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1. Plant community richness and foliar fungicides impact soil Streptomyces inhibition, resistance, and resource use phenotypes

Author: Matthew Michalska-Smith, Daniel C. Schlatter, Nuttapon Pombubpa, Sarah C. Castle, A. Stuart Grandy, Elizabeth T. Borer, Eric W. Seabloom, and Linda L. Kinkel
Subjects: soil nutrients, microbe-microbe interactions, phenotypes, co-evolution, phylogeny, plant diversity, Microbiology, QR1-502
Abstract: Plants serve as critical links between above- and below-ground microbial communitites, both influencing and being influenced by microbes in these two realms. Below-ground microbial communities are expected to respond to soil resource environments, which are mediated by the roots of plants that can, in turn, be influenced by the above-ground community of foliar endophytes. For instance, diverse plant communities deposit more, and more diverse, nutrients into the soil, and this deposition is often increased when foliar pathogens are removed. Differences in soil resources can alter soil microbial composition and phenotypes, including inhibitory capacity, resource use, and antibiotic resistance. In this work, we consider plots differing in plant richness and application of foliar fungicide, evaluating consequences on soil resource levels and root-associated Streptomyces phenotypes. Soil carbon, nitrogen, phosphorus, potassium, and organic matter were greater in samples from polyculture than monoculture, yet this increase was surprisingly offset when foliar fungal communities were disrupted. We find that Streptomyces phenotypes varied more between richness plots—with the Streptomyces from polyculture showing lower inhibitory capacity, altered resource-use profiles, and greater antibiotic resistance—than between subplots with/without foliar fungicide. Where foliar fungicide affected phenotypes, it did so differently in polyculture than in monoculture, for instance decreasing niche width and overlap in monoculture while increasing them in polyculture. No differences in phenotype were correlated with soil nutrient levels, suggesting the need for further research looking more closely at soil resource diversity and particular compounds that were found to differ between treatments.
Published: 2024
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2. Simulating Global Terrestrial Carbon and Nitrogen Biogeochemical Cycles With Implicit and Explicit Representations of Soil Microbial Activity

Author: William R. Wieder, Melannie D. Hartman, Emily Kyker‐Snowman, Brooke Eastman, Katerina Georgiou, Derek Pierson, Katherine S. Rocci, and A. Stuart Grandy
Subjects: soil biogeochemistry, carbon cycle, land models, global change, microbial models, soil organic matter, Physical geography, GB3-5030, Oceanography, GC1-1581
Abstract: Abstract Nutrient limitation is widespread in terrestrial ecosystems. Accordingly, representations of nitrogen (N) limitation in land models typically dampen rates of terrestrial carbon (C) accrual, compared with C‐only simulations. These previous findings, however, rely on soil biogeochemical models that implicitly represent microbial activity and physiology. Here we present results from a biogeochemical model testbed that allows us to investigate how an explicit versus implicit representation of soil microbial activity, as represented in the MIcrobial‐MIneral Carbon Stabilization (MIMICS) and Carnegie‐Ames‐Stanford Approach (CASA) soil biogeochemical models, respectively, influence plant productivity, and terrestrial C and N fluxes at initialization and over the historical period. When forced with common boundary conditions, larger soil C pools simulated by the MIMICS model reflect longer inferred soil organic matter (SOM) turnover times than those simulated by CASA. At steady state, terrestrial ecosystems experience greater N limitation when using the MIMICS‐CN model, which also increases the inferred SOM turnover time. Over the historical period, however, warming‐induced acceleration of SOM decomposition over high latitude ecosystems increases rates of N mineralization in MIMICS‐CN. This reduces N limitation and results in faster rates of vegetation C accrual. Moreover, as SOM stoichiometry is an emergent property of MIMICS‐CN, we highlight opportunities to deepen understanding of sources of persistent SOM and explore its potential sensitivity to environmental change. Our findings underscore the need to improve understanding and representation of plant and microbial resource allocation and competition in land models that represent coupled biogeochemical cycles under global change scenarios.
Published: 2024
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3. Performance of a Modular Ton-Scale Pixel-Readout Liquid Argon Time Projection Chamber

