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We discuss the track-based alignment for the Inner Detector of the ATLAS experiment. After describing the main alignment method based on the minimization of hit residuals, we focus on alignment methods using information from the…

High Energy Physics - Experiment · Physics 2019-08-13 Jochen Schieck

We present a new particle tracking software algorithm designed to accurately track the motion of low-contrast particles against a background with large variations in light levels. The method is based on a polynomial fit of the intensity…

Soft Condensed Matter · Physics 2009-11-13 Salman S. Rogers , Thomas A. Waigh , Xiubo Zhao , Jian R. Lu

Transit spectroscopy of habitable planets orbiting late-type stars requires high relative spectro-photometric accuracy between wavelengths during transit/eclipse observation. The spectro-photometric signal is not affected only by image…

Earth and Planetary Astrophysics · Physics 2018-12-05 Shohei Goda , Taro Matsuo

Reconstructing the trajectories of charged particles from the collection of hits they leave in the detectors of collider experiments like those at the Large Hadron Collider (LHC) is a challenging combinatorics problem and computationally…

High Energy Physics - Experiment · Physics 2024-03-15 Philippa Duckett , Gabriel Facini , Marcin Jastrzebski , Sarah Malik , Sebastien Rettie , Tim Scanlon

Reconstruction of displaced vertices is a cornerstone of both precision flavour physics and searches for long-lived particles (LLPs) at colliders. While existing vertexing algorithms are highly optimised for primary and short-lived…

High Energy Physics - Phenomenology · Physics 2025-10-02 Jonathan Kriewald

In the conventional change detection (CD) pipeline, two manually registered and labeled remote sensing datasets serve as the input of the model for training and prediction. However, in realistic scenarios, data from different periods or…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Yitao Zhao , Heng-Chao Li , Nanqing Liu , Rui Wang

Coordinate descent methods employ random partial updates of decision variables in order to solve huge-scale convex optimization problems. In this work, we introduce new adaptive rules for the random selection of their updates. By adaptive,…

Machine Learning · Computer Science 2017-03-08 Dmytro Perekrestenko , Volkan Cevher , Martin Jaggi

A procedure based on a Mixture Density Model for correcting experimental data for distortions due to finite resolution and limited detector acceptance is presented. Addressing the case that the solution is known to be non-negative, in the…

Data Analysis, Statistics and Probability · Physics 2015-03-09 Nikolai Gagunashvili

There are several studies proposing phenomenological consequences of a deformation of special and general relativity. Here, we cast novel constraints on the deformation parameter of a metric in the cotangent bundle accounting for a curved…

General Relativity and Quantum Cosmology · Physics 2020-11-18 J. J. Relancio , S. Liberati

In this paper, we aim at improving the tracking of road users in urban scenes. We present a constraint programming (CP) approach for the data association phase found in the tracking-by-detection paradigm of the multiple object tracking…

Computer Vision and Pattern Recognition · Computer Science 2020-03-11 Alexandre Pineault , Guillaume-Alexandre Bilodeau , Gilles Pesant

In the presence of Lorentz violation, the motion of a charged particle in a magnetic field is distorted. By measuring the eccentricities of particles' elliptical orbits and studying how those eccentricities vary with the absolute…

High Energy Physics - Phenomenology · Physics 2011-10-17 Brett Altschul

This paper provides a detailed description of a vertex fitting algorithm designed for precision measurements in low-energy particle physics experiments. An accurate reconstruction of low-momentum trajectories is facilitated by reducing the…

Instrumentation and Detectors · Physics 2024-04-30 Andrea Loreti

We analyze the coordinate descent method with a new coordinate selection strategy, called volume sampling. This strategy prescribes selecting subsets of variables of certain size proportionally to the determinants of principal submatrices…

Optimization and Control · Mathematics 2020-04-30 Anton Rodomanov , Dmitry Kropotov

Current and next-generation particle tracking detectors will incorporate precision timing capabilities with resolutions approaching tens of picoseconds. Using Technology Computer-Aided Design (TCAD) simulations of Low-Gain Avalanche Diode…

Minimizing a convex function of a measure with a sparsity-inducing penalty is a typical problem arising, e.g., in sparse spikes deconvolution or two-layer neural networks training. We show that this problem can be solved by discretizing the…

Optimization and Control · Mathematics 2020-11-04 Lenaic Chizat

Recent studies of optimization methods and GNC of spacecraft near small bodies focusing on descent, landing, rendezvous, etc., with key safety constraints such as line-of-sight conic zones and soft landings have shown promising results;…

Optimization and Control · Mathematics 2020-05-22 Steven van Leeuwen

Tracking by Deblatting stands for solving an inverse problem of deblurring and image matting for tracking motion-blurred objects. We propose non-causal Tracking by Deblatting which estimates continuous, complete and accurate object…

Computer Vision and Pattern Recognition · Computer Science 2019-11-27 Denys Rozumnyi , Jan Kotera , Filip Šroubek , Jiří Matas

We present a new particle tracking algorithm to accurately resolve large deformation and rotational motion fields, which takes advantage of both local and global particle tracking algorithms. We call this method the ScalE and Rotation…

Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to all previous work we wish to achieve this using from low-level, spatio-temporally local motion features used in commercial…

Computer Vision and Pattern Recognition · Computer Science 2015-04-22 Ognjen Arandjelovic , Duc-Son Pham , Svetha Venkatesh

Achieving high-performance in multi-object tracking algorithms heavily relies on modeling spatio-temporal relationships during the data association stage. Mainstream approaches encompass rule-based and deep learning-based methods for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-18 Zhonglin Liu , Shujie Chen , Jianfeng Dong , Xun Wang , Di Zhou