Author: "Bilicki, M" - Searchworks@Jio Institute Digital Library Search Results

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395 results on '"Bilicki, M"'

1. EMU/GAMA: Radio detected galaxies are more obscured than optically selected galaxies

Author: Ahmed, U. T., Hopkins, A. M., Ware, J., Gordon, Y. A., Bilicki, M., Brown, M. J. I., Cluver, M., Gürkan, G., López-Sánchez, Á. R., Leahy, D. A., Marchetti, L., Phillipps, S., Prandoni, I., Seymour, N., Taylor, E. N., and Vardoulaki, E.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We demonstrate the importance of radio selection in probing heavily obscured galaxy populations. We combine Evolutionary Map of the Universe (EMU) Early Science data in the Galaxy and Mass Assembly (GAMA) G23 field with the GAMA data, providing optical photometry and spectral line measurements, together with Wide-field Infrared Survey Explorer (WISE) infrared (IR) photometry, providing IR luminosities and colours. We investigate the degree of obscuration in star forming galaxies, based on the Balmer decrement (BD), and explore how this trend varies, over a redshift range of 0
Published: 2023

2. Cosmology from LOFAR Two-metre Sky Survey Data Release 2: Cross-correlation with the cosmic microwave background

Author: Nakoneczny, S. J., Alonso, D., Bilicki, M., Schwarz, D. J., Hale, C. L., Pollo, A., Heneka, C., Tiwari, P., Zheng, J., Brüggen, M., Jarvis, M. J., and Shimwell, T. W.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We combine the LOw-Frequency ARray (LOFAR) Two-metre Sky Survey (LoTSS) second data release (DR2) catalogue with gravitational lensing maps from the Cosmic Microwave Background (CMB) to place constraints on the bias evolution of LoTSS radio galaxies, and on the amplitude of matter perturbations. We construct a flux-limited catalogue, and analyse its harmonic-space cross-correlation with CMB lensing maps from Planck, $C_\ell^{g\kappa}$, as well as its auto-correlation, $C_\ell^{gg}$. We explore the models describing the redshift evolution of the large-scale radio galaxy bias, discriminating between them through the combination of both $C_\ell^{g\kappa}$ and $C_\ell^{gg}$. Fixing the bias evolution, we then use these data to place constraints on the amplitude of large scale density fluctuations. We report the significance of the $C_\ell^{g\kappa}$ signal at a level of $26.6\sigma$. We determine that a linear bias evolution of the form $b_g(z) = b_{g,D} / D(z)$, where $D(z)$ is the growth rate, is able to provide a good description of the data, and measure $b_{g,D} = 1.41 \pm 0.06$ for a sample flux-limited at $1.5\,{\rm mJy}$, for scales $\ell < 250$ for $C_\ell^{gg}$, and $\ell < 500$ for $C_\ell^{g\kappa}$. At the sample's median redshift, we obtain $b(z = 0.82) = 2.34 \pm 0.10$. Using $\sigma_8$ as a free parameter, while keeping other cosmological parameters fixed to the Planck values, we find fluctuations of $\sigma_8 = 0.75^{+0.05}_{-0.04}$. The result is in agreement with weak lensing surveys, and at $1\sigma$ difference with Planck CMB constraints. We also attempt to detect the late-time integrated Sachs-Wolfe effect with LOFAR, but with the current sky coverage, the cross-correlation with CMB temperature maps is consistent with zero. Our results are an important step towards constraining cosmology with radio continuum surveys from LOFAR and other future large radio surveys., Comment: The code is available at https://github.com/snakoneczny/cosmo-pipe
Published: 2023
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3. Cosmology from LOFAR Two-metre Sky Survey Data Release 2: Angular Clustering of Radio Sources

Author: Hale, C. L., Schwarz, D. J., Best, P. N., Nakoneczny, S. J., Alonso, D., Bacon, D., Böhme, L., Bhardwaj, N., Bilicki, M., Camera, S., Heneka, C. S., Pashapour-Ahmadabadi, M., Tiwari, P., Zheng, J., Duncan, K. J., Jarvis, M. J., Kondapally, R., Magliocchetti, M., Rottgering, H. J. A., and Shimwell, T. W.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Covering $\sim$5600 deg$^2$ to rms sensitivities of $\sim$70$-$100 $\mu$Jy beam$^{-1}$, the LOFAR Two-metre Sky Survey Data Release 2 (LoTSS-DR2) provides the largest low-frequency ($\sim$150 MHz) radio catalogue to date, making it an excellent tool for large-area radio cosmology studies. In this work, we use LoTSS-DR2 sources to investigate the angular two-point correlation function of galaxies within the survey. We discuss systematics in the data and an improved methodology for generating random catalogues, compared to that used for LoTSS-DR1, before presenting the angular clustering for $\sim$900,000 sources $\geq$$1.5$ mJy and a peak signal-to-noise $\geq$$7.5$ across $\sim$$80\%$ of the observed area. Using the clustering we infer the bias assuming two evolutionary models. When fitting {angular scales of $0.5 \leq\theta<5\,\deg$, using a linear bias model, we find LoTSS-DR2 sources are biased tracers of the underlying matter, with a bias of $b_{C}= 2.14^{+0.22}_{-0.20}$ (assuming constant bias) and $b_{E}(z=0)= 1.79^{+0.15}_{-0.14}$ (for an evolving model, inversely proportional to the growth factor), corresponding to $b_E= 2.81^{+0.24}_{-0.22}$ at the median redshift of our sample, assuming the LoTSS Deep Fields redshift distribution is representative of our data. This reduces to $b_{C}= 2.02^{+0.17}_{-0.16}$ and $b_{E}(z=0)= 1.67^{+0.12}_{-0.12}$ when allowing preferential redshift distributions from the Deep Fields to model our data. Whilst the clustering amplitude is slightly lower than LoTSS-DR1 ($\geq$2 mJy), our study benefits from larger samples and improved redshift estimates., Comment: Accepted for publication in MNRAS. 29 pages, 24 figures
Published: 2023

4. Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abe, H., Acernese, F., Ackley, K., Adamcewicz, C., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, 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., Almualla, M., Altin, P. A., Álvarez-López, S., Amato, A., Amez-Droz, L., Amorosi, A., Anand, S., Ananyeva, A., Andersen, R., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badalyan, A., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bai, Y., Baier, J. G., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barber, J., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscans, S., Bischi, M., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boër, M., Bogaert, G., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonnand, R., Booker, P., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brooks, A. F., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Cain III, H. W., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chalathadka-Subrahmanya, S., Chan, C., Chan, J. C. L., Chan, K. H. M., Chan, M., Chan, W. L., Chandra, K., Chang, I. P., Chang, R. -J., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chastain, L., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, X., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., Chia, H. Y., Chiadini, F., Chiang, C., Chiarini, G., Chiba, A., Chiba, R., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Colleoni, M., Collette, C. G., Collins, J., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Cousins, B., Couvares, P., Coward, D. M., Cowart, M. J., Cowburn, B. D., Coyne, D. C., Coyne, R., Craig, K., Creighton, J. D. E., Creighton, T. D., Criswell, A. W., Crockett-Gray, J. C. G., Croquette, M., Crouch, R., Crowder, S. G., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Curyło, M., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Darsow-Fromm, C., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Dave, I., Davenport, A., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dax, M., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., De Pietri, R., De Rosa, R., De Rossi, C., De Simone, R., Dhurandhar, S., Diab, R., Diamond, P. Z., Díaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Lieto, A., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Du, H., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Engl, A. J., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, C. R., Evans, M., Evans, T. M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fair, H., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., Fauchon-Jones, E. J., Favaro, G., Favata, M., Fays, M., Feicht, J., Fejer, M. M., Fenyvesi, E., Ferguson, D. L., Ferrante, I., Ferreira, T. A., Fidecaro, F., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franke, A., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fujii, S., Fukunaga, I., Fulda, P., Fyffe, M., Gabella, W. E., Gadre, B., Gair, J. R., Gais, J., Galaudage, S., Gallardo, S., Gamba, R., Ganapathy, D., Ganguly, A., Gaonkar, S. G., Garaventa, B., Garcia-Bellido, J., García-Núñez, C., García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., George, J., Gerberding, O., Gergely, L., Ghadiri, N., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Glotin, F., Godfrey, J., Godwin, P., Goetz, E., Goetz, R., Golomb, J., Lopez, S. Gomez, Goncharov, B., González, G., Goodwin-Jones, A. W., Gosselin, M., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Gruson, A. S., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupte, N., Gurav, R., Gurs, J., Gustafson, E. K., Gutierrez, N., Guzman, F., Haba, D., Haegel, L., Hain, G., Haino, S., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, F. J., Healy, J., Heffernan, A., Heidmann, 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. -S., Hennig, M., Henshaw, C., Hernandez, A., Hertog, T., Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, J., Hoang, S., Hochheim, S., Hofman, D., Hohmann, J. N., Holland, N. A., Holley-Bockelmann, K., Hollows, I. J., Holmes, Z. J., Holz, D. E., Hong, C., Hong, Q., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hoyland, D., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, S. -C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huang, Y., Huang, Y. T., Hübner, M. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Hur, R., Husa, S., Huxford, R., Huynh-Dinh, T., Hyland, J., Iakovlev, A., Iandolo, G. A., Iess, A., Inayoshi, K., Inoue, Y., Iorio, G., Iosif, P., Irwin, J., Isi, M., Ismail, M. A., Itoh, Y., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacqmin, T., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, D., Jain, T., James, A. L., James, P. A., Jamshidi, R., Jan, A. Z., Jani, K., Janiurek, L., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jarov, S., Jasal, P., Jaume, R., Javed, W., Jenner, K., Jennings, A., Jia, W., Jiang, J., Jin, H. -B., Johansmeyer, K., Johns, G. R., Johnson, N. A., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Karki, S., Karydas, T., Kas-danouche, Y. A., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, J., Kato, T., Katsanevas, S., Katsavounidis, E., Katsuren, J. K., Katzman, W., Kaur, T., Kawabe, K., Kéfélian, F., Keitel, D., Kelley-Derzon, J., Kemper, S. A., Kennington, J., Kesharwani, R., Key, J. S., Khadka, S., Khalili, F. Y., Khanam, T., Khazanov, E. A., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, P., Kim, S., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Kiyota, T., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Koliadko, N. D., Kolitsidou, P., Kolstein, M., Komori, K., Kondrashov, V., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kouvatsos, N., Kovalam, M., Koyama, N., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuroyanagi, S., Kuwahara, S., Kwak, K., Kwan, K., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Lakkis, M. H., Lalande, E., Lalleman, M., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., LeBohec, S., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levesque, C., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Lin, Chien-Yu, Lin, Chun-Yu, Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Llamas, F., Lo, R. K. L., Lo, T., Locquet, J. -P., London, L., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lott, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lovelace, G., Lowry, M. J., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Lynam, J. E., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., MacInnis, M., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magazzù, C., Magee, R. M., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., 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, B. B., Martinez, M., Martinez, V. A., Martinez, V., Martini, A., Martinovic, K., Martynov, D. V., Marx, E. J., Masalehdan, H., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Mateu-Lucena, M., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McGhee, G. I., McGinn, J., Mchedlidze, M., McIsaac, C., McIver, J., McKinney, K., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Mihaylov, D. P., Miller, A. L., Miller, A., Miller, B., Miller, S., Millhouse, M., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. ., Mishkin, A., Mishra, A., Mishra, C., Mishra, T., Mistry, T., Mitchell, A. L., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Modafferi, L. M., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Morales, M., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., 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., Murakoshi, M., Murray, P. G., Muusse, S., Nadji, S. L., Nagar, A., Nagar, T., Nagarajan, N., Nakamura, K., Nakano, H., Nakano, M., Napolano, V., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Nesseris, S., Neunzert, A., Ng, K. Y., Ng, S. W. S., Nguyen, C., Nguyen, P., Quynh, L. Nguyen, Nichols, S. A., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nurbek, G., Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oelker, E., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Ohta, H., Oliveira, A. S., Oliveri, R., Oloworaran, V., O'Neal, B., Oohara, K., O'Reilly, B., Ormiston, R. G., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ottaway, D. J., Ouzriat, A., Overmier, H., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pai, S. A., Pal, A., Pal, S., Palashov, O., Pálfi, M., Palomba, C., Pan, K. -C., Panda, P. K., Panebianco, L., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. H., Panzer, C. D., Paoletti, F., Paoli, A., Paolone, A., Papalexakis, E. E., Papalini, L., Pappas, G., Parisi, A., Park, J., Parker, W., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passuello, D., Patel, M., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pegoraro, M., Pele, A., Arellano, F. E. Peña, Penn, S., Perego, A., Pereira, A., Perez, C. J., Perez, J. J., Perez, L. H., Périgois, C., Perkins, C. C., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petermann, J., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M. ., Pillant, G., Pillas, M., Pilo, F., Pinard, L., Pineda-Bosque, C., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Ponrathnam, S., Poon, J., Porcelli, E., Portell, J., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Prudenzi, L., Puecher, A., Pullin, J., Punturo, M., Puosi, F., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quetschke, V., Quinonez, P. J., Quitzow-James, R., Raab, F. J., Raaijmakers, G., Radulesco, N., Raffai, P., Rail, S. X., Raja, S., Rajan, C., Ramirez, K. E., Ramos-Buades, A., Rana, D., Randel, E., Rangnekar, P. R., Rapagnani, P., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reid, S. W., Reitze, D. H., Relton, P., Renzini, A., Rettegno, P., Revenu, B., Reza, A., Rezac, M., Rezaei, A. S., Ricci, F., Ricci, M., Richards, D., Richardson, J. W., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Robertson, C., Robertson, N. A., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romanelli, M., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S., Royzman, A., Rozza, D., Ruggi, P., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Saha, S. S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sako, T., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Saravanan, T. R., Sarin, N., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, S., Sato, Y., Sauter, O., Savage, R. L., Savant, V., Sawada, T., Sawant, H. L., Sayah, S., Schaetzl, D., Scheel, M., Scherf, S. J., Scheuer, J., Schiworski, M. G., Schmidt, P., Schmidt, S., Schmitz, S. J., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schönbeck, A., Schouteden, K., Schuler, H., Schulte, B. W., Schutz, B. F., Schwartz, E., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Servignat, G., Setyawati, Y., Shaffer, T., Shahriar, M. S., Shaikh, M. A., Shams, B., Shao, L., Sharma, P., Sharma-Chaudhary, S., Shawhan, P., Shcheblanov, N. S., Sheela, A., Shen, B., Shepard, K. G., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Soldateschi, J., Somala, S. N., Somiya, K., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Soulard, R., Souradeep, T., Sowell, E., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Srivastava, A. K., Srivastava, V., Stachie, C., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Strang, L. C., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suh, H. G., Sullivan, A. G., Summerscales, T. Z., Sun, L., Sunil, S., Sur, A., Suresh, J., Sutton, P. J., Suzuki, Takamasa, Suzuki, Takanori, Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takatani, K., Takeda, H., Takeda, M., Talbot, C. J., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tanasijczuk, A. J., Tanioka, S., Tanner, D. B., Tao, D., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Terkowski, L., Themann, H., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tonelli, M., Toriyama, A., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trani, A. A., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tse, M., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Uehara, T., Ueno, K., Unnikrishnan, C. S., Ushiba, T., Utina, A., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venneberg, J., Verdier, P., Verkindt, D., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Veutro, A., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watada, K., Watarai, D., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Willetts, K., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wils, M., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wong, D., Wong, H. T., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Xu, V. A., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, M., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yang, F. W., Yang, K. Z., Yang, L. -C., Yang, Y. -C., Yang, Yang, Yang, Yi, Yap, M. J., Yarbrough, Z., Yeh, S. -W., Yelikar, A. B., Yeung, S. M. C., Yeung, T. Y., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuzurihara, H., Zadrożny, A., Zannelli, A. J., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zevin, M., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Yanqi, Zhang, Ya, Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level., Comment: 24 pages, 5 figures
Published: 2023

