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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.

168,695 papers · 148 categories

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48 results for Time-dependent Systems

Study on relativistic nonholonomic mechanics with time-dependent constraints.

problem Formulating classical time-dependent nonholonomic mechanics.
method Invariant formulation using moving frames and Chaplygin systems.
result Hamiltonization of time-dependent constraints achieved.

Paper adapts causal analysis for time-dependent systems, especially energy management.

problem Challenges in root-cause analysis for systems with lagged time-dependencies, particularly in energy management.
method Adapts causal root-cause analysis method to time-dependent systems, discusses two truncation approaches.
result Extension effectively localizes root-causes in feature and time domain with enough lags.

The paper extends Marsden-Weinstein reduction to mechanical presymplectic structures for time-dependent Hamiltonian systems.

problem Limitations of Marsden-Weinstein reduction for cosymplectic structures in time-dependent Hamiltonian systems.
method Developed Marsden-Weinstein reduction for mechanical presymplectic structures.
result Mechanical presymplectic structures provide a more suitable framework for time-dependent Hamiltonian systems than cosymplectic structures.

Proposes a Koopman operator method for time-dependent reliability analysis of nonlinear systems.

problem Challenges in time-dependent reliability analysis of nonlinear dynamical systems.
method Koopman operator approach for transforming nonlinear systems into linear ones, combined with deep learning for intrinsic coordinates.
result Robust and generalizable approach for time-dependent reliability analysis, superior to purely data-driven methods.

We analyze families of non-autonomous systems of first-order ordinary differential equations admitting a common time-dependent superposition rule, i.e., a time-dependent map expressing any solution of each of these systems in terms of a generic set of particular solutions of the system and some constants. We next study…

2010-03-18abs ↗pdf ↗

Develops methods to learn correlation potentials for time-dependent Kohn-Sham systems.

problem Learning the correlation potential for time-dependent Kohn-Sham systems.
method Optimizing a least-squares objective subject to the TDKS equation using adjoints.
result Learned correlation potential models match ground truth electron densities and can have memory.

A new RNN model tackles long-time dependencies with fast, invertible, and memory-efficient hidden states.

problem Challenges in processing sequential inputs with long-time dependencies in RNNs.
method A novel RNN architecture based on a Hamiltonian system of oscillators.
result The proposed RNN mitigates exploding and vanishing gradient problems, providing state-of-the-art performance.

The paper develops methods to derive mixed superposition rules for Lie systems and applies them to various physical systems.

problem Finding general solutions for Lie systems.
method Develops mixed superposition rules for Lie systems with imprimitive Lie algebras and semidirect sums.
result Extends coalgebra method to Lie systems of partial differential equations.

The aim of this paper is to geometrize time dependent Lagrangian mechanics in a way that the framework of second order tangent bundles plays an essential role. To this end, we first introduce the concepts of time dependent connections and time dependent semisprays on a manifold MM and their induced vector bundle struc…

2016-07-08abs ↗pdf ↗

The constraint reaction force of ideal nonholonomic constraints in time-dependent mechanics on a configuration bundle QRQ\to R is obtained. Using the vertical extension of Hamiltonian formalism to the vertical tangent bundle VQVQ of QRQ\to R, the Hamiltonian of a nonholonomic constrained system is constructed.

1998-07-13abs ↗pdf ↗

DeepONet accelerates reliability analysis of stochastic nonlinear systems.

problem Time-dependent reliability analysis of systems with stochastic forcing.
method DeepONet, a novel operator network, learns function-to-function mappings.
result DeepONet efficiently and accurately predicts system responses.

Dynamic Structural Causal Models handle time-dependent systems with cycles and latent confounding.

problem Representing and analyzing systems of Stochastic Differential Equations (SDEs) with DSCMs.
method Define time-splitting and subsampling operations to analyze DSCMs of SDEs, and apply existing causal discovery algorithms to time-series data.
result DSCMs provide a graphical Markov property for SDEs and enable identification of time-dependent causal effects.

A time-dependent double-barrier option is a derivative security that delivers the terminal value φ(ST)φ(S_T) at expiry TT if neither of the continuous time-dependent barriers $b_\pm:[0,T]\to \RR_+$ have been hit during the time interval [0,T][0,T]. Using a probabilistic approach we obtain a decomposition of the barrier opti…

2008-09-10abs ↗pdf ↗

Economics tool predicts failure times in reliability systems.

problem Predicting optimal failure times in weighted k-out-of-n reliability systems with heterogeneous component failure.
method Using rational expectations to analyze and predict failure times in reliability systems with heterogeneous component failure.
result Different measures are optimal for predicting system failure depending on component failure distributions.

We present a unified derivation of covariant time derivatives, which transform as tensors under a time-dependent coordinate change. Such derivatives are essential for formulating physical laws in a frame-independent manner. Three specific derivatives are described: convective, corotational, and directional. The covaria…

2001-02-28abs ↗pdf ↗

Proposes a method to estimate time-dependent probability density functions using binary classifiers.

problem Estimating time-dependent probability density functions of stochastic processes.
method Trains a time-dependent binary classifier to discriminate between realizations of a stochastic process at two nearby time instants.
result Explicitly models and accurately reconstructs complex time-dependent, multi-modal, and near-degenerate densities.

