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1. MuCol Milestone Report No. 5: Preliminary Parameters

Author

Accettura, Carlotta, Adrian, Simon, Agarwal, Rohit, Ahdida, Claudia, Aimé, Chiara, Aksoy, Avni, Alberghi, Gian Luigi, Alden, Siobhan, Alfonso, Luca, Amapane, Nicola, Amorim, David, Andreetto, Paolo, Anulli, Fabio, Appleby, Rob, Apresyan, Artur, Asadi, Pouya, Mahmoud, Mohammed Attia, Auchmann, Bernhard, Back, John, Badea, Anthony, Bae, Kyu Jung, Bahng, E. J., Balconi, Lorenzo, Balli, Fabrice, Bandiera, Laura, Barbagallo, Carmelo, Barlow, Roger, Bartoli, Camilla, Bartosik, Nazar, Barzi, Emanuela, Batsch, Fabian, Bauce, Matteo, Begel, Michael, Berg, J. Scott, Bersani, Andrea, Bertarelli, Alessandro, Bertinelli, Francesco, Bertolin, Alessandro, Bhat, Pushpalatha, Bianchi, Clarissa, Bianco, Michele, Bishop, William, Black, Kevin, Boattini, Fulvio, Bogacz, Alex, Bonesini, Maurizio, Bordini, Bernardo, de Sousa, Patricia Borges, Bottaro, Salvatore, Bottura, Luca, Boyd, Steven, Breschi, Marco, Broggi, Francesco, Brunoldi, Matteo, Buffat, Xavier, Buonincontri, Laura, Burrows, Philip Nicholas, Burt, Graeme Campbell, Buttazzo, Dario, Caiffi, Barbara, Calatroni, Sergio, Calviani, Marco, Calzaferri, Simone, Calzolari, Daniele, Cantone, Claudio, Capdevilla, Rodolfo, Carli, Christian, Carrelli, Carlo, Casaburo, Fausto, Casarsa, Massimo, Castelli, Luca, Catanesi, Maria Gabriella, Cavallucci, Lorenzo, Cavoto, Gianluca, Celiberto, Francesco Giovanni, Celona, Luigi, Cemmi, Alessia, Ceravolo, Sergio, Cerri, Alessandro, Cerutti, Francesco, Cesarini, Gianmario, Cesarotti, Cari, Chancé, Antoine, Charitonidis, Nikolaos, Chiesa, Mauro, Chiggiato, Paolo, Ciccarella, Vittoria Ludovica, Puviani, Pietro Cioli, Colaleo, Anna, Colao, Francesco, Collamati, Francesco, Costa, Marco, Craig, Nathaniel, Curtin, David, Damerau, Heiko, Da Molin, Giacomo, D'Angelo, Laura, Dasu, Sridhara, de Blas, Jorge, De Curtis, Stefania, De Gersem, Herbert, Delahaye, Jean-Pierre, Del Moro, Tommaso, Denisov, Dmitri, Denizli, Haluk, Dermisek, Radovan, Valdor, Paula Desiré, Desponds, Charlotte, Di Luzio, Luca, Di Meco, Elisa, Diociaiuti, Eleonora, Di Petrillo, Karri Folan, Di Sarcina, Ilaria, Dorigo, Tommaso, Dreimanis, Karlis, Pree, Tristan du, Yildiz, Hatice Duran, Edgecock, Thomas, Fabbri, Siara, Fabbrichesi, Marco, Farinon, Stefania, Ferrand, Guillaume, Somoza, Jose Antonio Ferreira, Fieg, Max, Filthaut, Frank, Fox, Patrick, Franceschini, Roberto, Ximenes, Rui Franqueira, Gallinaro, Michele, Garcia-Sciveres, Maurice, Garcia-Tabares, Luis, Gargiulo, Ruben, Garion, Cedric, Garzelli, Maria Vittoria, Gast, Marco, Generoso, Lisa, Gerber, Cecilia E., Giambastiani, Luca, Gianelle, Alessio, Gianfelice-Wendt, Eliana, Gibson, Stephen, Gilardoni, Simone, Giove, Dario Augusto, Giovinco, Valentina, Giraldin, Carlo, Glioti, Alfredo, Gorzawski, Arkadiusz, Greco, Mario, Grojean, Christophe, Grudiev, Alexej, Gschwendtner, Edda, Gueli, Emanuele, Guilhaudin, Nicolas, Han, Chengcheng, Han, Tao, Hauptman, John Michael, Herndon, Matthew, Hillier, Adrian D, Hillman, Micah, Holmes, Tova Ray, Homiller, Samuel, Jana, Sudip, Jindariani, Sergo, Johannesson, Sofia, Johnson, Benjamin, Jones, Owain Rhodri, Jurj, Paul-Bogdan, Kahn, Yonatan, Kamath, Rohan, Kario, Anna, Karpov, Ivan, Kelliher, David, Kilian, Wolfgang, Kitano, Ryuichiro, Kling, Felix, Kolehmainen, Antti, Kong, K. C., Kosse, Jaap, Krintiras, Georgios, Krizka, Karol, Kumar, Nilanjana, Kvikne, Erik, Kyle, Robert, Laface, Emanuele, Lane, Kenneth, Latina, Andrea, Lechner, Anton, Lee, Junghyun, Lee, Lawrence, Lee, Seh Wook, Lefevre, Thibaut, Leonardi, Emanuele, Lerner, Giuseppe, Li, Peiran, Li, Qiang, Li, Tong, Li, Wei, Lindroos, Mats, Lipton, Ronald, Liu, Da, Liu, Miaoyuan, Liu, Zhen, Voti, Roberto Li, Lombardi, Alessandra, Lomte, Shivani, Long, Kenneth, Longo, Luigi, Lorenzo, José, Losito, Roberto, Low, Ian, Lu, Xianguo, Lucchesi, Donatella, Luo, Tianhuan, Lupato, Anna, Ma, Yang, Machida, Shinji, Madlener, Thomas, Magaletti, Lorenzo, Maggi, Marcello, Durand, Helene Mainaud, Maltoni, Fabio, Manczak, Jerzy Mikolaj, Mandurrino, Marco, Marchand, Claude, Mariani, Francesco, Marin, Stefano, Mariotto, Samuele, Martin-Haugh, Stewart, Masullo, Maria Rosaria, Mauro, Giorgio Sebastiano, Mazzolari, Andrea, Mękała, Krzysztof, Mele, Barbara, Meloni, Federico, Meng, Xiangwei, Mentink, Matthias, Métral, Elias, Miceli, Rebecca, Milas, Natalia, Mohammadi, Abdollah, Moll, Dominik, Montella, Alessandro, Morandin, Mauro, Morrone, Marco, Mulder, Tim, Musenich, Riccardo, Nardecchia, Marco, Nardi, Federico, Nenna, Felice, Neuffer, David, Newbold, David, Novelli, Daniel, Olvegård, Maja, Onel, Yasar, Orestano, Domizia, Osborne, John, Otten, Simon, Torres, Yohan Mauricio Oviedo, Paesani, Daniele, Griso, Simone Pagan, Pagani, Davide, Pal, Kincso, Palmer, Mark, Pampaloni, Alessandra, Panci, Paolo, Pani, Priscilla, Papaphilippou, Yannis, Paparella, Rocco, Paradisi, Paride, Passeri, Antonio, Pasternak, Jaroslaw, Pastrone, Nadia, Pellecchia, Antonello, Piccinini, Fulvio, Piekarz, Henryk, Pieloni, Tatiana, Plouin, Juliette, Portone, Alfredo, Potamianos, Karolos, Potdevin, Joséphine, Prestemon, Soren, Puig, Teresa, Qiang, Ji, Quettier, Lionel, Rabemananjara, Tanjona Radonirina, Radicioni, Emilio, Radogna, Raffaella, Rago, Ilaria Carmela, Ratkus, Andris, Resseguie, Elodie, Reuter, Juergen, Ribani, Pier Luigi, Riccardi, Cristina, Ricciardi, Stefania, Robens, Tania, Robert, Youri, Rogers, Chris, Rojo, Juan, Romagnoni, Marco, Ronald, Kevin, Rosser, Benjamin, Rossi, Carlo, Rossi, Lucio, Rozanov, Leo, Ruhdorfer, Maximilian, Ruiz, Richard, Saini, Saurabh, Sala, Filippo, Salierno, Claudia, Salmi, Tiina, Salvini, Paola, Salvioni, Ennio, Sammut, Nicholas, Santini, Carlo, Saputi, Alessandro, Sarra, Ivano, Scarantino, Giuseppe, Schneider-Muntau, Hans, Schulte, Daniel, Scifo, Jessica, Sen, Tanaji, Senatore, Carmine, Senol, Abdulkadir, Sertore, Daniele, Sestini, Lorenzo, Rêgo, Ricardo César Silva, Simone, Federica Maria, Skoufaris, Kyriacos, Sorbello, Gino, Sorbi, Massimo, Sorti, Stefano, Soubirou, Lisa, Spataro, David, Queiroz, Farinaldo S., Stamerra, Anna, Stapnes, Steinar, Stark, Giordon, Statera, Marco, Stechauner, Bernd Michael, Su, Shufang, Su, Wei, Sun, Xiaohu, Sytov, Alexei, Tang, Jian, Tang, Jingyu, Taylor, Rebecca, Kate, Herman Ten, Testoni, Pietro, Thiele, Leonard Sebastian, Garcia, Rogelio Tomas, Topp-Mugglestone, Max, Torims, Toms, Torre, Riccardo, Tortora, Luca, Tortora, Ludovico, Trifinopoulos, Sokratis, Udongwo, Sosoho-Abasi, Vai, Ilaria, Valente, Riccardo Umberto, van Rienen, Ursula, Van Weelderen, Rob, Vanwelde, Marion, Velev, Gueorgui, Venditti, Rosamaria, Vendrasco, Adam, Verna, Adriano, Vernassa, Gianluca, Verweij, Arjan, Verwilligen, Piet, Villamizar, Yoxara, Vittorio, Ludovico, Vitulo, Paolo, Vojskovic, Isabella, Wang, Dayong, Wang, Lian-Tao, Wang, Xing, Wendt, Manfred, Widorski, Markus, Wozniak, Mariusz, Wu, Yongcheng, Wulzer, Andrea, Xie, Keping, Yang, Yifeng, Yap, Yee Chinn, Yonehara, Katsuya, Yoo, Hwi Dong, You, Zhengyun, Zanetti, Marco, Zaza, Angela, Zhang, Liang, Zhu, Ruihu, Zlobin, Alexander, Zuliani, Davide, and Zurita, José Francisco

Subjects
Physics - Accelerator Physics
Abstract

This document is comprised of a collection of updated preliminary parameters for the key parts of the muon collider. The updated preliminary parameters follow on from the October 2023 Tentative Parameters Report. Particular attention has been given to regions of the facility that are believed to hold greater technical uncertainty in their design and that have a strong impact on the cost and power consumption of the facility. The data is collected from a collaborative spreadsheet and transferred to overleaf.

