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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,181 papers · 148 categories

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25.0%50.0%75.0%100.0% · Jul 199219922001200920182026
48 results for first and second laws of thermodynamics

The study analyzes social and economic systems using bosonic and fermionic statistics.

problem Analyzing hierarchical social and economic systems.
method Intermediate Gentile statistics and derivation of thermodynamic laws.
result Introduces concepts like temperature and pressure for economic systems.

Entropy convexity characterizes strong energy condition in spacetimes.

problem Characterizing strong energy condition in nonsmooth spacetimes.
method Lifting fractional powers of Lorentz distance to probability measures and showing geodesic convexity of Boltzmann-Shannon entropy.
result Strong energy condition is equivalent to geodesic convexity of Boltzmann-Shannon entropy.

Geometric approach to quantum thermodynamics models state spaces and processes.

problem Quantum thermodynamics in the regime of non-equilibrium states.
method Contact geometry and principal fiber bundles to model quantum state spaces and processes.
result Geometric formulation reveals the fundamental thermodynamic relations and unattainability of the third law.

Financial market dynamics compared to thermodynamics.

problem Understanding the dynamics of financial markets through thermodynamic principles.
method Analogy with Szilárd information engine to derive market temperature and information extraction.
result Informed traders' gains are bounded by market temperature and information.

The paper provides a geometric framework for understanding non-equilibrium thermodynamics.

problem Unclear geometric structure of GENERIC in non-equilibrium thermodynamics.
method Cotangent lifts of dynamics, splitting into holonomic and vertical representatives, and formulation within contact geometry.
result Physical meaning and explicit formulation of the second law of thermodynamics within evolution equations.

The paper applies thermodynamics to financial markets to prove no-arbitrage constraints.

problem No arbitrage in financial markets under price impact.
method Stochastic thermodynamics applied to financial trading cycles.
result Proves any round-trip trading strategy yields non-positive expected profit.

The paper explores how organisms and machines learn from their environment using machine learning, information theory, and thermodynamics.

problem How organisms and machines adapt to their environment.
method Machine learning, information theory, and thermodynamics approaches to understanding and modeling adaptation.
result Unified view of adaptation in organisms and machines based on principles of machine learning, information theory, and thermodynamics.

Schrödinger and Onsager's ideas linked in nonequilibrium thermodynamics.

problem Linking Schrödinger's variational problem with Onsager's nonequilibrium statistical mechanics.
method Analyzing the historical context and comparing the two approaches.
result Schrödinger's ideas have not yet been fully integrated into the classical context of Onsager's work.

Every production-recycling iteration accumulates an inevitable proportion of its matter-energy in the environment, lest the production process itself would be a system in perpetual motion, violating the second law of Thermodynamics. Such high-entropy matter depletes finite stocks of ecosystem services provided by the e…

2013-09-09abs ↗pdf ↗

We formulate the variational problem for AdS gravity with Dirichlet boundary conditions and demonstrate that the covariant counterterms are necessary to make the variational problem well-posed. The holographic charges associated with asymptotic symmetries are then rederived via Noether's theorem and `covariant phase sp…

2005-05-23abs ↗pdf ↗

Unified theory for curved shell deformations with elastic and inelastic components.

problem Coupled nonlinear elastic and inelastic deformations of curved thin shells.
method Multiplicative decomposition of surface deformation gradient, detailed kinematics analysis, surface balance laws, constitutive relations derived from thermodynamics.
result Unified constitutive relations for growth, chemical swelling, thermoelasticity, viscoelasticity and elastoplasticity of shells.

This study compares different thermodynamic structure-informed neural networks for solving differential equations.

problem Improving the accuracy and physical consistency of neural network solutions to differential equations.
method Comprehensive evaluation of various thermodynamic formulations in physics-informed neural networks.
result Newtonian-residual-based PINNs fail to reliably recover physical quantities, while structure-preserving formulations enhance accuracy and robustness.

We formulate thermodynamics of economic systems in terms of an arbitrary probability distribution for a conserved economic quantity. As in statistical physics, thermodynamic macroeconomic variables emerge as the mean value of microeconomic variables and their determination is reduced to the computation of the partition…

2009-03-25abs ↗pdf ↗

The present paper analyses the formal parallelism existing between the laws of thermodynamics and some economic principles. Based on previous works, we shall show how the existence in Economics of principles analogous to those in thermodynamics involves the occurrence of economic events that remind of well-known phenom…

2015-05-03abs ↗pdf ↗

TANNs integrate thermodynamics into ANN models for accurate, consistent predictions.

problem Lack of rigorous physics-based approach in ANN constitutive modeling.
method TANNs encode thermodynamics principles in neural network architecture using automatic differentiation.
result TANNs produce thermodynamically consistent predictions without requiring large datasets.