The usual formulations of time-dependent mechanics start from a given splitting Y=R×MY=R\times M of the coordinate bundle YRY\to R. From physical viewpoint, this splitting means that a reference frame has been chosen. Obviously, such a splitting is broken under reference frame transformations and time-dependent canonical …

1997-02-25abs ↗pdf ↗

Paper develops semi-analytic method for American options in time-dependent jump-diffusion models.

problem Pricing American options in models with time-dependent and exponential jumps.
method Generalizes existing methods for barrier and American options to handle arbitrary time dependencies and solves the problem through algebraic and Fredholm-Volterra equations.
result Presents a semi-analytic solution for American options in time-dependent jump-diffusion models with exponential jumps.

In this paper we develop a Hamilton-Jacobi theory in the setting of almost Poisson manifolds. The theory extends the classical Hamilton-Jacobi theory and can be also applied to very general situations including nonholonomic mechanical systems and time dependent systems with external forces.

2012-09-24abs ↗pdf ↗

MAntRA combines machine learning and Bayesian methods for time-dependent reliability analysis of unknown systems.

problem Time-dependent reliability analysis of systems with unknown governing physics.
method Combines machine learning, Bayesian statistics, and stochastic integration to discover and analyze SDEs from data.
result Demonstrates the effectiveness of MAntRA on three numerical examples, indicating its potential for in-situ and heritage structure analysis.

New method for constructing contact Lie systems on various spaces.

problem Constructing contact Lie systems on Riemannian and Lorentzian spaces.
method Adaptation of scaling symmetries to Lie-Hamilton systems, leading to contact Lie systems.
result Curvature-dependent reductions of contact Lie systems on Cayley-Klein spaces.

CoNBONet improves reliability analysis of complex systems with fast, energy-efficient predictions.

problem Time-dependent reliability analysis of nonlinear systems under stochastic excitations is computationally demanding.
method CoNBONet combines deep operator networks with neuroscience-inspired neuron models for fast, energy-efficient inference.
result CoNBONet provides reliable coverage of failure probabilities with theoretical guarantees.

Study shows how heat leaks from material sets in low diffusivity scenarios.

problem Understanding heat leakage from material sets in low diffusivity limits.
method Generalized leading-order asymptotics for time-dependent diffusion processes.
result Diffusive transport out of a material set is proportional to the surface area of the set boundary.

Surrogate models help predict complex systems with less computational cost.

problem Uncertainty in complex systems due to variability and external loads.
method Surrogate models trained on limited simulations to approximate full time-dependent response.
result Efficient surrogate models reduce computational expense for UQ in nonlinear dynamics.

We address the problem of constructing numerical integrators for nonholonomic Lagrangian systems that enjoy appropriate discrete versions of the geometric properties of the continuous flow, including the preservation of energy. Building on previous work on time-dependent discrete mechanics, our approach is based on a d…

2002-09-24abs ↗pdf ↗

Extends integrability to cosymplectic manifolds.

problem Integrability of Hamiltonian systems on cosymplectic manifolds.
method Extended Arnold-Liouville and noncommutative integrability to cosymplectic manifolds, proved a variant of non-commutative integrability for specific fields, constructed action-angle variables.
result Variant of non-commutative integrability for evaluation and Reeb vector fields on cosymplectic manifolds.

The paper tackles drift identification in Lévy α-stable stochastic systems, proposing a Fourier space approach.

problem Estimating the drift field of a stochastic differential equation driven by Lévy α-stable noise.
method Fourier space approach, parameterizing the drift field using Fourier series, minimizing a loss function with gradients computed via the adjoint method.
result The method is capable of learning drift fields in qualitative and/or quantitative agreement with ground truth fields.

Starting from a bundle E over R, the dual of the first jet bundle, which is a co-dimension 1 sub-bundle of the cotangent bundle of E, is the appropriate manifold for the geometric description of time-dependent Hamiltonian systems. Based on previous work, we recall properties of the complete lifts of a type (1,1) tensor…

2014-07-18abs ↗pdf ↗

Optimizes electric field to control molecule states in Hartree-Fock theory.

problem Optimizing electric field to drive molecule from initial to target state.
method Trust region optimization with gradients from adjoint state method.
result Achieves desired target states with minimal control effort.

The Schlesinger equations S(n,m)S_{(n,m)} describe monodromy preserving deformations of order mm Fuchsian systems with n+1n+1 poles. They can be considered as a family of commuting time-dependent Hamiltonian systems on the direct product of nn copies of m×mm\times m matrix algebras equipped with the standard linear Poisson…

2006-10-10abs ↗pdf ↗

Developed a flexible Bayesian g-formula for causal survival analysis with time-dependent confounding.

problem Estimating causal survival curves in longitudinal observational studies with time-varying treatments and confounding.
method Incorporated Bayesian Additive Regression Trees (BART) into the g-formula to model time-evolving generative components and mitigate bias due to model misspecification.
result Demonstrated improved empirical performance and practical utility of the proposed method through simulations and real-world data analysis.

In this article we get a time-dependent Sobolev inequality along the Ricci flow which generalizes the earlier results of Zhang, Ye, Hsu. As an application of the time-dependent Sobolev inequality, we also get a growth of the ratio of bob-collapsing along the Ricci flow.

2008-12-10abs ↗pdf ↗