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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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119238356475 · Jun 202019922001200920172026
48 results for wave estimates

Study proves interaction of three impulsive gravitational waves, showing local solution and Lipschitz continuity.

problem Interaction of three impulsive gravitational waves in Einstein vacuum equations.
method Geometric estimates and wave estimates to prove local solution and continuity.
result Local solution to Einstein vacuum equations with three impulsive gravitational waves, Lipschitz continuity.

Study axisymmetric waves on extremal Kerr spacetime using physical-space estimates.

problem Obtain integrated local energy decay estimates for axisymmetric waves on extremal Kerr backgrounds.
method Use physical-space analysis and a method introduced by Stogin, simplifying Aretakis' derivation.
result Extend Morawetz estimates to extremal Kerr spacetime using purely classical currents.

Study proves well-posedness and scattering for wave equations on hyperbolic spaces with singular data.

problem Proving well-posedness and scattering for wave equations on hyperbolic spaces with singular initial data.
method Using weak-LpL^{p} spaces and dispersive estimates on Lorentz spaces, the study establishes global well-posedness and exponential asymptotic stability.
result Developed a scattering theory and constructed wave operators in a singular framework.

Second paper in series solves Einstein vacuum equations for three impulsive waves.

problem Solving local Cauchy problem for impulsive gravitational waves.
method Geometric commutators for energy estimates, fractional-derivative regularity, anisotropic Sobolev embedding.
result Scalar field becomes everywhere Lipschitz and C1,θC^{1,θ} away from singular region.

Simulation-based inference speeds up gravitational wave data analysis.

problem High-dimensional parameter spaces and complex noise in gravitational wave data.
method Simulation-based inference methods using machine learning techniques.
result Simulation-based inference methods improve speed over traditional methods.

Geometric focusing affects dispersive estimates for Schrödinger and wave equations.

problem Long-time decay rate in dispersive estimates for Schrödinger and wave equations on non-trapping asymptotically conic manifolds and exact metric cones.
method Classifying the long-time decay rate in dispersive estimates for the Schrödinger and wave equations on non-trapping asymptotically conic manifolds and exact metric cones in terms of the intensity of geometric focusing.
result Each multiplicity of conjugate points within distance π on Y = ∂X0 leads to a |t|1/2-loss in the long-time decay order and a half-order shift in the regularity index in the dispersive estimate for the Schrödinger equation.

The paper establishes scattering theory for wave equations on Schwarzschild spacetime.

problem Defocusing semilinear wave equations on Schwarzschild spacetime.
method Combining energy and pointwise decay results with Sobolev embedding, constructing scattering operator.
result Construction of a scattering operator mapping past to future scattering data.

Study dispersive estimates for Schrödinger and wave equations on a cone with specific metric.

problem Pointwise decay estimates for Schrödinger and wave equations on a product cone.
method Modified Hadamard parametrix on YY with ε>πε > π to prove dispersive estimates.
result Threshold of conjugate radius ε>πε > π for pointwise dispersive estimates.

Study examines wave equation decay and Strichartz estimates on conic manifolds.

problem Analyzing wave equation behavior on conic spaces with critical electromagnetic potentials.
method Established decay and Strichartz estimates through localized spectral measure construction.
result Extended and improved previous results on wave equation behavior with critical potentials.

Paper proves stability of multi-dimensional rarefaction waves in gas dynamics.

problem Challenges in constructing multi-dimensional rarefaction waves in gas dynamics.
method Geometric Weighted Energy Method (GWEM) to overcome derivative losses.
result Established nonlinear stability of multi-dimensional rarefaction waves for compressible Euler equations.

This paper addresses parameter estimation for wave equations with Markovian switching.

problem Parameter estimation for wave equations with abrupt changes.
method Bayesian statistical framework using discrete sparse Bayesian learning.
result Strong performance in parameter estimation for variable coefficient PDEs.

In a previous paper on coupled gravitational and electromagnetic perturbations of Reissner-Nordström spacetime in a polarized setting, we derived a system of wave equations for two independent quantities, one related to the Weyl curvature and one related to the Ricci curvature of the perturbed spacetime. We analyze her…

2018-04-16abs ↗pdf ↗

Novel approach to wave equations near null infinity in flat spacetimes.

problem Analyzing regularity and decay of wave equations near null infinity in asymptotically flat spacetimes.
method Microlocal analysis in a compactified spacetime with corners, focusing on edge-type wave operators.
result Microlocal regularity propagates across null infinity via radial sets, leading to new estimates for wave equations.

Deep learning helps remove secondary BB-mode polarization to detect primordial gravitational waves.

problem Removing secondary BB-mode polarization from CMB data to detect primordial gravitational waves.
method Applied deep learning (ResUNet-CMB) to estimate and remove multiple sources of secondary BB-mode polarization.
result Deep learning can produce nearly optimal, unbiased estimates of the amplitude of primordial gravitational waves.

WAVE improves stability in reinforcement learning by adaptively weighting critic's loss.

problem Inherent instability in actor-critic reinforcement learning algorithms.
method Wasserstein adaptive value estimation with Sinkhorn approximation.
result Achieves $\mathcal{O}\left(\frac{1}{k} ight)$ convergence rate for critic's mean squared error.