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, C. Adriano, A. Aduszkiewicz, J. Aguilar, B. Aimard, F. Akbar, K. Allison, S. Alonso Monsalve, M. Alrashed, A. Alton, R. Alvarez, T. Alves, H. Amar, P. Amedo, J. Anderson, D. A. Andrade, C. Andreopoulos, M. Andreotti, M. P. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, A. Aranda-Fernandez, L. Arellano, E. Arrieta Diaz, M. A. Arroyave, J. Asaadi, A. Ashkenazi, D. Asner, L. Asquith, E. Atkin, D. Auguste, A. Aurisano, V. Aushev, D. Autiero, F. Azfar, A. Back, H. Back, J. J. Back, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, W. Baldini, J. Baldonedo, B. Baller, B. Bambah, R. Banerjee, F. Barao, G. Barenboim, P. B̃arham Alzás, G. J. Barker, W. Barkhouse, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, D. Barrow, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, L. Bathe-Peters, J. B. R. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. L. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, E. Belchior, G. Bell, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, D. Benjamin, F. Bento Neves, J. Berger, S. Berkman, J. Bernal, P. Bernardini, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, A. T. Bezerra, T. J. Bezerra, A. Bhat, V. Bhatnagar, J. Bhatt, M. Bhattacharjee, M. Bhattacharya, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. D. Blaszczyk, G. C. Blazey, E. Blucher, J. Bogenschuetz, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, R. Borges Merlo, A. Borkum, N. Bostan, J. Bracinik, D. Braga, B. Brahma, D. Brailsford, F. Bramati, A. Branca, A. Brandt, J. Bremer, C. Brew, S. J. Brice, V. Brio, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, J. Buergi, D. Burgardt, S. Butchart, G. Caceres V., I. Cagnoli, T. Cai, R. Calabrese, J. Calcutt, M. Calin, L. Calivers, E. Calvo, A. Caminata, A. F. Camino, W. Campanelli, A. Campani, A. Campos Benitez, N. Canci, J. Capó, I. Caracas, D. Caratelli, D. Carber, J. M. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, N. Carrara, L. Carroll, T. Carroll, A. Carter, E. Casarejos, D. Casazza, J. F. Castaño Forero, F. A. Castaño, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, F. Cavanna, S. Centro, G. Cerati, C. Cerna, A. Cervelli, A. Cervera Villanueva, K. Chakraborty, S. Chakraborty, M. Chalifour, A. Chappell, N. Charitonidis, A. Chatterjee, H. Chen, M. Chen, W. C. Chen, Y. Chen, Z. Chen-Wishart, D. Cherdack, C. Chi, R. Chirco, N. Chitirasreemadam, K. Cho, S. Choate, D. Chokheli, P. S. Chong, B. Chowdhury, D. Christian, A. Chukanov, M. Chung, E. Church, M. F. Cicala, M. Cicerchia, V. Cicero, R. Ciolini, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. A. B. Coelho, A. Cohen, J. Collazo, J. Collot, E. Conley, J. M. Conrad, M. Convery, S. Copello, P. Cova, C. Cox, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, G. Crone, R. Cross, A. Cudd, C. Cuesta, Y. Cui, F. Curciarello, D. Cussans, J. Dai, O. Dalager, R. Dallavalle, W. Dallaway, H. da Motta, Z. A. Dar, R. Darby, L. Da Silva Peres, Q. David, G. S. Davies, S. Davini, J. Dawson, R. De Aguiar, P. De Almeida, P. Debbins, I. De Bonis, M. P. Decowski, A. de Gouvêa, P. C. De Holanda, I. L. De Icaza Astiz, P. De Jong, P. Del Amo Sanchez, A. De la Torre, G. De Lauretis, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, G. Delle Monache, N. Delmonte, P. De Lurgio, R. Demario, G. De Matteis, J. R. T. de Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, P. Denton, G. W. Deptuch, A. De Roeck, V. De Romeri, J. P. Detje, J. Devine, R. Dharmapalan, M. Dias, A. Diaz, J. S. Díaz, F. Díaz, F. Di Capua, A. Di Domenico, S. Di Domizio, S. Di Falco, L. Di Giulio, P. Ding, L. Di Noto, E. Diociaiuti, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. J. Dolinski, D. Domenici, L. Domine, S. Donati, Y. Donon, S. Doran, D. Douglas, T. A. Doyle, A. Dragone, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, K. Dugas, P. Dunne, B. Dutta, H. Duyang, D. A. Dwyer, A. S. Dyshkant, S. Dytman, M. Eads, A. Earle, S. Edayath, D. Edmunds, J. Eisch, P. Englezos, A. Ereditato, T. Erjavec, C. O. Escobar, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, L. Fajt, A. Falcone, M. Fani’, C. Farnese, S. Farrell, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, G. Ferry, L. Fields, P. Filip, A. Filkins, F. Filthaut, R. Fine, G. Fiorillo, M. Fiorini, S. Fogarty, W. Foreman, J. Fowler, J. Franc, K. Francis, D. Franco, J. Franklin, J. Freeman, J. Fried, A. Friedland, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, R. Gaba, A. Gabrielli, A. M. Gago, F. Galizzi, H. Gallagher, A. Gallas, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, S. Ganguly, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, F. Gardim, S. Gardiner, D. Gastler, A. Gauch, J. Gauvreau, P. Gauzzi, S. Gazzana, G. Ge, N. Geffroy, B. Gelli, S. Gent, L. Gerlach, Z. Ghorbani-Moghaddam, T. Giammaria, D. Gibin, I. Gil-Botella, S. Gilligan, A. Gioiosa, S. Giovannella, C. Girerd, A. K. Giri, C. Giugliano, V. Giusti, D. Gnani, O. Gogota, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. V. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, D. Gonzalez-Diaz, M. Gonzalez-Lopez, M. C. Goodman, S. Goswami, C. Gotti, J. Goudeau, E. Goudzovski, C. Grace, E. Gramellini, R. Gran, E. Granados, P. Granger, C. Grant, D. R. Gratieri, G. Grauso, P. Green, S. Greenberg, J. Greer, W. C. Griffith, F. T. Groetschla, K. Grzelak, L. Gu, W. Gu, V. Guarino, M. Guarise, R. Guenette, E. Guerard, M. Guerzoni, D. Guffanti, A. Guglielmi, B. Guo, Y. Guo, A. Gupta, V. Gupta, G. Gurung, D. Gutierrez, P. Guzowski, M. M. Guzzo, S. Gwon, A. Habig, H. Hadavand, L. Haegel, R. Haenni, L. Hagaman, A. Hahn, J. Haiston, J. Hakenmueller, T. Hamernik, P. Hamilton, J. Hancock, F. Happacher, D. A. Harris, J. Hartnell, T. Hartnett, J. Harton, T. Hasegawa, C. Hasnip, R. Hatcher, K. Hayrapetyan, J. Hays, E. Hazen, M. He, A. Heavey, K. M. Heeger, J. Heise, S. Henry, M. A. Hernandez Morquecho, K. Herner, V. Hewes, A. Higuera, C. Hilgenberg, S. J. Hillier, A. Himmel, E. Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, T. Holvey, E. Hoppe, S. Horiuchi, G. A. Horton-Smith, M. Hostert, T. Houdy, B. Howard, R. Howell, I. Hristova, M. S. Hronek, J. Huang, R. G. Huang, Z. Hulcher, M. Ibrahim, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, M. Ismerio Oliveira, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, D. Jena, I. Jentz, X. Ji, C. Jiang, J. Jiang, L. Jiang, A. Jipa, F. R. Joaquim, W. Johnson, C. Jollet, B. Jones, R. Jones, D. José Fernández, N. Jovancevic, M. Judah, C. K. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. C. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, M. Kandemir, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, I. Katsioulas, A. Kauther, N. Kazaryan, L. Ke, E. Kearns, P. T. Keener, K. J. Kelly, E. Kemp, O. Kemularia, Y. Kermaidic, W. Ketchum, S. H. Kettell, M. Khabibullin, N. Khan, A. Khvedelidze, D. Kim, J. Kim, M. Kim, B. King, B. Kirby, M. Kirby, A. Kish, J. Klein, J. Kleykamp, A. Klustova, T. Kobilarcik, L. Koch, K. Koehler, L. W. Koerner, D. H. Koh, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, I. Kotler, M. Kovalcuk, V. Kozhukalov, W. Krah, R. Kralik, M. Kramer, L. Kreczko, F. Krennrich, I. Kreslo, T. Kroupova, S. Kubota, M. Kubu, Y. Kudenko, V. A. Kudryavtsev, G. Kufatty, S. Kuhlmann, J. Kumar, P. Kumar, S. Kumaran, P. Kunze, J. Kunzmann, R. Kuravi, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, T. Labree, T. Lackey, A. Lambert, B. J. Land, C. E. Lane, N. Lane, K. Lang, T. Langford, M. Langstaff, F. Lanni, O. Lantwin, J. Larkin, P. Lasorak, D. Last, A. Laudrain, A. Laundrie, G. Laurenti, E. Lavaut, A. Lawrence, P. Laycock, I. Lazanu, M. Lazzaroni, T. Le, S. Leardini, J. Learned, T. LeCompte, C. Lee, V. Legin, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, D. Leon Silverio, L. M. Lepin, J.