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24 results on '"Collett, T. E."'

1. Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

Author

Pearce-Casey, R., Nagam, B. C., Wilde, J., Busillo, V., Ulivi, L., Andika, I. T., Manjón-García, A., Leuzzi, L., Matavulj, P., Serjeant, S., Walmsley, M., Barroso, J. A. Acevedo, O'Riordan, C. M., Clément, B., Tortora, C., Collett, T. E., Courbin, F., Gavazzi, R., Metcalf, R. B., Cabanac, R., Courtois, H. M., Crook-Mansour, J., Delchambre, L., Despali, G., Ecker, L. R., Franco, A., Holloway, P., Jahnke, K., Mahler, G., Marchetti, L., Melo, A., Meneghetti, M., Müller, O., Nucita, A. A., Pearson, J., Rojas, K., Scarlata, C., Schuldt, S., Sluse, D., Suyu, S. H., Vaccari, M., Vegetti, S., Verma, A., Vernardos, G., Bolzonella, M., Kluge, M., Saifollahi, T., Schirmer, M., Stone, C., Paulino-Afonso, A., Bazzanini, L., Hogg, N. B., Koopmans, L. V. E., Kruk, S., Mannucci, F., Bromley, J. M., Díaz-Sánchez, A., Dickinson, H. J., Powell, D. M., Bouy, H., Laureijs, R., Altieri, B., Amara, A., Andreon, S., Baccigalupi, C., Baldi, M., Balestra, A., Bardelli, S., Battaglia, P., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Faustini, F., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., George, K., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Nakajima, R., Neissner, C., Nichol, R. C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Burigana, C., Calabrese, M., Mora, A., Pöntinen, M., Scottez, V., Viel, M., and Margalef-Bentabol, B.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg^2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. Machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. We select all sources with VIS IE < 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just 11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artefacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected 10^5 lensing systems in Euclid, this implies 10^6 objects for human classification, which while very large is not in principle intractable and not without precedent., Comment: 22 pages, 11 figures, Euclid consortium paper, A&A submitted

Published
2024

2. Euclid: The Early Release Observations Lens Search Experiment

Author

Barroso, J. A. Acevedo, O'Riordan, C. M., Clément, B., Tortora, C., Collett, T. E., Courbin, F., Gavazzi, R., Metcalf, R. B., Busillo, V., Andika, I. T., Cabanac, R., Courtois, H. M., Crook-Mansour, J., Delchambre, L., Despali, G., Ecker, L. R., Franco, A., Holloway, P., Jackson, N., Jahnke, K., Mahler, G., Marchetti, L., Matavulj, P., Melo, A., Meneghetti, M., Moustakas, L. A., Müller, O., Nucita, A. A., Paulino-Afonso, A., Pearson, J., Rojas, K., Scarlata, C., Schuldt, S., Serjeant, S., Sluse, D., Suyu, S. H., Vaccari, M., Verma, A., Vernardos, G., Walmsley, M., Bouy, H., Walth, G. L., Powell, D. M., Bolzonella, M., Cuillandre, J. -C., Kluge, M., Saifollahi, T., Schirmer, M., Stone, C., Acebron, A., Bazzanini, L., Díaz-Sánchez, A., Hogg, N. B., Koopmans, L. V. E., Kruk, S., Leuzzi, L., Manjón-García, A., Mannucci, F., Nagam, B. C., Pearce-Casey, R., Scharré, L., Wilde, J., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Battaglia, P., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Caillat, A., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Cropper, M., Da Silva, A., Degaudenzi, H., De Lucia, G., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., George, K., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jhabvala, M., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kunz, M., Kurki-Suonio, H., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Mainetti, G., Maiorano, E., Mansutti, O., Marcin, S., Marggraf, O., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Medinaceli, E., Melchior, M., Mellier, Y., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Neissner, C., Nichol, R. C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sánchez, A. G., Sapone, D., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Steinwagner, J., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Weller, J., Zucca, E., Burigana, C., Scottez, V., and Viel, M.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We investigate the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we perform a systematic visual inspection of the $0.7\,\rm{deg}^2$ Euclid ERO data towards the Perseus cluster using both the high-resolution VIS $I_{\scriptscriptstyle\rm E}$ band, and the lower resolution NISP bands. We inspect every extended source brighter than magnitude $23$ in $I_{\scriptscriptstyle\rm E}$ with $41$ expert human classifiers. This amounts to $12\,086$ stamps of $10^{\prime\prime}\,\times\,10^{\prime\prime}$. We find $3$ grade A and $13$ grade B candidates. We assess the validity of these $16$ candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full $14\,000\,{\rm deg}^2$ of the Euclid Wide Survey should contain $100\,000^{+70\,000}_{-30\,000}$ galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of $170\,000$ discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range $0.\!\!^{\prime\prime}68\,<\,\theta_\mathrm{E}\,<1.\!\!^{\prime\prime}24$, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small Einstein radius systems. Whilst it is implausible to visually inspect the full Euclid data set, our results corroborate the promise that Euclid will ultimately deliver a sample of around $10^5$ galaxy-scale lenses., Comment: 21 pages, 20 figures, submitted to A&A