5. DES Y3 + KiDS-1000: Consistent cosmology combining cosmic shear surveys

Author: Survey, Dark Energy, Collaboration, Kilo-Degree Survey, Abbott, T. M. C., Aguena, M., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Asgari, M., Avila, S., Bacon, D., Bechtol, K., Becker, M. R., Bernstein, G. M., Bertin, E., Bilicki, M., Blazek, J., Bocquet, S., Brooks, D., Burger, P., Burke, D. L., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Cawthon, R., Chang, C., Chen, R., Choi, A., Conselice, C., Cordero, J., Crocce, M., da Costa, L. N., Pereira, M. E. da Silva, Dalal, R., Davis, C., de Jong, J. T. A., DeRose, J., Desai, S., Diehl, H. T., Dodelson, S., Doel, P., Doux, C., Drlica-Wagner, A., Dvornik, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Ferrero, I., Ferté, A., Flaugher, B., Friedrich, O., Frieman, J., García-Bellido, J., Gatti, M., Giannini, G., Giblin, B., Gruen, D., Gruendl, R. A., Gutierrez, G., Harrison, I., Hartley, W. G., Herner, K., Heymans, C., Hildebrandt, H., Hinton, S. R., Hoekstra, H., Hollowood, D. L., Honscheid, K., Huang, H., Huff, E. M., Huterer, D., James, D. J., Jarvis, M., Jeffrey, N., Jeltema, T., Joachimi, B., Joudaki, S., Kannawadi, A., Krause, E., Kuehn, K., Kuijken, K., Kuropatkin, N., Lahav, O., Leget, P. -F., Lemos, P., Li, S. -S., Li, X., Liddle, A. R., Lima, M., Lin, C. -A, Lin, H., MacCrann, N., Mahony, C., Marshall, J. L., McCullough, J., Mena-Fernández, J., Menanteau, F., Miquel, R., Mohr, J. J., Muir, J., Myles, J., Napolitano, N., Navarro-Alsina, A., Ogando, R. L. C., Palmese, A., Pandey, S., Park, Y., Paterno, M., Peacock, J. A., Petravick, D., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Prat, J., Radovich, M., Raveri, M., Reischke, R., Robertson, N. C., Rollins, R. P., Romer, A. K., Roodman, A., Rykoff, E. S., Samuroff, S., Sánchez, C., Sanchez, E., Sanchez, J., Schneider, P., Secco, L. F., Sevilla-Noarbe, I., Shan, H. -Y., Sheldon, E., Shin, T., Sifón, C., Smith, M., Soares-Santos, M., Stölzner, B., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., Troxel, M. A., Tröster, T., Tutusaus, I., Busch, J. L. van den, Varga, T. N., Walker, A. R., Weaverdyck, N., Wechsler, R. H., Weller, J., Wiseman, P., Wright, A. H., Yanny, B., Yin, B., Yoon, M., Zhang, Y., and Zuntz, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter $S_8 = \sigma_8 \sqrt{\Omega_{\rm m}/0.3}$ with a mean value of $0.790^{+0.018}_{-0.014}$. The mean marginal is lower than the maximum a posteriori estimate, $S_8=0.801$, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with $S_8$ constraints from observations of the cosmic microwave background by Planck, with agreement at the $1.7\sigma$ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum., Comment: 40 pages, 21 figures, 15 tables, accepted Open Journal of Astrophysics. Download the chains from https://des.ncsa.illinois.edu/releases/y3a2/Y3key-joint-des-kids or create your own chains with CosmoSIS using https://github.com/joezuntz/cosmosis-standard-library/blob/main/examples/des-y3_and_kids-1000.ini Watch the core team discuss this analysis at https://cosmologytalks.com/2023/05/26/des-kids
Published: 2023
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6. Wavelength-resolved reverberation mapping of intermediate redshift quasars HE 0413-4031 and HE 0435-4312: Dissecting Mg II, optical Fe II, and UV Fe II emission regions

Author: Prince, Raj, Zajaček, Michal, Panda, S., Hryniewicz, K., Jaiswal, V. K., Czerny, Bożena, Trzcionkowski, P., Bronikowski, M., Rałowski, M., Figaredo, C. S., Martinez-Aldama, M. L., Śniegowska, M., Średzińska, J., Bilicki, M., Naddaf, M-H, Pandey, A., Haas, M., Sarna, M. J., Pietrzyński, G., Karas, V., Olejak, A., Przyłuski, R., Sefako, R. R., Genade, A., Worters, H. L., Kozłowski, S., and Udalski, A.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract: We present the wavelength-resolved reverberation mapping (RM) of combined MgII and UV FeII broad-line emissions for two intermediate redshifts (z$\sim$1), luminous quasars - HE 0413-4031 and HE 0435-4312, monitored by the SALT and 1-m class telescopes between 2012-2022. Through this technique, we aim to disentangle the Mg II and FeII emission regions and to build a radius-luminosity relation for UV FeII emission, which has so far remained unconstrained. Several methodologies have been applied to constrain the time delays for total MgII and FeII emissions. In addition, this technique is performed to quantify the inflow or outflow of broad-line region gas around the supermassive black hole and to disentangle the emission/emitting regions from lines produced in proximity to each other. The mean total FeII time delay is nearly equal to the mean total Mg II time delay for HE 0435-4312 suggesting a co-spatiality of their emissions. However, in HE 0413-4031, the mean FeII time delay is found to be longer than the mean MgII time delay, suggesting that FeII is produced at longer distances from the black hole. The UV Fe II R-L relation is updated with these two quasars and compared with the optical FeII relation, which suggests that the optical FeII region is located further than the UV FeII by a factor of 1.7-1.9 i.e. $R_{\rm FeII-opt}\sim(1.7-1.9)R_{\rm FeII-UV}$. We detected a weak pattern in the time delay vs. wavelength relation, suggesting that the MgII broad-line originates a bit closer to the SMBH than the UV FeII, however, the difference is not very significant. Comparison of MgII, UV, and optical FeII R-L relations suggests that the difference may be larger for lower-luminosity sources, possibly with the MgII emission originating further from the SMBH. In the future, more RM data will be acquired to put better constraints on these trends, in particular the UV FeII R-L relation., Comment: 24 pages, 16 figures, 5 tables, Accepted for publication in A&A, in Press
Published: 2023
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7. Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Alléné, C., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Asada, H., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badaracco, F., Badger, C., Bae, S., Bae, Y., Bagnasco, S., Bai, Y., Baier, J. G., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Barayoga, J. 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., Basak, S., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belahcene, I., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., BenYaala, M., Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Bini, S., 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., Boër, M., Bogaert, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., 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., Bucci, F., Buchanan, J., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Caneva, G., Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakalis, W., Subrahmanya, S. Chalathadka, Champion, E., Chan, C. -H., Chan, C., Chan, C. L., Chan, K., Chan, M., Chandra, K., Chang, I. P., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, C., Chen, D., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y. -B., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C-Y., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, Q., Chu, Y-K., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Cohen, D. E., Colleoni, M., Collette, C. G., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Coschizza, A. C., Cotesta, R., Cottingham, 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., Craig, K., 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., Cuoco, E., Curyło, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., Dana, A., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Datta, Sayak, Datta, Sayantani, Dattilo, V., Dave, I., Davier, M., Davis, D., Davis, M. C., Daw, E. J., Dax, M., DeBra, D., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., Del Favero, V., De Lillo, F., De Lillo, N., Dell'Aquila, D., Del Pozzo, W., 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., Diab, R., Díaz, M. C., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giorgio, C., Di Giovanni, F., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Lieto, A., Di Michele, A., Di Pace, S., Di Palma, I., Di Renzo, F., Divakarla, A. K., Dmitriev, A., Doctor, Z., Doleva, P. P., Donahue, L., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Drori, Y., Ducoin, J. -G., Dunn, L., Dupletsa, U., 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., Eguchi, S., Eichholz, J., Eikenberry, S. S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Enomoto, Y., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evans, T. M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fair, H., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., 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, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Floden, E., Fong, H. K., Font, J. A., Fornal, B., Forsyth, P. W. F., Franke, A., Frasca, S., Frasconi, F., Freed, J. P., Frei, Z., Freise, A., Freitas, O., Frey, R., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fujii, Y., Fujikawa, Y., Fujimoto, Y., Fulda, P., Fyffe, M., Gabbard, H. A., Gabella, W. E., Gadre, B. U., Gair, J. R., Gais, J., Galaudage, S., Gamba, R., Ganapathy, D., Ganguly, A., Gao, D. -F., Gao, D., Gaonkar, S. G., Garaventa, B., García-Núñez, C., García-Quirós, C., Gardner, K. A., Gargiulo, J., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Ge, G. -G., Gemme, G., Gennai, A., George, J., Gerberding, O., Gergely, L., Ghonge, S., Ghosh, Abhirup, Ghosh, Archisman, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Gleckl, A. E., Godoy, F. G., Godwin, P., Goetz, E., Goetz, R., Golomb, J., Goncharov, B., González, G., Gosselin, M., Gouaty, R., Gould, D. W., Goyal, S., Grace, B., Grado, A., Graham, V., Granata, M., Granata, V., 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. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimm, S. J., Grote, H., Grunewald, S., Gruson, A. S., Guerra, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H. -K., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, P., Gupta, S. K., Gurs, J., Gustafson, R., Gutierrez, N., Guzman, F., Ha, S., Hadiputrawan, I. P. W., Haegel, L., Haino, S., Halim, O., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O., Hansen, H., Hanson, J., Harada, R., Harder, T., Haris, K., Harms, J., Harry, G. M., Harry, I. W., Hartwig, D., Hasegawa, K., Haskell, B., Haster, C. -J., Hathaway, J. S., Hattori, K., Haughian, K., Hayakawa, H., Hayama, 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. -S., Hennig, M., Henshaw, C., Hernandez, A. G., Vivanco, F. Hernandez, Heurs, M., Hewitt, A. L., Higginbotham, S., Hild, S., Hill, P., Himemoto, Y., Hines, A. S., Hirata, N., Hirose, C., Ho, T-C., Hochheim, S., Hofman, D., Hohmann, J. N., Holcomb, D. G., Holland, N. A., Hollows, I. J., Holmes, Z. J., Holt, K., Holz, D. E., Hong, Q., Hough, J., Hourihane, S., Howell, D., Howell, E. J., Hoy, C. G., Hoyland, D., Hreibi, A., Hsieh, B-H., Hsieh, H-F., Hsiung, C., Huang, H-Y., Huang, P., Huang, Y-C., Huang, Y. -J., Huang, Y., Hübner, M. T., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huttner, S. H., Huxford, R., Huynh-Dinh, T., Hyland, J., Iandolo, G. A., Ide, S., Idzkowski, B., Iess, A., Inayoshi, K., Inoue, Y., Iosif, P., Irwin, J., Gupta, Ish, Isi, M., Ito, K., Itoh, Y., Iyer, B. R., JaberianHamedan, V., Jacqmin, T., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., Jan, A. Z., Jani, K., Janquart, J., Janssens, K., Janthalur, N. N., Jaranowski, P., Jariwala, D., Jarov, S., Jaume, R., Jenkins, A. C., Jenner, K., Jeon, C., Jia, W., Jiang, J., Jin, H. -B., Johns, G. R., Johnston, R., Johny, N., Jones, A. W., Jones, D. I., Jones, P., Jones, R., Joshi, P., Ju, L., Jung, K., Jung, P., Junker, J., Juste, V., Kaihotsu, K., Kajita, T., Kakizaki, M., Kalaghatgi, C., Kalogera, V., Kamai, B., Kamiizumi, M., Kanda, N., 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., Kato, T., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kawabe, K., Kawaguchi, K., Kéfélian, F., Keitel, D., Key, J. S., Khadka, S., Khalili, F. Y., Khan, S., Khanam, T., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, J., Kim, K., Kim, P., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., King, B., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Kobayashi, Y., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Kondrashov, V., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kovalam, M., Koyama, N., Kozak, D. B., Kozakai, C., Kranzhoff, L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuromiya, Y., Kuroyanagi, S., Kuwahara, S., Kwak, K., Lacaille, G., Lagabbe, P., Laghi, D., Lalande, E., Lalleman, M., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., LeBohec, S., Lecoeuche, Y. K., Lee, E., Lee, H. M., Lee, K., Lee, R., Legred, I. N., Lehmann, J., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Leroy, N., Letendre, N., Levesque, C., Levin, Y., Leviton, J. N., Leyde, K., Li, A. K. Y., Li, B., Li, K. L., Li, P., Li, T. G. F., Li, X., Lin, C-Y., Lin, E. T., Lin, F-K., Lin, F-L., Lin, H. L., Lin, L. C. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, G. C., Liu, J., Liu, X., Llamas, F., Lo, R. K. L., Lo, T., 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., Lowry, M. J., Lucaccioni, J. F., Lück, H., Lumaca, D., Lundgren, A. P., Lung, Y., Luo, L. -W., Lussier, A. W., Lynam, J. E., Ma'arif, M., 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. N., Maksimovic, I., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B. R., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, 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., Masserot, A., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Mateu-Lucena, M., Matiushechkina, M., Mavalvala, N., McCann, J. J., McCarthy, R., McClelland, D. E., McClincy, P. K., McCormick, S., McCuller, L., McGhee, G. I., McGinn, J., McGuire, S. C., McIsaac, C., McIver, J., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Mendell, G., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Mihaylov, D. P., Miller, A., Miller, A. L., Miller, B., Millhouse, M., Mills, J. C., Milotti, E., Minenkov, Y., Mio, N., Mir, Ll. M., Miravet-Tenés, M., Mishkin, A., Mishra, C., Mishra, T., Mistry, T., Mitchell, A. L., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Miyakawa, O., Miyo, K., Miyoki, S., Mo, Geoffrey, Modafferi, L. M., Moguel, E., Mogushi, K., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moragues, J., Moraru, D., Morawski, F., More, A., More, S., Moreno, C., Moreno, G., Mori, Y., Morisaki, S., Morisue, N., Moriwaki, Y., Mours, B., Mow-Lowry, C. M., Mozzon, S., Muciaccia, F., Mukherjee, D., Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Muñiz, E. A., Murray, P. G., Muusse, S., Nadji, S. L., Nagano, K., Nagar, A., Nagar, T., Nakamura, K., Nakano, H., Nakano, M., Nakayama, Y., Napolano, V., Nardecchia, I., Narola, H., Naticchioni, L., Nayak, R. K., Neil, B. F., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neubauer, P., Neunzert, A., Ng, K. Y., Ng, S. W. S., Nguyen, C., Nguyen, P., Nguyen, T., Quynh, L. Nguyen, Ni, J., Ni, W. -T., Nichols, S. A., Nieradka, G., Nishimoto, T., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Notte, J., Novak, J., Nozaki, S., Nurbek, G., Nuttall, L. K., Obayashi, Y., Oberling, J., O'Brien, B. D., O'Dell, J., Oelker, E., Oertel, M., Ogaki, W., Oganesyan, G., Oh, J. J., Oh, K., Oh, S. H., O'Hanlon, T., Ohashi, M., Ohashi, T., Ohkawa, M., Ohme, F., Ohta, H., Okutani, Y., Oliveri, R., Olivetto, C., Oohara, K., Oram, R., O'Reilly, B., Ormiston, R. G., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, E., Oshino, S., Ossokine, S., Osthelder, C., Otabe, S., Ottaway, D. J., Overmier, H., Pace, A. E., Pagano, G., Pagano, R., Pagliaroli, G., Pai, A., Pai, S. A., Pal, S., Palamos, J. R., Palashov, O., Palomba, C., Pan, K. -C., Panda, P. K., Pang, P. T. H., Pannarale, F., Pant, B. C., Panther, F. 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Subjects: General Relativity and Quantum Cosmology, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract: Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects., Comment: 28 pages, 11 figures
Published: 2023