-Y. Li, S. W. Li, Y. Li, H. Liao, C. S. Lin, D. Lindebaum, S. Linden, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, H. Liu, J. Liu, Y. Liu, S. Lockwitz, M. Lokajicek, I. Lomidze, K. Long, T. V. Lopes, J. Lopez, I. López de Rego, N. López-March, T. Lord, J. M. LoSecco, W. C. Louis, A. Lozano Sanchez, X.-G. Lu, K. B. Luk, B. Lunday, X. Luo, E. Luppi, J. Maalmi, D. MacFarlane, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, M. MacMahon, A. Maddalena, A. Madera, P. Madigan, S. Magill, C. Magueur, K. Mahn, A. Maio, A. Major, K. Majumdar, M. Man, R. C. Mandujano, J. Maneira, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, S. Manthey Corchado, V. N. Manyam, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, F. Marinho, A. D. Marino, T. Markiewicz, F. Das Chagas Marques, C. Marquet, D. Marsden, M. Marshak, C. M. Marshall, J. Marshall, L. Martina, J. Martín-Albo, N. Martinez, D. A. Martinez Caicedo, F. Martínez López, P. Martínez Miravé, S. Martynenko, V. Mascagna, C. Massari, A. Mastbaum, F. Matichard, S. Matsuno, G. Matteucci, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, T. McAskill, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, L. Meazza, V. C. N. Meddage, B. Mehta, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, A. C. E. A. Mercuri, A. Meregaglia, M. D. Messier, S. Metallo, J. Metcalf, W. Metcalf, M. Mewes, H. Meyer, T. Miao, A. Miccoli, G. Michna, V. Mikola, R. Milincic, F. Miller, G. Miller, W. Miller, O. Mineev, A. Minotti, L. Miralles, O. G. Miranda, C. Mironov, S. Miryala, S. Miscetti, C. S. Mishra, S. R. Mishra, A. Mislivec, M. Mitchell, D. Mladenov, I. Mocioiu, A. Mogan, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, D. Montanino, L. M. Montaño Zetina, M. Mooney, A. F. Moor, Z. Moore, D. Moreno, O. Moreno-Palacios, L. Morescalchi, D. Moretti, R. Moretti, C. Morris, C. Mossey, M. Mote, C. A. Moura, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, F. Muheim, A. Muir, M. Mulhearn, D. Munford, L. J. Munteanu, H. Muramatsu, J. Muraz, M. Murphy, T. Murphy, J. Muse, A. Mytilinaki, J. Nachtman, Y. Nagai, S. Nagu, R. Nandakumar, D. Naples, S. Narita, A. Nath, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, A. Nehm, J. K. Nelson, O. Neogi, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, R. Nichol, F. Nicolas-Arnaldos, A. Nikolica, J. Nikolov, E. Niner, K. Nishimura, A. Norman, A. Norrick, P. Novella, J. A. Nowak, M. Oberling, J. P. Ochoa-Ricoux, S. Oh, S. B. Oh, A. Olivier, A. Olshevskiy, T. Olson, Y. Onel, Y. Onishchuk, A. Oranday, M. Osbiston, J. A. Osorio Vélez, L. Otiniano Ormachea, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, S. Pan, P. Panda, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, D. Papoulias, S. Paramesvaran, A. Paris, S. Parke, E. Parozzi, S. Parsa, Z. Parsa, S. Parveen, M. Parvu, D. Pasciuto, S. Pascoli, L. Pasqualini, J. Pasternak, C. Patrick, L. Patrizii, R. B. Patterson, T. Patzak, A. Paudel, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, E. Pedreschi, S. J. M. Peeters, W. Pellico, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. G. Peres, Y. F. Perez Gonzalez, L. Pérez-Molina, C. Pernas, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, M. Pfaff, V. Pia, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, J. Pinchault, K. Pitts, K. Plows, R. Plunkett, C. Pollack, T. Pollman, D. Polo-Toledo, F. Pompa, X. Pons, N. Poonthottathil, V. Popov, F. Poppi, J. Porter, M. Potekhin, R. Potenza, J. Pozimski, M. Pozzato, T. Prakash, C. Pratt, M. Prest, F. Psihas, D. Pugnere, X. Qian, J. L. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, S. Rajagopalan, M. Rajaoalisoa, I. Rakhno, L. Rakotondravohitra, L. Ralte, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, R. Ray, H. Razafinime, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, E. Renner, A. Renshaw, S. Rescia, F. Resnati, D. Restrepo, C. Reynolds, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, J. S. Ricol, M. Rigan, E. V. Rincón, A. Ritchie-Yates, S. Ritter, D. Rivera, R. Rivera, A. Robert, J. L. Rocabado Rocha, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, J. Rodriguez Rondon, S. Rosauro-Alcaraz, P. Rosier, D. Ross, M. Rossella, M. Rossi, M. Ross-Lonergan, N. Roy, P. Roy, C. Rubbia, A. Ruggeri, G. Ruiz Ferreira, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, S. K. Sahoo, N. Sahu, P. Sala, N. Samios, O. Samoylov, M. C. Sanchez, A. Sánchez Bravo, P. Sanchez-Lucas, V. Sandberg, D. A. Sanders, S. Sanfilippo, D. Sankey, D. Santoro, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, I. Sarra, G. Savage, V. Savinov, G. Scanavini, A. Scaramelli, A. Scarff, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, B. Schuld, A. Segade, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, M. H. Shaevitz, P. Shanahan, P. Sharma, R. Kumar, K. Shaw, T. Shaw, K. Shchablo, J. Shen, C. Shepherd-Themistocleous, A. Sheshukov, W. Shi, S. Shin, S. Shivakoti, I. Shoemaker, D. Shooltz, R. Shrock, B. Siddi, M. Siden, J. Silber, L. Simard, J. Sinclair, G. Sinev, Jaydip Singh, J. Singh, L. Singh, P. Singh, V. Singh, S. Singh Chauhan, R. Sipos, C. Sironneau, G. Sirri, K. Siyeon, K. Skarpaas, J. Smedley, E. Smith, J. Smith, P. Smith, J. Smolik, M. Smy, M. Snape, E. L. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. R. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, A. Sousa, K. Soustruznik, F. Spinella, J. Spitz, N. J. C. Spooner, K. Spurgeon, D. Stalder, M. Stancari, L. Stanco, J. Steenis, R. Stein, H. M. Steiner, A. F. Steklain Lisbôa, A. Stepanova, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. Subash, A. Surdo, L. Suter, C. M. Sutera, K. Sutton, Y. Suvorov, R. Svoboda, S. K. Swain, B. Szczerbinska, A. M. Szelc, A. Sztuc, A. Taffara, N. Talukdar, J. Tamara, H. A. Tanaka, S. Tang, N. Taniuchi, A. M. Tapia Casanova, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, E. Tatar, R. Tayloe, D. Tedeschi, A. M. Teklu, J. Tena Vidal, P. Tennessen, M. Tenti, K. Terao, F. Terranova, G. Testera, T. Thakore, A. Thea, A. Thiebault, S. Thomas, A. Thompson, C. Thorn, S. C. Timm, E. Tiras, V. Tishchenko, N. Todorović, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, D. Tran, R. Travaglini, J. Trevor, E. Triller, S. Trilov, J. Truchon, D. Truncali, W. H. Trzaska, Y. Tsai, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Z. Tu, S. Tufanli, C. Tunnell, J. Turner, M. Tuzi, J. Tyler, E. Tyley, M. Tzanov, M. A. Uchida, J. Ureña González, J. Urheim, T. Usher, H. Utaegbulam, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. F. Valle, R. Van Berg, R. G. Van de Water, D. V. Forero, A. Vannozzi, M. Van Nuland-Troost, F. Varanini, D. Vargas Oliva, S. Vasina, N. Vaughan, K. Vaziri, A. Vázquez-Ramos, J. Vega, S. Ventura, A. Verdugo, S. Vergani, M. Verzocchi, K. Vetter, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, E. Villa, S. Viola, B. Viren, A. Vizcaya-Hernandez, T. Vrba, Q. Vuong, A. V. Waldron, M. Wallbank, J. Walsh, T. Walton, H. Wang, J. Wang, L. Wang, M. H. L. S. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, L. Warsame, M. O. Wascko, D. Waters, A. Watson, K. Wawrowska, A. Weber, C. M. Weber, M. Weber, H. Wei, A. Weinstein, H. Wenzel, S. Westerdale, M. Wetstein, K. Whalen, J. Whilhelmi, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, F. Wilson, R. J. Wilson, P. Winter, W. Wisniewski, J. Wolcott, J. Wolfs, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, M. Wospakrik, K. Wresilo, C. Wret, S. Wu, W. Wu, M. Wurm, J. Wyenberg, Y. Xiao, I. Xiotidis, B. Yaeggy, N. Yahlali, E. Yandel, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, O. Zapata, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, M. Zhao, E. Zhivun, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and on behalf of the DUNE Collaboration
Subjects: neutrino, near detector, Deep Underground Neutrino Experiment, DUNE, Physics, QC1-999, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations.
Published: 2024
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4. Wet-dry cycling influences the formation of mineral-associated organic matter and its sensitivity to simulated root exudates

