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3. Generation of entanglement and non-stationary states via competing coherent and incoherent bosonic hopping

Author

Solanki, Parvinder, Cabot, Albert, Brunelli, Matteo, Carollo, Federico, Bruder, Christoph, and Lesanovsky, Igor

Subjects
Quantum Physics, Condensed Matter - Statistical Mechanics
Abstract

Incoherent stochastic processes added to unitary dynamics are typically deemed detrimental since they are expected to diminish quantum features such as superposition and entanglement. Instead of exhibiting energy-conserving persistent coherent motion, the dynamics of such open systems feature, in most cases, a steady state, which is approached in the long-time limit from all initial conditions. This can, in fact, be advantageous as it offers a mechanism for the creation of robust quantum correlations on demand without the need for fine-tuning. Here, we show this for a system consisting of two coherently coupled bosonic modes, which is a paradigmatic scenario for the realization of quantum resources such as squeezed entangled states. Rather counterintuitively, the mere addition of incoherent hopping, which results in a statistical coupling between the bosonic modes, leads to steady states with robust quantum entanglement and enables the emergence of persistent coherent non-stationary behavior.

Published
2025

4. Cosmic-ray acceleration and escape from supernova remnant W44 as probed by Fermi-LAT and MAGIC

Author

Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Asano, K., Babi'c, A., Baquero, A., de Almeida, U. Barres, Barrio, J. A., Batkovi'c, I., Bautista, A., Baxter, J., Gonz'alez, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Chilingarian, A., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Del Popolo, A., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Elsaesser, D., Emery, G., Escudero, J., na, L. Fari\, Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukazawa, Y., L'opez, R. J. Garc'ia, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Gliwny, P., Godinovi'c, N., Gozzini, S. R., Gradetzke, T., Grau, R., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Herrera, J., Hrupec, D., Hütten, M., Imazawa, R., Ishio, K., Mart'inez, I. Jim'enez, Jormanainen, J., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., L'ainez, M., Lamastra, A., Leone, F., Lindfors, E., Linhoff, L., Lombardi, S., Longo, F., L'opez-Coto, R., L'opez-Moya, M., L'opez-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Mang, N., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Mart'inez, M., Mart'inez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., Gonz'alez, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Nava, L., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikoli'c, L., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Palatiello, M., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Priyadarshi, C., Rhode, W., Rib'o, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Satalecka, K., Saturni, F. G., Schleicher, B., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Spolon, A., Stamerra, A., Striskovi'c, J., Strom, D., Strzys, M., Suda, Y., Suutarinen, S., Tajima, H., Takahashi, M., Takeishi, R., Temnikov, P., Terauchi, K., Terzi'c, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Will, M., Wunderlich, C., Yamamoto, T., Di Tria, R., Di Venere, L., Giordano, F., Bissaldi, E., Green, D., and Morlino, G.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Context. The supernova remnant (SNR) W44 and its surroundings are a prime target for studying the acceleration of cosmic rays (CRs). Several previous studies established an extended gamma-ray emission that is set apart from the radio shell of W44. This emission is thought to originate from escaped high-energy CRs that interact with a surrounding dense molecular cloud complex. Aims. We present a detailed analysis of Fermi-LAT data with an emphasis on the spatial and spectral properties of W44 and its surroundings. We also report the results of the observations performed with the MAGIC telescopes of the northwestern region of W44. Finally, we present an interpretation model to explain the gamma-ray emission of the SNR and its surroundings. Methods. We first performed a detailed spatial analysis of 12 years of Fermi-LAT data at energies above 1 GeV, in order to exploit the better angular resolution, while we set a threshold of 100MeV for the spectral analysis. We performed a likelihood analysis of 174 hours of MAGIC data above 130 GeV using the spatial information obtained with Fermi-LAT. Results. The combined spectra of Fermi-LAT and MAGIC, extending from 100MeV to several TeV, were used to derive constraints on the escape of CRs. Using a time-dependent model to describe the particle acceleration and escape from the SNR, we show that the maximum energy of the accelerated particles has to be ' 40 GeV. However, our gamma-ray data suggest that a small number of lower-energy particles also needs to escape. We propose a novel model, the broken-shock scenario, to account for this effect and explain the gamma-ray emission.

Published
2025

5. Characterization of Markarian 421 during its most violent year: Multiwavelength variability and correlations

Author

Abe, K., Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Asano, K., Baack, D., Babić, A., de Almeida, U. Barres, Barrio, J. A., Batković, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Campoy-Ordaz, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Ammando, F., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Di Venere, L., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsaesser, D., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinović, N., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kankkunen, S., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Leone, F., Lindfors, E., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Okumura, A., Otero-Santos, J., Paiano, S., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sobczynska, D., Stamerra, A., Strišković, J., Strom, D., Suda, Y., Tajima, H., Takahashi, M., Takeishi, R., Tavecchio, F., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Ventura, S., Verna, G., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Wersig, F., Will, M., Yamamoto, T., Jorstad, S. G., Marscher, A. P., Perri, M., Leto, C., Verrecchia, F., Aller, M., Max-Moerbeck, W., Readhead, A. C. S., Lähteenmäki, A., Tornikoski, M., Gurwell, M. A., and Wehrle, A. E.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Mrk 421 was in its most active state around early 2010, which led to the highest TeV gamma-ray flux ever recorded from any active galactic nuclei. We aim to characterize the multiwavelength behavior during this exceptional year for Mrk 421, and evaluate whether it is consistent with the picture derived with data from other less exceptional years. We investigated the period from November 5, 2009, (MJD 55140) until July 3, 2010, (MJD 55380) with extensive coverage from very-high-energy (VHE; E$\,>\,$100$\,$GeV) gamma rays to radio with MAGIC, VERITAS, Fermi-LAT, RXTE, Swift, GASP-WEBT, VLBA, and a variety of additional optical and radio telescopes. We investigated the variability and correlation behavior among different energy bands in great detail. We find the strongest variability in X-rays and VHE gamma rays, and PSDs compatible with power-law functions. We observe strong correlations between X-rays and VHE gamma rays. We also report a marginally significant positive correlation between high-energy (HE; E$\,>\,$100$\,$MeV) gamma rays and the ultraviolet band. We detected marginally significant correlations between the HE and VHE gamma rays, and between HE gamma rays and the X-ray, that disappear when the large flare in February 2010 is excluded from the correlation study. The activity of Mrk 421 also yielded the first ejection of features in the VLBA images of the jet of Mrk 421. Yet the large uncertainties in the ejection times of these radio features prevent us from firmly associating them to the specific flares recorded during the campaign. We also show that the collected multi-instrument data are consistent with a scenario where the emission is dominated by two regions, a compact and extended zone, which could be considered as a simplified implementation of an energy-stratified jet as suggested by recent IXPE observations., Comment: Accepted for publication in Astronomy & Astrophysics. Corresponding authors: Felix Schmuckermaier, David Paneque, Axel Arbet Engels

Published
2025

6. User Modeling in Model-Driven Engineering: A Systematic Literature Review

Author

Conrardy, Aaron, Capozucca, Alfredo, and Cabot, Jordi

Subjects
Computer Science - Software Engineering
Abstract

In software applications, user models can be used to specify the profile of the typical users of the application, including personality traits, preferences, skills, etc. In theory, this would enable an adaptive application behavior that could lead to a better user experience. Nevertheless, user models do not seem to be part of standard modeling languages nor common in current model-driven engineering (MDE) approaches. In this paper, we conduct a systematic literature review to analyze existing proposals for user modeling in MDE and identify their limitations. The results showcase that there is a lack of a unified and complete user modeling perspective. Instead, we observe a lot of fragmented and partial proposals considering only simple user dimensions and with lack of proper tool support. This limits the implementation of richer user interfaces able to better support the user-specific needs. Therefore, we hope this analysis triggers a discussion on the importance of user models and their inclusion in MDE pipelines. Especially in a context where, thanks to the rise of AI techniques, personalization, based on a rich number of user dimensions, is becoming more and more of a possibility., Comment: Submitted to the 21st European Conference on Modelling Foundations and Applications (ECMFA 2025)

Published
2024

7. Time-dependent modelling of short-term variability in the TeV-blazar VER J0521+211 during the major flare in 2020

Author

MAGIC Collaboration, Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Baack, D., Babić, A., de Almeida, U. Barres, Barrio, J. A., Batković, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Di Venere, L., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsaesser, D., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kankkunen, S., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Leone, F., Lindfors, E., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Spolon, A., Stamerra, A., Strišković, J., Strom, D., Strzys, M., Suda, Y., Tajima, H., Takahashi, M., Takeishi, R., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Verna, G., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Wersig, F., Will, M., Wunderlich, C., Yamamoto, T., collaborators, MWL, Bachev, R., Ramazani, V. Fallah, Filippenko, A. V., Hovatta, T., Jorstad, S. G., Kiehlmann, S., Lähteenmäki, A., Liodakis, I., Marscher, A. P., Max-Moerbeck, W., Omeliukh, A., Pursimo, T., Readhead, A. C. S., Rodrigues, X., Tornikoski, M., Wierda, F., and Zheng, W.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The BL Lacertae object VER J0521+211 underwent a notable flaring episode in February 2020. A short-term monitoring campaign, led by the MAGIC (Major Atmospheric Gamma Imaging Cherenkov) collaboration, covering a wide energy range from radio to very-high-energy (VHE, 100 GeV < E < 100 TeV) gamma rays was organised to study its evolution. These observations resulted in a consistent detection of the source over six consecutive nights in the VHE gamma-ray domain. Combining these nightly observations with an extensive set of multiwavelength data made modelling of the blazar's spectral energy distribution (SED) possible during the flare. This modelling was performed with a focus on two plausible emission mechanisms: i) a leptonic two-zone synchrotron-self-Compton scenario, and ii) a lepto-hadronic one-zone scenario. Both models effectively replicated the observed SED from radio to the VHE gamma-ray band. Furthermore, by introducing a set of evolving parameters, both models were successful in reproducing the evolution of the fluxes measured in different bands throughout the observing campaign. Notably, the lepto-hadronic model predicts enhanced photon and neutrino fluxes at ultra-high energies (E > 100 TeV). While the photon component, generated via decay of neutral pions, is not directly observable as it is subject to intense pair production (and therefore extinction) through interactions with the cosmic microwave background photons, neutrino detectors (e.g. IceCube) can probe the predicted neutrino component. Finally, the analysis of the gamma-ray spectra, as observed by MAGIC and the Fermi-LAT telescopes, yielded a conservative 95\% confidence upper limit of z \leq 0.244 for the redshift of this blazar., Comment: Accepted for publication in A&A

Published
2024
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8. Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension

Author

Ait, Adem, Izquierdo, Javier Luis Cánovas, and Cabot, Jordi

Subjects
Computer Science - Software Engineering
Abstract

Large Language Models (LLMs) have facilitated the definition of autonomous intelligent agents. Such agents have already demonstrated their potential in solving complex tasks in different domains. And they can further increase their performance when collaborating with other agents in a multi-agent system. However, the orchestration and coordination of these agents is still challenging, especially when they need to interact with humans as part of human-agentic collaborative workflows. These kinds of workflows need to be precisely specified so that it is clear whose responsible for each task, what strategies agents can follow to complete individual tasks or how decisions will be taken when different alternatives are proposed, among others. Current business process modeling languages fall short when it comes to specifying these new mixed collaborative scenarios. In this exploratory paper, we extend a well-known process modeling language (i.e., BPMN) to enable the definition of this new type of workflow. Our extension covers both the formalization of the new metamodeling concepts required and the proposal of a BPMN-like graphical notation to facilitate the definition of these workflows. Our extension has been implemented and is available as an open-source human-agentic workflow modeling editor on GitHub.

