281 research outputs found

    Survey Propagation as local equilibrium equations

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    It has been shown experimentally that a decimation algorithm based on Survey Propagation (SP) equations allows to solve efficiently some combinatorial problems over random graphs. We show that these equations can be derived as sum-product equations for the computation of marginals in an extended space where the variables are allowed to take an additional value -- * -- when they are not forced by the combinatorial constraints. An appropriate ``local equilibrium condition'' cost/energy function is introduced and its entropy is shown to coincide with the expected logarithm of the number of clusters of solutions as computed by SP. These results may help to clarify the geometrical notion of clusters assumed by SP for the random K-SAT or random graph coloring (where it is conjectured to be exact) and helps to explain which kind of clustering operation or approximation is enforced in general/small sized models in which it is known to be inexact.Comment: 13 pages, 3 figure

    Virgo Detector Characterization and Data Quality: results from the O3 run

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    The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave (GW) signals in the past few years, alongside the two Advanced LIGO instruments. First during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817), and then during the full Observation Run 3 (O3): an 11-months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient GW sources maintained by LIGO, Virgo and now KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise sources. These activities, collectively named {\em detector characterization and data quality} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end hardware to the final analyses. They are described in details in the following article, with a focus on the results achieved by the Virgo DetChar group during the O3 run. Concurrently, a companion article describes the tools that have been used by the Virgo DetChar group to perform this work.Comment: 57 pages, 18 figures. To be submitted to Class. and Quantum Grav. This is the "Results" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat

    Virgo Detector Characterization and Data Quality: tools

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    Detector characterization and data quality studies -- collectively referred to as {\em DetChar} activities in this article -- are paramount to the scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA global network of ground-based gravitational-wave (GW) detectors. They take place during each phase of the operation of the instruments (upgrade, tuning and optimization, data taking), are required at all steps of the dataflow (from data acquisition to the final list of GW events) and operate at various latencies (from near real-time to vet the public alerts to offline analyses). This work requires a wide set of tools which have been developed over the years to fulfill the requirements of the various DetChar studies: data access and bookkeeping; global monitoring of the instruments and of the different steps of the data processing; studies of the global properties of the noise at the detector outputs; identification and follow-up of noise peculiar features (whether they be transient or continuously present in the data); quick processing of the public alerts. The present article reviews all the tools used by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3, from April 2019 to March 2020), mainly to analyse the Virgo data acquired at EGO. Concurrently, a companion article focuses on the results achieved by the DetChar group during the O3 run using these tools.Comment: 44 pages, 16 figures. To be submitted to Class. and Quantum Grav. This is the "Tools" part of preprint arXiv:2205.01555 [gr-qc] which has been split into two companion articles: one about the tools and methods, the other about the analyses of the O3 Virgo dat

    Virgo Detector Characterization and Data Quality during the O3 run

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    The Advanced Virgo detector has contributed with its data to the rapid growth of the number of detected gravitational-wave signals in the past few years, alongside the two LIGO instruments. First, during the last month of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary mergers GW170814 and GW170817) and then during the full Observation Run 3 (O3): an 11 months data taking period, between April 2019 and March 2020, that led to the addition of about 80 events to the catalog of transient gravitational-wave sources maintained by LIGO, Virgo and KAGRA. These discoveries and the manifold exploitation of the detected waveforms require an accurate characterization of the quality of the data, such as continuous study and monitoring of the detector noise. These activities, collectively named {\em detector characterization} or {\em DetChar}, span the whole workflow of the Virgo data, from the instrument front-end to the final analysis. They are described in details in the following article, with a focus on the associated tools, the results achieved by the Virgo DetChar group during the O3 run and the main prospects for future data-taking periods with an improved detector.Comment: 86 pages, 33 figures. This paper has been divided into two articles which supercede it and have been posted to arXiv on October 2022. Please use these new preprints as references: arXiv:2210.15634 (tools and methods) and arXiv:2210.15633 (results from the O3 run

    Advanced Virgo Plus: Future Perspectives

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    While completing the commissioning phase to prepare the Virgo interferometer for the next joint Observation Run (O4), the Virgo collaboration is also finalizing the design of the next upgrades to the detector to be employed in the following Observation Run (O5). The major upgrade will concern decreasing the thermal noise limit, which will imply using very large test masses and increased laser beam size. But this will not be the only upgrade to be implemented in the break between the O4 and O5 observation runs to increase the Virgo detector strain sensitivity. The paper will cover the challenges linked to this upgrade and implications on the detector's reach and observational potential, reflecting the talk given at 12th Cosmic Ray International Seminar - CRIS 2022 held in September 2022 in Napoli