Published
2024

3. Euclid. I. Overview of the Euclid mission

Author

Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. S., Casas, R., Casas, S., Casenove, P., Casey, C. M., Cassata, P., Castander, F. J., Castelao, D., Castellano, M., Castiblanco, L., Castignani, G., Castro, T., Cavet, C., Cavuoti, S., Chabaud, P. -Y., Chambers, K. C., Charles, Y., Charlot, S., Chartab, N., Chary, R., Chaumeil, F., Cho, H., Chon, G., Ciancetta, E., Ciliegi, P., Cimatti, A., Cimino, M., Cioni, M. -R. L., Claydon, R., Cleland, C., Clément, B., Clements, D. L., Clerc, N., Clesse, S., Codis, S., Cogato, F., Colbert, J., Cole, R. E., Coles, P., Collett, T. E., Collins, R. S., Colodro-Conde, C., Colombo, C., Combes, F., Conforti, V., Congedo, G., Conseil, S., Conselice, C. J., Contarini, S., Contini, T., Conversi, L., Cooray, A. R., Copin, Y., Corasaniti, P. -S., Corcho-Caballero, P., Corcione, L., Cordes, O., Corpace, O., Correnti, M., Costanzi, M., Costille, A., Courbin, F., Mifsud, L. Courcoult, Courtois, H. M., Cousinou, M. -C., Covone, G., Cowell, T., Cragg, C., Cresci, G., Cristiani, S., Crocce, M., Cropper, M., Crouzet, P. E, Csizi, B., Cuby, J. -G., Cucchetti, E., Cucciati, O., Cuillandre, J. -C., Cunha, P. A. C., Cuozzo, V., Daddi, E., D'Addona, M., Dafonte, C., Dagoneau, N., Dalessandro, E., Dalton, G. B., D'Amico, G., Dannerbauer, H., Danto, P., Das, I., Da Silva, A., da Silva, R., Doumerg, W. d'Assignies, Daste, G., Davies, J. E., Davini, S., Dayal, P., de Boer, T., Decarli, R., De Caro, B., Degaudenzi, H., Degni, G., de Jong, J. T. A., de la Bella, L. F., de la Torre, S., Delhaise, F., Delley, D., Delucchi, G., De Lucia, G., Denniston, J., De Paolis, F., De Petris, M., Derosa, A., Desai, S., Desjacques, V., Despali, G., Desprez, G., De Vicente-Albendea, J., Deville, Y., Dias, J. D. F., Díaz-Sánchez, A., Diaz, J. J., Di Domizio, S., Diego, J. M., Di Ferdinando, D., Di Giorgio, A. M., Dimauro, P., Dinis, J., Dolag, K., Dolding, C., Dole, H., Sánchez, H. Domínguez, Doré, O., Dournac, F., Douspis, M., Dreihahn, H., Droge, B., Dryer, B., Dubath, F., Duc, P. -A., Ducret, F., Duffy, C., Dufresne, F., Duncan, C. A. J., Dupac, X., Duret, V., Durrer, R., Durret, F., Dusini, S., Ealet, A., Eggemeier, A., Eisenhardt, P. R. M., Elbaz, D., Elkhashab, M. Y., Ellien, A., Endicott, J., Enia, A., Erben, T., Vigo, J. A. Escartin, Escoffier, S., Sanz, I. Escudero, Essert, J., Ettori, S., Ezziati, M., Fabbian, G., Fabricius, M., Fang, Y., Farina, A., Farina, M., Farinelli, R., Farrens, S., Faustini, F., Feltre, A., Ferguson, A. M. N., Ferrando, P., Ferrari, A. G., Ferré-Mateu, A., Ferreira, P. G., Ferreras, I., Ferrero, I., Ferriol, S., Ferruit, P., Filleul, D., Finelli, F., Finkelstein, S. L., Finoguenov, A., Fiorini, B., Flentge, F., Focardi, P., Fonseca, J., Fontana, A., Fontanot, F., Fornari, F., Fosalba, P., Fossati, M., Fotopoulou, S., Fouchez, D., Fourmanoit, N., Frailis, M., Fraix-Burnet, D., Franceschi, E., Franco, A., Franzetti, P., Freihoefer, J., Frenk, C. . S., Frittoli, G., Frugier, P. -A., Frusciante, N., Fumagalli, A., Fumagalli, M., Fumana, M., Fu, Y., Gabarra, L., Galeotta, S., Galluccio, L., Ganga, K., Gao, H., García-Bellido, J., Garcia, K., Gardner, J. P., Garilli, B., Gaspar-Venancio, L. -M., Gasparetto, T., Gautard, V., Gavazzi, R., Gaztanaga, E., Genolet, L., Santos, R. Genova, Gentile, F., George, K., Gerbino, M., Ghaffari, Z., Giacomini, F., Gianotti, F., Gibb, G. P. S., Gillard, W., Gillis, B., Ginolfi, M., Giocoli, C., Girardi, M., Giri, S. K., Goh, L. W. K., Gómez-Alvarez, P., Gonzalez-Perez, V., Gonzalez, A. H., Gonzalez, E. J., Gonzalez, J. C., Beauchamps, S. Gouyou, Gozaliasl, G., Gracia-Carpio, J., Grandis, S., Granett, B. R., Granvik, M., Grazian, A., Gregorio, A., Grenet, C., Grillo, C., Grupp, F., Gruppioni, C., Gruppuso, A., Guerbuez, C., Guerrini, S., Guidi, M., Guillard, P., Gutierrez, C. M., Guttridge, P., Guzzo, L., Gwyn, S., Haapala, J., Haase, J., Haddow, C. R., Hailey, M., Hall, A., Hall, D., Hamaus, N., Haridasu, B. S., Harnois-Déraps, J., Harper, C., Hartley, W. G., Hasinger, G., Hassani, F., Hatch, N. A., Haugan, S. V. H., Häußler, B., Heavens, A., Heisenberg, L., Helmi, A., Helou, G., Hemmati, S., Henares, K., Herent, O., Hernández-Monteagudo, C., Heuberger, T., Hewett, P. C., Heydenreich, S., Hildebrandt, H., Hirschmann, M., Hjorth, J., Hoar, J., Hoekstra, H., Holland, A. D., Holliman, M. S., Holmes, W., Hook, I., Horeau, B., Hormuth, F., Hornstrup, A., Hosseini, S., Hu, D., Hudelot, P., Hudson, M. J., Huertas-Company, M., Huff, E. M., Hughes, A. C. N., Humphrey, A., Hunt, L. K., Huynh, D. D., Ibata, R., Ichikawa, K., Iglesias-Groth, S., Ilbert, O., Ilić, S., Ingoglia, L., Iodice, E., Israel, H., Israelsson, U. E., Izzo, L., Jablonka, P., Jackson, N., Jacobson, J., Jafariyazani, M., Jahnke, K., Jain, B., Jansen, H., Jarvis, M. J., Jasche, J., Jauzac, M., Jeffrey, N., Jhabvala, M., Jimenez-Teja, Y., Muñoz, A. Jimenez, Joachimi, B., Johansson, P. H., Joudaki, S., Jullo, E., Kajava, J. J. E., Kang, Y., Kannawadi, A., Kansal, V., Karagiannis, D., Kärcher, M., Kashlinsky, A., Kazandjian, M. V., Keck, F., Keihänen, E., Kerins, E., Kermiche, S., Khalil, A., Kiessling, A., Kiiveri, K., Kilbinger, M., Kim, J., King, R., Kirkpatrick, C. C., Kitching, T., Kluge, M., Knabenhans, M., Knapen, J. H., Knebe, A., Kneib, J. -P., Kohley, R., Koopmans, L. V. E., Koskinen, H., Koulouridis, E., Kou, R., Kovács, A., Kovačić, I., Kowalczyk, A., Koyama, K., Kraljic, K., Krause, O., Kruk, S., Kubik, B., Kuchner, U., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lacasa, F., Lacey, C. G., La Franca, F., Lagarde, N., Lahav, O., Laigle, C., La Marca, A., La