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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.

169,341 papers · 148 categories

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471114 · Oct 201919922001200920182026
48 results for satellite collision

Space debris warnings follow a predictable pattern, allowing timely satellite maneuvers.

problem Estimating when fresh information about space debris will arrive.
method Statistical learning model of the message arrival process, specifically a Bayesian Poisson process.
result The average prediction error for the next message arrival time is smaller than baseline predictions.

Residual neural networks improve collision prediction in planetary simulations.

problem Accurate prediction of planetary collisions in N-body simulations.
method Residual neural networks trained on collision data.
result Residual neural networks outperform existing methods in prediction accuracy and generalization.

Study nonholonomic systems with collisions using variational principles.

problem Variational problems on nonholonomic systems with collisions.
method Extended variational principle, introduced connection on principal bundles, applied Lagrange–Poincaré–Pontryagin reduction.
result Implicit Lagrange–d'Alembert–Pontryagin equations for nonholonomic systems with collisions.

Optimal alarms detect vehicle collisions with theoretical and empirical validation.

problem Detecting dangerous vehicle collisions in real-time.
method Surveyed and compared three classes of collision detection techniques: Monte Carlo, deterministic approximations, and machine learning.
result Monte Carlo sampling is a robust solution for real-time collision detection despite its simplicity.

Model forecasts motor vehicle collision rates with high accuracy.

problem Forecasting motor vehicle collision rates with high accuracy.
method Adopted Heston Stochastic Volatility model and extended it to account for seasonality and accelerated safety periods.
result Short-term forecasts show high accuracy (over 95%) and outperform existing models.

Paper analyzes dynamics of nonholonomic systems with collisions using variational techniques.

problem Analyzing the dynamics of nonholonomic mechanical systems with impacts.
method Variational techniques extended to nonsmooth context for collisions.
result Variational formulation for implicit nonholonomic mechanical systems with energy-momentum preserving collisions.

Deep neural network approximates collision avoidance table for aircraft systems.

problem High dimensionality of collision avoidance state space leads to large numeric tables.
method Used deep neural networks to approximate the numeric tables, using asymmetric loss functions and gradient descent.
result Reduced storage space by a factor of 1000, enabling current avionics systems.

New algorithms estimate and test collision probability with near-optimal sample complexity.

problem Estimating and testing collision probability in discrete distributions.
method Developed algorithms for (α,β)(α, β)-local differential privacy and sequential testing.
result Achieved nearly optimal sample complexity for estimating and testing collision probability.

Reduces necessary conditions for collision avoidance on curved spaces.

problem Finding non-intersecting trajectories for multiple agents on curved spaces.
method Reduction by Lie group symmetries of variational collision avoidance problems.
result Derives necessary conditions for reduced extremals.

New algorithm for multi-player bandits with collision-dependent rewards.

problem Stochastic multi-player multi-armed bandits with collision-dependent reward distributions.
method Error-Correction Collision Communication (EC3) algorithm.
result EC3 algorithm achieves optimal regret approaching centralized MP-MAB regret.

Develops machine learning classifiers for better centrality estimation in proton-nucleus and nucleus-nucleus collisions.

problem Direct measurement of centrality in A-A and p-A collisions is challenging due to limited data access.
method Uses machine learning techniques to classify centrality based on information from multiple detector subsystems.
result Improved centrality resolution can reduce volume fluctuations impact on physical observables.

Algorithm reduces regret in multi-player bandits with unknown collision rewards.

problem Reducing regret in multi-player multi-armed bandits with unknown collision rewards.
method Proposes an algorithm that combines a modified successive elimination strategy with a communication protocol to estimate suboptimality gaps and coordinate among players.
result Achieves logarithmic regret for the problem when collision reward is unknown.

New algorithm reduces regret in multi-player bandits with collision information.

problem Optimizing decisions in multi-player bandits with collision penalties.
method Developed an algorithm with optimal T\sqrt{T} regret under collision announcements, and sublinear regret without collision info.
result First T\sqrt{T}-type regret guarantee for non-stochastic multi-player multi-armed bandits with collision information.