    The Advanced Virgo+ status

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    The gravitational wave detector Advanced Virgo+ is currently in the commissioning phase in view of the fourth Observing Run (O4). The major upgrades with respect to the Advanced Virgo configuration are the implementation of an additional recycling cavity, the Signal Recycling cavity (SRC), at the output of the interferometer to broaden the sensitivity band and the Frequency Dependent Squeezing (FDS) to reduce quantum noise at all frequencies. The main difference of the Advanced Virgo + detector with respect to the LIGO detectors is the presence of marginally stable recycling cavities, with respect to the stable recycling cavities present in the LIGO detectors, which increases the difficulties in controlling the interferometer in presence of defects (both thermal and cold defects). This work will focus on the interferometer commissioning, highlighting the control challenges to maintain the detector in the working point which maximizes the sensitivity and the duty cycle for scientific data taking

    Search of the early O3 LIGO data for continuous gravitational waves from the Cassiopeia A and Vela Jr. supernova remnants

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    partially_open1412sìWe present directed searches for continuous gravitational waves from the neutron stars in the Cassiopeia A (Cas A) and Vela Jr. supernova remnants. We carry out the searches in the LIGO detector data from the first six months of the third Advanced LIGO and Virgo observing run using the weave semicoherent method, which sums matched-filter detection-statistic values over many time segments spanning the observation period. No gravitational wave signal is detected in the search band of 20–976 Hz for assumed source ages greater than 300 years for Cas A and greater than 700 years for Vela Jr. Estimates from simulated continuous wave signals indicate we achieve the most sensitive results to date across the explored parameter space volume, probing to strain magnitudes as low as ∼6.3×10^−26 for Cas A and ∼5.6×10^−26 for Vela Jr. at frequencies near 166 Hz at 95% efficiency.openAbbott, R.; Abbott, T. D.; Acernese, F.; Ackley, K.; Adams, C.; Adhikari, N.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agarwal, D.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Albanesi, S.; Allocca, A.; Altin, P. A.; Amato, A.; Anand, C.; Anand, S.; Ananyeva, A.; Anderson, S. B.; Anderson, W. G.; Andrade, T.; Andres, N.; Andrić, T.; Angelova, S. V.; Ansoldi, S.; Antelis, J. M.; Antier, S.; Appert, S.; Arai, K.; Araya, M. C.; Areeda, J. S.; Arène, M.; Arnaud, N.; Aronson, S. M.; Arun, K. G.; Asali, Y.; Ashton, G.; Assiduo, M.; Aston, S. M.; Astone, P.; Aubin, F.; Austin, C.; Babak, S.; Badaracco, F.; Bader, M. K. M.; Badger, C.; Bae, S.; Baer, A. M.; Bagnasco, S.; Bai, Y.; Baird, J.; Ball, M.; Ballardin, G.; Ballmer, S. W.; Balsamo, A.; Baltus, G.; Banagiri, S.; Bankar, D.; Barayoga, J. C.; Barbieri, C.; Barish, B. C.; Barker, D.; Barneo, P.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Barton, M. A.; Bartos, I.; Bassiri, R.; Basti, A.; Bawaj, M.; Bayley, J. C.; Baylor, A. C.; Bazzan, M.; Bécsy, B.; Bedakihale, V. M.; Bejger, M.; Belahcene, I.; Benedetto, V.; Beniwal, D.; Bennett, T. F.; Bentley, J. D.; BenYaala, M.; Bergamin, F.; Berger, B. K.; Bernuzzi, S.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Beveridge, D.; Bhandare, R.; Bhardwaj, U.; Bhattacharjee, D.; Bhaumik, S.; Bilenko, I. A.; Billingsley, G.; Bini, S.; Birney, R.; Birnholtz, O.; Biscans, S.; Bischi, M.; Biscoveanu, S.; Bisht, A.; Biswas, B.; Bitossi, M.; Bizouard, M.