destination’s economic development.Originality/valueThis research offers a novel comparative analysis of social media on wine festival tourism experiences in diverse regions. Unlike hotel reviews, typically posted after consumption, forums offer unique and broader perspectives on discussions before, during, and after experiencing the wine festival.

A Systematic Survey of Moon-forming Giant Impacts. II. Rotating Bodies

In the leading theory of lunar formation, known as the giant impact hypothesis, a collision between two planet-sized objects resulted in a young Earth surrounded by a circumplanetary debris disk from which the Moon later accreted. The range of giant impacts that could conceivably explain the Earth–Moon system is limited by the set of known physical and geochemical constraints. However, while several distinct Moon-forming impact scenarios have been proposed—from small, high-velocity impactors to low-velocity mergers between equal-mass objects—none of these scenarios have been successful at explaining the full set of known constraints, especially without invoking one or more controversial post-impact processes. Allowing for pre-impact rotation of the colliding bodies has been suggested as an avenue that may produce more promising collision outcomes. However, to date, only limited studies of pre-impact rotation have been conducted. Therefore, in this second paper of the series, we focus on pairwise impacts between rotating bodies. Using nonrotating collisions as a baseline, we systematically study the effects of rotation on collision outcomes. We consider nine distinct rotation configurations and a range of rotation rates up to the rotational stability limit. Notably, we identify a population of collisions that can produce low post-impact angular momentum (AM) budgets and massive, iron-poor protolunar disks. Furthermore, even when pre-impact rotation is included, we demonstrate that the canonical Moon-forming impact can only generate sufficiently massive protolunar disks in the presence of excessive post-impact AM budgets; this casts doubt on the canonical impact scenario.

An Information Manifold Perspective for Analyzing Test Data.

Modifications of current psychometric models for analyzing test data are proposed that produce an additive scale measure of information. This information measure is a one-dimensional space curve or curved surface manifold that is invariant across varying manifold indexing systems. The arc length along a curve manifold is used as it is an additive metric having a defined zero and a version of the bit as a unit. This property, referred to here as the scope of the test or an item, facilitates the evaluation of graphs and numerical summaries. The measurement power of the test is defined by the length of the manifold, and the performance or experiential level of a person by a position along the curve. In this study, we also use all information from the items including the information from the distractors. Test data from a large-scale college admissions test are used to illustrate the test information manifold perspective and to compare it with the well-known item response theory nominal model. It is illustrated that the use of information theory opens a vista of new ways of assessing item performance and inter-item dependency, as well as test takers' knowledge.

Negative cumulative residual extropy under concomitants of generalized order statistics based on Cambanis bivariate family with applications

Abstract Thermodynamics, statistical mechanics, and quantum mechanics are the branches of physics that use entropy and extropy measures. It also seems to quantify the degree of signal uncertainty in information theory. Recently, extropy has been widely used in the literature as a measure of dispersion or uncertainty. Within generalized Farlie-Gumbel-Morgenstern families, the Cambanis bivariate family holds a prominent position as an efficient and adaptable extended family. Motivated by this, our work gives numerous characterizations of Cambanis copula based on order statistics (OSs). Also, we study the negative cumulative residual extropy and various measures of information associated with it for concomitants generalized OSs.
Moreover, we study OSs and sequential OSs for each information measure in a computational study. This study offers a few beautiful symmetrical and asymmetric relationships that these information measures satisfy. Additionally, the empirical technique is applied to the Cambanis family to estimate every measure of negative extropy discussed in this work. As a final step, we have examined a bivariate real-world data set for illustrative purposes.

INFORMATIONAL PERSPECTIVE ON RAMIFICATIONS IN CONSTRUCTAL DESIGN

What insights can informational analysis provide regarding the ramifications predicted by constructal design? The first step in answering this research question is to consider symmetric and asymmetric flow architectures. In the symmetric case, radial multi-branching shows diminishing returns of diversity (measured by the system’s informature) in line with high thermofluid performance. In asymmetric flow architectures, assuming an evolution toward maximum complexity (as defined in information theory), patterns emerge like sap distribution in leaves.

