473,537 results on '"Angelo, A"'
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2. Transforming Family: Queer Kinship and Migration in Contemporary Francophone Literature by Jocelyn Frelier (review)
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Angelo, Adrienne
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- 2023
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3. Presidential Powers in Postcolonial Africa Deserve Historical Attention
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Angelo, Anaïs
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- 2022
4. Nina Bouraoui: la tentation de l'universel par Rabiaa Marhouch (review)
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Angelo, Adrienne
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- 2023
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5. Un sang d’encre: du corps en littérature contemporaine by Nora Cottille-Foley (review)
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Angelo, Adrienne
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- 2023
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6. Donor Support to Inclusive Education for Children with Disabilities: Who Does What in GPE Partner Countries?
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Global Partnership for Education (GPE), Stuart Cameron, Sophia D’Angelo, Daniela Gamboa Zapatel, and Maria Qureshi
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Children with disabilities remain among the most excluded from education in Global Partnership for Education (GPE) partner countries and other lower-income countries. Despite considerable activity funded both through GPE and by other donors, as well as by partner countries themselves, the level of international support to inclusive education remains too low and patchy for countries to transform their education systems so they are fully inclusive of children with disabilities. Development partners need to coordinate; help to build a stronger evidence base at global, regional and national levels; and go beyond isolated interventions to support reforms that have the potential to make the whole system more inclusive. To do this, development partners need to share knowledge on their activities globally and at the country level. This paper, and the underlying mapping exercise, aims to facilitate knowledge sharing in the sector by analyzing thematic and geographic focus areas of major development partners supporting inclusive education.
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- 2024
7. Minimizing speculation overhead in a parallel recognizer for regular texts
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Borsotti, Angelo, Breveglieri, Luca, Reghizzi, Stefano Crespi, and Morzenti, Angelo
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Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
Speculative data-parallel algorithms for language recognition have been widely experimented for various types of finite-state automata (FA), deterministic (DFA) and nondeterministic (NFA), often derived from regular expressions (RE). Such an algorithm cuts the input string into chunks, independently recognizes each chunk in parallel by means of identical FAs, and at last joins the chunk results and checks overall consistency. In chunk recognition, it is necessary to speculatively start the FAs in any state, thus causing an overhead that reduces the speedup compared to a serial algorithm. Existing data-parallel DFA-based recognizers suffer from the excessive number of starting states, and the NFA-based ones suffer from the number of nondeterministic transitions. Our data-parallel algorithm is based on the new FA type called reduced interface DFA (RI-DFA), which minimizes the speculation overhead without incurring in the penalty of nondeterministic transitions or of impractically enlarged DFA machines. The algorithm is proved to be correct and theoretically efficient, because it combines the state-reduction of an NFA with the speed of deterministic transitions, thus improving on both DFA-based and NFA-based existing implementations. The practical applicability of the RI-DFA approach is confirmed by a quantitative comparison of the number of starting states for a large public benchmark of complex FAs. On multi-core computing architectures, the RI-DFA recognizer is much faster than the NFA-based one on all benchmarks, while it matches the DFA-based one on some benchmarks and performs much better on some others. The extra time cost needed to construct an RI-DFA compared to a DFA is moderate and is compatible with a practical use.
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- 2024
8. AXI-REALM: Safe, Modular and Lightweight Traffic Monitoring and Regulation for Heterogeneous Mixed-Criticality Systems
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Benz, Thomas, Ottaviano, Alessandro, Liang, Chaoqun, Balas, Robert, Garofalo, Angelo, Restuccia, Francesco, Biondi, Alessandro, Rossi, Davide, and Benini, Luca
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Computer Science - Hardware Architecture - Abstract
The automotive industry is transitioning from federated, homogeneous, interconnected devices to integrated, heterogeneous, mixed-criticality systems (MCS). This leads to challenges in achieving timing predictability techniques due to access contention on shared resources, which can be mitigated using hardware-based spatial and temporal isolation techniques. Focusing on the interconnect as the point of access for shared resources, we propose AXI-REALM, a lightweight, modular, technology-independent, and open-source real-time extension to AXI4 interconnects. AXI-REALM uses a budget-based mechanism enforced on periodic time windows and transfer fragmentation to provide fair arbitration, coupled with execution predictability on real-time workloads. AXI-REALM features a comprehensive bandwidth and latency monitor at both the ingress and egress of the interconnect system. Latency information is also used to detect and reset malfunctioning subordinates, preventing missed deadlines. We provide a detailed cost assessment in a 12 nm node and an end-to-end case study implementing AXI-REALM into an open-source MCS, incurring an area overhead of less than 2%. When running a mixed-criticality workload, with a time-critical application sharing the interconnect with non-critical applications, we demonstrate that the critical application can achieve up to 68.2% of the isolated performance by enforcing fairness on the interconnect traffic through burst fragmentation, thus reducing the subordinate access latency by up to 24 times. Near-ideal performance, (above 95% of the isolated performance) can be achieved by distributing the available bandwidth in favor of the critical application., Comment: 14 pages, 13 figures, 3 tables, submitted to the IEEE for possible publication
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- 2025
9. On the Energy Consumption of Test Generation
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Kifetew, Fitsum, Prandi, Davide, and Susi, Angelo
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Computer Science - Software Engineering - Abstract
Research in the area of automated test generation has seen remarkable progress in recent years, resulting in several approaches and tools for effective and efficient generation of test cases. In particular, the EvoSuite tool has been at the forefront of this progress embodying various algorithms for automated test generation of Java programs. EvoSuite has been used to generate test cases for a wide variety of programs as well. While there are a number of empirical studies that report results on the effectiveness, in terms of code coverage and other related metrics, of the various test generation strategies and algorithms implemented in EvoSuite, there are no studies, to the best of our knowledge, on the energy consumption associated to the automated test generation. In this paper, we set out to investigate this aspect by measuring the energy consumed by EvoSuite when generating tests. We also measure the energy consumed in the execution of the test cases generated, comparing them with those manually written by developers. The results show that the different test generation algorithms consumed different amounts of energy, in particular on classes with high cyclomatic complexity. Furthermore, we also observe that manual tests tend to consume more energy as compared to automatically generated tests, without necessarily achieving higher code coverage. Our results also give insight into the methods that consume significantly higher levels of energy, indicating potential points of improvement both for EvoSuite as well as the different programs under test., Comment: Accepted for publication at 2025 IEEE Conference on Software Testing, Verification and Validation (ICST)
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- 2025
10. Impact of correlated noise on the reconstruction of the stochastic gravitational wave background with Einstein Telescope
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Caporali, Ilaria, Capurri, Giulia, Del Pozzo, Walter, Ricciardone, Angelo, and Dall'Armi, Lorenzo Valbusa
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General Relativity and Quantum Cosmology ,Astrophysics - Cosmology and Nongalactic Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Einstein Telescope (ET) is a proposed next-generation Gravitational Wave (GW) interferometer designed to detect a large number of astrophysical and cosmological sources with unprecedented sensitivity. A key target for ET is the detection of a stochastic gravitational-wave background (SGWB), a faint signal from unresolved GW sources. In its proposed triangular configuration, correlated Newtonian noise of seismic origin poses some challenges for the SGWB detection. We study the impact of correlated noise on the SGWB detection and relative parameter estimation for ET in the triangular configuration, comparing it to a 2L configuration with two separated L-shaped detectors. We perform a Bayesian analysis on simulated data, which shows that accurate reconstruction of the SGWB parameters and instrumental noise is achievable if the noise is properly modeled. We illustrate that neglecting correlated noise leads to significant biases in the parameter reconstruction. Our results show that while the 2L configuration provides slightly better parameter estimation precision, mainly due to its longer arm length, the triangular configuration remains competitive when accurate noise modeling is provided., Comment: 10 pages, 5 figures, 4 appendices
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- 2025
11. The putative center in NGC 1052
