This study analyzes cryptocurrency price dynamics using complexity-entropy causality.
problem Understanding the price dynamics of cryptocurrencies during market booms and busts.
method Used permutation-information-theory quantifiers and complexity-entropy causality plane.
result Discerned three distinct dynamics in cryptocurrency price data.
Study uses new statistical tool to classify corporate bonds by informational efficiency, aligning with credit ratings.
problem Under scrutiny of credit rating agencies after subprime crisis, the study explores the relationship between credit ratings and informational efficiency.
method Used a permutation-information-theory analysis on a sample of corporate bonds using a complexity-entropy causality plane.
result The classification of bonds by informational efficiency agrees with their credit ratings, forming two clusters: investment and speculative grades.
Paper analyzes Libor rates using information theory to detect abnormal movements around the financial crisis.
problem Detecting abnormal movements in Libor rates during the financial crisis.
method Complexity-Entropy Causality Plane analysis with moving windows.
result Abnormal movements in Libor rates around the financial crisis period.
Cryptocurrencies are ranked for efficiency using a new Complexity-Entropy Plane.
problem Evaluating the efficiency of cryptocurrencies using traditional financial metrics.
method Developed a Binary Complexity-Entropy Plane (BiCEP) to analyze daily price fluctuations of major cryptocurrencies.
result Only Shiba Inu (SHIB) is significantly inefficient, while most cryptocurrencies operate in close-to-efficient conditions.
The paper uses information theory to detect anomalies in Libor rates.
problem Detecting anomalies in Libor rates during the financial crisis.
method Complexity-entropy causality plane analysis of time series data.
result Anomalous behavior in Libor rates detected, suggesting potential manipulation.
Cryptocurrency time-series predictability is low, resembling Brownian noise.
problem Low predictability of cryptocurrency exchange rates.
method Complexity and model predictions of Litecoin, Binance Coin, Bitcoin, Ethereum, and XRP exchange rates.
result Simpler models outperform complex ones in cryptocurrency forecasting.
Machine learning and complexity-entropy methods estimate liquid crystal properties from textures.
problem Extracting physical properties from liquid crystal textures.
method Combining permutation entropy, statistical complexity, and machine learning.
result Significant precision in predicting physical properties of liquid crystals.
The abstract discusses a new causal structure on manifolds using paths and points.
problem Constructing a causal structure on manifolds using paths and points.
method Constructing a four-manifold from pairs of points and paths, and a seven-dimensional manifold from pairs of points and conics.
result The causal structure corresponds to a conformal structure only when the underlying surface is a real projective plane.
A simple characterization of the causal automorphisms of 1+1 Minkowski spacetime is given.
We study the temporal evolution of the market efficiency in the stock markets using the complexity, entropy density, standard deviation, autocorrelation function, and probability distribution of the log return for Standard and Poor's 500 (S&P 500), Nikkei stock average index, and Korean composition stock price index (K…
New definitions of null infinity extend black hole theory to generalized plane waves.
problem Extend black hole theory to generalized plane waves with non-standard null infinity.
method New definitions of null infinity and black hole regions in terms of causal boundaries.
result Closed trapped surfaces are inside black hole regions if null infinity is regular and null convergence condition is obeyed.
In this paper, we parametrize the space of isometric immersions of the hyperbolic plane into the hyperbolic 3-space in terms of null-causal curves in the space of oriented geodesics. Moreover, we characterize "ideal cones" (i.e., cones whose vertices are on the ideal boundary) by behavior of their mean curvature.
The notion of a causal boundary for a spacetime has been a controversial topic during the last three decades. Moreover, recently the role of the boundary in the AdS/CFT correspondence for plane waves, have stimulated its redefinition with some possible alternatives. Our aim is threefold. First, to review the different …
Classifies zero mean curvature surfaces in Lorentz-Minkowski space by their causal characters.
problem Classifying zero mean curvature surfaces in Lorentz-Minkowski space.
method Classification based on foliation by circles and straight lines in parallel planes.
result Surfaces with exactly two causal characters have a lightlike part as a straight line.
Study of closed trajectories in hyperbolic plane with specific curvature constraints.
problem Critical trajectories in hyperbolic plane for a specific energy function.
method Classification of critical trajectories based on momentum causal character, proof of existence of closed trajectories.
result Existence of countably many closed trajectories with time-like momentum.
