English
Related papers

Related papers: Waveform Simulation in PandaX-4T

200 papers

The PandaX project consists of a series of xenon-based experiments that are used to search for dark matter (DM) particles and to study the fundamental properties of neutrinos. The next DM experiment PandaX-4T will be using 4 ton liquid…

Instrumentation and Detectors · Physics 2020-12-15 Qibin Zheng , Yanlin Huang , Di Huang , Jianglai Liu , Xiangxiang Ren , Anqing Wang , Meng Wang , Jijun Yang , Binbin Yan , Yong Yang

We study the problem of reconstructing a signal from its projection on a subspace. The proposed signal reconstruction algorithms utilize a guiding subspace that represents desired properties of reconstructed signals. We show that optimal…

Information Theory · Computer Science 2016-06-13 Akshay Gadde , Andrew Knyazev , Dong Tian , Hassan Mansour

X-ray spectral fitting of astronomical sources requires convolving the intrinsic spectrum or model with the instrumental response. Standard forward modeling techniques have proven success in recovering the underlying physical parameters in…

Instrumentation and Methods for Astrophysics · Physics 2021-05-21 Carter Lee Rhea , Julie Hlavacek-Larrondo , Ralph Kraft , Akos Bogdan , Rudy Geelen

Four-dimensional scanning transmission electron microscopy (4D-STEM) is one of the most rapidly growing modes of electron microscopy imaging. The advent of fast pixelated cameras and the associated data infrastructure have greatly…

Applications · Statistics 2019-08-27 Xin Li , Ondrej Dyck , Stephen Jesse , Andrew R. Lupini , Sergei V. Kalinin , Mark P. Oxley

This paper studies linear reconstruction of partially observed functional data which are recorded on a discrete grid. We propose a novel estimation approach based on approximate factor models with increasing rank taking into account…

Statistics Theory · Mathematics 2024-05-22 Maximilian Ofner , Siegfried Hörmann

Dark wavefront sensing takes shape following quantum mechanics concepts in which one is able to "see" an object in one path of a two-arm interferometer using an as low as desired amount of light actually "hitting" the occulting object. A…

Diffusion model shows remarkable potential on sparse-view computed tomography (SVCT) reconstruction. However, when a network is trained on a limited sample space, its generalization capability may be constrained, which degrades performance…

Image and Video Processing · Electrical Eng. & Systems 2025-11-11 Zekun Zhou , Tan Liu , Bing Yu , Yanru Gong , Liu Shi , Qiegen Liu

Suppose we wish to recover a signal x in C^n from m intensity measurements of the form |<x,z_i>|^2, i = 1, 2,..., m; that is, from data in which phase information is missing. We prove that if the vectors z_i are sampled independently and…

Information Theory · Computer Science 2011-09-22 Emmanuel J. Candes , Thomas Strohmer , Vladislav Voroninski

One-dimensional signal decomposition is a well-established and widely used technique across various scientific fields. It serves as a highly valuable pre-processing step for data analysis. While traditional decomposition techniques often…

Machine Learning · Computer Science 2025-06-09 Samuele Salti , Andrea Pinto , Alessandro Lanza , Serena Morigi

In many applications, signals are measured according to a linear process, but the phases of these measurements are often unreliable or not available. To reconstruct the signal, one must perform a process known as phase retrieval. This paper…

Functional Analysis · Mathematics 2013-07-30 Matthew Fickus , Dustin G. Mixon , Aaron A. Nelson , Yang Wang

We consider the problem of signal reconstruction for a system under sparse signal corruption by a malicious agent. The reconstruction problem follows the standard error coding problem that has been studied extensively in the literature. We…

Optimization and Control · Mathematics 2023-04-28 Yu Zheng , Olugbenga Moses Anubi , Lalit Mestha , Hema Achanta

The characterization of a binary function by partial frequency information is considered. We show that it is possible to reconstruct binary signals from incomplete frequency measurements via the solution of a simple linear optimization…

Information Theory · Computer Science 2012-04-19 Yu Mao

Simulation results for future measurements of electromagnetic proton form factors at \PANDA (FAIR) within the PandaRoot software framework are reported. The statistical precision with which the proton form factors can be determined is…