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Baczko, Anne-Kathrin, Kadler, Matthias, Ros, Eduardo, Fromm, Christian M., Wielgus, Maciek, Perucho, Manel, Krichbaum, Thomas P., Baloković, Mislav, Blackburn, Lindy, Chan, Chi-kwan, Issaoun, Sara, Janssen, Michael, Ricci, Luca, Akiyama, Kazunori, Albentosa-Ruíz, Ezequiel, Alberdi, Antxon, Alef, Walter, Algaba, Juan Carlos, Anantua, Richard, Asada, Keiichi, Azulay, Rebecca, Bach, Uwe, Ball, David, Bandyopadhyay, Bidisha, Barrett, John, Bauböck, Michi, Benson, Bradford A., Bintley, Dan, Blundell, Raymond, Bouman, Katherine L., Bower, Geoffrey C., Boyce, Hope, Bremer, Michael, Brinkerink, Christiaan D., Brissenden, Roger, Britzen, Silke, Broderick, Avery E., Broguiere, Dominique, Bronzwaer, Thomas, Bustamante, Sandra, Byun, Do-Young, Carlstrom, John E., Ceccobello, Chiara, Chael, Andrew, Chang, Dominic O., Chatterjee, Koushik, Chatterjee, Shami, Chen, Ming-Tang, Chen, Yongjun, Cheng, Xiaopeng, Cho, Ilje, Christian, Pierre, Conroy, Nicholas S., Conway, John E., Cordes, James M., Crawford, Thomas M., Crew, Geoffrey B., Cruz-Osorio, Alejandro, Cui, Yuzhu, Dahale, Rohan, Davelaar, Jordy, De Laurentis, Mariafelicia, Deane, Roger, Dempsey, Jessica, Desvignes, Gregory, Dexter, Jason, Dhruv, Vedant, Dihingia, Indu K., Doeleman, Sheperd S., Dougall, Sean Taylor, Dzib, Sergio A., Eatough, Ralph P., Emami, Razieh, Falcke, Heino, Farah, Joseph, Fish, Vincent L., Fomalont, Edward, Ford, H. Alyson, Foschi, Marianna, Fraga-Encinas, Raquel, Freeman, William T., Friberg, Per, Fuentes, Antonio, Galison, Peter, Gammie, Charles F., García, Roberto, Gentaz, Olivier, Georgiev, Boris, Goddi, Ciriaco, Gold, Roman, Gómez-Ruiz, Arturo I., Gómez, José L., Gu, Minfeng, Gurwell, Mark, Hada, Kazuhiro, Haggard, Daryl, Haworth, Kari, Hecht, Michael H., Hesper, Ronald, Heumann, Dirk, Ho, Luis C., Ho, Paul, Honma, Mareki, Huang, Chih-Wei L., Huang, Lei, Hughes, David H., Impellizzeri, C. M. Violette, Inoue, Makoto, James, David J., Jannuzi, Buell T., Jeter, Britton, Jiang, Wu, Jiménez-Rosales, Alejandra, Johnson, Michael D., Jorstad, Svetlana, Joshi, Abhishek V., Jung, Taehyun, Karami, Mansour, Karuppusamy, Ramesh, Kawashima, Tomohisa, Keating, Garrett K., Kettenis, Mark, Kim, Dong-Jin, Kim, Jae-Young, Kim, Jongsoo, Kim, Junhan, Kino, Motoki, Koay, Jun Yi, Kocherlakota, Prashant, Kofuji, Yutaro, Koyama, Shoko, Kramer, Carsten, Kramer, Joana A., Kramer, Michael, Kuo, Cheng-Yu, La Bella, Noemi, Lauer, Tod R., Lee, Daeyoung, Lee, Sang-Sung, Leung, Po Kin, Levis, Aviad, Li, Zhiyuan, Lico, Rocco, Lindahl, Greg, Lindqvist, Michael, Lisakov, Mikhail, Liu, Jun, Liu, Kuo, Liuzzo, Elisabetta, Lo, Wen-Ping, Lobanov, Andrei P., Loinard, Laurent, Lonsdale, Colin J., Lowitz, Amy E., Lu, Ru-Sen, MacDonald, Nicholas R., Mao, Jirong, Marchili, Nicola, Markoff, Sera, Marrone, Daniel P., Marscher, Alan P., Martí-Vidal, Iván, Matsushita, Satoki, Matthews, Lynn D., Medeiros, Lia, Menten, Karl M., Michalik, Daniel, Mizuno, Izumi, Mizuno, Yosuke, Moran, James M., Moriyama, Kotaro, Moscibrodzka, Monika, Mulaudzi, Wanga, Müller, Cornelia, Müller, Hendrik, Mus, Alejandro, Musoke, Gibwa, Myserlis, Ioannis, Nadolski, Andrew, Nagai, Hiroshi, Nagar, Neil M., Nair, Dhanya G., Nakamura, Masanori, Narayanan, Gopal, Natarajan, Iniyan, Nathanail, Antonios, Fuentes, Santiago Navarro, Neilsen, Joey, Neri, Roberto, Ni, Chunchong, Noutsos, Aristeidis, Nowak, Michael A., Oh, Junghwan, Okino, Hiroki, Sánchez, Héctor Raúl Olivares, Ortiz-León, Gisela N., Oyama, Tomoaki, Özel, Feryal, Palumbo, Daniel C. M., Paraschos, Georgios Filippos, Park, Jongho, Parsons, Harriet, Patel, Nimesh, Pen, Ue-Li, Pesce, Dominic W., Piétu, Vincent, Plambeck, Richard, PopStefanija, Aleksandar, Porth, Oliver, Pötzl, Felix M., Prather, Ben, Preciado-López, Jorge A., Principe, Giacomo, Psaltis, Dimitrios, Pu, Hung-Yi, Ramakrishnan, Venkatessh, Rao, Ramprasad, Rawlings, Mark G., Raymond, Alexander W., Ricarte, Angelo, Ripperda, Bart, Roelofs, Freek, Rogers, Alan, Romero-Cañizales, Cristina, Roshanineshat, Arash, Rottmann, Helge, Roy, Alan L., Ruiz, Ignacio, Ruszczyk, Chet, Rygl, Kazi L. J., Sánchez, Salvador, Sánchez-Argüelles, David, Sánchez-Portal, Miguel, Sasada, Mahito, Satapathy, Kaushik, Savolainen, Tuomas, Schloerb, F. Peter, Schonfeld, Jonathan, Schuster, Karl-Friedrich, Shao, Lijing, Shen, Zhiqiang, Small, Des, Sohn, Bong Won, SooHoo, Jason, Salas, León David Sosapanta, Souccar, Kamal, Stanway, Joshua S., Sun, He, Tazaki, Fumie, Tetarenko, Alexandra J., Tiede, Paul, Tilanus, Remo P. J., Titus, Michael, Torne, Pablo, Toscano, Teresa, Traianou, Efthalia, Trent, Tyler, Trippe, Sascha, Turk, Matthew, van Bemmel, Ilse, van Langevelde, Huib Jan, van Rossum, Daniel R., Vos, Jesse, Wagner, Jan, Ward-Thompson, Derek, Wardle, John, Washington, Jasmin E., Weintroub, Jonathan, Wharton, Robert, Wiik, Kaj, Witzel, Gunther, Wondrak, Michael F., Wong, George N., Wu, Qingwen, Yadlapalli, Nitika, Yamaguchi, Paul, Yfantis, Aristomenis, Yoon, Doosoo, Young, André, Young, Ken, Younsi, Ziri, Yu, Wei, Yuan, Feng, Yuan, Ye-Fei, Zensus, J. Anton, Zhang, Shuo, and Zhao, Guang-Yao
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Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Astrophysics of Galaxies - Abstract
Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A
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- 2025
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12. The TESS-Keck Survey XXIV: Outer Giants may be More Prevalent in the Presence of Inner Small Planets
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Van Zandt, Judah, Petigura, Erik A., Lubin, Jack, Weiss, Lauren M., Turtelboom, Emma V., Fetherolf, Tara, Murphy, Joseph M. Akana, Crossfield, Ian J. M., Gilbert, Greg, Mocnik, Teo, Batalha, Natalie M., Dressing, Courtney, Fulton, Benjamin, Howard, Andrew W., Huber, Daniel, Isaacson, Howard, Kane, Stephen R., Robertson, Paul, Roy, Arpita, Angelo, Isabel, Behmard, Aida, Beard, Corey, Chontos, Ashley, Dai, Fei, Dalba, Paul A., Giacalone, Steven, Hill, Michelle L., Hirsch, Lea A., Holcomb, Rae, Howell, Steve B., Mayo, Andrew W., MacDougall, Mason G., Pidhorodetska, Daria, Polanski, Alex S., Rogers, James, Rosenthal, Lee J., Rubenzahl, Ryan A., Scarsdale, Nicholas, Tyler, Dakotah, Yee, Samuel W., and Zink, Jon
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Astrophysics - Earth and Planetary Astrophysics - Abstract
We present the results of the Distant Giants Survey, a three-year radial velocity (RV) campaign to search for wide-separation giant planets orbiting Sun-like stars known to host an inner transiting planet. We defined a distant giant to have $a$ = 1--10 AU and $M_{p} \sin i = 70-4000$ \mearth~ = 0.2-12.5 \mj, and required transiting planets to have $a<1$ AU and $R_{p} = 1-4$ \rearth. We assembled our sample of 47 stars using a single selection function, and observed each star at monthly intervals to obtain $\approx$30 RV observations per target. The final catalog includes a total of twelve distant companions: four giant planets detected during our survey, two previously known giant planets, and six objects of uncertain disposition identified through RV/astrometric accelerations. Statistically, half of the uncertain objects are planets and the remainder are stars/brown dwarfs. We calculated target-by-target completeness maps to account for missed planets. We found evidence for a moderate enhancement of distant giants (DG) in the presence of close-in small planets (CS), P(DG|CS) = $30^{+14}_{-12}\%$, over the field rate of P(DG) = $16^{+2}_{-2}\%$. No enhancement is disfavored ($p \sim$ 8%). In contrast to a previous study, we found no evidence that stellar metallicity enhances P(DG|CS). We found evidence that distant giant companions are preferentially found in systems with multiple transiting planets and have lower eccentricities than randomly selected giant planets. This points toward dynamically cool formation pathways for the giants that do not disturb the inner systems., Comment: 32 pages, 20 figures, 4 tables. Comments welcome
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- 2025
13. Test Case Generation for Simulink Models: An Experience from the E-Bike Domain
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Marzella, Michael, Bombarda, Andrea, Minervini, Marcello, Bisceglia, Nunzio Marco, Gargantini, Angelo, and Menghi, Claudio
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Computer Science - Software Engineering - Abstract
Cyber-physical systems development often requires engineers to search for defects in their Simulink models. Search-based software testing (SBST) is a standard technology that supports this activity. To increase practical adaption, industries need empirical evidence of the effectiveness and efficiency of (existing) SBST techniques on benchmarks from different domains and of varying complexity. To address this industrial need, this paper presents our experience assessing the effectiveness and efficiency of SBST in generating failure-revealing test cases for cyber-physical systems requirements. Our study subject is within the electric bike (e-Bike) domain and concerns the software controller of an e-Bike motor, particularly its functional, regulatory, and safety requirements. We assessed the effectiveness and efficiency of HECATE, an SBST framework for Simulink models, to analyze two software controllers. HECATE successfully identified failure-revealing test cases for 83% (30 out of 36) of our experiments. It required, on average, 1 h 17 min 26 s (min = 11 min 56 s, max = 8 h 16 min 22 s, std = 1 h 50 min 34 s) to compute the failure-revealing test cases. The developer of the e-Bike model confirmed the failures identified by HECATE. We present the lessons learned and discuss the relevance of our results for industrial applications, the state of practice improvement, and the results' generalizability., Comment: 10 pages, 2 pages for references
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- 2025
14. A multi-frequency study of sub-parsec jets with the Event Horizon Telescope