Marle, O., Lamine, B., Lam, M. C., Lançon, A., Landt, H., Langer, M., Lapi, A., Larcheveque, C., Larsen, S. S., Lattanzi, M., Laudisio, F., Laugier, D., Laureijs, R., Laurent, V., Lavaux, G., Lawrenson, A., Lazanu, A., Lazeyras, T., Boulc'h, Q. Le, Brun, A. M. C. Le, Brun, V. Le, Leclercq, F., Lee, S., Graet, J. Le, Legrand, L., Leirvik, K. N., Jeune, M. Le, Lembo, M., Mignant, D. Le, Lepinzan, M. D., Lepori, F., Reun, A. Le, Leroy, G., Lesci, G. F., Lesgourgues, J., Leuzzi, L., Levi, M. E., Liaudat, T. I., Libet, G., Liebing, P., Ligori, S., Lilje, P. B., Lin, C. -C., Linde, D., Linder, E., Lindholm, V., Linke, L., Li, S. -S., Liu, S. J., Lloro, I., Lobo, F. S. N., Lodieu, N., Lombardi, M., Lombriser, L., Lonare, P., Longo, G., López-Caniego, M., Lopez, X. Lopez, Alvarez, J. Lorenzo, Loureiro, A., Loveday, J., Lusso, E., Macias-Perez, J., Maciaszek, T., Maggio, G., Magliocchetti, M., Magnard, F., Magnier, E. A., Magro, A., Mahler, G., Mainetti, G., Maino, D., Maiorano, E., Malavasi, N., Mamon, G. A., Mancini, C., Mandelbaum, R., Manera, M., Manjón-García, A., Mannucci, F., Mansutti, O., Outeiro, M. Manteiga, Maoli, R., Maraston, C., Marcin, S., Marcos-Arenal, P., Margalef-Bentabol, B., Marggraf, O., Marinucci, D., Marinucci, M., Markovic, K., Marleau, F. R., Marpaud, J., Martignac, J., Martín-Fleitas, J., Martin-Moruno, P., Martin, E. L., Martinelli, M., Martinet, N., Martin, H., Martins, C. J. A. P., Marulli, F., Massari, D., Massey, R., Masters, D. C., Matarrese, S., Matsuoka, Y., Matthew, S., Maughan, B. J., Mauri, N., Maurin, L., Maurogordato, S., McCarthy, K., McConnachie, A. W., McCracken, H. J., McDonald, I., McEwen, J. D., McPartland, C. J. R., Medinaceli, E., Mehta, V., Mei, S., Melchior, M., Melin, J. -B., Ménard, B., Mendes, J., Mendez-Abreu, J., Meneghetti, M., Mercurio, A., Merlin, E., Metcalf, R. B., Meylan, G., Migliaccio, M., Mignoli, M., Miller, L., Miluzio, M., Milvang-Jensen, B., Mimoso, J. P., Miquel, R., Miyatake, H., Mobasher, B., Mohr, J. J., Monaco, P., Monguió, M., Montoro, A., Mora, A., Dizgah, A. Moradinezhad, Moresco, M., Moretti, C., Morgante, G., Morisset, N., Moriya, T. J., Morris, P. W., Mortlock, D. J., Moscardini, L., Mota, D. F., Mottet, S., Moustakas, L. A., Moutard, T., Müller, T., Munari, E., Murphree, G., Murray, C., Murray, N., Musi, P., Nadathur, S., Nagam, B. C., Nagao, T., Naidoo, K., Nakajima, R., Nally, C., Natoli, P., Navarro-Alsina, A., Girones, D. Navarro, Neissner, C., Nersesian, A., Nesseris, S., Nguyen-Kim, H. N., Nicastro, L., Nichol, R. C., Nielbock, M., Niemi, S. -M., Nieto, S., Nilsson, K., Noller, J., Norberg, P., Nouri-Zonoz, A., Ntelis, P., Nucita, A. A., Nugent, P., Nunes, N. J., Nutma, T., Ocampo, I., Odier, J., Oesch, P. A., Oguri, M., Oliveira, D. Magalhaes, Onoue, M., Oosterbroek, T., Oppizzi, F., Ordenovic, C., Osato, K., Pacaud, F., Pace, F., Padilla, C., Paech, K., Pagano, L., Page, M. J., Palazzi, E., Paltani, S., Pamuk, S., Pandolfi, S., Paoletti, D., Paolillo, M., Papaderos, P., Pardede, K., Parimbelli, G., Parmar, A., Partmann, C., Pasian, F., Passalacqua, F., Paterson, K., Patrizii, L., Pattison, C., Paulino-Afonso, A., Paviot, R., Peacock, J. A., Pearce, F. R., Pedersen, K., Peel, A., Peletier, R. F., Ibanez, M. Pellejero, Pello, R., Penny, M. T., Percival, W. J., Perez-Garrido, A., Perotto, L., Pettorino, V., Pezzotta, A., Pezzuto, S., Philippon, A., Pierre, M., Piersanti, O., Pietroni, M., Piga, L., Pilo, L., Pires, S., Pisani, A., Pizzella, A., Pizzuti, L., Plana, C., Polenta, G., Pollack, J. E., Poncet, M., Pöntinen, M., Pool, P., Popa, L. A., Popa, V., Popp, J., Porciani, C., Porth, L., Potter, D., Poulain, M., Pourtsidou, A., Pozzetti, L., Prandoni, I., Pratt, G. W., Prezelus, S., Prieto, E., Pugno, A., Quai, S., Quilley, L., Racca, G. D., Raccanelli, A., Rácz, G., Radinović, S., Radovich, M., Ragagnin, A., Ragnit, U., Raison, F., Ramos-Chernenko, N., Ranc, C., Rasera, Y., Raylet, N., Rebolo, R., Refregier, A., Reimberg, P., Reiprich, T. H., Renk, F., Renzi, A., Retre, J., Revaz, Y., Reylé, C., Reynolds, L., Rhodes, J., Ricci, F., Ricci, M., Riccio, G., Ricken, S. O., Rissanen, S., Risso, I., Rix, H. -W., Robin, A. C., Rocca-Volmerange, B., Rocci, P. -F., Rodenhuis, M., Rodighiero, G., Monroy, M. Rodriguez, Rollins, R. P., Romanello, M., Roman, J., Romelli, E., Romero-Gomez, M., Roncarelli, M., Rosati, P., Rosset, C., Rossetti, E., Roster, W., Rottgering, H. J. A., Rozas-Fernández, A., Ruane, K., Rubino-Martin, J. A., Rudolph, A., Ruppin, F., Rusholme, B., Sacquegna, S., Sáez-Casares, I., Saga, S., Saglia, R., Sahlén, M., Saifollahi, T., Sakr, Z., Salvalaggio, J., Salvaterra, R., Salvati, L., Salvato, M., Salvignol, J. -C., Sánchez, A. G., Sanchez, E., Sanders, D. B., Sapone, D., Saponara, M., Sarpa, E., Sarron, F., Sartori, S., Sartoris, B., Sassolas, B., Sauniere, L., Sauvage, M., Sawicki, M., Scaramella, R., Scarlata, C., Scharré, L., Schaye, J., Schewtschenko, J. A., Schindler, J. -T., Schinnerer, E., Schirmer, M., Schmidt, F., Schmidt, M., Schneider, A., Schneider, M., Schneider, P., Schöneberg, N., Schrabback, T., Schultheis, M., Schulz, S., Schuster, N., Schwartz, J., Sciotti, D., Scodeggio, M., Scognamiglio, D., Scott, D., Scottez, V., Secroun, A., Sefusatti, E., Seidel, G., Seiffert, M., Sellentin, E., Selwood, M., Semboloni, E., Sereno, M., Serjeant, S., Serrano, S., Setnikar, G., Shankar, F., Sharples, R. M., Short, A., Shulevski, A., Shuntov, M., Sias, M., Sikkema, G., Silvestri, A., Simon, P., Sirignano, C., Sirri, G., Skottfelt, J., Slezak, E., Sluse, D., Smith, G. P., Smith, L. C., Smith, R. E., Smit, S. J. A., Soldano, F., Solheim, B. G. B., Sorce, J. G., Sorrenti, F., Soubrie, E., Spinoglio, L., Mancini, A. Spurio, Stadel, J., Stagnaro, L., Stanco, L., Stanford, S. A., Starck, J. -L., Stassi, P., Steinwagner, J., Stern, D., Stone, C., Strada, P., Strafella, F., Stramaccioni, D., Surace, C., Sureau, F., Suyu, S. H., Swindells, I., Szafraniec, M., Szapudi, I., Taamoli, S., Talia, M., Tallada-Crespí, P., Tanidis, K., Tao, C., Tarrío, P., Tavagnacco, D., Taylor, A. N., Taylor, J. E., Taylor, P. L., Teixeira, E. M., Tenti, M., Idiago, P. Teodoro, Teplitz, H. I., Tereno, I., Tessore, N., Testa, V., Testera, G., Tewes, M., Teyssier, R., Theret, N., Thizy, C., Thomas, P. D., Toba, Y., Toft, S., Toledo-Moreo, R., Tolstoy, E., Tommasi, E., Torbaniuk, O., Torradeflot, F., Tortora, C., Tosi, S., Tosti, S., Trifoglio, M., Troja, A., Trombetti, T., Tronconi, A., Tsedrik, M., Tsyganov, A., Tucci, M., Tutusaus, I., Uhlemann, C., Ulivi, L., Urbano, M., Vacher, L., Vaillon, L., Valageas, P., Valdes, I., Valentijn, E. A., Valenziano, L., Valieri, C., Valiviita, J., Broeck, M. Van den, Vassallo, T., Vavrek, R., Vega-Ferrero, J., Venemans, B., Venhola, A., Ventura, S., Kleijn, G. Verdoes, Vergani, D., Verma, A., Vernizzi, F., Veropalumbo, A., Verza, G., Vescovi, C., Vibert, D., Viel, M., Vielzeuf, P., Viglione, C., Viitanen, A., Villaescusa-Navarro, F., Vinciguerra, S., Visticot, F., Voggel, K., von Wietersheim-Kramsta, M., Vriend, W. J., Wachter, S., Walmsley, M., Walth, G., Walton, D. M., Walton, N. A., Wander, M., Wang, L., Wang, Y., Weaver, J. R., Weller, J., Wetzstein, M., Whalen, D. J., Whittam, I. H., Widmer, A., Wiesmann, M., Wilde, J., Williams, O. R., Winther, H. -A., Wittje, A., Wong, J. H. W., Wright, A. H., Yankelevich, V., Yeung, H. W., Yoon, M., Youles, S., Yung, L. Y. A., Zacchei, A., Zalesky, L., Zamorani, G., Vitorelli, A. Zamorano, Marc, M. Zanoni, Zennaro, M., Zerbi, F. M., Zinchenko, I. A., Zoubian, J., Zucca, E., and Zumalacarregui, M.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