Published
2024

9. A joint effort to discover and characterize two resonant mini Neptunes around TOI-1803 with TESS, HARPS-N and CHEOPS

Author

Zingales, T., Malavolta, L., Borsato, L., Turrini, D., Bonfanti, A., Polychroni, D., Mantovan, G., Nardiello, D., Nascimbeni, V., Lanza, A. F., Bekkelien, A., Sozzetti, A., Broeg, C., Naponiello, L., Lendl, M., Bonomo, A. S., Simon, A. E., Desidera, S., Piotto, G., Mancini, L., Hooton, M. J., Bignamini, A., Egger, J. A., Maggio, A., Alibert, Y., Locci, D., Delrez, L., Biassoni, F., Fossati, L., Cabona, L., Lacedelli, G., Carleo, I., Leonardi, P., Andreuzzi, G., Brandeker, A., Cosentino, R., Correia, A. C. M., Claudi, R., Alonso, R., Damasso, M., Wilson, T. G., Bàrczy, T., Pinamonti, M., Baker, D., Barkaoui, K., Navascues, D. Barrado, Barros, S. C. C., Baumjohann, W., Beck, T., Beichman, C., Benz, W., Bieryla, A., Billot, N., Bosch-Cabot, P., Bouma, L. G., Ciardi, D. R., Cameron, A. Collier, Collins, K. A., Crossfield, Ian J. M., Csizmadia, Sz., Cubillos, P. E., Davies, M. B., Deleuil, M., Deline, A., Demangeon, O. D. S., Demory, B. O., Derekas, A., Dragomir, D., Edwards, B., Ehrenreich, D., Erikson, A., Falk, B., Fortier, A., Fridlund, M., Fukui, A., Gandolfi, D., Gazeas, K., Gillon, M., Gonzales, E., Gudel, M., Guerra, P., Guunther, M. N., Heitzmann, A., Helling, Ch., Howell, S. B., Isaak, K. G., Jenkins, J., Kiss, L. L., Korth, J., Lam, K. W. F., Laskar, J., Etangs, A. Lecavelier des, Magrin, D., Matson, R., Matthews, E. C., Maxted, P. F. L., McDermott, S., Munari, M., Mordasini, C., Narita, N., Olofsson, G., Ottensamer, R., Pagano, I., Pallè, E., Peter, G., Pollacco, D., Queloz, D., Ragazzoni, R., Rando, N., Ratti, F., Rauer, H., Ribas, I., Salmon, S., Santos, N. C., Scandariato, G., Seager, S., Sègransan, D., Smith, A. M. S., Schlieder, J., Schwarz, R. P., Shporer, A., Sousa, S. G., Stalport, M., Steinberger, M., Sulis, S., Szabò, Gy. M., Twicken, J. D., Udry, S., Van Grootel, V., Venturini, J., Villaver, E., Walton, N. A., and Winn, J. N.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

We present the discovery of two mini Neptunes near a 2:1 orbital resonance configuration orbiting the K0 star TOI-1803. We describe their orbital architecture in detail and suggest some possible formation and evolution scenarios. Using CHEOPS, TESS, and HARPS-N datasets we can estimate the radius and the mass of both planets. We used a multidimensional Gaussian Process with a quasi-periodic kernel to disentangle the planetary components from the stellar activity in the HARPS-N dataset. We performed dynamical modeling to explain the orbital configuration and performed planetary formation and evolution simulations. For the least dense planet, we define possible atmospheric characterization scenarios with simulated JWST observations. TOI-1803 b and TOI-1803 c have orbital periods of $\sim$6.3 and $\sim$12.9 days, respectively, residing in close proximity to a 2:1 orbital resonance. Ground-based photometric follow-up observations revealed significant transit timing variations (TTV) with an amplitude of $\sim$10 min and $\sim$40 min, respectively, for planet -b and -c. With the masses computed from the radial velocities data set, we obtained a density of (0.39$\pm$0.10) $\rho_{earth}$ and (0.076$\pm$0.038) $\rho_{earth}$ for planet -b and -c, respectively. TOI-1803 c is among the least dense mini Neptunes currently known, and due to its inflated atmosphere, it is a suitable target for transmission spectroscopy with JWST. We report the discovery of two mini Neptunes close to a 2:1 orbital resonance. The detection of significant TTVs from ground-based photometry opens scenarios for a more precise mass determination. TOI-1803 c is one of the least dense mini Neptune known so far, and it is of great interest among the scientific community since it could constrain our formation scenarios., Comment: 26 Pages, 21 Figures Accepted for Publication in Astronomy & Astrophysics

Published
2024

10. Towards the interoperability of low-code platforms

Author

Alfonso, Iván, Conrardy, Aaron, and Cabot, Jordi

Subjects
Computer Science - Software Engineering, D.2.12
Abstract

With the promise of accelerating software development, low-code platforms (LCPs) are becoming popular across various industries. Nevertheless, there are still barriers hindering their adoption. Among them, vendor lock-in is a major concern, especially considering the lack of interoperability between these platforms. Typically, after modeling an application in one LCP, migrating to another requires starting from scratch remodeling everything (the data model, the graphical user interface, workflows, etc.), in the new platform. To overcome this situation, this work proposes an approach to improve the interoperability of LCPs by (semi)automatically migrating models specified in one platform to another one. The concrete migration path depends on the capabilities of the source and target tools. We first analyze popular LCPs, characterize their import and export alternatives and define transformations between those data formats when available. This is then complemented with an LLM-based solution, where image recognition features of large language models are employed to migrate models based on a simple image export of the model at hand. The full pipelines are implemented on top of the BESSER modeling framework that acts as a pivot representation between the tools., Comment: Submitted to International Conference on Advanced Information Systems Engineering (CAiSE25)

Published
2024

11. Thermodynamics of coupled time crystals with an application to energy storage

Author

Paulino, Paulo J., Cabot, Albert, De Chiara, Gabriele, Antezza, Mauro, Lesanovsky, Igor, and Carollo, Federico

Subjects
Quantum Physics, Condensed Matter - Statistical Mechanics
Abstract

Open many-body quantum systems can exhibit intriguing nonequilibrium phases of matter, such as time crystals. In these phases, the state of the system spontaneously breaks the time-translation symmetry of the dynamical generator, which typically manifests through persistent oscillations of an order parameter. A paradigmatic model displaying such a symmetry breaking is the boundary time crystal, which has been extensively analyzed experimentally and theoretically. Despite the broad interest in these nonequilibrium phases, their thermodynamics and their fluctuating behavior remain largely unexplored, in particular for the case of coupled time crystals. In this work, we consider two interacting boundary time crystals and derive a consistent interpretation of their thermodynamic behavior. We fully characterize their average dynamics and the behavior of their quantum fluctuations, which allows us to demonstrate the presence of quantum and classical correlations in both the stationary and the time-crystal phases displayed by the system. We furthermore exploit our theoretical derivation to explore possible applications of time crystals as quantum batteries, demonstrating their ability to efficiently store energy., Comment: 15 + 18 pages, 8 figures

Published
2024

12. Artificial Intelligence End-to-End Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Author

Botifoll, Marc, Pinto-Huguet, Ivan, Rotunno, Enzo, Galvani, Thomas, Coll, Catalina, Kavkani, Payam Habibzadeh, Spadaro, Maria Chiara, Niquet, Yann-Michel, Eriksen, Martin Børstad, Martí-Sánchez, Sara, Katsaros, Georgios, Scappucci, Giordano, Krogstrup, Peter, Isella, Giovanni, Cabot, Andreu, Merino, Gonzalo, Ordejón, Pablo, Roche, Stephan, Grillo, Vincenzo, and Arbiol, Jordi

Subjects
Condensed Matter - Materials Science
Abstract

This article introduces a groundbreaking analytical workflow designed for the holistic characterisation, modelling and physical simulation of device heterostructures. Our innovative workflow autonomously, comprehensively and locally characterises the crystallographic information and 3D orientation of the crystal phases, the elemental composition, and the strain maps of devices from (scanning) transmission electron microscopy data. It converts a manual characterisation process that traditionally takes days into an automatic routine completed in minutes. This is achieved through a physics-guided artificial intelligence model that combines unsupervised and supervised machine learning in a modular way to provide a representative 3D description of the devices, materials structures, or samples under analysis. To culminate the process, we integrate the extracted knowledge to automate the generation of both 3D finite element and atomic models of millions of atoms acting as digital twins, enabling simulations that yield essential physical and chemical insights crucial for understanding the device's behaviour in practical applications. We prove this end-to-end workflow with a state-of-the-art materials platform based on SiGe planar heterostructures for hosting coherent and scalable spin qubits. Our workflow connects representative digital twins of the experimental devices with their theoretical properties to reveal the true impact that every atom in the structure has on their electronic properties, and eventually, into their functional quantum performance. Notably, the versatility of our workflow is demonstrated through its successful application to a wide array of materials systems, device configurations and sample morphologies.

Published
2024

13. Insights from the first flaring activity of a high-synchrotron-peaked blazar with X-ray polarization and VHE gamma rays

Author

MAGIC Collaboration, Abe, K., Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Asano, K., Babić, A., de Almeida, U. Barres, Barrio, J. A., Barrios-Jiménez, L., Batković, I., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Chilingarian, A., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Ammando, F., D'Amico, G., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Di Venere, L., Dinesh, A., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsaesser, D., Escudero, J., Fariña, L., Foffano, L., Font, L., Fröse, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinović, N., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Imazawa, R., Israyelyan, D., Itokawa, T., Martínez, I. Jiménez, Quiles, J. Jiménez, Jormanainen, J., Kankkunen, S., Kayanoki, T., Kerszberg, D., Khachatryan, M., Kluge, G. W., Kobayashi, Y., Konrad, J., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Lindfors, E., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Maruševec, P., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Okumura, A., Paiano, S., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schmuckermaier, F., Schubert, J. L., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Stamerra, A., Strišković, J., Strom, D., Strzys, M., Suda, Y., Tajima, H., Takahashi, M., Takeishi, R., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Ventura, S., Verna, G., Viale, I., Vigliano, A., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Wersig, F., Will, M., Yamamoto, T., Yeung, P. K. H., Liodakis, I., Middei, R., Kiehlmann, S., Gesu, L. D., Kim, D. E., Ehlert, S. R., Saade, M. L., Kaaret, P., Maksym, W. P., Chen, C. T., Pérez, I. De La Calle, Perri, M., Verrecchia, F., Domann, O., Dürr, S., Feige, M., Heidemann, M., Koppitz, O., Manhalter, G., Reinhart, D., Steineke, R., Lorey, C., McCall, C., Jermak, H. E., Steele, I. A., Ramazani, V. Fallah, Otero-Santos, J., Morcuende, D., Aceituno, F. J., Casanova, V., Sota, A., Jorstad, S. G., Marscher, A. P., Pauley, C., Sasada, M., Kawabata, K. S., Uemura, M., Mizuno, T., Nakaoka, T., Akitaya, H., Myserlis, I., Gurwell, M., Keating, G. K., Rao, R., Angelakis, E., and Kraus, A.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We study a flaring activity of the HSP Mrk421 that was characterized from radio to very-high-energy (VHE; E $>0.1$TeV) gamma rays with MAGIC, Fermi-LAT, Swift, XMM-Newton and several optical and radio telescopes. These observations included, for the first time for a gamma-ray flare of a blazar, simultaneous X-ray polarization measurements with IXPE. We find substantial variability in both X-rays and VHE gamma rays throughout the campaign, with the highest VHE flux above 0.2 TeV occurring during the IXPE observing window, and exceeding twice the flux of the Crab Nebula. However, the VHE and X-ray spectra are on average softer, and the correlation between these two bands weaker that those reported in previous flares of Mrk421. IXPE reveals an X-ray polarization degree significantly higher than that at radio and optical frequencies. The X-ray polarization angle varies by $\sim$100$^\circ$ on timescales of days, and the polarization degree changes by more than a factor 4. The highest X-ray polarization degree reaches 26%, around which a X-ray counter-clockwise hysteresis loop is measured with XMM-Newton. It suggests that the X-ray emission comes from particles close to the high-energy cutoff, hence possibly probing an extreme case of the Turbulent Extreme Multi-Zone model. We model the broadband emission with a simplified stratified jet model throughout the flare. The polarization measurements imply an electron distribution in the X-ray emitting region with a very high minimum Lorentz factor, which is expected in electron-ion plasma, as well as a variation of the emitting region size up to a factor of three during the flaring activity. We find no correlation between the fluxes and the evolution of the model parameters, which indicates a stochastic nature of the underlying physical mechanism. Such behaviour would be expected in a highly turbulent electron-ion plasma crossing a shock front., Comment: Accepted in Astronomy and Astrophysics (on January 17th 2025). Corresponding authors: Axel Arbet-Engels, Lea Heckmann, David Paneque