Published
2024
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2. CASCO: Cosmological and AStrophysical parameters from Cosmological simulations and Observations -- II. Constraining cosmology and astrophysical processes with early- and late-type galaxies

Author

Busillo, Valerio, Tortora, Crescenzo, Covone, Giovanni, Koopmans, Leon V. E., Silvestrini, Michela, and Napolitano, Nicola R.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Physical processes impact galaxy formation and evolution in diverse ways, requiring validation of their implementation in cosmological simulations through comparisons with real data across various galaxy types and properties. In this second paper of the CASCO series, we compare the structural properties and dark matter (DM) content of early-type galaxies from the CAMELS IllustrisTNG simulations to three observational datasets (SPIDER, $\textrm{ATLAS}^{\textrm{3D}}$, and MaNGA DynPop), to constrain cosmological and astrophysical feedback parameters, contrasting these results with those obtained for late-type galaxies. We analyze the size-, internal DM fraction-, and DM mass-stellar mass relations, identifying the best-fit simulation for each dataset. For SPIDER, we find cosmological parameter values consistent with literature and results obtained from the comparison between simulations and late-type galaxies, with supernova feedback parameters differing from results derived for late-type galaxies. For $\textrm{ATLAS}^{\textrm{3D}}$, cosmological parameter results align with SPIDER, while supernova feedback parameters are more consistent with late-type galaxies results. MaNGA DynPop yields extreme cosmological parameter values but similar supernova feedback results to $\textrm{ATLAS}^{\textrm{3D}}$. However, no single simulation matches the full range of observational trends, especially when combining early- and late-type galaxies from MaNGA DynPop. These findings highlight the limitations of simulations in reproducing diverse galaxy properties, underscoring the challenge of capturing the complexity of galaxy formation across all types., Comment: 11 figures, 7 tables, 20 pages, accepted for publication on A&A

Published
2024

3. Leveraging Transfer Learning for Astronomical Image Analysis

Author

Cavuoti, Stefano, Doorenbos, Lars, De Cicco, Demetra, Sasanelli, Gianluca, Brescia, Massimo, Longo, Giuseppe, Paolillo, Maurizio, Torbaniuk, Olena, Angora, Giuseppe, and Tortora, Crescenzo

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The exponential growth of astronomical data from large-scale surveys has created both opportunities and challenges for the astrophysics community. This paper explores the possibilities offered by transfer learning techniques in addressing these challenges across various domains of astronomical research. We present a set of recent applications of transfer learning methods for astronomical tasks based on the usage of a pre-trained convolutional neural networks. The examples shortly discussed include the detection of candidate active galactic nuclei (AGN), the possibility of deriving physical parameters for galaxies directly from images, the identification of artifacts in time series images, and the detection of strong lensing candidates and outliers. We demonstrate how transfer learning enables efficient analysis of complex astronomical phenomena, particularly in scenarios where labeled data is scarce. This kind of method will be very helpful for upcoming large-scale surveys like the Rubin Legacy Survey of Space and Time (LSST). By showcasing successful implementations and discussing methodological approaches, we highlight the versatility and effectiveness of such techniques., Comment: proceeding of the Seventeenth Marcel Grossmann Meeting

Published
2024

4. Linear Realisability over nets: multiplicatives (long version)

Author

Ragot, Adrien, Seiller, Thomas, and de Falco, Lorenzo Tortora

Subjects
Computer Science - Logic in Computer Science
Abstract

We provide a new realisability model based on orthogonality for the multiplicative fragment of linear logic, both in presence of generalised axioms (MLL*) and in the standard case (MLL). The novelty is the definition of cut elimination for generalised axioms. We prove that our model is adequate and complete both for MLL* and MLL.

Published
2024

5. 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

6. Elucidating chirality transfer in liquid crystals of viruses

Author

Grelet, Eric and Tortora, Maxime

Subjects
Condensed Matter - Soft Condensed Matter, Physics - Biological Physics
Abstract

Chirality is ubiquitous in nature across all length scales, with major implications spanning the fields of biology, chemistry and physics to materials science. How chirality propagates from nanoscale building blocks to meso- and macroscopic helical structures remains an open issue. Here, working with a canonical system of filamentous viruses, we demonstrate that their self-assembly into chiral liquid crystal phases quantitatively results from the interplay between two main mechanisms of chirality transfer: electrostatic interactions from the helical charge patterns on the virus surface, and fluctuation-based helical deformations leading to viral backbone helicity. Our experimental and theoretical approach provides a comprehensive framework for deciphering how chirality is hierarchically and quantitatively propagated across spatial scales. Our work highlights the ways in which supramolecular helicity may arise from subtle chiral contributions of opposite handedness which either act cooperatively or competitively, thus accounting for the multiplicity of chiral behaviors observed for nearly identical molecular systems.

Published
2024
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7. VST-SMASH: the VST Survey of Mass Assembly and Structural Hierarchy

Author

Tortora, Crescenzo, Ragusa, Rossella, Gatto, Massimiliano, Spavone, Marilena, Hunt, Leslie, Ripepi, Vincenzo, Dall'Ora, Massimo, Abdurro'uf, Annibali, Francesca, Baes, Maarten, Belfiore, Francesco Michel Concetto, Bellucco, Nicola, Bolzonella, Micol, Cantiello, Michele, Dimauro, Paola, Kluge, Mathias, Lelli, Federico, Napolitano, Nicola R., Nucita, Achille, Radovich, Mario, Scaramella, Roberto, Schinnerer, Eva, Testa, Vincenzo, and Unni, Aiswarya

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The VLT Survey Telescope Survey of Mass Assembly and Structural Hierarchy (VST-SMASH) aims to detect tidal features and remnants around very nearby galaxies, a unique and essential diagnostic of the hierarchical nature of galaxy formation. Leveraging optimal sky conditions at ESO's Paranal Observatory, combined with the VST's multi-band optical filters, VST-SMASH aims to be the definitive survey of stellar streams and tidal remnants in the Local Volume, targeting a low surface-brightness limit of $\mu \sim$ 30 mag arcsec$^{-2}$ in the g and r bands, and $\mu \sim$ 28 mag arcsec$^{-2}$ in the i band, in a volume-limited sample of local galaxies within 11 Mpc and the Euclid footprint., Comment: 4 pages, 2 figures, 1 table, published in the ESO Messenger 193

Published
2024

8. RAZOR: Refining Accuracy by Zeroing Out Redundancies

Author

Riccio, Daniel, Tortora, Genoveffa, and Sangiovanni, Mara

Subjects
Computer Science - Machine Learning
Abstract

In many application domains, the proliferation of sensors and devices is generating vast volumes of data, imposing significant pressure on existing data analysis and data mining techniques. Nevertheless, an increase in data volume does not inherently imply an increase in informational content, as a substantial portion may be redundant or represent noise. This challenge is particularly evident in the deep learning domain, where the utility of additional data is contingent on its informativeness. In the absence of such, larger datasets merely exacerbate the computational cost and complexity of the learning process. To address these challenges, we propose RAZOR, a novel instance selection technique designed to extract a significantly smaller yet sufficiently informative subset from a larger set of instances without compromising the learning process. RAZOR has been specifically engineered to be robust, efficient, and scalable, making it suitable for large-scale datasets. Unlike many techniques in the literature, RAZOR is capable of operating in both supervised and unsupervised settings. Experimental results demonstrate that RAZOR outperforms recent state-of-the-art techniques in terms of both effectiveness and efficiency., Comment: 17 pages, 3 figures

Published
2024

9. The muon beam monitor for the FAMU experiment: design, simulation, test and operation

Author

Rossini, R., Baldazzi, G., Banfi, S., Baruzzo, M., Benocci, R., Bertoni, R., Bonesini, M., Carsi, S., Cirrincione, D., Clemenza, M., Colace, L., de Bari, A., de Vecchi, C., Fasci, E., Gaigher, R., Gianfrani, L., Hillier, A. D., Ishida, K., King, P. J. C., Lord, J. S., Mazza, R., Menegolli, A., Mocchiutti, E., Monzani, S., Moretti, L., Petroselli, C., Pizzolotto, C., Prata, M. C., Pullia, M., Quintieri, L., Ramponi, R., Rossella, M., Sbrizzi, A., Toci, G., Tortora, L., Vallazza, E. S., Yokoyama, K., and Vacchi, A.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

FAMU is an INFN-led muonic atom physics experiment based at the RIKEN-RAL muon facility at the ISIS Neutron and Muon Source (United Kingdom). The aim of FAMU is to measure the hyperfine splitting in muonic hydrogen to determine the value of the proton Zemach radius with accuracy better than 1%.The experiment has a scintillating-fibre hodoscope for beam monitoring and data normalisation. In order to carry out muon flux estimation, low-rate measurements were performed to extract the single-muon average deposited charge. Then, detector simulation in Geant4 and FLUKA allowed a thorough understanding of the single-muon response function, crucial for determining the muon flux. This work presents the design features of the FAMU beam monitor, along with the simulation and absolute calibration measurements in order to enable flux determination and enable data normalisation.

Published
2024
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10. Galaxy-Galaxy Strong Lensing with U-Net (GGSL-UNet). I. Extracting 2-Dimensional Information from Multi-Band Images in Ground and Space Observations

Author

Zhong, Fucheng, Luo, Ruibiao, Napolitano, Nicola R., Tortora, Crescenzo, Li, Rui, Zhu, Xincheng, Busillo, Valerio, Koopmans, L. V. E., and Longo, Giuseppe

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present a novel deep learning method to separately extract the two-dimensional flux information of the foreground galaxy (deflector) and background system (source) of Galaxy-Galaxy Strong Lensing events using U-Net (GGSL-Unet for short). In particular, the segmentation of the source image is found to enhance the performance of the lens modeling, especially for ground-based images. By combining mock lens foreground+background components with real sky survey noise to train the GGSL-Unet, we show it can correctly model the input image noise and extract the lens signal. However, the most important result of this work is that the GGSL-UNet can accurately reconstruct real ground-based lensing systems from the Kilo Degree Survey (KiDS) in one second. We also test the GGSL-UNet on space-based (HST) lenses from BELLS GALLERY, and obtain comparable accuracy of standard lens modeling tools. Finally, we calculate the magnitudes from the reconstructed deflector and source images and use this to derive photometric redshifts (photo-z), with the photo-z of the deflector well consistent with spectroscopic ones. This first work, demonstrates the great potential of the generative network for lens finding, image denoising, source segmentation, and decomposing and modeling of strong lensing systems. For the upcoming ground- and space-based surveys, the GGSL-UNet can provide high-quality images as well as geometry and redshift information for precise lens modeling, in combination with classical MCMC modeling for best accuracy in the galaxy-galaxy strong lensing analysis., Comment: 27 pages, 19 figures. Commnets are welcome. Darft has been submitted to ApJS

Published
2024

11. Using Convolutional Neural Networks to Search for Strongly Lensed Quasars in KiDS DR5

Author

He, Zizhao, Li, Rui, Shu, Yiping, Tortora, Crescenzo, Er, Xinzhong, Canameras, Raoul, Schuldt, Stefan, Napolitano, Nicola R., N, Bharath Chowdhary, Chen, Qihang, Li, Nan, Feng, Haicheng, Deng, Limeng, Li, Guoliang, Koopmans, L. V. E., and Dvornik, Andrej

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

Gravitationally strongly lensed quasars (SL-QSO) offer invaluable insights into cosmological and astrophysical phenomena. With the data from ongoing and next-generation surveys, thousands of SL-QSO systems can be discovered expectedly, leading to unprecedented opportunities. However, the challenge lies in identifying SL-QSO from enormous datasets with high recall and purity in an automated and efficient manner. Hence, we developed a program based on a Convolutional Neural Network (CNN) for finding SL-QSO from large-scale surveys and applied it to the Kilo-degree Survey Data Release 5 (KiDS DR5). Our approach involves three key stages: firstly, we pre-selected ten million bright objects (with $r$-band $\tt{MAG\_AUTO} < 22$), excluding stars from the dataset; secondly, we established realistic training and test sets to train and fine-tune the CNN, resulting in the identification of 4195 machine candidates, and the false positive rate (FPR) of $\sim$1/2000 and recall of 0.8125 evaluated by using the real test set containing 16 confirmed lensed quasars; thirdly, human inspections were performed for further selections, and then 272 SL-QSO candidates were eventually found in total, including 16 high-score, 118 median-score, and 138 lower-score candidates, separately. Removing the systems already confirmed or identified in other papers, we end up with 229 SL-QSO candidates, including 7 high-score, 95 median-score, and 127 lower-score candidates, and the corresponding catalog is publicly available online., Comment: 11 Figures, 4 Tables. Submitted to ApJ. Comments Welcome!