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Röder, Jan, Wielgus, Maciek, Lobanov, Andrei P., Krichbaum, Thomas P., Nair, Dhanya G., Lee, Sang-Sung, Ros, Eduardo, Fish, Vincent L., Blackburn, Lindy, Chan, Chi-kwan, Issaoun, Sara, Janssen, Michael, Johnson, Michael D., Doeleman, Sheperd S., Bower, Geoffrey C., Crew, Geoffrey B., Tilanus, Remo P. J., Savolainen, Tuomas, Impellizzeri, C. M. Violette, Alberdi, Antxon, Baczko, Anne-Kathrin, Gómez, José L., Lu, Ru-Sen, Paraschos, Georgios F., Traianou, Efthalia, Goddi, Ciriaco, Kim, Daewon, Lisakov, Mikhail, Kovalev, Yuri Y., Voitsik, Petr A., Sokolovsky, Kirill V., Akiyama, Kazunori, Albentosa-Ruíz, Ezequiel, Alef, Walter, Algaba, Juan Carlos, Anantua, Richard, Asada, Keiichi, Azulay, Rebecca, Bach, Uwe, Ball, David, Baloković, Mislav, Bandyopadhyay, Bidisha, Barrett, John, Bauböck, Michi, Benson, Bradford A., Bintley, Dan, Blundell, Raymond, Bouman, Katherine L., Bremer, Michael, Brinkerink, Christiaan D., Brissenden, Roger, Britzen, Silke, Broderick, Avery E., Broguiere, Dominique, Bronzwaer, Thomas, Bustamante, Sandra, Byun, Do-Young, Carlstrom, John E., Ceccobello, Chiara, Chael, Andrew, Chang, Dominic O., Chatterjee, Koushik, Chatterjee, Shami, Chen, Ming-Tang, Chen, Yongjun, Cheng, Xiaopeng, Cho, Ilje, Christian, Pierre, Conroy, Nicholas S., Conway, John E., Cordes, James M., Crawford, Thomas M., Cruz-Osorio, Alejandro, Cui, Yuzhu, Curd, Brandon, Dahale, Rohan, Davelaar, Jordy, De Laurentis, Mariafelicia, Deane, Roger, Dempsey, Jessica, Desvignes, Gregory, Dexter, Jason, Dhruv, Vedant, Dihingia, Indu K., Dougall, Sean Taylor, Dzib, Sergio A., Eatough, Ralph P., Emami, Razieh, Falcke, Heino, Farah, Joseph, Fomalont, Edward, Ford, H. Alyson, Foschi, Marianna, Fraga-Encinas, Raquel, Freeman, William T., Friberg, Per, Fromm, Christian M., Fuentes, Antonio, Galison, Peter, Gammie, Charles F., García, Roberto, Gentaz, Olivier, Georgiev, Boris, Gold, Roman, Gómez-Ruiz, Arturo I., Gu, Minfeng, Gurwell, Mark, Hada, Kazuhiro, Haggard, Daryl, Haworth, Kari, Hecht, Michael H., Hesper, Ronald, Heumann, Dirk, Ho, Luis C., Ho, Paul, Honma, Mareki, Huang, Chih-Wei L., Huang, Lei, Hughes, David H., Ikeda, Shiro, Inoue, Makoto, James, David J., Jannuzi, Buell T., Jeter, Britton, Jiang, Wu, Jiménez-Rosales, Alejandra, Jorstad, Svetlana, Joshi, Abhishek V., Jung, Taehyun, Karami, Mansour, Karuppusamy, Ramesh, Kawashima, Tomohisa, Keating, Garrett K., Kettenis, Mark, Kim, Dong-Jin, Kim, Jae-Young, Kim, Jongsoo, Kim, Junhan, Kino, Motoki, Koay, Jun Yi, Kocherlakota, Prashant, Kofuji, Yutaro, Koyama, Shoko, Kramer, Carsten, Kramer, Joana A., Kramer, Michael, Kuo, Cheng-Yu, La Bella, Noemi, Lauer, Tod R., Lee, Daeyoung, Leung, Po Kin, Levis, Aviad, Li, Zhiyuan, Lico, Rocco, Lindahl, Greg, Lindqvist, Michael, Liu, Jun, Liu, Kuo, Liuzzo, Elisabetta, Lo, Wen-Ping, Loinard, Laurent, Lonsdale, Colin J., Lowitz, Amy E., MacDonald, Nicholas R., Mao, Jirong, Marchili, Nicola, Markoff, Sera, Marrone, Daniel P., Marscher, Alan P., Martí-Vidal, Iván, Matsushita, Satoki, Matthews, Lynn D., Medeiros, Lia, Menten, Karl M., Michalik, Daniel, Mizuno, Izumi, Mizuno, Yosuke, Moran, James M., Moriyama, Kotaro, Moscibrodzka, Monika, Mulaudzi, Wanga, Müller, Cornelia, Müller, Hendrik, Mus, Alejandro, Musoke, Gibwa, Myserlis, Ioannis, Nadolski, Andrew, Nagai, Hiroshi, Nagar, Neil M., Nakamura, Masanori, Narayanan, Gopal, Natarajan, Iniyan, Nathanail, Antonios, Fuentes, Santiago Navarro, Neilsen, Joey, Neri, Roberto, Ni, Chunchong, Noutsos, Aristeidis, Nowak, Michael A., Oh, Junghwan, Okino, Hiroki, Sánchez, Héctor R. Olivares, Ortiz-León, Gisela N., Oyama, Tomoaki, özel, Feryal, Palumbo, Daniel C. M., Park, Jongho, Parsons, Harriet, Patel, Nimesh, Pen, Ue-Li, Pesce, Dominic W., Piétu, Vincent, Plambeck, Richard, PopStefanija, Aleksandar, Porth, Oliver, Pötzl, Felix M., Prather, Ben, Preciado-López, Jorge A., Principe, Giacomo, Psaltis, Dimitrios, Pu, Hung-Yi, Ramakrishnan, Venkatessh, Rao, Ramprasad, Rawlings, Mark G., Ricarte, Angelo, Ripperda, Bart, Roelofs, Freek, Rogers, Alan, Romero-Cañizales, Cristina, Roshanineshat, Arash, Rottmann, Helge, Roy, Alan L., Ruiz, Ignacio, Ruszczyk, Chet, Rygl, Kazi L. J., Sánchez, Salvador, Sánchez-Argüelles, David, Sánchez-Portal, Miguel, Sasada, Mahito, Satapathy, Kaushik, Schloerb, F. Peter, Schonfeld, Jonathan, Schuster, Karl-Friedrich, Shao, Lijing, Shen, Zhiqiang, Small, Des, Sohn, Bong Won, SooHoo, Jason, Salas, León David Sosapanta, Souccar, Kamal, Stanway, Joshua S., Sun, He, Tazaki, Fumie, Tetarenko, Alexandra J., Tiede, Paul, Titus, Michael, Torne, Pablo, Toscano, Teresa, Trent, Tyler, Trippe, Sascha, Turk, Matthew, van Bemmel, Ilse, van Langevelde, Huib J., van Rossum, Daniel R., Vos, Jesse, Wagner, Jan, Ward-Thompson, Derek, Wardle, John, Washington, Jasmin E., Weintroub, Jonathan, Wharton, Robert, Wiik, Kaj, Witzel, Gunther, Wondrak, Michael F., Wong, George N., Wu, Qingwen, Yadlapalli, Nitika, Yamaguchi, Paul, Yfantis, Aristomenis, Yoon, Doosoo, Young, André, Young, Ken, Younsi, Ziri, Yu, Wei, Yuan, Feng, Yuan, Ye-Fei, Zensus, J. Anton, Zhang, Shuo, Zhao, Guang-Yao, and Zhao, Shan-Shan
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Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Astrophysics of Galaxies ,Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.
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- 2025
15. Search-based Testing of Simulink Models with Requirements Tables
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Formica, Federico, George, Chris, Rahmatyan, Shayda, Pantelic, Vera, Lawford, Mark, Gargantini, Angelo, and Menghi, Claudio
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Computer Science - Software Engineering - Abstract
Search-based software testing (SBST) of Simulink models helps find scenarios that demonstrate that the system can reach a state that violates one of its requirements. However, many SBST techniques for Simulink models rely on requirements being expressed in logical languages, limiting their adoption in industry. To help with the adoption, SBST methods and tools for Simulink models need to be integrated with tools used by engineers to specify requirements. This work presents the first black-box testing approach for Simulink models that supports Requirements Table (RT), a tool from Simulink Requirements Toolbox used by practitioners to express software requirements. We evaluated our solution by considering 60 model-RT combinations each made by a model and an RT. Our SBST framework returned a failure-revealing test case for 70% of the model-RT combinations. Remarkably, it identified a failure-revealing test case for three model-RT combinations for a cruise controller of an industrial simulator that other previously used tools were not able to find. The efficiency of our SBST solution is acceptable for practical applications and comparable with existing SBST tools that are not based on RT.
- Published
- 2025
16. Robust Moving-horizon Estimation for Nonlinear Systems: From Perfect to Imperfect Optimization
- Author
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Alessandri, Angelo
- Subjects
Electrical Engineering and Systems Science - Systems and Control ,93 - Abstract
Robust stability of moving-horizon estimators is investigated for nonlinear discrete-time systems that are detectable in the sense of incremental input/output-to-state stability and are affected by disturbances. The estimate of a moving-horizon estimator stems from the on-line solution of a least-squares minimization problem at each time instant. The resulting stability guarantees depend on the optimization tolerance in solving such minimization problems. Specifically, two main contributions are established: (i) the robust stability of the estimation error, while supposing to solve exactly the on-line minimization problem; (ii) the practical robust stability of the estimation error with state estimates obtained by an imperfect minimization. Finally, the construction of such robust moving-horizon estimators and the performances resulting from the design based on the theoretical findings are showcased with two numerical examples., Comment: 18 pages, 2 figures, 24 bibliographic references
- Published
- 2025
17. Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run
- Author
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The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. 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L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. P., Palomba, C., Palud, P., Pan, H., Pan, J., Pan, K. C., Panai, R., Panda, P. K., Pandey, S., Panebianco, L., Pang, P. T. H., Pannarale, F., Pannone, K. A., Pant, B. C., Panther, F. H., Paoletti, F., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Paquis, A., Parisi, A., Park, B. -J., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passenger, L., Passuello, D., Patane, O., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, K., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, Z., Perez, J. J., Périgois, C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petracca, S., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piarulli, M., Piccari, L., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Puecher, A., Pullin, J., Punturo, M., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Raab, F. J., Raabith, S. S., Raaijmakers, G., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Ranjan, S., Ransom, K., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Relton, P., Renzini, A. I., Rettegno, P., Revenu, B., Reyes, R., Rezaei, A. S., Ricci, F., Ricci, M., Ricciardone, A., Richardson, J. W., Richardson, M., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S. K., Roy, S., Rozza, D., Ruggi, P., Ruhama, N., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Saha, S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Santoliquido, F., Saravanan, T. R., Sarin, N., Sasaoka, S., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Scacco, V., Schaetzl, D., Scheel, M., Schiebelbein, A., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schulte, B. W., Schutz, B. F., Schwartz, E., Scialpi, M., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Serra, M., Servignat, G., Sevrin, A., Shaffer, T., Shah, U. S., Shaikh, M. A., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shaw, M. R., Shawhan, P., Shcheblanov, N. S., Sheridan, E., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singh, S., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somiya, K., Song, I., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Sotani, H., Soulard, R., Southgate, A., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Spoon, J. B., Sprague, C. A., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suleiman, L., Sullivan, K. D., Sun, L., Sunil, S., Suresh, J., Sutton, P. J., Suzuki, T., Suzuki, Y., Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takase, T., Takatani, K., Takeda, H., Takeshita, K., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, P., Tiwari, S., Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troian, G., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., Zweizig, J., Furlan, S. B. Araujo, Arzoumanian, Z., Basu, A., Cassity, A., Cognard, I., Crowter, K., del Palacio, S., Espinoza, C. M., Fonseca, E., Flynn, C. M. L., Gancio, G., Garcia, F., Gendreau, K. C., Good, D. C., Guillemot, L., Guillot, S., Keith, M. J., Kuiper, L., Lower, M. E., Lyne, A. G., McKee, J. W., Meyers, B. W., Palfreyman, J. L., Pearlman, A. B., Romero, G. E., Shannon, R. M., Shaw, B., Stairs, I. H., Stappers, B. W., Tan, C. M., Theureau, G., Thompson, M., Weltevrede, P., and Zubieta, E.