Author: Andrea Jilling, Noah W. Sokol, Karen Morán-Rivera, and A. Stuart Grandy
Subjects: Mineral-associated organic matter, Wet-dry cycles, Priming, Science
Abstract: Mineral particles provide reactive sites for organic carbon (C) to bind in soil; this ‘mineral-associated organic matter’ (MAOM) may persist for centuries to millennia or cycle rapidly in minutes to days. The conditions and processes that influence short and long-term cycling of MAOM are poorly constrained. Soil moisture is one key control on organic matter cycling in soil, and projected shifts in moisture regimes towards more intense rainfall and prolonged drought under climate change may alter MAOM formation and cycling. Here, in a 3-week laboratory incubation study, we evaluated how two contrasting moisture regimes affected the formation and cycling of 13C-labeled MAOM from two mineralogically-distinct soil types. Repeated wet-dry cycling (between 3% and 60% of water-holding capacity) enhanced the formation of 13C-MAOM relative to constant moisture conditions. The two soil types differed in rates of MAOM formation and the sensitivity of newly-formed and pre-existing MAOM to subsequent priming in the presence of simulated exudates (glucose and/or oxalic acid). Wet-dry cycling enhanced the decomposition of newly-formed MAOM and it further accelerated the potential priming of pre-existing MAOM. Therefore, while repeated cycles between drought-like and “optimal” moisture conditions may promote the formation of MAOM, they may also undermine the stability of pre-existing MAOM and limit opportunities for new C inputs to enter more persistent forms.
Published: 2024
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5. Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, C. Adriano, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, F. Akbar, B. Ali-Mohammadzadeh, K. Allison, S. Alonso Monsalve, M. AlRashed, C. Alt, A. Alton, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, S. Antusch, A. Aranda-Fernandez, L. Arellano, L. O. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Ayala Lara, M. Ayala-Torres, F. Azfar, A. Back, H. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, G. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, J. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. L. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, E. Belchior Batista das Chagas, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, A. T. Bezerra, T. J. Bezerra, A. Bhardwaj, V. Bhatnagar, M. Bhattacharjee, D. Bhattarai, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. D. M. Blaszczyk, G. C. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, A. Borkum, N. Bostan, P. Bour, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Branca, A. Brandt, J. Bremer, C. Brew, S. J. Brice, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, I. Butorov, I. Cagnoli, T. Cai, D. Caiulo, R. Calabrese, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, A. Caminata, A. Campos Benitez, D. Caratelli, D. Carber, J. M. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, T. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, G. Cavallaro, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, E. Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, M. S. Chavarry Neyra, H. Chen, M. Chen, Y. Chen, Z. Chen, Z. Chen-Wishart, Y. Cheon, D. Cherdack, C. Chi, S. Childress, R. Chirco, A. Chiriacescu, K. Cho, S. Choate, D. Chokheli, P. S. Chong, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, M. Chung, E. Church, V. Cicero, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. Coelho, J. Collot, N. Colton, E. Conley, R. Conley, J. Conrad, M. Convery, S. Copello, P. Cova, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, R. Cross, A. Cudd, C. Cuesta, Y. Cui, D. Cussans, J. Dai, O. Dalager, H. Da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, S. De, P. Debbins, I. De Bonis, M. Decowski, A. De Gouvea, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, V. De Leo, D. Delepine, M. Delgado, A. Dell’Acqua, N. Delmonte, P. De Lurgio, J. R. De Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. W. Deptuch, A. De Roeck, V. De Romeri, G. De Souza, R. Devi, R. Dharmapalan, M. Dias, J. Diaz, F. Díaz, F. Di Capua, A. Di Domenico, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, G. Dirkx, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. Dolinski, L. Domine, Y. Donon, D. Douglas, A. Dragone, G. Drake, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, P. Dunne, B. Dutta, H. Duyang, O. Dvornikov, D. Dwyer, A. Dyshkant, M. Eads, A. Earle, D. Edmunds, J. Eisch, L. Emberger, S. Emery, P. Englezos, A. Ereditato, T. Erjavec, C. Escobar, L. Escudero Sanchez, G. Eurin, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, M. Fani’, C. Farnese, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, P. Fernandez Menendez, F. Ferraro, L. Fields, P. Filip, F. Filthaut, R. Fine, G. Fiorillo, M. Fiorini, V. Fischer, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, S. Fogarty, W. Foreman, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, A. Gabrielli, A. Gago, H. Gallagher, A. Gallas, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, S. Ganguly, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, J. Gauvreau, P. Gauzzi, G. Ge, N. Geffroy, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, P. Giammaria, T. Giammaria, N. Giangiacomi, D. Gibin, I. Gil-Botella, S. Gilligan, C. Girerd, A. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. Gollwitzer, R. A. Gomes, L. Gomez Bermeo, L. S. Gomez Fajardo, F. Gonnella, D. González Caamaño, D. Gonzalez-Diaz, M. Gonzalez-Lopez, M. C. Goodman, O. Goodwin, S. Goswami, C. Gotti, E. Goudzovski, C. Grace, R. Gran, E. Granados, P. Granger, C. Grant, D. Gratieri, P. Green, S. Green, S. Greenberg, L. Greenler, J. Greer, J. Grenard, C. Griffith, M. Groh, J. Grudzinski, K. Grzelak, W. Gu, E. Guardincerri, V. Guarino, M. Guarise, R. Guenette, E. Guerard, M. Guerzoni, D. Guffanti, A. Guglielmi, B. Guo, A. Gupta, V. Gupta, K. Guthikonda, P. Guzowski, M. M. Guzzo, S. Gwon, C. Ha, K. Haaf, A. Habig, H. Hadavand, R. Haenni, A. Hahn, J. Haiston, P. Hamacher-Baumann, T. Hamernik, P. Hamilton, J. Han, D. A. Harris, J. Hartnell, T. Hartnett, J. Harton, T. Hasegawa, C. Hasnip, R. Hatcher, K. W. Hatfield, A. Hatzikoutelis, C. Hayes, K. Hayrapetyan, J. Hays, E. Hazen, M. He, A. Heavey, K. M. Heeger, J. Heise, S. Henry, M. Hernandez Morquecho, K. Herner, J. Hewes, C. Hilgenberg, T. Hill, S. J. Hillier, A. Himmel, E. Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, I. Hristova, M. S. Hronek, J. Huang, Z. Hulcher, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, F. Jediny, D. Jena, Y. Jeong, C. Jesús-Valls, X. Ji, J. Jiang, L. Jiang, S. Jiménez, A. Jipa, F. Joaquim, W. Johnson, N. Johnston, B. Jones, M. Judah, C. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, F. Kamiya, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, O. Kemularia, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, A. Klustova, T. Kobilarcik, K. Koehler, L. W. Koerner, D. H. Koh, S. Kohn, P. P. Koller, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. Kostelecky, K. Kothekar, R. Kralik, L. Kreczko, F. Krennrich, I. Kreslo, W. Kropp, T. Kroupova, S. Kubota, Y. Kudenko, V. A. Kudryavtsev, S. Kuhlmann, S. Kulagin, J. Kumar, P. Kumar, P. Kunze, R. Kuravi, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, D. Kwak, A. Lambert, B. Land, C. E. Lane, K. Lang, T. Langford, M. Langstaff, J. Larkin, P. Lasorak, D. Last, A. Laundrie, G. Laurenti, A. Lawrence, I. Lazanu, R. LaZur, M. Lazzaroni, T. Le, S. Leardini, J. Learned, P. LeBrun, T. LeCompte, C. Lee, S. Lee, G. Lehmann Miotto, R. Lehnert, M. Leigui de Oliveira, M. Leitner, L. M. Lepin, S. Li, Y. Li, H. Liao, C. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, T. Lord, J. LoSecco, W. C. Louis, X. Lu, K. Luk, B. Lunday, X. Luo, E. Luppi, T. Lux, V. P. Luzio, J. Maalmi, D. MacFarlane, A. Machado, P. Machado, C. Macias, J. Macier, A. Maddalena, A. Madera, P. Madigan, S. Magill, K. Mahn, A. Maio, A. Major, J. A. Maloney, G. Mandrioli, R. C. Mandujano, J. C. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, V. N. Manyam, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, R. Marie, F. Marinho, A. D. Marino, T. Markiewicz, D. Marsden, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martín-Albo, N. Martinez, D. A. Martinez Caicedo, P. Martínez Miravé, S. Martynenko, V. Mascagna, K. Mason, A. Mastbaum, F. Matichard, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, E. Mazzucato, T. McAskill, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, M. Messier, W. Metcalf, M. Mewes, H. Meyer, T. Miao, G. Michna, V. Mikola, R. 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Ochoa-Ricoux, A. Olivier, A. Olshevskiy, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, E. Parozzi, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. Peeters, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, V. Pia, F. Piastra, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, K. Plows, R. Plunkett, F. Pompa, X. Pons, N. Poonthottathil, F. Poppi, S. Pordes, J. Porter, S. Porzio, M. Potekhin, R. Potenza, B. V. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, M. Prest, S. Prince, F. Psihas, D. Pugnere, X. Qian, J. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, A. Rakotonandrasana, L. Rakotondravohitra, R. Rameika, M. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Raut, H. Razafinime, R. Razakamiandra, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, A. Renshaw, S. Rescia, F. Resnati, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, L. C. Rice, J. S. Ricol, A. Rigamonti, Y. Rigaut, E. V. Rincón, H. Ritchie-Yates, D. Rivera, A. Robert, J. Rocabado Rocha, L. Rochester, M. Roda, P. Rodrigues, J. V. Rodrigues da Silva Leite, M. J. Rodriguez Alonso, J. Rodriguez Rondon, S. Rosauro-Alcaraz, P. Rosier, B. Roskovec, M. Rossella, M. Rossi, J. Rout, P. Roy, A. Rubbia, C. Rubbia, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, N. Sahu, P. Sala, N. Samios, O. Samoylov, M. Sanchez, V. Sandberg, D. A. Sanders, D. Sankey, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, D. Sgalaberna, M. Shaevitz, S. Shafaq, F. Shaker, M. Shamma, R. Sharankova, H. R. Sharma, R. Sharma, R. K. Sharma, K. Shaw, T. Shaw, K. Shchablo, C. Shepherd-Themistocleous, A. Sheshukov, S. Shin, I. Shoemaker, D. Shooltz, R. Shrock, H. Siegel, L. Simard, J. Sinclair, G. Sinev, J. Singh, L. Singh, P. Singh, V. Singh, R. Sipos, F. Sippach, G. Sirri, A. Sitraka, K. Siyeon, K. Skarpaas, E. Smith, P. Smith, J. Smolik, M. Smy, E. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, F. Soto Ugaldi, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, M. Stancari, L. Stanco, C. Stanford, R. Stein, H. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. Suárez Sunción, H. Sullivan, A. Surdo, V. Susic, L. Suter, C. Sutera, Y. Suvorov, R. Svoboda, B. Szczerbinska, A. M. Szelc, N. Talukdar, H. Tanaka, S. Tang, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, N. Tata, E. Tatar, R. Tayloe, A. Teklu, P. Tennessen, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, T. Thakore, A. Thea, C. Thorn, S. Timm, V. Tishchenko, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, R. Travaglini, J. Trevor, S. Trilov, W. H. Trzaska, Y. Tsai, Z. Tsamalaidze, K. Tsang, N. Tsverava, S. Z. Tu, S. Tufanli, C. Tull, J. Tyler, E. Tyley, M. Tzanov, L. Uboldi, M. A. Uchida, J. Urheim, T. Usher, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. D. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, D. Vannerom, F. Varanini, D. Vargas Oliva, G. Varner, J. Vasel, S. Vasina, G. Vasseur, N. Vaughan, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, C. Wallis, T. Walton, H. Wang, J. Wang, L. Wang, M. H. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, M. Wascko, D. Waters, A. Watson, K. Wawrowska, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, W. Wisniewski, J. Wolcott, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, C. Wret, W. Wu, Y. Xiao, B. Yaeggy, E. Yandel, G. Yang, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, Y. Yoon, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and DUNE Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 $$\pm 0.6$$ ± 0.6 % and 84.1 $$\pm 0.6$$ ± 0.6 %, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation.
Published: 2023
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6. Short‐term responses of soil carbon, nitrogen, and microbial biomass to cover crop mixtures and monocultures