Published
2024

4. Lensed Type Ia Supernova 'Encore' at z=2: The First Instance of Two Multiply-Imaged Supernovae in the Same Host Galaxy

Author

Pierel, J. D. R., Newman, A. B., Dhawan, S., Gu, M., Joshi, B. A., Li, T., Schuldt, S., Strolger, L. G., Suyu, S. H., Caminha, G. B., Cohen, S. H., Diego, J. M., Dsilva, J. C. J., Ertl, S., Frye, B. L., Granata, G., Grillo, C., Koekemoer, A. M., Li, J., Robotham, A., Summers, J., Treu, T., Windhorst, R. A., Zitrin, A., Agarwal, S., Agrawal, A., Arendse, N., Belli, S., Burns, C., Cañameras, R., Chakrabarti, S., Chen, W., Collett, T. E., Coulter, D. A., Ellis, R. S., Engesser, M., Foo, N., Fox, O. D., Gall, C., Garuda, N., Gezari, S., Gomez, S., Glazebrook, K., Hjorth, J., Huang, X., Jha, S. W., Kamieneski, P. S., Kelly, P., Larison, C., Moustakas, L. A., Pascale, M., Pérez-Fournon, I., Petrushevska, T., Poidevin, F., Rest, A., Shahbandeh, M., Shajib, A. J., Siebert, M., Storfer, C., Talbot, M., Wang, Q., Wevers, T., and Zenati, Y.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

A bright ($m_{\rm F150W,AB}$=24 mag), $z=1.95$ supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply-imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called "Requiem", and therefore the new SN is named "Encore". This makes the MACS J0138.0$-$2155 cluster the first known system to produce more than one multiply-imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a $\sim10$ year window to be $\approx3\%$. These observations have the potential to yield a Hubble Constant ($H_0$) measurement with $\sim10\%$ precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of $\sim2030$, providing an unprecedented baseline for time-delay cosmography., Comment: Accepted, ApJL

Published
2024
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5. Strong Lensing by Galaxies

Author

Shajib, A. J., Vernardos, G., Collett, T. E., Motta, V., Sluse, D., Williams, L. L. R., Saha, P., Birrer, S., Spiniello, C., and Treu, T.

Published
2024
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6. A search for gravitationally lensed supernovae within the Zwicky Transient Facility public survey

Author

Magee, M. R., de Murieta, A. Sainz, Collett, T. E., and Enzi, W.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Strong gravitational lensing of supernovae is exceedingly rare. To date, only a handful of lensed supernovae are known. Despite this, lensed supernovae have emerged as a promising method for measuring the current expansion rate of the Universe and breaking the Hubble tension. We present an extensive search for gravitationally lensed supernovae within the Zwicky Transient Facility (ZTF) public survey, covering 15,215 transients with good light curves discovered during four years of observations. We crossmatch a catalogue of known and candidate lens galaxies with our sample and find three coincident sources, which were due to chance alignment. To search for supernovae magnified by unknown lenses, we test multiple methods suggested in the literature for the first time on real data. This includes selecting objects with extremely red colours, those that appear inconsistent with the host galaxy redshift, and those with bright absolute magnitudes inferred from the host galaxy redshift. We find a few hundred candidates, most of which are due to contamination from activate galactic nuclei, bogus detections, or unlensed supernovae. The false positive rate from these methods presents significant challenges for future surveys. In total, 132 unique transients were identified across all of our selection methods that required detailed manual rejection, which would be infeasible for larger samples. Overall, we do not find any compelling candidates for lensed supernovae, which is broadly consistent with previous estimates for the rate of lensed supernovae from the ZTF public survey alone and the number expected to pass the selection cuts we apply., Comment: Updated selection criteria. 20 pages, 13 figures, and 3 tables including the appendices

Published
2023
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7. Strong Lensing by Galaxies

Author

Shajib, A. J., Vernardos, G., Collett, T. E., Motta, V., Sluse, D., Williams, L. L. R., Saha, P., Birrer, S., Spiniello, C., and Treu, T.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Strong gravitational lensing at the galaxy scale is a valuable tool for various applications in astrophysics and cosmology. The primary uses of galaxy-scale lensing are to study elliptical galaxies' mass structure and evolution, constrain the stellar initial mass function, and measure cosmological parameters. Since the discovery of the first galaxy-scale lens in the 1980s, this field has made significant advancements in data quality and modeling techniques. In this review, we describe the most common methods for modeling lensing observables, especially imaging data, as they are the most accessible and informative source of lensing observables. We then summarize the primary findings from the literature on the astrophysical and cosmological applications of galaxy-scale lenses. We also discuss the current limitations of the data and methodologies and provide an outlook on the expected improvements in both areas in the near future., Comment: Submitted to Space Science Reviews, Topical Collection "Strong Gravitational Lensing", eds. J. Wambsganss et al. This version: updated after peer review

Published
2022

8. The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign. I. Overview and classification of candidates selected by two techniques

Author

Treu, T., Agnello, A., Baumer, M. A., Birrer, S., Buckley-Geer, E. J., Courbin, F., Kim, Y. J., Lim, H., Marshall, P. J., Nord, B., Schechter, P. L., Sivakumar, P. R., Abramson, L. E., Anguita, T., Apostolovski, Y., Auger, M. W., Chan, J. H. H., Chen, G. C. F., Collett, T. E., Fassnacht, C. D., Hsueh, J. -W., Lemon, C., McMahon, R. G., Motta, V., Ostrovski, F., Rojas, K., Rusu, C. E., Williams, P., Frieman, J., Meylan, G., Suyu, S. H., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Avila, S., Banerji, M., Brooks, D., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., D'Andrea, C. B., da Costa, L. N., De Vicente, J., Doel, P., Eifler, T. F., Flaugher, B., Fosalba, P., García-Bellido, J., Goldstein, D. A., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hollowood, D., Honscheid, K., James, D. J., Kuehn, K., Kuropatkin, N., Lima, M., Maia, M. A. G., Martini, P., Menanteau, F., Miquel, R., Plazas, A. A., Romer, A. K., Sanchez, E., Scarpine, V., Schindler, R., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, D. L., and Walker, A. R.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