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables
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- 2025
18. Open-Source Heterogeneous SoCs for AI: The PULP Platform Experience
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Conti, Francesco, Garofalo, Angelo, Rossi, Davide, Tagliavini, Giuseppe, and Benini, Luca
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Computer Science - Hardware Architecture ,Computer Science - Neural and Evolutionary Computing ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Since 2013, the PULP (Parallel Ultra-Low Power) Platform project has been one of the most active and successful initiatives in designing research IPs and releasing them as open-source. Its portfolio now ranges from processor cores to network-on-chips, peripherals, SoC templates, and full hardware accelerators. In this article, we focus on the PULP experience designing heterogeneous AI acceleration SoCs - an endeavour encompassing SoC architecture definition; development, verification, and integration of acceleration IPs; front- and back-end VLSI design; testing; development of AI deployment software., Comment: Preprinted submitted to IEEE Solid-State Circuits Magazine
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- 2024
19. Comments on Orbits of particles with magnetic dipole moment around magnetized Schwarzschild black holes: Applications to S2 star orbit, arXiv:2406.03371v2
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Sodejana, Miles Angelo
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General Relativity and Quantum Cosmology - Abstract
We provided comments on the article Orbits of particles with magnetic dipole moment around magnetized Schwarzschild black holes: Applications to S2 star orbit by Uktamjon Uktamov, Mohsen Fathi, Javlon Rayimbaev, and Ahmadjon Abdujabbarov from arXiv:2406.03371v2. We derived the Hamilton-Jacobi equation used in the article from the Lagrangian utilized and found inconsistencies in the use of the interaction term which describes the magnetic dipole moment of the particle. Consequently, this results in incorrect equations of motion for the particle., Comment: 5 pages; comment on arXiv:2406.03371v2
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- 2024
20. Demographics of black holes at $<$100 R$_{\rm g}$ scales: accretion flows, jets, and shadows
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Nair, Dhanya G., Nagar, Neil M., Ramakrishnan, Venkatessh, Wielgus, Maciek, Arratia, Vicente, Krichbaum, Thomas P., Zhang, Xinyue A., Ricarte, Angelo, S., Silpa, Hernández-Yévenes, Joaquín, Ford, Nicole M., Bandyopadhyay, Bidisha, Gurwell, Mark, Burridge, Roman, Pesce, Dominic W., Doeleman, Sheperd S., Kim, Jae-Young, Kim, Daewon, Janssen, Michael, von Fellenberg, Sebastiano D., Fromm, Christian M., Lee, Deokhyeong, Falcke, Heino, Wagner, Jan, Bower, Geoffrey C., Baczko, Anne-Kathrin, Kim, Dong-Jin, Akiyama, Kazunori, Asada, Keiichi, Arevalo, Patricia, Bignall, Hayley, Blackburn, Lindy, Broderick, Avery E., Brunthaler, Andreas, Chan, Chi-kwan, Doi, Akihiro, Fish, Vincent L., Fomalont, Edward, Gómez, José L., Haggard, Daryl, Hada, Kazuhiro, Herrera-Camus, Rodrigo, Hoak, Daniel, Hughes, David, Hlavacek-Larrondo, Julie, Jorstad, Svetlana, Johnson, Michael D., Kawashima, Tomohisa, Keating, Garrett K., Kharb, Preeti, Koay, Jun Yi, Koyama, Shoko, Kuo, Cheng-Yu, Leigh, Nathan W. C., Lira, Paulina, Lindqvist, Michael, Lobanov, Andrei P., Lo, Wen-Ping, Lu, Ru-Sen, Markoff, Sera, MacDonald, Nicholas R., Martínez-Aldama, Mary Loli, Matthews, Lynn D., Matsushita, Satoki, Mezcua, Mar, Moscibrodzka, Monika, Müller, Hendrik, Nagai, Hiroshi, Nakamura, Masanori, Natarajan, Priyamvada, Narayanan, Gopal, Nowak, Michael A., Sánchez, Héctor Raúl Olivares, Park, Jongho, Psaltis, Dimitrios, Pu, Hung-Yi, Porth, Oliver, Rao, Ramprasad, Reynolds, Cormac, Reeves, Rodrigo, Romero-Cañizales, Cristina, Ros, Eduardo, Rottmann, Helge, Roy, Alan L., Schleicher, Dominik, Savolainen, Tuomas, Impellizzeri, C. M. Violette, Treister, Ezequiel, Wiik, Kaj, and Zensus, J. Anton
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Astrophysics - Astrophysics of Galaxies - Abstract
Using the Event Horizon Telescope (EHT), the gravitationally lensed rings around the supermassive black holes (SMBHs) in Messier 87 (M87) and Sagittarius A* (Sgr A*) have now been successfully imaged at a resolution under 10 gravitational radii (R$_{\rm g}$ $ = \rm{GM/c^2}$). To expand studies beyond M87 and Sgr A*, we have constructed the Event Horizon and Environs (ETHER) sample, a comprehensive database encompassing approximately 3.15 million SMBH mass estimates, $\sim$ 20,000 Very-Long Baseline Interferometry (VLBI) radio flux densities, and $\sim$ 36,000 hard X-ray flux densities. This database is designed to identify and optimize target selection for the EHT and its upgrades on the ground and in space. We have identified a Gold Sample (GS) of nearby low-luminosity Active Galactic Nuclei (AGNs) within it that are ideal for studying jet bases and potentially imaging black hole shadows. We observed 27 of these AGNs using the EHT from 2022 to 2024, providing an opportunity to resolve and image accretion flows and jets at resolutions of $\leq$ 100 R$_{\rm g}$. Only a few SMBHs have sufficiently high enough flux density to be imaged at scales of $\leq$ 50 R$_{\rm g}$ with the present EHT. Among these are M87, Sgr A*, NGC4594 (Sombrero/M104), NGC4261, and NGC4374 (Messier 84/M84). Of these, NGC4261, Sombrero, and M84 have been observed and/or are scheduled for deep imaging with EHT+ALMA from 2023 to 2025. Sombrero, NGC4261, M84, NGC4278, and NGC5232 are clearly detected in our EHT+ALMA observations in 2022, indicating that the 230 GHz flux density from the accretion flows is significantly high. Ongoing imaging of the ETHER GS will enable measurements of black hole mass and spin, help constrain General Relativity, and enrich our understanding of jet launching and accretion inflows across a broad multi-parameter space, including black hole mass, spin, accretion rate, and orientation., Comment: 9 pages, 6 figures, 1 table, published in Proceedings of the 16th EVN Symposium, Ed. E. Ros, P. Benke, S.A. Dzib, I. Rottmann, & J.A. Zensus, Bonn: Max-Planck-Institut f\"ur Radioastronomie, 2024, pages 75-84, https://cloud.mpifr-bonn.mpg.de/index.php/s/BkX2CC2Xjn2aKR4
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- 2024
21. Non-linear effects on the Cosmological Gravitational Wave Background anisotropies
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Mierna, Alina, Matarrese, Sabino, Bartolo, Nicola, and Ricciardone, Angelo
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Astrophysics - Cosmology and Nongalactic Astrophysics ,General Relativity and Quantum Cosmology ,High Energy Physics - Theory - Abstract
The Cosmological Gravitational Wave Background (CGWB) anisotropies contain valuable information about the physics of the early universe. Given that General Relativity is intrinsically nonlinear, it is important to look beyond first-order contributions in cosmological perturbations. In this work, we present a non-perturbative approach for the computation of CGWB anisotropies at large scales, providing the extension of the initial conditions and the Sachs-Wolfe effect for the CGWB, which encodes the full non-linearity of the scalar metric perturbations. We also derive the non-perturbative expression for three-point correlation of the gravitational wave energy density perturbation in the case of an inflationary CGWB with a scale-invariant power spectrum and negligible primordial non-Gaussianity. We show that, under such conditions, the gravitational wave energy density perturbations are lognormally distributed, leading to an interesting effect such as intermittency.
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- 2024
22. Spectral Properties and Magic Generation in $T$-doped Random Clifford Circuits
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Szombathy, Dominik, Valli, Angelo, Moca, Cătălin Paşcu, Asbóth, János, Farkas, Lóránt, Rakovszky, Tibor, and Zaránd, Gergely
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Quantum Physics - Abstract
We study the emergence of complexity in deep random $N$-qubit $T$-gate doped Clifford circuits, as reflected in their spectral properties and in magic generation, characterized by the stabilizer R\'enyi entropy. For pure (undoped) Clifford circuits, a unique periodic orbit structure in the space of Pauli strings implies peculiar spectral correlations and level statistics with large degeneracies. $T$-gate doping induces an exponentially fast transition to chaotic behavior, described by random matrix theory. To characterize magic generation properties of the Clifford+$T$ ensemble, we determine the distribution of magic, as well as the average nonstabilizing power of the quantum circuit ensemble. In the dilute limit, $N_T \ll N$, magic generation is governed by single-qubit behavior, and magic increases linearly with the number of $T$-gates, $N_T$. For $N_T\gg N$, magic distribution converges to that of Haar-random unitaries, and averages to a finite magic density, $\mu$, $\lim_{N\to\infty} \langle\mu\rangle_\text{Haar} = 1$. Although our numerics has large finite-size effects, finite size scaling reveals a magic density phase transition at a critical $T$-gate density, $n^{*}_T = (N_T/N)^* \approx 2.41$ in the $N \to \infty$ limit. This is in contrast to the spectral transition, where ${\cal O} (1)$ $T$-gates suffice to remove spectral degeneracies and to induce a transition to chaotic behavior in the thermodynamic limit. Magic is therefore a more sensitive indicator of complexity., Comment: 13 pages, 9 figures
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- 2024
23. Deciphering Social Behaviour: a Novel Biological Approach For Social Users Classification
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Allegrini, Edoardo, Di Paolo, Edoardo, Petrocchi, Marinella, and Spognardi, Angelo