Published
2024

14. A new method of reconstructing images of gamma-ray telescopes applied to the LST-1 of CTAO

Author

Project, CTA-LST, Abe, K., Abe, S., Abhishek, A., Acero, F., Aguasca-Cabot, A., Agudo, I., Alispach, C., Crespo, N. Alvarez, Ambrosino, D., Antonelli, L. A., Aramo, C., Arbet-Engels, A., Arcaro, C., Asano, K., Aubert, P., Baktash, A., Balbo, M., Bamba, A., Larriva, A. Baquero, de Almeida, U. Barres, Barrio, J. A., Jiménez, L. Barrios, Batkovic, I., Baxter, J., González, J. Becerra, Bernardini, E., Medrano, J. Bernete, Berti, A., Bezshyiko, I., Bhattacharjee, P., Bigongiari, C., Bissaldi, E., Blanch, O., Bonnoli, G., Bordas, P., Borkowski, G., Brunelli, G., Bulgarelli, A., Burelli, I., Burmistrov, L., Buscemi, M., Cardillo, M., Caroff, S., Carosi, A., Carrasco, M. S., Cassol, F., Castrejón, N., Cauz, D., Cerasole, D., Ceribella, G., Chai, Y., Cheng, K., Chiavassa, A., Chikawa, M., Chon, G., Chytka, L., Cicciari, G. M., Cifuentes, A., Contreras, J. L., Cortina, J., Costantini, H., Da Vela, P., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Lotto, B., de Menezes, R., Del Burgo, R., Del Peral, L., Delgado, C., Mengual, J. Delgado, della Volpe, D., Dellaiera, M., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsässer, D., Emery, G., Escudero, J., Ramazani, V. Fallah, Ferrarotto, F., Fiasson, A., Foffano, L., Coromina, L. Freixas, Fröse, S., Fukazawa, Y., López, R. Garcia, Gasbarra, C., Gasparrini, D., Geyer, D., Paiva, J. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Grau, R., Green, D., Green, J., Gunji, S., Günther, P., Hackfeld, J., Hadasch, D., Hahn, A., Hassan, T., Hayashi, K., Heckmann, L., Heller, M., Llorente, J. Herrera, Hirotani, K., Hoffmann, D., Horns, D., Houles, J., Hrabovsky, M., Hrupec, D., Hui, D., Iarlori, M., Imazawa, R., Inada, T., Inome, Y., Inoue, S., Ioka, K., Iori, M., Iuliano, A., Martinez, I. Jimenez, Quiles, J. Jimenez, Jurysek, J., Kagaya, M., Kalashev, O., Karas, V., Katagiri, H., Kataoka, J., Kerszberg, D., Kobayashi, Y., Kohri, K., Kong, A., Kubo, H., Kushida, J., Lainez, M., Lamanna, G., Lamastra, A., Lemoigne, L., Linhoff, M., Longo, F., López-Coto, R., López-Oramas, A., Loporchio, S., Lorini, A., Bahilo, J. Lozano, Luciani, H., Luque-Escamilla, P. L., Majumdar, P., Makariev, M., Mallamaci, M., Mandat, D., Manganaro, M., Manicò, G., Mannheim, K., Marchesi, S., Mariotti, M., Marquez, P., Marsella, G., Martí, J., Martinez, O., Martínez, G., Martínez, M., Mas-Aguilar, A., Maurin, G., Mazin, D., Méndez-Gallego, J., Guillen, E. Mestre, Micanovic, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., Mizuno, T., Gonzalez, M. Molero, Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moya, V., Muraishi, H., Nagataki, S., Nakamori, T., Neronov, A., Nickel, L., Rosillo, M. Nievas, Nikolic, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Oka, T., Okumura, A., Orito, R., Otero-Santos, J., Ottanelli, P., Owen, E., Palatiello, M., Paneque, D., Pantaleo, F. R., Paoletti, R., Paredes, J. M., Pech, M., Pecimotika, M., Peresano, M., Pfeifle, F., Pietropaolo, E., Pihet, M., Pirola, G., Plard, C., Podobnik, F., Pons, E., Prandini, E., Priyadarshi, C., Prouza, M., Rainò, S., Rando, R., Rhode, W., Ribó, M., Righi, C., Rizi, V., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Ruina, A., Ruiz-Velasco, E., Saito, T., Sakurai, S., Sanchez, D. A., Sano, H., Šarić, T., Sato, Y., Saturni, F. G., Savchenko, V., Schiavone, F., Schleicher, B., Schmuckermaier, F., Schubert, J. L., Schussler, F., Schweizer, T., Arroyo, M. Seglar, Siegert, T., Sitarek, J., Sliusar, V., Strišković, J., Strzys, M., Suda, Y., Tajima, H., Takahashi, H., Takahashi, M., Takata, J., Takeishi, R., Tam, P. H. T., Tanaka, S. J., Tateishi, D., Tavernier, T., Temnikov, P., Terada, Y., Terauchi, K., Terzic, T., Teshima, M., Tluczykont, M., Tokanai, F., Torres, D. F., Travnicek, P., Tutone, A., Vacula, M., Vallania, P., van Scherpenberg, J., Acosta, M. Vázquez, Ventura, S., Verna, G., Viale, I., Vigliano, A., Vigorito, C. F., Visentin, E., Vitale, V., Voitsekhovskyi, V., Voutsinas, G., Vovk, I., Vuillaume, T., Walter, R., Wan, L., Will, M., Wójtowicz, J., Yamamoto, T., Yamazaki, R., Yeung, P. K. H., Yoshida, T., Yoshikoshi, T., Zhang, W., and Zywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Imaging atmospheric Cherenkov telescopes (IACTs) are used to observe very high-energy photons from the ground. Gamma rays are indirectly detected through the Cherenkov light emitted by the air showers they induce. The new generation of experiments, in particular the Cherenkov Telescope Array Observatory (CTAO), sets ambitious goals for discoveries of new gamma-ray sources and precise measurements of the already discovered ones. To achieve these goals, both hardware and data analysis must employ cutting-edge techniques. This also applies to the LST-1, the first IACT built for the CTAO, which is currently taking data on the Canary island of La Palma. This paper introduces a new event reconstruction technique for IACT data, aiming to improve the image reconstruction quality and the discrimination between the signal and the background from misidentified hadrons and electrons. The technique models the development of the extensive air shower signal, recorded as a waveform per pixel, seen by CTAO telescopes' cameras. Model parameters are subsequently passed to random forest regressors and classifiers to extract information on the primary particle. The new reconstruction was applied to simulated data and to data from observations of the Crab Nebula performed by the LST-1. The event reconstruction method presented here shows promising performance improvements. The angular and energy resolution, and the sensitivity, are improved by 10 to 20% over most of the energy range. At low energy, improvements reach up to 22%, 47%, and 50%, respectively. A future extension of the method to stereoscopic analysis for telescope arrays will be the next important step., Comment: Accepted in A&A

Published
2024
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15. Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics

Author

Perrella, Stefano, Proietti, Lorenzo, Cabot, Pere-Lluís Huguet, Barba, Edoardo, and Navigli, Roberto

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Machine Translation (MT) evaluation metrics assess translation quality automatically. Recently, researchers have employed MT metrics for various new use cases, such as data filtering and translation re-ranking. However, most MT metrics return assessments as scalar scores that are difficult to interpret, posing a challenge to making informed design choices. Moreover, MT metrics' capabilities have historically been evaluated using correlation with human judgment, which, despite its efficacy, falls short of providing intuitive insights into metric performance, especially in terms of new metric use cases. To address these issues, we introduce an interpretable evaluation framework for MT metrics. Within this framework, we evaluate metrics in two scenarios that serve as proxies for the data filtering and translation re-ranking use cases. Furthermore, by measuring the performance of MT metrics using Precision, Recall, and F-score, we offer clearer insights into their capabilities than correlation with human judgments. Finally, we raise concerns regarding the reliability of manually curated data following the Direct Assessments+Scalar Quality Metrics (DA+SQM) guidelines, reporting a notably low agreement with Multidimensional Quality Metrics (MQM) annotations., Comment: Accepted at EMNLP 2024 Main Conference. 26 pages

Published
2024

16. On the Creation of Representative Samples of Software Repositories

Author

Gorostidi, June, Ait, Adem, Cabot, Jordi, and Izquierdo, Javier Luis Cánovas

Subjects
Computer Science - Software Engineering
Abstract

Software repositories is one of the sources of data in Empirical Software Engineering, primarily in the Mining Software Repositories field, aimed at extracting knowledge from the dynamics and practice of software projects. With the emergence of social coding platforms such as GitHub, researchers have now access to millions of software repositories to use as source data for their studies. With this massive amount of data, sampling techniques are needed to create more manageable datasets. The creation of these datasets is a crucial step, and researchers have to carefully select the repositories to create representative samples according to a set of variables of interest. However, current sampling methods are often based on random selection or rely on variables which may not be related to the research study (e.g., popularity or activity). In this paper, we present a methodology for creating representative samples of software repositories, where such representativeness is properly aligned with both the characteristics of the population of repositories and the requirements of the empirical study. We illustrate our approach with use cases based on Hugging Face repositories., Comment: The paper has been accepted for publication in the Proceedings of the 18th International Symposium on Empirical Software Engineering and Measurement (ESEM 2024)

Published
2024

17. Standardised formats and open-source analysis tools for the MAGIC telescopes data

Author

Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Babić, A., de Almeida, U. Barres, Barrio, J. A., Batković, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Delfino, M., Delgado, J., Di Pierro, F., Di Tria, R., Di Venere, L., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Elsaesser, D., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Hütten, M., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Leone, F., Lindfors, E., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolić, L., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Priyadarshi, C., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Spolon, A., Stamerra, A., Strišković, J., Strom, D., Strzys, M., Suda, Y., Suutarinen, S., Tajima, H., Takahashi, M., Takeishi, R., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Will, M., Wunderlich, C., Yamamoto, T., Jouvin, L., Linhoff, L., and Linhoff, M.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Instruments for gamma-ray astronomy at Very High Energies ($E>100\,{\rm GeV}$) have traditionally derived their scientific results through proprietary data and software. Data standardisation has become a prominent issue in this field both as a requirement for the dissemination of data from the next generation of gamma-ray observatories and as an effective solution to realise public data legacies of current-generation instruments. Specifications for a standardised gamma-ray data format have been proposed as a community effort and have already been successfully adopted by several instruments. We present the first production of standardised data from the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) telescopes. We converted $166\,{\rm h}$ of observations from different sources and validated their analysis with the open-source software Gammapy. We consider six data sets representing different scientific and technical analysis cases and compare the results obtained analysing the standardised data with open-source software against those produced with the MAGIC proprietary data and software. Aiming at a systematic production of MAGIC data in this standardised format, we also present the implementation of a database-driven pipeline automatically performing the MAGIC data reduction from the calibrated down to the standardised data level. In all the cases selected for the validation, we obtain results compatible with the MAGIC proprietary software, both for the manual and for the automatic data productions. Part of the validation data set is also made publicly available, thus representing the first large public release of MAGIC data. This effort and this first data release represent a technical milestone toward the realisation of a public MAGIC data legacy., Comment: Accepted for publication in the Journal of High Energy Astrophysics

Published
2024

18. Abstraction Engineering

Author

Bencomo, Nelly, Cabot, Jordi, Chechik, Marsha, Cheng, Betty H. C., Combemale, Benoit, Wąsowski, Andrzej, and Zschaler, Steffen

Subjects
Computer Science - Software Engineering
Abstract

Modern software-based systems operate under rapidly changing conditions and face ever-increasing uncertainty. In response, systems are increasingly adaptive and reliant on artificial-intelligence methods. In addition to the ubiquity of software with respect to users and application areas (e.g., transportation, smart grids, medicine, etc.), these high-impact software systems necessarily draw from many disciplines for foundational principles, domain expertise, and workflows. Recent progress with lowering the barrier to entry for coding has led to a broader community of developers, who are not necessarily software engineers. As such, the field of software engineering needs to adapt accordingly and offer new methods to systematically develop high-quality software systems by a broad range of experts and non-experts. This paper looks at these new challenges and proposes to address them through the lens of Abstraction. Abstraction is already used across many disciplines involved in software development -- from the time-honored classical deductive reasoning and formal modeling to the inductive reasoning employed by modern data science. The software engineering of the future requires Abstraction Engineering -- a systematic approach to abstraction across the inductive and deductive spaces. We discuss the foundations of Abstraction Engineering, identify key challenges, highlight the research questions that help address these challenges, and create a roadmap for future research.