-A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bobba, F.; Bode, N.; Boer, M.; Bogaert, G.; Boldrini, M.; Bonavena, L. D.; Bondu, F.; Bonilla, E.; Bonnand, R.; Booker, P.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, N.; Bose, S.; Bossilkov, V.; Boudart, V.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Bramley, A.; Branch, A.; Branchesi, M.; Brau, J. E.; Breschi, M.; Briant, T.; Briggs, J. H.; Brillet, A.; Brinkmann, M.; Brockill, P.; Brooks, A. F.; Brooks, J.; Brown, D. D.; Brunett, S.; Bruno, G.; Bruntz, R.; Bryant, J.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buscicchio, R.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Bustillo, J. Calderón; Callaghan, J. D.; Callister, T. A.; Calloni, E.; Cameron, J.; Camp, J. B.; Canepa, M.; Canevarolo, S.; Cannavacciuolo, M.; Cannon, K. C.; Cao, H.; Capote, E.; Carapella, G.; Carbognani, F.; Carlin, J. B.; Carney, M. F.; Carpinelli, M.; Carrillo, G.; Carullo, G.; Carver, T. L.; Diaz, J. Casanueva; Casentini, C.; Castaldi, G.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Ceasar, M.; Cella, G.; Cerdá-Durán, P.; Cesarini, E.; Chaibi, W.; Chakravarti, K.; Subrahmanya, S. Chalathadka; Champion, E.; Chan, C.-H.; Chan, C.; Chan, C. L.; Chan, K.; Chandra, K.; Chanial, P.; Chao, S.; Charlton, P.; Chase, E. A.; Chassande-Mottin, E.; Chatterjee, C.; Chatterjee, Debarati; Chatterjee, Deep; Chaturvedi, M.; Chaty, S.; Chen, H. Y.; Chen, J.; Chen, X.; Chen, Y.; Chen, Z.; Cheng, H.; Cheong, C. K.; Cheung, H. Y.; Chia, H. Y.; Chiadini, F.; Chiarini, G.; Chierici, R.; Chincarini, A.; Chiofalo, M. L.; Chiummo, A.; Cho, G.; Cho, H. S.; Choudhary, R. K.; Choudhary, S.; Christensen, N.; Chu, Q.; Chua, S.; Chung, K. W.; Ciani, G.; Ciecielag, P.; Cieślar, M.; Cifaldi, M.; Ciobanu, A. A.; Ciolfi, R.; Cipriano, F.; Cirone, A.; Clara, F.; Clark, E. N.; Clark, J. A.; Clarke, L.; Clearwater, P.; Clesse, S.; Cleva, F.; Coccia, E.; Codazzo, E.; Cohadon, P.-F.; Cohen, D. E.; Cohen, L.; Colleoni, M.; Collette, C. G.; Colombo, A.; Colpi, M.; Compton, C. M.; Constancio, M.; Conti, L.; Cooper, S. J.; Corban, P.; Corbitt, T. R.; Cordero-Carrión, I.; Corezzi, S.; Corley, K. R.; Cornish, N.; Corre, D.; Corsi, A.; Cortese, S.; Costa, C. A.; Cotesta, R.; Coughlin, M. W.; Coulon, J.-P.; Countryman, S. T.; Cousins, B.; Couvares, P.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Creighton, J. D. E.; Creighton, T. D.; Criswell, A. W.; Croquette, M.; Crowder, S. G.; Cudell, J. R.; Cullen, T. J.; Cumming, A.; Cummings, R.; Cunningham, L.; Cuoco, E.; Curyło, M.; Dabadie, P.; Canton, T. Dal; Dall’Osso, S.; Dálya, G.; Dana, A.; DaneshgaranBajastani, L. M.; D’Angelo, B.; Danilishin, S.; D’Antonio, S.; Danzmann, K.; Darsow-Fromm, C.; Dasgupta, A.; Datrier, L. E. H.; Datta, S.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Davis, D.; Davis, M. C.; Daw, E. J.; Dean, R.; DeBra, D.; Deenadayalan, M.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Favero, V.; De Lillo, F.; De Lillo, N.; Del Pozzo, W.; DeMarchi, L. M.; De Matteis, F.; D’Emilio, V.; Demos, N.; Dent, T.; Depasse, A.; De Pietri, R.; De Rosa, R.; De Rossi, C.; DeSalvo, R.; De Simone, R.; Dhurandhar, S.; Díaz, M. C.; Diaz-Ortiz, M.; Didio, N. A.; Dietrich, T.; Di Fiore, L.; Di Fronzo, C.; Di Giorgio, C.; Di Giovanni, F.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Ding, B.; Di Pace, S.; Di Palma, I.; Di Renzo, F.; Divakarla, A. K.; Dmitriev, A.; Doctor, Z.; D’Onofrio, L.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorrington, I.; Drago, M.; Driggers, J. C.; Drori, Y.; Ducoin, J.-G.; Dupej, P.; Durante, O.; D’Urso, D.; Duverne, P.