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Computer Science - Social and Information Networks - Abstract
Social media platforms continue to struggle with the growing presence of social bots-automated accounts that can influence public opinion and facilitate the spread of disinformation. Over time, these social bots have advanced significantly, making them increasingly difficult to distinguish from genuine users. Recently, new groups of bots have emerged, utilizing Large Language Models to generate content for posting, further complicating detection efforts. This paper proposes a novel approach that uses algorithms to measure the similarity between DNA strings, commonly used in biological contexts, to classify social users as bots or not. Our approach begins by clustering social media users into distinct macro species based on the similarities (and differences) observed in their timelines. These macro species are subsequently classified as either bots or genuine users, using a novel metric we developed that evaluates their behavioral characteristics in a way that mirrors biological comparison methods. This study extends beyond past approaches that focus solely on identical behaviors via analyses of the accounts' timelines. By incorporating new metrics, our approach systematically classifies non-trivial accounts into appropriate categories, effectively peeling back layers to reveal non-obvious species., Comment: Accepted at 40th ACM/SIGAPP Symposium On Applied Computing 2025
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- 2024
- Full Text
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24. Terrestrial Very-Long-Baseline Atom Interferometry: Summary of the Second Workshop
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Abdalla, Adam, Abe, Mahiro, Abend, Sven, Abidi, Mouine, Aidelsburger, Monika, Alibabaei, Ashkan, Allard, Baptiste, Antoniadis, John, Arduini, Gianluigi, Augst, Nadja, Balamatsias, Philippos, Balaz, Antun, Banks, Hannah, Barcklay, Rachel L., Barone, Michele, Barsanti, Michele, Bason, Mark G., Bassi, Angelo, Bayle, Jean-Baptiste, Baynham, Charles F. A., Beaufils, Quentin, Beldjoudi, Slyan, Belic, Aleksandar, Bennetts, Shayne, Bernabeu, Jose, Bertoldi, Andrea, Bigard, Clara, Bigelow, N. P., Bingham, Robert, Blas, Diego, Bobrick, Alexey, Boehringer, Samuel, Bogojevic, Aleksandar, Bongs, Kai, Bortoletto, Daniela, Bouyer, Philippe, Brand, Christian, Buchmueller, Oliver, Buica, Gabriela, Calatroni, Sergio, Calmels, Lo, Canizares, Priscilla, Canuel, Benjamin, Caramete, Ana, Caramete, Laurentiu-Ioan, Carlesso, Matteo, Carlton, John, Carman, Samuel P., Carroll, Andrew, Casariego, Mateo, Chairetis, Minoas, Charmandaris, Vassilis, Chauhan, Upasna, Chen, Jiajun, Luisa, Maria, Chiofalo, Ciampini, Donatella, Cimbri, Alessia, Clad, Pierre, Coleman, Jonathon, Constantin, Florin Lucian, Contaldi, Carlo R., Corgier, Robin, Dash, Bineet, Davies, G. J., de Rham, Claudia, De Roeck, Albert, Derr, Daniel, Dey, Soumyodeep, Di Pumpo, Fabio, Djordjevic, Goran S., Doebrich, Babette, Dornan, Peter, Doser, Michael, Drougakis, Giannis, Dunningham, Jacob, Duspayev, Alisher, Easo, Sajan, Eby, Joshua, Efremov, Maxim, Elertas, Gedminas, Ellis, John, Entin, Nicholas, Fairhurst, Stephen, Fani, Mattia, Fassi, Farida, Fayet, Pierre, Felea, Daniel, Feng, Jie, Flack, Robert, Foot, Chris, Freegarde, Tim, Fuchs, Elina, Gaaloul, Naceur, Gao, Dongfeng, Gardner, Susan, Garraway, Barry M., Alzar, Carlos L. Garrido, Gauguet, Alexandre, Giese, Enno, Gill, Patrick, Giudice, Gian F., Glasbrenner, Eric P., Glick, Jonah, Graham, Peter W., Granados, Eduardo, Griffin, Paul F., Gue, Jordan, Guellati-Khelifa, Saida, Gupta, Subhadeep, Gupta, Vishu, Hackermueller, Lucia, Haehnelt, Martin, Hakulinen, Timo, Hammerer, Klemens, Hanimeli, Ekim T., Harte, Tiffany, Hartmann, Sabrina, Hawkins, Leonie, Hees, Aurelien, Herbst, Alexander, Hird, Thomas M., Hobson, Richard, Hogan, Jason, Holst, Bodil, Holynski, Michael, Hosten, Onur, Hsu, Chung Chuan, Huang, Wayne Cheng-Wei, Hughes, Kenneth M., Hussain, Kamran, Huetsi, Gert, Iovino, Antonio, Isfan, Maria-Catalina, Janson, Gregor, Jeglic, Peter, Jetzer, Philippe, Jiang, Yijun, Juzeliunas, Gediminas, Kaenders, Wilhelm, Kalliokoski, Matti, Kehagias, Alex, Kilian, Eva, Klempt, Carsten, Knight, Peter, Koley, Soumen, Konrad, Bernd, Kovachy, Tim, Krutzik, Markus, Kumar, Mukesh, Kumar, Pradeep, Labiad, Hamza, Lan, Shau-Yu, Landragin, Arnaud, Landsberg, Greg, Langlois, Mehdi, Lanigan, Bryony, Poncin-Lafitte, Christophe Le, Lellouch, Samuel, Leone, Bruno, Lewicki, Marek, Lien, Yu-Hung, Lombriser, Lucas, Asamar, Elias Lopez, Lopez-Gonzalez, J. Luis, Lowe, Adam, Lu, Chen, Luciano, Giuseppe Gaetano, Lundblad, Nathan, Monjaraz, Cristian de J. Lpez, Mackoit-Sinkeviien, Maena, Maggiore, Michele, Majumdar, Anirban, Makris, Konstantinos, Maleknejad, Azadeh, Marchant, Anna L., Mariotti, Agnese, Markou, Christos, Matthews, Barnaby, Mazumdar, Anupam, McCabe, Christopher, Meister, Matthias, Mentasti, Giorgio, Menu, Jonathan, Messineo, Giuseppe, Meyer-Hoppe, Bernd, Micalizio, Salvatore, Migliaccio, Federica, Millington, Peter, Milosevic, Milan, Mishra, Abhay, Mitchell, Jeremiah, Morley, Gavin W., Mouelle, Noam, Mueller, Juergen, Newbold, David, Ni, Wei-Tou, Niehof, Christian, Noller, Johannes, Odzak, Senad, Oi, Daniel K. L., Oikonomou, Andreas, Omar, Yasser, Overstreet, Chris, Pahl, Julia, Paling, Sean, Pan, Zhongyin, Pappas, George, Pareek, Vinay, Pasatembou, Elizabeth, Paternostro, Mauro, Pathak, Vishal K., Pelucchi, Emanuele, Santos, Franck Pereira dos, Peters, Achim, Pichery, Annie, Pikovski, Igor, Pilaftsis, Apostolos, Pislan, Florentina-Crenguta, Plunkett, Robert, Poggiani, Rosa, Prevedelli, Marco, Veettil, Vishnupriya Puthiya, Rafelski, Johann, Raidal, Juhan, Raidal, Martti, Rasel, Ernst Maria, Renaux-Petel, Sebastien, Richaud, Andrea, Rivero-Antunez, Pedro, Rodzinka, Tangui, Roura, Albert, Rudolph, Jan, Sabulsky, Dylan, Safronova, Marianna S., Sakellariadou, Mairi, Salvi, Leonardo, Sameed, Muhammed, Sarkar, Sumit, Schach, Patrik, Schaeffer, Stefan Alaric, Schelfhout, Jesse, Schilling, Manuel, Schkolnik, Vladimir, Schleich, Wolfgang P., Schlippert, Dennis, Schneider, Ulrich, Schreck, Florian, Schwartzman, Ariel, Schwersenz, Nico, Sergijenko, Olga, Sfar, Haifa Rejeb, Shao, Lijing, Shipsey, Ian, Shu, Jing, Singh, Yeshpal, Sopuerta, Carlos F., Sorba, Marianna, Sorrentino, Fiodor, Spallicci, Alessandro D. A. M, Stefanescu, Petruta, Stergioulas, Nikolaos, Stoerk, Daniel, Stroehle, Jannik, Sunilkumar, Hrudya Thaivalappil, Tam, Zoie, Tandon, Dhruv, Tang, Yijun, Tell, Dorothee, Tempere, Jacques, Temples, Dylan J., Thampy, Rohit P, Tietje, Ingmari C., Tino, Guglielmo M., Tinsley, Jonathan N., Mircea, Ovidiu Tintareanu, Tkalec, Kimberly, Tolley, Andrew J., Tornatore, Vincenza, Torres-Orjuela, Alejandro, Treutlein, Philipp, Trombettoni, Andrea, Ufrecht, Christian, Urrutia, Juan, Valenzuela, Tristan, Valerio, Linda R., van der Grinten, Maurits, Vaskonen, Ville, Vazquez-Aceves, Veronica, Veermae, Hardi, Vetrano, Flavio, Vitanov, Nikolay V., von Klitzing, Wolf, Wald, Sebastian, Walker, Thomas, Walser, Reinhold, Wang, Jin, Wang, Yan, Weidner, C. A., Wenzlawski, Andr, Werner, Michael, Woerner, Lisa, Yahia, Mohamed E., Yazgan, Efe, Cruzeiro, Emmanuel Zambrini, Zarei, M., Zhan, Mingsheng, Zhang, Shengnan, Zhou, Lin, and Zupanic, Erik
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High Energy Physics - Experiment ,Astrophysics - Instrumentation and Methods for Astrophysics ,General Relativity and Quantum Cosmology ,High Energy Physics - Phenomenology ,Physics - Atomic Physics - Abstract
This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/
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- 2024
25. Robustness of chaotic-light correlation imaging against turbulence
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Scala, Giovanni, Massaro, Gianlorenzo, Borreggine, Germano, Lupo, Cosmo, D'Angelo, Milena, and Pepe, Francesco V.
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Physics - Optics ,Quantum Physics - Abstract
We consider an imaging scheme, inspired by microscopy, in which both correlation imaging and first-order intensity imaging can be performed simultaneously, to investigate the effects of strong turbulence on the two different kinds of images. The comparison between direct and correlation imaging in the presence of strong turbulence unambiguously revealed an advantage of the latter. Remarkably, this advantage, quantified by analyzing the visibility of periodic sample patterns, is more striking when the presence of turbulence becomes the dominant factor in determining the image resolution., Comment: 14 pages, 3 figures
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- 2024
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26. Inflation without an Inflaton
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Bertacca, Daniele, Jimenez, Raul, Matarrese, Sabino, and Ricciardone, Angelo
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Astrophysics - Cosmology and Nongalactic Astrophysics ,High Energy Physics - Theory - Abstract
We propose a novel scenario in which scalar perturbations, that seed the large scale structure of the Universe, are generated without relying on a scalar field (the inflaton). In this framework, inflation is driven by a de Sitter space-time (dS), where tensor metric fluctuations (i.e., gravitational waves) naturally arise from quantum vacuum oscillations, and scalar fluctuations are generated via second-order tensor effects. We compute the power spectrum of such scalar fluctuations and show it to be consistent with near scale-invariance. We derive the necessary conditions under which scalar perturbations become significant and much larger than the tensor modes, and we identify a natural mechanism to end inflation via a transition to a radiation-dominated phase. Our proposed mechanism could remove the need for a model-dependent scenario: the choice of a scalar field, as the inflaton, to drive inflation.