Informeasure: an R/bioconductor package for quantifying nonlinear dependence between variables in biological networks from an information theory perspective

BackgroundUsing information measures to infer biological regulatory networks can capture nonlinear relationships between variables. However, it is computationally challenging, and there is a lack of convenient tools.ResultsWe introduce Informeasure, an R package designed to quantify nonlinear dependencies in biological regulatory networks from an information theory perspective. This package compiles a comprehensive set of information measurements, including mutual information, conditional mutual information, interaction information, partial information decomposition, and part mutual information. Mutual information is used for bivariate network inference, while the other four estimators are dedicated to trivariate network analysis.ConclusionsInformeasure is a turnkey solution, allowing users to utilize these information measures immediately upon installation. Informeasure is available as an R/Bioconductor package at https://bioconductor.org/packages/Informeasure.

The Functional Connectome Mediating Circadian Synchrony in the Suprachiasmatic Nucleus.

Circadian rhythms in mammals arise from the spatiotemporal synchronization of ~20,000 neuronal clocks in the Suprachiasmatic Nucleus (SCN). While anatomical, molecular, and genetic approaches have revealed diverse cell types and signaling mechanisms, the network wiring that enables SCN cells to communicate and synchronize remains unclear. To overcome the challenges of revealing functional connectivity from fixed tissue, we developed MITE (Mutual Information & Transfer Entropy), an information theory approach that infers directed cell-cell connections with high fidelity. By analyzing 3447 hours of continuously recorded clock gene expression from 9011 cells in 17 mice, we found that the functional connectome of SCN was highly conserved bilaterally and across mice, sparse, and organized into a dorsomedial and a ventrolateral module. While most connections were local, we discovered long-range connections from ventral cells to cells in both the ventral and dorsal SCN. Based on their functional connectivity, SCN cells can be characterized as circadian signal generators, broadcasters, sinks, or bridges. For example, a subset of VIP neurons acts as hubs that generate circadian signals critical to synchronize daily rhythms across the SCN neural network. Simulations of the experimentally inferred SCN networks recapitulated the stereotypical dorsal-to-ventral wave of daily PER2 expression and ability to spontaneously synchronize, revealing that SCN emergent dynamics are sculpted by cell-cell connectivity. We conclude that MITE provides a powerful method to infer functional connectomes, and that the conserved architecture of cell-cell connections mediates circadian synchrony across space and time in the mammalian SCN.

Current directions in the development of the general criminalistic through the prism of modern technologies

The article examines some current trends in the development of the general theory of criminalistics in line with the integration and differentiation of scientific knowledge, considering trends in global digitalization and integration of modern technologies in the field of crime investigation. An analysis of current definitions of the subject of criminology given by leading forensic scientists from Russia, Belarus, Kazakhstan, Azerbaijan and other countries has been carried out, which shows that most of them, one way or another, are consistent with the definition of the subject of science by R. S. Belkin. A comparative analysis of digital criminalistic (V. B. Vekhov and S. V. Zuev), by which the authors understand a particular theory of criminalistics, includes a general part very similar to the general provisions of the theory of information and computer support for criminalistic activities developed by us and a special part that relates first to the development of information and computer support for criminalistic equipment and technology. The ways of developing the theory of criminalistic trace science are outlined, in which, considering new forensic technologies, the relationships between the scene of the incident, the victim, the method of crime and the criminal should be connected through various mechanisms of trace formation. The methods of computer crimes and the concept of constructing information and computer criminalistic models of computer crimes based on the theory of information and computer support for criminalistic activities are considered. The basis was chosen to be correlations between combinations of IT-technologies used to carry out computer crimes, the trace pattern in the form of digital footprints and the level of competence in IT-technologies of the criminal and the victim.

