检索结果-内蒙古大学图书馆

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

Physical Review D 2021年第12期104卷 122004-122004页

作者： R. Abbott T. D. Abbott F. Acernese K. Ackley C. Adams N. Adhikari R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu S. Albanesi A. Allocca P. A. Altin A. Amato C. Anand S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando T. Andrade N. Andres T. Andrić S. V. Angelova S. Ansoldi J. M. Antelis S. Antier S. Appert Koji Arai Koya Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud S. M. Aronson K. G. Arun H. Asada Y. Asali G. Ashton Y. Aso M. Assiduo S. M. Aston P. Astone F. Aubin C. Austin S. Babak F. Badaracco M. K. M. Bader C. Badger S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer A. Balsamo G. Baltus S. Banagiri D. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi C. P. L. Berry D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge R. Bhandare U. Bhardwaj D. Bhattacharjee S. Bhaumik I. A. Bilenko G. Billingsley S. Bini R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini L. D. Bonavena F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic C. Buy R. L. Byer L. Cadonati G. Cagnoli C. Cahillane J. Calderón Bustillo J. D. Callagh LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy OzGrav School of Physics and Astronomy Monash University Clayton 3800 Victoria Australia LIGO Livingston Observatory Livingston Louisiana 70754 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan INFN Sezione di Torino I-10125 Torino Italy Università di Napoli “Federico II ” Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy Université de Lyon Université Claude Bernard Lyon 1 CNRS Institut Lumière Matière F-69622 Villeurbanne Franc

This paper presents the results of a search for generic short-duration gravitational-wave transients in data from the third observing run of Advanced LIGO and Advanced Virgo. Transients with durations of milliseconds to a few seconds in the 24–4096 Hz frequency band are targeted by the search, with no assumptions made regarding the incoming signal direction, polarization, or morphology. Gravitational waves from compact binary coalescences that have been identified by other targeted analyses are detected, but no statistically significant evidence for other gravitational wave bursts is found. Sensitivities to a variety of signals are presented. These include updated upper limits on the source rate density as a function of the characteristic frequency of the signal, which are roughly an order of magnitude better than previous upper limits. This search is sensitive to sources radiating as little as ∼10−10 M⊙c2 in gravitational waves at ∼70 Hz from a distance of 10 kpc, with 50% detection efficiency at a false alarm rate of one per century. The sensitivity of this search to two plausible astrophysical sources is estimated: neutron star f modes, which may be excited by pulsar glitches, as well as selected core-collapse supernova models.

关键词： Gravitational wave sources Gravitational waves

来源：评论

学校读者我要写书评

暂无评论

All-sky search for continuous gravitational waves from isolated neutron stars in the early O3 LIGO data