8. Open data from the third observing run of LIGO, Virgo, KAGRA and GEO

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Almualla, M., Altin, P. A., Amato, A., Amez-Droz, L., Amorosi, A., Anand, S., Ananyeva, A., Andersen, R., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Asada, H., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badalyan, A., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bai, Y., Baier, J. G., Baiotti, L., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barber, J., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Barthelmy, S. D., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Baylor, A. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. 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Subjects: General Relativity and Quantum Cosmology
Abstract: The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in April of 2019 and lasting six months, O3b starting in November of 2019 and lasting five months, and O3GK starting in April of 2020 and lasting 2 weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main dataset, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages., Comment: 27 pages, 3 figures
Published: 2023
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9. The Faraday Rotation Measure Grid of the LOFAR Two-metre Sky Survey: Data Release 2

Author: O'Sullivan, S. P., Shimwell, T. W., Hardcastle, M. J., Tasse, C., Heald, G., Carretti, E., Brüggen, M., Vacca, V., Sobey, C., Van Eck, C. L., Horellou, C., Beck, R., Bilicki, M., Bourke, S., Botteon, A., Croston, J. H., Drabent, A., Duncan, K., Heesen, V., Ideguchi, S., Kirwan, M., Lawlor, L., Mingo, B., Nikiel-Wroczyński, B., Piotrowska, J., Scaife, A. M. M., and van Weeren, R. J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: A Faraday rotation measure (RM) catalogue, or RM Grid, is a valuable resource for the study of cosmic magnetism. Using the second data release (DR2) from the LOFAR Two-metre Sky Survey (LoTSS), we have produced a catalogue of 2461 extragalactic high-precision RM values across 5720 deg$^{2}$ of sky (corresponding to a polarized source areal number density of $\sim$0.43 deg$^{-2}$). The linear polarization and RM properties were derived using RM synthesis from the Stokes $Q$ and $U$ channel images at an angular resolution of 20'' across a frequency range of 120 to 168 MHz with a channel bandwidth of 97.6 kHz. The fraction of total intensity sources ($>1$ mJy beam$^{-1}$) found to be polarized was $\sim$0.2%. The median detection threshold was 0.6 mJy beam$^{-1}$ ($8\sigma_{QU}$), with a median RM uncertainty of 0.06 rad m$^{-2}$ (although a systematic uncertainty of up to 0.3 rad m$^{-2}$ is possible, after the ionosphere RM correction). The median degree of polarization of the detected sources is 1.8%, with a range of 0.05% to 31%. Comparisons with cm-wavelength RMs indicate minimal amounts of Faraday complexity in the LoTSS detections, making them ideal sources for RM Grid studies. Host galaxy identifications were obtained for 88% of the sources, along with redshifts for 79% (both photometric and spectroscopic), with the median redshift being 0.6. The focus of the current catalogue was on reliability rather than completeness, and we expect future versions of the LoTSS RM Grid to have a higher areal number density. In addition, 25 pulsars were identified, mainly through their high degrees of linear polarization., Comment: 20 pages, 23 figures, 3 tables. Accepted for publication in MNRAS. Go to https://lofar-mksp.org/data/ to download the catalogue and associated data products
Published: 2023
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10. Modeling Strong Lenses from Wide-Field Ground-Based Observations in KiDS and GAMA

Author: Knabel, Shawn, Holwerda, B. W., Nightingale, J., Treu, T., Bilicki, M., Brough, S., Driver, S., Finnerty, L., Haberzettl, L., Hegde, S., Hopkins, A. M., Kuijken, K., Liske, J., Pimbblet, K. A., Steele, R. C., and Wright, A. H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Despite the success of galaxy-scale strong gravitational lens studies with Hubble-quality imaging, the number of well-studied strong lenses remains small. As a result, robust comparisons of the lens models to theoretical predictions are difficult. This motivates our application of automated Bayesian lens modeling methods to observations from public data releases of overlapping large ground-based imaging and spectroscopic surveys: Kilo-Degree Survey (KiDS) and Galaxy and Mass Assembly (GAMA), respectively. We use the open-source lens modeling software PyAutoLens to perform our analysis. We demonstrate the feasibility of strong lens modeling with large-survey data at lower resolution as a complementary avenue to studies that utilize more time-consuming and expensive observations of individual lenses at higher resolution. We discuss advantages and challenges, with special consideration given to determining background source redshifts from single-aperture spectra and to disentangling foreground lens and background source light. High uncertainties in the best-fit parameters for the models due to the limits of optical resolution in ground-based observatories and the small sample size can be improved with future study. We give broadly applicable recommendations for future efforts, and with proper application this approach could yield measurements in the quantities needed for robust statistical inference., Comment: 25 pages, 19 figures, accepted for publication in MNRAS following peer review
Published: 2023
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11. Search for subsolar-mass black hole binaries in the second part of Advanced LIGO's and Advanced Virgo's third observing run

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Alléné, C., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Arun, K. G., Asada, H., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badaracco, F., Badger, C., Bae, S., Bae, Y., Bagnasco, S., Bai, Y., Baier, J. G., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Barayoga, J. 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., Basak, S., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belahcene, I., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., BenYaala, M., Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Berry, C. P. L., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Bini, S., 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., Boër, M., Bogaert, G., Boldrini, M., Bolingbroke, G. N., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonnand, R., Booker, P., 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., Bucci, F., Buchanan, J., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callaghan, J. D., Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Caneva, G., Cannavacciuolo, M., Cannon, K. C., Cao, H., Cao, Z., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakalis, W., Subrahmanya, S. Chalathadka, Champion, E., Chan, C. -H., Chan, C., Chan, C. L., Chan, K., Chan, M., Chandra, K., Chang, I. P., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chatziioannou, K., Chen, C., Chen, D., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y. -B., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C-Y., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, Q., Chu, Y-K., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. A., Clarke, T. A., Clearwater, P., Clesse, S., Cleva, F., Coccia, E., Codazzo, E., Cohadon, P. -F., Cohen, D. E., Colleoni, M., Collette, C. G., Colombo, A., Colpi, M., Compton, C. M., Conti, L., Cooper, S. J., Corban, P., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Coschizza, A. C., Cotesta, R., Cottingham, 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., Craig, K., 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., Cuoco, E., Curyło, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Dálya, G., Dana, A., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darsow-Fromm, C., Dasgupta, A., Datrier, L. E. H., Datta, Sayantani, Dattilo, V., Dave, I., Davier, M., Davis, D., Davis, M. C., Daw, E. 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S., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Engelby, E., Enomoto, Y., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evans, T. M., Evstafyeva, T., Ewing, B. E., Fabrizi, F., Faedi, F., Fafone, V., Fair, H., Fairhurst, S., Fan, P. C., Farah, A. M., Farr, B., Farr, W. M., 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, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Floden, E., Fong, H. K., Font, J. A., Fornal, B., Forsyth, P. W. F., Franke, A., Frasca, S., Frasconi, F., Freed, J. P., Frei, Z., Freise, A., Freitas, O., Frey, R., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fujii, Y., Fujikawa, Y., Fujimoto, Y., Fulda, P., Fyffe, M., Gabbard, H. A., Gabella, W. E., Gadre, B. U., Gair, J. 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C., Jenner, K., Jeon, C., Jia, W., Jiang, J., Jin, H. -B., Johns, G. R., Johnston, R., Johny, N., Jones, A. W., Jones, D. I., Jones, P., Jones, R., Joshi, P., Ju, L., Jung, K., Jung, P., Junker, J., Juste, V., Kaihotsu, K., Kajita, T., Kakizaki, M., Kalaghatgi, C., Kalogera, V., Kamai, B., Kamiizumi, M., Kanda, N., 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., Kato, T., Katsanevas, S., Katsavounidis, E., Katzman, W., Kaur, T., Kawabe, K., Kawaguchi, K., Kéfélian, F., Keitel, D., Key, J. S., Khadka, S., Khalili, F. Y., Khan, S., Khanam, T., Khazanov, E. A., Khetan, N., Khursheed, M., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, J., Kim, K., Kim, P., Kim, W. S., Kim, Y. -M., Kimball, C., Kimura, N., King, B., Kinley-Hanlon, M., Kirchhoff, R., Kissel, J. S., Klimenko, S., Klinger, T., Knee, A. M., Knust, N., Kobayashi, Y., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Kondrashov, V., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kovalam, M., Koyama, N., Kozak, D. B., Kozakai, C., Kranzhoff, L., Kringel, V., Krishnendu, N. V., Królak, A., Kuehn, G., Kuijer, P., Kulkarni, S., Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuromiya, Y., Kuroyanagi, S., Kuwahara, S., Kwak, K., Lacaille, G., Lagabbe, P., Laghi, D., Lalande, E., Lalleman, M., Lamberts, A., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., LeBohec, S., Lecoeuche, Y. K., Lee, E., Lee, H. M., Lee, H. W., Lee, K., Lee, R., Legred, I. N., Lehmann, J., Lemaître, A., Lenti, M., Leonardi, M., Leonova, E., Leroy, N., Letendre, N., Levesque, C., Levin, Y., Leviton, J. N., Leyde, K., Li, A. K. Y., Li, B., Li, K. L., Li, P., Li, T. G. F., Li, X., Lin, C-Y., Lin, E. T., Lin, F-K., Lin, F-L., Lin, H. L., Lin, L. C. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, G. C., Liu, J., Liu, X., Llamas, F., Lo, R. K. L., Lo, T., 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., Lowry, M. J., Lucaccioni, J. F., Lück, H., Lumaca, D., Lundgren, A. P., Lung, Y., Luo, L. -W., Lussier, A. W., Lynam, J. E., Ma'arif, M., 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. N., Maksimovic, I., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B. R., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, 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., Masserot, A., Masso-Reid, M., Mastrogiovanni, S., Matas, A., Mateu-Lucena, M., Matiushechkina, M., Mavalvala, N., McCann, J. J., McCarthy, R., McClelland, D. E., McClincy, P. K., McCormick, S., McCuller, L., McGhee, G. I., McGinn, J., McGuire, S. C., McIsaac, C., McIver, J., McLeod, A., McRae, T., McWilliams, S. T., Meacher, D., Mehmet, M., Mehta, A. K., Meijer, Q., Melatos, A., Mendell, G., Menendez-Vazquez, A., Menoni, C. S., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Meyers, P. M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Mihaylov, D. P., Miller, A., Miller, A. L., Miller, B., Millhouse, M., Mills, J. 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Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We describe a search for gravitational waves from compact binaries with at least one component with mass 0.2 $M_\odot$ -- $1.0 M_\odot$ and mass ratio $q \geq 0.1$ in Advanced LIGO and Advanced Virgo data collected between 1 November 2019, 15:00 UTC and 27 March 2020, 17:00 UTC. No signals were detected. The most significant candidate has a false alarm rate of 0.2 $\mathrm{yr}^{-1}$. We estimate the sensitivity of our search over the entirety of Advanced LIGO's and Advanced Virgo's third observing run, and present the most stringent limits to date on the merger rate of binary black holes with at least one subsolar-mass component. We use the upper limits to constrain two fiducial scenarios that could produce subsolar-mass black holes: primordial black holes (PBH) and a model of dissipative dark matter. The PBH model uses recent prescriptions for the merger rate of PBH binaries that include a rate suppression factor to effectively account for PBH early binary disruptions. If the PBHs are monochromatically distributed, we can exclude a dark matter fraction in PBHs $f_\mathrm{PBH} \gtrsim 0.6$ (at 90% confidence) in the probed subsolar-mass range. However, if we allow for broad PBH mass distributions we are unable to rule out $f_\mathrm{PBH} = 1$. For the dissipative model, where the dark matter has chemistry that allows a small fraction to cool and collapse into black holes, we find an upper bound $f_{\mathrm{DBH}} < 10^{-5}$ on the fraction of atomic dark matter collapsed into black holes., Comment: https://dcc.ligo.org/P2200139
Published: 2022
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12. Model-based cross-correlation search for gravitational waves from the low-mass X-ray binary Scorpius X-1 in LIGO O3 data

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abbott, R., Abe, H., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Adya, V. B., Affeldt, C., Agarwal, D., Agathos, M., Aguiar, O. D., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Alléné, C., Allocca, A., Altin, P. A., Amato, A., Anand, S., Ananyeva, A., Anderson, S. B., Anderson, W. G., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Ansoldi, S., Antelis, J. M., Antier, S., Apostolatos, T., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Arène, M., Aritomi, N., Arnaud, N., Arogeti, M., Aronson, S. M., Asada, H., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Aubin, F., AultONeal, K., Babak, S., Badaracco, F., Badger, C., Bae, S., Bae, Y., Bagnasco, S., Bai, Y., Baier, J. G., Baird, J., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Baltus, G., Banagiri, S., Banerjee, B., Bankar, D., Barayoga, J. 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., Basak, S., Bassiri, R., Basti, A., Bawaj, M., Bayley, J. C., Bazzan, M., Bécsy, B., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belahcene, I., Bell, A. S., Benedetto, V., Beniwal, D., Benoit, W., Bentley, J. D., BenYaala, M., Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bhandare, R., Bhandari, A. V., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bianchi, A., Bilenko, I. A., Bilicki, M., Billingsley, G., Bini, S., 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. 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B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castaldi, G., Caudill, S., Cavaglià, M., Cavalier, F., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakalis, W., Subrahmanya, S. Chalathadka, Champion, E., Chan, C. -H., Chan, C., Chan, C. L., Chan, K., Chan, M., Chandra, K., Chang, I. P., Chang, W., Chanial, P., Chao, S., Chapman-Bird, C., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, C., Chen, D., Chen, H. Y., Chen, J., Chen, K., Chen, X., Chen, Y. -B., Chen, Y. -R., Chen, Y., Cheng, H., Chessa, P., Cheung, H. Y., Chia, H. Y., Chiadini, F., Chiang, C-Y., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Choudhary, R. K., Choudhary, S., Christensen, N., Chu, Q., Chu, Y-K., Chua, S. S. Y., Chung, K. W., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciobanu, A. A., Ciolfi, R., Clara, F., Clark, J. 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A., Thrane, E., Tiwari, Shubhanshu, Tiwari, Srishti, Tiwari, V., Toivonen, A. M., Tolley, A. E., Tomaru, T., Tomura, T., Tonelli, M., Torres-Forné, A., Torrie, C. I., Melo, I. Tosta e, Tournefier, E., Töyrä, D., Trapananti, A., Travasso, F., Traylor, G., Trenado, J., Trevor, M., Tringali, M. C., Tripathee, A., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsai, D., Tsang, K. W., Tsang, T., Tsao, J-S., Tse, M., Tso, R., Tsuchida, S., Tsukada, L., Tsuna, D., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Tuyenbayev, D., Ubach, H., Ubhi, A. S., Uchikata, N., Uchiyama, T., Udall, R. P., Ueda, A., Uehara, T., Ueno, K., Ueshima, G., Unnikrishnan, C. S., Urban, A. L., Ushiba, T., Utina, A., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valentini, M., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., Van de Walle, A., van Dongen, J., van Haevermaet, H., van Heijningen, J. V., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venneberg, J., Venugopalan, G., Verdier, P., Verkindt, D., Verma, P., Verma, Y., Vermeulen, S. M., Veske, D., Vetrano, F., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Villa-Ortega, V., Vinet, J. -Y., Virtuoso, A., Vitale, S., Vocca, H., von Reis, E. R. G., von Wrangel, J. S. A., Vorvick, C., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Walet, R. C., Walker, M., Wallace, G. S., Wallace, L., Wang, J., Wang, J. Z., Wang, W. H., Ward, R. L., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watada, K., Watarai, D., Watchi, J., Wayt, K. E., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Weller, C. M., Weller, R. A., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., White, D. D., Whiting, B. F., Whittle, C., Wilk, O. S., Wilken, D., Williams, C. E., Williams, D., Williams, M. J., Williamson, A. R., Willis, J. L., Willke, B., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wojtowicz, I. A., Wong, D., Wong, I. C. F., Wright, M., Wu, C., Wu, D. S., Wu, H., Wysocki, D. M., Xiao, L., Yadav, N., Yamada, T., Yamamoto, H., Yamamoto, K., Yamamoto, T., Yamashita, K., Yamazaki, R., Yang, F. W., Yang, K. Z., Yang, L., Yang, Y. -C., Yang, Y., Yang, Yang, Yap, M. J., Yeeles, D. W., Yeh, S. -W., Yelikar, A. B., Yokoyama, J., Yokozawa, T., Yoo, J., Yoshioka, T., Yu, Hang, Yu, Haocun, Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeidler, S., Zelenova, T., Zendri, J. -P., Zevin, M., Zhan, M., Zhang, H., Zhang, J., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, G., Zhao, Y., Zhao, Yue, Zheng, Y., Zhou, R., Zhu, X. J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., and Zweizig, J.
Subjects: Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We present the results of a model-based search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO detector data from the third observing run of Advanced LIGO, Advanced Virgo and KAGRA. This is a semicoherent search which uses details of the signal model to coherently combine data separated by less than a specified coherence time, which can be adjusted to balance sensitivity with computing cost. The search covered a range of gravitational-wave frequencies from 25Hz to 1600Hz, as well as ranges in orbital speed, frequency and phase determined from observational constraints. No significant detection candidates were found, and upper limits were set as a function of frequency. The most stringent limits, between 100Hz and 200Hz, correspond to an amplitude h0 of about 1e-25 when marginalized isotropically over the unknown inclination angle of the neutron star's rotation axis, or less than 4e-26 assuming the optimal orientation. The sensitivity of this search is now probing amplitudes predicted by models of torque balance equilibrium. For the usual conservative model assuming accretion at the surface of the neutron star, our isotropically-marginalized upper limits are close to the predicted amplitude from about 70Hz to 100Hz; the limits assuming the neutron star spin is aligned with the most likely orbital angular momentum are below the conservative torque balance predictions from 40Hz to 200Hz. Assuming a broader range of accretion models, our direct limits on gravitational-wave amplitude delve into the relevant parameter space over a wide range of frequencies, to 500Hz or more., Comment: 19 pages, Open Access Journal PDF
Published: 2022
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13. Galaxy and Mass Assembly (GAMA): Probing galaxy-group correlations in redshift space with the halo streaming model