-A.; Dwyer, S. E.; Eassa, C.; Easter, P. J.; Ebersold, M.; Eckhardt, T.; Eddolls, G.; Edelman, B.; Edo, T. B.; Edy, O.; Effler, A.; Eichholz, J.; Eikenberry, S. S.; Eisenmann, M.; Eisenstein, R. A.; Ejlli, A.; Engelby, E.; Errico, L.; Essick, R. C.; Estellés, H.; Estevez, D.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Ewing, B. E.; Fafone, V.; Fair, H.; Fairhurst, S.; Farah, A. M.; Farinon, S.; Farr, B.; Farr, W. M.; Farrow, N. W.; Fauchon-Jones, E. J.; Favaro, G.; Favata, M.; Fays, M.; Fazio, M.; Feicht, J.; Fejer, M. M.; Fenyvesi, E.; Ferguson, D. L.; Fernandez-Galiana, A.; Ferrante, I.; Ferreira, T. A.; Fidecaro, F.; Figura, P.; Fiori, I.; Fishbach, M.; Fisher, R. P.; Fittipaldi, R.; Fiumara, V.; Flaminio, R.; Floden, E.; Fong, H.; Font, J. A.; Fornal, B.; Forsyth, P. W. F.; Franke, A.; Frasca, S.; Frasconi, F.; Frederick, C.; Freed, J. P.; Frei, Z.; Freise, A.; Frey, R.; Fritschel, P.; Frolov, V. V.; Fronzé, G. G.; Fulda, P.; Fyffe, M.; Gabbard, H. A.; Gadre, B. U.; Gair, J. R.; Gais, J.; Galaudage, S.; Gamba, R.; Ganapathy, D.; Ganguly, A.; Gaonkar, S. G.; Garaventa, B.; García-Núñez, C.; García-Quirós, C.; Garufi, F.; Gateley, B.; Gaudio, S.; Gayathri, V.; Gemme, G.; Gennai, A.; George, J.; Gerberding, O.; Gergely, L.; Gewecke, P.; Ghonge, S.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, Shaon; Ghosh, Shrobana; Giacomazzo, B.; Giacoppo, L.; Giaime, J. A.; Giardina, K. D.; Gibson, D. R.; Gier, C.; Giesler, M.; Giri, P.; Gissi, F.; Glanzer, J.; Gleckl, A. E.; Godwin, P.; Goetz, E.; Goetz, R.; Gohlke, N.; Goncharov, B.; González, G.; Gopakumar, A.; Gosselin, M.; Gouaty, R.; Gould, D. W.; Grace, B.; Grado, A.; Granata, M.; Granata, V.; Grant, A.; Gras, S.; Grassia, P.; Gray, C.; Gray, R.; Greco, G.; Green, A. C.; Green, R.; Gretarsson, A. M.; Gretarsson, E. M.; Griffith, D.; Griffiths, W.; Griggs, H. L.; Grignani, G.; Grimaldi, A.; Grimm, S. J.; Grote, H.; Grunewald, S.; Gruning, P.; Guerra, D.; Guidi, Gianluca; Guimaraes, A. R.; Guixé, G.; Gulati, H. K.; Guo, H.-K.; Guo, Y.; Gupta, Anchal; Gupta, Anuradha; Gupta, P.; Gustafson, E. K.; Gustafson, R.; Guzman, F.; Haegel, L.; Halim, O.; Hall, E. D.; Hamilton, E. Z.; Hammond, G.; Haney, M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hannuksela, O.; Hansen, H.; Hansen, T. J.; Hanson, J.; Harder, T.; Hardwick, T.; Haris, K.; Harms, J.; Harry, G. M.; Harry, I. W.; Hartwig, D.; Haskell, B.; Hasskew, R. K.; Haster, C.-J.; Haughian, K.; Hayes, F. J.; Healy, J.; Heidmann, A.; Heidt, A.; Heintze, M. C.; Heinze, J.; Heinzel, J.; Heitmann, H.; Hellman, F.; Hello, P.; Helmling-Cornell, A. F.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennes, E.; Hennig, J.; Hennig, M. H.; Hernandez, A. G.; Vivanco, F. Hernandez; Heurs, M.; Hild, S.; Hill, P.; Hines, A. S.; Hochheim, S.; Hofman, D.; Hohmann, J. N.; Holcomb, D. G.; Holland, N. A.; Hollows, I. J.; Holmes, Z. J.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Hourihane, S.; Howell, E. J.; Hoy, C. G.; Hoyland, D.; Hreibi, A.; Hsu, Y.; Huang, Y.; Hübner, M. T.; Huddart, A. D.; Hughey, B.; Hui, V.; Husa, S.; Huttner, S. H.; Huxford, R.; Huynh-Dinh, T.; Idzkowski, B.; Iess, A.; Ingram, C.; Isi, M.; Isleif, K.; Iyer, B. R.; JaberianHamedan, V.; Jacqmin, T.; Jadhav, S. J.; Jadhav, S. P.; James, A. L.; Jan, A. Z.; Jani, K.; Janquart, J.; Janssens, K.; Janthalur, N. N.; Jaranowski, P.; Jariwala, D.; Jaume, R.; Jenkins, A. C.; Jenner, K.; Jeunon, M.; Jia, W.; Johns, G. R.; Jones, A. W.; Jones, D. I.; Jones, J. D.; Jones, P.; Jones, R.; Jonker, R. J. G.; Ju, L.; Junker, J.; Juste, V.; Kalaghatgi, C. V.; Kalogera, V.; Kamai, B.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kao, Y.; Kapadia, S. J.; Kapasi, D. P.; Karat, S.; Karathanasis, C.; Karki, S.; Kashyap, R.; Kasprzack, M.; Kastaun, W.; Katsanevas, S.; Katsavounidis, E.; Katzman, W.