The primary goals of the STRong lensing Insights into the Dark Energy Survey (STRIDES) collaboration are to measure the dark energy equation of state parameter and the free streaming length of dark matter. To this aim, STRIDES is discovering strongly lensed quasars in the imaging data of the Dark Energy Survey and following them up to measure time delays, high resolution imaging, and spectroscopy sufficient to construct accurate lens models. In this paper, we first present forecasts for STRIDES. Then, we describe the STRIDES classification scheme, and give an overview of the Fall 2016 follow-up campaign. We continue by detailing the results of two selection methods, the Outlier Selection Technique and a morphological algorithm, and presenting lens models of a system, which could possibly be a lensed quasar in an unusual configuration. We conclude with the summary statistics of the Fall 2016 campaign. Including searches presented in companion papers (Anguita et al.; Ostrovski et al.), STRIDES followed up 117 targets identifying 7 new strongly lensed systems, and 7 nearly identical quasars (NIQs), which could be confirmed as lenses by the detection of the lens galaxy. 76 candidates were rejected and 27 remain otherwise inconclusive, for a success rate in the range 6-35\%. This rate is comparable to that of previous searches like SQLS even though the parent dataset of STRIDES is purely photometric and our selection of candidates cannot rely on spectroscopic information., Comment: (MNRAS in press; color scheme of Figures 1-4 improved with respect to v1)

Published
2018
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9. Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars

Author

Shajib, A. J., Birrer, S., Treu, T., Auger, M. W., Agnello, A., Anguita, T., Buckley-Geer, E. J., Chan, J. H. H., Collett, T. E., Courbin, F., Fassnacht, C. D., Frieman, J., Kayo, I., Lemon, C., Lin, H., Marshall, P. J., McMahon, R., More, A., Morgan, N. D., Motta, V., Oguri, M., Ostrovski, F., Rusu, C. E., Schechter, P. L., Shanks, T., Suyu, S. H., Meylan, G., Abbott, T. M. C., Allam, S., Annis, J., Avila, S., Bertin, E., Brooks, D., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Cunha, C. E., da Costa, L. N., De Vicente, J., Desai, S., Doel, P., Flaugher, B., Fosalba, P., García-Bellido, J., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hollowood, D. L., Hoyle, B., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Plazas, A. A., Sanchez, E., Scarpine, V., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., and Walker, A. R.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Strong-gravitational lens systems with quadruply-imaged quasars (quads) are unique probes to address several fundamental problems in cosmology and astrophysics. Although they are intrinsically very rare, ongoing and planned wide-field deep-sky surveys are set to discover thousands of such systems in the next decade. It is thus paramount to devise a general framework to model strong-lens systems to cope with this large influx without being limited by expert investigator time. We propose such a general modelling framework (implemented with the publicly available software Lenstronomy) and apply it to uniformly model three-band Hubble Space Telescope Wide Field Camera 3 images of 13 quads. This is the largest uniformly modelled sample of quads to date and paves the way for a variety of studies. To illustrate the scientific content of the sample, we investigate the alignment between the mass and light distribution in the deflectors. The position angles of these distributions are well-aligned, except when there is strong external shear. However, we find no correlation between the ellipticity of the light and mass distributions. We also show that the observed flux-ratios between the images depart significantly from the predictions of simple smooth models. The departures are strongest in the bluest band, consistent with microlensing being the dominant cause in addition to millilensing. Future papers will exploit this rich dataset in combination with ground based spectroscopy and time delays to determine quantities such as the Hubble constant, the free streaming length of dark matter, and the normalization of the initial stellar mass function., Comment: 22 pages, 9 figures, 8 tables, Accepted to MNRAS. This version: updated Table 4 from the erratum

Published
2018
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10. Lensed Type Ia Supernova “Encore” at z = 2: The First Instance of Two Multiply Imaged Supernovae in the Same Host Galaxy

Author

Pierel, J. D. R., primary, Newman, A. B., additional, Dhawan, S., additional, Gu, M., additional, Joshi, B. A., additional, Li, T., additional, Schuldt, S., additional, Strolger, L. G., additional, Suyu, S. H., additional, Caminha, G. B., additional, Cohen, S. H., additional, Diego, J. M., additional, DŚilva, J. C. J., additional, Ertl, S., additional, Frye, B. L., additional, Granata, G., additional, Grillo, C., additional, Koekemoer, A. M., additional, Li, J., additional, Robotham, A., additional, Summers, J., additional, Treu, T., additional, Windhorst, R. A., additional, Zitrin, A., additional, Agarwal, S., additional, Agrawal, A., additional, Arendse, N., additional, Belli, S., additional, Burns, C., additional, Cañameras, R., additional, Chakrabarti, S., additional, Chen, W., additional, Collett, T. E., additional, Coulter, D. A., additional, Ellis, R. S., additional, Engesser, M., additional, Foo, N., additional, Fox, O. D., additional, Gall, C., additional, Garuda, N., additional, Gezari, S., additional, Gomez, S., additional, Glazebrook, K., additional, Hjorth, J., additional, Huang, X., additional, Jha, S. W., additional, Kamieneski, P. S., additional, Kelly, P., additional, Larison, C., additional, Moustakas, L. A., additional, Pascale, M., additional, Pérez-Fournon, I., additional, Petrushevska, T., additional, Poidevin, F., additional, Rest, A., additional, Shahbandeh, M., additional, Shajib, A. J., additional, Siebert, M., additional, Storfer, C., additional, Talbot, M., additional, Wang, Q., additional, Wevers, T., additional, and Zenati, Y., additional

Published
2024
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11. Lensed Type Ia Supernova “Encore” at z = 2:The First Instance of Two Multiply Imaged Supernovae in the Same Host Galaxy

Author

Pierel, J. D. R., Newman, A. B., Dhawan, S., Gu, M., Joshi, B. A., Li, T., Schuldt, S., Strolger, L. G., Suyu, S. H., Caminha, G. B., Cohen, S. H., Diego, J. M., Dśilva, J. C. J., Ertl, S., Frye, B. L., Granata, G., Grillo, C., Koekemoer, A. M., Li, J., Robotham, A., Summers, J., Treu, T., Windhorst, R. A., Zitrin, A., Agarwal, S., Agrawal, A., Arendse, N., Belli, S., Burns, C., Cañameras, R., Chakrabarti, S., Chen, W., Collett, T. E., Coulter, D. A., Ellis, R. S., Engesser, M., Foo, N., Fox, O. D., Gall, C., Garuda, N., Gezari, S., Gomez, S., Glazebrook, K., Hjorth, J., Huang, X., Jha, S. W., Kamieneski, P. S., Kelly, P., Larison, C., Moustakas, L. A., Pascale, M., Pérez-fournon, I., Petrushevska, T., Poidevin, F., Rest, A., Shahbandeh, M., Shajib, A. J., Siebert, M., Storfer, C., Talbot, M., Wang, Q., Wevers, T., Zenati, Y., Pierel, J. D. R., Newman, A. B., Dhawan, S., Gu, M., Joshi, B. A., Li, T., Schuldt, S., Strolger, L. G., Suyu, S. H., Caminha, G. B., Cohen, S. H., Diego, J. M., Dśilva, J. C. J., Ertl, S., Frye, B. L., Granata, G., Grillo, C., Koekemoer, A. M., Li, J., Robotham, A., Summers, J., Treu, T., Windhorst, R. A., Zitrin, A., Agarwal, S., Agrawal, A., Arendse, N., Belli, S., Burns, C., Cañameras, R., Chakrabarti, S., Chen, W., Collett, T. E., Coulter, D. A., Ellis, R. S., Engesser, M., Foo, N., Fox, O. D., Gall, C., Garuda, N., Gezari, S., Gomez, S., Glazebrook, K., Hjorth, J., Huang, X., Jha, S. W., Kamieneski, P. S., Kelly, P., Larison, C., Moustakas, L. A., Pascale, M., Pérez-fournon, I., Petrushevska, T., Poidevin, F., Rest, A., Shahbandeh, M., Shajib, A. J., Siebert, M., Storfer, C., Talbot, M., Wang, Q., Wevers, T., and Zenati, Y.