Author: Hang, Qianjun, Peacock, John A., Alam, Shadab, Cai, Yan-Chuan, Kraljic, Katarina, van Daalen, Marcel, Bilicki, M., Holwerda, B. W., and Loveday, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We have studied the galaxy-group cross-correlations in redshift space for the Galaxy And Mass Assembly (GAMA) Survey. We use a set of mock GAMA galaxy and group catalogues to develop and test a novel 'halo streaming' model for redshift-space distortions. This treats 2-halo correlations via the streaming model, plus an empirical 1-halo term derived from the mocks, allowing accurate modelling into the nonlinear regime. In order to probe the robustness of the growth rate inferred from redshift-space distortions, we divide galaxies by colour, and divide groups according to their total stellar mass, calibrated to total mass via gravitational lensing. We fit our model to correlation data, to obtain estimates of the perturbation growth rate, $f\sigma_8$, validating parameter errors via the dispersion between different mock realizations. In both mocks and real data, we demonstrate that the results are closely consistent between different subsets of the group and galaxy populations, considering the use of correlation data down to some minimum projected radius, $r_{\rm min}$. For the mock data, we can use the halo streaming model to below $r_{\rm min} = 5h^{-1}$ Mpc, finding that all subsets yield growth rates within about 3% of each other, and consistent with the true value. For the actual GAMA data, the results are limited by cosmic variance: $f\sigma_8=0.29\pm 0.10$ at an effective redshift of 0.20; but there is every reason to expect that this method will yield precise constraints from larger datasets of the same type, such as the DESI bright galaxy survey., Comment: 17 pages, 12 figures. Matched to the accepted version
Published: 2022
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14. KiDS-1000: cosmic shear with enhanced redshift calibration

Author: Busch, J. L. van den, Wright, A. H., Hildebrandt, H., Bilicki, M., Asgari, M., Joudaki, S., Blake, C., Heymans, C., Kannawadi, A., Shan, H. Y., and Tröster, T.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a cosmic shear analysis with an improved redshift calibration for the fourth data release of the Kilo-Degree Survey (KiDS-1000) using self-organising maps (SOMs). Compared to the previous analysis of the KiDS-1000 data, we expand the redshift calibration sample to more than twice its size, now consisting of data of 17 spectroscopic redshift campaigns, and significantly extending the fraction of KiDS galaxies we are able to calibrate with our SOM redshift methodology. We then enhance the calibration sample with precision photometric redshifts from COSMOS2015 and the Physics of the Accelerated Universe Survey (PAUS), allowing us to fill gaps in the spectroscopic coverage of the KiDS data. Finally we perform a Complete Orthogonal Sets of E/B-Integrals (COSEBIs) cosmic shear analysis of the newly calibrated KiDS sample. We find $S_8 = 0.748_{-0.025}^{+0.021}$, which is in good agreement with previous KiDS studies and increases the tension with measurements of the cosmic microwave background to 3.4{\sigma}. We repeat the redshift calibration with different subsets of the full calibration sample and obtain, in all cases, agreement within at most 0.5{\sigma} in $S_8$ compared to our fiducial analysis. Including additional photometric redshifts allows us to calibrate an additional 6 % of the source galaxy sample. Even though further systematic testing with simulated data is necessary to quantify the impact of redshift outliers, precision photometric redshifts can be beneficial at high redshifts and to mitigate selection effects commonly found in spectroscopically selected calibration samples., Comment: 18 pages, 15 figures, 6 tables
Published: 2022
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15. Consistent lensing and clustering in a low-S8 Universe with BOSS, DES Year 3, HSC Year 1, and KiDS-1000

Author: Amon, A, Robertson, NC, Miyatake, H, Heymans, C, White, M, DeRose, J, Yuan, S, Wechsler, RH, Varga, TN, Bocquet, S, Dvornik, A, More, S, Ross, AJ, Hoekstra, H, Alarcon, A, Asgari, M, Blazek, J, Campos, A, Chen, R, Choi, A, Crocce, M, Diehl, HT, Doux, C, Eckert, K, Elvin-Poole, J, Everett, S, Ferté, A, Gatti, M, Giannini, G, Gruen, D, Gruendl, RA, Hartley, WG, Herner, K, Hildebrandt, H, Huang, S, Huff, EM, Joachimi, B, Lee, S, MacCrann, N, Myles, J, Navarro-Alsina, A, Nishimichi, T, Prat, J, Secco, LF, Sevilla-Noarbe, I, Sheldon, E, Shin, T, Tröster, T, Troxel, MA, Tutusaus, I, Wright, AH, Yin, B, Aguena, M, Allam, S, Annis, J, Bacon, D, Bilicki, M, Brooks, D, Burke, DL, Rosell, A Carnero, Carretero, J, Castander, FJ, Cawthon, R, Costanzi, M, da Costa, LN, Pereira, MES, de Jong, J, De Vicente, J, Desai, S, Dietrich, JP, Doel, P, Ferrero, I, Frieman, J, García-Bellido, J, Gerdes, DW, Gschwend, J, Gutierrez, G, Hinton, SR, Hollowood, DL, Honscheid, K, Huterer, D, Kannawadi, A, Kuehn, K, Kuropatkin, N, Lahav, O, Lima, M, Maia, MAG, Marshall, JL, Menanteau, F, Miquel, R, Mohr, JJ, Morgan, R, Muir, J, Paz-Chinchón, F, Pieres, A, Malagón, AA Plazas, Porredon, A, Rodriguez-Monroy, M, Roodman, A, and Sanchez, E
Subjects: Astronomical Sciences, Physical Sciences, gravitational lensing: weak, large-scale structure of Universe, cosmology: observations, Astronomical and Space Sciences, Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics, Space sciences
Abstract: We evaluate the consistency between lensing and clustering based on measurements from Baryon Oscillation Spectroscopic Survey combined with galaxy-galaxy lensing from Dark Energy Survey (DES) Year 3, Hyper Suprime-Cam Subaru Strategic Program (HSC) Year 1, and Kilo-Degree Survey (KiDS)-1000. We find good agreement between these lensing data sets. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck (S8 = 0.83), and a Lensing cosmology (S8 = 0.76). For a joint analysis limited to large scales, we find that both cosmologies provide an acceptable fit to the data. Full utilization of the higher signal-to-noise small-scale measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic inconsistency parameter for each redshift bin, A, that decouples the lensing and clustering. With a wide range of scales, we find different results for the consistency between the two cosmologies. Limiting the analysis to the bins for which the impact of the lens sample selection is expected to be minimal, for the Lensing cosmology, the measurements are consistent with A = 1; A = 0.91 ± 0.04 (A = 0.97 ± 0.06) using DES+KiDS (HSC). For the Planck case, we find a discrepancy: A = 0.79 ± 0.03 (A = 0.84 ± 0.05) using DES+KiDS (HSC). We demonstrate that a kinematic Sunyaev-Zeldovich-based estimate for baryonic effects alleviates some of the discrepancy in the Planck cosmology. This analysis demonstrates the statistical power of small-scale measurements; however, caution is still warranted given modelling uncertainties and foreground sample selection effects.
Published: 2022

16. Deep ASKAP EMU Survey of the GAMA23 field: Properties of radio sources

Author: Gürkan, Gülay, Prandoni, I., O'Brien, A., Raja, W., Marchetti, L., Vaccari, M., Driver, S., Taylor, E., Franzen, T., Brown, M. J. I., Shabala, S., Andernach, H., Hopkins, A. M., Norris, R. P., Leahy, D., Bilicki, M., Farajollahi, H., Galvin, T., Heald, G., Koribalski, B. S., An, T., and Warhurst, K.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present the Australian Square Kilometre Array Pathfinder (ASKAP) observations of the Galaxy and Mass Assembly (GAMA)-23h field. The survey was carried out at 887.5 MHz and covers a 83 square degree field. We imaged the calibrated visibility data, taken as part of the Evolutionary Mapping of Universe (EMU) Early Science Programme, using the latest version of the ASKAPSoft pipeline. The final mosaic has an angular resolution of 10 arcsec and a central rms noise of around 38 $\mu$Jy beam$^{-1}$. The derived radio source catalogue has 39812 entries above a peak flux density threshold of 5$\sigma$. We searched for the radio source host galaxy counterparts using the GAMA spectroscopic (with an i-band magnitude limit of 19.2 mag) and multi-wavelength catalogues that are available as part of the collaboration. We identified hosts with GAMA spectroscopic redshifts for 5934 radio sources. We describe the data reduction, imaging, and source identification process, and present the source counts. Thanks to the wide area covered by our survey, we obtain very robust counts down to 0.2 mJy. ASKAP's exceptional survey speed, providing efficient, sensitive and high resolution mapping of large regions of the sky in conjunction with the multi-wavelength data available for the GAMA23 field, allowed us to discover 63 giant radio galaxies. The data presented here demonstrate the excellent capabilities of ASKAP in the pre-SKA era., Comment: 18 pages, 15 figures, accepted by MNRAS
Published: 2022
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17. The LOFAR Two-metre Sky Survey -- V. Second data release

Author: Shimwell, T. W., Hardcastle, M. J., Tasse, C., Best, P. N., Röttgering, H. J. A., Williams, W. L., Botteon, A., Drabent, A., Mechev, A., Shulevski, A., van Weeren, R. J., Bester, L., Brüggen, M., Brunetti, G., Callingham, J. R., Chyży, K. T., Conway, J. E., Dijkema, T. J., Duncan, K., de Gasperin, F., Hale, C. L., Haverkorn, M., Hugo, B., Jackson, N., Mevius, M., Miley, G. K., Morabito, L. K., Morganti, R., Offringa, A., Oonk, J. B. R., Rafferty, D., Sabater, J., Smith, D. J. B., Schwarz, D. J., Smirnov, O., O'Sullivan, S. P., Vedantham, H., White, G. J., Albert, J. G., Alegre, L., Asabere, B., Bacon, D. J., Bonafede, A., Bonnassieux, E., Brienza, M., Bilicki, M., Bonato, M., Rivera, G. Calistro, Cassano, R., Cochrane, R., Croston, J. H., Cuciti, V., Dallacasa, D., Danezi, A., Dettmar, R. J., Di Gennaro, G., Edler, H. W., Enßlin, T. A., Emig, K. L., Franzen, T. M. O., García-Vergara, C., Grange, Y. G., Gürkan, G., Hajduk, M., Heald, G., Heesen, V., Hoang, D. N., Hoeft, M., Horellou, C., Iacobelli, M., Jamrozy, M., Jelić, V., Kondapally, R., Kukreti, P., Kunert-Bajraszewska, M., Magliocchetti, M., Mahatma, V., Małek, K., Mandal, S., Massaro, F., Meyer-Zhao, Z., Mingo, B., Mostert, R. I. J., Nair, D. G., Nakoneczny, S. J., Nikiel-Wroczyński, B., Orrú, E., Pajdosz-Śmierciak, U., Pasini, T., Prandoni, I., van Piggelen, H. E., Rajpurohit, K., Retana-Montenegro, E., Riseley, C. J., Rowlinson, A., Saxena, A., Schrijvers, C., Sweijen, F., Siewert, T. M., Timmerman, R., Vaccari, M., Vink, J., West, J. L., Wołowska, A., Zhang, X., and Zheng, J.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: In this data release from the LOFAR Two-metre Sky Survey (LoTSS) we present 120-168MHz images covering 27% of the northern sky. Our coverage is split into two regions centred at approximately 12h45m +44$^\circ$30' and 1h00m +28$^\circ$00' and spanning 4178 and 1457 square degrees respectively. The images were derived from 3,451hrs (7.6PB) of LOFAR High Band Antenna data which were corrected for the direction-independent instrumental properties as well as direction-dependent ionospheric distortions during extensive, but fully automated, data processing. A catalogue of 4,396,228 radio sources is derived from our total intensity (Stokes I) maps, where the majority of these have never been detected at radio wavelengths before. At 6" resolution, our full bandwidth Stokes I continuum maps with a central frequency of 144MHz have: a median rms sensitivity of 83$\mu$Jy/beam; a flux density scale accuracy of approximately 10%; an astrometric accuracy of 0.2"; and we estimate the point-source completeness to be 90% at a peak brightness of 0.8mJy/beam. By creating three 16MHz bandwidth images across the band we are able to measure the in-band spectral index of many sources, albeit with an error on the derived spectral index of +/-0.2 which is a consequence of our flux-density scale accuracy and small fractional bandwidth. Our circular polarisation (Stokes V) 20" resolution 120-168MHz continuum images have a median rms sensitivity of 95$\mu$Jy/beam, and we estimate a Stokes I to Stokes V leakage of 0.056%. Our linear polarisation (Stokes Q and Stokes U) image cubes consist of 480 x 97.6 kHz wide planes and have a median rms sensitivity per plane of 10.8mJy/beam at 4' and 2.2mJy/beam at 20"; we estimate the Stokes I to Stokes Q/U leakage to be approximately 0.2%. Here we characterise and publicly release our Stokes I, Q, U and V images in addition to the calibrated uv-data., Comment: 23 figures, 1 table and 29 pages. The catalogues, images and uv-data associated with this data release are publicly available via https://lofar-surveys.org/
Published: 2022
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18. Consistent lensing and clustering in a low-$S_8$ Universe with BOSS, DES Year 3, HSC Year 1 and KiDS-1000