Published
2024

19. A Metascience Study of the Impact of Low-Code Techniques in Modeling Publications

Author

Tosi, Mauro Dalle Lucca, Izquierdo, Javier Luis Cánovas, and Cabot, Jordi

Subjects
Computer Science - Software Engineering, Computer Science - Digital Libraries
Abstract

In the last years, model-related publications have been exploring the application of modeling techniques in different domains. Initially focused on UML and the Model-Driven Architecture approach, the literature has been evolving towards the usage of more general concepts such as Model-Driven Development or Model-Driven Engineering. With the emergence of Low-Code software development platforms, the modeling community has been studying how these two fields may combine and benefit from each other, thus leading to the publication of a number of works in recent years. In this paper, we present a metascience study of Low-Code. Our study has a two-fold approach: (1) to examine the composition (size and diversity) of the emerging Low-Code community; and (2) to investigate how this community differs from the "classical" model-driven community in terms of people, venues, and types of publications. Through this study, we aim to benefit the low-code community by helping them better understand its relationship with the broader modeling community. Ultimately, we hope to trigger a discussion about the current and possible future evolution of the low-code community as part of its consolidation as a new research field.

Published
2024

20. ReLiK: Retrieve and LinK, Fast and Accurate Entity Linking and Relation Extraction on an Academic Budget

Author

Orlando, Riccardo, Cabot, Pere-Lluis Huguet, Barba, Edoardo, and Navigli, Roberto

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Entity Linking (EL) and Relation Extraction (RE) are fundamental tasks in Natural Language Processing, serving as critical components in a wide range of applications. In this paper, we propose ReLiK, a Retriever-Reader architecture for both EL and RE, where, given an input text, the Retriever module undertakes the identification of candidate entities or relations that could potentially appear within the text. Subsequently, the Reader module is tasked to discern the pertinent retrieved entities or relations and establish their alignment with the corresponding textual spans. Notably, we put forward an innovative input representation that incorporates the candidate entities or relations alongside the text, making it possible to link entities or extract relations in a single forward pass and to fully leverage pre-trained language models contextualization capabilities, in contrast with previous Retriever-Reader-based methods, which require a forward pass for each candidate. Our formulation of EL and RE achieves state-of-the-art performance in both in-domain and out-of-domain benchmarks while using academic budget training and with up to 40x inference speed compared to competitors. Finally, we show how our architecture can be used seamlessly for Information Extraction (cIE), i.e. EL + RE, and setting a new state of the art by employing a shared Reader that simultaneously extracts entities and relations., Comment: Findings of the Association for Computational Linguistics ACL 2024

Published
2024

21. Evaluating Large Language Models for automatic analysis of teacher simulations

Author

de-Fitero-Dominguez, David, Albaladejo-González, Mariano, Garcia-Cabot, Antonio, Garcia-Lopez, Eva, Moreno-Cediel, Antonio, Barno, Erin, and Reich, Justin

Subjects
Computer Science - Artificial Intelligence
Abstract

Digital Simulations (DS) provide safe environments where users interact with an agent through conversational prompts, providing engaging learning experiences that can be used to train teacher candidates in realistic classroom scenarios. These simulations usually include open-ended questions, allowing teacher candidates to express their thoughts but complicating an automatic response analysis. To address this issue, we have evaluated Large Language Models (LLMs) to identify characteristics (user behaviors) in the responses of DS for teacher education. We evaluated the performance of DeBERTaV3 and Llama 3, combined with zero-shot, few-shot, and fine-tuning. Our experiments discovered a significant variation in the LLMs' performance depending on the characteristic to identify. Additionally, we noted that DeBERTaV3 significantly reduced its performance when it had to identify new characteristics. In contrast, Llama 3 performed better than DeBERTaV3 in detecting new characteristics and showing more stable performance. Therefore, in DS where teacher educators need to introduce new characteristics because they change depending on the simulation or the educational objectives, it is more recommended to use Llama 3. These results can guide other researchers in introducing LLMs to provide the highly demanded automatic evaluations in DS.

Published
2024

22. Exploiting nonequilibrium phase transitions and strong symmetries for continuous measurement of collective observables

Author

Cabot, Albert, Carollo, Federico, and Lesanovsky, Igor

Subjects
Quantum Physics, Condensed Matter - Statistical Mechanics
Abstract

Dissipative many-body quantum dynamics can feature strong symmetries which give rise to conserved quantities. We discuss here how a strong symmetry in conjunction with a nonequilibrium phase transition allows to devise a protocol for measuring collective many-body observables. To demonstrate this idea we consider a collective spin system whose constituents are governed by a dissipative dynamics that conserves the total angular momentum. We show that by continuously monitoring the system output the value of the total angular momentum can be inferred directly from the time-integrated emission signal, without the need of repeated projective measurements or reinitializations of the spins. This may offer a route towards the measurement of collective properties in qubit ensembles, with applications in quantum tomography, quantum computation and quantum metrology.

Published
2024
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23. A detailed study of the very-high-energy Crab pulsar emission with the LST-1

Author

Project, CTA-LST, Abe, K., Abe, S., Abhishek, A., Acero, F., Aguasca-Cabot, A., Agudo, I., Crespo, N. Alvarez, Antonelli, L. A., Aramo, C., Arbet-Engels, A., Arcaro, C., Artero, M., Asano, K., Aubert, P., Baktash, A., Bamba, A., Larriva, A. Baquero, Baroncelli, L., de Almeida, U. Barres, Barrio, J. A., Batkovic, I., Baxter, J., González, J. Becerra, Bernardini, E., Medrano, J. Bernete, Berti, A., Bhattacharjee, P., Bigongiari, C., Bissaldi, E., Blanch, O., Bonnoli, G., Bordas, P., Brunelli, G., Bulgarelli, A., Burelli, I., Burmistrov, L., Buscemi, M., Cardillo, M., Caroff, S., Carosi, A., Carrasco, M. S., Cassol, F., Castrejón, N., Cauz, D., Cerasole, D., Ceribella, G., Chai, Y., Cheng, K., Chiavassa, A., Chikawa, M., Chon, G., Chytka, L., Cicciari, G. M., Cifuentes, A., Contreras, J. L., Cortina, J., Costantini, H., Da Vela, P., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Lotto, B., de Menezes, R., Del Peral, L., Delgado, C., Mengual, J. Delgado, della Volpe, D., Dellaiera, M., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Eisenberger, L., Elsässer, D., Emery, G., Escudero, J., Ramazani, V. Fallah, Ferrarotto, F., Fiasson, A., Foffano, L., Coromina, L. Freixas, Fröse, S., Fukazawa, Y., López, R. Garcia, Gasbarra, C., Gasparrini, D., Gavira, L., Geyer, D., Paiva, J. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Grau, R., Green, D., Green, J., Gunji, S., Günther, P., Hackfeld, J., Hadasch, D., Hahn, A., Hassan, T., Hayashi, K., Heckmann, L., Heller, M., Llorente, J. Herrera, Hirotani, K., Hoffmann, D., Horns, D., Houles, J., Hrabovsky, M., Hrupec, D., Hui, D., Iarlori, M., Imazawa, R., Inada, T., Inome, Y., Ioka, K., Iori, M., Martinez, I. Jimenez, Quiles, J. Jiménez, Jurysek, J., Kagaya, M., Karas, V., Katagiri, H., Kataoka, J., Kerszberg, D., Kobayashi, Y., Kohri, K., Kong, A., Kubo, H., Kushida, J., Lainez, M., Lamanna, G., Lamastra, A., Lemoigne, L., Linhoff, M., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Bahilo, J. Lozano, Luque-Escamilla, P. L., Majumdar, P., Makariev, M., Mallamaci, M., Mandat, D., Manganaro, M., Manicò, G., Mannheim, K., Marchesi, S., Mariotti, M., Marquez, P., Marsella, G., Martí, J., Martinez, O., Martínez, G., Martínez, M., Mas-Aguilar, A., Maurin, G., Mazin, D., Guillen, E. Mestre, Micanovic, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., Mizuno, T., Gonzalez, M. Molero, Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moya, V., Muraishi, H., Nagataki, S., Nakamori, T., Neronov, A., Nickel, L., Rosillo, M. Nievas, Nikolic, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Oka, T., Okumura, A., Orito, R., Otero-Santos, J., Ottanelli, P., Owen, E., Palatiello, M., Paneque, D., Pantaleo, F. R., Paoletti, R., Paredes, J. M., Pech, M., Pecimotika, M., Peresano, M., Pfeiffle, F., Pietropaolo, E., Pihet, M., Pirola, G., Plard, C., Podobnik, F., Pons, E., Prandini, E., Priyadarshi, C., Prouza, M., Rando, R., Rhode, W., Ribó, M., Righi, C., Rizi, V., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Saito, T., Sakurai, S., Sanchez, D. A., Sano, H., Šarić, T., Sato, Y., Saturni, F. G., Savchenko, V., Schiavone, F., Schleicher, B., Schmuckermaier, F., Schubert, J. L., Schussler, F., Schweizer, T., Arroyo, M. Seglar, Siegert, T., Silvia, R., Sitarek, J., Sliusar, V., Strišković, J., Strzys, M., Suda, Y., Tajima, H., Takahashi, H., Takahashi, M., Takata, J., Takeishi, R., Tam, P. H. T., Tanaka, S. J., Tateishi, D., Tavernier, T., Temnikov, P., Terada, Y., Terauchi, K., Terzic, T., Teshima, M., Tluczykont, M., Tokanai, F., Torres, D. F., Travnicek, P., Truzzi, S., Tutone, A., Vacula, M., Vallania, P., van Scherpenberg, J., Acosta, M. Vázquez, Verna, G., Viale, I., Vigliano, A., Vigorito, C. F., Visentin, E., Vitale, V., Voitsekhovskyi, V., Voutsinas, G., Vovk, I., Vuillaume, T., Walter, R., Wan, L., Will, M., Yamamoto, T., Yamazaki, R., Yeung, P. K. H., Yoshida, T., Yoshikoshi, T., Zhang, W., and Zywucka, N.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Context: There are currently three pulsars firmly detected by imaging atmospheric Cherenkov telescopes (IACTs), two of them reaching TeV energies, challenging models of very-high-energy (VHE) emission in pulsars. More precise observations are needed to better characterize pulsar emission at these energies. The LST-1 is the prototype of the Large-Sized Telescope, that will be part of the Cherenkov Telescope Array Observatory (CTAO). Its improved performance over previous IACTs makes it well suited for studying pulsars. Aims: To study the Crab pulsar emission with the LST-1, improving and complementing the results from other telescopes. These observations can also be used to characterize the potential of the LST-1 to study other pulsars and detect new ones. Methods: We analyzed a total of $\sim$103 hours of gamma-ray observations of the Crab pulsar conducted with the LST-1 in the period from September 2020 to January 2023. The observations were carried out at zenith angles less than 50 degrees. A new analysis of the Fermi-LAT data was also performed, including $\sim$14 years of observations. Results: The Crab pulsar phaseogram, long-term light-curve, and phase-resolved spectra are reconstructed with the LST-1 from 20 GeV to 450 GeV for P1 and up to 700 GeV for P2. The pulsed emission is detected with a significance of 15.2$\sigma$. The two characteristic emission peaks of the Crab pulsar are clearly detected (>10$\sigma$), as well as the so-called bridge emission (5.7$\sigma$). We find that both peaks are well described by power laws, with spectral indices of $\sim$3.44 and $\sim$3.03 respectively. The joint analysis of Fermi-LAT and LST-1 data shows a good agreement between both instruments in the overlapping energy range. The detailed results obtained in the first observations of the Crab pulsar with LST-1 show the potential that CTAO will have to study this type of sources., Comment: Accepted by A&A