High Energy Physics - Experiment · Physics 2016-09-30 PANDA Collaboration , B. Singh , W. Erni , B. Krusche , M. Steinacher , N. Walford , B. Liu , H. Liu , Z. Liu , X. Shen , C. Wang , J. Zhao , M. Albrecht , T. Erlen , M. Fink , F. Heinsius , T. Held , T. Holtmann , S. Jasper , I. Keshk , H. Koch , B. Kopf , M. Kuhlmann , M. Kümmel , S. Leiber , M. Mikirtychyants , P. Musiol , A. Mustafa , M. Pelizäus , J. Pychy , M. Richter , C. Schnier , T. Schröder , C. Sowa , M. Steinke , T. Triffterer , U. Wiedner , M. Ball , R. Beck , C. Hammann , B. Ketzer , M. Kube , P. Mahlberg , M. Rossbach , C. Schmidt , R. Schmitz , U. Thoma , M. Urban , D. Walther , C. Wendel , A. Wilson , A. Bianconi , M. Bragadireanu , M. Caprini , D. Pantea , B. Patel , W. Czyzycki , M. Domagala , G. Filo , J. Jaworowski , M. Krawczyk , F. Lisowski , E. Lisowski , M. Michałek , P. Poznański , J. Płażek , K. Korcyl , A. Kozela , P. Kulessa , P. Lebiedowicz , K. Pysz , W. Schäfer , A. Szczurek , T. Fiutowski , M. Idzik , B. Mindur , D. Przyborowski , K. Swientek , J. Biernat , B. Kamys , S. Kistryn , G. Korcyl , W. Krzemien , A. Magiera , P. Moskal , A. Pyszniak , Z. Rudy , P. Salabura , J. Smyrski , P. Strzempek , A. Wronska , I. Augustin , R. Böhm , I. Lehmann , D. Nicmorus Marinescu , L. Schmitt , V. Varentsov , M. Al-Turany , A. Belias , H. Deppe , R. Dzhygadlo , A. Ehret , H. Flemming , A. Gerhardt , K. Götzen , A. Gromliuk , L. Gruber , R. Karabowicz , R. Kliemt , M. Krebs , U. Kurilla , D. Lehmann , S. Löchner , J. Lühning , U. Lynen , H. Orth , M. Patsyuk , K. Peters , T. Saito , G. Schepers , C. J. Schmidt , C. Schwarz , J. Schwiening , A. Täschner , M. Traxler , C. Ugur , B. Voss , P. Wieczorek , A. Wilms , M. Zühlsdorf , V. Abazov , G. Alexeev , V. A. Arefiev , V. Astakhov , M. Yu. Barabanov , B. V. Batyunya , Y. Davydov , V. Kh. Dodokhov , A. Efremov , A. Fechtchenko , A. G. Fedunov , A. Galoyan , S. Grigoryan , E. K. Koshurnikov , Y. Yu. Lobanov , V. I. Lobanov , A. F. Makarov , L. V. Malinina , V. Malyshev , A. G. Olshevskiy , E. Perevalova , A. A. Piskun , T. Pocheptsov , G. Pontecorvo , V. Rodionov , Y. Rogov , R. Salmin , A. Samartsev , M. G. Sapozhnikov , G. Shabratova , N. B. Skachkov , A. N. Skachkova , E. A. Strokovsky , M. Suleimanov , R. Teshev , V. Tokmenin , V. Uzhinsky , A. Vodopianov , S. A. Zaporozhets , N. I. Zhuravlev , A. G. Zorin , D. Branford , D. Glazier , D. Watts , M. Böhm , A. Britting , W. Eyrich , A. Lehmann , M. Pfaffinger , F. Uhlig , S. Dobbs , K. Seth , A. Tomaradze , T. Xiao , D. Bettoni , V. Carassiti , A. Cotta Ramusino , P. Dalpiaz , A. Drago , E. Fioravanti , I. Garzia , M. Savrie , V. Akishina , I. Kisel , G. Kozlov , M. Pugach , M. Zyzak , P. Gianotti , C. Guaraldo , V. Lucherini , A. Bersani , G. Bracco , M. Macri , R. F. Parodi , K. Biguenko , K. Brinkmann , V. Di Pietro , S. Diehl , V. Dormenev , P. Drexler , M. Düren , E. Etzelmüller , M. Galuska , E. Gutz , C. Hahn , A. Hayrapetyan , M. Kesselkaul , W. Kühn , T. Kuske , J. S. Lange , Y. Liang , V. Metag , M. Nanova , S. Nazarenko , R. Novotny , T. Quagli , S. Reiter , J. Rieke , C. Rosenbaum , M. Schmidt , R. Schnell , H. Stenzel , U. Thöring , M. Ullrich , M. N. Wagner , T. Wasem , B. Wohlfahrt , H. Zaunick , D. Ireland , G. Rosner , B. Seitz , P. N. Deepak , A. Kulkarni , A. Apostolou , M. Babai , M. Kavatsyuk , P. J. Lemmens , M. Lindemulder , H. Loehner , J. Messchendorp , P. Schakel , H. Smit , M. Tiemens , J. C. van der Weele , R. Veenstra , S. Vejdani , K. Dutta , K. Kalita , A. Kumar , A. Roy , H. Sohlbach , M. Bai , L. Bianchi , M. Büscher , L. Cao , A. Cebulla , R. Dosdall , A. Gillitzer , F. Goldenbaum , D. Grunwald , A. Herten , Q. Hu , G. Kemmerling , H. Kleines , A. Lehrach , R. Nellen , H. Ohm , S. Orfanitski , D. Prasuhn , E. Prencipe , J. Pütz , J. Ritman , S. Schadmand , T. Sefzick , V. Serdyuk , G. Sterzenbach , T. Stockmanns , P. Wintz , P. Wüstner , H. Xu , A. Zambanini , S. Li , Z. Li , Z. Sun , H. Xu , V. Rigato , L. Isaksson , P. Achenbach , O. Corell , A. Denig , M. Distler , M. Hoek , A. Karavdina , W. Lauth , Z. Liu , H. Merkel , U. Müller , J. Pochodzalla , S. Sanchez , S. Schlimme , C. Sfienti , M. Thiel , H. Ahmadi , S. Ahmed , S. Bleser , L. Capozza , M. Cardinali , A. Dbeyssi , M. Deiseroth , F. Feldbauer , M. Fritsch , B. Fröhlich , P. Jasinski , D. Kang , D. Khaneft , R. Klasen , H. H. Leithoff , D. Lin , F. Maas , S. Maldaner , M. Marta , M. Michel , M. C. Mora Espí , C. Morales Morales , C. Motzko , F. Nerling , O. Noll , S. Pflüger , A. Pitka , D. Rodríguez Piñeiro , A. Sanchez-Lorente , M. Steinen , R. Valente , T. Weber , M. Zambrana , I. Zimmermann , A. Fedorov , M. Korjik , O. Missevitch , A. Boukharov , O. Malyshev , I. Marishev , V. Balanutsa , P. Balanutsa , V. Chernetsky , A. Demekhin , A. Dolgolenko , P. Fedorets , A. Gerasimov , V. Goryachev , V. Chandratre , V. Datar , D. Dutta , V. Jha , H. Kumawat , A. K. Mohanty , A. Parmar , B. Roy , G. Sonika , C. Fritzsch , S. Grieser , A. Hergemöller , B. Hetz , N. Hüsken , A. Khoukaz , J. P. Wessels , K. Khosonthongkee , C. Kobdaj , A. Limphirat , P. Srisawad , Y. Yan , M. Barnyakov , A. Yu. Barnyakov , K. Beloborodov , A. E. Blinov , V. E. Blinov , V. S. Bobrovnikov , S. Kononov , E. A. Kravchenko , I. A. Kuyanov , K. Martin , A. P. Onuchin , S. Serednyakov , A. Sokolov , Y. Tikhonov , E. Atomssa , R. Kunne , D. Marchand , B. Ramstein , J. van de Wiele , Y. Wang , G. Boca , S. Costanza , P. Genova , P. Montagna , A. Rotondi , V. Abramov , N. Belikov , S. Bukreeva , A. Davidenko , A. Derevschikov , Y. Goncharenko , V. Grishin , V. Kachanov , V. Kormilitsin , A. Levin , Y. Melnik , N. Minaev , V. Mochalov , D. Morozov , L. Nogach , S. Poslavskiy , A. Ryazantsev , S. Ryzhikov , P. Semenov , I. Shein , A. Uzunian , A. Vasiliev , A. Yakutin , E. Tomasi-Gustafsson , U. Roy , B. Yabsley , S. Belostotski , G. Gavrilov , A. Izotov , S. Manaenkov , O. Miklukho , D. Veretennikov , A. Zhdanov , K. Makonyi , M. Preston , P. Tegner , D. Wölbing , T. Bäck , B. Cederwall , A. K. Rai , S. Godre , D. Calvo , S. Coli , P. De Remigis , A. Filippi , G. Giraudo , S. Lusso , G. Mazza , M. Mignone , A. Rivetti , R. Wheadon , F. Balestra , F. Iazzi , R. Introzzi , A. Lavagno , J. Olave , A. Amoroso , M. P. Bussa , L. Busso , F. De Mori , M. Destefanis , L. Fava , L. Ferrero , M. Greco , J. Hu , L. Lavezzi , M. Maggiora , G. Maniscalco , S. Marcello , S. Sosio , S. Spataro , R. Birsa , F. Bradamante , A. Bressan , A. Martin , H. Calen , W. Ikegami Andersson , T. Johansson , A. Kupsc , P. Marciniewski , M. Papenbrock , J. Pettersson , K. Schönning , M. Wolke , B. Galnander , J. Diaz , V. Pothodi Chackara , A. Chlopik , G. Kesik , D. Melnychuk , B. Slowinski , A. Trzcinski , M. Wojciechowski , S. Wronka , B. Zwieglinski , P. Bühler , J. Marton , D. Steinschaden , K. Suzuki , E. Widmann , J. Zmeskal