Author: Amon, A., Robertson, N. C., Miyatake, H., Heymans, C., White, M., DeRose, J., Yuan, S., Wechsler, R. H., Varga, T. N., Bocquet, S., Dvornik, A., More, S., Ross, A. J., Hoekstra, H., Alarcon, A., Asgari, M., Blazek, J., Campos, A., Chen, R., Choi, A., Crocce, M., Diehl, H. T., Doux, C., Eckert, K., Elvin-Poole, J., Everett, S., Ferté, A., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Hartley, W. G., Herner, K., Hildebrandt, H., Huang, S., Huff, E. M., Joachimi, B., Lee, S., MacCrann, N., Myles, J., Alsina, A. Navarro, Nishimichi, T., Prat, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Trster, T., Troxel, M. A., Tutusaus, I., Wright, A. H., Yin, B., Aguena, M., Allam, S., Annis, J., Bacon, D., Bilicki, M., Brooks, D., Burke, D. L., Rosell, A. Carnero, Carretero, J., Castander, F. J., Cawthon, R., Costanzi, M., da Costa, L. N., Pereira, M. E. S., de Jong, J., De Vicente, J., Desai, S., Dietrich, J. P., Doel, P., Ferrero, I., Frieman, J., García-Bellido, J., Gerdes, D. W., Gschwend, J., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., Huterer, D., Kannawadi, A., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., Marshall, J. L., Menanteau, F., Miquel, R., Mohr, J. J., Morgan, R., Muir, J., Paz-Chinchon, F., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Rodriguez-Monroy, M., Roodman, A., Sanchez, E., Serrano, S., Shan, H., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., To, C., and Zhang, Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We evaluate the consistency between lensing and clustering probes of large-scale structure based on measurements of projected galaxy clustering from BOSS combined with overlapping galaxy-galaxy lensing from three surveys: DES Y3, HSC Y1, and KiDS-1000. An intra-lensing-survey study finds good agreement between these lensing data. We model the observations using the Dark Emulator and fit the data at two fixed cosmologies: Planck, with $S_8=0.83$, and a Lensing cosmology with $S_8=0.76$. For a joint analysis limited to scales with $R>5.25h^{-1}$Mpc, we find that both cosmologies provide an acceptable fit to the data. Full utilisation of the small-scale clustering and lensing measurements is hindered by uncertainty in the impact of baryon feedback and assembly bias, which we account for with a reasoned theoretical error budget. We incorporate a systematic scaling parameter for each redshift bin, $A$, that decouples the lensing and clustering to capture any inconsistency. When a wide range of scales ($0.15
Published: 2022
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19. Wavelength-resolved Reverberation Mapping of quasar CTSC30.10: Dissecting MgII and FeII emission regions

Author: Prince, Raj, Zajaček, Michal, Czerny, Bożena, Trzcionkowski, P., Bronikowski, M., Figaredo, C. S., Panda, S., Martinez-Aldama, M. L., Hryniewicz, K., Jaiswal, V. K., Śniegowska, M., Naddaf, M., Bilicki, M., Haas, M., Sarna, M. J., Karas, V., Olejak, A., Przyłuski, R., Rałowski, M., Udalski, A., Sefako, R. R., Genade, A., and Worters, H. L.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We present the results of the reverberation monitoring aimed at MgII broad line and FeII pseudocontinuum for the luminous quasar CTS C30.10 (z = 0.90052) with the Southern African Large Telescope covering the years 2012-2021. We aimed at disentangling the MgII and UV FeII variability and the first measurement of UV FeII time delay for a distant quasar. We used several methods for time-delay measurements and determined both FeII and MgII time delays as well as performed a wavelength-resolved time delay study for a combination of MgII and FeII in the 2700 - 2900 \AA restframe wavelength range. We obtain the time delay for MgII of $275.5^{+12.4}_{-19.5}$ days in the rest frame, while for FeII we have two possible solutions of $270.0^{+13.8}_{-25.3}$ days and $180.3^{+26.6}_{-30.0}$ in the rest frame. Combining this result with the old measurement of FeII UV time delay for NGC 5548 we discuss for the first time the radius-luminosity relation for UV FeII with the slope consistent with $0.5$ within uncertainties. Since FeII time delay has a shorter time-delay component but lines are narrower than MgII, we propose that the line delay measurement is biased towards the BLR part facing the observer, with the bulk of the Fe II emission may arise from the more distant BLR region, one that is shielded from the observer., Comment: 22 pages, 19 Figures, 6 Tables, Submitted to Astronomy and Astrophysics, Comments are welcome
Published: 2022
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20. Galaxy and Mass Assembly (GAMA): Mid-infrared properties as tracers of galaxy environment

Author: Sureshkumar, U., Durkalec, A., Pollo, A., Bilicki, M., Cluver, M. E., Bellstedt, S., Farrow, D. J., Loveday, J., Taylor, E. N., and Bland-Hawthorn, J.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We investigate how different mid-infrared (mid-IR) properties of galaxies trace the environment in which the galaxies are located. For this purpose, we first study the dependence of galaxy clustering on the absolute magnitude at 3.4 $\mu$m and redshift. Then, we look into the environmental dependence of mid-IR luminosities and the galaxy properties derived from these luminosities. We also explore how various infrared galaxy luminosity selections influence the galaxy clustering measurements. We use a set of W1 (3.4 $\mu$m) absolute magnitude ($M_\text{W1}$) selected samples from the Galaxy and Mass Assembly (GAMA) survey matched with mid-IR properties from the Wide-field Infrared Survey Explorer (WISE) in the redshift range $0.07 \leq z < 0.43$. We compute the galaxy two-point correlation function (2pCF) and compare the clustering lengths between subsamples binned in $M_\text{W1}$ and in redshift. We also measure the marked correlation functions (MCFs) using the luminosities in the WISE W1 to W4 (3.4 to 22 $\mu$m) bands as marks. Additionally, we compare the measurements of MCFs with different estimates of stellar mass and star formation rate used as marks. Finally, we check how different selections applied to the sample affect the clustering measurements. We show strong clustering dependence on the W1 absolute magnitude: galaxies brighter in the W1 band are more strongly clustered than their fainter counterparts. We also observe a lack of significant redshift dependence of clustering in the redshift range $0.07 \leq z < 0.43$. We show that although W1 and W2 bands are direct indicators of stellar mass, a galaxy sample selected based on W1 or W2 bands does not perfectly show the clustering behaviour of a stellar mass selected sample. Similar is the case with the proxy relation between W3 and W4 bands and star formation rate., Comment: 18 pages, 12 figures, matches the version published in A&A
Published: 2022
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21. KiDS & Euclid: Cosmological implications of a pseudo angular power spectrum analysis of KiDS-1000 cosmic shear tomography

Author: Loureiro, A., Whittaker, L., Mancini, A. Spurio, Joachimi, B., Cuceu, A., Asgari, M., Stölzner, B., Tröster, T., Wright, A. H., Bilicki, M., Dvornik, A., Giblin, B., Heymans, C., Hildebrandt, H., Shan, H., Amara, A., Auricchio, N., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Capobianco, V., Carbone, C., Carretero, J., Castellano, M., Cavuoti, S., Cimatti, A., Cledassou, R., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hormuth, F., Jahnke, K., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kuijken, K., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lloro, I., Mansutti, O., Marggraf, O., Markovic, K., Marulli, F., Massey, R., Meneghetti, M., Meylan, G., Moresco, M., Morin, B., Moscardini, L., Munari, E., Niemi, S. M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Pettorino, V., Pires, S., Poncet, M., Popa, L., Raison, F., Rhodes, J., Rix, H., Roncarelli, M., Saglia, R., Schneider, P., Secroun, A., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. L., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Valentijn, E. A., Wang, Y., Welikala, N., Weller, J., Zamorani, G., Zoubian, J., Andreon, S., Baldi, M., Camera, S., Farinelli, R., Polenta, G., and Tessore, N.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a tomographic weak lensing analysis of the Kilo Degree Survey Data Release 4 (KiDS-1000), using a new pseudo angular power spectrum estimator (pseudo-$C_{\ell}$) under development for the ESA Euclid mission. Over 21 million galaxies with shape information are divided into five tomographic redshift bins, ranging from 0.1 to 1.2 in photometric redshift. We measured pseudo-$C_{\ell}$ using eight bands in the multipole range $76<\ell<1500$ for auto- and cross-power spectra between the tomographic bins. A series of tests were carried out to check for systematic contamination from a variety of observational sources including stellar number density, variations in survey depth, and point spread function properties. While some marginal correlations with these systematic tracers were observed, there is no evidence of bias in the cosmological inference. B-mode power spectra are consistent with zero signal, with no significant residual contamination from E/B-mode leakage. We performed a Bayesian analysis of the pseudo-$C_{\ell}$ estimates by forward modelling the effects of the mask. Assuming a spatially flat $\Lambda$CDM cosmology, we constrained the structure growth parameter $S_8 = \sigma_8(\Omega_{\rm m}/0.3)^{1/2} = 0.754_{-0.029}^{+0.027}$. When combining cosmic shear from KiDS-1000 with baryon acoustic oscillation and redshift space distortion data from recent Sloan Digital Sky Survey (SDSS) measurements of luminous red galaxies, as well as the Lyman-$\alpha$ forest and its cross-correlation with quasars, we tightened these constraints to $S_8 = 0.771^{+0.006}_{-0.032}$. These results are in very good agreement with previous KiDS-1000 and SDSS analyses and confirm a $\sim 3\sigma$ tension with early-Universe constraints from cosmic microwave background experiments., Comment: 24 pages, 17 figures, Accepted by A&A
Published: 2021
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22. GLADE+: An Extended Galaxy Catalogue for Multimessenger Searches with Advanced Gravitational-wave Detectors

Author: Dálya, G., Díaz, R., Bouchet, F. R., Frei, Z., Jasche, J., Lavaux, G., Macas, R., Mukherjee, S., Pálfi, M., de Souza, R. S., Wandelt, B. D., Bilicki, M., and Raffai, P.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We present GLADE+, an extended version of the GLADE galaxy catalogue introduced in our previous paper for multimessenger searches with advanced gravitational-wave detectors. GLADE+ combines data from six separate but not independent astronomical catalogues: the GWGC, 2MPZ, 2MASS XSC, HyperLEDA, and WISExSCOSPZ galaxy catalogues, and the SDSS-DR16Q quasar catalogue. To allow corrections of CMB-frame redshifts for peculiar motions, we calculated peculiar velocities along with their standard deviations of all galaxies having $B$-band magnitude data within redshift $z=0.05$ using the "Bayesian Origin Reconstruction from Galaxies" formalism. GLADE+ is complete up to luminosity distance $d_L=47^{+4}_{-2}$ Mpc in terms of the total expected $B$-band luminosity of galaxies, and contains all of the brightest galaxies giving 90\% of the total $B$-band and $K$-band luminosity up to $d_L\simeq 130$ Mpc. We include estimations of stellar masses and individual binary neutron star merger rates for galaxies with $W1$ magnitudes. These parameters can help in ranking galaxies in a given gravitational wave localization volume in terms of their likelihood of being hosts, thereby possibly reducing the number of pointings and total integration time needed to find the electromagnetic counterpart., Comment: 9 pages, 4 figures, accepted for publication in MNRAS
Published: 2021
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23. Deep Extragalactic VIsible Legacy Survey (DEVILS): Consistent multi-wavelength photometry for the DEVILS regions (COSMOS, XMMLSS & ECDFS)

Author: Davies, L. J. M., Thorne, J. E., Robotham, A. S. G., Bellstedt, S., Driver, S. P., Adams, N. J., Bilicki, M., Bowler, R. A. A., Bravo, M., Cortese, L., Foster, C., Grootes, M. W., Häußler, B., Hashemizadeh, A., Holwerda, B. W., Hurley, P., Jarvis, M. J., Lidman, C., Maddox, N., Meyer, M., Paolillo, M., Phillipps, S., Radovich, M., Siudek, M., Vaccari, M., and Windhorst, R. A.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Deep Extragalactic VIsible Legacy Survey (DEVILS) is an ongoing high-completeness, deep spectroscopic survey of $\sim$60,000 galaxies to Y$<$21.2 mag, over $\sim$6 deg2 in three well-studied deep extragalactic fields: D10 (COSMOS), D02 (XMM-LSS) and D03 (ECDFS). Numerous DEVILS projects all require consistent, uniformly-derived and state-of-the-art photometric data with which to measure galaxy properties. Existing photometric catalogues in these regions either use varied photometric measurement techniques for different facilities/wavelengths leading to inconsistencies, older imaging data and/or rely on source detection and photometry techniques with known problems. Here we use the ProFound image analysis package and state-of-the-art imaging datasets (including Subaru-HSC, VST-VOICE, VISTA-VIDEO and UltraVISTA-DR4) to derive matched-source photometry in 22 bands from the FUV to 500{\mu}m. This photometry is found to be consistent, or better, in colour-analysis to previous approaches using fixed-size apertures (which are specifically tuned to derive colours), but produces superior total source photometry, essential for the derivation of stellar masses, star-formation rates, star-formation histories, etc. Our photometric catalogue is described in detail and, after internal DEVILS team projects, will be publicly released for use by the broader scientific community., Comment: 33 pages, 22 figures, Accepted to MNRAS
Published: 2021
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24. Galaxy and Mass Assembly (GAMA): Tracing galaxy environment using the marked correlation function

Author: Sureshkumar, U., Durkalec, A., Pollo, A., Bilicki, M., Loveday, J., Farrow, D. J., Holwerda, B. W., Hopkins, A. M., Liske, J., Pimbblet, K. A., Taylor, E. N., and Wright, A. H.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: We investigate how different galaxy properties - luminosities in u, g, r, J, K-bands, stellar mass, star formation rate and specific star formation rate trace the environment in the local universe. We also study the effect of survey flux limits on galaxy clustering measurements. We measure the two-point correlation function (2pCF) and marked correlation functions (MCFs) using the aforementioned properties as marks. We use nearly stellar-mass-complete galaxy sample in the redshift range 0.1 < z < 0.16 from the Galaxy And Mass Assembly (GAMA) survey with a flux limit of r < 19.8. Further, we impose a brighter flux limit of r < 17.8 to our sample and repeat the measurements to study how this affects galaxy clustering analysis. We compare our results to measurements from the Sloan Digital Sky Survey (SDSS) with flux limits of r < 17.8 and r < 16.8. We show that the stellar mass is the best tracer of galaxy environment, the K-band luminosity being a good substitute, although such a proxy sample misses close pairs of evolved, red galaxies. We also confirm that the u-band luminosity is a good, but not a perfect proxy of star formation rate in the context of galaxy clustering. We observe an effect of the survey flux limit on clustering studies - samples with a higher flux limit (smaller magnitude) miss some information about close pairs of starburst galaxies., Comment: 15 pages, 7 figures, matches the version published in A&A
Published: 2021
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25. Bright galaxy sample in the Kilo-Degree Survey Data Release 4: selection, photometric redshifts, and physical properties

Author: Bilicki, M., Dvornik, A., Hoekstra, H., Wright, A. H., Chisari, N. E., Vakili, M., Asgari, M., Giblin, B., Heymans, C., Hildebrandt, H., Holwerda, B. W., Hopkins, A., Johnston, H., Kannawadi, A., Kuijken, K., Nakoneczny, S. J., Shan, H. Y., Sonnenfeld, A., and Valentijn, E.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present a bright galaxy sample with accurate and precise photometric redshifts (photo-zs), selected using $ugriZYJHK_\mathrm{s}$ photometry from the Kilo-Degree Survey (KiDS) Data Release 4 (DR4). The highly pure and complete dataset is flux-limited at $r<20$ mag, covers $\sim1000$ deg$^2$, and contains about 1 million galaxies after artifact masking. We exploit the overlap with Galaxy And Mass Assembly (GAMA) spectroscopy as calibration to determine photo-zs with the supervised machine learning neural network algorithm implemented in the ANNz2 software. The photo-zs have mean error of $|\langle \delta z \rangle| \sim 5 \times 10^{-4}$ and low scatter (scaled mean absolute deviation of $\sim 0.018(1+z)$), both practically independent of the $r$-band magnitude and photo-z at $0.05 < z_\mathrm{phot} < 0.5$. Combined with the 9-band photometry, these allow us to estimate robust absolute magnitudes and stellar masses for the full sample. As a demonstration of the usefulness of these data we split the dataset into red and blue galaxies, use them as lenses and measure the weak gravitational lensing signal around them for five stellar mass bins. We fit a halo model to these high-precision measurements to constrain the stellar-mass--halo-mass relations for blue and red galaxies. We find that for high stellar mass ($M_\star>5\times 10^{11} M_\odot$), the red galaxies occupy dark matter halos that are much more massive than those occupied by blue galaxies with the same stellar mass. The data presented here are publicly released via the KiDS webpage at http://kids.strw.leidenuniv.nl/DR4/brightsample.php., Comment: Matches the published version. Data available at http://kids.strw.leidenuniv.nl/DR4/brightsample.php
Published: 2021
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26. Discovery of two Einstein crosses from massive post--blue nugget galaxies at z>1 in KiDS