Published
2024

13. Erratum: Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars

Author

Shajib, A J, primary, Birrer, S, additional, Treu, T, additional, Auger, M W, additional, Agnello, A, additional, Anguita, T, additional, Buckley-Geer, E J, additional, Chan, J H H, additional, Collett, T E, additional, Courbin, F, additional, Fassnacht, C D, additional, Frieman, J, additional, Kayo, I, additional, Lemon, C, additional, Lin, H, additional, Marshall, P J, additional, McMahon, R, additional, More, A, additional, Morgan, N D, additional, Motta, V, additional, Oguri, M, additional, Ostrovski, F, additional, Rusu, C E, additional, Schechter, P L, additional, Shanks, T, additional, Suyu, S H, additional, Meylan, G, additional, Abbott, T M C, additional, Allam, S, additional, Annis, J, additional, Avila, S, additional, Bertin, E, additional, Brooks, D, additional, Carnero Rosell, A, additional, Carrasco Kind, M, additional, Carretero, J, additional, Cunha, C E, additional, da Costa, L N, additional, De Vicente, J, additional, Desai, S, additional, Doel, P, additional, Flaugher, B, additional, Fosalba, P, additional, García-Bellido, J, additional, Gerdes, D W, additional, Gruen, D, additional, Gruendl, R A, additional, Gutierrez, G, additional, Hartley, W G, additional, Hollowood, D L, additional, Hoyle, B, additional, James, D J, additional, Kuehn, K, additional, Kuropatkin, N, additional, Lahav, O, additional, Lima, M, additional, Maia, M A G, additional, March, M, additional, Marshall, J L, additional, Melchior, P, additional, Menanteau, F, additional, Miquel, R, additional, Plazas, A A, additional, Sanchez, E, additional, Scarpine, V, additional, Sevilla-Noarbe, I, additional, Smith, M, additional, Soares-Santos, M, additional, Sobreira, F, additional, Suchyta, E, additional, Swanson, M E C, additional, Tarle, G, additional, and Walker, A R, additional

Published
2021
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14. Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 12 quadruply+ imaged quasars

Author

Shajib, A. J., Birrer, S., Treu, T., Auger, M. W., Agnello, A., Anguita, T., Buckley-Geer, E. J., Chan, J. H. H., Collett, T. E., Courbin, F., Fassnacht, C. D., Frieman, J., Kayo, I., Lemon, C., Lin, H., Marshall, P. J., McMahon, R., More, A., Morgan, N. D., Motta, V., Oguri, M., Ostrovski, F., Rusu, C. E., Schechter, P. L., Shanks, T., Suyu, S. H., Meylan, G., Abbott, T. M. C., Allam, S., Annis, J., Avila, S., Bertin, E., Brooks, D., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Cunha, C. E., Costa, L. N. da, Vicente, J. De, Desai, S., Doel, P., Flaugher, B., Fosalba, P., García-Bellido, J., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hollowood, D. L., Hoyle, B., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Plazas, A. A., Sanchez, E., Scarpine, V., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., and Walker, A. R.

Subjects
astro-ph.GA, RCUK, Astrophysics::Cosmology and Extragalactic Astrophysics, STFC
Abstract

Strong-gravitational lens systems with quadruply-imaged quasars (quads) are unique probes to address several fundamental problems in cosmology and astrophysics. Although they are intrinsically very rare, ongoing and planned wide-field deep-sky surveys are set to discover thousands of such systems in the next decade. It is thus paramount to devise a general framework to model strong-lens systems to cope with this large influx without being limited by expert investigator time. We propose such a general modelling framework (implemented with the publicly available software Lenstronomy) and apply it to uniformly model three band Hubble Space Telescope Wide Field Camera 3 images of 12 quads. This is the largest uniformly modelled sample of quads to date and paves the way for a variety of studies. To illustrate the scientific content of the sample, we investigate the alignment between the mass and light distribution in the deflectors. The position angles of these distributions are well-aligned, except when there is strong external shear. However, we find no correlation between the ellipticity of the light and mass distributions. We also show that the observed flux-ratios between the images depart significantly from the predictions of simple smooth models. The departures are strongest in the bluest band, consistent with microlensing being the dominant cause in addition to millilensing. Future papers will exploit this rich dataset in combination with ground based spectroscopy and time delays to determine quantities such as the Hubble constant, the free streaming length of dark matter, and the normalization of the initial stellar mass function.

Published
2019
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15. Finding high-redshift strong lenses in DES using convolutional neural networks

Author

Jacobs, C, Collett, T E, Desai, Shantanu et. al., Jacobs, C, Collett, T E, and Desai, Shantanu et. al.

Abstract

We search Dark Energy Survey (DES) Year 3 imaging data for galaxy-galaxy strong gravitational lenses using convolutional neural networks. We generate 250 000 simulated lenses at redshifts > 0.8 from which we create a data set for training the neural networks with realistic seeing, sky and shot noise. Using the simulations as a guide, we build a catalogue of 1.1 million DES sources with 1.8 < g − i < 5, 0.6 < g − r < 3, r mag > 19, g mag > 20, and i mag > 18.2. We train two ensembles of neural networks on training sets consisting of simulated lenses, simulated non-lenses, and real sources. We use the neural networks to score images of each of the sources in our catalogue with a value from 0 to 1, and select those with scores greater than a chosen threshold for visual inspection, resulting in a candidate set of 7301 galaxies. During visual inspection, we rate 84 as 'probably' or 'definitely' lenses. Four of these are previously known lenses or lens candidates. We inspect a further 9428 candidates with a different score threshold, and identify four new candidates. We present 84 new strong lens candidates, selected after a few hours of visual inspection by astronomers. This catalogue contains a comparable number of high-redshift lenses to that predicted by simulations. Based on simulations, we estimate our sample to contain most discoverable lenses in this imaging and at this redshift range.