引用

Physical Review D 2021年第8期104卷 082004-082004页

作者： R. Abbott T. D. Abbott S. Abraham F. Acernese K. Ackley A. Adams C. Adams R. X. Adhikari V. B. Adya C. Affeldt D. Agarwal M. Agathos K. Agatsuma N. Aggarwal O. D. Aguiar L. Aiello A. Ain P. Ajith T. Akutsu K. M. Aleman G. Allen A. Allocca P. A. Altin A. Amato S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Ando S. V. Angelova S. Ansoldi J. M. Antelis S. Antier S. Appert Koya Arai Koji Arai Y. Arai S. Araki A. Araya M. C. Araya J. S. Areeda M. Arène N. Aritomi N. Arnaud S. M. Aronson H. Asada Y. Asali G. Ashton Y. Aso S. M. Aston P. Astone F. Aubin P. Aufmuth K. AultONeal C. Austin S. Babak F. Badaracco M. K. M. Bader S. Bae Y. Bae A. M. Baer S. Bagnasco Y. Bai L. Baiotti J. Baird R. Bajpai M. Ball G. Ballardin S. W. Ballmer M. Bals A. Balsamo G. Baltus S. Banagiri D. Bankar R. S. Bankar J. C. Barayoga C. Barbieri B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta J. Bartlett M. A. Barton I. Bartos R. Bassiri A. Basti M. Bawaj J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale M. Bejger I. Belahcene V. Benedetto D. Beniwal M. G. Benjamin T. F. Bennett J. D. Bentley M. BenYaala F. Bergamin B. K. Berger S. Bernuzzi D. Bersanetti A. Bertolini J. Betzwieser R. Bhandare A. V. Bhandari D. Bhattacharjee S. Bhaumik J. Bidler I. A. Bilenko G. Billingsley R. Birney O. Birnholtz S. Biscans M. Bischi S. Biscoveanu A. Bisht B. Biswas M. Bitossi M.-A. Bizouard J. K. Blackburn J. Blackman C. D. Blair D. G. Blair R. M. Blair F. Bobba N. Bode M. Boer G. Bogaert M. Boldrini F. Bondu E. Bonilla R. Bonnand P. Booker B. A. Boom R. Bork V. Boschi N. Bose S. Bose V. Bossilkov V. Boudart Y. Bouffanais A. Bozzi C. Bradaschia P. R. Brady A. Bramley A. Branch M. Branchesi J. E. Brau M. Breschi T. Briant J. H. Briggs A. Brillet M. Brinkmann P. Brockill A. F. Brooks J. Brooks D. D. Brown S. Brunett G. Bruno R. Bruntz J. Bryant A. Buikema T. Bulik H. J. Bulten A. Buonanno R. Buscicchio D. Buskulic R. L. Byer L. Cadonati M. Caesar G. Cagnoli C. Cahillane H. W. Cain, III J. Calderón Bustillo J. LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Louisiana State University Baton Rouge Louisiana 70803 USA Inter-University Centre for Astronomy and Astrophysics Pune 411007 India Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli Complesso Universitario di Monte S.Angelo I-80126 Napoli Italy OzGrav School of Physics and Astronomy Monash University Clayton 3800 Victoria Australia Christopher Newport University Newport News Virginia 23606 USA LIGO Livingston Observatory Livingston Louisiana 70754 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany University of Cambridge Cambridge CB2 1TN United Kingdom Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena D-07743 Jena Germany University of Birmingham Birmingham B15 2TT United Kingdom Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA) Northwestern University Evanston Illinois 60208 USA Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Gravity Exploration Institute Cardiff University Cardiff CF24 3AA United Kingdom Gran Sasso Science Institute (GSSI) I-67100 L’Aquila Italy INFN Laboratori Nazionali del Gran Sasso I-67100 Assergi Italy INFN Sezione di Pisa I-56127 Pisa Italy Università di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan California State University Fullerton Fullerton California 92831 USA NCSA University of Illi

We report on an all-sky search for continuous gravitational waves in the frequency band 20–2000 Hz and with a frequency time derivative in the range of [−1.0,+0.1]×10−8 Hz/s. Such a signal could be produced by a nearby, spinning and slightly nonaxisymmetric isolated neutron star in our Galaxy. This search uses the LIGO data from the first six months of Advanced LIGO’s and Advanced Virgo’s third observational run, O3. No periodic gravitational wave signals are observed, and 95% confidence-level (C.L.) frequentist upper limits are placed on their strengths. The lowest upper limits on worst-case (linearly polarized) strain amplitude h0 are ∼1.7×10−25 near 200 Hz. For a circularly polarized source (most favorable orientation), the lowest upper limits are ∼6.3×10−26. These strict frequentist upper limits refer to all sky locations and the entire range of frequency derivative values. For a population-averaged ensemble of sky locations and stellar orientations, the lowest 95% C.L. upper limits on the strain amplitude are ∼1.4×10−25. These upper limits improve upon our previously published all-sky results, with the greatest improvement (factor of ∼2) seen at higher frequencies, in part because quantum squeezing has dramatically improved the detector noise level relative to the second observational run, O2. These limits are the most constraining to date over most of the parameter space searched.

关键词： Astrophysical studies of gravity Gravitational wave detection Gravitational wave sources Gravitational waves

来源：评论

学校读者我要写书评

暂无评论

Search for Continuous Gravitational Waves from Known Pulsars in the First Part of the Fourth LIGO-Virgo-KAGRA Observing Run