Published
2024

25. Application of the Tree-of-Thoughts Framework to LLM-Enabled Domain Modeling

Author

Silva, Jonathan, Ma, Qin, Cabot, Jordi, Kelsen, Pierre, Proper, Henderik A., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Maass, Wolfgang, editor, Han, Hyoil, editor, Yasar, Hasan, editor, and Multari, Nick, editor

Published
2025
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26. Constraints on Lorentz invariance violation from the extraordinary Mrk 421 flare of 2014 using a novel analysis method

Author

MAGIC Collaboration, Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Babić, A., Baquero, A., de Almeida, U. Barres, Barrio, J. A., Batković, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bošnjak, Ž., Bronzini, E., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Del Popolo, A., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Di Venere, L., Donini, A., Dorner, D., Doro, M., Elsaesser, D., Emery, G., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinović, N., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Hütten, M., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kankkunen, S., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Leone, F., Lindfors, E., Linhoff, L., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nogues, L., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Palatiello, M., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Priyadarshi, C., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Saturni, F. G., Schleicher, B., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Stamerra, A., Strišković, J., Strom, D., Suda, Y., Tajima, H., Takahashi, M., Takeishi, R., Tavecchio, F., Temnikov, P., Terauchi, K., Terzić, T., Teshima, M., Truzzi, S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Viale, I., Vigorito, C. F., Vitale, V., Vovk, I., Walter, R., Will, M., Wunderlich, C., and Yamamoto, T.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Phenomenology
Abstract

The Lorentz Invariance Violation (LIV), a proposed consequence of certain quantum gravity (QG) scenarios, could instigate an energy-dependent group velocity for ultra-relativistic particles. This energy dependence, although suppressed by the massive QG energy scale $E_\mathrm{QG}$, expected to be on the level of the Planck energy $1.22 \times 10^{19}$ GeV, is potentially detectable in astrophysical observations. In this scenario, the cosmological distances traversed by photons act as an amplifier for this effect. By leveraging the observation of a remarkable flare from the blazar Mrk\,421, recorded at energies above 100 GeV by the MAGIC telescopes on the night of April 25 to 26, 2014, we look for time delays scaling linearly and quadratically with the photon energies. Using for the first time in LIV studies a binned-likelihood approach we set constraints on the QG energy scale. For the linear scenario, we set $95\%$ lower limits $E_\mathrm{QG}>2.7\times10^{17}$ GeV for the subluminal case and $E_\mathrm{QG}> 3.6 \times10^{17}$ GeV for the superluminal case. For the quadratic scenario, the $95\%$ lower limits for the subluminal and superluminal cases are $E_\mathrm{QG}>2.6 \times10^{10}$ GeV and $E_\mathrm{QG}>2.5\times10^{10}$ GeV, respectively.

Published
2024
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27. Building BESSER: an open-source low-code platform

Author

Alfonso, Iván, Conrardy, Aaron, Sulejmani, Armen, Nirumand, Atefeh, Haq, Fitash Ul, Gomez-Vazquez, Marcos, Sottet, Jean-Sébastien, and Cabot, Jordi

Subjects
Computer Science - Software Engineering, D.2.2
Abstract

Low-code platforms (latest reincarnation of the long tradition of model-driven engineering approaches) have the potential of saving us countless hours of repetitive boilerplate coding tasks. However, as software systems grow in complexity, low-code platforms need to adapt as well. Notably, nowadays this implies adapting to the modeling and generation of smart software. At the same time, if we want to broaden the userbase of this type of tools, we should also be able to provide more open source alternatives that help potential users avoid vendor lock-ins and give them the freedom to explore low-code development approaches (even adapting the tool to better fit their needs). To fulfil these needs, we are building BESSER, an open source low-code platform for developing (smart) software. BESSER offers various forms (i.e., notations) for system and domain specification (e.g. UML for technical users and chatbots for business users) together with a number of generators. Both types of components can be extended and are open to contributions from the community., Comment: Accepted in Exploring Modeling Methods for Systems Analysis and Development (EMSAD 2024) conference

Published
2024
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28. Risks and Opportunities of Open-Source Generative AI

Author

Eiras, Francisco, Petrov, Aleksandar, Vidgen, Bertie, Schroeder, Christian, Pizzati, Fabio, Elkins, Katherine, Mukhopadhyay, Supratik, Bibi, Adel, Purewal, Aaron, Botos, Csaba, Steibel, Fabro, Keshtkar, Fazel, Barez, Fazl, Smith, Genevieve, Guadagni, Gianluca, Chun, Jon, Cabot, Jordi, Imperial, Joseph, Nolazco, Juan Arturo, Landay, Lori, Jackson, Matthew, Torr, Phillip H. S., Darrell, Trevor, Lee, Yong, and Foerster, Jakob

Subjects
Computer Science - Machine Learning
Abstract

Applications of Generative AI (Gen AI) are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about the potential risks of the technology, and resulted in calls for tighter regulation, in particular from some of the major tech companies who are leading in AI development. This regulation is likely to put at risk the budding field of open-source generative AI. Using a three-stage framework for Gen AI development (near, mid and long-term), we analyze the risks and opportunities of open-source generative AI models with similar capabilities to the ones currently available (near to mid-term) and with greater capabilities (long-term). We argue that, overall, the benefits of open-source Gen AI outweigh its risks. As such, we encourage the open sourcing of models, training and evaluation data, and provide a set of recommendations and best practices for managing risks associated with open-source generative AI., Comment: Extension of arXiv:2404.17047

Published
2024

29. LangBiTe: A Platform for Testing Bias in Large Language Models

Author

Morales, Sergio, Clarisó, Robert, and Cabot, Jordi

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence
Abstract

The integration of Large Language Models (LLMs) into various software applications raises concerns about their potential biases. Typically, those models are trained on a vast amount of data scrapped from forums, websites, social media and other internet sources, which may instill harmful and discriminating behavior into the model. To address this issue, we present LangBiTe, a testing platform to systematically assess the presence of biases within an LLM. LangBiTe enables development teams to tailor their test scenarios, and automatically generate and execute the test cases according to a set of user-defined ethical requirements. Each test consists of a prompt fed into the LLM and a corresponding test oracle that scrutinizes the LLM's response for the identification of biases. LangBite provides users with the bias evaluation of LLMs, and end-to-end traceability between the initial ethical requirements and the insights obtained.

Published
2024

30. A Framework to Model ML Engineering Processes

Author

Morales, Sergio, Clarisó, Robert, and Cabot, Jordi

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The development of Machine Learning (ML) based systems is complex and requires multidisciplinary teams with diverse skill sets. This may lead to communication issues or misapplication of best practices. Process models can alleviate these challenges by standardizing task orchestration, providing a common language to facilitate communication, and nurturing a collaborative environment. Unfortunately, current process modeling languages are not suitable for describing the development of such systems. In this paper, we introduce a framework for modeling ML-based software development processes, built around a domain-specific language and derived from an analysis of scientific and gray literature. A supporting toolkit is also available.

Published
2024

31. Near to Mid-term Risks and Opportunities of Open-Source Generative AI

Author

Eiras, Francisco, Petrov, Aleksandar, Vidgen, Bertie, de Witt, Christian Schroeder, Pizzati, Fabio, Elkins, Katherine, Mukhopadhyay, Supratik, Bibi, Adel, Csaba, Botos, Steibel, Fabro, Barez, Fazl, Smith, Genevieve, Guadagni, Gianluca, Chun, Jon, Cabot, Jordi, Imperial, Joseph Marvin, Nolazco-Flores, Juan A., Landay, Lori, Jackson, Matthew, Röttger, Paul, Torr, Philip H. S., Darrell, Trevor, Lee, Yong Suk, and Foerster, Jakob

Subjects
Computer Science - Machine Learning
Abstract

In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential risks and resulted in calls for tighter regulation, in particular from some of the major tech companies who are leading in AI development. This regulation is likely to put at risk the budding field of open-source Generative AI. We argue for the responsible open sourcing of generative AI models in the near and medium term. To set the stage, we first introduce an AI openness taxonomy system and apply it to 40 current large language models. We then outline differential benefits and risks of open versus closed source AI and present potential risk mitigation, ranging from best practices to calls for technical and scientific contributions. We hope that this report will add a much needed missing voice to the current public discourse on near to mid-term AI safety and other societal impact., Comment: Accepted to ICML'24 as a position paper

Published
2024

32. Broadband Multi-wavelength Properties of M87 during the 2018 EHT Campaign including a Very High Energy Flaring Episode