This study uses reinforcement learning to mitigate imminent collisions by controlling car speed and direction.

problem Mitigating imminent collisions on roads.
method Constructed a model using camera images to predict obstacle dynamics. Trained reinforcement learning policies to control braking and steering.
result Both reinforcement learning policies outperform a baseline policy, with the injury model-based policy showing the highest performance.

Examining orbits ending in binary collisions for three equal masses under an inverse cube force.

problem Analyzing orbits ending in binary collisions for three equal masses under an inverse cube force.
method Reparametrizing orbits as geodesics on a negatively curved metric on a pair of pants.
result Visibility properties of negatively curved surfaces describe orbits beginning or ending in binary collisions.

New algorithms tackle adversarial multi-player bandits with forced-collision communication.

problem No-sensing adversarial multi-player multi-armed bandits (MP-MAB) problem.
method Adversary-Adaptive Collision-Communication (A2C2) algorithms, attackability-aware and unaware settings, information-theoretic tools, error-correction coding.
result Asymptotic attackability-dependent sublinear regret achieved, with or without knowing attackability.

New strategy achieves optimal regret without communication or collisions in multi-player bandit.

problem Cooperative multi-player stochastic multi-armed bandit with shared randomness.
method Combination of combinatorial approach to generalize geometric intuition.
result Achieves near-optimal regret ildeO(T) ilde{O}(\sqrt{T}) for any number of players and arms without collisions.

Novel method decomposes configuration space for improved collision checking.

problem Improving collision checking in high-degree-of-freedom robot motion planning.
method Proposes a configuration space decomposition method to build a composite classifier.
result Composite classifier outperforms state-of-the-art single classifier methods.

This study analyzes satellite communication latency using a stochastic geometry model.

problem Latency analysis of LEO satellite relay communication systems.
method Stochastic geometry framework with spherical BPP models, suboptimal satellite relay selection strategy.
result Derives distance distributions and analytical expressions for transmission delays.

Any knot in a solid torus, called a pattern or satellite operator, acts on knots in the 3-sphere via the satellite construction. We introduce a generalization of satellite operators which form a group (unlike traditional satellite operators), modulo a generalization of concordance. This group has an action on the set o…

2013-06-19abs ↗pdf ↗

Study shows how transformers classify symbols without naming them, proving a margin-versus-collision criterion.

problem How transformers classify symbols without naming them.
method Logistic classification analysis of transformer-kernel regime, colored collision graph.
result Decomposes learned predictor into ideal template-level classifier and finite-sample perturbation.

Develops a new framework for integrating satellite allocations in small portfolios.

problem Feasibility constraints in small portfolios, not return predictability, are the primary concerns.
method A four-layer feasibility framework: physical, economic, structural, and epistemic.
result Closed-form feasibility bounds on satellite size, turnover, and breadth without return forecasts.

FedSpace optimizes ML training on satellites and ground stations.

problem Training machine learning models on satellites with limited bandwidth.
method Federated Learning framework that dynamically schedules model aggregation based on satellite orbits.
result Reduces training time by 1.7 days over state-of-the-art algorithms.

New algorithm syncs multi-player bandits by deliberately causing collisions.

problem Stochastic multiplayer multi-armed bandit problem with collisions.
method Decentralized algorithm that exploits communication between players to share information.
result Achieves performance of centralized algorithm with negligible cost.

The Gluck twist preserves the diffeomorphism type of certain satellite 2-knots.

problem Preserving the diffeomorphism type of satellite 2-knots under the Gluck twist.
method Using new descriptions of satellite 2-knots, the paper shows that the Gluck twist does not change the diffeomorphism type of certain satellite 2-knots in three ways.
result The Gluck twist preserves the diffeomorphism type of certain satellite 2-knots.

Researchers compute Khovanov polynomials for satellite knots.

problem Computing Khovanov polynomials for satellite knots.
method Explicit computation using a computer program for two families of satellite knots.
result Khovanov polynomials can be expressed as a linear combination of pattern and companion invariants, with a jump at a critical point.