引用

Astrophysical Journal 2025年第2期983卷 99-99页

作者： Abac, A.G. Abbott, R. Abouelfettouh, I. Acernese, F. Ackley, K. Adhicary, S. Adhikari, N. Adhikari, R.X. Adkins, V.K. Agarwal, D. Agathos, M. Aghaei Abchouyeh, M. Aguiar, O.D. Aguilar, I. Aiello, L. Ain, A. Ajith, P. Akutsu, T. Albanesi, S. Alfaidi, R.A. Al-Jodah, A. Alléné, C. Allocca, A. Al-Shammari, S. Altin, P.A. Alvarez-Lopez, S. Amato, A. Amez-Droz, L. Amorosi, A. Amra, C. Ananyeva, A. Anderson, S.B. Anderson, W.G. Andia, M. Ando, M. Andrade, T. Andres, N. Andrés-Carcasona, M. Andrić, T. Anglin, J. Ansoldi, S. Antelis, J.M. Antier, S. Aoumi, M. Appavuravther, E.Z. Appert, S. Apple, S.K. Arai, K. Araya, A. Araya, M.C. Areeda, J.S. Argianas, L. Aritomi, N. Armato, F. Arnaud, N. Arogeti, M. Aronson, S.M. Ashton, G. Aso, Y. Assiduo, M. Assis de Souza Melo, S. Aston, S.M. Astone, P. Attadio, F. Aubin, F. AultONeal, K. Avallone, G. Babak, S. Badaracco, F. Badger, C. Bae, S. Bagnasco, S. Bagui, E. Baier, J.G. Baiotti, L. Bajpai, R. Baka, T. Ball, M. Ballardin, G. Ballmer, S.W. Banagiri, S. Banerjee, B. Bankar, D. Baral, P. Barayoga, J.C. Barish, B.C. Barker, D. Barneo, P. Barone, F. Barr, B. Barsotti, L. Barsuglia, M. Barta, D. Bartoletti, A.M. Barton, M.A. Bartos, I. Basak, S. Basalaev, A. Bassiri, R. Basti, A. Bates, D.E. Bawaj, M. Baxi, P. Bayley, J.C. Baylor, A.C. Baynard, P.A. Bazzan, M. Bedakihale, V.M. Beirnaert, F. Bejger, M. Belardinelli, D. Bell, A.S. Benedetto, V. Benoit, W. Bentley, J.D. Ben Yaala, M. Bera, S. Berbel, M. Bergamin, F. Berger, B.K. Bernuzzi, S. Beroiz, M. Bersanetti, D. Bertolini, A. Betzwieser, J. Beveridge, D. Bevins, N. Bhandare, R. Bhardwaj, U. Bhatt, R. Bhattacharjee, D. Bhaumik, S. Bhowmick, S. Bianchi, A. Bilenko, I.A. Billingsley, G. Binetti, A. Bini, S. Birnholtz, O. Biscoveanu, S. Bisht, A. Bitossi, M. Bizouard, M.-A. Blackburn, J.K. Blagg, L.A. Blair, C.D. Blair, D.G. Bobba, F. Bode, N. Boileau, G. Boldrini, M. Bolingbroke, G.N. Bolliand, A. Bonavena, L.D. Bondarescu, R. Bondu, F. Bonilla, E. Bonilla, M.S. Bonino, A. Bonnand, R. Booker, P. Borchers, A. Boschi, V. Bose, S. Boss Max Planck Institute for Gravitational Physics (Albert Einstein Institute) Potsdam D-14476 Germany LIGO Laboratory California Institute of Technology Pasadena 91125 CA United States LIGO Hanford Observatory Richland 99352 WA United States Dipartimento di Farmacia Università di Salerno Fisciano Salerno I-84084 Italy INFN Sezione di Napoli Napoli I-80126 Italy University of Warwick Coventry CV 47AL United Kingdom The Pennsylvania State University University Park 16802 PA United States University of Wisconsin-Milwaukee Milwaukee 53201 WI United States Louisiana State University Baton Rouge 70803 LA United States Université Catholique de Louvain Louvain-la-Neuve B-1348 Belgium Inter-University Centre for Astronomy and Astrophysics Pune 411007 India Queen Mary University of London London E1 4NS United Kingdom Department of Physics and Astronomy Sejong University 209 Neungdong-ro Gwangjin-gu Seoul 143-747 South Korea Instituto Nacional de Pesquisas Espaciais São José dos Campos São Paulo 12227-010 Brazil Stanford University Stanford 94305 CA United States Università di Roma Tor Vergata Roma I-00133 Italy INFN Sezione di Roma Tor Vergata Roma I-00133 Italy Cardiff University Cardiff CF24 3AA United Kingdom Universiteit Antwerpen Antwerpen 2000 Belgium International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan INFN Sezione di Torino Torino I-10125 Italy Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena Jena D-07743 Germany Dipartimento di Fisica Università degli Studi di Torino Torino I-10125 Italy SUPA University of Glasgow Glasgow G12 8QQ United Kingdom OzGrav University of Western Australia Crawley 6009 WA

