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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.

168,657 papers · 148 categories

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6121723 · Sep 201919922001200920172026
48 results for impulsive gravitational waves

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.

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.

We review recent work on the Einstein equations of general relativity when the curvature is defined in a weak sense. Weakly regular spacetimes are constructed, in which impulsive gravitational waves, as well as shock waves, propagate.

2010-09-09abs ↗pdf ↗

Stability of timelike Ricci bounds in low-regularity spacetimes.

problem Stability of synthetic timelike Ricci curvature bounds under C0C^0-limits.
method Constructing smooth approximations and analyzing limiting behavior via Lorentzian optimal transport.
result Impulsive gravitational waves satisfy synthetic timelike Ricci curvature lower bounds.

We define the notion of geodesic completeness for semi-Riemannian metrics of low regularity in the framework of the geometric theory of generalized functions. We then show completeness of a wide class of impulsive gravitational wave space-times.

2013-10-09abs ↗pdf ↗

Gravitational wave memory increases faster than Brownian motion in early universe and astrophysical sources.

problem Detecting gravitational wave memory from early universe and astrophysical sources.
method Investigated gravitational wave sources in early universe and astrophysical settings, showing memory increases faster than Brownian motion.
result Gravitational wave memory increases following a power law, faster than the t\sqrt{t} scaling law of Brownian motion.

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.

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.

Study examines the training process of an unsupervised learning model for detecting gravitational-wave transient noise.

problem Transient noise in gravitational-wave detector data causes instability and signal overlap.
method Unsupervised deep learning with variational autoencoder and invariant information clustering applied to the Gravity Spy dataset.
result Training process of the unsupervised learning architecture is examined and reported.

Unsupervised learning classifies transient noise in gravitational wave detectors.

problem Transient noise interferes with gravitational wave signals, causing instability.
method Combines variational autoencoder and invariant information clustering.
result Consistent classification with Gravity Spy project labels.

TIER uses extended strain data to improve gravitational wave detection sensitivity.

problem Improving gravitational wave detection sensitivity using extended strain data.
method TIER framework using machine learning to capture extended strain data features.
result Up to 20% improvement in sensitive volume time in LIGO-Virgo-Kagra O3 data.

Deep learning predicts nuclear equation of state from rotating core collapse GW signals.

problem Classifying the nuclear equation of state from rotating core collapse gravitational wave signals.
method Employed deep convolutional neural networks to classify visual and temporal patterns in GW signals.
result Up to 97% correct classifications of nuclear equation of state in the test set.

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 ↗

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.

Machine learning classifies gravitational wave signals to test General Relativity.

problem Testing General Relativity with gravitational wave signals from binary black hole mergers.
method Convolutional Neural Networks (CNNs) trained on whitened waveforms and response function type observables.
result CNNs improve classification sensitivity by a factor of approximately 33 compared to whitened waveforms.

We prove that the essential smoothness of the gravitational metric at shock waves in GR, a PDE regularity issue for weak solutions of the Einstein equations, is determined by a geometrical condition which we introduce and name the {\it Riemann-flat condition}. The Riemann-flat condition determines whether or not the es…

2016-10-07abs ↗pdf ↗

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.

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.

Bayesian Neural Networks detect gravitational wave events with high accuracy and real-time potential.

problem Detecting and identifying the full duration of compact binary coalescence events in gravitational wave data.
method Integrating Bayesian approach into a CLDNN classifier that combines CNN and LSTM for event detection and uncertainty estimation.
result Successfully detected all seven BBH events in LIGO Livingston O2 data with high accuracy.

Ehlers-Kundt conjecture is a physical assertion about the fundamental role of plane waves for the description of gravitational waves. Mathematically, it becomes equivalent to a problem on the Euclidean plane R2{\mathbb R}^2 with a very simple formulation in Classical Mechanics: given a non-necessarily autonomous potent…

2017-06-12abs ↗pdf ↗

Given a real vector space V of finite dimension, together with a particular homogeneous field of bivectors that we call a "field of projective forces", we define a law of dynamics such that the position of the particle is a "ray" i.e. a half-line drawn from the origin of V. The impulsion is a bivector whose support is …

2005-01-11abs ↗pdf ↗

Paper proves trapped surface formation for EMCSF system without symmetry assumptions.

problem Formation of trapped surfaces for the Einstein--Maxwell--charged scalar field system.
method Scale-critical trapped surface formation result established from past null infinity.
result Focusing of gravitational waves, concentration of electromagnetic fields, or condensation of scalar fields can lead to trapped surface formation.

Flatly Foliated Relativity (FFR) is a new theory which conceptually lies between Special Relativity (SR) and General Relativity (GR), in which spacetime is foliated by flat Euclidean spaces. While GR is based on the idea that "matter curves spacetime", FFR is based on the idea that "matter curves spacetime, but not spa…

2019-11-03abs ↗pdf ↗

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.

GNPE improves inference for astrophysical systems.

problem Efficiently incorporating geometric properties like equivariances in neural density estimation.
method GNPE integrates equivariances into neural posterior estimation, standardizing data pose while estimating parameters.
result GNPE achieves state-of-the-art accuracy in astrophysical binary black hole inference, reducing inference times by 3 orders of magnitude.

A classical problem in general relativity is the Cauchy problem for the linearised Einstein equation (the initial value problem for gravitational waves) on a globally hyperbolic vacuum spacetime. A well-known result is that it is uniquely solvable up to gauge solutions, given initial data on a spacelike Cauchy hypersur…

2018-02-16abs ↗pdf ↗

A general class of Lorentzian metrics, M0xR2M_0 x R^2, ds2=<.,.>+2dudv+H(x,u)du2ds^2 = <.,.> + 2 du dv + H(x,u) du^2, with (M0,<.,.>(M_0, <.,.> 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…

2002-11-05abs ↗pdf ↗