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- 2024
27. An update on the determination of the sphaleron rate in finite temperature QCD
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Bellini, Nicolò, Bonanno, Claudio, D'Angelo, Francesco, D'Elia, Massimo, Giorgieri, Andrea, and Maio, Lorenzo
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High Energy Physics - Lattice ,High Energy Physics - Phenomenology ,High Energy Physics - Theory - Abstract
The sphaleron rate is a key phenomenological quantity both for the axion thermal production in the Early Universe and the Chiral Magnetic Effect occurring in the Quark-Gluon Plasma in presence of a background magnetic field. In this talk we present an extension of our recent determination of the sphaleron rate, in the SU(3) gauge theory, based on the determination of the two-point function of the topological charge density at finite temperature., Comment: 11 pages, 3 figures, contribution for the Proceedings of the 41st International Symposium on Lattice Field Theory (Lattice 2024), 28 July - 3 August 2024, Liverpool, UK
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- 2024
28. Stochastic Model for a Piezoelectric Energy Harvester Driven by Broadband Vibrations
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Sanfelice, Angelo, Costanzo, Luigi, Schiavo, Alessandro Lo, Sarracino, Alessandro, and Vitelli, Massimo
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Condensed Matter - Statistical Mechanics ,Physics - Instrumentation and Detectors - Abstract
We present an experimental and numerical study of a piezoelectric energy harvester driven by broadband vibrations. This device can extract power from random fluctuations and can be described by a stochastic model, based on an underdamped Langevin equation with white noise, which mimics the dynamics of the piezoelectric material. A crucial point in the modelisation is represented by the appropriate description of the coupled load circuit that is necessary to harvest electrical energy. We consider a linear load (resistance) and a nonlinear load (diode bridge rectifier connected to the parallel of a capacitance and a load resistance), and focus on the characteristic curve of the extracted power as a function of the load resistance, in order to estimate the optimal values of the parameters that maximise the collected energy. In both cases, we find good agreement between the numerical simulations of the theoretical model and the results obtained in experiments. In particular, we observe a non-monotonic behaviour of the characteristic curve which signals the presence of an optimal value for the load resistance at which the extracted power is maximised. We also address a more theoretical issue, related to the inference of the non-equilibrium features of the system from data: we show that the analysis of high-order correlation functions of the relevant variables, when in the presence of nonlinearities, can represent a simple and effective tool to check the irreversible dynamics., Comment: 11 pages, 13 figures
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- 2024
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29. PROPOE 2: Avan\c{c}os na S\'intese Computacional de Poemas Baseados em Prosa Liter\'aria Brasileira
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Sousa, Felipe José D., Cerqueira, Sarah P., Queiroz, João, and Loula, Angelo
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Computer Science - Computation and Language - Abstract
The computational generation of poems is a complex task, which involves several sound, prosodic and rhythmic resources. In this work we present PROPOE 2, with the extension of structural and rhythmic possibilities compared to the original system, generating poems from metered sentences extracted from the prose of Brazilian literature, with multiple rhythmic assembly criteria. These advances allow for a more coherent exploration of rhythms and sound effects for the poem. Results of poems generated by the system are demonstrated, with variations in parameters to exemplify generation and evaluation using various criteria. A gera\c{c}\~ao computacional de poemas \'e uma tarefa complexa, que envolve diversos recursos sonoros, pros\'odicos e r\'itmicos. Neste trabalho apresentamos PROPOE 2, com a amplia\c{c}\~ao de possibilidades estruturais e r\'itmicas em rela\c{c}\~ao ao sistema original, gerando poemas a partir de senten\c{c}as metrificadas extra\'idas da prosa da literatura brasileira, com m\'ultiplos crit\'erios r\'itmicos de montagem. Esses avan\c{c}os permitem uma explora\c{c}\~ao mais coerente de ritmos e efeitos sonoros para o poema. Resultados de poemas gerados pelo sistema s\~ao demonstrados, com varia\c{c}\~oes de par\^ametros para exemplificar a gera\c{c}\~ao e a avalia\c{c}\~ao pelos variados crit\'erios., Comment: in Portuguese language
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- 2024
30. Robust image classification with multi-modal large language models
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Villani, Francesco, Maljkovic, Igor, Lazzaro, Dario, Sotgiu, Angelo, Cinà, Antonio Emanuele, and Roli, Fabio
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Cryptography and Security ,Computer Science - Machine Learning - Abstract
Deep Neural Networks are vulnerable to adversarial examples, i.e., carefully crafted input samples that can cause models to make incorrect predictions with high confidence. To mitigate these vulnerabilities, adversarial training and detection-based defenses have been proposed to strengthen models in advance. However, most of these approaches focus on a single data modality, overlooking the relationships between visual patterns and textual descriptions of the input. In this paper, we propose a novel defense, Multi-Shield, designed to combine and complement these defenses with multi-modal information to further enhance their robustness. Multi-Shield leverages multi-modal large language models to detect adversarial examples and abstain from uncertain classifications when there is no alignment between textual and visual representations of the input. Extensive evaluations on CIFAR-10 and ImageNet datasets, using robust and non-robust image classification models, demonstrate that Multi-Shield can be easily integrated to detect and reject adversarial examples, outperforming the original defenses.
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- 2024
31. Multidimensional Territorial Attractiveness: an Application to European Flows
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Calò, Emanuele and Facchini, Angelo
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Physics - Physics and Society - Abstract
In Regional Economics, the attractiveness of regions for capital, migrants, tourists, and other kinds of flows is a relevant topic. Usually, studies in this field have mainly explored single flows, characterizing the dimensions of territorial attractiveness separately, rarely considering the interwoven effect of flows. Here we investigate attractiveness from a multi-dimensional perspective (i.e., dealing with different flows), asking how various types of regional flows collectively shape the attractiveness dynamics of European regions. We analyze eight distinct flow types across NUTS2 regions from 2010 to 2018, employing a multilayer network approach. Notably, the multilayer approach unveils insights that would be missed in single-layer analyses. Community detection reveals complex structures that demonstrate the cohesive power of national borders and the existence of strong cross-border ties in specific regions. Our study contributes to a more nuanced understanding of regional attractiveness, with implications for targeted policy interventions in regional development and European cohesion., Comment: Main: 23 pages, 10 figures, 4 tables. Supplementary: 18 pages, 10 figures, 10 tables
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- 2024
32. Point-set registration in bounded domains via the Fokker-Planck equation
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Iollo, Angelo and Taddei, Tommaso
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Mathematics - Numerical Analysis - Abstract
We present a point set registration method in bounded domains based on the solution to the Fokker Planck equation. Our approach leverages (i) density estimation based on Gaussian mixture models; (ii) a stabilized finite element discretization of the Fokker Planck equation; (iii) a specialized method for the integration of the particles. We review relevant properties of the Fokker Planck equation that provide the foundations for the numerical method. We discuss two strategies for the integration of the particles and we propose a regularization technique to control the distance of the particles from the boundary of the domain. We perform extensive numerical experiments for two two-dimensional model problems to illustrate the many features of the method.
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- 2024
33. Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Field
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Aggarwal, Tanay, Salatino, Angelo, Osborne, Francesco, and Motta, Enrico
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Computer Science - Digital Libraries ,Computer Science - Artificial Intelligence ,Computer Science - Information Retrieval - Abstract
Ontologies of research topics are crucial for structuring scientific knowledge, enabling scientists to navigate vast amounts of research, and forming the backbone of intelligent systems such as search engines and recommendation systems. However, manual creation of these ontologies is expensive, slow, and often results in outdated and overly general representations. As a solution, researchers have been investigating ways to automate or semi-automate the process of generating these ontologies. This paper offers a comprehensive analysis of the ability of large language models (LLMs) to identify semantic relationships between different research topics, which is a critical step in the development of such ontologies. To this end, we developed a gold standard based on the IEEE Thesaurus to evaluate the task of identifying four types of relationships between pairs of topics: broader, narrower, same-as, and other. Our study evaluates the performance of seventeen LLMs, which differ in scale, accessibility (open vs. proprietary), and model type (full vs. quantised), while also assessing four zero-shot reasoning strategies. Several models have achieved outstanding results, including Mixtral-8x7B, Dolphin-Mistral-7B, and Claude 3 Sonnet, with F1-scores of 0.847, 0.920, and 0.967, respectively. Furthermore, our findings demonstrate that smaller, quantised models, when optimised through prompt engineering, can deliver performance comparable to much larger proprietary models, while requiring significantly fewer computational resources., Comment: submitted to Information Processing & Management
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- 2024
34. Germanium target sensed by phonon-mediated kinetic inductance detectors
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Delicato, Daniele, Angelone, Danilo, Bandiera, Laura, Calvo, Martino, Cappelli, Matteo, Chowdhury, Usasi, Del Castello, Giorgio, Folcarelli, Matteo, Roccagiovine, Matteo del Gallo, Guidi, Vincenzo, Pesce, Giovanni Luca, Romagnoni, Marco, Cruciani, Angelo, Mazzolari, Andrea, Monfardini, Alessandro, and Vignati, Marco
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Physics - Instrumentation and Detectors - Abstract
Cryogenic phonon detectors are adopted in experiments searching for dark matter interactions or coherent elastic neutrino-nucleus scattering, thanks to the low energy threshold they can achieve. The phonon-mediated sensing of particle interactions in passive silicon absorbers has been demonstrated with Kinetic Inductance Detectors (KIDs). Targets with neutron number larger than silicon, however, feature higher cross section to neutrinos while multi-target absorbers in dark matter experiments would provide a stronger evidence of a possible signal. In this work we present the design, fabrication and operation of KIDs coupled to a germanium absorber, achieving phonon-sensing performance comparable to silicon absorbers. The device introduced in this work is a proof of concept for a scalable neutrino detector and for a multi-target dark matter experiment., Comment: 3 Figures, 2 Tables, 5 pages
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- 2024
35. Axiomatic approach to measures of total correlations
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Moraes, Gabriel L., Angelo, Renato M., and Costa, Ana C. S.
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Quantum Physics - Abstract
Correlations play a pivotal role in various fields of science, particularly in quantum mechanics, yet their proper quantification remains a subject of debate. In this work, we aim to discuss the challenge of defining a reliable measure of total correlations. We first outline essential properties that an effective correlation measure should satisfy and review existing measures, including quantum mutual information, the p-norm of the correlation matrix, and the recently defined quantum Pearson correlation coefficient. Additionally, we introduce new measures based on R\'enyi and Tsallis relative entropies, as well as the Kullback-Leibler divergence. Our analysis reveals that while quantum mutual information, the p-norm, and the Pearson measure exhibit equivalence for two-qubit systems, they all suffer from an ordering problem. Despite criticisms regarding its reliability, we argue that quantum mutual information remains a valid measure of total correlations., Comment: 8 pages, 1 figure, 1 table
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- 2024
36. A Flexible Template for Edge Generative AI with High-Accuracy Accelerated Softmax & GELU
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Belano, Andrea, Tortorella, Yvan, Garofalo, Angelo, Benini, Luca, Rossi, Davide, and Conti, Francesco
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Computer Science - Hardware Architecture - Abstract
Transformer-based generative Artificial Intelligence (GenAI) models achieve remarkable results in a wide range of fields, including natural language processing, computer vision, and audio processing. However, this comes at the cost of increased complexity and the need of sophisticated non-linearities such as softmax and GELU. Even if Transformers are computationally dominated by matrix multiplications (MatMul), these non-linearities can become a performance bottleneck, especially if dedicated hardware is used to accelerate MatMul operators. In this work, we introduce a GenAI BFloat16 Transformer acceleration template based on a heterogeneous tightly-coupled cluster containing 256KiB of shared SRAM, 8 general-purpose RISC-V cores, a 24x8 systolic array MatMul accelerator, and a novel accelerator for Transformer softmax and GELU non-linearities: SoftEx. SoftEx introduces an approximate exponentiation algorithm balancing efficiency (121x speedup over glibc's implementation) with accuracy (mean relative error of 0.14%). In 12nm technology, SoftEx occupies 0.039 mm$^2$, only 3.22% of the cluster, which achieves an operating frequency of 1.12 GHz. Compared to optimized software running on the RISC-V cores, SoftEx achieves significant improvements, accelerating softmax and GELU computations by up to 10.8x and 5.11x, respectively, while reducing their energy consumption by up to 10.8x and 5.29x. These enhancements translate into a 1.58x increase in throughput (310 GOPS at 0.8V) and a 1.42x improvement in energy efficiency (1.34 TOPS/W at 0.55V) on end-to-end ViT inference workloads.