Published
2024

12. INSPIRE: INvestigating Stellar Population In RElics -- VII. The local environment of ultra-compact massive galaxies

Author

Scognamiglio, Diana, Spiniello, Chiara, Radovich, Mario, Tortora, Crescenzo, Napolitano, Nicola R., Li, Rui, Maturi, Matteo, Maksymowicz-Maciata, Michalina, Cappellari, Michele, Arnaboldi, Magda, Bevacqua, Davide, Coccato, Lodovico, D'Ago, Giuseppe, Feng, Hai-Cheng, Ferré-Mateu, Anna, Hartke, Johanna, Martín-Navarro, Ignacio, and Pulsoni, Claudia

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Relic galaxies, the oldest ultra-compact massive galaxies (UCMGs), contain almost exclusively "pristine" stars formed during an intense star formation (SF) burst at high redshift. As such, they allow us to study in detail the early mechanism of galaxy assembly in the Universe. Using the largest catalogue of spectroscopically confirmed UCMGs for which a degree of relicness (DoR) had been estimated, the INSPIRE catalogue, we investigate whether or not relics prefer dense environments. The objective of this study is to determine if the DoR, which measures how extreme the SF history was, and the surrounding environment are correlated. In order to achieve this goal, we employ the AMICO galaxy cluster catalogue to compute the probability for a galaxy to be a member of a cluster, and measure the local density around each UCMG using machine learning-based photometric redshifts. We find that UCMGs can reside both in clusters and in the field, but objects with very low DoR (< 0.3, i.e., a relatively extended SF history) prefer under-dense environments. We additionally report a correlation between the DoR and the distance from the cluster centre: more extreme relics, when located in clusters, tend to occupy the more central regions of them. We finally outline potential evolution scenarios for UCMGs at different DoR to reconcile their presence in both clusters and field environments, Comment: Accepted for publication on MNRAS, 11 pages, 8 figure, 1 table

Published
2024

13. Euclid preparation. XLIX. Selecting active galactic nuclei using observed colours

Author

Euclid Collaboration, Bisigello, L., Massimo, M., Tortora, C., Fotopoulou, S., Allevato, V., Bolzonella, M., Gruppioni, C., Pozzetti, L., Rodighiero, G., Serjeant, S., Cunha, P. A. C., Gabarra, L., Feltre, A., Humphrey, A., La Franca, F., Landt, H., Mannucci, F., Prandoni, I., Radovich, M., Ricci, F., Salvato, M., Shankar, F., Stern, D., Spinoglio, L., Vergani, D., Vignali, C., Zamorani, G., Yung, L. Y. A., Charlot, S., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Battaglia, P., Bender, R., Bonino, D., Branchini, E., Brau-Nogue, S., Brescia, M., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Polenta, G., Poncet, M., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Surace, C., Tallada-Crespí, P., Taylor, A. N., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Wang, Y., Zoubian, J., Zucca, E., Biviano, A., Bozzo, E., Colodro-Conde, C., Di Ferdinando, D., Fabbian, G., Graciá-Carpio, J., Marcin, S., Mauri, N., Sakr, Z., Scottez, V., Tenti, M., Akrami, Y., Baccigalupi, C., Ballardini, M., Bethermin, M., Blanchard, A., Borgani, S., Borla, A. S., Bruton, S., Burigana, C., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Coupon, A. R. Cooray J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Ganga, K., García-Bellido, J., Giacomini, F., Gozaliasl, G., Gregorio, A., Hildebrandt, H., Muñoz, A. Jiminez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mainetti, G., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Patrizii, L., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sereno, M., Simon, P., Stadel, J., Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Viel, M., and Zinchenko, I. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Euclid will cover over 14000 $deg^{2}$ with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution and AGN. In this work we identify the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin legacy survey of space and time (LSST) and observations already available from Spitzer/IRAC. The analysis is performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We make use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these catalogues we estimate the best colour selection, maximising the harmonic mean (F1) of completeness and purity. The selection of unobscured AGN in both Euclid surveys is possible with Euclid photometry alone with F1=0.22-0.23, which can increase to F1=0.43-0.38 if we limit at z>0.7. Such selection is improved once the Rubin/LSST filters (a combination of the u, g, r, or z filters) are considered, reaching F1=0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]-[4.5] colour, which is possible only in the EDS, results in an F1-score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST. The selection of composite ($f_{{\rm AGN}}$=0.05-0.65 at 8-40 $\mu m$) and obscured AGN is challenging, with F1<0.3 even when including ancillary data. This is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3-5 $\mu m$., Comment: 25 pages, 28 figures, accepted for publication on A&A

Published
2024

14. 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

15. The 'Yes, Magellanic Clouds Again' survey: preliminary results

Author

Gatto, M., Ripepi, V., Tosi, M., Bellazzini, M., Cignoni, M., Tortora, C., and Dall'Ora, M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present preliminary findings from the photometric survey "Yes, Magellanic Clouds Again" (YMCA, PI: V. Ripepi), covering 110 square degrees in the outer regions of the Magellanic Clouds (MCs), a pair of interacting galaxies and the most massive dwarf satellites of the Milky Way. %The survey achieves a notable photometric depth, allowing us to resolve faint, old stellar populations. Among the key results, we discovered four star clusters (SCs) within the Large Magellanic Cloud (LMC) exhibiting ages within the so-called "age gap", a period deemed so far devoid of SCs. Additionally, we unveiled an ancient stellar system associated with the LMC, featuring structural properties in between the globular clusters and the ultra-faint dwarf galaxies of the Local Group. These discoveries significantly contribute to our understanding of the MCs' evolution and their complex interaction history., Comment: 5 Pages, 1 figure, accepted for publication in "Il Nuovo Cimento - Colloquia and Communications in Physics."

Published
2024

16. Ephemeris Reconstruction for Comet 67P/Churyumov-Gerasimenko During Rosetta Proximity Phase from Radiometric Data Analysis

Author

Manghi, Riccardo Lasagni, Zannoni, Marco, Tortora, Paolo, Budnik, Frank, Godard, Bernard, and Attree, Nicholas

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

This study provides a continuous ephemeris reconstruction for comet 67P/Churyumov-Gerasimenko by reanalyzing Rosetta radiometric measurements and Earth-based astrometry. Given the comet-to-spacecraft relative trajectory provided by the navigation team, these measurements were used to estimate the comet state and some critical physical parameters, most notably the non-gravitational accelerations induced by the outgassing of surface volatiles, for which different models were tested and compared. The reference reconstructed ephemeris, which uses a stochastic acceleration model, has position uncertainties below 10 km, 30 km, and 80 km in the orbital radial, tangential, and normal directions for the whole duration of the Rosetta proximity phase (from July 2014 to October 2016). Furthermore, the solution can fit ground-based astrometry between March 2010 and July 2018, covering a complete heliocentric orbit of 67P. The estimated comet non-gravitational accelerations are dominated by the orbital radial and normal components, reaching peak values of $(1.28 \pm 0.17) \times 10^{-8} \, \text{m/s}^2$ and $(0.52 \pm 0.20) \times 10^{-8} \, \text{m/s}^2$, respectively 15 days and 24 days after perihelion. Furthermore, the acceleration magnitude is shown to have a steep dependence on the comet heliocentric distance $\text{NGA} \sim r_\odot^{-6}$ and shows asymmetries in the pre- and post-perihelion activities. The estimated acceleration components, agnostic due to the limited physical assumptions, could be used as a constraint for future investigations involving high-fidelity thermophysical models of the comet surface., Comment: Preprint version of conference proceeding for the 2024 AAS/AIAA Astrodynamics Specialist Conference (#AAS24-331)

Published
2024

17. Interim report for the International Muon Collider Collaboration (IMCC)

Author

Accettura, C., Adrian, S., Agarwal, R., Ahdida, C., Aimé, C., Aksoy, A., Alberghi, G. L., Alden, S., Amapane, N., Amorim, D., Andreetto, P., Anulli, F., Appleby, R., Apresyan, A., Asadi, P., Mahmoud, M. Attia, Auchmann, B., Back, J., Badea, A., Bae, K. J., Bahng, E. J., Balconi, L., Balli, F., Bandiera, L., Barbagallo, C., Barlow, R., Bartoli, C., Bartosik, N., Barzi, E., Batsch, F., Bauce, M., Begel, M., Berg, J. S., Bersani, A., Bertarelli, A., Bertinelli, F., Bertolin, A., Bhat, P., Bianchi, C., Bianco, M., Bishop, W., Black, K., Boattini, F., Bogacz, A., Bonesini, M., Bordini, B., de Sousa, P. Borges, Bottaro, S., Bottura, L., Boyd, S., Breschi, M., Broggi, F., Brunoldi, M., Buffat, X., Buonincontri, L., Burrows, P. N., Burt, G. C., Buttazzo, D., Caiffi, B., Calatroni, S., Calviani, M., Calzaferri, S., Calzolari, D., Cantone, C., Capdevilla, R., Carli, C., Carrelli, C., Casaburo, F., Casarsa, M., Castelli, L., Catanesi, M. G., Cavallucci, L., Cavoto, G., Celiberto, F. G., Celona, L., Cemmi, A., Ceravolo, S., Cerri, A., Cerutti, F., Cesarini, G., Cesarotti, C., Chancé, A., Charitonidis, N., Chiesa, M., Chiggiato, P., Ciccarella, V. L., Puviani, P. Cioli, Colaleo, A., Colao, F., Collamati, F., Costa, M., Craig, N., Curtin, D., D'Angelo, L., Da Molin, G., Damerau, H., Dasu, S., de Blas, J., De Curtis, S., De Gersem, H., Del Moro, T., Delahaye, J. -P., Denisov, D., Denizli, H., Dermisek, R., Valdor, P. Desiré, Desponds, C., Di Luzio, L., Di Meco, E., Di Petrillo, K. F., Di Sarcina, I., Diociaiuti, E., Dorigo, T., Dreimanis, K., Pree, T. du, Edgecock, T., Fabbri, S., Fabbrichesi, M., Farinon, S., Ferrand, G., Somoza, J. A. Ferreira, Fieg, M., Filthaut, F., Fox, P., Franceschini, R., Ximenes, R. Franqueira, Gallinaro, M., Garcia-Sciveres, M., Garcia-Tabares, L., Gargiulo, R., Garion, C., Garzelli, M. V., Gast, M., Gerber, C. E., Giambastiani, L., Gianelle, A., Gianfelice-Wendt, E., Gibson, S., Gilardoni, S., Giove, D. A., Giovinco, V., Giraldin, C., Glioti, A., Gorzawski, A., Greco, M., Grojean, C., Grudiev, A., Gschwendtner, E., Gueli, E., Guilhaudin, N., Han, C., Han, T., Hauptman, J. M., Herndon, M., Hillier, A. D., Hillman, M., Holmes, T. R., Homiller, S., Jana, S., Jindariani, S., Johannesson, S., Johnson, B., Jones, O. R., Jurj, P. -B., Kahn, Y., Kamath, R., Kario, A., Karpov, I., Kelliher, D., Kilian, W., Kitano, R., Kling, F., Kolehmainen, A., Kong, K. C., Kosse, J., Krintiras, G., Krizka, K., Kumar, N., Kvikne, E., Kyle, R., Laface, E., Lane, K., Latina, A., Lechner, A., Lee, J., Lee, L., Lee, S. W., Lefevre, T., Leonardi, E., Lerner, G., Li, P., Li, Q., Li, T., Li, W., Voti, R. Li, Lindroos, M., Lipton, R., Liu, D., Liu, M., Liu, Z., Lombardi, A., Lomte, S., Long, K., Longo, L., Lorenzo, J., Losito, R., Low, I., Lu, X., Lucchesi, D., Luo, T., Lupato, A., Métral, E., Mękała, K., Ma, Y., Mańczak, J. M., Machida, S., Madlener, T., Magaletti, L., Maggi, M., Durand, H. Mainaud, Maltoni, F., Mandurrino, M., Marchand, C., Mariani, F., Marin, S., Mariotto, S., Martin-Haugh, S., Masullo, M. R., Mauro, G. S., Mazzolari, A., Mele, B., Meloni, F., Meng, X., Mentink, M., Miceli, R., Milas, N., Mohammadi, A., Moll, D., Montella, A., Morandin, M., Morrone, M., Mulder, T., Musenich, R., Nardecchia, M., Nardi, F., Neuffer, D., Newbold, D., Novelli, D., Olvegård, M., Onel, Y., Orestano, D., Osborne, J., Otten, S., Torres, Y. M. Oviedo, Paesani, D., Griso, S. Pagan, Pagani, D., Pal, K., Palmer, M., Pampaloni, A., Panci, P., Pani, P., Papaphilippou, Y., Paparella, R., Paradisi, P., Passeri, A., Pastrone, N., Pellecchia, A., Piccinini, F., Piekarz, H., Pieloni, T., Plouin, J., Portone, A., Potamianos, K., Potdevin, J., Prestemon, S., Puig, T., Qiang, J., Quettier, L., Rabemananjara, T. R., Radicioni, E., Radogna, R., Rago, I. C., Ratkus, A., Resseguie, E., Reuter, J., Ribani, P. L., Riccardi, C., Ricciardi, S., Robens, T., Robert, Y., Roger, C., Rojo, J., Romagnoni, M., Ronald, K., Rosser, B., Rossi, C., Rossi, L., Rozanov, L., Ruhdorfer, M., Ruiz, R., Queiroz, F. S., Saini, S., Sala, F., Salierno, C., Salmi, T., Salvini, P., Salvioni, E., Sammut, N., Santini, C., Saputi, A., Sarra, I., Scarantino, G., Schneider-Muntau, H., Schulte, D., Scifo, J., Sen, T., Senatore, C., Senol, A., Sertore, D., Sestini, L., Rêgo, R. C. Silva, Simone, F. M., Skoufaris, K., Sorbello, G., Sorbi, M., Sorti, S., Soubirou, L., Spataro, D., Stamerra, A., Stapnes, S., Stark, G., Statera, M., Stechauner, B. M., Su, S., Su, W., Sun, X., Sytov, A., Tang, J., Taylor, R., Kate, H. Ten, Testoni, P., Thiele, L. S., Garcia, R. Tomas, Mugglestone, M. Topp, Torims, T., Torre, R., Tortora, L. T., Trifinopoulos, S., Udongwo, S. -A., Vai, I., Valente, R. U., van Rienen, U., van Weelderen, R., Vanwelde, M., Velev, G., Venditti, R., Vendrasco, A., Verna, A., Verweij, A., Verwilligen, P., Villamzar, Y., Vittorio, L., Vitulo, P., Vojskovic, I., Wang, D., Wang, L. -T., Wang, X., Wendt, M., Widorski, M., Wozniak, M., Wu, Y., Wulzer, A., Xie, K., Yang, Y., Yap, Y. C., Yonehara, K., Yoo, H. D., You, Z., Zanetti, M., Zaza, A., Zhang, L., Zhu, R., Zlobin, A., Zuliani, D., and Zurita, J. F.