Published
2019

16. Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars

Author

Shajib, A J, primary, Birrer, S, additional, Treu, T, additional, Auger, M W, additional, Agnello, A, additional, Anguita, T, additional, Buckley-Geer, E J, additional, Chan, J H H, additional, Collett, T E, additional, Courbin, F, additional, Fassnacht, C D, additional, Frieman, J, additional, Kayo, I, additional, Lemon, C, additional, Lin, H, additional, Marshall, P J, additional, McMahon, R, additional, More, A, additional, Morgan, N D, additional, Motta, V, additional, Oguri, M, additional, Ostrovski, F, additional, Rusu, C E, additional, Schechter, P L, additional, Shanks, T, additional, Suyu, S H, additional, Meylan, G, additional, Abbott, T M C, additional, Allam, S, additional, Annis, J, additional, Avila, S, additional, Bertin, E, additional, Brooks, D, additional, Carnero Rosell, A, additional, Carrasco Kind, M, additional, Carretero, J, additional, Cunha, C E, additional, da Costa, L N, additional, De Vicente, J, additional, Desai, S, additional, Doel, P, additional, Flaugher, B, additional, Fosalba, P, additional, García-Bellido, J, additional, Gerdes, D W, additional, Gruen, D, additional, Gruendl, R A, additional, Gutierrez, G, additional, Hartley, W G, additional, Hollowood, D L, additional, Hoyle, B, additional, James, D J, additional, Kuehn, K, additional, Kuropatkin, N, additional, Lahav, O, additional, Lima, M, additional, Maia, M A G, additional, March, M, additional, Marshall, J L, additional, Melchior, P, additional, Menanteau, F, additional, Miquel, R, additional, Plazas, A A, additional, Sanchez, E, additional, Scarpine, V, additional, Sevilla-Noarbe, I, additional, Smith, M, additional, Soares-Santos, M, additional, Sobreira, F, additional, Suchyta, E, additional, Swanson, M E C, additional, Tarle, G, additional, and Walker, A R, additional

Published
2018
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17. The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign – I. Overview and classification of candidates selected by two techniques

Author

Treu, T, primary, Agnello, A, additional, Baumer, M A, additional, Birrer, S, additional, Buckley-Geer, E J, additional, Courbin, F, additional, Kim, Y J, additional, Lin, H, additional, Marshall, P J, additional, Nord, B, additional, Schechter, P L, additional, Sivakumar, P R, additional, Abramson, L E, additional, Anguita, T, additional, Apostolovski, Y, additional, Auger, M W, additional, Chan, J H H, additional, Chen, G C F, additional, Collett, T E, additional, Fassnacht, C D, additional, Hsueh, J-W, additional, Lemon, C, additional, McMahon, R G, additional, Motta, V, additional, Ostrovski, F, additional, Rojas, K, additional, Rusu, C E, additional, Williams, P, additional, Frieman, J, additional, Meylan, G, additional, Suyu, S H, additional, Abbott, T M C, additional, Abdalla, F B, additional, Allam, S, additional, Annis, J, additional, Avila, S, additional, Banerji, M, additional, Brooks, D, additional, Rosell, A Carnero, additional, Kind, M Carrasco, additional, Carretero, J, additional, Castander, F J, additional, D’Andrea, C B, additional, da Costa, L N, additional, De Vicente, J, additional, Doel, P, additional, Eifler, T F, additional, Flaugher, B, additional, Fosalba, P, additional, García-Bellido, J, additional, Goldstein, D A, additional, Gruen, D, additional, Gruendl, R A, additional, Gutierrez, G, additional, Hartley, W G, additional, Hollowood, D, additional, Honscheid, K, additional, James, D J, additional, Kuehn, K, additional, Kuropatkin, N, additional, Lima, M, additional, Maia, M A G, additional, Martini, P, additional, Menanteau, F, additional, Miquel, R, additional, Plazas, A A, additional, Romer, A K, additional, Sanchez, E, additional, Scarpine, V, additional, Schindler, R, additional, Schubnell, M, additional, Sevilla-Noarbe, I, additional, Smith, M, additional, Smith, R C, additional, Soares-Santos, M, additional, Sobreira, F, additional, Suchyta, E, additional, Swanson, M E C, additional, Tarle, G, additional, Thomas, D, additional, Tucker, D L, additional, and Walker, A R, additional

Published
2018
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18. Models of the strongly lensed quasar DES J0408−5354

Author

Agnello, A, Lin, H, Buckley Geer, L, Treu, T, Bonvin, V, Courbin, F, Lemon, C, Morishita, T, Amara, A, Auger, M W, Birrer, S, Chan, J, Collett, T E, More, A, Fassnacht, C D, Frieman, J, Marshall, P J, McMahon, R G, Meylan, G, Suyu, S H, Castander, F J, Finley, D A, Howell, A, Kochanek, C, Makler, M, Martini, P, Morgan, N, Nord, B, Ostrovski, F, Schechter, P, Tucker, D L, Wechsler, R H, Abbott, T M C, Abdalla, F B, Allam, S, Benoit-Lévy, A, Bertin, E, Brooks, D, Burke, D L, Rosell, A Carnero, Kind, M Carrasco, Carretero, J, Crocce, M, Cunha, C E, D’Andrea, C B, da Costa, L N, Desai, Shantanu, Agnello, A, Lin, H, Buckley Geer, L, Treu, T, Bonvin, V, Courbin, F, Lemon, C, Morishita, T, Amara, A, Auger, M W, Birrer, S, Chan, J, Collett, T E, More, A, Fassnacht, C D, Frieman, J, Marshall, P J, McMahon, R G, Meylan, G, Suyu, S H, Castander, F J, Finley, D A, Howell, A, Kochanek, C, Makler, M, Martini, P, Morgan, N, Nord, B, Ostrovski, F, Schechter, P, Tucker, D L, Wechsler, R H, Abbott, T M C, Abdalla, F B, Allam, S, Benoit-Lévy, A, Bertin, E, Brooks, D, Burke, D L, Rosell, A Carnero, Kind, M Carrasco, Carretero, J, Crocce, M, Cunha, C E, D’Andrea, C B, da Costa, L N, and Desai, Shantanu

Abstract

We present detailed modelling of the recently discovered, quadruply lensed quasar J0408−5354, with the aim of interpreting its remarkable configuration: besides three quasar images (A,B,D) around the main deflector (G1), a fourth image (C) is significantly reddened and dimmed by a perturber (G2) which is not detected in the Dark Energy Survey imaging data. From lens models incorporating (dust-corrected) flux ratios, we find a perturber Einstein radius 0.04 arcsec ≲ RE, G2 ≲ 0.2 arcsec and enclosed mass Mp(RE, G2) ≲ 1.0 × 1010 M⊙. The main deflector has stellar mass log10(M⋆/M⊙)=11.49+0.46−0.32 , a projected mass Mp(RE, G1) ≈ 6 × 1011 M⊙ within its Einstein radius RE, G1 = (1.85 ± 0.15) arcsec and predicted velocity dispersion 267–280 km s−1. Follow-up images from a companion monitoring campaign show additional components, including a candidate second source at a redshift between the quasar and G1. Models with free perturbers, and dust-corrected and delay-corrected flux ratios, are also explored. The predicted time-delays (ΔtAB = (135.0 ± 12.6) d, ΔtBD = (21.0 ± 3.5) d) roughly agree with those measured, but better imaging is required for proper modelling and comparison. We also discuss some lessons learnt from J0408−5354 on lensed quasar finding strategies, due to its chromaticity and morphology.