Author: Igor Alexandre deSouza, Amanda B. Daly, Jörg Schnecker, Nicholas D. Warren, Adalfredo Rocha Lobo Jr, Richard G. Smith, Andre Fonseca Brito, and A. Stuart Grandy
Subjects: Agriculture, Environmental sciences, GE1-350
Abstract: Abstract Increasingly, cover crops are being adopted for the purpose of improving soil health, yet the timescale and magnitude by which living annual cover crops might modify soil chemical and biological aspects of soil health is not well understood. At the same time, there is growing interest among farmers in cover crop mixtures due to perceptions that species‐rich cover crop communities will enhance soil health relative to monocultures. In a field experiment in southeast New Hampshire, we investigated how groups of cover crops grown as monocultures and mixtures for specific seasonal niches (winter/spring, summer, and fall) influenced levels of soil nitrogen (N) and carbon (C), microbial biomass carbon (MBC), and nitrogen (MBN). Soils were sampled at cover crop maturity (winter/spring group), and at seeding, mid‐season, and maturity (summer and fall groups). In the winter/spring group, average total soil N ranged from 0.192 to 0.215 mg g−1 dry soil; highest total soil C content was 2.66 mg g−1 dry soil; and average MBC ranged from 304.8 to 387.3 μg C g−1 dry soil. In the summer group soil MBC decreased from 909.5 μg C g−1 dry soil at mid‐season to 644.9 μg C g−1 dry soil at the end of the growth cycle. In the fall group MBC fell and rose over the season in the range of 236.0–808.3 μg C g−1 dry soil. We found little evidence that cover crops influenced soil C and N parameters during the cover crop growth period relative to a weedy control or that mixtures differed from monocultures. MBC and MBN were more influenced by seasonality than the composition or diversity of the cover crop stand.
Published: 2023
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7. Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. AlRashed, C. Alt, A. Alton, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, S. Antusch, A. Aranda-Fernandez, L. Arellano, L. O. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Ayala Lara, M. Ayala-Torres, F. Azfar, M. Babicz, A. Back, H. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, G. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, E. Batista das Chagas, J. Battat, F. Battisti, F. Bay, M. C. Q. Bazetto, J. Bazo Alba, J. F. Beacom, E. Bechetoille, B. Behera, C. Beigbeder, L. Bellantoni, G. Bellettini, V. Bellini, O. Beltramello, N. Benekos, C. Benitez Montiel, F. Bento Neves, J. Berger, S. Berkman, P. Bernardini, R. M. Berner, A. Bersani, S. Bertolucci, M. Betancourt, A. Betancur Rodríguez, A. Bevan, Y. Bezawada, T. S. Bezerra, A. Bhardwaj, V. Bhatnagar, M. Bhattacharjee, D. Bhattarai, S. Bhuller, B. Bhuyan, S. Biagi, J. Bian, M. Biassoni, K. Biery, B. Bilki, M. Bishai, A. Bitadze, A. Blake, F. Blaszczyk, G. Blazey, E. Blucher, J. Boissevain, S. Bolognesi, T. Bolton, L. Bomben, M. Bonesini, M. Bongrand, C. Bonilla-Diaz, F. Bonini, A. Booth, F. Boran, S. Bordoni, A. Borkum, N. Bostan, P. Bour, C. Bourgeois, D. Boyden, J. Bracinik, D. Braga, D. Brailsford, A. Branca, A. Brandt, J. Bremer, D. Breton, C. Brew, S. J. Brice, C. Brizzolari, C. Bromberg, J. Brooke, A. Bross, G. Brunetti, M. Brunetti, N. Buchanan, H. Budd, I. Butorov, I. Cagnoli, T. Cai, D. Caiulo, R. Calabrese, P. Calafiura, J. Calcutt, M. Calin, S. Calvez, E. Calvo, A. Caminata, M. Campanelli, D. Caratelli, D. Carber, J. Carceller, G. Carini, B. Carlus, M. F. Carneiro, P. Carniti, I. Caro Terrazas, H. Carranza, T. Carroll, J. F. Castaño Forero, A. Castillo, C. Castromonte, E. Catano-Mur, C. Cattadori, F. Cavalier, G. Cavallaro, F. Cavanna, S. Centro, G. Cerati, A. Cervelli, A. Cervera Villanueva, M. Chalifour, A. Chappell, E. Chardonnet, N. Charitonidis, A. Chatterjee, S. Chattopadhyay, M. Chavarry Neyra, H. Chen, M. Chen, Y. Chen, Z. Chen, Z. Chen-Wishart, Y. Cheon, D. Cherdack, C. Chi, S. Childress, R. Chirco, A. Chiriacescu, G. Chisnall, K. Cho, S. Choate, D. Chokheli, P. S. Chong, A. Christensen, D. Christian, G. Christodoulou, A. Chukanov, M. Chung, E. Church, V. Cicero, P. Clarke, G. Cline, T. E. Coan, A. G. Cocco, J. Coelho, N. Colton, E. Conley, R. Conley, J. Conrad, M. Convery, S. Copello, P. Cova, L. Cremaldi, L. Cremonesi, J. I. Crespo-Anadón, M. Crisler, E. Cristaldo, J. Crnkovic, R. Cross, A. Cudd, C. Cuesta, Y. Cui, D. Cussans, O. Dalager, H. Da Motta, L. Da Silva Peres, C. David, Q. David, G. S. Davies, S. Davini, J. Dawson, K. De, S. De, P. Debbins, I. De Bonis, M. Decowski, A. De Gouvea, P. C. De Holanda, I. L. De Icaza Astiz, A. Deisting, P. De Jong, A. Delbart, D. Delepine, M. Delgado, A. Dell’Acqua, N. Delmonte, P. De Lurgio, J. R. De Mello Neto, D. M. DeMuth, S. Dennis, C. Densham, G. W. Deptuch, A. De Roeck, V. De Romeri, G. De Souza, R. Devi, R. Dharmapalan, M. Dias, F. Diaz, J. Diaz, S. Di Domizio, L. Di Giulio, P. Ding, L. Di Noto, G. Dirkx, C. Distefano, R. Diurba, M. Diwan, Z. Djurcic, D. Doering, S. Dolan, F. Dolek, M. Dolinski, L. Domine, Y. Donon, D. Douglas, D. Douillet, A. Dragone, G. Drake, F. Drielsma, L. Duarte, D. Duchesneau, K. Duffy, P. Dunne, B. Dutta, H. Duyang, O. Dvornikov, D. Dwyer, A. Dyshkant, M. Eads, A. Earle, D. Edmunds, J. Eisch, L. Emberger, S. Emery, P. Englezos, A. Ereditato, T. Erjavec, C. Escobar, G. Eurin, J. J. Evans, E. Ewart, A. C. Ezeribe, K. Fahey, A. Falcone, M. Fani’, C. Farnese, Y. Farzan, D. Fedoseev, J. Felix, Y. Feng, E. Fernandez-Martinez, P. Fernandez Menendez, M. Fernandez Morales, F. Ferraro, L. Fields, P. Filip, F. Filthaut, M. Fiorini, V. Fischer, R. S. Fitzpatrick, W. Flanagan, B. Fleming, R. Flight, S. Fogarty, W. Foreman, J. Fowler, W. Fox, J. Franc, K. Francis, D. Franco, J. Freeman, J. Freestone, J. Fried, A. Friedland, F. Fuentes Robayo, S. Fuess, I. K. Furic, K. Furman, A. P. Furmanski, A. Gabrielli, A. Gago, H. Gallagher, A. Gallas, A. Gallego-Ros, N. Gallice, V. Galymov, E. Gamberini, T. Gamble, F. Ganacim, R. Gandhi, R. Gandrajula, F. Gao, S. Gao, D. Garcia-Gamez, M. Á. García-Peris, S. Gardiner, D. Gastler, J. Gauvreau, G. Ge, N. Geffroy, B. Gelli, A. Gendotti, S. Gent, Z. Ghorbani-Moghaddam, P. Giammaria, T. Giammaria, N. Giangiacomi, D. Gibin, I. Gil-Botella, S. Gilligan, C. Girerd, A. Giri, D. Gnani, O. Gogota, M. Gold, S. Gollapinni, K. 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Hinkle, L. R. Hirsch, J. Ho, J. Hoff, A. Holin, E. Hoppe, G. A. Horton-Smith, M. Hostert, A. Hourlier, B. Howard, R. Howell, J. Hoyos, I. Hristova, M. S. Hronek, J. Huang, Z. Hulcher, G. Iles, N. Ilic, A. M. Iliescu, R. Illingworth, G. Ingratta, A. Ioannisian, B. Irwin, L. Isenhower, R. Itay, C. M. Jackson, V. Jain, E. James, W. Jang, B. Jargowsky, F. Jediny, D. Jena, Y. Jeong, C. Jesús-Valls, X. Ji, L. Jiang, S. Jiménez, A. Jipa, R. Johnson, W. Johnson, N. Johnston, B. Jones, S. Jones, M. Judah, C. Jung, T. Junk, Y. Jwa, M. Kabirnezhad, A. Kaboth, I. Kadenko, I. Kakorin, A. Kalitkina, D. Kalra, F. Kamiya, N. Kaneshige, D. M. Kaplan, G. Karagiorgi, G. Karaman, A. Karcher, M. Karolak, Y. Karyotakis, S. Kasai, S. P. Kasetti, L. Kashur, N. Kazaryan, E. Kearns, P. Keener, K. J. Kelly, E. Kemp, O. Kemularia, W. Ketchum, S. H. Kettell, M. Khabibullin, A. Khotjantsev, A. Khvedelidze, D. Kim, B. King, B. Kirby, M. Kirby, J. Klein, A. Klustova, T. Kobilarcik, K. Koehler, L. W. Koerner, D. H. Koh, S. Kohn, P. P. Koller, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. Kostelecky, K. Kothekar, R. Kralik, L. Kreczko, F. Krennrich, I. Kreslo, W. Kropp, T. Kroupova, S. Kubota, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, P. Kumar, P. Kunze, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, D. Kwak, A. Lambert, B. Land, C. E. Lane, K. Lang, T. Langford, M. Langstaff, J. Larkin, P. Lasorak, D. Last, A. Laundrie, G. Laurenti, A. Lawrence, I. Lazanu, R. LaZur, M. Lazzaroni, T. Le, S. Leardini, J. Learned, P. LeBrun, T. LeCompte, C. Lee, S. Lee, G. Lehmann Miotto, R. Lehnert, M. Leigui de Oliveira, M. Leitner, L. M. Lepin, S. Li, Y. Li, H. Liao, C. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, T. Lord, J. LoSecco, W. C. Louis, X. Lu, K. Luk, B. Lunday, X. Luo, E. Luppi, T. Lux, V. P. Luzio, J. Maalmi, D. MacFarlane, A. Machado, P. Machado, C. Macias, J. 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Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, and R. Zwaska
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation.
Published: 2022
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8. Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

