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This study presents a scalable data-driven algorithm designed to efficiently address the challenging problem of reachability analysis. Analysis of cyber-physical systems (CPS) relies typically on parametric physical models of dynamical…

Robotics · Computer Science 2025-05-22 Navid Hashemi , Lars Lindemann , Jyotirmoy Deshmukh

We present an imaging modality that enables detection of magnetic moments and their resulting stray magnetic fields. We use wide-field magnetic imaging that employs a diamond-based magnetometer and has combined magneto-optic detection (e.g.…

The influence of a magnetic field on the broadening of spectral lines and transition arrays in complex spectra is investigated. The anomalous absorption or emission Zeeman pattern is a superposition of many profiles with different relative…

Atomic Physics · Physics 2019-04-30 Jean-Christophe Pain , Franck Gilleron

Magnetic fields have important or dominant effects in many areas of astrophysics, but have been very difficult to quantify. Spectropolarimetry from Ground State Alignment (GSA) has been suggested as a direct tracer of magnetic field in…

Astrophysics of Galaxies · Physics 2019-03-28 Huirong Yan , Cecile Gry , Francois Boulanger , Francesco Leone

Phylogenetic analysis of DNA or other data commonly gives rise to a collection or sample of inferred evolutionary trees. Principal Components Analysis (PCA) cannot be applied directly to collections of trees since the space of evolutionary…

Statistics Theory · Mathematics 2012-02-24 Tom M. W. Nye

Principal Component Analysis (PCA) is one of the most important methods to handle high dimensional data. However, most of the studies on PCA aim to minimize the loss after projection, which usually measures the Euclidean distance, though in…

Machine Learning · Computer Science 2019-03-19 Kai Liu , Qiuwei Li , Hua Wang , Gongguo Tang

Principal Component Analysis (PCA) is one of the most commonly used statistical methods for data exploration, and for dimensionality reduction wherein the first few principal components account for an appreciable proportion of the…

Methodology · Statistics 2024-01-11 Caren Marzban , Ulvi Yurtsever , Michael Richman

In the last decade we have seen an enormous increase in the size and quality of spectroscopic galaxy surveys, both at low and high redshift. New statistical techniques to analyse large portions of galaxy spectra are now finding favour over…

We extend the principal component analysis (PCA) to second-order stationary vector time series in the sense that we seek for a contemporaneous linear transformation for a $p$-variate time series such that the transformed series is segmented…

Methodology · Statistics 2018-12-21 Jinyuan Chang , Bin Guo , Qiwei Yao

The growing sample of magnetic stars shows a remarkable diversity in the properties of their magnetic fields. The overall goal of current studies is to understand the origin, evolution, and structure of stellar magnetic fields in stars of…

Solar and Stellar Astrophysics · Physics 2019-10-16 Swetlana Hubrig , Markus Schöller

Cryo-electron microscopy nowadays often requires the analysis of hundreds of thousands of 2D images as large as a few hundred pixels in each direction. Here we introduce an algorithm that efficiently and accurately performs principal…

Computer Vision and Pattern Recognition · Computer Science 2015-12-16 Zhizhen Zhao , Yoel Shkolnisky , Amit Singer

The data were obtained using two spectropolarimeters - Narval at the Bernard Lyot Telescope, Pic du Midi, France, and ESPaDOnS at CFHT, Hawaii. Thirty-eight circularly-polarized spectra have been collected in the period June 2010 - January…

Solar and Stellar Astrophysics · Physics 2015-06-12 S. Tsvetkova , P. Petit , M. Auriere , R. Konstantinova-Antova , G. A. Wade , C. Charbonnel , T. Decressin , R. Bogdanovski

We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the…

Instrumentation and Methods for Astrophysics · Physics 2015-06-16 R. Casini , A. Asensio Ramos , B. W. Lites , A. Lopez Ariste

Recent observations have shown that protoplanetary disks around young stars can embed a wide variety of features. Raw disk images produced by high-contrast imaging instruments are corrupted by slowly varying residual stellar light in the…

Instrumentation and Methods for Astrophysics · Physics 2023-07-18 S. Juillard , V. Christiaens , O. Absil

We present a comprehensive investigation of the magnetic cycle of the young, active solar analogue $\iota$ Horologii ($\iota$ Hor) based on intensive spectropolarimetric monitoring using HARPSpol. Over a nearly three-year campaign, the…

Semantic segmentation of functional magnetic resonance imaging (fMRI) makes great sense for pathology diagnosis and decision system of medical robots. The multi-channel fMRI provides more information of the pathological features. But the…

Computer Vision and Pattern Recognition · Computer Science 2017-07-12 Lei Tai , Haoyang Ye , Qiong Ye , Ming Liu

In this paper, we introduce new algorithms for Principal Component Analysis (PCA) with outliers. Utilizing techniques from computational geometry, specifically higher-degree Voronoi diagrams, we navigate to the optimal subspace for PCA even…

Machine Learning · Computer Science 2025-10-07 Sajjad Hashemian , Mohammad Saeed Arvenaghi , Ebrahim Ardeshir-Larijani

Asteroseismology has revealed small core-to-surface rotation contrasts in stars in the whole HR diagram. This is the signature of strong transport of angular momentum (AM) in stellar interiors. One of the plausible candidates to efficiently…

Solar and Stellar Astrophysics · Physics 2022-05-24 Hachem Dhouib , Stéphane Mathis , Lisa Bugnet , Timothy Van Reeth , Conny Aerts

The next generation of weak lensing surveys will trace the evolution of matter perturbations and gravitational potentials from the matter dominated epoch until today. Along with constraining the dynamics of dark energy, they will probe the…

Cosmology and Nongalactic Astrophysics · Physics 2012-02-14 Alireza Hojjati , Gong-Bo Zhao , Levon Pogosian , Alessandra Silvestri , Robert Crittenden , Kazuya Koyama

In this work, we develop a novel principal component analysis (PCA) for semimartingales by introducing a suitable spectral analysis for the quadratic variation operator. Motivated by high-dimensional complex systems typically found in…

Statistics Theory · Mathematics 2016-03-10 Alberto Ohashi , Alexandre B Simas