Subjects
Physics - Accelerator Physics, High Energy Physics - Experiment
Abstract

The International Muon Collider Collaboration (IMCC) [1] was established in 2020 following the recommendations of the European Strategy for Particle Physics (ESPP) and the implementation of the European Strategy for Particle Physics-Accelerator R&D Roadmap by the Laboratory Directors Group [2], hereinafter referred to as the the European LDG roadmap. The Muon Collider Study (MuC) covers the accelerator complex, detectors and physics for a future muon collider. In 2023, European Commission support was obtained for a design study of a muon collider (MuCol) [3]. This project started on 1st March 2023, with work-packages aligned with the overall muon collider studies. In preparation of and during the 2021-22 U.S. Snowmass process, the muon collider project parameters, technical studies and physics performance studies were performed and presented in great detail. Recently, the P5 panel [4] in the U.S. recommended a muon collider R&D, proposed to join the IMCC and envisages that the U.S. should prepare to host a muon collider, calling this their "muon shot". In the past, the U.S. Muon Accelerator Programme (MAP) [5] has been instrumental in studies of concepts and technologies for a muon collider., Comment: This document summarises the International Muon Collider Collaboration (IMCC) progress and status of the Muon Collider R&D programme

Published
2024

18. State-dependent mobility edge in kinetically constrained models

Author

Badbaria, Manthan, Pancotti, Nicola, Singh, Rajeev, Marino, Jamir, and Valencia-Tortora, Riccardo J.

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Disordered Systems and Neural Networks, Quantum Physics
Abstract

In this work, we show that the kinetically constrained quantum East model lies between a quantum scarred and a many-body localized system featuring an unconventional type of mobility edge in the spectrum. We name this scenario $\textit{state-dependent}$ mobility edge: while the system does not exhibit a sharp separation in energy between thermal and non-thermal eigenstates, the abundance of non-thermal eigenstates results in slow entanglement growth for $\textit{many}$ initial states, such as product states, below a finite energy density. We characterize the state-dependent mobility edge by looking at the complexity of classically simulating dynamics using tensor network for system sizes well beyond those accessible via exact diagonalization. Focusing on initial product states, we observe a qualitative change in the dynamics of the bond dimension needed as a function of their energy density. Specifically, the bond dimension typically grows $\textit{polynomially}$ in time up to a certain energy density, where we locate the state-dependent mobility edge, enabling simulations for long times. Above this energy density, the bond dimension typically grows $\textit{exponentially}$ making the simulation practically unfeasible beyond short times, as generally expected in interacting theories. We correlate the polynomial growth of the bond dimension to the presence of many non-thermal eigenstates around that energy density, a subset of which we compute via tensor network., Comment: 12+3 pages; 8+5 figures

Published
2024

19. A new perspective on the stellar Mass-Metallicity Relation of quiescent galaxies from the LEGA-C survey

Author

Bevacqua, D., Saracco, P., Boecker, A., D'Ago, G., De Lucia, G., De Propris, R., La Barbera, F., Pasquali, A., Spiniello, C., and Tortora, C.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We investigate the stellar Mass-Metallicity Relation (MZR) using a sample of 637 quiescent galaxies with 10.4 <= log(M*/M ) < 11.7 selected from the LEGA-C survey at 0.6 <= z <= 1. We derive mass-weighted stellar metallicities using full-spectral fitting. We find that while lower-mass galaxies are both metal -rich and -poor, there are no metal-poor galaxies at high masses, and that metallicity is bounded at low values by a mass-dependent lower limit. This lower limit increases with mass, empirically defining a MEtallicity-Mass Exclusion (MEME) zone. We find that the spectral index MgFe = \sqrt{Mgb \times Fe4383}, a proxy for the stellar metallicity, also shows a mass-dependent lower limit resembling the MEME relation. Crucially, MgFe is independent of stellar population models and fitting methods. By constructing the Metallicity Enrichment Histories, we find that, after the first Gyr, the Star Formation History of galaxies has a mild impact on the observed metallicity distribution. Finally, from the average formation times, we find that galaxies populate differently the metallicity-mass plane at different cosmic times, and that the MEME limit is recovered by galaxies that formed at z >= 3. Our work suggests that the stellar metallicity of quiescent galaxies is bounded by a lower limit which increases with the stellar mass. On the other hand, low-mass galaxies can have metallicities as high as galaxies ~1 dex more massive. This suggests that, at log(M*/M ) >= 10.4, rather than lower-mass galaxies being systematically less metallic, the observed MZR might be a consequence of the lack of massive, metal-poor galaxies., Comment: Accepted for publication in A&A

Published
2024
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20. Euclid preparation. LI. Forecasting the recovery of galaxy physical properties and their relations with template-fitting and machine-learning methods

Author

Euclid Collaboration, Enia, A., Bolzonella, M., Pozzetti, L., Humphrey, A., Cunha, P. A. C., Hartley, W. G., Dubath, F., Paltani, S., Lopez, X. Lopez, Quai, S., Bardelli, S., Bisigello, L., Cavuoti, S., De Lucia, G., Ginolfi, M., Grazian, A., Siudek, M., Tortora, C., Zamorani, G., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Castignani, G., Cimatti, A., Colodro-Conde, C., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Gillis, B., Giocoli, C., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., 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., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Neissner, C., Niemi, S. -M., Nightingale, J. W., Padilla, C., Pasian, F., Pedersen, K., Pettorino, V., Polenta, G., Poncet, M., Popa, L. A., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sapone, D., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Surace, C., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Zucca, E., Biviano, A., Boucaud, A., Burigana, C., Calabrese, M., Vigo, J. A. Escartin, Gracia-Carpio, J., Mauri, N., Pezzotta, A., Pöntinen, M., Porciani, C., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bergamini, P., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Bruton, S., Cabanac, R., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Contini, T., Cooray, A. R., Cucciati, O., Davini, S., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrari, A. G., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gianotti, F., Gozaliasl, G., Hall, A., Hemmati, S., Hildebrandt, H., Hjorth, J., Muñoz, A. Jimenez, Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Graet, J. Le, Legrand, L., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Walton, Nicholas A., Patrizii, L., Popa, V., Potter, D., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Schultheis, M., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Tanidis, K., Tao, C., Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., Verza, G., Zinchenko, I. A., Rodighiero, G., and Talia, M.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Euclid will collect an enormous amount of data during the mission's lifetime, observing billions of galaxies in the extragalactic sky. Along with traditional template-fitting methods, numerous machine learning algorithms have been presented for computing their photometric redshifts and physical parameters (PPs), requiring significantly less computing effort while producing equivalent performance measures. However, their performance is limited by the quality and amount of input information, to the point where the recovery of some well-established physical relationships between parameters might not be guaranteed. To forecast the reliability of Euclid photo-$z$s and PPs calculations, we produced two mock catalogs simulating Euclid photometry. We simulated the Euclid Wide Survey (EWS) and Euclid Deep Fields (EDF). We tested the performance of a template-fitting algorithm (Phosphoros) and four ML methods in recovering photo-$z$s, PPs (stellar masses and star formation rates), and the SFMS. To mimic the Euclid processing as closely as possible, the models were trained with Phosphoros-recovered labels. For the EWS, we found that the best results are achieved with a mixed labels approach, training the models with wide survey features and labels from the Phosphoros results on deeper photometry, that is, with the best possible set of labels for a given photometry. This imposes a prior, helping the models to better discern cases in degenerate regions of feature space, that is, when galaxies have similar magnitudes and colors but different redshifts and PPs, with performance metrics even better than those found with Phosphoros. We found no more than 3% performance degradation using a COSMOS-like reference sample or removing u band data, which will not be available until after data release DR1. The best results are obtained for the EDF, with appropriate recovery of photo-$z$, PPs, and the SFMS., Comment: 26 pages, 13 figures. Accepted for publication on A&A

Published
2024
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21. The YMCA (Yes, Magellanic Clouds Again) survey: probing the outer regions of the Magellanic system with VST

Author

Gatto, Massimiliano, Ripepi, Vincenzo, Bellazzini, Michele, Tosi, Monica, Cignoni, Michele, Tortora, Crescenzo, Marconi, Marcella, Dall'Ora, Massimo, Cioni, Maria-Rosa L., Musella, Ilaria, Schipani, Pietro, and Spavone, Marilena

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Magellanic Clouds (MCs) are the Milky Way's most massive dwarf satellites. As they also represent the closest pair of galaxies in an ongoing tidal interaction, while simultaneously infalling into the Milky Way halo, they provide a unique opportunity to study in detail an ongoing three-body encounter. We present the ``YMCA (Yes, Magellanic Clouds Again) survey: probing the outer regions of the Magellanic system with VST'' based on deep optical photometry carried out with the VLT Survey Telescope (VST). YMCA targeted 110 square degrees, in the g and i filters, in the periphery of both the MCs, including a long strip in between the Large Magellanic Cloud (LMC) and the Small Magellanic Cloud (SMC). The photometry of YMCA is sufficiently deep (50\% complete down to $g \simeq 23.5-24.0$~mag) to allow for a detailed analysis of main-sequence stars in regions of the MCs remained relatively unexplored at these faint magnitudes. The resulting colour-magnitude diagrams reveal that the outskirts of the MCs are predominantly characterized by intermediate-age and old stellar populations, with limited or negligible evidence of recent star formation. The analysis of the age distribution of star clusters (SCs) within the surveyed area, both already known and newly discovered candidates, hints at a close fly-by between the LMC and SMC that occurred $\simeq 2.5-3.0$~Gyr ago, in agreement with previous results. We also report the discovery of candidate SCs with ages within the so-called ``age-gap'', questioning its real existence., Comment: 28 pages, 21 figures. Accepted for publication on A&A

Published
2024
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22. The CUbesat Solar Polarimeter (CUSP) mission overview

Author

Fabiani, Sergio, Del Monte, Ettore, Baffo, Ilaria, Bonomo, Sergio, Brienza, Daniele, Campana, Riccardo, Centrone, Mauro, Contini, Gessica, Costa, Enrico, Cucinella, Giovanni, Curatolo, Andrea, De Angelis, Nicolas, De Cesare, Giovanni, Del Re, Andrea, Di Cosimo, Sergio, Di Filippo, Simone, Di Marco, Alessandro, Di Persio, Giuseppe, Donnarumma, Immacolata, Fanelli, Pierluigi, Leonetti, Paolo, Locarini, Alfredo, Loffredo, Pasqualino, Lombardi, Giovanni, Minervini, Gabriele, Modenini, Dario, Muleri, Fabio, Natalucci, Silvia, Negri, Andrea, Perelli, Massimo, Rossi, Monia, Rubini, Alda, Scalise, Emanuele, Soffitta, Paolo, Terracciano, Andrea, Tortora, Paolo, Zaccagnino, Emauele, and Zambardi, Alessandro

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

The CUbesat Solar Polarimeter (CUSP) project is a future CubeSat mission orbiting the Earth aimed to measure the linear polarization of solar flares in the hard X-ray band, by means of a Compton scattering polarimeter. CUSP will allow us to study the magnetic reconnection and particle acceleration in the flaring magnetic structures of our star. The project is in the framework of the Italian Space Agency Alcor Program, which aims to develop new CubeSat missions. CUSP is approved for a Phase B study that will last for 12 months, starting in mid-2024. We report on the current status of the CUSP mission project as the outcome of the Phase A., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024. arXiv admin note: substantial text overlap with arXiv:2208.06211