Author

Algaba, J. C., Balokovic, M., Chandra, S., Cheong, W. Y., Cui, Y. Z., D'Ammando, F., Falcone, A. D., Ford, N. M., Giroletti, M., Goddi, C., Gurwell, M. A., Hada, K., Haggard, D., Jorstad, S., Kaur, A., Kawashima, T., Kerby, S., Kim, J. Y., Kino, M., Kravchenko, E. V., Lee, S. S., Lu, R. S., Markoff, S., Michail, J., Neilsen, J., Nowak, M. A., Principe, G., Ramakrishnan, V., Ripperda, B., Sasada, M., Savchenko, S. S., Sheridan, C., Akiyama, K., Alberdi, A., Alef, W., Anantua, R., Asada, K., Azulay, R., Bach, U., Baczko, A. -K., Ball, D., Bandyopadhyay, B., Barrett, J., Bauböck, M., Benson, B. A., Bintley, D., Blackburn, L., Blundell, R., Bouman, K. L., Bower, G. C., Boyce, H., Bremer, M., Brissenden, R., Britzen, S., Broderick, A. E., Broguiere, D., Bronzwaer, T., Bustamante, S., Carlstrom, J. E., Chael, A., Chan, C. -K., Chang, D. O., Chatterjee, K., Chatterjee, S., Chen, M. -T., Chen, Y., Cheng, X., Cho, I., Christian, P., Conroy, N. S., Conway, J. E., Crawford, T. M., Crew, G. B., Cruz-Osorio, A., Dahale, R., Davelaar, J., De Laurentis, M., Deane, R., Dempsey, J., Desvignes, G., Dexter, J., Dhruv, V., Dihingia, I. K., Doeleman, S. S., Dzib, S. A., Eatough, R. P., Emami, R., Falcke, H., Farah, J., Fish, V. L., Fomalont, E., Ford, H. A., Foschi, M., Fraga-Encinas, R., Freeman, W. T., Friberg, P., Fromm, C. M., Fuentes, A., Galison, P., Gammie, C. F., García, R., Gentaz, O., Georgiev, B., Gold, R., Gómez-Ruiz, A. I., Gómez, J. L., Gu, M., Hesper, R., Heumann, D., Ho, L. C., Ho, P., Honma, M., Huang, C. -W. L., Huang, L., Hughes, D. H., Ikeda, S., Impellizzeri, C. M. V., Inoue, M., Issaoun, S., James, D. J., Jannuzi, B. T., Janssen, M., Jeter, B., Jiang, W., Jiménez-Rosales, A., Johnson, M. D., Jones, A. C., Joshi, A. V., Jung, T., Karuppusamy, R., Keating, G. K., Kettenis, M., Kim, D. -J., Kim, J., Koay, J. Y., Kocherlakota, P., Kofuji, Y., Koch, P. M., Koyama, S., Kramer, C., Kramer, J. A., Kramer, M., Krichbaum, T. P., Kuo, C. -Y., La Bella, N., Levis, A., Li, Z., Lico, R., Lindahl, G., Lindqvist, M., Lisakov, M., Liu, J., Liu, K., Liuzzo, E., Lo, W. -P., Lobanov, A. P., Loinard, L., Lonsdale, C. J., Lowitz, A. E., MacDonald, N. R., Mao, J., Marchili, N., Marrone, D. P., Marscher, A. P., Martí-Vidal, I., Matsushita, S., Matthews, L. D., Medeiros, L., Menten, K. M., Mizuno, I., Mizuno, Y., Montgomery, J., Moran, J. M., Moriyama, K., Moscibrodzka, M., Mulaudzi, W., Müller, C., Müller, H., Mus, A., Musoke, G., Myserlis, I., Nagai, H., Nagar, N. M., Nair, D. G., Nakamura, M., Narayanan, G., Natarajan, I., Nathanail, A., Fuentes, S. Navarro, Ni, C., Oh, J., Okino, H., Olivares, H., Oyama, T., Özel, F., Palumbo, D. C. M., Paraschos, G. Filippos, Park, J., Parsons, H., Patel, N., Pen, U. -L., Pesce, D. W., Piétu, V., PopStefanija, A., Porth, O., Prather, B., Psaltis, D., Pu, H. -Y., Rao, R., Rawlings, M. G., Raymond, A. 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A., Welker, L., Zietkiewicz, M., Abdalla, G., Aleva, C., Benkhali, H. A. Ait, Aldous, M., Amin, M., Aschieri, M. A., de Deus, E., Santos, J. de Los, Fontanot, D., Jorfi, S., Levens, P., Zwart, A. E. E., Oliviero, S., Puglisi, D., Thiel, M., Zaharijas, C., Amaral, F., Boella, L., Holincheck, L., Queiroz, R., Sofue, H., Tellis, G., Wagner, G., Wierzcholska, A., Zacharias, M., Zdziarski, A. A., Zech, A., Zywucka, N., Abe, S., Abhir, J., Abhishek, A., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Babic, A., de Almeida, U. Barres, Barrio, J. A., Batkovic, I., Bautista, A., Baxter, J., González, J. Becerra, Bednarek, W., Bernardini, E., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bonnoli, G., Bosnjak, Z., Bronzini, E., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Castro-Tirado, A. J., Cerasole, D., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Tria, R., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Elsaesser, D., Escudero, J., Fariña, L., Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Godinovic, N., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Llorente, J. Herrera, Hrupec, D., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. 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Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies
Abstract

The nearby elliptical galaxy M87 contains one of the only two supermassive black holes whose emission surrounding the event horizon has been imaged by the Event Horizon Telescope (EHT). In 2018, more than two dozen multi-wavelength (MWL) facilities (from radio to gamma-ray energies) took part in the second M87 EHT campaign. The goal of this extensive MWL campaign was to better understand the physics of the accreting black hole M87*, the relationship between the inflow and inner jets, and the high-energy particle acceleration. Understanding the complex astrophysics is also a necessary first step towards performing further tests of general relativity. The MWL campaign took place in April 2018, overlapping with the EHT M87* observations. We present a new, contemporaneous spectral energy distribution (SED) ranging from radio to very high energy (VHE) gamma-rays, as well as details of the individual observations and light curves. We also conduct phenomenological modelling to investigate the basic source properties. We present the first VHE gamma-ray flare from M87 detected since 2010. The flux above 350 GeV has more than doubled within a period of about 36 hours. We find that the X-ray flux is enhanced by about a factor of two compared to 2017, while the radio and millimetre core fluxes are consistent between 2017 and 2018. We detect evidence for a monotonically increasing jet position angle that corresponds to variations in the bright spot of the EHT image. Our results show the value of continued MWL monitoring together with precision imaging for addressing the origins of high-energy particle acceleration. While we cannot currently pinpoint the precise location where such acceleration takes place, the new VHE gamma-ray flare already presents a challenge to simple one-zone leptonic emission model approaches, and emphasises the need for combined image and spectral modelling., Comment: 46 pages, 23 figures, accepted by Astronomy & Astrophysics on August. 29, 2024

Published
2024
Full Text
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33. From Image to UML: First Results of Image Based UML Diagram Generation Using LLMs

Author

Conrardy, Aaron and Cabot, Jordi

Subjects
Computer Science - Software Engineering
Abstract

In software engineering processes, systems are first specified using a modeling language such as UML. These initial designs are often collaboratively created, many times in meetings where different domain experts use whiteboards, paper or other types of quick supports to create drawings and blueprints that then will need to be formalized. These proper, machine-readable, models are key to ensure models can be part of automated processes (e.g. input of a low-code generation pipeline, a model-based testing system, ...). But going from hand-drawn diagrams to actual models is a time-consuming process that sometimes ends up with such drawings just added as informal images to the software documentation, reducing their value a lot. To avoid this tedious task, we explore the usage of Large Language Models (LLM) to generate the formal representation of (UML) models from a given drawing. More specifically, we have evaluated the capabilities of different LLMs to convert images of UML class diagrams into the actual models represented in the images. While the results are good enough to use such an approach as part of a model-driven engineering pipeline we also highlight some of their current limitations and the need to keep the human in the loop to overcome those limitations., Comment: Accepted in First Large Language Models for Model-Driven Engineering Workshop (LLM4MDE 2024)

Published
2024

34. Using Large Language Models to Enrich the Documentation of Datasets for Machine Learning

Author

Giner-Miguelez, Joan, Gómez, Abel, and Cabot, Jordi

Subjects
Computer Science - Digital Libraries, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, H.4.4
Abstract

Recent regulatory initiatives like the European AI Act and relevant voices in the Machine Learning (ML) community stress the need to describe datasets along several key dimensions for trustworthy AI, such as the provenance processes and social concerns. However, this information is typically presented as unstructured text in accompanying documentation, hampering their automated analysis and processing. In this work, we explore using large language models (LLM) and a set of prompting strategies to automatically extract these dimensions from documents and enrich the dataset description with them. Our approach could aid data publishers and practitioners in creating machine-readable documentation to improve the discoverability of their datasets, assess their compliance with current AI regulations, and improve the overall quality of ML models trained on them. In this paper, we evaluate the approach on 12 scientific dataset papers published in two scientific journals (Nature's Scientific Data and Elsevier's Data in Brief) using two different LLMs (GPT3.5 and Flan-UL2). Results show good accuracy with our prompt extraction strategies. Concrete results vary depending on the dimensions, but overall, GPT3.5 shows slightly better accuracy (81,21%) than FLAN-UL2 (69,13%) although it is more prone to hallucinations. We have released an open-source tool implementing our approach and a replication package, including the experiments' code and results, in an open-source repository.

Published
2024

37. Fertility protection during chemotherapy treatment by boosting the NAD(P)+ metabolome

Author

Ho, Wing-Hong Jonathan, Marinova, Maria B, Listijono, Dave R, Bertoldo, Michael J, Richani, Dulama, Kim, Lynn-Jee, Brown, Amelia, Riepsamen, Angelique H, Cabot, Safaa, Frost, Emily R, Bustamante, Sonia, Zhong, Ling, Selesniemi, Kaisa, Wong, Derek, Madawala, Romanthi, Marchante, Maria, Goss, Dale M, Li, Catherine, Araki, Toshiyuki, Livingston, David J, Turner, Nigel, Sinclair, David A, Walters, Kirsty A, Homer, Hayden A, Gilchrist, Robert B, and Wu, Lindsay E

Published
2024
Full Text
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39. High-resolution Spectroscopic Reconnaissance of a Temperate Sub-Neptune

Author

Cabot, Samuel H. C., Madhusudhan, Nikku, Constantinou, Savvas, Valencia, Diana, Vos, Johanna M., Masseron, Thomas, and Cheverall, Connor J.

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

The study of temperate sub-Neptunes is the new frontier in exoplanetary science. A major development in the past year has been the first detection of carbon-bearing molecules in the atmosphere of a temperate sub-Neptune, K2-18 b, a possible Hycean world, with the James Webb Space Telescope (JWST). The JWST is poised to characterise the atmospheres of several other such planets with important implications for planetary processes in the temperate regime. Meanwhile, ground-based high-resolution spectroscopy has been highly successful in detecting chemical signatures of giant exoplanets, though low-mass planets have remained elusive. In the present work, we report the atmospheric reconnaissance of a temperate sub-Neptune using ground-based high-resolution transmission spectroscopy. The long orbital period and the low systemic velocity results in a low planetary radial velocity during transit, making this system a valuable testbed for high-resolution spectroscopy of temperate sub-Neptunes. We observe high-resolution time-series spectroscopy in the H- and K-bands during the planetary transit with the IGRINS instrument (R$\sim$45,000) on Gemini-South. Using observations from a single transit we find marginal evidence (2.2$\sigma$) for the presence of methane (CH$_4$) in the atmosphere and no evidence for ammonia (NH$_3$) despite its strong detectability for a cloud-free H$_2$-rich atmosphere. We assess our findings using injection tests with different atmospheric scenarios, and find them to be consistent with a high CH$_4$/NH$_3$ ratio and/or the presence of high-altitude clouds. Our results demonstrate the capability of Gemini-S/IGRINS for atmospheric characterization of temperate sub-Neptunes, and the complementarity between space- and ground-based facilities in this planetary regime., Comment: Accepted for publication in ApJ Letters