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Keitel, D.; Key, J. S.; Khadka, S.; Khalili, F. Y.; Khan, S.; Khazanov, E. A.; Khetan, N.; Khursheed, M.; Kijbunchoo, N.; Kim, C.; Kim, J. C.; Kim, K.; Kim, W. S.; Kim, Y.-M.; Kimball, C.; Kinley-Hanlon, M.; Kirchhoff, R.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Knee, A. M.; Knowles, T. D.; Knyazev, E.; Koch, P.; Koekoek, G.; Koley, S.; Kolitsidou, P.; Kolstein, M.; Komori, K.; Kondrashov, V.; Kontos, A.; Koper, N.; Korobko, M.; Kovalam, M.; Kozak, D. B.; Kringel, V.; Krishnendu, N. V.; Królak, A.; Kuehn, G.; Kuei, F.; Kuijer, P.; Kumar, A.; Kumar, P.; Kumar, Rahul; Kumar, Rakesh; Kuns, K.; Kuwahara, S.; Lagabbe, P.; Laghi, D.; Lalande, E.; Lam, T. L.; Lamberts, A.; Landry, M.; Lane, B. B.; Lang, R. N.; Lange, J.; Lantz, B.; La Rosa, I.; Lartaux-Vollard, A.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lecoeuche, Y. K.; Lee, H. M.; Lee, H. W.; Lee, J.; Lee, K.; Lehmann, J.; Lemaître, A.; Leroy, N.; Letendre, N.; Levesque, C.; Levin, Y.; Leviton, J. N.; Leyde, K.; Li, A. K. Y.; Li, B.; Li, J.; Li, T. G. F.; Li, X.; Linde, F.; Linker, S. D.; Linley, J. N.; Littenberg, T. B.; Liu, J.; Liu, K.; Liu, X.; Llamas, F.; Llorens-Monteagudo, M.; Lo, R. K. L.; Lockwood, A.; London, L. T.; Longo, A.; Lopez, D.; Portilla, M. Lopez; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lott, T. P.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lucaccioni, J. F.; Lück, H.; Lumaca, D.; Lundgren, A. P.; Lynam, J. E.; Macas, R.; MacInnis, M.; Macleod, D. M.; MacMillan, I. A. O.; Macquet, A.; Hernandez, I. Magaña; Magazzù, C.; Magee, R. M.; Maggiore, R.; Magnozzi, M.; Mahesh, S.; Majorana, E.; Makarem, C.; Maksimovic, I.; Maliakal, S.; Malik, A.; Man, N.; Mandic, V.; Mangano, V.; Mango, J. L.; Mansell, G. L.; Manske, M.; Mantovani, M.; Mapelli, M.; Marchesoni, F.; Marion, F.; Mark, Z.; Márka, S.; Márka, Z.; Markakis, C.; Markosyan, A. S.; Markowitz, A.; Maros, E.; Marquina, A.; Marsat, S.; Martelli, F.; Martin, I. W.; Martin, R. M.; Martinez, M.; Martinez, V. A.; Martinez, V.; Martinovic, K.; Martynov, D. V.; Marx, E. J.; Masalehdan, H.; Mason, K.; Massera, E.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matas, A.; Mateu-Lucena, M.; Matichard, F.; Matiushechkina, M.; Mavalvala, N.; McCann, J. J.; McCarthy, R.; McClelland, D. E.; McClincy, P. K.; McCormick, S.; McCuller, L.; McGhee, G. I.; McGuire, S. C.; McIsaac, C.; McIver, J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Mehmet, M.; Mehta, A. K.; Meijer, Q.; Melatos, A.; Melchor, D. A.; Mendell, G.; Menendez-Vazquez, A.; Menoni, C. S.; Mercer, R. A.; Mereni, L.; Merfeld, K.; Merilh, E. L.; Merritt, J. D.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Meylahn, F.; Mhaske, A.; Miani, A.; Miao, H.; Michaloliakos, I.; Michel, C.; Middleton, H.; Milano, L.; Miller, A.; Miller, A. L.; Miller, B.; Millhouse, M.; Mills, J. C.; Milotti, E.; Minazzoli, O.; Minenkov, Y.; Mir, Ll. M.; Miravet-Tenés, M.; Mishra, C.; Mishra, T.; Mistry, T.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Mo, Geoffrey; Moguel, E.; Mogushi, K.; Mohapatra, S. R. P.; Mohite, S. R.; Molina, I.; Molina-Ruiz, M.; Mondin, M.; Montani, M.; Moore, C. J.; Moraru, D.; Morawski, F.; More, A.; Moreno, C.; Moreno, G.; Morisaki, S.; Mours, B.; Mow-Lowry, C. M.; Mozzon, S.; Muciaccia, F.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, Soma; Mukherjee, Subroto; Mukherjee, Suvodip; Mukund, N.; Mullavey, A.; Munch, J.; Muñiz, E. A.; Murray, P. G.; Musenich, R.; Muusse, S.; Nadji, S. L.; Nagar, A.; Napolano, V.; Nardecchia, I.; 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    Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data