Published
2024

23. Characterization of avalanche photodiodes (APDs) for the CUbesat Solar Polarimeter (CUSP) mission

Author

Cologgi, F., Alimenti, A., Fabiani, S., Torokthii, K., Silva, E., Del Monte, E., Baffo, I., Bonomo, S., Brienza, D., Campana, R., Centrone, M., Contini, G., Costa, E., Curatolo, A., Cucinella, G., DevAngelis, N., De Cesare, G., Del Re, A., Di Cosimo, S., Di Filippo, S., Di Marco, A., Di Persio, G., Donnarumma, I., Fanelli, P., Leonetti, P., Locarini, A., Loffredo, P., Lombardi, G., Minervini, G., Modenini, D., Muleri, F., Natalucci, S., Nigri, A., Perelli, M., Rossi, M., Rubini, A., Scalise, E., Soffitta, P., Terracciano, C., Tortora, P., Zaccagnino, E., and Zambardi, A.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

The CUbesat Solar Polarimeter (CUSP) project is a CubeSat mission orbiting the Earth aimed to measure the linear polarization of solar flares in the hard X-ray band by means of a Compton scattering polarimeter. CUSP will allow the study of the magnetic reconnection and particle acceleration in the flaring magnetic structures of our star. CUSP is a project in the framework of the Alcor Program of the Italian Space Agency aimed at developing new CubeSat missions. It is approved for a Phase B study. In this work, we report on the characterization of the Avalanche Photodiodes (APDs) that will be used as readout sensors of the absorption stage of the Compton polarimeter. We assessed the APDs gain and energy resolution as a function of temperature by irradiating the sensor with a \textsuperscript{55}Fe radioactive source. Moreover, the APDs were also characterized as being coupled to a GAGG scintillator., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024

Published
2024

24. The multi$-$physics analysis and design of CUSP, a two CubeSat constellation for Space Weather and Solar flares X-ray polarimetry

Author

Lombardi, Giovanni, Fabiani, Sergio, Del Monte, Ettore, Costa, Enrico, Soffitta, Paolo, Muleri, Fabio, Baffo, Ilaria, Biancolini, Marco E., Bonomo, Sergio, Brienza, Daniele, Campana, Riccardo, Centrone, Mauro, Contini, Gessica, Cucinella, Giovanni, Curatolo, Andrea, De Angelis, Nicolas, De Cesare, Giovanni, Del Re, Andrea, Di Cosimo, Sergio, Di Filippo, Simone, Di Marco, Alessandro, Di Meo, Emanuele, Di Persio, Giuseppe, Donnarumma, Immacolata, Fanelli, Pierluigi, Leonetti, Paolo, Locarini, Alfredo, Loffredo, Pasqualino, Lopez, Andrea, Minervini, Gabriele, Modenini, Dario, Natalucci, Silvia, Negri, Andrea, Perelli, Massimo, Rossi, Monia, Rubini, Alda, Scalise, Emanuele, Terracciano, Andrea, Tortora, Paolo, Zaccagnino, Emanuele, and Zambardi, Alessandro

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

The CUbesat Solar Polarimeter (CUSP) project aims to develop a constellation of two CubeSats orbiting the Earth to measure the linear polarization of solar flares in the hard X-ray band by means of a Compton scattering polarimeter on board of each satellite. CUSP will allow to study the magnetic reconnection and particle acceleration in the flaring magnetic structures. CUSP is a project approved for a Phase B study by the Italian Space Agency in the framework of the Alcor program aimed to develop CubeSat technologies and missions. In this paper we describe the a method for a multi-physical simulation analysis while analyzing some possible design optimization of the payload design solutions adopted. In particular, we report the mechanical design for each structural component, the results of static and dynamic finite element analysis, the preliminary thermo-mechanical analysis for two specific thermal cases (hot and cold orbit) and a topological optimization of the interface between the platform and the payload., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024

Published
2024

25. The evaluation of the CUSP scientific performance by a GEANT4 Monte Carlo simulation

Author

De Cesare, Giovanni, Fabiani, Sergio, Campana, Riccardo, Lombardi, Giovanni, Del Monte, Ettore, Costa, Enrico, Baffo, Ilaria, Bonomo, Sergio, Brienza, Daniele, Centrone, Mauro, Contini, Gessica, Cucinella, Giovanni, Curatolo, Andrea, De Angelis, Nicolas, Del Re, Andrea, Di Cosimo, Sergio, Di Filippo, Simone, Di Marco, Alessandro, Di Persio, Giuseppe, Donnarumma, Immacolata, Fanelli, Pierluigi, Leonetti, Paolo, Locarini, Alfredo, Loffredo, Pasqualino, Minervini, Gabriele, Modenini, Dario, Muleri, Fabio, Natalucci, Silvia, Negri, Andrea, Perelli, Massimo, Rossi, Monia, Rubini, Alda, Scalise, Emanuele, Soffitta, Paolo, Terracciano, Andrea, Tortora, Paolo, Zaccagnino, Emauele, and Zambardi, Alessandro

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

The CUbesat Solar Polarimeter (CUSP) project is a CubeSat mission orbiting the Earth aimed to measure the linear polarization of solar flares in the hard X-ray band by means of a Compton scattering polarimeter. CUSP will allow to study the magnetic reconnection and particle acceleration in the flaring magnetic structures of our star. CUSP is a project in the framework of the Alcor Program of the Italian Space Agency aimed to develop new CubeSat missions. It is approved for a Phase B study. In this work, we report on the accurate simulation of the detector's response to evaluate the scientific performance. A GEANT4 Monte Carlo simulation is used to assess the physical interactions of the source photons with the detector and the passive materials. Using this approach, we implemented a detailed CUSP Mass Model. In this work, we report on the evaluation of the detector's effective area as a function of the beam energy., Comment: Proceeding of SPIE Conference "Astronomical Telescopes+ Instrumentation", Yokohama (Japan), 16-21 June 2024

Published
2024

29. Gapless dynamic magnetic ground state in the charge-gapped trimer iridate Ba$_4$NbIr$_3$O$_{12}$

Author

Bandyopadhyay, Abhisek, Lee, S., Adroja, D. T., Lees, M. R., Stenning, G. B. G., Aich, P., Tortora, Luca, Meneghini, C., Cibin, G., Berlie, Adam, Saha, R. A., Takegami, D., Melendez-Sans, A., Poelchen, G., Yoshimura, M., Tsuei, K. D., Hu, Z., Chan, Ting-Shan, Chattopadhyay, S., Thakur, G. S., and Choi, Kwang-Yong

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

We present an experimental investigation of the magnetic ground state in Ba$_4$NbIr$_3$O$_{12}$, a fractional valent trimer iridate. X-ray absorption and photoemission spectroscopy show that the Ir valence lies between 3+ and 4+ while Nb is pentavalent. Combined dc/ac magnetization, specific heat, and muon spin rotation/relaxation ($\mu$SR) measurements reveal no magnetic phase transition down to 0.05~K. Despite a significant Weiss temperature ($\Theta_{\mathrm{W}} \sim -15$ to $-25$~K) indicating antiferromagnetic correlations, a quantum spin-liquid (QSL) phase emerges and persists down to 0.1~K. This state likely arises from geometric frustration in the edge-sharing equilateral triangle Ir network. Our $\mu$SR analysis reveals a two-component depolarization, arising from the coexistence of rapidly (90\%) and slowly (10\%) fluctuating Ir moments. Powder x-ray diffraction and Ir-L$_3$edge x-ray absorption fine structure spectroscopy identify ~8-10\% Nb/Ir site-exchange, reducing frustration within part of the Ir network, and likely leading to the faster muon spin relaxation, while the structurally ordered Ir ions remain highly geometrically frustrated, giving rise to the rapidly spin-fluctuating QSL ground state. At low temperatures, the magnetic specific heat varies as $\gamma T + \alpha T^2$, indicating gapless spinon excitations, and possible Dirac QSL features with linear spinon dispersion, respectively., Comment: 27 pages, 15 figures

Published
2024

30. Retrieval of the physical parameters of galaxies from WEAVE-StePS-like data using machine learning

Author

Angthopo, J., Granett, B. R., La Barbera, F., Longhetti, M., Iovino, A., Fossati, M., Ditrani, F. R., Costantin, L., Zibetti, S., Gallazzi, A., Sánchez-Blázquez, P., Tortora, C., Spiniello, C., Poggianti, B., Vazdekis, A., Balcells, M., Bardelli, S., Benn, C. R., Bianconi, M., Bolzonella, M., Busarello, G., Cassarà, L. P., Corsini, E. M., Cucciati, O., Dalton, G., Ferré-Mateu, A., García-Benito, R., Delgado, R. M. González, Gafton, E., Gullieuszik, M., Haines, C. P., Iodice, E., Ikhsanova, A., Jin, S., Knapen, J. H., McGee, S., Mercurio, A., Merluzzi, P., Morelli, L., Moretti, A., Murphy, D. N. A., Pizzella, A., Pozzetti, L., Ragusa, R., Trager, S. C., Vergani, D., Vulcani, B., Talia, M., and Zucca, E.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The WHT Enhanced Area Velocity Explorer (WEAVE) is a new, massively multiplexing spectrograph. This new instrument will be exploited to obtain high S/N spectra of $\sim$25000 galaxies at intermediate redshifts for the WEAVE Stellar Population Survey (WEAVE-StePS). We test machine learning methods for retrieving the key physical parameters of galaxies from WEAVE-StePS-like spectra using both photometric and spectroscopic information at various S/Ns and redshifts. We simulated $\sim$105000 galaxy spectra assuming SFH with an exponentially declining star formation rate, covering a wide range of ages, stellar metallicities, sSFRs, and dust extinctions. We then evaluated the ability of the random forest and KNN algorithms to correctly predict such parameters assuming no measurement errors. We checked how much the predictive ability deteriorates for different S/Ns and redshifts, finding that both algorithms still accurately estimate the ages and metallicities with low bias. The dispersion varies from 0.08-0.16 dex for ages and 0.11-0.25 dex for metallicity, depending on the redshift and S/N. For dust attenuation, we find a similarly low bias and dispersion. For the sSFR, we find a very good constraining power for star-forming galaxies, log sSFR$\gtrsim$ -11, where the bias is $\sim$ 0.01 dex and the dispersion is $\sim$ 0.10 dex. For more quiescent galaxies, with log sSFR$\lesssim$ -11, we find a higher bias, 0.61-0.86 dex, and a higher dispersion, $\sim$ 0.4 dex, for different S/Ns and redshifts. Generally, we find that the RF outperforms the KNN. Finally, the retrieved sSFR was used to successfully classify galaxies as part of the blue cloud, green valley, or red sequence. We demonstrate that machine learning algorithms can accurately estimate the physical parameters of simulated galaxies even at relatively low S/N=10 per angstrom spectra with available ancillary photometric information., Comment: 19 pages, 10 + 2 figures, 4 tables, accepted in A&A