Researchers create black holes isometric to extremal Reissner-Nordström.

problem Third law of black hole thermodynamics.
method Novel CkC^k characteristic gluing procedure and scalar field pulses.
result Definitive disproof of the third law of black hole thermodynamics.

The article explores how organisms and machines learn and recognize the world using Bayesian inference and thermodynamics.

problem Understanding how organisms and machines learn and recognize the world.
method Introducing a thermodynamic view of the Bayesian brain hypothesis, using a simple generative model of spiking neural populations.
result The process of Bayesian inference can be quantified using entropy, revealing the perceptual capacity of neural activity.

The notion of utility maximising entropy (u-entropy) of a probability density, which was introduced and studied by Slomczynski and Zastawniak (Ann. Prob 32 (2004) 2261-2285, arXiv:math.PR/0410115 v1), is extended in two directions. First, the relative u-entropy of two probability measures in arbitrary probability space…

2007-09-09abs ↗pdf ↗

Geodesic coordinates derived for a specific metric in surface group representations.

problem Computing geodesic coordinates for a specific metric in surface group representations.
method Using thermodynamic formalism and gauge-theoretic formulas, computing first and second derivatives of the pressure metric.
result First derivatives of the pressure metric vanish at the Fuchsian locus.

Unified thermodynamic approach to Transformer attention dynamics.

problem Understanding the statistical mechanics of Transformer attention.
method Constructing a Lagrangian on the information manifold to analyze attention dynamics.
result Establishes a formal correspondence between scaled dot-product attention and canonical ensemble statistics.

Study finds conservation laws for a specific class of parabolic equations.

problem Existence and structure of conservation laws for evolutionary scalar second-order differential equations.
method Calculation of linearized characteristic cohomology to find conservation laws, showing dependence on second derivatives.
result Only Monge-Ampère type equations have non-trivial conservation laws.

This work develops a machine learning approach to EOS models that accounts for thermodynamic constraints and model uncertainty.

problem Developing accurate equation of state models for high energy-density experiments with inherent uncertainties.
method Physics-informed Gaussian process regression (GPR) framework to capture model uncertainty and thermodynamic constraints.
result The proposed framework reduces prediction uncertainty by incorporating thermodynamic constraints, as demonstrated for diamond carbon EOS.

New analysis shows temperature guarantees generalization in stochastic training.

problem Analyzing the generalization gap in stochastic training algorithms.
method Analyzing Langevin dynamics with positive temperature and bounding the generalization gap.
result Bounding the generalization gap by √(βE[L(θ_0)] + log(1/δ))/√N with probability 1-δ.

The study describes society as a probabilistic system with entropy and diversity, finding new statistical approaches.

problem Understanding entropy and diversity in social systems.
method Modeling society as a probabilistic system, analyzing entropy and inequality, applying thermodynamic principles.
result New statistical approaches (Fermi-Dirac and Bose-Einstein) for employment and income distribution.

Universal model for soft tissue mechanics under shock waves.

problem Modeling shock wave mechanics in soft biological tissues.
method Continuum mixture theory with phase-field mechanics.
result Universal thermodynamically consistent formulation for soft porous tissues.

Algorithm learns latent variables for thermodynamically-consistent deep neural networks.

problem Predicting time evolution of large-scale physical systems with thermodynamic consistency.
method Sparse autoencoders and structure-preserving neural networks.
result Method conserves total energy and entropy inequality for both conservative and dissipative systems.

Statistical models of economic distributions lead to Boltzmann distributions rather than a Pareto power law. This result is supported by two facts: 1. the distributions of income, car sales, marriages or jobs are a matter of chances and luck and not of reason! 2. Data for property, automobile sales, marriages and job m…

2002-04-10abs ↗pdf ↗

Using a model based on generalised Lotka Volterra dynamics together with some recent results for the solution of generalised Langevin equations, we show that the equilibrium solution for the probability distribution of wealth has two characteristic regimes. For large values of wealth it takes the form of a Pareto style…

2000-10-16abs ↗pdf ↗

Parsimonious neural networks discover interpretable physical laws from data.

problem Discovering interpretable physical laws from data using machine learning.
method Combining neural networks with evolutionary optimization to balance accuracy and parsimony.
result Developed models for classical mechanics and materials melting temperature prediction.

The paper solves a thermodynamics problem about crystal shape.

problem Understanding if minimizing free energy with convex potential and mass constraint generates a convex crystal.
method Utilized a stability theorem, convexity, and a new maximum principle approach to prove a three-dimensional convexity theorem.
result Completely settled the Almgren problem in R3\mathbb R^3 under generic conditions.

The paper studies symmetries and conservation laws of non-diagonalisable hydrodynamic systems.

problem Integrating non-diagonalisable hydrodynamic systems of partial differential equations.
method Analysis of gl-regular Nijenhuis operators, splitting Theorem for symmetries and conservation laws, relationship between symmetries and conservation laws.
result The system of partial differential equations is integrable in quadratures.