Realistic simulation is key to enabling safe and scalable development of % self-driving vehicles. A core component is simulating the sensors so that the entire autonomy system can be tested in simulation. Sensor simulation involves modeling…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Jingkang Wang , Sivabalan Manivasagam , Yun Chen , Ze Yang , Ioan Andrei Bârsan , Anqi Joyce Yang , Wei-Chiu Ma , Raquel Urtasun

We propose SatelliteFormula, a novel symbolic regression framework that derives physically interpretable expressions directly from multi-spectral remote sensing imagery. Unlike traditional empirical indices or black-box learning models,…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Zhenyu Yu , Mohd. Yamani Idna Idris , Pei Wang , Yuelong Xia , Fei Ma , Rizwan Qureshi

Computing accurate estimates of the Fourier transform of analog signals from discrete data points is important in many fields of science and engineering. The conventional approach of performing the discrete Fourier transform of the data…

Machine Learning · Statistics 2017-12-08 Luca Ambrogioni , Eric Maris

Optical aberrations prevent telescopes from reaching their theoretical diffraction limit. Once estimated, these aberrations can be compensated for using deformable mirrors in a closed loop. Focal plane wavefront sensing enables the…

Recently it has been shown that the intensity time-bandwidth product of optical signals can be engineered to match that of the data acquisition instrument. In particular, it is possible to slow down an ultrafast signal, resulting in…

Optics · Physics 2015-06-22 Jacky Chan , Ata Mahjoubfar , Mohammad H. Asghari , Bahram Jalali

The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform. Mathematically, it is obtained by correlating the waveform with its…

Signal Processing · Electrical Eng. & Systems 2024-06-11 Samuel Pinilla , Kumar Vijay Mishra , Brian M. Sadler , Henry Arguello

Wavefront sensing is a set of techniques providing efficient means to ascertain the shape of an optical wavefront or its deviation from an ideal reference. Due to its wide dynamical range and high optical efficiency, the Shack-Hartmann is…

Quantum Physics · Physics 2014-02-14 B. Stoklasa , L. Motka , J. Rehacek , Z. Hradil , L. L. Sanchez-Soto