Recently ({\em Class. Quant. Grav.} {\bf 20} 625-664) the concept of {\em causal mapping} between spacetimes --essentially equivalent in this context to the {\em chronological map} one in abstract chronological spaces--, and the related notion of {\em causal structure}, have been introduced as new tools to study causal…
The paper explores neutral 4-manifolds with null boundaries using causal topology.
problem Neutral 4-manifolds with null boundaries and their topological properties.
method Neutral causal topology, foliation of null hypersurfaces, and geometric constructions.
result Neutral 4-manifolds with null boundaries and their topological properties.
Equivalence found between smooth and synthetic timelike curvature bounds.
problem Understanding timelike sectional curvature bounds in spacetime geometry.
method Established equivalence between sectional curvature bounds on timelike planes and synthetic timelike bounds.
result Equivalence proved for sectional curvature bounds on timelike planes and synthetic timelike bounds on strongly causal spacetimes.
Starting from the recent classification of quotients of Freund--Rubin backgrounds in string theory of the type AdS_{p+1} x S^q by one-parameter subgroups of isometries, we investigate the physical interpretation of the associated quotients by discrete cyclic subgroups. We establish which quotients have well-behaved cau…
Review of information plane analyses in neural networks, highlighting mixed results and methodological challenges.
problem Understanding the relationship between information-theoretic compression and neural network performance.
method Literature review and detailed analysis of information quantity estimation methods.
result Information plane compression is not necessarily information-theoretic but compatible with geometric compression.
Causal fermion systems and Riemannian fermion systems are proposed as a framework for describing non-smooth geometries. In particular, this framework provides a setting for spinors on singular spaces. The underlying topological structures are introduced and analyzed. The connection to the spin condition in differential…
Study counts catenoids connecting two coaxial circles in 3D Lorentz-Minkowski space.
problem Determining the number of catenoids connecting two coaxial circles in 3D Lorentz-Minkowski space.
method Separated analysis by circle type and catenoid causal character (spacelike and timelike).
result Number of catenoids is determined for different circle and catenoid types.
New metrics derived from geodesics simplify semi-Riemannian geometry.
problem Simplifying complex semi-Riemannian metrics.
method Constructing plane wave limits along geodesics.
result Generalizes Penrose's limit and encodes tensorial geometry.
The paper classifies ruled surfaces in Lorentz-Minkowski space that are stationary for the moment of inertia.
problem Classifying ruled surfaces in Lorentz-Minkowski space that are stationary for the moment of inertia.
method Maximum principle applications, classification based on causal character of rulings.
result Planes are the only cylindrical stationary surfaces. For non-cylindrical surfaces, classification depends on the causal character of the rulings.
A general class of Lorentzian metrics, M0xR2, ds2=<.,.>+2dudv+H(x,u)du2, with (M0,<.,.> any Riemannian manifold, is introduced in order to generalize classical exact plane fronted waves. Here, we start a systematic study of their main geodesic properties: geodesic completeness, geodesic connected…
Cognitive abstraction metrics predict deep neural networks' generalization ability.
problem Understanding deep neural networks' generalization ability.
method Defined Cognitive Neural Activation (CNA) metric based on information complexity and activation patterns.
result CNA is highly predictive of generalization ability, outperforming other metrics.
New entire graphs of mixed type found in Lorentz-Minkowski space.
problem Finding entire graphs of mixed type with zero mean curvature.
method Constructing families of real analytic entire graphs of mixed type.
result Several families of entire graphs of mixed type with zero mean curvature were constructed.
Study on Hausdorff dimension and curvature bounds in sub-Lorentzian Heisenberg group.
problem Hausdorff dimension and curvature bounds in sub-Lorentzian Heisenberg group.
method Elementary variational approach, Lorentzian isoperimetric problem, uniform estimate of causal diamonds.
result Heisenberg group has Lorentzian Hausdorff dimension 4 and satisfies neither timelike curvature-dimension nor measure contraction properties.
Study on surfaces in a pseudo-isotropic space with constant curvature.
problem Characterizing surfaces in a specific pseudo-isotropic space.
method Formulated curvature and torsion formulas for spacelike and timelike curves; introduced formulas for Gaussian and mean curvature for timelike surfaces.
result Timelike surfaces in the space have constant Gaussian and mean curvature.
The notion of wind Finslerian structure is developed; this is a generalization of Finsler metrics where the indicatrices at the tangent spaces may not contain the zero vector. In the particular case that these indicatrices are ellipsoids, called here wind Riemannian structures, they admit a double interpretation which …
Study examines market response to concentrated policy communication using entropy measures.
problem Characterizing market response under concentrated policy communication.
method Jointly examines dispersion and information complexity (entropy) using sliding window cumulative entropy.
result Entropy captures both market volatility and narrative constraints, signaling coherent policy-driven moves.