Author: A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, A. Aduszkiewicz, J. Aguilar, Z. Ahmad, J. Ahmed, B. Aimard, B. Ali-Mohammadzadeh, T. Alion, K. Allison, S. Alonso Monsalve, M. AlRashed, C. Alt, A. Alton, R. Alvarez, P. Amedo, J. Anderson, C. Andreopoulos, M. Andreotti, M. Andrews, F. Andrianala, S. Andringa, N. Anfimov, A. Ankowski, M. Antoniassi, M. Antonova, A. Antoshkin, S. Antusch, A. Aranda-Fernandez, L. Arellano, L. O. Arnold, M. A. Arroyave, J. Asaadi, L. Asquith, A. Aurisano, V. Aushev, D. Autiero, V. Ayala Lara, M. Ayala-Torres, F. Azfar, A. Back, H. Back, J. J. Back, C. Backhouse, I. Bagaturia, L. Bagby, N. Balashov, S. Balasubramanian, P. Baldi, B. Baller, B. Bambah, F. Barao, G. Barenboim, P. Barham Alzas, G. Barker, W. Barkhouse, C. Barnes, G. Barr, J. Barranco Monarca, A. Barros, N. Barros, J. L. Barrow, A. Basharina-Freshville, A. Bashyal, V. Basque, C. Batchelor, E. Batista das Chagas, J. B. R. 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Kirby, J. Klein, A. Klustova, T. Kobilarcik, K. Koehler, L. W. Koerner, D. H. Koh, S. Kohn, P. P. Koller, L. Kolupaeva, D. Korablev, M. Kordosky, T. Kosc, U. Kose, V. A. Kostelecký, K. Kothekar, R. Kralik, L. Kreczko, F. Krennrich, I. Kreslo, W. Kropp, T. Kroupova, S. Kubota, Y. Kudenko, V. A. Kudryavtsev, S. Kulagin, J. Kumar, P. Kumar, P. Kunze, N. Kurita, C. Kuruppu, V. Kus, T. Kutter, J. Kvasnicka, D. Kwak, A. Lambert, B. Land, C. E. Lane, K. Lang, T. Langford, M. Langstaff, J. Larkin, P. Lasorak, D. Last, A. Laundrie, G. Laurenti, A. Lawrence, I. Lazanu, R. LaZur, M. Lazzaroni, T. Le, S. Leardini, J. Learned, P. LeBrun, T. LeCompte, C. Lee, S. Y. Lee, G. Lehmann Miotto, R. Lehnert, M. A. Leigui de Oliveira, M. Leitner, L. M. Lepin, S. W. Li, Y. Li, H. Liao, C. S. Lin, Q. Lin, S. Lin, R. A. Lineros, J. Ling, A. Lister, B. R. Littlejohn, J. Liu, Y. Liu, S. Lockwitz, T. Loew, M. Lokajicek, I. Lomidze, K. Long, T. Lord, J. M. LoSecco, W. C. Louis, X.-G. Lu, K. B. Luk, B. Lunday, X. Luo, E. Luppi, T. Lux, V. P. Luzio, J. Maalmi, D. MacFarlane, A. A. Machado, P. Machado, C. T. Macias, J. R. Macier, A. Maddalena, A. Madera, P. Madigan, S. Magill, K. Mahn, A. Maio, A. Major, J. A. Maloney, G. Mandrioli, R. C. Mandujano, J. Maneira, L. Manenti, S. Manly, A. Mann, K. Manolopoulos, M. Manrique Plata, V. N. Manyam, L. Manzanillas, M. Marchan, A. Marchionni, W. Marciano, D. Marfatia, C. Mariani, J. Maricic, R. Marie, F. Marinho, A. D. Marino, D. Marsden, M. Marshak, C. Marshall, J. Marshall, J. Marteau, J. Martín-Albo, N. Martinez, D. A. Martinez Caicedo, P. Martínez Miravé, S. Martynenko, V. Mascagna, K. Mason, A. Mastbaum, F. Matichard, S. Matsuno, J. Matthews, C. Mauger, N. Mauri, K. Mavrokoridis, I. Mawby, R. Mazza, A. Mazzacane, E. Mazzucato, T. McAskill, E. McCluskey, N. McConkey, K. S. McFarland, C. McGrew, A. McNab, A. Mefodiev, P. Mehta, P. Melas, O. Mena, H. Mendez, P. Mendez, D. P. Méndez, A. Menegolli, G. Meng, M. D. Messier, W. Metcalf, T. Mettler, M. Mewes, H. Meyer, T. Miao, G. Michna, T. Miedema, V. Mikola, R. Milincic, G. Miller, W. Miller, J. Mills, O. Mineev, A. Minotti, O. G. Miranda, S. Miryala, C. S. Mishra, S. R. Mishra, A. Mislivec, M. Mitchell, D. Mladenov, I. Mocioiu, K. Moffat, N. Moggi, R. Mohanta, T. A. Mohayai, N. Mokhov, J. Molina, L. Molina Bueno, E. Montagna, A. Montanari, C. Montanari, D. Montanari, L. M. Montañno Zetina, S. H. Moon, M. Mooney, A. F. Moor, D. Moreno, D. Moretti, C. Morris, C. Mossey, M. Mote, E. Motuk, C. A. Moura, J. Mousseau, G. Mouster, W. Mu, L. Mualem, J. Mueller, M. Muether, S. Mufson, F. Muheim, A. Muir, M. Mulhearn, D. Munford, H. Muramatsu, S. Murphy, J. Musser, J. Nachtman, S. Nagu, M. Nalbandyan, R. Nandakumar, D. Naples, S. Narita, A. Nath, A. Navrer-Agasson, N. Nayak, M. Nebot-Guinot, K. Negishi, J. K. Nelson, J. Nesbit, M. Nessi, D. Newbold, M. Newcomer, H. Newton, R. Nichol, F. Nicolas-Arnaldos, A. Nikolica, E. Niner, K. Nishimura, A. Norman, A. Norrick, R. Northrop, P. Novella, J. A. Nowak, M. Oberling, J. Ochoa-Ricoux, A. Olivier, A. Olshevskiy, Y. Onel, Y. Onishchuk, J. Ott, L. Pagani, G. Palacio, O. Palamara, S. Palestini, J. M. Paley, M. Pallavicini, C. Palomares, W. Panduro Vazquez, E. Pantic, V. Paolone, V. Papadimitriou, R. Papaleo, A. Papanestis, S. Paramesvaran, S. Parke, E. Parozzi, Z. Parsa, M. Parvu, S. Pascoli, L. Pasqualini, J. Pasternak, J. Pater, C. Patrick, L. Patrizii, R. B. Patterson, S. J. Patton, T. Patzak, A. Paudel, B. Paulos, L. Paulucci, Z. Pavlovic, G. Pawloski, D. Payne, V. Pec, S. J. M. Peeters, A. Pena Perez, E. Pennacchio, A. Penzo, O. L. G. Peres, J. Perry, D. Pershey, G. Pessina, G. Petrillo, C. Petta, R. Petti, V. Pia, F. Piastra, L. Pickering, F. Pietropaolo, V. L. Pimentel, G. Pinaroli, K. Plows, R. Plunkett, R. Poling, F. Pompa, X. Pons, N. Poonthottathil, F. Poppi, S. Pordes, J. Porter, M. Potekhin, R. Potenza, B. V. K. S. Potukuchi, J. Pozimski, M. Pozzato, S. Prakash, T. Prakash, M. Prest, S. Prince, F. Psihas, D. Pugnere, X. Qian, J. L. Raaf, V. Radeka, J. Rademacker, B. Radics, A. Rafique, E. Raguzin, M. Rai, M. Rajaoalisoa, I. Rakhno, A. Rakotonandrasana, L. Rakotondravohitra, R. Rameika, M. A. Ramirez Delgado, B. Ramson, A. Rappoldi, G. Raselli, P. Ratoff, S. Raut, R. F. Razakamiandra, E. M. Rea, J. S. Real, B. Rebel, R. Rechenmacher, M. Reggiani-Guzzo, J. Reichenbacher, S. D. Reitzner, H. Rejeb Sfar, A. Renshaw, S. Rescia, F. Resnati, M. Ribas, S. Riboldi, C. Riccio, G. Riccobene, L. C. J. Rice, J. S. Ricol, A. Rigamonti, Y. Rigaut, E. V. Rincón, H. Ritchie-Yates, D. Rivera, A. Robert, L. Rochester, M. Roda, P. Rodrigues, M. J. Rodriguez Alonso, E. Rodriguez Bonilla, J. Rodriguez Rondon, S. Rosauro-Alcaraz, M. Rosenberg, P. Rosier, B. Roskovec, M. Rossella, M. Rossi, J. Rout, P. Roy, A. Rubbia, C. Rubbia, B. Russell, D. Ruterbories, A. Rybnikov, A. Saa-Hernandez, R. Saakyan, S. Sacerdoti, T. Safford, N. Sahu, K. Sakashita, P. Sala, N. Samios, O. Samoylov, M. C. Sanchez, V. Sandberg, D. A. Sanders, D. Sankey, S. Santana, M. Santos-Maldonado, N. Saoulidou, P. Sapienza, C. Sarasty, I. Sarcevic, G. Savage, V. Savinov, A. Scaramelli, A. Scarff, A. Scarpelli, T. Schefke, H. Schellman, S. Schifano, P. Schlabach, D. Schmitz, A. W. Schneider, K. Scholberg, A. Schukraft, E. Segreto, A. Selyunin, C. R. Senise, J. Sensenig, A. Sergi, D. Sgalaberna, M. H. Shaevitz, S. Shafaq, F. Shaker, M. Shamma, R. Sharankova, H. R. Sharma, R. Sharma, R. K. Sharma, T. Shaw, K. Shchablo, C. Shepherd-Themistocleous, A. Sheshukov, S. Shin, I. Shoemaker, D. Shooltz, R. Shrock, H. Siegel, L. Simard, J. Sinclair, G. Sinev, J. Singh, L. Singh, P. Singh, V. Singh, R. Sipos, F. W. Sippach, G. Sirri, A. Sitraka, K. Siyeon, K. Skarpaas, A. Smith, E. Smith, P. Smith, J. Smolik, M. Smy, E. Snider, P. Snopok, D. Snowden-Ifft, M. Soares Nunes, H. Sobel, M. Soderberg, S. Sokolov, C. J. Solano Salinas, S. Söldner-Rembold, S. R. Soleti, N. Solomey, V. Solovov, W. E. Sondheim, M. Sorel, A. Sotnikov, J. Soto-Oton, F. A. Soto Ugaldi, A. Sousa, K. Soustruznik, F. Spagliardi, M. Spanu, J. Spitz, N. J. C. Spooner, K. Spurgeon, M. Stancari, L. Stanco, C. Stanford, R. Stein, H. M. Steiner, A. F. Steklain Lisbôa, J. Stewart, B. Stillwell, J. Stock, F. Stocker, T. Stokes, M. Strait, T. Strauss, L. Strigari, A. Stuart, J. G. Suarez, J. M. Suárez Sunción, H. Sullivan, D. Summers, A. Surdo, V. Susic, L. Suter, C. M. Sutera, R. Svoboda, B. Szczerbinska, A. M. Szelc, H. Tanaka, S. Tang, A. Tapia, B. Tapia Oregui, A. Tapper, S. Tariq, E. Tarpara, N. Tata, E. Tatar, R. Tayloe, A. M. Teklu, P. Tennessen, M. Tenti, K. Terao, C. A. Ternes, F. Terranova, G. Testera, T. Thakore, A. Thea, J. L. Thompson, C. Thorn, S. C. Timm, V. Tishchenko, L. Tomassetti, A. Tonazzo, D. Torbunov, M. Torti, M. Tortola, F. Tortorici, N. Tosi, D. Totani, M. Toups, C. Touramanis, R. Travaglini, J. Trevor, S. Trilov, W. H. Trzaska, Y. Tsai, Y.-T. Tsai, Z. Tsamalaidze, K. V. Tsang, N. Tsverava, S. Tufanli, C. Tull, E. Tyley, M. Tzanov, L. Uboldi, M. A. Uchida, J. Urheim, T. Usher, S. Uzunyan, M. R. Vagins, P. Vahle, S. Valder, G. D. A. Valdiviesso, E. Valencia, R. Valentim, Z. Vallari, E. Vallazza, J. W. F. Valle, S. Vallecorsa, R. Van Berg, R. G. Van de Water, D. Vanegas Forero, D. Vannerom, F. Varanini, D. Vargas Oliva, G. Varner, J. Vasel, S. Vasina, G. Vasseur, N. Vaughan, K. Vaziri, S. Ventura, A. Verdugo, S. Vergani, M. A. Vermeulen, M. Verzocchi, M. Vicenzi, H. Vieira de Souza, C. Vignoli, C. Vilela, B. Viren, T. Vrba, T. Wachala, A. V. Waldron, M. Wallbank, C. Wallis, H. Wang, J. Wang, L. Wang, M. H. L. S. Wang, X. Wang, Y. Wang, K. Warburton, D. Warner, M. O. Wascko, D. Waters, A. Watson, K. Wawrowska, P. Weatherly, A. Weber, M. Weber, H. Wei, A. Weinstein, D. Wenman, M. Wetstein, A. White, L. H. Whitehead, D. Whittington, M. J. Wilking, A. Wilkinson, C. Wilkinson, Z. Williams, F. Wilson, R. J. Wilson, W. Wisniewski, J. Wolcott, T. Wongjirad, A. Wood, K. Wood, E. Worcester, M. Worcester, K. Wresilo, C. Wret, W. Wu, Y. Xiao, F. Xie, B. Yaeggy, E. Yandel, G. Yang, K. Yang, T. Yang, A. Yankelevich, N. Yershov, K. Yonehara, Y. S. Yoon, T. Young, B. Yu, H. Yu, J. Yu, Y. Yu, W. Yuan, R. Zaki, J. Zalesak, L. Zambelli, B. Zamorano, A. Zani, L. Zazueta, G. P. Zeller, J. Zennamo, K. Zeug, C. Zhang, S. Zhang, Y. Zhang, M. Zhao, E. Zhivun, G. Zhu, E. D. Zimmerman, S. Zucchelli, J. Zuklin, V. Zutshi, R. Zwaska, and DUNE Collaboration
Subjects: Astrophysics, QB460-466, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6 $$\times $$ × 6 $$\times $$ × 6 m $$^3$$ 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019–2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.
Published: 2022
Full Text: View/download PDF