Published
2024

40. Dark Matter Line Searches with the Cherenkov Telescope Array

Author

Abe, S., Abhir, J., Abhishek, A., Acero, F., Acharyya, A., Adam, R., Aguasca-Cabot, A., Agudo, I., Aguirre-Santaella, A., Alfaro, J., Alfaro, R., Alvarez-Crespo, N., Batista, R. Alves, Amans, J. -P., Amato, E., Ambrosi, G., Angel, L., Aramo, C., Arcaro, C., Arnesen, T. T. H., Arrabito, L., Asano, K., Ascasibar, Y., Aschersleben, J., Ashkar, H., Backes, M., Baktash, A., Balazs, C., Balbo, M., Larriva, A. Baquero, Martins, V. Barbosa, de Almeida, U. Barres, Barrio, J. A., Batković, I., Batzofin, R., Baxter, J., González, J. Becerra, Beck, G., Benbow, W., Berge, D., Bernardini, E., Bernete, J., Bernlöhr, K., Berti, A., Bertucci, B., Bhattacharjee, P., Bhattacharyya, S., Bigongiari, C., Biland, A., Bissaldi, E., Biteau, J., Blanch, O., Blazek, J., Bocchino, F., Boisson, C., Bolmont, J., Bonnoli, G., Bonollo, A., Bordas, P., Bosnjak, Z., Bottacini, E., Böttcher, M., Bringmann, T., Bronzini, E., Brose, R., Brown, A. M., Brunelli, G., Bulgarelli, A., Bulik, T., Burelli, I., Burmistrov, L., Burton, M., Buscemi, M., Bylund, T., Cailleux, J., Campoy-Ordaz, A., Cantlay, B. K., Capasso, G., Caproni, A., Capuzzo-Dolcetta, R., Caraveo, P., Caroff, S., Carosi, A., Carosi, R., Carquin, E., Carrasco, M. -S., Cassol, F., Castaldini, L., Castrejon, N., Castro-Tirado, A. J., Cerasole, D., Cerruti, M., Chadwick, P. M., Chaty, S., Chen, A. W., Chernyakova, M., Chiavassa, A., Chudoba, J., Chytka, L., Cicciari, G. M., Cifuentes, A., Araujo, C. H. Coimbra, Colapietro, M., Conforti, V., Conte, F., Contreras, J. L., Costa, A., Costantini, H., Cotter, G., Cristofari, P., Cuevas, O., Curtis-Ginsberg, Z., D'Amico, G., D'Ammando, F., Dai, S., Dalchenko, M., Dazzi, F., De Angelis, A., de Lavergne, M. de Bony, De Caprio, V., Pino, E. M. de Gouveia Dal, De Lotto, B., De Lucia, M., de Menezes, R., de Naurois, M., de Souza, V., del Peral, L., del Valle, M. V., Giler, A. G. Delgado, Mengual, J. Delgado, Delgado, C., Dell'aiera, M., della Volpe, D., Depaoli, D., Di Girolamo, T., Di Piano, A., Di Pierro, F., Di Tria, R., Di Venere, L., Díaz, C., Diebold, S., Dinesh, A., Djuvsland, J., Dominik, R. M., Prester, D. Dominis, Donini, A., Dorner, D., Dörner, J., Doro, M., Dournaux, J. -L., Duangchan, C., Dubos, C., Ducci, L., Dwarkadas, V. V., Ebr, J., Eckner, C., Egberts, K., Einecke, S., Elsässer, D., Emery, G., Errando, M., Escanuela, C., Escarate, P., Godoy, M. Escobar, Escudero, J., Esposito, P., Ettori, S., Falceta-Goncalves, D., Fedorova, E., Fegan, S., Feng, Q., Ferrand, G., Ferrarotto, F., Fiandrini, E., Fiasson, A., Filipovic, M., Fioretti, V., Fiori, M., Foffano, L., Guiteras, L. Font, Fontaine, G., Fröse, S., Fukazawa, Y., Fukui, Y., Furniss, A., Galanti, G., Galaz, G., Galelli, C., Gallozzi, S., Gammaldi, V., Garczarczyk, M., Gasbarra, C., Gasparrini, D., Ghalumyan, A., Gianotti, F., Giarrusso, M., Paiva, J. G. Giesbrecht Formiga, Giglietto, N., Giordano, F., Giuffrida, R., Glicenstein, J. -F., Glombitza, J., Goldoni, P., González, J. M., González, M. M., Coelho, J. Goulart, Gradetzke, T., Granot, J., Grasso, D., Grau, R., Gréaux, L., Green, D., Green, J. G., Grolleron, G., Guedes, L. M. V., Gueta, O., Hackfeld, J., Hadasch, D., Hamal, P., Hanlon, W., Hara, S., Harvey, V. M., Hassan, T., Hayashi, K., Heß, B., Heckmann, L., Heller, M., Cadena, S. Hernández, Hervet, O., Hinton, J., Hiroshima, N., Hnatyk, B., Hnatyk, R., Hofmann, W., Holder, J., Horan, D., Horvath, P., Hovatta, T., Hrabovsky, M., Hrupec, D., Iarlori, M., Inada, T., Incardona, F., Inoue, S., Inoue, Y., Iocco, F., Iori, M., Ishio, K., Jamrozy, M., Janecek, P., Jankowsky, F., Jean, P., Quiles, J. Jimenez, Jin, W., Juramy-Gilles, C., Jurysek, J., Kagaya, M., Kalekin, O., Karas, V., Katagiri, H., Kataoka, J., Kaufmann, S., Kazanas, D., Kerszberg, D., Kieda, D. B., Kleiner, T., Kluge, G., Kobayashi, Y., Kohri, K., Komin, N., Kornecki, P., Kosack, K., Kowal, G., Kubo, H., Kushida, J., La Barbera, A., La Palombara, N., Láinez, M., Lamastra, A., Lapington, J., Laporte, P., Lazarević, S., Lazendic-Galloway, J., Lemoine-Goumard, M., Lenain, J. -P., Leone, F., Leonora, E., Leto, G., Lindfors, E., Linhoff, M., Liodakis, I., Lipniacka, A., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Bahilo, J. Lozano, Luque-Escamilla, P. L., Macias, O., Majumdar, P., Mallamaci, M., Malyshev, D., Mandat, D., Manicò, G., Mariotti, M., Márquez, I., Marquez, P., Marsella, G., Martí, J., Martínez, G. A., Martínez, M., Martinez, O., Marty, C., Mas-Aguilar, A., Mastropietro, M., Mazin, D., Menchiari, S., Mestre, E., Meunier, J. -L., Meyer, D. M. -A., Meyer, M., Miceli, D., Miceli, M., Michailidis, M., Michałowski, J., Miener, T., Miranda, J. M., Mitchell, A., Mizote, M., Mizuno, T., Moderski, R., Molero, M., Molfese, C., Molina, E., Montaruli, T., Moralejo, A., Morcuende, D., Morselli, A., Moulin, E., Zamanillo, V. Moya, Munari, K., Murach, T., Muraczewski, A., Muraishi, H., Nakamori, T., Nayak, A., Nemmen, R., Neto, J. P., Nickel, L., Niemiec, J., Nieto, D., Rosillo, M. Nievas, Nikołajuk, M., Nikolić, L., Nishijima, K., Noda, K., Nosek, D., Novotny, V., Nozaki, S., Ohishi, M., Ohtani, Y., Okumura, A., Olive, J. -F., Ong, R. A., Orienti, M., Orito, R., Orlandini, M., Orlando, E., Orlando, S., Ostrowski, M., Otero-Santos, J., Oya, I., Pagano, I., Pagliaro, A., Palatiello, M., Panebianco, G., Paneque, D., Pantaleo, F. R., Paredes, J. M., Parmiggiani, N., Patricelli, B., Pe'er, A., Pech, M., Pecimotika, M., Pensec, U., Peresano, M., Pérez-Romero, J., Persic, M., Peters, K. P., Petruk, O., Piano, G., Pierre, E., Pietropaolo, E., Pihet, M., Pinchbeck, L., Pirola, G., Pittori, C., Plard, C., Podobnik, F., Pohl, M., Pollet, V., Ponti, G., Prandini, E., Principe, G., Priyadarshi, C., Produit, N., Prouza, M., Pueschel, E., Pühlhofer, G., Pumo, M. L., Queiroz, F., Quirrenbach, A., Rainò, S., Rando, R., Razzaque, S., Regeard, M., Reimer, A., Reimer, O., Reisenegger, A., Rhode, W., Ribeiro, D., Ribó, M., Ricci, C., Richtler, T., Rico, J., Rieger, F., Riitano, L., Rizi, V., Roache, E., Fernandez, G. Rodriguez, Frías, M. D. Rodríguez, Rodríguez-Vázquez, J. J., Romano, P., Romeo, G., Rosado, J., de Leon, A. Rosales, Rowell, G., Rudak, B., Ruiter, A. J., Rulten, C. B., Sadeh, I., Saha, L., Saito, T., Salzmann, H., Sánchez-Conde, M., Sandaker, H., Sangiorgi, P., Sano, H., Santander, M., Santos-Lima, R., Sapienza, V., Šarić, T., Sarkar, A., Sarkar, S., Saturni, F. G., Savarese, S., Scherer, A., Schiavone, F., Schipani, P., Schleicher, B., Schovanek, P., Schubert, J. L., Schwanke, U., Arroyo, M. Seglar, Seitenzahl, I. R., Sergijenko, O., Servillat, M., Siegert, T., Siejkowski, H., Siqueira, C., Sliusar, V., Slowikowska, A., Sol, H., Spencer, S. T., Spiga, D., Stamerra, A., Stanič, S., Starecki, T., Starling, R., Stawarz, Ł., Steppa, C., Hatlen, E. Sæther, Stolarczyk, T., Strišković, J., Suda, Y., Świerk, P., Tajima, H., Tak, D., Takahashi, M., Takeishi, R., Tavernier, T., Tejedor, L. A., Terauchi, K., Teshima, M., Testa, V., Tian, W. W., Tibaldo, L., Tibolla, O., Peixoto, C. J. Todero, Torradeflot, F., Torres, D. F., Tosti, G., Tothill, N., Toussenel, F., Tramacere, A., Travnicek, P., Tripodo, G., Trois, A., Truzzi, S., Tutone, A., Vaclavek, L., Vacula, M., Vallania, P., Vallés, R., van Eldik, C., van Scherpenberg, J., Vandenbroucke, J., Vassiliev, V., Acosta, M. Vázquez, Vecchi, M., Ventura, S., Vercellone, S., Verna, G., Viana, A., Viaux, N., Vigliano, A., Vignatti, J., Vigorito, C. F., Villanueva, J., Visentin, E., Vitale, V., Vodeb, V., Voisin, V., Voitsekhovskyi, V., Vorobiov, S., Voutsinas, G., Vovk, I., Vuillaume, T., Wagner, S. J., Walter, R., White, M., White, R., Wierzcholska, A., Will, M., Williams, D. A., Wohlleben, F., Wolter, A., Yamamoto, T., Yang, L., Yoshida, T., Yoshikoshi, T., Zaharijas, G., Zampieri, L., Sanchez, R. Zanmar, Zavrtanik, D., Zavrtanik, M., Zdziarski, A. A., Zech, A., Zhang, W., Zhdanov, V. I., Ziętara, K., Živec, M., and Zuriaga-Puig, J.

Subjects
High Energy Physics - Phenomenology, Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version

Published
2024
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41. Low-Modeling of Software Systems

Author

Cabot, Jordi

Subjects
Computer Science - Software Engineering
Abstract

There is a growing need for better development methods and tools to keep up with the increasing complexity of new software systems. New types of user interfaces, the need for intelligent components, sustainability concerns, ... bring new challenges that we need to handle. In the last years, model-driven engineering has been key to improving the quality and productivity of software development, but models themselves are becoming increasingly complex to specify and manage. In this paper, we present the concept of low-modeling as a solution to enhance current model-driven engineering techniques and get them ready for this new generation of software systems.