Reputational Discrimination and Fairness in China’s Social Credit System

As the first nationwide reputation system, the Chinese Social Credit System (SCS) employs a plethora of information technologies to rate citizens according to a state-defined notion of trustworthiness. Complementing extant research about the SCS that highlights important concerns regarding privacy and surveillance, our work explores the economic facets of the system on the basis of microeconomic and informational theories. We identify reputational discrimination as the basic working principle of the SCS, and propose that in addition to carrots and sticks, which are often highlighted as the main tools of the SCS to incentivize individuals to trustworthy behavior, status is another important variable the planner disposes of. Using a contest model approach, we find that when status is used as a complementary instrument to rewards and punishments, a planner who cares about efficiency, morality, and strictness treats most unfair those that are already bad off. Our work adds another dimension to the policy analysis of the SCS, and advances the understanding of the informational design of the SCS by investigating the fairness-related concerns that the system raises for individuals. Our findings underscore the importance of incorporating fairness principles into the SCS, to not further widen existing economic and societal gaps.

Enhancing Quantum Entanglement Through Parametric Control of Atom‐Cavity States

AbstractDicke states form a class of entangled states that has attracted much attention for their applications in various quantum algorithms. They emerge as eigenstates of the Tavis–Cummings (TC) Hamiltonian, a simplification of the Dicke model, which describes an assembly of two‐level atoms trapped in an electromagnetic cavity. In this letter, it is showed that in the regime where the field energy is large with respect to the atomic energy splitting, precise control of the ground state can be implemented. Specifically, pure Dicke states can be selected and produced by appropriate tuning of the parameters. This result may have important applications in quantum engineering and quantum information theory.

Revisiting the standard for modeling functional brain network activity: Application to consciousness.

Functional connectivity (FC) of resting-state fMRI time series can be estimated using methods that differ in their temporal sensitivity (static vs. dynamic) and the number of regions included in the connectivity estimation (derived from a prior atlas). This paper presents a novel framework for identifying and quantifying resting-state networks using resting-state fMRI recordings. The study employs a linear latent variable model to generate spatially distinct brain networks and their associated activities. It specifically addresses the atlas selection problem, and the statistical inference and multivariate analysis of the obtained brain network activities. The approach is demonstrated on a dataset of resting-state fMRI recordings from monkeys under different anesthetics using static FC. Our results suggest that two networks, one fronto-parietal and cingular and another temporo-parieto-occipital (posterior brain) strongly influences shifts in consciousness, especially between anesthesia and wakefulness. Interestingly, this observation aligns with the two prominent theories of consciousness: the global neural workspace and integrated information theories of consciousness. The proposed method is also able to decipher the level of anesthesia from the brain network activities. Overall, we provide a framework that can be effectively applied to other datasets and may be particularly useful for the study of disorders of consciousness.

Views on the creation of strategic reserves in the period between the World Wars

The need to study the development of military theoretical views on the creation and use of strategic reserves in the interwar years is due to the need for an in-depth study of the experience of developing military strategy, including in the creation of strategic reserves in the interests of solving modern problems of military construction of the Republic of Kazakhstan. This article analyzes the views of theorists and practitioners of the Soviet theory of military art, which were developed in the period between the world wars, on the process of early creation and use of strategic reserves in future wars in which the state may be involved. Based on this analysis, some issues have been identified that need to be addressed by officials responsible for the development of the theory of strategic reserves formation at the present stage.

Dichotomy or Continuum: Grice's Distinction between Natural and Nonnatural Meaning

Grice (1957), in his theory of meaning, introduced a distinction between two different types of meaning: nonnatural meaning and natural meaning. Grice’s distinction has been put to use in other areas of philosophy as well. Most famously, Dretske (1981, 1986) used Grice’s distinction in his naturalized epistemology. Scarantino and Piccinini (2010) offered a probabilistic alternative for semantic theories of information based on Grice's distinction. In both Dretske’s and Scarantino and Piccinini’s works, Grice’s distinction is assumed to form a dichotomy. This dichotomous nature, I claim, is at the root of some of the problems that afflict Dretske’s information-based naturalized epistemology and Scarantino and Piccinini’s probabilistic approach to information. In this paper, I suggest a revised version of Grice's distinction. In this revised version, instead of a dichotomy, natural and nonnatural meaning categories form a continuity, allowing overlapping and mixed intermediary categories between natural and nonnatural meaning. This continuous version, I further claim, provides more resources for avoiding some of the problems that afflict Dretske’s naturalized epistemology and Scarantino and Piccinini’s probabilistic approach to information.