Author: Napolitano, N. R., Li, R., Spiniello, C., Tortora, C., Sergeyev, A., D'Ago, G., Guo, X., Xie, L., Radovich, M., Roy, N., Koopmans, L. V. E., Kuijken, K., Bilicki, M., Erben, T., Getman, F., Heymans, C., Hildebrandt, H., Moya, C., Shan, H. Y., Vernardos, G., and Wright, A. H.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We report the discovery of two Einstein Crosses (ECs) in the footprint of the Kilo-Degree Survey (KiDS): KIDS J232940-340922 and KIDS J122456+005048. Using integral field spectroscopy from MUSE@VLT, we confirm their gravitational-lens nature. In both cases, the four spectra of the source clearly show a prominence of absorption features, hence revealing an evolved stellar population with little star formation. The lensing model of the two systems, assuming a singular isothermal ellipsoid (SIE) with external shear, shows that: 1) the two crosses, located at redshift $z=0.38$ and 0.24, have Einstein radius $R_{\rm E}=5.2$ kpc and 5.4 kpc, respectively; 2) their projected dark matter fractions inside the half effective radius are 0.60 and 0.56 (Chabrier IMF); 3) the sources are ultra-compact galaxies, $R_{\rm e}\sim0.9$ kpc (at redshift $z_{\rm s}=1.59$) and $R_{\rm e}\sim0.5$ kpc ($z_{\rm s}=1.10$), respectively. These results are unaffected by the underlying mass density assumption. Due to size, blue color and absorption-dominated spectra, corroborated by low specific star-formation rates derived from optical-NIR spectral energy distribution fitting, we argue that the two lensed sources in these ECs are blue nuggets migrating toward their quenching phase., Comment: Accepted for publication on APJL
Published: 2020
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27. Photometric selection and redshifts for quasars in the Kilo-Degree Survey Data Release 4

Author: Nakoneczny, S. J., Bilicki, M., Pollo, A., Asgari, M., Dvornik, A., Erben, T., Giblin, B., Heymans, C., Hildebrandt, H., Kannawadi, A., Kuijken, K., Napolitano, N. R., and Valentijn, E.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a catalog of quasars and corresponding redshifts in the Kilo-Degree Survey (KiDS) Data Release 4. We trained machine learning (ML) models, using optical ugri and near-infrared ZYJHK_s bands, on objects known from Sloan Digital Sky Survey (SDSS) spectroscopy. We define inference subsets from the 45 million objects of the KiDS photometric data limited to 9-band detections. We show that projections of the high-dimensional feature space can be successfully used to investigate the estimations. The model creation employs two test subsets: randomly selected and the faintest objects, which allows to fit the bias versus variance trade-off. We tested three ML models: random forest (RF), XGBoost (XGB), and artificial neural network (ANN). We find that XGB is the most robust model for classification, while ANN performs the best for combined classification and redshift. The inference results are tested using number counts, Gaia parallaxes, and other quasar catalogs. Based on these tests, we derived the minimum classification probability which provides the best purity versus completeness trade-off: p(QSO_cand) > 0.9 for r < 22 and p(QSO_cand) > 0.98 for 22 < r < 23.5. We find 158,000 quasar candidates in the safe inference subset (r < 22) and an additional 185,000 candidates in the reliable extrapolation regime (22 < r < 23.5). Test-data purity equals 97% and completeness is 94%; the latter drops by 3% in the extrapolation to data fainter by one magnitude than the training set. The photometric redshifts were modeled with Gaussian uncertainties. The redshift error (mean and scatter) equals 0.01 +/- 0.1 in the safe subset and -0.0004 +/- 0.2 in the extrapolation, in a redshift range of 0.14 < z < 3.63. Our success of the extrapolation challenges the way that models are optimized and applied at the faint data end. The catalog is ready for cosmology and active galactic nucleus (AGN) studies., Comment: We publicly release the catalog at kids.strw.leidenuniv.nl/DR4/quasarcatalog.php , and the code at github.com/snakoneczny/kids-quasars
Published: 2020
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28. Spectroscopic observations of the machine-learning selected anomaly catalogue from the AllWISE Sky Survey

Author: Solarz, A., Thomas, R., Montenegro-Montes, F. M., Gromadzki, M., Donoso, E., Koprowski, M., Wyrzykowski, L., Diaz, C. G., Sani, E., and Bilicki, M.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract: We present the results of a programme to search and identify the nature of unusual sources within the All-sky Wide-field Infrared Survey Explorer (WISE) that is based on a machine-learning algorithm for anomaly detection, namely one-class support vector machines (OCSVM). Designed to detect sources deviating from a training set composed of known classes, this algorithm was used to create a model for the expected data based on WISE objects with spectroscopic identifications in the Sloan Digital Sky Survey (SDSS). Subsequently, it marked as anomalous those sources whose WISE photometry was shown to be inconsistent with this model. We report the results from optical and near-infrared spectroscopy follow-up observations of a subset of 36 bright ($g_{AB}$<19.5) objects marked as 'anomalous' by the OCSVM code to verify its performance. Among the observed objects, we identified three main types of sources: i) low redshift (z~0.03-0.15) galaxies containing large amounts of hot dust (53%), including three Wolf-Rayet galaxies; ii) broad-line quasi-stellar objects (QSOs) (33%) including low-ionisation broad absorption line (LoBAL) quasars and a rare QSO with strong and narrow ultraviolet iron emission; iii) Galactic objects in dusty phases of their evolution (3%). The nature of four of these objects (11%) remains undetermined due to low signal-to-noise or featureless spectra. The current data show that the algorithm works well at detecting rare but not necessarily unknown objects among the brightest candidates. They mostly represent peculiar sub-types of otherwise well-known sources., Comment: 17 pages, 17 figures
Published: 2020
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29. KiDS-1000 catalogue: Redshift distributions and their calibration

Author: Hildebrandt, H., Busch, J. L. van den, Wright, A. H., Blake, C., Joachimi, B., Kuijken, K., Tröster, T., Asgari, M., Bilicki, M., de Jong, J. T. A., Dvornik, A., Erben, T., Getman, F., Giblin, B., Heymans, C., Kannawadi, A., Lin, C. -A., and Shan, H. -Y.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present redshift distribution estimates of galaxies selected from the fourth data release of the Kilo-Degree Survey over an area of $\sim1000$ deg$^2$ (KiDS-1000). These redshift distributions represent one of the crucial ingredients for weak gravitational lensing measurements with the KiDS-1000 data. The primary estimate is based on deep spectroscopic reference catalogues that are re-weighted with the help of a self-organising map (SOM) to closely resemble the KiDS-1000 sources, split into five tomographic redshift bins in the photometric redshift range $0.1
Published: 2020
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30. KiDS-1000 Methodology: Modelling and inference for joint weak gravitational lensing and spectroscopic galaxy clustering analysis

Author: Joachimi, B., Lin, C. -A., Asgari, M., Tröster, T., Heymans, C., Hildebrandt, H., Köhlinger, F., Sánchez, A. G., Wright, A. H., Bilicki, M., Blake, C., Busch, J. L. van den, Crocce, M., Dvornik, A., Erben, T., Getman, F., Giblin, B., Hoekstra, H., Kannawadi, A., Kuijken, K., Napolitano, N. R., Schneider, P., Scoccimarro, R., Sellentin, E., Shan, H. Y., von Wietersheim-Kramsta, M., and Zuntz, J.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present the methodology for a joint cosmological analysis of weak gravitational lensing from the fourth data release of the ESO Kilo-Degree Survey (KiDS-1000) and galaxy clustering from the partially overlapping BOSS and 2dFLenS surveys. Cross-correlations between galaxy positions and ellipticities have been incorporated into the analysis, necessitating a hybrid model of non-linear scales that blends perturbative and non-perturbative approaches, and an assessment of contributions by astrophysical effects. All weak lensing signals are measured consistently via Fourier-space statistics that are insensitive to the survey mask and display low levels of mode mixing. The calibration of photometric redshift distributions and multiplicative gravitational shear bias has been updated, and a more complete tally of residual calibration uncertainties is propagated into the likelihood. A dedicated suite of more than 20000 mocks is used to assess the performance of covariance models and to quantify the impact of survey geometry and spatial variations of survey depth on signals and their errors. The sampling distributions for the likelihood and the $\chi^2$ goodness-of-fit statistic have been validated, with proposed changes to the number of degrees of freedom. Standard weak lensing point estimates on $S_8=\sigma_8\,(\Omega_{\rm m}/0.3)^{1/2}$ derived from its marginal posterior are easily misinterpreted to be biased low, and an alternative estimator and associated credible interval have been proposed. Known systematic effects pertaining to weak lensing modelling and inference are shown to bias $S_8$ by no more than 0.1 standard deviations, with the caveat that no conclusive validation data exist for models of intrinsic galaxy alignments. Compared to the previous KiDS analyses, $S_8$ constraints are expected to improve by 20% for weak lensing alone and by 29% for the joint analysis. [abridged], Comment: 45 pages, 34 figures, 7 tables; minor changes to match version accepted by A&A. The KiDS-1000 data products are available for download at http://kids.strw.leidenuniv.nl/DR4/lensing.php. This data release includes open source software, the shear-photo-z catalogue, the cosmic shear and 3x2pt data vectors and covariances, and posteriors in the form of Multinest chains
Published: 2020
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31. The frequency of dust lanes in edge-on spiral galaxies identified by Galaxy Zoo in KiDS imaging of GAMA targets

Author: Holwerda, B. W., Kelvin, L., Baldry, I., Lintott, C., Alpaslan, M., Pimbblet, K. A., Liske, J., Kitching, T., Bamford, S., de Jong, J., Bilicki, M., Hopkins, A., Bridge, J., Steele, R., Jacques, A., Goswami, S., Kusmic, S., Roemer, W., Kruk, S., Popescu, C. C., Kuijken, K., Wang, L., and Wright, A.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Dust lanes bisect the plane of a typical edge-on spiral galaxy as a dark optical absorption feature. Their appearance is linked to the gravitational stability of spiral disks; the fraction of edge-on galaxies that displays a dust lane is a direct indicator of the typical vertical balance between gravity and turbulence; a balance struck between the energy input from star-formation and the gravitational pull into the plane of the disk. Based on morphological classifications by the Galaxy~Zoo project on the Kilo-Degree Survey (KiDS) imaging data in the Galaxy and Mass Assembly (GAMA) fields, we explore the relation of dust lanes to the galaxy characteristics, most of which were determined using the {\sc magphys} spectral energy distribution fitting tool: stellar mass, total and specific star-formation rates, and several parameters describing the cold dust component. We find that the fraction of dust lanes does depend on the stellar mass of the galaxy; they start to appear at $M^* \sim 10^9 M_\odot$. A dust lane also implies strongly a dust mass of at least $10^5 M_\odot$, but otherwise does not correlate with cold dust mass parameters of the {\sc magphys} spectral energy distribution analysis, nor is there a link with star-formation rate, specific or total. Dust lane identification does not depend on disk ellipticity (disk thickness) or Sersic profile but correlates with bulge morphology; a round bulge favors dust lane votes. The central component along the line of sight that produces the dust lane is not associated with either one of the components fit by {\sc magphys}, the cold diffuse component or the localized, heated component in HII regions, but a mix of these two., Comment: Accepted for publication in the Astronomical Journal
Published: 2019
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32. Effect of galaxy mergers on star formation rates

Author: Pearson, W. J., Wang, L., Alpaslan, M., Baldry, I., Bilicki, M., Brown, M. J. I., Grootes, M. W., Holwerda, B. W., Kitching, T. D., Kruk, S., and van der Tak, F. F. S.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Galaxy mergers and interactions are an integral part of our basic understanding of how galaxies grow and evolve over time. However, the effect that galaxy mergers have on star formation rates (SFR) is contested, with observations of galaxy mergers showing reduced, enhanced and highly enhanced star formation. We aim to determine the effect of galaxy mergers on the SFR of galaxies using statistically large samples of galaxies, totalling over 200\,000, over a large redshift range, 0.0 to 4.0. We train and use convolutional neural networks to create binary merger identifications (merger or non-merger) in the SDSS, KiDS and CANDELS imaging surveys. We then compare the galaxy main sequence subtracted SFR of the merging and non-merging galaxies to determine what effect, if any, a galaxy merger has on SFR. We find that the SFR of merging galaxies are not significantly different from the SFR of non-merging systems. The changes in the average SFR seen in the star forming population when a galaxy is merging are small, of the order of a factor of 1.2. However, the higher the SFR above the galaxy main sequence, the higher the fraction of galaxy mergers. Galaxy mergers have little effect on the SFR of the majority of merging galaxies compared to the non-merging galaxies. The typical change in SFR is less than 0.1~dex in either direction. Larger changes in SFR can be seen but are less common. The increase in merger fraction as the distance above the galaxy main sequence increases demonstrates that galaxy mergers can induce starbursts., Comment: 20 pages, 17 figures, 6 tables, 3 appendices, accepted for publication in A&A
Published: 2019
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33. ASKAP Commissioning Observations of the GAMA 23 Field

Author: Leahy, Denis A., Hopkins, A. M., Norris, R. P., Marvil, J., Collier, J. D., Taylor, E. N., Allison, J. R., Anderson, C., Bell, M., Bilicki, M., Bland-Hawthorn, J., Brough, S., Brown, M. J. I., Driver, S., Gurkan, G., Harvey-Smith, L., Heywood, I., Holwerda, B. W., Liske, J., Lopez-Sanchez, A. R., McConnell, D., Moffett, A., Owers, M. S., Pimbblet, K. A., Raja, W., Seymour, N., Voronkov, M. A., and Wang, L.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We have observed the G23 field of the Galaxy And Mass Assembly (GAMA) survey using the Australian Square Kilometre Array Pathfinder (ASKAP) in its commissioning phase, to validate the performance of the telescope and to characterize the detected galaxy populations. This observation covers $\sim$48 deg$^2$ with synthesized beam of 32.7$^{\prime\prime}$ by 17.8$^{\prime\prime}$ at 936 MHz, and $\sim$39 deg$^2$ with synthesized beam of 15.8$^{\prime\prime}$ by 12.0$^{\prime\prime}$ at 1320 MHz. At both frequencies, the r.m.s. (root-mean-square) noise is $\sim$0.1 mJy/beam. We combine these radio observations with the GAMA galaxy data, which includes spectroscopy of galaxies that are i-band selected with a magnitude limit of 19.2. Wide-field Infrared Survey Explorer (WISE) infrared (IR) photometry is used to determine which galaxies host an active galactic nucleus (AGN). In properties including source counts, mass distributions, and IR vs. radio luminosity relation, the ASKAP detected radio sources behave as expected. Radio galaxies have higher stellar mass and luminosity in IR, optical and UV than other galaxies. We apply optical and IR AGN diagnostics and find that they disagree for $\sim$30% of the galaxies in our sample. We suggest possible causes for the disagreement. Some cases can be explained by optical extinction of the AGN, but for more than half of the cases we do not find a clear explanation. Radio sources are more likely ($\sim$6%) to have an AGN than radio quiet galaxies ($\sim$1%), but the majority of AGN are not detected in radio at this sensitivity., Comment: 26 pages, 22 figures, 6 tables. Accepted for publication in Publications of the Astronomical Society of Australia
Published: 2019
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34. 4MOST Consortium Survey 8: Cosmology Redshift Survey (CRS)