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of general relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering single-harmonic and dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is 6.4 × 10^-27 for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is 8.8 × 10^-9 for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets, we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of nonstandard polarizations as predicted by the Brans-Dicke theory. © 2025. The Author(s). Published by the American Astronomical Society.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ultralight vector dark matter search using data from the KAGRA O3GK run

引用

Physical Review D 2024年第4期110卷 042001页

作者： A. G. Abac R. Abbott H. Abe I. Abouelfettouh F. Acernese K. Ackley C. Adamcewicz S. Adhicary N. Adhikari R. X. Adhikari V. K. Adkins V. B. Adya C. Affeldt D. Agarwal M. Agathos O. D. Aguiar I. Aguilar L. Aiello A. Ain P. Ajith T. Akutsu S. Albanesi R. A. Alfaidi A. Al-Jodah C. Alléné A. Allocca S. Al-Shammari P. A. Altin S. Alvarez-Lopez A. Amato L. Amez-Droz A. Amorosi C. Amra S. Anand A. Ananyeva S. B. Anderson W. G. Anderson M. Andia M. Ando T. Andrade N. Andres M. Andrés-Carcasona T. Andrić J. Anglin S. Ansoldi J. M. Antelis S. Antier M. Aoumi E. Z. Appavuravther S. Appert S. K. Apple K. Arai A. Araya M. C. Araya J. S. Areeda N. Aritomi F. Armato N. Arnaud M. Arogeti S. M. Aronson K. G. Arun G. Ashton Y. Aso M. Assiduo S. Assis de Souza Melo S. M. Aston P. Astone F. Aubin K. AultONeal G. Avallone S. Babak F. Badaracco C. Badger S. Bae S. Bagnasco E. Bagui Y. Bai J. G. Baier R. Bajpai T. Baka M. Ball G. Ballardin S. W. Ballmer S. Banagiri B. Banerjee D. Bankar P. Baral J. C. Barayoga B. C. Barish D. Barker P. Barneo F. Barone B. Barr L. Barsotti M. Barsuglia D. Barta S. D. Barthelmy M. A. Barton I. Bartos S. Basak A. Basalaev R. Bassiri A. Basti M. Bawaj P. Baxi J. C. Bayley A. C. Baylor M. Bazzan B. Bécsy V. M. Bedakihale F. Beirnaert M. Bejger D. Belardinelli A. S. Bell V. Benedetto D. Beniwal W. Benoit J. D. Bentley M. Ben Yaala S. Bera M. Berbel F. Bergamin B. K. Berger S. Bernuzzi M. Beroiz D. Bersanetti A. Bertolini J. Betzwieser D. Beveridge N. Bevins R. Bhandare U. Bhardwaj R. Bhatt D. Bhattacharjee S. Bhaumik S. Bhowmick A. Bianchi I. A. Bilenko G. Billingsley A. Binetti S. Bini O. Birnholtz S. Biscoveanu A. Bisht M. Bitossi M.-A. Bizouard J. K. Blackburn C. D. Blair D. G. Blair F. Bobba N. Bode G. Bogaert G. Boileau M. Boldrini G. N. Bolingbroke A. Bolliand L. D. Bonavena R. Bondarescu F. Bondu E. Bonilla M. S. Bonilla A. Bonino R. Bonnand P. Booker A. Borchers V. Boschi S. Bose V. Bossilkov V. Boudart A. Boumerdassi A. Bozzi C. Bradaschia P. R. Brady M. Braglia A. Branch M. Branchesi M. Breschi T. B Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-14476 Potsdam Germany LIGO Laboratory California Institute of Technology Pasadena California 91125 USA Graduate School of Science Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo 152-8551 Japan LIGO Hanford Observatory Richland Washington 99352 USA Dipartimento di Farmacia Università di Salerno I-84084 Fisciano Salerno Italy INFN Sezione di Napoli I-80126 Napoli Italy University of Warwick Coventry CV4 7AL United Kingdom OzGrav School of Physics & Astronomy Monash University Clayton 3800 Victoria Australia The Pennsylvania State University University Park Pennsylvania 16802 USA University of Wisconsin-Milwaukee Milwaukee Wisconsin 53201 USA Louisiana State University Baton Rouge Louisiana 70803 USA OzGrav Australian National University Canberra Australian Capital Territory 0200 Australia Max Planck Institute for Gravitational Physics (Albert Einstein Institute) D-30167 Hannover Germany Leibniz Universität Hannover D-30167 Hannover Germany Inter-University Centre for Astronomy and Astrophysics Pune 411007 India University of Cambridge Cambridge CB2 1TN United Kingdom Instituto Nacional de Pesquisas Espaciais 12227-010 São José dos Campos São Paulo Brazil Stanford University Stanford California 94305 USA Cardiff University Cardiff CF24 3AA United Kingdom INFN Sezione di Pisa I-56127 Pisa Italy International Centre for Theoretical Sciences Tata Institute of Fundamental Research Bengaluru 560089 India Gravitational Wave Science Project National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Dipartimento di Fisica Università degli Studi di Torino I-10125 Torino Italy INFN Sezione di Torino I-10125 Torino Italy SUPA University of Glasgow Glasgow G12 8QQ United Kingdom OzGrav University of Western Austral

