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Related papers: A Unified Approach for Beam-to-Beam Contact

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In millimeter-wave (mmWave) communications, directional transmission based on beamforming is important to compensate for high pathloss. To maintain the desired direction transmission gain, beam scanning that involves the transmitter sending…

Systems and Control · Electrical Eng. & Systems 2024-01-02 Huang-Chou Lin , Kuang-Hao , Liu

Physics simulation is ubiquitous in robotics. Whether in model-based approaches (e.g., trajectory optimization), or model-free algorithms (e.g., reinforcement learning), physics simulators are a central component of modern control pipelines…

Robotics · Computer Science 2024-07-23 Quentin Le Lidec , Wilson Jallet , Louis Montaut , Ivan Laptev , Cordelia Schmid , Justin Carpentier

Bounce-averaged theories provide a framework for simulating relatively slow processes, such as collisional transport and quasilinear diffusion, by averaging these processes over the fast periodic motions of a particle on a closed orbit.…

Plasma Physics · Physics 2025-07-02 I. E. Ochs

Despite decades of research, the modeling of moving contact lines has remained a formidable challenge in fluid dynamics whose resolution will impact numerous industrial, biological, and daily life applications. On the one hand, molecular…

Soft Condensed Matter · Physics 2018-11-09 E. R. Smith , P. E. Theodorakis , R. V. Craster , O. K. Matar

Approximate Bayesian Computation (ABC) methods have become essential tools for performing inference when likelihood functions are intractable or computationally prohibitive. However, their scalability remains a major challenge in…

Methodology · Statistics 2025-07-09 Antoine Luciano , Charly Andral , Christian P. Robert , Robin J. Ryder

Approximate Bayesian Computation (ABC) is a powerful method for carrying out Bayesian inference when the likelihood is computationally intractable. However, a drawback of ABC is that it is an approximate method that induces a systematic…

Methodology · Statistics 2015-09-29 Minh Ngoc Tran , Robert Kohn

Cooperative perception is a promising technique for intelligent and connected vehicles through vehicle-to-everything (V2X) cooperation, provided that accurate pose information and relative pose transforms are available. Nevertheless,…

Robotics · Computer Science 2024-02-23 Zhiying Song , Tenghui Xie , Hailiang Zhang , Jiaxin Liu , Fuxi Wen , Jun Li

A generalization of the ABC model, a one-dimensional model of a driven system of three particle species with local dynamics, is introduced, in which the model evolves under either (i) density-conserving or (ii) nonconserving dynamics. For…

Statistical Mechanics · Physics 2015-05-19 A. Lederhendler , D. Mukamel

In the development of new cancer treatment, an essential step is to determine the maximum tolerated dose (MTD) via phase I clinical trials. Generally speaking, phase I trial designs can be classified as either model-based or algorithm-based…

Applications · Statistics 2022-03-02 Huaqing Jin , Wenbin Du , Guosheng Yin

We consider modeling for strong-strong beam-beam interactions beyond preceding linearized/perturbative methods such as soft gaussian approximation or FMM (HFMM) etc. In our approach discrete coherent modes, discovered before, and possible…

Accelerator Physics · Physics 2007-05-23 Antonina N. Fedorova , Michael G. Zeitlin

Contact dynamics (CD) is a powerful method to solve the dynamics of large systems of colliding rigid bodies. CD can be computationally more efficient than classical penalty-based discrete element methods (DEM) for simulating contact between…

Classical Physics · Physics 2018-05-22 Tyler Olsen , Ken Kamrin

Control techniques like MPC can realize contact-rich manipulation which exploits dynamic information, maintaining friction limits and safety constraints. However, contact geometry and dynamics are required to be known. This information is…

Robotics · Computer Science 2023-10-10 Kevin Haninger , Kangwagye Samuel , Filippo Rozzi , Sehoon Oh , Loris Roveda

Performing exact posterior inference in complex generative models is often difficult or impossible due to an expensive to evaluate or intractable likelihood function. Approximate Bayesian computation (ABC) is an inference framework that…

Machine Learning · Statistics 2016-02-16 Jovana Mitrovic , Dino Sejdinovic , Yee Whye Teh

Approximate Bayesian Computation (ABC) enables statistical inference in simulator-based models whose likelihoods are difficult to calculate but easy to simulate from. ABC constructs a kernel-type approximation to the posterior distribution…

Methodology · Statistics 2022-12-02 Yuexi Wang , Tetsuya Kaji , Veronika Ročková

Complicated generative models often result in a situation where computing the likelihood of observed data is intractable, while simulating from the conditional density given a parameter value is relatively easy. Approximate Bayesian…

Machine Learning · Statistics 2015-12-29 Mijung Park , Wittawat Jitkrittum , Dino Sejdinovic

Accurately handling contact with friction remains a core bottleneck for Material Point Method (MPM), from reliable contact point detection to enforcing frictional contact laws (non-penetration, Coulomb friction, and maximum dissipation…

Robotics · Computer Science 2026-02-03 Etienne Ménager , Justin Carpentier

A common problem in natural sciences is the comparison of competing models in the light of observed data. Bayesian model comparison provides a statistically sound framework for this comparison based on the evidence each model provides for…

Machine Learning · Statistics 2022-03-23 Jan Boelts

The conventional no-slip boundary condition leads to a non-integrable stress singularity at a moving contact line. This makes numerical simulations challenging, especially when capillary effects are essential for the dynamics of the flow.…

Fluid Dynamics · Physics 2017-09-18 Hanna Holmgren , Gunilla Kreiss

Motivated by real-world applications of unmanned aerial vehicles, this paper introduces a decentralized control mechanism to guide steering control of autonomous agents maneuvering in the vicinity of multiple moving entities (e.g. other…

Systems and Control · Electrical Eng. & Systems 2021-04-28 Kevin S. Galloway , Biswadip Dey

The original formulation of BEAMS - Bayesian Estimation Applied to Multiple Species - showed how to use a dataset contaminated by points of multiple underlying types to perform unbiased parameter estimation. An example is cosmological…

Instrumentation and Methods for Astrophysics · Physics 2016-03-02 James Newling , Bruce. A. Bassett , Renée Hlozek , Martin Kunz , Mathew Smith , Melvin Varughese
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