Author: Richard, J., Kneib, J. -P., Blake, C., Raichoor, A., Comparat, J., Shanks, T., Sorce, J., Sahlén, M., Howlett, C., Tempel, E., McMahon, R., Bilicki, M., Roukema, B., Loveday, J., Pryer, D., Buchert, T., and Zhao, C.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The 4MOST Cosmology Redshift Survey (CRS) will perform stringent cosmological tests via spectroscopic clustering measurements that will complement the best lensing, cosmic microwave background and other surveys in the southern hemisphere. The combination of carefully selected samples of bright galaxies, luminous red galaxies, emission-line galaxies and quasars, totalling about 8 million objects over the redshift range $z = 0.15$ to $3.5$, will allow definitive tests of gravitational physics. Many key science questions will be addressed by combining CRS spectra of these targets with data from current or future facilities such as the Large Synoptic Survey Telescope, the Square Kilometre Array and the Euclid mission., Comment: Part of the 4MOST issue of The Messenger, published in preparation of the 4MOST Community Workshop, see http://www.eso.org/sci/meetings/2019/4MOST.html
Published: 2019
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35. 4MOST: Project overview and information for the First Call for Proposals

Author: de Jong, R. S., Agertz, O., Berbel, A. Agudo, Aird, J., Alexander, D. A., Amarsi, A., Anders, F., Andrae, R., Ansarinejad, B., Ansorge, W., Antilogus, P., Anwand-Heerwart, H., Arentsen, A., Arnadottir, A., Asplund, M., Auger, M., Azais, N., Baade, D., Baker, G., Baker, S., Balbinot, E., Baldry, I. K., Banerji, M., Barden, S., Barklem, P., Barthélémy-Mazot, E., Battistini, C., Bauer, S., Bell, C. P. M., Bellido-Tirado, O., Bellstedt, S., Belokurov, V., Bensby, T., Bergemann, M., Bestenlehner, J. M., Bielby, R., Bilicki, M., Blake, C., Bland-Hawthorn, J., Boeche, C., Boland, W., Boller, T., Bongard, S., Bongiorno, A., Bonifacio, P., Boudon, D., Brooks, D., Brown, M. J. I., Brown, R., Brüggen, M., Brynnel, J., Brzeski, J., Buchert, T., Buschkamp, P., Caffau, E., Caillier, P., Carrick, J., Casagrande, L., Case, S., Casey, A., Cesarini, I., Cescutti, G., Chapuis, D., Chiappini, C., Childress, M., Christlieb, N., Church, R., Cioni, M. -R. L., Cluver, M., Colless, M., Collett, T., Comparat, J., Cooper, A., Couch, W., Courbin, F., Croom, S., Croton, D., Daguisé, E., Dalton, G., Davies, L. J. M., Davis, T., de Laverny, P., Deason, A., Dionies, F., Disseau, K., Doel, P., Döscher, D., Driver, S. P., Dwelly, T., Eckert, D., Edge, A., Edvardsson, B., Youssoufi, D. El, Elhaddad, A., Enke, H., Erfanianfar, G., Farrell, T., Fechner, T., Feiz, C., Feltzing, S., Ferreras, I., Feuerstein, D., Feuillet, D., Finoguenov, A., Ford, D., Fotopoulou, S., Fouesneau, M., Frenk, C., Frey, S., Gaessler, W., Geier, S., Fusillo, N. Gentile, Gerhard, O., Giannantonio, T., Giannone, D., Gibson, B., Gillingham, P., González-Fernández, C., Gonzalez-Solares, E., Gottloeber, S., Gould, A., Grebel, E. K., Gueguen, A., Guiglion, G., Haehnelt, M., Hahn, T., Hansen, C. J., Hartman, H., Hauptner, K., Hawkins, K., Haynes, D., Haynes, R., Heiter, U., Helmi, A., Aguayo, C. Hernandez, Hewett, P., Hinton, S., Hobbs, D., Hoenig, S., Hofman, D., Hook, I., Hopgood, J., Hopkins, A., Hourihane, A., Howes, L., Howlett, C., Huet, T., Irwin, M., Iwert, O., Jablonka, P., Jahn, T., Jahnke, K., Jarno, A., Jin, S., Jofre, P., Johl, D., Jones, D., Jönsson, H., Jordan, C., Karovicova, I., Khalatyan, A., Kelz, A., Kennicutt, R., King, D., Kitaura, F., Klar, J., Klauser, U., Kneib, J., Koch, A., Koposov, S., Kordopatis, G., Korn, A., Kosmalski, J., Kotak, R., Kovalev, M., Kreckel, K., Kripak, Y., Krumpe, M., Kuijken, K., Kunder, A., Kushniruk, I., Lam, M. I, Lamer, G., Laurent, F., Lawrence, J., Lehmitz, M., Lemasle, B., Lewis, J., Li, B., Lidman, C., Lind, K., Liske, J., Lizon, J. -L., Loveday, J., Ludwig, H. -G., McDermid, R. M., Maguire, K., Mainieri, V., Mali, S., Mandel, H., Mandel, K., Mannering, L., Martell, S., Delgado, D. Martinez, Matijevic, G., McGregor, H., McMahon, R., McMillan, P., Mena, O., Merloni, A., Meyer, M. J., Michel, C., Micheva, G., Migniau, J. -E., Minchev, I., Monari, G., Muller, R., Murphy, D., Muthukrishna, D., Nandra, K., Navarro, R., Ness, M., Nichani, V., Nichol, R., Nicklas, H., Niederhofer, F., Norberg, P., Obreschkow, D., Oliver, S., Owers, M., Pai, N., Pankratow, S., Parkinson, D., Parry, I., Paschke, J., Paterson, R., Pecontal, A., Phillips, D., Pillepich, A., Pinard, L., Pirard, J., Piskunov, N., Plank, V., Plüschke, D., Pons, E., Popesso, P., Power, C., Pragt, J., Pramskiy, A., Pryer, D., Quattri, M., Queiroz, A. B. de Andrade, Quirrenbach, A., Rahurkar, S., Raichoor, A., Ramstedt, S., Rau, A., Recio-Blanco, A., Reiss, R., Renaud, F., Revaz, Y., Rhode, P., Richard, J., Richter, A. D., Rix, H. -W., Robotham, A. S. G., Roelfsema, R., Romaniello, M., Rosario, D., Rothmaier, F., Roukema, B., Ruchti, G., Rupprecht, G., Rybizki, J., Ryde, N., Saar, A., Sadler, E., Sahlén, M., Salvato, M., Sassolas, B., Saunders, W., Saviauk, A., Sbordone, L., Schmidt, T., Schnurr, O., Scholz, R. -D., Schwope, A., Seifert, W., Shanks, T., Sheinis, A., Sivov, T., Skúladóttir, Á., Smartt, S., Smedley, S., Smith, G., Smith, R., Sorce, J., Spitler, L., Starkenburg, E., Steinmetz, M., Stilz, I., Storm, J., Sullivan, M., Sutherland, W., Swann, E., Tamone, A., Taylor, E. N., Teillon, J., Tempel, E., ter Horst, R., Thi, W. -F., Tolstoy, E., Trager, S., Traven, G., Tremblay, P. -E., Tresse, L., Valentini, M., van de Weygaert, R., Ancker, M. van den, Veljanoski, J., Venkatesan, S., Wagner, L., Wagner, K., Walcher, C. J., Waller, L., Walton, N., Wang, L., Winkler, R., Wisotzki, L., Worley, C. C., Worseck, G., Xiang, M., Xu, W., Yong, D., Zhao, C., Zheng, J., Zscheyge, F., and Zucker, D.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We introduce the 4-metre Multi-Object Spectroscopic Telescope (4MOST), a new high-multiplex, wide-field spectroscopic survey facility under development for the four-metre-class Visible and Infrared Survey Telescope for Astronomy (VISTA) at Paranal. Its key specifications are: a large field of view (FoV) of 4.2 square degrees and a high multiplex capability, with 1624 fibres feeding two low-resolution spectrographs ($R = \lambda/\Delta\lambda \sim 6500$), and 812 fibres transferring light to the high-resolution spectrograph ($R \sim 20\,000$). After a description of the instrument and its expected performance, a short overview is given of its operational scheme and planned 4MOST Consortium science; these aspects are covered in more detail in other articles in this edition of The Messenger. Finally, the processes, schedules, and policies concerning the selection of ESO Community Surveys are presented, commencing with a singular opportunity to submit Letters of Intent for Public Surveys during the first five years of 4MOST operations., Comment: Part of the 4MOST issue of The Messenger, published in preparation of 4MOST Community Workshop, see http://www.eso.org/sci/meetings/2019/4MOST.html
Published: 2019
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36. The fourth data release of the Kilo-Degree Survey: ugri imaging and nine-band optical-IR photometry over 1000 square degrees

Author: Kuijken, K., Heymans, C., Dvornik, A., Hildebrandt, H., de Jong, J. T. A., Wright, A. H., Erben, T., Bilicki, M., Giblin, B., Shan, H. -Y., Getman, F., Grado, A., Hoekstra, H., Miller, L., Napolitano, N., Paolilo, M., Radovich, M., Schneider, P., Sutherland, W., Tewes, M., Tortora, C., Valentijn, E. A., and Kleijn, G. A. Verdoes
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: The Kilo-Degree Survey (KiDS) is an ongoing optical wide-field imaging survey with the OmegaCAM camera at the VLT Survey Telescope, specifically designed for measuring weak gravitational lensing by galaxies and large-scale structure. When completed it will consist of 1350 square degrees imaged in four filters (ugri). Here we present the fourth public data release which more than doubles the area of sky covered by data release 3. We also include aperture-matched ZYJHKs photometry from our partner VIKING survey on the VISTA telescope in the photometry catalogue. We illustrate the data quality and describe the catalogue content. Two dedicated pipelines are used for the production of the optical data. The Astro-WISE information system is used for the production of co-added images in the four survey bands, while a separate reduction of the r-band images using the theli pipeline is used to provide a source catalogue suitable for the core weak lensing science case. All data have been re-reduced for this data release using the latest versions of the pipelines. The VIKING photometry is obtained as forced photometry on the theli sources, using a re-reduction of the VIKING data that starts from the VISTA pawprints. Modifications to the pipelines with respect to earlier releases are described in detail. The photometry is calibrated to the Gaia DR2 G band using stellar locus regression. In this data release a total of 1006 square-degree survey tiles with stacked ugri images are made available, accompanied by weight maps, masks, and single-band source lists. We also provide a multi-band catalogue based on r-band detections, including homogenized photometry and photometric redshifts, for the whole dataset. Mean limiting magnitudes (5 sigma in a 2" aperture) are 24.23, 25.12, 25.02, 23.68 in ugri, respectively, and the mean r-band seeing is 0.70"., Comment: 25 pages, accepted for publication in Astronomy and Astrophysics. For access to the images and catalogues see http://kids.strw.leidenuniv.nl/DR4/
Published: 2019
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37. Radio-Infrared Correlation for Local Dusty Galaxies and Dusty AGNs from the AKARI All Sky Survey

Author: Solarz, A., Pollo, A., Bilicki, M., Pępiak, A., Takeuchi, T. T., and Piątek, P.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We use the new release of the AKARI Far-Infrared all sky Survey matched with the NVSS radio database to investigate the local ($z<0.25$) far infrared-radio correlation (FIRC) of different types of extragalactic sources. To obtain the redshift information for the AKARI FIS sources we crossmatch the catalogue with the SDSS DR8. This also allows us to use emission line properties to divide sources into four categories: i) star-forming galaxies (SFGs), ii) composite galaxies (displaying both star-formation and active nucleus components), iii) Seyfert galaxies, and iv) low-ionization nuclear emission-line region (LINER) galaxies. We find that the Seyfert galaxies have the lowest FIR/radio flux ratios and display excess radio emission when compared to the SFGs. We conclude that FIRC can be used to separate SFGs and AGNs only for the most radio-loud objects., Comment: 9 pages, accepted to PASJ
Published: 2019
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38. Clustering properties of TGSS radio sources

Author: Dolfi, A., Branchini, E., Bilicki, M., Balaguera-Antolínez, A., Prandoni, I., and Pandit, R.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We investigate the clustering properties of radio sources in the Alternative Data Release 1 of the TIFR GMRT Sky Survey (TGSS), focusing on large angular scales, where previous analyses have detected a large clustering signal. After appropriate data selection, the TGSS sample we use contains ~110,000 sources selected at 150 MHz over ~70% of the sky. The survey footprint is largely superimposed on that of the NRAO VLA Sky Survey (NVSS) with the majority of TGSS sources having a counterpart in the NVSS sample. These characteristics make TGSS suitable for large-scale clustering analyses and facilitate the comparison with the results of previous studies. In this analysis we focus on the angular power spectrum, although the angular correlation function is also computed to quantify the contribution of multiple-component radio sources. We find that on large angular scales, corresponding to multipoles $2 \leq \ell \leq 30$, the amplitude of the TGSS angular power spectrum is significantly larger than that of the NVSS. We do not identify any observational systematic effects that may explain this mismatch. We have produced a number of physically motivated models for the TGSS angular power spectrum and found that all of them fail to match observations, even when taking into account observational and theoretical uncertainties. The same models provide a good fit to the angular spectrum of the NVSS sources. These results confirm the anomalous nature of the TGSS large-scale power, which has no obvious physical origin and seems to indicate that unknown systematic errors are present in the TGSS dataset., Comment: updated to match the published version
Published: 2019
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39. All-sky angular power spectra from cleaned WISE$\times$SuperCOSMOS galaxy number counts

Author: Xavier, H. S., Costa-Duarte, M. V., Balaguera-Antolínez, A., and Bilicki, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Aiming to extract cosmological information from linear scales of the WISE$\times$SuperCOSMOS photometric redshift catalog, we perform a characterization of the systematic effects associated with stellar content, evidencing the presence of contamination and obscuration. We create an integrated model for these effects (which together we call `usurper contamination'), devise a method to remove both of them simultaneously and show its functionality by applying it to a set of mock catalogs. When administered to WISE$\times$SuperCOSMOS data, our method shows to improve the measurements of angular power spectra on scales $\ell\lesssim15$ and the extraction of cosmological parameters therefrom, even though a significant excess of power remains at these scales. When ignoring scales $\ell<15$, we still find strong indications of systematics, albeit these can be localized in the southern equatorial hemisphere. An independent analysis of the northern hemisphere at $\ell\geq 15$ agrees with a $\Lambda$CDM model with parameters from the Planck satellite and gives $\Omega_{\mathrm{c}}=0.254\pm0.020$ and $\Omega_{\mathrm{b}}<0.065$ at 95% confidence limit when combined with priors on $H_0$, $A_s$ and $n_s$., Comment: 33 pages, 20 figures, 5 tables. Accepted for publication in JCAP
Published: 2018
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40. LinKS: Discovering galaxy-scale strong lenses in the Kilo-Degree Survey using Convolutional Neural Networks

Author: Petrillo, C. E., Tortora, C., Vernardos, G., Koopmans, L. V. E., Kleijn, G. Verdoes, Bilicki, M., Napolitano, N. R., Chatterjee, S., Covone, G., Dvornik, A., Erben, T., Getman, F., Giblin, B., Heymans, C., de Jong, J. T. A., Kuijken, K., Schneider, P., Shan, H., Spiniello, C., and Wright, A. H.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We present a new sample of galaxy-scale strong gravitational-lens candidates, selected from 904 square degrees of Data Release 4 of the Kilo-Degree Survey (KiDS), i.e., the "Lenses in the Kilo-Degree Survey" (LinKS) sample. We apply two Convolutional Neural Networks (ConvNets) to $\sim88\,000$ colour-magnitude selected luminous red galaxies yielding a list of 3500 strong-lens candidates. This list is further down-selected via human inspection. The resulting LinKS sample is composed of 1983 rank-ordered targets classified as "potential lens candidates" by at least one inspector. Of these, a high-grade subsample of 89 targets is identified with potential strong lenses by all inspectors. Additionally, we present a collection of another 200 strong lens candidates discovered serendipitously from various previous ConvNet runs. A straightforward application of our procedure to future Euclid or LSST data can select a sample of $\sim3000$ lens candidates with less than 10 per cent expected false positives and requiring minimal human intervention., Comment: 19 pages, 11 figures, accepted for publication in MNRAS
Published: 2018
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41. Catalog of quasars from the Kilo-Degree Survey Data Release 3