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation timescale of DM.

关键词： Dark matter Particle dark matter Gravitational wave detectors

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: Alpha-synuclein facilitates to form short unconventional microtubules that have a unique function in the axonal transport

引用

Scientific reports 2018年第1期8卷 8019页

作者： Shiori Toba Mingyue Jin Masami Yamada Kanako Kumamoto Sakiko Matsumoto Takuo Yasunaga Yuko Fukunaga Atsuo Miyazawa Sakiko Fujita Kyoko Itoh Shinji Fushiki Hiroaki Kojima Hideki Wanibuchi Yoshiyuki Arai Takeharu Nagai Shinji Hirotsune Department of Genetic Disease Research Osaka City University Graduate School of Medicine Asahi-machi 1-4-3 Abeno Osaka 545-8585 Japan. Department of Bioscience and Bioinformatics Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Kawazu 680-4 Iizuka Fukuoka 820-850 Japan. JST-SENTAN 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan. JST-CREST 4-1-8 Honcho Kawaguchi Saitama 332-0012 Japan. Graduate School of Life Science University of Hyogo 3-2-1 Kouto Kamigori-cho Ako-gun Hyogo 678-1297 Japan. RSC-University of Hyogo Leading Program Center RIKEN SPring-8 Center 1-1-1 Kouto Sayo-cho Sayo-gun Hyogo 679-5148 Japan. Graduate School of Materials Science Nara Institute of Science and Technology 8916-5 Takayama Ikoma Nara 630-0101 Japan. Department of Pathology and Applied Neurobiology Kyoto Prefectural University of Medicine Graduate School of Medical Sciences Kajii-cho Kawaramachi-Hirokoji Kamigyo-ku Kyoto 602-8566 Japan. Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Kobe 651-2492 Japan. Department of Pathology Osaka City University Graduate School of Medicine Asahi-machi 1-4-3 Abeno Osaka 545-8586 Japan. Department of Biomolecular Science and Engineering Institute of Scientific and Industrial Research Osaka University Mihoga-oka 8-1 Osaka 567-0047 Japan. Department of Genetic Disease Research Osaka City University Graduate School of Medicine Asahi-machi 1-4-3 Abeno Osaka 545-8585 Japan. shinjih@med.osaka-cu.ac.jp.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cascaded free search differential evolution applied to nonlinear system identification based on correlation functions and neural networks 4

Cascaded free search differential evolution applied to nonli...

引用

4th IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2014

作者： Ayala, Helon Vicente Hultmann Da Cruz, Luciano F. Freire, Roberto Z. Dos Santos Coelho, Leandro Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Imaculada Conceicao St. 1155 Curitiba80215-901 Brazil Department of Electrical Engineering Federal University of Parana Cel. F. H. dos Santos Av. 210 Curitiba81531-970 Brazil

ISBN: (纸本)9781479945313

This paper presents a procedure for input selection and parameter estimation for system identification based on Radial Basis Functions Neural Networks (RBFNNs) models and Free Search Differential Evolution (FSDE). We adopt a cascaded evolutionary algorithm approach and problem decomposition to define the model orders and the related model parameters based on higher orders correlation functions. Thus, we adopt two distinct populations: the first to select the lags on the inputs and outputs of the system and the second to define the parameters for the RBFNN. We show the results when the proposed methodology is applied to model a coupled drives system with real acquired data. We use to this end the canonical binary genetic algorithm (selection of lags) and the recently proposed FSDE (definition of the model parameters), which is very convenient for the present problem for having few control parameters. The results show the validity of the approach when compared to a classical input selection algorithm. © 2014 IEEE.