New framework learns disentangled causal representations from observed labels.
problem Learning meaningful disentangled causal representations from observed data.
method ICM-VAE framework using flow-based diffeomorphic functions and causal disentanglement prior.
result Induces highly disentangled causal factors and improves robustness.
Using symplectic topology and the Radon transform, we prove that smooth 4-dimensional projective planes are diffeomorphic to CP2. We define the notion of a plane curve in a smooth projective plane, show that plane curves in high dimensional regular planes are lines, prove that homeomorphisms preserving plan…
Reinterprets Granger causality with causal Bayesian networks and Reichenbach's principles.
problem Lack of a rigorous causal foundation in Granger causality.
method Reinterpreting Granger causality through Reichenbach's principles and causal Bayesian networks, implementing as c-GC.
result c-GC provides a more principled framework for causal discovery in observational datasets.
Study bifurcation in plane-to-plane germs with specific properties.
problem Understanding the structure of bifurcations in a specific class of geometric objects.
method Explicit description of the bifurcation diagram of the topologically A-versal unfolding.
result Explicit description of the bifurcation diagram for a specific class of plane-to-plane germs.
We define generalized distance-squared mappings, and we concentrate on the plane to plane case. We classify generalized distance-squared mappings of the plane into the plane in a recognizable way.
New measures for causal entropy and information gain studied.
problem Quantifying causal relationships in machine learning.
method Formal study of causal entropy and information gain.
result Established fundamental properties and relationships.
The study classifies semiaffine stable planes into affine, projective, or punctured projective planes.
problem Characterizing semiaffine stable planes.
method Analyzing properties of lines and points in stable planes.
result Semiaffine stable planes are either affine, projective, or punctured projective planes.
We quantify causal bias in continuous treatment settings.
problem Identifying and quantifying causal bias in continuous treatment scenarios.
method Developed a novel characterization of causal bias in structural causal models, proving conditions for zero bias and efficient estimation.
result Causal bias can be estimated efficiently under certain structural equation restrictions, allowing for causal regularization of predictive models.
Improved Granger causality method for dynamic time series data.
problem Traditional Granger causality method assumes constant causalities, failing to model dynamic causalities.
method Dynamic window-level Granger causality (DWGC) method with causality indexing.
result Improved DWGC method better detects window-level causalities.
Extends results on automorphism groups of flat Minkowski planes to toroidal circle planes.
problem Understanding automorphism groups of toroidal circle planes.
method Extending Schenkel's results to toroidal circle planes.
result Automorphism groups of toroidal circle planes have dimensions at most 6 and can have dimensions at least 4 or kernels of dimension 3.
The study examines causal razors and their logical relations, highlighting a dilemma in causal discovery.
problem Selecting a reasonable scoring criterion for causal discovery algorithms.
method Review and logical comparison of numerous causal razors, focusing on parameter minimality in multinomial models.
result Parameter minimality poses a dilemma in selecting a reasonable scoring criterion for causal discovery algorithms.
Stable planes are locally isomorphic to classical projective planes.
problem Characterizing stable planes that are locally isomorphic to classical projective planes.
method Analyzing properties of stable planes and comparing them to classical projective planes over specific fields.
result Simply connected stable planes with connected lines are isomorphic to open subplanes of classical projective planes.
CIB compresses variables causally, preserving key causal interactions.
problem Constructing causal variable abstractions in complex systems.
method Causal Information Bottleneck (CIB) method, extending IB to include causal structures.
result CIB produces causally interpretable abstractions that accurately capture causal relations.
Paper characterizes and represents pairwise causal background knowledge for improved causal inference.
problem Improving causal inference by handling pairwise causal constraints.
method Graphical characterization, direct causal clause (DCC), unified representation, MPDAG, polynomial-time algorithms.
result Pairwise causal background knowledge uniquely decomposes into MPDAG and DCCs, improving causal effect identification.
Python toolbox uncovers causal relationships from data.
problem Discovering causal relationships from observational data.
method End-to-end approach using algorithms from 'Bnlearn' and 'Pcalg', including pairwise causal discovery.
result Recovery of direct dependencies and causal relationships.
Only vertical planes are asymptotic to other planes in 3D space.
problem Characterizing asymptotic planes in 3D space.
method Proof of uniqueness for complete translators with finite topology.
result Vertical planes are the only asymptotic planes in 3D space.
A new method clusters heterogeneous subgroups for accurate causal learning.
problem Diverse causal relationships across different time spans, regions, or strategies.
method Nonlinear Causal Kernel Clustering
result Reduction in prediction error through enhanced causal learning.