Author: Nakoneczny, S., Bilicki, M., Solarz, A., Pollo, A., Maddox, N., Spiniello, C., Brescia, M., and Napolitano, N. R.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Computer Science - Machine Learning
Abstract: We present a catalog of quasars selected from broad-band photometric ugri data of the Kilo-Degree Survey Data Release 3 (KiDS DR3). The QSOs are identified by the random forest (RF) supervised machine learning model, trained on SDSS DR14 spectroscopic data. We first cleaned the input KiDS data from entries with excessively noisy, missing or otherwise problematic measurements. Applying a feature importance analysis, we then tune the algorithm and identify in the KiDS multiband catalog the 17 most useful features for the classification, namely magnitudes, colors, magnitude ratios, and the stellarity index. We used the t-SNE algorithm to map the multi-dimensional photometric data onto 2D planes and compare the coverage of the training and inference sets. We limited the inference set to r<22 to avoid extrapolation beyond the feature space covered by training, as the SDSS spectroscopic sample is considerably shallower than KiDS. This gives 3.4 million objects in the final inference sample, from which the random forest identified 190,000 quasar candidates. Accuracy of 97%, purity of 91%, and completeness of 87%, as derived from a test set extracted from SDSS and not used in the training, are confirmed by comparison with external spectroscopic and photometric QSO catalogs overlapping with the KiDS footprint. The robustness of our results is strengthened by number counts of the quasar candidates in the r band, as well as by their mid-infrared colors available from WISE. An analysis of parallaxes and proper motions of our QSO candidates found also in Gaia DR2 suggests that a probability cut of p(QSO)>0.8 is optimal for purity, whereas p(QSO)>0.7 is preferable for better completeness. Our study presents the first comprehensive quasar selection from deep high-quality KiDS data and will serve as the basis for versatile studies of the QSO population detected by this survey., Comment: Data available from the KiDS website at http://kids.strw.leidenuniv.nl/DR3/quasarcatalog.php and the source code from https://github.com/snakoneczny/kids-quasars
Published: 2018
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42. Deep Extragalactic VIsible Legacy Survey (DEVILS): Motivation, Design and Target Catalogue

Author: Davies, L. J. M., Robotham, A. S. G., Driver, S. P., Lagos, C. P., Cortese, L., Mannering, E., Foster, C., Lidman, C., Hashemizadeh, A., Koushan, S., O'Toole, S., Baldry, I. K., Bilicki, M., Bland-Hawthorn, J., Bremer, M. N., Brown, M. J. I., Bryant, J. J., Catinella, B., Croom, S. M., Grootes, M. W., Holwerda, B. W., Jarvis, M. J., Maddox, N., Meyer, M., Moffett, A. J., Phillipps, S., Taylor, E. N., Windhorst, R. A., and Wolf, C.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The Deep Extragalactic VIsible Legacy Survey (DEVILS) is a large spectroscopic campaign at the Anglo-Australian Telescope (AAT) aimed at bridging the near and distant Universe by producing the highest completeness survey of galaxies and groups at intermediate redshifts ($0.3
Published: 2018
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43. KiDS-SQuaD: The KiDS Strongly lensed Quasar Detection project

Author: Spiniello, C., Agnello, A., Napolitano, N. R., Sergeyev, A. V., Getman, F. I., Tortora, C., Spavone, M., Bilicki, M., Buddelmeijer, H., Koopmans, L. V. E., Kuijken, K., Vernardos, G., Bannikova, E., and Capaccioli, M.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: New methods have been recently developed to search for strong gravitational lenses, in particular lensed quasars, in wide-field imaging surveys. Here, we compare the performance of three different, morphology- and photometry- based methods to find lens candidates over the Kilo-Degree Survey (KiDS) DR3 footprint (440 deg$^2$). The three methods are: i) a multiplet detection in KiDS-DR3 and/or Gaia-DR1, ii) direct modeling of KiDS cutouts and iii) positional offsets between different surveys (KiDS-vs-Gaia, Gaia-vs-2MASS), with purpose-built astrometric recalibrations. The first benchmark for the methods has been set by the recovery of known lenses. We are able to recover seven out of ten known lenses and pairs of quasars observed in the KiDS DR3 footprint, or eight out of ten with improved selection criteria and looser colour pre-selection. This success rate reflects the combination of all methods together, which, taken individually, performed significantly worse (four lenses each). One movelty of our analysis is that the comparison of the performances of the different methods has revealed the pros and cons of the approaches and, most of all, the complementarities. We finally provide a list of high-grade candidates found by one or more methods, awaiting spectroscopic follow-up for confirmation. Of these, KiDS 1042+0023 is to our knowledge the first confirmed lensed quasar from KiDS, exhibiting two quasar spectra at the same source redshift at either sides of a red galaxy, with uniform flux-ratio $f\approx1.25$ over the wavelength range $0.45\mu\mathrm{m}<\lambda<0.75\mu\mathrm{m}.$, Comment: 12 pages, 4 figures, 4 tables, accepted for publication in MNRAS
Published: 2018
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44. Wide-area tomography of CMB lensing and the growth of cosmological density fluctuations

Author: Peacock, J. A. and Bilicki, M.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We describe a tomographic dissection of the Planck CMB lensing data, cross-correlating this map with galaxies in different ranges of photometric redshift. We use the nearly all-sky 2MPZ and WISExSCOS catalogues for z<0.35, extending to z<0.6 using SDSS. We describe checks for consistency between the different datasets, and perform a test for possible leakage of thermal Sunyaev--Zel'dovich signal into our cross-correlation measurements. The amplitude of the cross-correlation allows us to estimate the evolution of density fluctuations as a function of redshift, thus providing a test of theories of modified gravity. Assuming the common parametrisation for the logarithmic growth rate, f_g=Omega_m(z)^gamma, we infer gamma=0.77 +/- 0.18 when Omega_m is fixed using external data. Thus CMB lensing tomography is currently consistent with Einstein gravity, where gamma=0.55 is expected. We discuss how such constraints may be expected to improve with future data., Comment: Accepted for publication in MNRAS; small updates to text and references to match accepted version
Published: 2018
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45. The galaxy environment in GAMA G3C groups using the Kilo Degree Survey Data Release 3

Author: Costa-Duarte, M. V., Viola, M., Molino, A., Kuijken, K., Sodré Jr., L., Bilicki, M., Brouwer, M. M., Buddelmeijer, H., Getman, F., Grado, A., de Jong, J. T. A., Kleijn, G. V., Napolitano, N., Puddu, E., Radovich, M., and Vakili, M.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We aim to investigate the galaxy environment in GAMA Galaxy Groups Catalogue (G3C) using a volume-limited galaxy sample from the Kilo Degree Survey Data Release 3. The k-Nearest Neighbour technique is adapted to take into account the probability density functions (PDFs) of photometric redshifts in our calculations. This algorithm was tested on simulated KiDS tiles, showing its capability of recovering the relation between galaxy colour, luminosity and local environment. The characterization of the galaxy environment in G3C groups shows systematically steeper density contrasts for more massive groups. The red galaxy fraction gradients in these groups is evident for most of group mass bins. The density contrast of red galaxies is systematically higher at group centers when compared to blue galaxy ones. In addition, distinct group center definitions are used to show that our results are insensitive to center definitions. These results confirm the galaxy evolution scenario which environmental mechanisms are responsible for a slow quenching process as galaxies fall into groups and clusters, resulting in a smooth observed colour gradients in galaxy systems., Comment: 14 pages, Accepted to MNRAS
Published: 2017
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46. Search for unusual objects in the WISE Survey

Author: Solarz, A., Bilicki, M., and Pollo, A.
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Automatic source detection and classification tools based on machine learning (ML) algorithms are growing in popularity due to their efficiency when dealing with large amounts of data simultaneously and their ability to work in multidimensional parameter spaces. In this work, we present a new, automated method of outlier selection based on support vector machine (SVM) algorithm called one-class SVM (OCSVM), which uses the training data as one class to construct a model of 'normality' in order to recognize novel points. We test the performance of OCSVM algorithm on \textit{Wide-field Infrared Survey Explorer (WISE)} data trained on the Sloan Digital Sky Survey (SDSS) sources. Among others, we find $\sim 40,000$ sources with abnormal patterns which can be associated with obscured and unobscured active galactic nuclei (AGN) source candidates. We present the preliminary estimation of the clustering properties of these objects and find that the unobscured AGN candidates are preferentially found in less massive dark matter haloes ($M_{DMH}\sim10^{12.4}$) than the obscured candidates ($M_{DMH}\sim 10^{13.2}$). This result contradicts the unification theory of AGN sources and indicates that the obscured and unobscured phases of AGN activity take place in different evolutionary paths defined by different environments., Comment: 4 figures, 6 pages
Published: 2017

47. KiDS+2dFLenS+GAMA: Testing the cosmological model with the $E_{\rm G}$ statistic

Author: Amon, A., Blake, C., Heymans, C., Leonard, C. D., Asgari, M., Bilicki, M., Choi, A., Erben, T., Glazebrook, K., Harnois-Deraps, J., Hildebrandt, H., Hoekstra, H., Joachimi, B., Joudaki, S., Kuijken, K., Lidman, C., Loveday, J., Parkinson, D., Valentijn, E. A., and Wolf, C.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: We present a new measurement of $E_{\rm G}$, which combines measurements of weak gravitational lensing, real-space galaxy clustering and redshift space distortions. This statistic was proposed as a consistency test of General Relativity (GR) that is insensitive to linear, deterministic galaxy bias and the matter clustering amplitude. We combine deep imaging data from KiDS with overlapping spectroscopy from 2dFLenS, BOSS DR12 and GAMA and find $E_{\rm G}(\overline{z}=0.267)=0.43 \pm 0.13$ (GAMA), $E_{\rm G}(\overline{z}=0.305)=0.27 \pm 0.08$ (LOWZ+2dFLOZ) and $E_{\rm G}(\overline{z}=0.554)=0.26 \pm 0.07$ (CMASS+2dFHIZ). We demonstrate that the existing tension in the value of the matter density parameter hinders the robustness of this statistic as solely a test of GR. We find that our $E_{\rm G}$ measurements, as well as existing ones in the literature, favour a lower matter density cosmology than the Cosmic Microwave Background. For a flat $\Lambda$CDM Universe and assuming GR, we find $\Omega_{\rm m}(z=0)=0.25\pm0.03$. With this paper we publicly release the 2dFLenS dataset at: \url{http://2dflens.swin.edu.au}., Comment: 17 pages, 8 figures
Published: 2017
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48. Extracting cosmological information from the angular power spectrum of the 2MASS Photometric Redshift catalogue

Author: Balaguera-Antolínez, A., Bilicki, M., Branchini, E., and Postiglione, A.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract: Using the almost all-sky 2MASS Photometric Redshift catalogue (2MPZ) we perform for the first time a tomographic analysis of galaxy angular clustering in the local Universe ($z<0.24$). We estimate the angular auto- and cross-power spectra of 2MPZ galaxies in three photometric redshift bins, and use dedicated mock catalogues to assess their errors. We measure a subset of cosmological parameters, having fixed the others at their Planck values, namely the baryon fraction $f_{b}=0.14^{+0.09}_{-0.06}$, the total matter density parameter $\Omega_{\rm m}=0.30\pm 0.06$, and the effective linear bias of 2MPZ galaxies $b_{\rm eff}$, which grows from $1.1^{+0.3}_{-0.4}$ at $\langle z \rangle=0.05$ up to $2.1^{+0.3}_{-0.5}$ at $\langle z\rangle=0.2$, largely because of the flux-limited nature of the dataset. The results obtained here for the local Universe agree with those derived with the same methodology at higher redshifts, and confirm the importance of the tomographic technique for next-generation photometric surveys such as Euclid or LSST., Comment: Accepted for publication in MNRAS
Published: 2017
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49. Photometric redshifts for the Kilo-Degree Survey. Machine-learning analysis with artificial neural networks

Author: Bilicki, M., Hoekstra, H., Brown, M. J. I., Amaro, V., Blake, C., Cavuoti, S., de Jong, J. T. A., Georgiou, C., Hildebrandt, H., Wolf, C., Amon, A., Brescia, M., Brough, S., Costa-Duarte, M. V., Erben, T., Glazebrook, K., Grado, A., Heymans, C., Jarrett, T., Joudaki, S., Kuijken, K., Longo, G., Napolitano, N., Parkinson, D., Vellucci, C., Kleijn, G. A. Verdoes, and Wang, L.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: We present a machine-learning photometric redshift analysis of the Kilo-Degree Survey Data Release 3, using two neural-network based techniques: ANNz2 and MLPQNA. Despite limited coverage of spectroscopic training sets, these ML codes provide photo-zs of quality comparable to, if not better than, those from the BPZ code, at least up to zphot<0.9 and r<23.5. At the bright end of r<20, where very complete spectroscopic data overlapping with KiDS are available, the performance of the ML photo-zs clearly surpasses that of BPZ, currently the primary photo-z method for KiDS. Using the Galaxy And Mass Assembly (GAMA) spectroscopic survey as calibration, we furthermore study how photo-zs improve for bright sources when photometric parameters additional to magnitudes are included in the photo-z derivation, as well as when VIKING and WISE infrared bands are added. While the fiducial four-band ugri setup gives a photo-z bias $\delta z=-2e-4$ and scatter $\sigma_z<0.022$ at mean z = 0.23, combining magnitudes, colours, and galaxy sizes reduces the scatter by ~7% and the bias by an order of magnitude. Once the ugri and IR magnitudes are joined into 12-band photometry spanning up to 12 $\mu$, the scatter decreases by more than 10% over the fiducial case. Finally, using the 12 bands together with optical colours and linear sizes gives $\delta z<4e-5$ and $\sigma_z<0.019$. This paper also serves as a reference for two public photo-z catalogues accompanying KiDS DR3, both obtained using the ANNz2 code. The first one, of general purpose, includes all the 39 million KiDS sources with four-band ugri measurements in DR3. The second dataset, optimized for low-redshift studies such as galaxy-galaxy lensing, is limited to r<20, and provides photo-zs of much better quality than in the full-depth case thanks to incorporating optical magnitudes, colours, and sizes in the GAMA-calibrated photo-z derivation., Comment: A&A, in press. Data available from the KiDS website http://kids.strw.leidenuniv.nl/DR3/ml-photoz.php#annz2
Published: 2017
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50. The dipole anisotropy of WISE x SuperCOSMOS number counts

Author: Bengaly, C. A. P., Novaes, C. P., Xavier, H. S., Bilicki, M., Bernui, A., and Alcaniz, J. S.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, General Relativity and Quantum Cosmology
Abstract: We probe the isotropy of the Universe with the largest all-sky photometric redshift dataset currently available, namely WISE~$\times$~SuperCOSMOS. We search for dipole anisotropy of galaxy number counts in multiple redshift shells within the $0.10 < z < 0.35$ range, for two subsamples drawn from the same parent catalogue. Our results show that the dipole directions are in good agreement with most of the previous analyses in the literature, and in most redshift bins the dipole amplitudes are well consistent with $\Lambda$CDM-based mocks in the cleanest sample of this catalogue. In the $z<0.15$ range, however, we obtain a persistently large anisotropy in both subsamples of our dataset. Overall, we report no significant evidence against the isotropy assumption in this catalogue except for the lowest redshift ranges. The origin of the latter discrepancy is unclear, and improved data may be needed to explain it., Comment: 5 pages, 4 figures, 2 tables. Published in MNRAS
Published: 2017
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