关键词： Parameter estimation

来源：评论

学校读者我要写书评

暂无评论

Cascaded evolutionary multiobjective identification based on correlation function statistical tests for improving velocity analyzes in swimming

Cascaded evolutionary multiobjective identification based on...

引用

2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM 2014

作者： Ayala, Helon Vicente Hultmann Da Cruz, Luciano Ferreira Freire, Roberto Zanetti Coelho, Leandro Dos Santos Industrial and Systems Engineering Graduate Program PUCPR Curitiba Brazil Industrial and Systems Engineering Graduate Program Department of Electrical Engineering UFPR Curitiba Brazil

ISBN: (纸本)9781479944682

By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively. © 2014 IEEE.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

The global spectrum of tree crown architecture

引用

Nature communications 2025年第1期16卷 4876页

作者： Tommaso Jucker Fabian Jörg Fischer Jérôme Chave David A Coomes John Caspersen Arshad Ali Grace Jopaul Loubota Panzou Ted R Feldpausch Daniel Falster Vladimir A Usoltsev Toby D Jackson Stephen Adu-Bredu Luciana F Alves Mohammad Aminpour Bhely Angoboy Ilondea Niels P R Anten Cécile Antin Yousef Askari Narayanan Ayyappan Lindsay F Banin Nicolas Barbier John J Battles Hans Beeckman Yannick E Bocko Ben Bond-Lamberty Frans Bongers Samuel Bowers Michiel van Breugel Arthur Chantrain Rajeev Chaudhary Jingyu Dai Michele Dalponte Kangbéni Dimobe Jean-Christophe Domec Jean-Louis Doucet Juan Manuel Dupuy Rada Remko A Duursma Moisés Enríquez Karin Y van Ewijk William Farfán-Rios Adeline Fayolle Marco Ferretti Eric Forni David I Forrester Hammad Gilani John L Godlee Matthias Haeni Jefferson S Hall Jie-Kun He Andreas Hemp José L Hernández-Stefanoni Steven I Higgins Robert J Holdaway Kiramat Hussain Lindsay B Hutley Tomoaki Ichie Yoshiko Iida Hai-Sheng Jiang Puspa Raj Joshi Hasan Kaboli Maryam Kazempour Larsary Tanaka Kenzo Brian D Kloeppel Takashi S Kohyama Suwash Kunwar Shem Kuyah Jakub Kvasnica Siliang Lin Emily R Lines Hongyan Liu Craig Lorimer Jean-Joël Loumeto Yadvinder Malhi Peter L Marshall Eskil Mattsson Radim Matula Jorge A Meave Sylvanus Mensah Xiangcheng Mi Stéphane T Momo Glenn R Moncrieff Francisco Mora Rodrigo Muñoz Sarath P Nissanka Zamah Shari Nur Hajar Kevin L O'Hara Steven Pearce Raphaël Pelissier Pablo L Peri Pierre Ploton Lourens Poorter Mohsen Javanmiri Pour Hassan Pourbabaei Sabina C Ribeiro Casey Ryan Anvar Sanaei Jennifer Sanger Michael Schlund Giacomo Sellan Alexander Shenkin Bonaventure Sonké Frank J Sterck Martin Svátek Kentaro Takagi Anna T Trugman Matthew A Vadeboncoeur Ahmad Valipour Mark C Vanderwel Alejandra G Vovides Peter Waldner Weiwei Wang Li-Qiu Wang Christian Wirth Murray Woods Wenhua Xiang Fabiano de Aquino Ximenes Yaozhan Xu Toshihiro Yamada Miguel A Zavala Niklaus E Zimmermann School of Biological Sciences University of Bristol Bristol BS8 1TQ UK. t.jucker@bristol.ac.uk. School of Biological Sciences University of Bristol Bristol BS8 1TQ UK. UMR5300 Centre de Recherche sur la Biodiversité et l'Environnement CNRS INPT IRD Université de Toulouse Bât 4R1 118 route de Narbonne 31062 Toulouse France. Conservation Research Institute University of Cambridge Cambridge CB2 3EA UK. Institute of Forestry and Conservation University of Toronto 33 Willcocks Street Toronto ON M5S 3B3 Canada. Forest Ecology Research Group College of Life Sciences Hebei University Baoding 071002 Hebei China. Institut Supérieur des Sciences Géographiques Environnementales et de l'Aménagement (ISSGEA) Université DENIS SASSOU-N'GUESSO Kintélé République du Congo. Laboratoire de Biodiversité de Gestion des Ecosystèmes et de l'Environnement (LBGE) Faculté des Sciences et Techniques Université Marien NGOUABI BP 69 Brazzaville Brazzaville République du Congo. Faculty of Environment Science and Economy University of Exeter Exeter EX4 4QE UK. Evolution & Ecology Research Centre University of New South Wales Sydney NSW Sydney Australia. Department of Forest Mensuration and Management Ural State Forest Engineering and Economic University Yekaterinburg Russia. Forestry Research Institute of Ghana Council for Scientific and Industrial Research University Kumasi Ghana. Center for Tropical Research Institute of the Environment and Sustainability University of California Los Angeles Los Angeles CA USA. Natural Recourses and Watershed Management Office West Azerbaijan Province Urmia Iran. Institut National pour l'Etude et la Recherche Agronomiques BP 2037 Kinshasa Democratic Republic of the Congo. Université Pédagogique Nationale BP 8815 Kinshasa-Ngaliema Democratic Republic of the Congo. Center for Crop Systems Analysis Wageningen University & Research Wageningen Netherlands. AMAP lab Montpellier University IRD CIRAD CNRS INRAE Montpellier France. Rese