9. Fast-decaying plant litter enhances soil carbon in temperate forests but not through microbial physiological traits

Author: Matthew E. Craig, Kevin M. Geyer, Katilyn V. Beidler, Edward R. Brzostek, Serita D. Frey, A. Stuart Grandy, Chao Liang, and Richard P. Phillips
Subjects: Science
Abstract: Mineral-associated soil carbon buildup is poorly explained by microbial necromass production (a common hypothesis). During litter decomposition, these processes are decoupled by priming effects and alternate soil carbon formation pathways
Published: 2022
Full Text: View/download PDF

10. Dye Attenuation Without Dye: Quantifying Concentration Fields with Short-wave Infrared Imaging

Author: Fortune, George T., Etzold, Merlin A., Landel, Julien R., and Dalziel, Stuart B.
Subjects: Physics - Fluid Dynamics
Abstract: Dye attenuation, or photometric imaging, is an optical technique commonly used in fluid dynamics to measure tracer concentration fields and fluid thicknesses under the assumption that the motion of the dye is representative of the fluid motion and that its presence does not affect the behaviour of the system. However, in some systems, particularly living biological systems or those with strong chemical interactions and reactions, the addition of dye may non-trivially influence the system and may not follow the fluid containing it. To overcome this, we demonstrate how short-wave infrared imaging can be used to measure concentration and height profiles of water and other liquids without the introduction of dye for heights down to 0.2mm with spatial and temporal resolutions of the order of 50 microns per pixel and 120 fps respectively. We showcase the utility of this technique by demonstrating its ability to accurately track the temporal evolution of the total water content of two model systems, namely a water drop spreading on a glass slide and spreading within a hydrogel sheet, validating both against an analytical mass balance. Finally, we discuss how the spectral resolution of the present setup could be increased to the point that concentrations within a multi-component system containing more than one type of liquid could be quantified.
Published: 2024

11. Pattern Formation in Crumpled Hydrogel upon Rapid Dehydration with Acetone

Author: Fortune, George T., Etzold, Merlin A., Landel, Julien R., and Dalziel, Stuart B.
Subjects: Condensed Matter - Soft Condensed Matter
Abstract: From microactuators to biological tissues, non-porous materials with the ability to strongly expand when in contact with a solvent are ubiquitous. Consequently, the swelling of polymer systems such as hydrogel has received recently much research attention. However, the related dehydration of these systems has received much less attention. Here, we present experiments investigating the rapid dehydration of a swollen hydrogel sheet whose surface exhibits a transient crumpling instability characterised by line segments of cusps patterning the surface of the gel into an array of bumps. We perform this dehydration through immersion in acetone, which is highly miscible in water, but poorly miscible in the hydrogel. We report the onset of a fascinating pattern formation where regions of the hydrogel sheet turn turbid. We find that the emerging pattern is independent of the overall extent of the hydrated swollen surface. The pattern wavelength only depends on the duration of hydration before immersion in acetone, growing temporally with a power law behaviour. We conclude through drawing comparisons between features of this dehydration induced pattern and the original crumpling instability in the water swollen hydrogel sheet.
Published: 2024

12. Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving

Author: Tsesmelis, Theodore, Palmieri, Luca, Khoroshiltseva, Marina, Islam, Adeela, Elkin, Gur, Shahar, Ofir Itzhak, Scarpellini, Gianluca, Fiorini, Stefano, Ohayon, Yaniv, Alali, Nadav, Aslan, Sinem, Morerio, Pietro, Vascon, Sebastiano, Gravina, Elena, Napolitano, Maria Cristina, Scarpati, Giuseppe, Zuchtriegel, Gabriel, Spühler, Alexandra, Fuchs, Michel E., James, Stuart, Ben-Shahar, Ohad, Pelillo, Marcello, and Del Bue, Alessio
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dataset has unique properties that are uncommon to current benchmarks for 2D and 3D puzzle solving. The fragments and fractures are realistic, caused by a collapse of a fresco during a World War II bombing at the Pompeii archaeological park. The fragments are also eroded and have missing pieces with irregular shapes and different dimensions, challenging further the reassembly algorithms. The dataset is multi-modal providing high resolution images with characteristic pictorial elements, detailed 3D scans of the fragments and meta-data annotated by the archaeologists. Ground truth has been generated through several years of unceasing fieldwork, including the excavation and cleaning of each fragment, followed by manual puzzle solving by archaeologists of a subset of approx. 1000 pieces among the 16000 available. After digitizing all the fragments in 3D, a benchmark was prepared to challenge current reassembly and puzzle-solving methods that often solve more simplistic synthetic scenarios. The tested baselines show that there clearly exists a gap to fill in solving this computationally complex problem., Comment: NeurIPS 2024, Track Datasets and Benchmarks, 10 pages
Published: 2024

13. A model for the emission line galaxy luminosity function and flux ratios at high-redshifts

Author: Pathak, Aadarsh, Wyithe, J. Stuart B., Sutherland, Ralph S., and Kewley, L. J
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: We present $[OIII]/H_{\rm \beta}$ emision line flux ratio predictions for galaxies at $z \sim 7-9$ using the MAPPINGS V v5.2.0 photoionization modelling code combined with an analytic galaxy formation model. Properties such as pressure and ionization parameter that determine emission line properties are thought to evolve towards high redshift. In order to determine the range of expected interstellar conditions we extend previous modelling of the Star Formation Rate Density (SFRD) function to calculate the metallicity and ionization parameter, and incorporate the potential impact of turbulence on the density of the ISM. To validate our emission line predictions we calculate the [OIII] line luminosity and its dependence on UV luminosity, as well as the flux ratio $[OIII]/H_{\rm \beta}$ and its variation with the line luminosity, finding that both reproduce recent JWST observations from the FRESCO survey. We also use our model to predict the number counts of emission line galaxies across a range of redshift as well as the dependence of $[OIII]/H_{\rm \beta}$ on ionization parameter and metallicity. Finally, we show that the dependence of flux ratio on luminosity may provide a diagnostic of turbulent motion in galactic discs., Comment: 12 pages, 17 figures, Submitted to MNRAS
Published: 2024