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- 2024
37. ASb3Mn9O19 (A = K or Rb): New Mn-Based Two-Dimensional Magnetoplumbites with Geometric and Magnetic Frustration
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Chen, Jianyi, Calder, Stuart, Paddison, Joseph A. M., Angelo, Gina, Klivansky, Liana, Zhang, Jian, Cao, Huibo, and Gui, Xin
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Condensed Matter - Materials Science ,Condensed Matter - Strongly Correlated Electrons - Abstract
Magnetoplumbites are one of the most broadly studied families of hexagonal ferrites, typically with high magnetic ordering temperatures, making them excellent candidates for permanent magnets. However, magnetic frustration was rarely observed in magnetoplumbites. Herein, we report the discovery, synthesis and characterization of the first Mn-based magnetoplumbite, as well as the first magnetoplumbite involving pnictogens (Sb), ASb3Mn9O19 (A = K or Rb). The Mn3+ (S = 2) cations, further confirmed by DC magnetic susceptibility and X-ray photoelectron spectroscopy, construct three geometrically frustrated sublattices, including Kagome, triangular and puckered honeycomb lattices. Magnetic properties measurements revealed strong antiferromagnetic spin-spin coupling as well as multiple low-temperature magnetic features. Heat capacity data did not show any prominent lambda-anomaly, suggesting minimal associated magnetic entropy. Moreover, neutron powder diffraction implied the absence of long-range magnetic ordering in KSb3Mn9O19 down to 3 K. However, several magnetic peaks were observed in RbSb3Mn9O19 at 3 K, corresponding to an incommensurate magnetic structure. Interestingly, strong diffuse scattering was seen in the neutron powder diffraction patterns of both compounds at low angles, and was analyzed by reverse Monte Carlo refinements, indicating short-range spin ordering related to frustrated magnetism as well as two-dimensional magnetic correlations in ASb3Mn9O19 (A = K or Rb)., Comment: 39 pages, 14 figures, 8 tables
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- 2024
38. The Growth of Galaxy Stellar Haloes Over $0.2 \leq z \leq 1.1$
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Williams, Devin J., Damjanov, Ivana, Sawicki, Marcin, Souchereau, Harrison, Chen, Lingjian, Desprez, Guillaume, George, Angelo, Annunziatella, Marianna, and Gwyn, Stephen
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Astrophysics - Astrophysics of Galaxies - Abstract
Galaxies are predicted to assemble their stellar haloes through the accretion of stellar material from interactions with their cosmic environment. Observations that trace stellar halo buildup probe the processes that drive galaxy size and stellar mass growth. We investigate stellar halo assembly over $0.2 \leq z \leq 1.1$ in a mass-complete ($M_{\star} \geq 10^{9.5}M_{\odot}$) sample of 242,456 star-forming and 88,421 quiescent galaxies (SFGs and QGs) from the CLAUDS and HSC-SSP surveys. We extract galaxy rest-frame $g$-band surface brightness ($\mu_g$) profiles to study faint, extended emission in galaxy outskirts. We examine trends in galaxy assembly by analyzing the median $\mu_g$ profiles in different SFG and QG \msS ranges with decreasing redshift and connecting evolution in galaxy $\mu_g$ profiles with the underlying stellar mass growth in galaxies. Since $z=1.1$, the majority of evolution in the median $\mu_g$ profiles of galaxies ($\sim$64$\%$ in SFGs and $\sim$71$\%$ in QGs) occurs throughout their stellar halo regions (2-10$R_e$). More massive galaxies assemble stellar halo material more rapidly at $0.2 \leq z \leq 1.1$. Over this period, QGs grow a larger fraction of their stellar haloes than SFGs at fixed $M_{\star}$ (factor of $\sim$1.2). Although star formation can account for the stellar halo growth observed in low-mass SFGs ($10^{9.5}M_\odot \leq M_\star < 10^{10.5}M_\odot$), high-mass SFGs ($M_\star \geq 10^{10.5}M_\odot$) and both low- and high-mass QGs require an additional assembly mechanism. Our results suggest accretion via minor mergers drives additional stellar halo growth in these galaxies. The contribution from accretion is larger in more massive galaxies (over $M_{\star} \geq 10^{9.5}M_{\odot}$), and QGs exhibit larger fractional increases to their ex-situ fractions over $0.2 \leq z \leq 1.1$ than SFGs at fixed $M_{\star}$., Comment: 29 pages, 15 figures, 2 tables. Submitted for publication in ApJ
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- 2024
39. Deep Learning for Sea Surface Temperature Reconstruction under Cloud Occlusion
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Asperti, Andrea, Aydogdu, Ali, Clementi, Emanuela, Greco, Angelo, Mentaschi, Lorenzo, Merizzi, Fabio, Miraglio, Pietro, Oddo, Paolo, Pinardi, Nadia, and Testa, Alessandro
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Computer Science - Computer Vision and Pattern Recognition ,I.4.5 - Abstract
Sea Surface Temperature (SST) is crucial for understanding Earth's oceans and climate, significantly influencing weather patterns, ocean currents, marine ecosystem health, and the global energy balance. Large-scale SST monitoring relies on satellite infrared radiation detection, but cloud cover presents a major challenge, creating extensive observational gaps and hampering our ability to fully capture large-scale ocean temperature patterns. Efforts to address these gaps in existing L4 datasets have been made, but they often exhibit notable local and seasonal biases, compromising data reliability and accuracy. To tackle this challenge, we employed deep neural networks to reconstruct cloud-covered portions of satellite imagery while preserving the integrity of observed values in cloud-free areas, using MODIS satellite derived observations of SST. Our best-performing architecture showed significant skill improvements over established methodologies, achieving substantial reductions in error metrics when benchmarked against widely used approaches and datasets. These results underscore the potential of advanced AI techniques to enhance the completeness of satellite observations in Earth-science remote sensing, providing more accurate and reliable datasets for environmental assessments, data-driven model training, climate research, and seamless integration into model data assimilation workflows.
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- 2024
40. Contextual Data Integration for Bike-sharing Demand Prediction with Graph Neural Networks in Degraded Weather Conditions
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Rochas, Romain, Furno, Angelo, and Faouzi, Nour-Eddin El
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Computer Science - Artificial Intelligence - Abstract
Demand for bike sharing is impacted by various factors, such as weather conditions, events, and the availability of other transportation modes. This impact remains elusive due to the complex interdependence of these factors or locationrelated user behavior variations. It is also not clear which factor is additional information which are not already contained in the historical demand. Intermodal dependencies between bike-sharing and other modes are also underexplored, and the value of this information has not been studied in degraded situations. The proposed study analyzes the impact of adding contextual data, such as weather, time embedding, and road traffic flow, to predict bike-sharing Origin-Destination (OD) flows in atypical weather situations Our study highlights a mild relationship between prediction quality of bike-sharing demand and road traffic flow, while the introduced time embedding allows outperforming state-of-the-art results, particularly in the case of degraded weather conditions. Including weather data as an additional input further improves our model with respect to the basic ST-ED-RMGC prediction model by reducing of more than 20% the prediction error in degraded weather condition.
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- 2024
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- View/download PDF
41. The ATTUNE model for Artificial Trust Towards Human Operators
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Petousakis, Giannis, Cangelosi, Angelo, Stolkin, Rustam, and Chiou, Manolis
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Computer Science - Robotics - Abstract
This paper presents a novel method to quantify Trust in HRI. It proposes an HRI framework for estimating the Robot Trust towards the Human in the context of a narrow and specified task. The framework produces a real-time estimation of an AI agent's Artificial Trust towards a Human partner interacting with a mobile teleoperation robot. The approach for the framework is based on principles drawn from Theory of Mind, including information about the human state, action, and intent. The framework creates the ATTUNE model for Artificial Trust Towards Human Operators. The model uses metrics on the operator's state of attention, navigational intent, actions, and performance to quantify the Trust towards them. The model is tested on a pre-existing dataset that includes recordings (ROSbags) of a human trial in a simulated disaster response scenario. The performance of ATTUNE is evaluated through a qualitative and quantitative analysis. The results of the analyses provide insight into the next stages of the research and help refine the proposed approach., Comment: Published in IEEE SMC 2024
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- 2024
42. Diode effect in Fraunhofer patterns of disordered multi-terminal Josephson junctions
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Chirolli, Luca, Greco, Angelo, Crippa, Alessandro, Strambini, Elia, Cuoco, Mario, Amico, Luigi, and Giazotto, Francesco
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Condensed Matter - Superconductivity ,Condensed Matter - Mesoscale and Nanoscale Physics ,Quantum Physics - Abstract
We study the role of different spatial inhomogeneities in generating the conditions for the appearance of a superconducting diode effect in the Fraunhofer pattern of wide Josephson junctions. Through the scattering matrix approach, we highlight the role of mirror symmetry of the junction in forbidding the diode effect in both the two-terminal and the multi-terminal case. As sources of mirror symmetry breaking, we study spatial potentials of long and short wavelength with respect to the size of the system, mimicking the effect of side gates and atomic scale disorder, respectively, as well as the geometry of the junction, and assess their impact on the diode effect. As a common trend, we observe qualitatively similar rectification patterns magnified at the nodal points of the Fraunhofer pattern by destructing interference. In multi-terminal mirror-symmetric setups, we single out the phase at additional terminals as a controllable knob to tune the diode effect at the finite field. The work presents a comprehensive treatment of the role of pure spatial inhomogeneity in the emergence of a diode effect in wide junctions., Comment: 11 pages, 6 figures
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- 2024
43. IXPE Observation of the Low-Synchrotron Peaked Blazar S4 0954+65 During An Optical-X-ray Flare
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Kouch, Pouya M., Liodakis, Ioannis, Fenu, Francesco, Zhang, Haocheng, Boula, Stella, Middei, Riccardo, Di Gesu, Laura, Paraschos, Georgios F., Agudo, Iván, Jorstad, Svetlana G., Lindfors, Elina, Marscher, Alan P., Krawczynski, Henric, Negro, Michela, Hu, Kun, Kim, Dawoon E., Cavazzuti, Elisabetta, Errando, Manel, Blinov, Dmitry, Gourni, Anastasia, Kiehlmann, Sebastian, Kourtidis, Angelos, Mandarakas, Nikos, Triantafyllou, Nikolaos, Vervelaki, Anna, Borman, George A., Kopatskaya, Evgenia N., Larionova, Elena G., Morozova, Daria A., Savchenko, Sergey S., Vasilyev, Andrey A., Troitskiy, Ivan S., Grishina, Tatiana S., Zhovtan, Alexey V., Aceituno, Francisco José, Bonnoli, Giacomo, Casanova, Víctor, Escudero, Juan, Agís-González, Beatriz, Husillos, César, Otero-Santos, Jorge, Piirola, Vilppu, Sota, Alfredo, Myserlis, Ioannis, Gurwell, Mark, Keating, Garrett K., Rao, Ramprasad, Angelakis, Emmanouil, Kraus, Alexander, Antonelli, Lucio Angelo, Bachetti, Matteo, Baldini, Luca, Baumgartner, Wayne H., Bellazzini, Ronaldo, Bianchi, Stefano, Bongiorno, Stephen D., Bonino, Raffaella, Brez, Alessandro, Bucciantini, Niccolò, Capitanio, Fiamma, Castellano, Simone, Chen, Chien-Ting, Ciprini, Stefano, Costa, Enrico, De Rosa, Alessandra, Del Monte, Ettore, Di Lalla, Niccolò, Di Marco, Alessandro, Donnarumma, Immacolata, Doroshenko, Victor, Dovčiak, Michal, Ehlert, Steven R., Enoto, Teruaki, Evangelista, Yuri, Fabiani, Sergio, Ferrazzoli, Riccardo, Garcia, Javier A., Gunji, Shuichi, Hayashida, Kiyoshi, Heyl, Jeremy, Iwakiri, Wataru, Kaaret, Philip, Karas, Vladimir, Kislat, Fabian, Kitaguchi, Takao, Kolodziejczak, Jeffery J., La Monaca, Fabio, Latronico, Luca, Maldera, Simone, Manfreda, Alberto, Marin, Frédéric, Marinucci, Andrea, Marshall, Herman L., Massaro, Francesco, Matt, Giorgio, Mitsuishi, Ikuyuki, Mizuno, Tsunefumi, Muleri, Fabio, Ng, Chi-Yung, O'Dell, Stephen L., Omodei, Nicola, Oppedisano, Chiara, Papitto, Alessandro, Pavlov, George G., Peirson, Abel Lawrence, Perri, Matteo, Pesce-Rollins, Melissa, Petrucci, Pierre-Olivier, Pilia, Maura, Possenti, Andrea, Poutanen, Juri, Puccetti, Simonetta, Ramsey, Brian D., Rankin, John, Ratheesh, Ajay, Roberts, Oliver J., Sgrò, Carmelo, Slane, Patrick, Soffitta, Paolo, Spandre, Gloria, Swartz, Douglas A., Tamagawa, Toru, Tavecchio, Fabrizio, Taverna, Roberto, Tawara, Yuzuru, Tennant, Allyn F., Thomas, Nicholas E., Tombesi, Francesco, Trois, Alessio, Tsygankov, Sergey S., Turolla, Roberto, Romani, Roger W., Vink, Jacco, Weisskopf, Martin C., Wu, Kinwah, Xie, Fei, and Zane, Silvia