Trees can differ enormously in their crown architectural traits, such as the scaling relationships between tree height, crown width and stem diameter. Yet despite the importance of crown architecture in shaping the structure and function of terrestrial ecosystems, we lack a complete picture of what drives this incredible diversity in crown shapes. Using data from 374,888 globally distributed trees, we explore how climate, disturbance, competition, functional traits, and evolutionary history constrain the height and crown width scaling relationships of 1914 tree species. We find that variation in height-diameter scaling relationships is primarily controlled by water availability and light competition. Conversely, crown width is predominantly shaped by exposure to wind and fire, while also covarying with functional traits related to mechanical stability and photosynthesis. Additionally, we identify several plant lineages with highly distinctive stem and crown forms, such as the exceedingly slender dipterocarps of Southeast Asia, or the extremely wide crowns of legume trees in African savannas. Our study charts the global spectrum of tree crown architecture and pinpoints the processes that shape the 3D structure of woody ecosystems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

引用

The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

关键词：

来源：评论

学校读者我要写书评

暂无评论

Face recognition using Support Vector Machine and multiscale directional image representation methods: A comparative study

Face recognition using Support Vector Machine and multiscale...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Daniel M. M. da Costa Sarajane M. Peres Clodoaldo A. M. Lima Pollyana Mustaro Information Systems Program University of São Paulo São Paulo SP Brazil Graduate Program in Electrical Engineering and Computing Mackenzie Presbyterian University São Paulo SP Brazil

ISBN: (纸本)9781479919611

In recent years, human identification based on face recognition has attracted the attention of the scientific community and the general public due to its wide range of applications. A face recognition system involves three important phases: face detection, feature extraction and classification (identification and/or verification). The robustness of face recognition could be improved by treating the variations in these stages. One of the main issues in design of face recognition system is how to extract discriminative facial features. A precise extraction of a representative feature set will improve the performance of a face recognition system. Various techniques have been used to represent images efficiently, of which the most well-known and widely applied are Wavelet, Contourlet, Shearlet and Curvelet Transform. Their ability to capture localized time-frequency information of image motivates their use for feature extraction. In this paper, we conduct a systematic empirical study on these transforms as feature extractors from face images. To further reduce the feature dimensionality, we adopt Principal Component Analysis and Linear Discriminant Analysis to select the most discriminative feature sets. The performance levels delivered by each transform are contrasted in terms of the accuracy measure computed over the outputs generated by the Support Vector Machine classifier (SVM). Experimental results conducted on a publicly available database are reported whereby we observe that the Curvelet Transform followed by the Wavelet Transform significantly outperform the others according to accuracy measure calculated over the SVM classifier.

关键词： Face recognition Support vector machines Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：