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    All-sky search for long-duration gravitational-wave bursts in the third Advanced LIGO and Advanced Virgo run

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    After the detection of gravitational waves from compact binary coalescences, the search for transient gravitational-wave signals with less well-defined waveforms for which matched filtering is not well suited is one of the frontiers for gravitational-wave astronomy. Broadly classified into “short” ≲1  s and “long” ≳1  s duration signals, these signals are expected from a variety of astrophysical processes, including non-axisymmetric deformations in magnetars or eccentric binary black hole coalescences. In this work, we present a search for long-duration gravitational-wave transients from Advanced LIGO and Advanced Virgo’s third observing run from April 2019 to March 2020. For this search, we use minimal assumptions for the sky location, event time, waveform morphology, and duration of the source. The search covers the range of 2–500 s in duration and a frequency band of 24–2048 Hz. We find no significant triggers within this parameter space; we report sensitivity limits on the signal strength of gravitational waves characterized by the root-sum-square amplitude hrss as a function of waveform morphology. These hrss limits improve upon the results from the second observing run by an average factor of 1.8

    Search for continuous gravitational wave emission from the Milky Way center in O3 LIGO--Virgo data

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    We present a directed search for continuous gravitational wave (CW) signals emitted by spinning neutron stars located in the inner parsecs of the Galactic Center (GC). Compelling evidence for the presence of a numerous population of neutron stars has been reported in the literature, turning this region into a very interesting place to look for CWs. In this search, data from the full O3 LIGO--Virgo run in the detector frequency band [10,2000] Hz[10,2000]\rm~Hz have been used. No significant detection was found and 95%\% confidence level upper limits on the signal strain amplitude were computed, over the full search band, with the deepest limit of about 7.6×10267.6\times 10^{-26} at 142 Hz\simeq 142\rm~Hz. These results are significantly more constraining than those reported in previous searches. We use these limits to put constraints on the fiducial neutron star ellipticity and r-mode amplitude. These limits can be also translated into constraints in the black hole mass -- boson mass plane for a hypothetical population of boson clouds around spinning black holes located in the GC.Comment: 25 pages, 5 figure
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