Published
2017

19. The DES Bright Arcs Survey: Hundreds of Candidate Strongly Lensed Galaxy Systems from the Dark Energy Survey Science Verification and Year 1 Observations

Author

Diehl, H T, Buckley-Geer, E J, Lindgren, K A, Nord, B, Gaitsch, H, Gaitsch, S, Lin, H, Allam, S, Collett, T E, Furlanetto, C, Gill, M S S, More, A, Nightingale, J, Odden, C, Pellico, A, Tucker, D L, Costa, L N da, Neto, A F, Kuropatkin, N, Soares-Santos, M, Welch, B, Zhang, Y, Frieman, J A, Abdalla, F B, Annis, J, Benoit-Lévy, A, Bertin, E, Brooks, D, Burke, D L, Rosell, A C, Kind, M C, Carretero, J, Cunha, C E, D’Andrea, C B, Desai, Shantanu, et al, ., Diehl, H T, Buckley-Geer, E J, Lindgren, K A, Nord, B, Gaitsch, H, Gaitsch, S, Lin, H, Allam, S, Collett, T E, Furlanetto, C, Gill, M S S, More, A, Nightingale, J, Odden, C, Pellico, A, Tucker, D L, Costa, L N da, Neto, A F, Kuropatkin, N, Soares-Santos, M, Welch, B, Zhang, Y, Frieman, J A, Abdalla, F B, Annis, J, Benoit-Lévy, A, Bertin, E, Brooks, D, Burke, D L, Rosell, A C, Kind, M C, Carretero, J, Cunha, C E, D’Andrea, C B, Desai, Shantanu, and et al, .

Abstract

We report the results of searches for strong gravitational lens systems in the Dark Energy Survey (DES) Science Verification and Year 1 observations. The Science Verification data span approximately 250 sq. deg. with a median i-band limiting magnitude for extended objects (10 sigma) of 23.0. The Year 1 data span approximately 2000 sq. deg. and have an i-band limiting magnitude for extended objects (10 sigma) of 22.9. As these data sets are both wide and deep, they are particularly useful for identifying strong gravitational lens candidates. Potential strong gravitational lens candidate systems were initially identified based on a color and magnitude selection in the DES object catalogs or because the system is at the location of a previously identified galaxy cluster. Cutout images of potential candidates were then visually scanned using an object viewer and numerically ranked according to whether or not we judged them to be likely strong gravitational lens systems. Having scanned nearly 400,000 cutouts, we present 374 candidate strong lens systems, of which 348 are identified for the first time. We provide the R.A. and decl., the magnitudes and photometric properties of the lens and source objects, and the distance (radius) of the source(s) from the lens center for each system.

Published
2017

20. SPACE WARPS - I. Crowdsourcing the discovery of gravitational lenses

Author

Marshall, P J, Verma, A, More, A, Davis, C P, More, S, Kapadia, A, Parrish, M, Snyder, C, Wilcox, J, Baeten, E, Macmillan, C, Cornen, C, Baumer, M, Simpson, E, Lintott, C J, Miller, D, Paget, E, Simpson, R, Smith, A M, Ku ng, R, Saha, P, Collett, T E, University of Zurich, and Marshall, P J

Subjects
1912 Space and Planetary Science, 530 Physics, 3103 Astronomy and Astrophysics, 10192 Physics Institute
Published
2016

21. Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars.

Author

Shajib, A J, Birrer, S, Treu, T, Auger, M W, Agnello, A, Anguita, T, Buckley-Geer, E J, Chan, J H H, Collett, T E, Courbin, F, Fassnacht, C D, Frieman, J, Kayo, I, Lemon, C, Lin, H, Marshall, P J, McMahon, R, More, A, Morgan, N D, and Motta, V

Subjects
GALAXIES, COMPUTER software, ASTROPHYSICS, METAPHYSICAL cosmology
Abstract

Strong-gravitational lens systems with quadruply imaged quasars (quads) are unique probes to address several fundamental problems in cosmology and astrophysics. Although they are intrinsically very rare, ongoing and planned wide-field deep-sky surveys are set to discover thousands of such systems in the next decade. It is thus paramount to devise a general framework to model strong-lens systems to cope with this large influx without being limited by expert investigator time. We propose such a general modelling framework (implemented with the publicly available software lenstronomy) and apply it to uniformly model three-band Hubble Space Telescope Wide Field Camera 3 images of 13 quads. This is the largest uniformly modelled sample of quads to date and paves the way for a variety of studies. To illustrate the scientific content of the sample, we investigate the alignment between the mass and light distribution in the deflectors. The position angles of these distributions are well-aligned, except when there is strong external shear. However, we find no correlation between the ellipticity of the light and mass distributions. We also show that the observed flux-ratios between the images depart significantly from the predictions of simple smooth models. The departures are strongest in the bluest band, consistent with microlensing being the dominant cause in addition to millilensing. Future papers will exploit this rich data set in combination with ground-based spectroscopy and time delays to determine quantities such as the Hubble constant, the free streaming length of dark matter, and the normalization of the initial stellar mass function. [ABSTRACT FROM AUTHOR]

Published
2019
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22. SPACE WARPS- II. New gravitational lens candidates from the CFHTLS discovered through citizen science

Author

More, A, Verma, A, Marshall, P J, More, S, Baeten, E, Wilcox, J, Macmillan, C, Cornen, C, Kapadia, A, Parrish, M, Snyder, C, Davis, C P, Gavazzi, R, Lintott, C J, Simpson, R, Miller, D, Smith, A M, Paget, E, Saha, P, Ku ng, R, Collett, T E, More, A, Verma, A, Marshall, P J, More, S, Baeten, E, Wilcox, J, Macmillan, C, Cornen, C, Kapadia, A, Parrish, M, Snyder, C, Davis, C P, Gavazzi, R, Lintott, C J, Simpson, R, Miller, D, Smith, A M, Paget, E, Saha, P, Ku ng, R, and Collett, T E

Abstract

We report the discovery of 29 promising (and 59 total) new lens candidates from the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS) based on about 11 million classifications performed by citizen scientists as part of the first Space Warps lens search. The goal of the blind lens search was to identify lens candidates missed by robots (the ringfinder on galaxy scales and arcfinder on group/cluster scales) which had been previously used to mine the CFHTLS for lenses. We compare some properties of the samples detected by these algorithms to the Space Warps sample and find them to be broadly similar. The image separation distribution calculated from the Space Warps sample shows that previous constraints on the average density profile of lens galaxies are robust. Space Warps recovers about 65 per cent of known lenses, while the new candidates show a richer variety compared to those found by the two robots. This detection rate could be increased to 80 per cent by only using classifications performed by expert volunteers (albeit at the cost of a lower purity), indicating that the training and performance calibration of the citizen scientists is very important for the success of Space Warps. In this work we present the SIMCT pipeline, used for generating in situ a sample of realistic simulated lensed images. This training sample, along with the false positives identified during the search, has a legacy value for testing future lens-finding algorithms. We make the pipeline and the training set publicly available.

Published
2016

24. Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars (vol 483, pg 5671, 2019)

Author

Shajib, A. J., Birrer, S., Treu, T., Auger, M. W., Agnello, A., Anguita, T., Buckley-Geer, E. J., Chan, J. H. H., Collett, T. E., Courbin, F., Fassnacht, C. D., Frieman, J., Kayo, I., Lemon, C., Lin, H., Marshall, P. J., McMahon, R., More, A., Morgan, N. D., Motta, V., Oguri, M., Ostrovski, F., Rusu, C. E., Schechter, P. L., Shanks, T., Suyu, S. H., Meylan, G., Abbott, T. M. C., Allam, S., Annis, J., Avila, S., Bertin, E., Brooks, D., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Cunha, C. E., da Costa, L. N., De Vicente, J., Desai, S., Doel, P., Flaugher, B., Fosalba, P., Garcia-Bellido, J., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hollowood, D. L., Hoyle, B., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., March, M., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Plazas, A. A., Sanchez, E., Scarpine, V., Sevilla-Noarbe, I., Smith, M., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E. C., Tarle, G., and Walker, A. R.

Subjects
gravitational lensing: strong, galaxies: structure, galaxies: elliptical and lenticular, addenda, methods: data analysis, errata, cd

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