Published
2024

31. Euclid preparation. LVIII. Detecting globular clusters in the Euclid survey

Author

Euclid Collaboration, Voggel, K., Lançon, A., Saifollahi, T., Larsen, S. S., Cantiello, M., Rejkuba, M., Cuillandre, J. -C., Hudelot, P., Nucita, A. A., Urbano, M., Romelli, E., Raj, M. A., Schirmer, M., Tortora, C., Abdurro'uf, Annibali, F., Baes, M., Boldrini, P., Cabanac, R., Carollo, D., Conselice, C. J., Duc, P. -A., Ferguson, A. M. N., Hunt, L. K., Knapen, J. H., Lonare, P., Marleau, F. R., Paolillo, M., Poulain, M., Sánchez-Janssen, R., Sola, E., Andreon, S., Auricchio, N., Baccigalupi, C., Baldi, M., Bardelli, S., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carlberg, R. G., Carretero, J., Casas, S., Castellano, M., Castignani, G., Cavuoti, S., Cimatti, A., Colodro-Conde, C., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., 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., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., George, K., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Haugan, S. V. H., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kohley, R., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Liebing, P., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinelli, M., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., 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., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Renzi, A., Rhodes, J., Riccio, G., Roncarelli, M., Rossetti, E., Saglia, R., Sakr, Z., Sapone, D., Sartoris, B., Scaramella, R., Schneider, P., Schrabback, T., Secroun, A., Sefusatti, E., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Steinwagner, J., Surace, C., Tallada-Crespí, P., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zamorani, G., Zucca, E., Biviano, A., Bolzonella, M., Bozzo, E., Burigana, C., Calabrese, M., Di Ferdinando, D., Vigo, J. A. Escartin, Farinelli, R., Gracia-Carpio, J., Mauri, N., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Ballardini, M., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Bruton, S., Calabro, A., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castro, T., Chambers, K. C., Contarini, S., Cooray, A. R., De Caro, B., Desprez, G., Díaz-Sánchez, A., Di Domizio, S., Dole, H., Escoffier, S., Ferrero, I., Finelli, F., Fornari, F., Gabarra, L., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Giacomini, F., Gozaliasl, G., Hall, A., Hildebrandt, H., Hjorth, J., Ilbert, O., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Libet, G., Loureiro, A., Macias-Perez, J., Maggio, G., Magliocchetti, M., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., Metcalf, R. B., Monaco, P., Moretti, C., Morgante, G., Walton, Nicholas A., Patrizii, L., Pezzotta, A., Pöntinen, M., Popa, V., Porciani, C., Potter, D., Reimberg, P., Risso, I., Rocci, P. -F., Sahlén, M., Schneider, A., Sereno, M., Simon, P., Mancini, A. Spurio, Testera, G., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valiviita, J., Vergani, D., Verza, G., Zinchenko, I. A., Mamon, G. A., and Scott, D.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Extragalactic globular clusters (EGCs) are an abundant and powerful tracer of galaxy dynamics and formation, and their own formation and evolution is also a matter of extensive debate. The compact nature of globular clusters means that they are hard to spatially resolve and thus study outside the Local Group. In this work we have examined how well EGCs will be detectable in images from the Euclid telescope, using both simulated pre-launch images and the first early-release observations of the Fornax galaxy cluster. The Euclid Wide Survey will provide high-spatial resolution VIS imaging in the broad IE band as well as near-infrared photometry (YE, JE, and HE). We estimate that the galaxies within 100 Mpc in the footprint of the Euclid survey host around 830 000 EGCs of which about 350 000 are within the survey's detection limits. For about half of these EGCs, three infrared colours will be available as well. For any galaxy within 50Mpc the brighter half of its GC luminosity function will be detectable by the Euclid Wide Survey. The detectability of EGCs is mainly driven by the residual surface brightness of their host galaxy. We find that an automated machine-learning EGC-classification method based on real Euclid data of the Fornax galaxy cluster provides an efficient method to generate high purity and high completeness GC candidate catalogues. We confirm that EGCs are spatially resolved compared to pure point sources in VIS images of Fornax. Our analysis of both simulated and first on-sky data show that Euclid will increase the number of GCs accessible with high-resolution imaging substantially compared to previous surveys, and will permit the study of GCs in the outskirts of their hosts. Euclid is unique in enabling systematic studies of EGCs in a spatially unbiased and homogeneous manner and is primed to improve our understanding of many understudied aspects of GC astrophysics., Comment: Accepted in A&A

Published
2024

32. Euclid: Early Release Observations -- Dwarf galaxies in the Perseus galaxy cluster

Author

Marleau, F. R., Cuillandre, J. -C., Cantiello, M., Carollo, D., Duc, P. -A., Habas, R., Hunt, L. K., Jablonka, P., Mirabile, M., Mondelin, M., Poulain, M., Saifollahi, T., Sánchez-Janssen, R., Sola, E., Urbano, M., Zöller, R., Bolzonella, M., Lançon, A., Laureijs, R., Marchal, O., Schirmer, M., Stone, C., Boselli, A., Ferré-Mateu, A., Hatch, N. A., Kluge, M., Montes, M., Sorce, J. G., Tortora, C., Venhola, A., Golden-Marx, J. B., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Battaglia, P., Bender, R., Bodendorf, C., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Duncan, C. A. J., Dupac, X., Dusini, S., Ealet, A., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Fotopoulou, S., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Hailey, M., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hu, D., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kitching, T., Kohley, R., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., 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., Refregier, A., Renzi, A., Rhodes, J., Riccio, G., Rix, H. -W., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Scaramella, R., Schneider, P., Secroun, A., Seidel, G., Seiffert, M., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Tsyganov, A., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Williams, O. R., Zamorani, G., Zucca, E., Baccigalupi, C., Biviano, A., Burigana, C., De Lucia, G., George, K., Scottez, V., Viel, M., Simon, P., Mora, A., Martín-Fleitas, J., and Scott, D.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We make use of the unprecedented depth, spatial resolution, and field of view of the Euclid Early Release Observations of the Perseus galaxy cluster to detect and characterise the dwarf galaxy population in this massive system. The Euclid high resolution VIS and combined VIS+NIR colour images were visually inspected and dwarf galaxy candidates were identified. Their morphologies, the presence of nuclei, and their globular cluster (GC) richness were visually assessed, complementing an automatic detection of the GC candidates. Structural and photometric parameters, including Euclid filter colours, were extracted from 2-dimensional fitting. Based on this analysis, a total of 1100 dwarf candidates were found across the image, with 638 appearing to be new identifications. The majority (96%) are classified as dwarf ellipticals, 53% are nucleated, 26% are GC-rich, and 6% show disturbed morphologies. A relatively high fraction of galaxies, 8%, are categorised as ultra-diffuse galaxies. The majority of the dwarfs follow the expected scaling relations. Globally, the GC specific frequency, S_N, of the Perseus dwarfs is intermediate between those measured in the Virgo and Coma clusters. While the dwarfs with the largest GC counts are found throughout the Euclid field of view, those located around the east-west strip, where most of the brightest cluster members are found, exhibit larger S_N values, on average. The spatial distribution of the dwarfs, GCs, and intracluster light show a main iso-density/isophotal centre displaced to the west of the bright galaxy light distribution. The ERO imaging of the Perseus cluster demonstrates the unique capability of Euclid to concurrently detect and characterise large samples of dwarfs, their nuclei, and their GC systems, allowing us to construct a detailed picture of the formation and evolution of galaxies over a wide range of mass scales and environments., Comment: 44 pages, 24 figures, 5 tables, paper submitted to A&A as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

33. Euclid: Early Release Observations -- Overview of the Perseus cluster and analysis of its luminosity and stellar mass functions

Author

Cuillandre, J. -C., Bolzonella, M., Boselli, A., Marleau, F. R., Mondelin, M., Sorce, J. G., Stone, C., Buitrago, F., Cantiello, Michele, George, K., Hatch, N. A., Quilley, L., Mannucci, F., Saifollahi, T., Sánchez-Janssen, R., Tarsitano, F., Tortora, C., Xu, X., Bouy, H., Gwyn, S., Kluge, M., Lançon, A., Laureijs, R., Schirmer, M., Abdurro'uf, Awad, P., Baes, M., Bournaud, F., Carollo, D., Codis, S., Conselice, C. J., De Lapparent, V., Duc, P. -A., Ferré-Mateu, A., Gillard, W., Golden-Marx, J. B., Jablonka, P., Habas, R., Hunt, L. K., Mei, S., Miville-Deschênes, M. -A., Montes, M., Nersesian, A., Peletier, R. F., Poulain, M., Scaramella, R., Scialpi, M., Sola, E., Stephan, J., Ulivi, L., Urbano, M., Zöller, R., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Melchior, M., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Nakajima, R., Nichol, R. C., Niemi, S. -M., 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., Saglia, R., Sapone, D., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Zucca, E., Biviano, A., Burigana, C., Castignani, G., De Lucia, G., Scottez, V., Mora, A., Simon, P., Martín-Fleitas, J., and Scott, D.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Euclid ERO programme targeted the Perseus cluster of galaxies, gathering deep data in the central region of the cluster over 0.7 square degree, corresponding to approximately 0.25 r_200. The data set reaches a point-source depth of IE=28.0 (YE, JE, HE = 25.3) AB magnitudes at 5 sigma with a 0.16" and 0.48" FWHM, and a surface brightness limit of 30.1 (29.2) mag per square arcsec. The exceptional depth and spatial resolution of this wide-field multi-band data enable the simultaneous detection and characterisation of both bright and low surface brightness galaxies, along with their globular cluster systems, from the optical to the NIR. This study advances beyond previous analyses of the cluster and enables a range of scientific investigations summarised here. We derive the luminosity and stellar mass functions (LF and SMF) of the Perseus cluster in the Euclid IE band, thanks to supplementary u,g,r,i,z and Halpha data from the CFHT. We adopt a catalogue of 1100 dwarf galaxies, detailed in the corresponding ERO paper. We identify all other sources in the Euclid images and obtain accurate photometric measurements using AutoProf or AstroPhot for 138 bright cluster galaxies, and SourceExtractor for half a million compact sources. Cluster membership for the bright sample is determined by calculating photometric redshifts with Phosphoros. Our LF and SMF are the deepest recorded for the Perseus cluster, highlighting the groundbreaking capabilities of the Euclid telescope. Both the LF and SMF fit a Schechter plus Gaussian model. The LF features a dip at M(IE)=-19 and a faint-end slope of alpha_S = -1.2 to -1.3. The SMF displays a low-mass-end slope of alpha_S = -1.2 to -1.35. These observed slopes are flatter than those predicted for dark matter halos in cosmological simulations, offering significant insights for models of galaxy formation and evolution., Comment: Submitted to A&A, 44 pages, 35 figures, Part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

34. Euclid: Early Release Observations -- Globular clusters in the Fornax galaxy cluster, from dwarf galaxies to the intracluster field

Author

Saifollahi, T., Voggel, K., Lançon, A., Cantiello, Michele, Raj, M. A., Cuillandre, J. -C., Larsen, S. S., Marleau, F. R., Venhola, A., Schirmer, M., Carollo, D., Duc, P. -A., Ferguson, A. M. N., Hunt, L. K., Kümmel, M., Laureijs, R., Marchal, O., Nucita, A. A., Peletier, R. F., Poulain, M., Rejkuba, M., Sánchez-Janssen, R., Urbano, M., Abdurro'uf, Altieri, B., Baes, M., Bolzonella, M., Conselice, C. J., Cote, P., Dimauro, P., Gonzalez, A. H., Habas, R., Hudelot, P., Kluge, M., Lonare, P., Massari, D., Romelli, E., Scaramella, R., Sola, E., Stone, C., Tortora, C., van Mierlo, S. E., Knapen, J. H., Martín-Fleitas, J., Mora, A., Román, J., Aghanim, N., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kitching, T., Kohley, R., Kubik, B., Kuijken, K., Kunz, M., Kurki-Suonio, H., Lahav, O., Mignant, D. Le, Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Melchior, M., Mellier, Y., Meneghetti, M., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Racca, G. D., Raison, F., Rebolo, R., Refregier, A., Renzi, A., Rhodes, J., Riccio, G., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tsyganov, A., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Wang, Y., Weller, J., Williams, O. R., Zamorani, G., Zucca, E., Biviano, A., Burigana, C., Scottez, V., Simon, P., Balogh, M., and Scott, D.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

We present an analysis of Euclid observations of a 0.5 deg$^2$ field in the central region of the Fornax galaxy cluster that were acquired during the performance verification phase. With these data, we investigate the potential of Euclid for identifying GCs at 20 Mpc, and validate the search methods using artificial GCs and known GCs within the field from the literature. Our analysis of artificial GCs injected into the data shows that Euclid's data in $I_{\rm E}$ band is 80% complete at about $I_{\rm E} \sim 26.0$ mag ($M_{V\rm } \sim -5.0$ mag), and resolves GCs as small as $r_{\rm h} = 2.5$ pc. In the $I_{\rm E}$ band, we detect more than 95% of the known GCs from previous spectroscopic surveys and GC candidates of the ACS Fornax Cluster Survey, of which more than 80% are resolved. We identify more than 5000 new GC candidates within the field of view down to $I_{\rm E}$ mag, about 1.5 mag fainter than the typical GC luminosity function turn-over magnitude, and investigate their spatial distribution within the intracluster field. We then focus on the GC candidates around dwarf galaxies and investigate their numbers, stacked luminosity distribution and stacked radial distribution. While the overall GC properties are consistent with those in the literature, an interesting over-representation of relatively bright candidates is found within a small number of relatively GC-rich dwarf galaxies. Our work confirms the capabilities of Euclid data in detecting GCs and separating them from foreground and background contaminants at a distance of 20 Mpc, particularly for low-GC count systems such as dwarf galaxies., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