Published
2024

42. Performance and first measurements of the MAGIC Stellar Intensity Interferometer

Author

MAGIC Collaboration, Abe, S., Abhir, J., Acciari, V. A., Aguasca-Cabot, A., Agudo, I., Aniello, T., Ansoldi, S., Antonelli, L. A., Engels, A. Arbet, Arcaro, C., Artero, M., Asano, K., Babić, A., Baquero, A., de Almeida, U. Barres, Barrio, J. A., Batković, I., Bautista, A., Baxter, J., González, J. Becerra, Bernardini, E., Bernardos, M., Bernete, J., Berti, A., Besenrieder, J., Bigongiari, C., Biland, A., Blanch, O., Bošnjak, Ž., Burelli, I., Busetto, G., Campoy-Ordaz, A., Carosi, A., Carosi, R., Carretero-Castrillo, M., Ceribella, G., Chai, Y., Cifuentes, A., Colombo, E., Contreras, J. L., Cortina, J., Covino, S., D'Amico, G., D'Elia, V., Da Vela, P., Dazzi, F., De Angelis, A., De Lotto, B., de Menezes, R., Del Popolo, A., Delfino, M., Delgado, J., Mendez, C. Delgado, Di Pierro, F., Di Venere, L., Prester, D. Dominis, Donini, A., Dorner, D., Doro, M., Elsaesser, D., Emery, G., Escudero, J., na, L. Fari, Fattorini, A., Foffano, L., Font, L., Fröse, S., Fukami, S., Fukazawa, Y., López, R. J. García, Garczarczyk, M., Gasparyan, S., Gaug, M., Paiva, J. G. Giesbrecht, Giglietto, N., Giordano, F., Gliwny, P., Gradetzke, T., Grau, R., Green, D., Green, J. G., Günther, P., Hadasch, D., Hahn, A., Hassan, T., Heckmann, L., Herrera, J., Hrupec, D., Hütten, M., Imazawa, R., Ishio, K., Martínez, I. Jiménez, Jormanainen, J., Kayanoki, T., Kerszberg, D., Kluge, G. W., Kobayashi, Y., Kouch, P. M., Kubo, H., Kushida, J., Láinez, M., Lamastra, A., Leone, F., Lindfors, E., Linhoff, L., Lombardi, S., Longo, F., López-Coto, R., López-Moya, M., López-Oramas, A., Loporchio, S., Lorini, A., Lyard, E., Fraga, B. Machado de Oliveira, Majumdar, P., Makariev, M., Maneva, G., Mang, N., Manganaro, M., Mangano, S., Mannheim, K., Mariotti, M., Martínez, M., Martínez-Chicharro, M., Mas-Aguilar, A., Mazin, D., Menchiari, S., Mender, S., Miceli, D., Miener, T., Miranda, J. M., Mirzoyan, R., González, M. Molero, Molina, E., Mondal, H. A., Moralejo, A., Morcuende, D., Nakamori, T., Nanci, C., Neustroev, V., Nickel, L., Rosillo, M. Nievas, Nigro, C., Nikolić, L., Nilsson, K., Nishijima, K., Ekoume, T. Njoh, Noda, K., Nozaki, S., Ohtani, Y., Okumura, A., Otero-Santos, J., Paiano, S., Palatiello, M., Paneque, D., Paoletti, R., Paredes, J. M., Peresano, M., Persic, M., Pihet, M., Pirola, G., Podobnik, F., Moroni, P. G. Prada, Prandini, E., Principe, G., Priyadarshi, C., Rhode, W., Ribó, M., Rico, J., Righi, C., Sahakyan, N., Saito, T., Satalecka, K., Saturni, F. G., Schleicher, B., Schmidt, K., Schmuckermaier, F., Schubert, J. L., Schweizer, T., Sciaccaluga, A., Silvestri, G., Sitarek, J., Sliusar, V., Sobczynska, D., Spolon, A., Stamerra, A., Strišković, J., Strom, D., Strzys, M., Suda, Y., Surić, T., Suutarinen, S., Tajima, H., Takahashi, M., Takeishi, R., Temnikov, P., Terauchi, K., Terzić, T., Truzzi, M. Teshima S., Tutone, A., Ubach, S., van Scherpenberg, J., Acosta, M. Vazquez, Ventura, S., Viale, I., Vigorito, C. F., Vitale, V., Walter, R., Will, M., Wunderlich, C., Yamamoto, T., Díaz, G. Chon C., Fiori, M., Lobo, M., Naletto, G., Polo, M., Rodríguez-Vázquez, J. J., Saha, P., and Zampieri, L.

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

In recent years, a new generation of optical intensity interferometers has emerged, leveraging the existing infrastructure of Imaging Atmospheric Cherenkov Telescopes (IACTs). The MAGIC telescopes host the MAGIC-SII system (Stellar Intensity Interferometer), implemented to investigate the feasibility and potential of this technique on IACTs. After the first successful measurements in 2019, the system was upgraded and now features a real-time, dead-time-free, 4-channel, GPU-based correlator. These hardware modifications allow seamless transitions between MAGIC's standard very-high-energy gamma-ray observations and optical interferometry measurements within seconds. We establish the feasibility and potential of employing IACTs as competitive optical Intensity Interferometers with minimal hardware adjustments. The measurement of a total of 22 stellar diameters are reported, 9 corresponding to reference stars with previous comparable measurements, and 13 with no prior measurements. A prospective implementation involving telescopes from the forthcoming Cherenkov Telescope Array Observatory's northern hemisphere array, such as the first prototype of its Large-Sized Telescopes, LST-1, is technically viable. This integration would significantly enhance the sensitivity of the current system and broaden the UV-plane coverage. This advancement would enable the system to achieve competitive sensitivity with the current generation of long-baseline optical interferometers over blue wavelengths., Comment: 18 pages, 13 figures, submitted to MNRAS

Published
2024
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43. Microwave control of collective quantum jump statistics of a dissipative Rydberg gas

Author

Liu, Zong-Kai, Sun, Kong-Hao, Cabot, Albert, Carollo, Federico, Zhang, Jun, Zhang, Zheng-Yuan, Zhang, Li-Hua, Liu, Bang, Han, Tian-Yu, Li, Qing, Ma, Yu, Chen, Han-Chao, Lesanovsky, Igor, Ding, Dong-Sheng, and Shi, Bao-Sen

Subjects
Quantum Physics
Abstract

Quantum many-body systems near phase transitions respond collectively to externally applied perturbations. We explore this phenomenon in a laser-driven dissipative Rydberg gas that is tuned to a bistable regime. Here two metastable phases coexist, which feature a low and high density of Rydberg atoms, respectively. The ensuing collective dynamics, which we monitor in situ, is characterized by stochastic collective jumps between these two macroscopically distinct many-body phases. We show that the statistics of these jumps can be controlled using a dual-tone microwave field. In particular, we find that the distribution of jump times develops peaks corresponding to subharmonics of the relative microwave detuning. Our study demonstrates the control of collective statistical properties of dissipative quantum many-body systems without the necessity of fine-tuning or of ultra cold temperatures. Such robust phenomena may find technological applications in quantum sensing and metrology.

Published
2024
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44. On the Readiness of Scientific Data for a Fair and Transparent Use in Machine Learning

Author

Giner-Miguelez, Joan, Gómez, Abel, and Cabot, Jordi

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Digital Libraries
Abstract

To ensure the fairness and trustworthiness of machine learning (ML) systems, recent legislative initiatives and relevant research in the ML community have pointed out the need to document the data used to train ML models. Besides, data-sharing practices in many scientific domains have evolved in recent years for reproducibility purposes. In this sense, academic institutions' adoption of these practices has encouraged researchers to publish their data and technical documentation in peer-reviewed publications such as data papers. In this study, we analyze how this broader scientific data documentation meets the needs of the ML community and regulatory bodies for its use in ML technologies. We examine a sample of 4041 data papers of different domains, assessing their completeness, coverage of the requested dimensions, and trends in recent years. We focus on the most and least documented dimensions and compare the results with those of an ML-focused venue (NeurIPS D&B track) publishing papers describing datasets. As a result, we propose a set of recommendation guidelines for data creators and scientific data publishers to increase their data's preparedness for its transparent and fairer use in ML technologies.

Published
2024

45. Enhanced Automated Code Vulnerability Repair using Large Language Models

Author

de-Fitero-Dominguez, David, Garcia-Lopez, Eva, Garcia-Cabot, Antonio, and Martinez-Herraiz, Jose-Javier

Subjects
Computer Science - Software Engineering, Computer Science - Computation and Language
Abstract

This research addresses the complex challenge of automated repair of code vulnerabilities, vital for enhancing digital security in an increasingly technology-driven world. The study introduces a novel and efficient format for the representation of code modification, using advanced Large Language Models (LLMs) such as Code Llama and Mistral. These models, fine-tuned on datasets featuring C code vulnerabilities, significantly improve the accuracy and adaptability of automated code repair techniques. A key finding is the enhanced repair accuracy of these models when compared to previous methods such as VulRepair, which underscores their practical utility and efficiency. The research also offers a critical assessment of current evaluation metrics, such as perfect predictions, and their limitations in reflecting the true capabilities of automated repair models in real-world scenarios. Following this, it underscores the importance of using test datasets devoid of train samples, emphasizing the need for dataset integrity to enhance the effectiveness of LLMs in code repair tasks. The significance of this work is its contribution to digital security, setting new standards for automated code vulnerability repair and paving the way for future advancements in the fields of cybersecurity and artificial intelligence. The study does not only highlight the potential of LLMs in enhancing code security but also fosters further exploration and research in these crucial areas.

Published
2024
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48. On the Readiness of Scientific Data Papers for a Fair and Transparent Use in Machine Learning

Author

Joan Giner-Miguelez, Abel Gómez, and Jordi Cabot

Subjects
Science
Abstract

Abstract To ensure the fairness and trustworthiness of machine learning (ML) systems, recent legislative initiatives and relevant research in the ML community have pointed out the need to document the data used to train ML models. Besides, data-sharing practices in many scientific domains have evolved in recent years for reproducibility purposes. In this sense, academic institutions’ adoption of these practices has encouraged researchers to publish their data and technical documentation in peer-reviewed publications such as data papers. In this study, we analyze how this broader scientific data documentation meets the needs of the ML community and regulatory bodies for its use in ML technologies. We examine a sample of 4041 data papers of different domains, assessing their coverage and trends in the requested dimensions and comparing them to those from an ML-focused venue (NeurIPS D&B), which publishes papers describing datasets. As a result, we propose a set of recommendation guidelines for data creators and scientific data publishers to increase their data’s preparedness for its transparent and fairer use in ML technologies.

Published
2025
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49. Realizing high power factor and thermoelectric performance in band engineered AgSbTe2

Author

Yu Zhang, Congcong Xing, Dongyang Wang, Aziz Genç, Seng Huat Lee, Cheng Chang, Zhi Li, Luyao Zheng, Khak Ho Lim, Hangtian Zhu, Rabeya Bosry Smriti, Yu Liu, Shaobo Cheng, Min Hong, Xiaolei Fan, Zhiqiang Mao, Li-Dong Zhao, Andreu Cabot, Tiejun Zhu, and Bed Poudel

Subjects
Science
Abstract

Abstract AgSbTe2 is a promising p-type thermoelectric material operating in the mid-temperature regime. To further enhance its thermoelectric performance, previous research has mainly focused on reducing lattice thermal conductivity by forming ordered nanoscale domains for instance. However, the relatively low power factor is the main limitation affecting the power density of AgSbTe2-based thermoelectric devices. In this work, we demonstrate that hole-doped AgSbTe2 with Sn induces the formation of a new impurity band just above the valence band maximum. This approach significantly improves the electrical transport properties, contrary to previous strategies that focused on reducing lattice thermal conductivity. As a result, we achieve a record-high power factor of 27 μWcm−1K−2 and a peak thermoelectric figure of merit zT of 2.5 at 673 K. This exceptional performance is attributed to an increased hole concentration resulting from the formation of the impurity band and a lower formation energy of the defect complexes ( $${V}_{{Ag}}^{1-}$$ V A g 1 − + $${{Sn}}_{{Sb}}^{1-}$$ S n S b 1 − ). Besides, the doped materials exhibit a significantly improved Seebeck coefficient by inhibiting bipolar conductivity and preventing the formation of n-type Ag2Te. Additionally, the optimized AgSbTe2 is used to fabricate a unicouple thermoelectric device that achieves energy conversion efficiencies of up to 12.1% and a high power density of 1.13 Wcm−2. This study provides critical insights and guidance for optimizing the performance of p-type AgSbTe2 in thermoelectric applications.

Published
2025
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50. A Pedagogical Strategy Applied in Physical Education to Encourage Sustainable Physical Activity

Author

Rachel Surprenant and Isabelle Cabot

Abstract

It is known that the practice of physical activity (PA) drops off drastically in late adolescence, during the transition to adulthood, leading to a deterioration in physical fitness among post-secondary students. Given the importance of the consequences of physical inactivity, interventions aimed at the sustained adoption of sufficient PA practice must be developed. The objective of this study is to evaluate the impact of a pedagogical strategy based on the question-behavior effect (QBE) implemented in the final post-secondary physical education and health (PEH) course and that capitalizes on the benefits derived from PA. An iterative, self-reflective exercise involving the personal benefits derived from PA practiced in PEH class was tested among 496 students (mean age: 19.10 [SD: 2.42]) from 15 post-secondary institutions and divided into three groups: self-reflection on benefits and on PA practiced (Group A; n = 152), self-reflection on PA practiced (Group B; n = 142), no self-reflection (Group C; n = 210). Two measurements of weekly PA practiced outside the school setting were taken: one week before the start of the final semester of PEH, and then six months after the end of that semester. In particular, the results indicate that PA practice outside of school increased among participants in Group A and that the proportion of students who were inactive at Time 1 who became active at Time 2 was higher in Group A. Thus, it appears that repeated awareness of the personal benefits of practicing PA in PEH class promotes engagement in PA done outside of class.

Published
2023

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