Proves energy estimates for tensorial wave equations, decoupling components for stability proof.

problem Proving stability of (1+3)(1+3)-Minkowski space-time with various non-linearities.
method Decouples energy estimates for tensorial wave equations, exploiting tensorial structure and Lie derivatives.
result Decoupled energy estimates for tensorial solutions, allowing new stability proofs.

Neural networks improve gravitational-wave parameter estimation.

problem Estimating parameters of binary black hole systems from gravitational-wave data.
method Autoregressive normalizing flows for likelihood-free inference.
result Performance comparable to current best deep-learning approaches, with fast sampling.

We study the following problem: Given initial data on a compact Cauchy horizon, does there exist a unique solution to wave equations on the globally hyperbolic region? Our main results apply to any spacetime satisfying the null energy condition and containing a compact Cauchy horizon with surface gravity that can be no…

2018-02-27abs ↗pdf ↗

Study proves global existence and decay for complex wave equations.

problem Global existence and decay for quasilinear wave equations with weak-null condition.
method Novel decoupling of higher order energy estimates, focusing on tangential components.
result Established global existence and decay for solutions with small data.

A nonlinear wave alternative for the standard Black-Scholes option-pricing model is presented. The adaptive-wave model, representing 'controlled Brownian behavior' of financial markets, is formally defined by adaptive nonlinear Schrödinger (NLS) equations, defining the option-pricing wave function in terms of the stock…

2009-11-10abs ↗pdf ↗

Estimates classical potential from stock price data using quantum mechanics.

problem Estimating classical potential from empirical stock price data.
method Quantum mechanical model of stock price distribution, estimating potential from wave function.
result Suggests methods to evaluate classical potential for Schrodinger equation.

New approach simplifies proof of wave equations on black holes.

problem Global existence and decay for semilinear wave equations on extremal Reissner-Nordström black holes.
method Develops a new approach based on weaker estimates, avoiding near-horizon sharp estimates.
result Simpler and more streamlined proof without requiring near-horizon sharp estimates.

The Einstein equations in wave map gauge are a geometric second order system for a Lorentzian metric. To study existence of solutions of this hyperbolic quasi diagonal system with initial data on a characteristic cone which are not zero in a neighbourhood of the vertex one can appeal to theorems due to Cagnac and Dossa…

2010-12-02abs ↗pdf ↗

We explore a model of dark matter called wave dark matter (also known as scalar field dark matter and boson stars) which has recently been motivated by a new geometric perspective by Bray. Wave dark matter describes dark matter as a scalar field which satisfies the Einstein-Klein-Gordon equations. These equations rely …

2013-11-24abs ↗pdf ↗

The mixture of Gaussian distributions, a soft version of k-means , is considered a state-of-the-art clustering algorithm. It is widely used in computer vision for selecting classes, e.g., color, texture, and shapes. In this algorithm, each class is described by a Gaussian distribution, defined by its mean and covarianc…

2016-12-29abs ↗pdf ↗

Kolmogorov-Arnold network improves GW catalog posterior construction.

problem Efficiently constructing posterior distributions for GW catalogs.
method Using the Kolmogorov-Arnold network to create lightweight neural density estimators.
result Kolmogorov-Arnold network achieves superior interpretability and accuracy in posterior construction.

We prove a dynamical wave trace formula for asymptotically hyperbolic (n+1) dimensional manifolds with negative (but not necessarily constant) sectional curvatures which equates the renormalized wave trace to the lengths of closed geodesics. A corollary of this dynamical trace formula is a dynamical resonance-wave trac…

2008-09-19abs ↗pdf ↗

Study shows how electromagnetic and gravitational waves can form trapped surfaces.

problem Formation of trapped surfaces from initial data with electromagnetic fields.
method Established a scale-critical semi-global existence result from past null infinity for the Einstein-Maxwell system.
result Generalized approach for studying Einstein vacuum equations and extended a result to scale-critical regime.

Estimates high-dimensional posterior densities by marginal distributions and neural networks.

problem High-dimensional probability density estimation for inference is difficult.
method Direct estimation of lower-dimensional marginal distributions, using Moment Networks for fast computation of moments.
result Demonstrates estimation of gravitational wave time series and applications in cosmology.

Global existence and decay for quasilinear wave equations on various spacetimes, including Kerr black holes.

problem Global existence and decay for quasilinear wave equations on asymptotically flat spacetimes.
method Dyadically localised nature and direct use of a blackbox linear inhomogeneous energy estimate on exactly stationary metrics.
result Global existence and decay for small-data solutions to quasilinear wave equations on a wide variety of spacetime backgrounds, including Kerr black holes.

Analyzes Gerstner's trochoidal waves and their geometric properties.

problem Understanding the geometry and kinematics of trochoidal waves.
method Derives velocity and arc length conditions for cycloidal, curtate, and prolate trochoids using Galilean transformations.
result Conditions for arc lengths of prolate and curtate trochoids to coincide over a wave cycle.

New method for efficient inference over complex parameter spaces.

problem Challenges in Bayesian inference for high-dimensional, intractable likelihoods.
method Arbitrary Marginal Neural Ratio Estimation (AMNRE) for simulation-based inference.
result Efficient inference over arbitrary subsets of parameters without numerical integration.