35. Euclid: Early Release Observations -- Deep anatomy of nearby galaxies

Author

Hunt, L. K., Annibali, F., Cuillandre, J. -C., Ferguson, A. M. N., Jablonka, P., Larsen, S. S., Marleau, F. R., Schinnerer, E., Schirmer, M., Stone, C., Tortora, C., Saifollahi, T., Lançon, A., Bolzonella, M., Gwyn, S., Kluge, M., Laureijs, R., Carollo, D., Collins, M. L. M., Dimauro, P., Duc, P. -A., Erkal, D., Howell, J. M., Nally, C., Saremi, E., Scaramella, R., Belokurov, V., Conselice, C. J., Knapen, J. H., McConnachie, A. W., McDonald, I., Carretero, J. Miro, Roman, J., Sauvage, M., Sola, E., Aghanim, N., Altieri, B., Andreon, S., Auricchio, N., Awan, S., Azzollini, R., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Candini, G. P., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Corcione, L., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fosalba, P., Frailis, M., Franceschi, E., Fumana, M., Galeotta, S., Garilli, B., Gillard, W., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Grupp, F., Guzzo, L., Haugan, S. V. H., Hoar, J., Hoekstra, H., Holliman, M. S., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kohley, R., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Mignant, D. Le, Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., 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., Racca, G. D., Raison, F., Rebolo, R., Refregier, A., Renzi, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Sartoris, B., Schneider, P., Schrabback, T., Scodeggio, M., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., 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., Williams, O. R., Zamorani, G., Zucca, E., Burigana, C., De Lucia, G., George, K., Scottez, V., Miluzio, M., Simon, P., Mora, A., Martín-Fleitas, J., and Scott, D.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Euclid is poised to make significant advances in the study of nearby galaxies in the local Universe. Here we present a first look at 6 galaxies observed for the Nearby Galaxy Showcase as part of the Euclid Early Release Observations acquired between August and November, 2023. These targets, 3 dwarf galaxies (HolmbergII, IC10, NGC6822) and 3 spirals (IC342, NGC2403, NGC6744), range in distance from about 0.5 Mpc to 8.8 Mpc. Our assessment of the surface brightness depths in the stacked Euclid images confirms previous estimates in 100 arcsec^2 regions of 1sigma=30.5 mag/arcsec^2 for VIS, but slightly deeper than previous estimates for NISP with 1sigma=29.2-29.4 mag/arcsec^2. By combining Euclid HE, YE, and IE into RGB images, we illustrate the large field-of-view covered by a single Reference Observing Sequence, together with exquisite detail on parsec scales in these nearby galaxies. Radial surface brightness and color profiles demonstrate galaxy colors in agreement with stellar population synthesis models. Standard stellar photometry selection techniques find approximately 1.3 million stars across the 6 galaxy fields. Euclid's resolved stellar photometry allows us to constrain the star-formation histories of these galaxies, by disentangling the distributions of young stars, as well as asymptotic giant branch and red giant branch stellar populations. We finally examine 2 galaxies individually for surrounding satellite systems. Our analysis of the ensemble of dwarf satellites around NGC6744 reveals a new galaxy, EDwC1, a nucleated dwarf spheroidal at the end of a spiral arm. Our new census of the globular clusters around NGC2403 yields 9 new star-cluster candidates, 8 of which with colors indicative of evolved stellar populations. In summary, our investigation of the 6 Showcase galaxies demonstrates that Euclid is a powerful probe of the anatomy of nearby galaxies [abridged]., Comment: 36 pages; 20 figures in main text; 4 Appendices. Submitted to A&A, as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

36. Euclid: Early Release Observations -- Programme overview and pipeline for compact- and diffuse-emission photometry

Author

Cuillandre, J. -C., Bertin, E., Bolzonella, M., Bouy, H., Gwyn, S., Isani, S., Kluge, M., Lai, O., Lançon, A., Lang, D. A., Laureijs, R., Saifollahi, T., Schirmer, M., Stone, C., Abdurro'uf, Aghanim, N., Altieri, B., Annibali, F., Atek, H., Awad, P., Baes, M., Bañados, E., Barrado, D., Belladitta, S., Belokurov, V., Boselli, A., Bournaud, F., Bovy, J., Bowler, R. A. A., Buenadicha, G., Buitrago, F., Cantiello, M., Carollo, D., Codis, S., Collins, M. L. M., Congedo, G., Dalessandro, E., de Lapparent, V., De Paolis, F., Diego, J. M., Dimauro, P., Dinis, J., Dole, H., Duc, P. -A., Erkal, D., Ezziati, M., Ferguson, A. M. N., Ferré-Mateu, A., Franco, A., Gavazzi, R., George, K., Gillard, W., Golden-Marx, J. B., Goldman, B., Gonzalez, A. H., Habas, R., Hartley, W. G., Hatch, N. A., Kohley, R., Hoar, J., Howell, J. M., Hunt, L. K., Jablonka, P., Jauzac, M., Kang, Y., Knapen, J. H., Kneib, J. -P., Kuzma, P. B., Larsen, S. S., Marchal, O., Martín-Fleitas, J., Marcos-Arenal, P., Marleau, F. R., Martín, E. L., Massari, D., McConnachie, A. W., Meneghetti, M., Miluzio, M., Carretero, J. Miro, Miyatake, H., Mondelin, M., Montes, M., Mora, A., Müller, O., Nally, C., Noeske, K., Nucita, A. A., Oesch, P. A., Oguri, M., Peletier, R. F., Poulain, M., Quilley, L., Racca, G. D., Rejkuba, M., Rhodes, J., Rocci, P. -F., Román, J., Sacquegna, S., Saremi, E., Scaramella, R., Schinnerer, E., Serjeant, S., Sola, E., Sorce, J. G., Tarsitano, F., Tereno, I., Toft, S., Tortora, C., Urbano, M., Venhola, A., Voggel, K., Weaver, J. R., Xu, X., Žerjal, M., Zöller, R., Andreon, S., Auricchio, N., Baldi, M., Balestra, A., Bardelli, S., Basset, A., Bender, R., Bodendorf, C., Branchini, E., Brau-Nogue, S., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Castander, F. J., Castellano, M., Cavuoti, S., Cimatti, A., Conselice, C. J., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Cuby, J. -G., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Douspis, M., Duncan, C. A. J., Dupac, X., Dusini, S., Fabricius, M., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Galeotta, S., Garilli, B., 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., Hudelot, P., Jahnke, K., Jhabvala, M., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kubik, B., Kuijken, K., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., McCracken, H. J., Medinaceli, E., Mellier, Y., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Munari, E., Nakajima, R., Nichol, R. C., Niemi, S. -M., Padilla, C., Paltani, S., Pasian, F., Peacock, J. A., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Polenta, G., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Refregier, A., Renzi, A., Riccio, G., Rix, Hans-Walter, Romelli, E., Roncarelli, M., Rossetti, E., Saglia, R., Sapone, D., Schneider, P., Schrabback, T., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Skottfelt, J., Stanco, L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Toledo-Moreo, R., Tsyganov, A., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Kleijn, G. Verdoes, Wang, Y., Weller, J., Williams, O. R., Zamorani, G., Zucca, E., Baccigalupi, C., Burigana, C., Casenove, P., Liebing, P., Scottez, V., Simon, P., and Scott, D.

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

The Euclid ERO showcase Euclid's capabilities in advance of its main mission, targeting 17 astronomical objects, from galaxy clusters, nearby galaxies, globular clusters, to star-forming regions. A total of 24 hours observing time was allocated in the early months of operation, engaging the scientific community through an early public data release. We describe the development of the ERO pipeline to create visually compelling images while simultaneously meeting the scientific demands within months of launch, leveraging a pragmatic, data-driven development strategy. The pipeline's key requirements are to preserve the image quality and to provide flux calibration and photometry for compact and extended sources. The pipeline's five pillars are: removal of instrumental signatures; astrometric calibration; photometric calibration; image stacking; and the production of science-ready catalogues for both the VIS and NISP instruments. We report a PSF with a full width at half maximum of 0.16" in the optical and 0.49" in the three NIR bands. Our VIS mean absolute flux calibration is accurate to about 1%, and 10% for NISP due to a limited calibration set; both instruments have considerable colour terms. The median depth is 25.3 and 23.2 AB mag with a SNR of 10 for galaxies, and 27.1 and 24.5 AB mag at an SNR of 5 for point sources for VIS and NISP, respectively. Euclid's ability to observe diffuse emission is exceptional due to its extended PSF nearly matching a pure diffraction halo, the best ever achieved by a wide-field, high-resolution imaging telescope. Euclid offers unparalleled capabilities for exploring the LSB Universe across all scales, also opening a new observational window in the NIR. Median surface-brightness levels of 29.9 and 28.3 AB mag per square arcsec are achieved for VIS and NISP, respectively, for detecting a 10 arcsec x 10 arcsec extended feature at the 1 sigma level., Comment: Submitted to A&A, 44 pages, 36 figures - Part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

37. 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

38. Superconducting properties and electronic structure of CuAl2-type transition-metal zirconide Fe1-xNixZr2

Author

Shimada, Ryunosuke, Watanabe, Yuto, Tortora, Lorenzo, Tomassucci, Giovanni, Hacisalihoǧlu, Muammer Yasin, Arima, Hiroto, Yamashita, Aichi, Miura, Akira, Moriyoshi, Chikako, Saini, Naurang L., and Mizuguchi, Yoshikazu

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Strongly Correlated Electrons
Abstract

CuAl2-type transition-metal (Tr) zirconides are superconductor family, and the Tr-site element substitution largely modifies its transition temperature (Tc). Here, we synthesized polycrystalline samples of Fe1-xNixZr2 by arc melting. From magnetic susceptibility measurements, bulk superconductivity was observed for 0.4 < x < 0.8, and the highest Tc of 2.8 K was observed for x = 0.6. Specific heat measurements were also performed, bulk superconductivity was observed for 0.4 < x < 0.8, and the highest Tc of 2.6 K was observed for x = 0.6. The obtained superconductivity phase diagram exhibits dome-shaped trend, which is similar to unconventional superconductors, where magnetic fluctuations are essential for superconductivity. In addition, from the c/a lattice constant ratio analysis, we show the possible relationship between the suppression of bulk superconductivity in the Ni-rich compositions and a collapsed tetragonal transition., Comment: 16 pages, 8 figures, SI

Published
2024
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39. Zeno physics of the Ising chain with symmetry-breaking boundary dephasing

Author

Javed, Umar, Valencia-Tortora, Riccardo J., Marino, Jamir, Oganesyan, Vadim, and Kolodrubetz, Michael

Subjects
Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Statistical Mechanics, Quantum Physics
Abstract

In few-qubit systems, the quantum Zeno effect arises when measurement occurs sufficiently frequently that the spins are unable to relax between measurements. This can compete with Hamiltonian terms, resulting in interesting relaxation processes which depend non-monotonically on the ratio of measurement rate to coherent oscillations. While Zeno physics for a single qubit is well-understood, an interesting open question is how the Zeno effect is modified by coupling the measured spin to a non-trivial bulk. In this work, we study the effect of coupling a one-dimensional transverse field Ising to a Zeno spin which lives at the boundary. We find that sharp singularities occur in the boundary relaxation dynamics, which can be tied to the emergence or destruction of edge modes that can be found analytically. Finally, we provide numerical evidence that the dynamical singularities are stable in the presence of integrability-breaking interactions.

Published
2024

42. Defining the Position of [177Lu]Lu-PSMA Radioligand Therapy in the Treatment Landscape of Metastatic Castration-Resistant Prostate Cancer: A Meta-analysis of Clinical Trials

Author

Ciccarese, Chiara, Bauckneht, Matteo, Zagaria, Luca, Fornarini, Giuseppe, Beccia, Viria, Lanfranchi, Francesco, Perotti, Germano, Pinterpe, Giada, Migliaccio, Fortuna, Tortora, Giampaolo, Leccisotti, Lucia, Sambuceti, Gianmario, Giordano, Alessandro, Caffo, Orazio, and Iacovelli, Roberto

Published
2024
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45. Time and frequency transfers in optical spacetime

Author

Bourgoin, Adrien, Teyssandier, Pierre, Tortora, Paolo, and Zannoni, Marco

Subjects
General Relativity and Quantum Cosmology
Abstract

Solving the null geodesic equations for a ray of light is a difficult task even considering a stationary spacetime. The problem becomes even more difficult if the electromagnetic signal propagates through a flowing optical medium. Indeed, because of the interaction between light and matter, the signal does not follow a null geodesic path of the spacetime metric anymore. However, having a clear description of how the time and frequency transfers are affected in this very situation is of a prime importance in astronomy. As a matter of fact, ranging to satellites and Moon, very long baseline interferometry, global navigation satellite systems, and radio occultation experiments are few examples of techniques involving light propagation in flowing optical media. By applying the time transfer functions formalism to optical spacetime, we show that the time and frequency transfers can be determined iteratively up to any desired order within the quasi-Minkowskian path approximation. We present some applications in the context of radio occultation experiments and discuss possible future applications to the modeling of tropospheric delays., Comment: 11 pages, 5 figures, proceeding des Journ\'ees syst\`emes de r\'ef\'erences spatio-temporels 2023

Published
2024

46. Investigating the Proton Structure: The FAMU experiment

Author

Vacchi, A., Adamczak, A., Bakalov, D., Baldazzi, G., Baruzzo, M., Benocci, R., Bertoni, R., Bonesini, M., Cabrera, H., Carsi, S., Cirrincione, D., Chignoli, F., Clemenza, M., Colace, L., Danailov, M., Danev, P., de Bari, A., De Vecchi, C., De Vincenzi, M., Fasci, E., Gadedjisso-Tossou, K. S., Gianfrani, L., Hillier, A. D., Ishida, K., King, P. J. C., Maggi, V., Mazza, R., Menegolli, A., Mocchiutti, E., Moretti, L., Morgante, G., Niemela, J., Petroselli, C., Pizzolotto, C., Pullia, A., Ramponi, R., Roman, H. E., Rossella, M., Rossini, R., Sarkar, R., Sbrizzi, A., Stoilov, M., Stoychev, L., Suarez-Vargas, J. J., Toci, G., Tortora, L., Vallazza, E., Xiao, C., and Yokoyama, K.