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Astrophysics - High Energy Astrophysical Phenomena - Abstract
The X-ray polarization observations made possible with the Imaging X-ray Polarimetry Explorer (IXPE) offer new ways of probing high-energy emission processes in astrophysical jets from blazars. Here we report on the first X-ray polarization observation of the blazar S4 0954+65 in a high optical and X-ray state. During our multi-wavelength campaign on the source, we detected an optical flare whose peak coincided with the peak of an X-ray flare. This optical-X-ray flare most likely took place in a feature moving along the parsec-scale jet, imaged at 43 GHz by the Very Long Baseline Array. The 43 GHz polarization angle of the moving component underwent a rotation near the time of the flare. In the optical band, prior to the IXPE observation, we measured the polarization angle to be aligned with the jet axis. In contrast, during the optical flare the optical polarization angle was perpendicular to the jet axis; after the flare, it reverted to being parallel to the jet axis. Due to the smooth behavior of the optical polarization angle during the flare, we favor shocks as the main acceleration mechanism. We also infer that the ambient magnetic field lines in the jet were parallel to the jet position angle. The average degree of optical polarization during the IXPE observation was (14.3$\pm$4.1)%. Despite the flare, we only detected an upper limit of 14% (at 3$\sigma$ level) on the X-ray polarization degree; although a reasonable assumption on the X-ray polarization angle results in an upper limit of 8.8% ($3\sigma$). We model the spectral energy distribution (SED) and spectral polarization distribution (SPD) of S4 0954+65 with leptonic (synchrotron self-Compton) and hadronic (proton and pair synchrotron) models. The constraints we obtain with our combined multi-wavelength polarization observations and SED modeling tentatively disfavor hadronic models for the X-ray emission in S4 0954+65., Comment: Submitted to A&A, 16 pages, 5 figures, and 7 tables
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- 2024
44. Use-Inspired Mobile Robot to Improve Safety of Building Retrofit Workforce in Constrained Spaces
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Suresh, Smruti, Carvajal, Michael Angelo, Hanson, Nathaniel, Holand, Ethan, Hibbard, Samuel, and Padir, Taskin
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Computer Science - Robotics - Abstract
The inspection of confined critical infrastructure such as attics or crawlspaces is challenging for human operators due to insufficient task space, limited visibility, and the presence of hazardous materials. This paper introduces a prototype of PARIS (Precision Application Robot for Inaccessible Spaces): a use-inspired teleoperated mobile robot manipulator system that was conceived, developed, and tested for and selected as a Phase I winner of the U.S. Department of Energy's E-ROBOT Prize. To improve the thermal efficiency of buildings, the PARIS platform supports: 1) teleoperated mapping and navigation, enabling the human operator to explore compact spaces; 2) inspection and sensing, facilitating the identification and localization of under-insulated areas; and 3) air-sealing targeted gaps and cracks through which thermal energy is lost. The resulting versatile platform can also be tailored for targeted application of treatments and remediation in constrained spaces., Comment: 6 Pages, 7 Figures. Accepted for publication in the Proceedings of 2024 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)
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- 2024
45. Triple Evolution Pathways to Black Hole Low-Mass X-ray Binaries: Insights from V404 Cygni
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Shariat, Cheyanne, Naoz, Smadar, El-Badry, Kareem, Rocha, Kyle Akira, Kalogera, Vicky, Stephan, Alexander P., Burdge, Kevin B., and Angelo, Isabel
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Astrophysics - Solar and Stellar Astrophysics ,Astrophysics - High Energy Astrophysical Phenomena - Abstract
A recent discovery shows that V404 Cygni, a prototypical black hole low-mass X-ray binary (BH-LMXB) is a hierarchical triple: the BH and donor star are orbited by a $1.2$ M$_{\odot}$ tertiary at a distance of at least $3500$ au. Motivated by this system, we evolve a grid of $\sim50,000$ triple star systems, spanning a broad range of initial orbits. Our calculations employ {\tt MESA} stellar evolution models, using {\tt POSYDON}, and self-consistently track the effects of eccentric Kozai-Lidov (EKL) oscillations, mass loss, tides, and BH natal kicks. In our simulations, the progenitors of V404 Cygni-like systems have initial outer separations of $1000 - 10000$ au and inner separations of $\sim100$ au, such that they avoid Roche lobe overflow most of the time. Later on, EKL oscillations drive the inner binary to high eccentricities until tides shrink the orbit and mass transfer begins. Notably, such systems only form in simulations with very weak black hole natal kicks ($\lesssim 5\,{\rm km\,s^{-1}}$) because stronger kicks unbind the tertiaries. Our simulations also predict a population of BH-LMXB triples that form via the classical common-envelope channel, when the BH progenitor does overflow its Roche lobe. The formation rate for this channel is also higher in triples than in isolated binaries because early EKL oscillations cause inner binaries with a wider range of initial separations to enter and survive a common envelope. Our calculations demonstrate that at least some stellar BHs form with extremely weak kicks, and that triple evolution is a significant formation channel for BH-LMXBs., Comment: Submitted to ApJ, comments are welcome
- Published
- 2024
46. Open Challenges in the Formal Verification of Autonomous Driving
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Burgio, Paolo, Ferrando, Angelo, and Villani, Marco
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Computer Science - Software Engineering ,Computer Science - Artificial Intelligence ,Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Robotics - Abstract
In the realm of autonomous driving, the development and integration of highly complex and heterogeneous systems are standard practice. Modern vehicles are not monolithic systems; instead, they are composed of diverse hardware components, each running its own software systems. An autonomous vehicle comprises numerous independent components, often developed by different and potentially competing companies. This diversity poses significant challenges for the certification process, as it necessitates certifying components that may not disclose their internal behaviour (black-boxes). In this paper, we present a real-world case study of an autonomous driving system, identify key open challenges associated with its development and integration, and explore how formal verification techniques can address these challenges to ensure system reliability and safety., Comment: In Proceedings FMAS2024, arXiv:2411.13215
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- 2024
- Full Text
- View/download PDF
47. RV4Chatbot: Are Chatbots Allowed to Dream of Electric Sheep?
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Gatti, Andrea, Mascardi, Viviana, and Ferrando, Angelo
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Computer Science - Artificial Intelligence ,Computer Science - Human-Computer Interaction ,Computer Science - Software Engineering - Abstract
Chatbots have become integral to various application domains, including those with safety-critical considerations. As a result, there is a pressing need for methods that ensure chatbots consistently adhere to expected, safe behaviours. In this paper, we introduce RV4Chatbot, a Runtime Verification framework designed to monitor deviations in chatbot behaviour. We formalise expected behaviours as interaction protocols between the user and the chatbot. We present the RV4Chatbot design and describe two implementations that instantiate it: RV4Rasa, for monitoring chatbots created with the Rasa framework, and RV4Dialogflow, for monitoring Dialogflow chatbots. Additionally, we detail experiments conducted in a factory automation scenario using both RV4Rasa and RV4Dialogflow., Comment: In Proceedings FMAS2024, arXiv:2411.13215
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- 2024
- Full Text
- View/download PDF
48. ROSMonitoring 2.0: Extending ROS Runtime Verification to Services and Ordered Topics
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Saadat, Maryam Ghaffari, Ferrando, Angelo, Dennis, Louise A., and Fisher, Michael
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Computer Science - Software Engineering ,Computer Science - Artificial Intelligence ,Computer Science - Robotics - Abstract
Formal verification of robotic applications presents challenges due to their hybrid nature and distributed architecture. This paper introduces ROSMonitoring 2.0, an extension of ROSMonitoring designed to facilitate the monitoring of both topics and services while considering the order in which messages are published and received. The framework has been enhanced to support these novel features for ROS1 -- and partially ROS2 environments -- offering improved real-time support, security, scalability, and interoperability. We discuss the modifications made to accommodate these advancements and present results obtained from a case study involving the runtime monitoring of specific components of a fire-fighting Uncrewed Aerial Vehicle (UAV)., Comment: In Proceedings FMAS2024, arXiv:2411.13215
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- 2024
- Full Text
- View/download PDF
49. Entanglement growth in the dark intervals of a locally monitored free-fermion chain
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Di Fresco, Giovanni, Gal, Youenn Le, Valenti, Davide, Schirò, Marco, and Carollo, Angelo
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Quantum Physics ,Condensed Matter - Disordered Systems and Neural Networks ,Condensed Matter - Statistical Mechanics - Abstract
We consider a free fermionic chain with monitoring of the particle density on a single site of the chain and study the entanglement dynamics of quantum jump trajectories. We show that the entanglement entropy grows in time towards a stationary state which display volume law scaling of the entropy, in stark contrast with both the unitary dynamics after a local quench and the no-click limit corresponding to full post-selection. We explain the extensive entanglement growth as a consequence of the peculiar distribution of quantum jumps in time, which display superpoissonian waiting time distribution characterised by a bunching of quantum jumps followed by long dark intervals where no-clicks are detected, akin to the distribution of fluorescence light in a driven atom. We show that the presence of dark intervals is the key feature to explain the effect and that by increasing the number of sites which are monitored the volume law scaling gives away to the Zeno effect and its associated area law., Comment: 11 pages, 8 figures
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- 2024
50. Non-Abelian entanglement asymmetry in random states
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Russotto, Angelo, Ares, Filiberto, and Calabrese, Pasquale
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High Energy Physics - Theory ,Condensed Matter - Statistical Mechanics ,Quantum Physics - Abstract
The entanglement asymmetry measures the extent to which a symmetry is broken within a subsystem of an extended quantum system. Here, we analyse this quantity in Haar random states for arbitrary compact, semi-simple Lie groups, building on and generalising recent results obtained for the $U(1)$ symmetric case. We find that, for any symmetry group, the average entanglement asymmetry vanishes in the thermodynamic limit when the subsystem is smaller than its complement. When the subsystem and its complement are of equal size, the entanglement asymmetry jumps to a finite value, indicating a sudden transition of the subsystem from a fully symmetric state to one devoid of any symmetry. For larger subsystem sizes, the entanglement asymmetry displays a logarithmic scaling with a coefficient fixed by the dimension of the group. We also investigate the fluctuations of the entanglement asymmetry, which tend to zero in the thermodynamic limit. We check our findings against exact numerical calculations for the $SU(2)$ and $SU(3)$ groups. We further discuss their implications for the thermalisation of isolated quantum systems and black hole evaporation., Comment: 28 pages, 6 figures. References added
- Published
- 2024
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