Subjects
Physics - Atomic Physics
Abstract

The article gives the motivations for the measurement of the hyperfine splitting (hfs) in the ground state of muonic hydrogen to explore the properties of the proton at low momentum transfer. It summarizes these proposed measurement methods and finally describes the FAMU experiment in more detail.

Published
2024
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47. Euclid preparation. XLIII. Measuring detailed galaxy morphologies for Euclid with machine learning

Author

Euclid Collaboration, Aussel, B., Kruk, S., Walmsley, M., Huertas-Company, M., Castellano, M., Conselice, C. J., Veneri, M. Delli, Sánchez, H. Domínguez, Duc, P. -A., Kuchner, U., La Marca, A., Margalef-Bentabol, B., Marleau, F. R., Stevens, G., Toba, Y., Tortora, C., Wang, L., Aghanim, N., Altieri, B., Amara, A., Andreon, S., Auricchio, N., Baldi, M., Bardelli, S., Bender, R., Bodendorf, C., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Capobianco, V., Carbone, C., Carretero, J., Casas, S., Cavuoti, S., Cimatti, A., Congedo, G., Conversi, L., Copin, Y., Courbin, F., Courtois, H. M., Cropper, M., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Dubath, F., Dupac, X., Dusini, S., Farina, M., Farrens, S., Ferriol, S., Fotopoulou, S., Frailis, M., Franceschi, E., Franzetti, P., Fumana, M., Galeotta, S., Garilli, B., Gillis, B., Giocoli, C., Grazian, A., Grupp, F., Haugan, S. V. H., Holmes, W., Hook, I., Hormuth, F., Hornstrup, A., Hudelot, P., Jahnke, K., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kubik, B., Kümmel, M., Kunz, M., Kurki-Suonio, H., Laureijs, R., Ligori, S., Lilje, P. B., Lindholm, V., Lloro, I., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martinet, N., Marulli, F., Massey, R., Maurogordato, S., Medinaceli, E., Mei, S., Mellier, Y., Meneghetti, M., Merlin, E., Meylan, G., Moresco, M., Moscardini, L., Munari, E., Niemi, S. -M., 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., Sapone, D., Sartoris, B., Schirmer, M., Schneider, P., Secroun, A., Seidel, G., Serrano, S., Sirignano, C., Sirri, G., Stanco, L., Starck, J. -L., Tallada-Crespí, P., Taylor, A. N., Teplitz, H. I., Tereno, I., Toledo-Moreo, R., Torradeflot, F., Tutusaus, I., Valentijn, E. A., Valenziano, L., Vassallo, T., Veropalumbo, A., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zoubian, J., Zucca, E., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Colodro-Conde, C., Di Ferdinando, D., Farinelli, R., Graciá-Carpio, J., Mainetti, G., Marcin, S., Mauri, N., Neissner, C., Nucita, A. A., Sakr, Z., Scottez, V., Tenti, M., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Anselmi, S., Baccigalupi, C., Ballardini, M., Borgani, S., Borlaff, A. S., Bretonnière, H., Bruton, S., Cabanac, R., Calabro, A., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Cañas-Herrera, G., Chambers, K. C., Coupon, J., Cucciati, O., Davini, S., De Lucia, G., Desprez, G., Di Domizio, S., Dole, H., Díaz-Sánchez, A., Vigo, J. A. Escartin, Escoffier, S., Ferrero, I., Finelli, F., Gabarra, L., Ganga, K., García-Bellido, J., Gaztanaga, E., George, K., Giacomini, F., Gozaliasl, G., Gregorio, A., Guinet, D., Hall, A., Hildebrandt, H., Munoz, A. Jimenez, Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Legrand, L., Loureiro, A., Macias-Perez, J., Magliocchetti, M., Maoli, R., Martinelli, M., Martins, C. J. A. P., Matthew, S., Maturi, M., Maurin, L., Metcalf, R. B., Migliaccio, M., Monaco, P., Morgante, G., Nadathur, S., Walton, Nicholas A., Peel, A., Pezzotta, A., Popa, V., Porciani, C., Potter, D., Pöntinen, M., Reimberg, P., Rocci, P. -F., Sánchez, A. G., Schneider, A., Sefusatti, E., Sereno, M., Simon, P., Mancini, A. Spurio, Stanford, S. A., Steinwagner, J., Testera, G., Tewes, M., Teyssier, R., Toft, S., Tosi, S., Troja, A., Tucci, M., Valieri, C., Valiviita, J., Vergani, D., and Zinchenko, I. A.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The Euclid mission is expected to image millions of galaxies with high resolution, providing an extensive dataset to study galaxy evolution. We investigate the application of deep learning to predict the detailed morphologies of galaxies in Euclid using Zoobot a convolutional neural network pretrained with 450000 galaxies from the Galaxy Zoo project. We adapted Zoobot for emulated Euclid images, generated based on Hubble Space Telescope COSMOS images, and with labels provided by volunteers in the Galaxy Zoo: Hubble project. We demonstrate that the trained Zoobot model successfully measures detailed morphology for emulated Euclid images. It effectively predicts whether a galaxy has features and identifies and characterises various features such as spiral arms, clumps, bars, disks, and central bulges. When compared to volunteer classifications Zoobot achieves mean vote fraction deviations of less than 12% and an accuracy above 91% for the confident volunteer classifications across most morphology types. However, the performance varies depending on the specific morphological class. For the global classes such as disk or smooth galaxies, the mean deviations are less than 10%, with only 1000 training galaxies necessary to reach this performance. For more detailed structures and complex tasks like detecting and counting spiral arms or clumps, the deviations are slightly higher, around 12% with 60000 galaxies used for training. In order to enhance the performance on complex morphologies, we anticipate that a larger pool of labelled galaxies is needed, which could be obtained using crowdsourcing. Finally, our findings imply that the model can be effectively adapted to new morphological labels. We demonstrate this adaptability by applying Zoobot to peculiar galaxies. In summary, our trained Zoobot CNN can readily predict morphological catalogues for Euclid images., Comment: 27 pages, 26 figures, 5 tables, published in A&A

Published
2024
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48. INSPIRE: INvestigating Stellar Population In RElics VI -- The low-mass end slope of the stellar Initial Mass Function and chemical composition

Author

Maksymowicz-Maciata, Michalina, Spiniello, Chiara, Martín-Navarro, Ignacio, Ferré-Mateu, Anna, Bevacqua, Davide, Cappellari, Michele, D'Ago, Giuseppe, Tortora, Crescenzo, Arnaboldi, Magda, Hartke, Johanna, Saracco, Paolo, and Scognamiglio, Diana

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

The INSPIRE project has built the largest sample of ultra-compact massive galaxies (UCMGs) at 0.12, and the other stellar population parameters.We use the Full-Index-Fitting method to fit the INSPIRE spectra to single stellar population (SSP) models. This allows us to measure, for the first time, the low-mass end slope of the IMF, as well as stellar metallicity [M/H], [Mg/Fe], [Ti/Fe] and [Na/Fe] ratios, and study correlations between them and the DoR. Similarly to normal-sized galaxies, UCMGs with larger stellar masses have overall higher metallicities. We found a correlation between the low-mass end of the IMF slope and the DoR, that, however, breaks down for systems with a more extended SFH. An even stronger dependency is found between the IMF and the fraction of mass formed at high-z. At equal velocity dispersion and metallicity, galaxies with a higher DoR have a dwarf-richer IMF than that of low-DoR counterparts. This might indicate that the cosmic epoch and formation mechanisms influence the fragmentation of the star formation cloud and hence might be the explanation for IMF variations detected in massive ETGs., Comment: 16 pages, 11 figures, submitted to MNRAS

Published
2024

49. The TNG50-SKIRT Atlas: wavelength dependence of the effective radius

Author

Baes, Maarten, Mosenkov, Aleksandr, Kelly, Raymond, Abdurro'uf, Andreadis, Nick, Tulu, Sena Bokona, Camps, Peter, Emana, Abdissa Tassama, Fritz, Jacopo, Gebek, Andrea, Kovacic, Inja, La Marca, Antonio, Martorano, Marco, Nersesian, Angelos, Rodriguez-Gomez, Vicente, Tortora, Crescenzo, Trcka, Ana, Meulen, Bert Vander, van der Wel, Arjen, and Wang, Lingyu

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Galaxy sizes correlate with many other important properties of galaxies, and the cosmic evolution of galaxy sizes is an important observational diagnostic for constraining galaxy evolution models. The effective radius is probably the most widely used indicator of galaxy size. We used the TNG50-SKIRT Atlas to investigate the wavelength dependence of the effective radius of galaxies at optical and near-infrared (NIR) wavelengths. We find that, on average, the effective radius in every band exceeds the stellar mass effective radius, and that this excess systematically decreases with increasing wavelength. The optical g-band (NIR Ks-band) effective radius is on average 58% (13%) larger than the stellar mass effective radius. Effective radii measured from dust-obscured images are systematically larger than those measured from dust-free images, although the effect is limited (8.7% in the g-band, 2.1% in the Ks-band). We find that stellar population gradients are the dominant factor (about 80%) in driving the wavelength dependence of the effective radius, and that differential dust attenuation is a secondary factor (20%). Comparing our results to recent observational data, we find offsets in the absolute values of the median effective radii, up to 50% for the population of blue galaxies. We find better agreement in the slope of the wavelength dependence of the effective radius, with red galaxies having a slightly steeper slope than green-blue galaxies. Comparing our effective radii with those of galaxies from the Siena Galaxy Atlas in separate bins in z-band absolute magnitude and g-z colour, we find excellent agreement for the reddest galaxies, but again significant offsets for the blue populations: up to 70% for galaxies around Mz=-21.5. This difference in median effective radius for the bluer galaxies is most probably due to (abridged...)., Comment: 11 pages, 10 figures, accepted for publication in A&A

Published
2024

50. The TNG50-SKIRT Atlas: post-processing methodology and first data release

Author

Baes, Maarten, Gebek, Andrea, Trcka, Ana, Camps, Peter, van der Wel, Arjen, Abdurro'uf, Andreadis, Nick, Tulu, Sena Bokona, Emana, Abdissa Tassama, Fritz, Jacopo, Kelly, Raymond, Kovacic, Inja, La Marca, Antonio, Martorano, Marco, Mosenkov, Aleksandr, Nersesian, Angelos, Rodriguez-Gomez, Vicente, Tortora, Crescenzo, Meulen, Bert Vander, and Wang, Lingyu

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generation of synthetic images through 3D radiative transfer post-processing that properly accounts for different stellar populations and interstellar dust attenuation. We use the SKIRT code to generate the TNG50-SKIRT Atlas, a synthetic UV to near-infrared broadband image atlas for a complete stellar-mass selected sample of 1154 galaxies extracted from the TNG50 cosmological simulation at $z=0$. The images have a high spatial resolution (100 pc) and a wide field of view (160 kpc). In addition to the dust-obscured images, we also release dust-free images and physical parameter property maps with matching characteristics. As a sanity check and preview application we discuss the UVJ diagram of the galaxy sample. We investigate the effect of dust attenuation on the UVJ diagram and find that it affects both the star-forming and the quiescent galaxy populations. The quiescent galaxy region is polluted by younger and star-forming highly inclined galaxies, while dust attenuation induces a separation in inclination of the star-forming galaxy population, with low-inclination galaxies remaining at the blue side of the diagram and high-inclination galaxies systematically moving towards the red side. This image atlas can be used for a variety of other applications, including galaxy morphology studies and the investigation of local scaling relations. We publicly release the images and parameter maps, and we invite the community to use them., Comment: 13 pages, 7 figures, accepted for publication in A&A

Published
2024

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