14. Velocity dispersion function evolution from strong lensing statistics

Author: Ferrami, Giovanni and Wyithe, J. Stuart B.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The redshift and size distributions of galaxy scale strong lenses depend on the evolution of early-type galaxies (ETGs) in the redshift range 0.2
Published: 2024

15. Peripheral brain interfacing: Reading high-frequency brain signals from the output of the nervous system

Author: Ibáñez, Jaime, Zicher, Blanka, Burdet, Etienne, Baker, Stuart N., Mehring, Carsten, and Farina, Dario
Subjects: Quantitative Biology - Neurons and Cognition
Abstract: Accurate and robust recording and decoding from the central nervous system (CNS) is essential for advances in human-machine interfacing. However, technologies used to directly measure CNS activity are limited by their resolution, sensitivity to interferences, and invasiveness. Advances in muscle recordings and deep learning allow us to decode the spiking activity of spinal motor neurons (MNs) in real time and with high accuracy. MNs represent the motor output layer of the CNS, receiving and sampling signals originating in different regions in the nervous system, and generating the neural commands that control muscles. The input signals to MNs can be estimated from the MN outputs. Here we argue that peripheral neural interfaces using muscle sensors represent a promising, non-invasive approach to estimate some neural activity from the CNS that reaches the MNs but does not directly modulate force production. We also discuss the evidence supporting this concept, and the necessary advances to consolidate and test MN-based CNS interfaces in controlled and real-world settings.
Published: 2024

16. Synthetic Light Curves and Spectra for the Photospheric Phase of a 3D Stripped-Envelope Supernova Explosion Model

Author: Maunder, Thomas, Callan, Fionntan P., Sim, Stuart A., Heger, Alexander, and Müller, Bernhard
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract: We present synthetic light curves and spectra from three-dimensional (3D) Monte Carlo radiative transfer simulations based on a 3D core-collapse supernova explosion model of an ultra-stripped $3.5\,\mathrm{M}_{\odot}$ progenitor. Our calculations predict a fast and faint transient with $\Delta m_{15} \sim 1\texttt{-} 2\,\mathrm{mag}$ and peak bolometric luminosity between $-15.3\,\mathrm{mag}$ and $-16.4\,\mathrm{mag}$. Due to a large-scale unipolar asymmetry in the distribution of $^{56}\mathrm{Ni}$, there is a pronounced viewing-angle dependence with about $1\,\mathrm{mag}$ difference between the directions of highest and lowest luminosity. The predicted spectra for this rare class of explosions do not yet match any observed counterpart. They are dominated by prominent Mg~II lines, but features from O, C, Si, and Ca are also found. In particular, the O~I line at \wl{7}{774} appears as a blended feature together with Mg~II emission. Our model is not only faster and fainter than the observed Ib/c supernova population, but also shows a correlation between higher peak luminosity and larger $\Delta m_{15}$ that is not present in observational samples. A possible explanation is that the unusually small ejecta mass of our model accentuates the viewing-angle dependence of the photometry. We suggest that the viewing-angle dependence of the photometry may be used to constrain asymmetries in explosion models of more typical stripped-envelope supernova progenitors in future., Comment: 13 pages, 18 figures, submitted to MNRAS
Published: 2024

17. SIROCCO: A Publicly Available Monte Carlo Ionization and Radiative Transfer Code for Astrophysical Outflows

Author: Matthews, James H., Long, Knox S., Knigge, Christian, Sim, Stuart A., Parkinson, Edward J., Higginbottom, Nick, Mangham, Samuel W., Scepi, Nicolas, Wallis, Austen, Hewitt, Henrietta A., and Mosallanezhad, Amin
Subjects: Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: Outflows are critical components of many astrophysical systems, including accreting compact binaries and active galactic nuclei (AGN). These outflows can significantly affect a system's evolution and alter its observational appearance by reprocessing the radiation produced by the central engine. Sirocco (Simulating Ionization and Radiation in Outflows Created by Compact Objects - or "the code formerly known as Python") is a Sobolev-based Monte Carlo ionization and radiative transfer code. It is designed to simulate the spectra produced by any system with an azimuthally-symmetric outflow, from spherical stellar winds to rotating, biconical accretion disc winds. Wind models can either be parametrized or imported, e.g. from hydrodynamical simulations. The radiation sources include an optically thick accretion disc and various central sources with flexible spectra and geometries. The code tracks the "photon packets" produced by the sources in any given simulation as they traverse and interact with the wind. The code assumes radiative near-equilibrium, so the thermal and ionization state can be determined iteratively from these interactions. Once the physical properties in the wind have converged, Sirocco can be used to generate synthetic spectra at a series of observer sightlines. Here, we describe the physical assumptions, operation, performance and limitations of the code. We validate it against tardis, cmfgen and cloudy, finding good agreement, and present illustrative synthetic spectra from disc winds in cataclysmic variables, tidal disruption events, AGN and X-ray binaries. Sirocco is publicly available on GitHub, alongside its associated data, documentation and sample input files covering a wide range of astrophysical applications., Comment: 26 pages, 16 figures. Submitted to MNRAS. This is the release paper for the SIROCCO code, which can be found at https://github.com/sirocco-rt/sirocco with links to documentation. Underlying data and figure scripts available at https://github.com/sirocco-rt/release-models -- comments on the code, paper or documentation are welcomed
Published: 2024

18. Crux, a Precise Verifier for Rust and Other Languages

Author: Pernsteiner, Stuart, Diatchki, Iavor S., Dockins, Robert, Dodds, Mike, Hendrix, Joe, Ravich, Tristan, Redmond, Patrick, Scott, Ryan, and Tomb, Aaron
Subjects: Computer Science - Programming Languages
Abstract: We present Crux, a cross-language verification tool for Rust and C/LLVM. Crux targets bounded, intricate pieces of code that are difficult for humans to get right: for example, cryptographic modules and serializer / deserializer pairs. Crux builds on the same framework as the mature SAW-Cryptol toolchain, but Crux provides an interface where proofs are phrased as symbolic unit tests. Crux is designed for use in production environments, and has already seen use in industry. In this paper, we focus on Crux-MIR, our verification tool for Rust. Crux-MIR provides a bit-precise model of safe and unsafe Rust which can be used to check both inline properties about Rust code, and extensional equality to executable specifications written in Cryptol or in the hacspec dialect of Rust. Notably, Crux-MIR supports compositional reasoning, which is necessary to scale to even moderately complex proofs. We demonstrate Crux-MIR by verifying the Ring library implementations of SHA1 and SHA2 against pre-existing functional specifications. Crux is available at https://crux.galois.com.
Published: 2024

19. Momentum-Resolved Fingerprint of Mottness in Layer-Dimerized Nb$_3$Br$_8$

Author: Date, Mihir, Petocchi, Francesco, Yen, Yun, Krieger, Jonas A., Pal, Banabir, Hasse, Vicky, McFarlane, Emily C., Körner, Chris, Yoon, Jiho, Watson, Matthew D., Strocov, Vladimir N., Xu, Yuanfeng, Kostanovski, Ilya, Ali, Mazhar N., Ju, Sailong, Plumb, Nicholas C., Sentef, Michael A., Woltersdorf, Georg, Schüler, Michael, Werner, Philipp, Felser, Claudia, Parkin, Stuart S. P., and Schröter, Niels B. M.
Subjects: Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science, Condensed Matter - Other Condensed Matter
Abstract: In a well-ordered crystalline solid, insulating behaviour can arise from two mechanisms: electrons can either scatter off a periodic potential, thus forming band gaps that can lead to a band insulator, or they localize due to strong interactions, resulting in a Mott insulator. For an even number of electrons per unit cell, either band- or Mott-insulators can theoretically occur. However, unambiguously identifying an unconventional Mott-insulator with an even number of electrons experimentally has remained a longstanding challenge due to the lack of a momentum-resolved fingerprint. This challenge has recently become pressing for the layer dimerized van der Waals compound Nb$_3$Br$_8$, which exhibits a puzzling magnetic field-free diode effect when used as a weak link in Josephson junctions, but has previously been considered to be a band-insulator. In this work, we present a unique momentum-resolved signature of a Mott-insulating phase in the spectral function of Nb$_3$Br$_8$: the top of the highest occupied band along the out-of-plane dimerization direction $k_z$ has a momentum space separation of $\Delta k_z=2\pi/d$, whereas the valence band maximum of a band insulator would be separated by less than $\Delta k_z=\pi/d$, where $d$ is the average spacing between the layers. As the strong electron correlations inherent in Mott insulators can lead to unconventional superconductivity, identifying Nb$_3$Br$_8$ as an unconventional Mott-insulator is crucial for understanding its apparent time-reversal symmetry breaking Josephson diode effect. Moreover, the momentum-resolved signature employed here could be used to detect quantum phase transition between band- and Mott-insulating phases in van der Waals heterostructures, where interlayer interactions and correlations can be easily tuned to drive such transition., Comment: 9 pages, 3 figures
Published: 2024

20. Nanothermodynamics: There's plenty of room on the inside

Author: Chamberlin, Ralph V. and Lindsay, Stuart M.
Subjects: Condensed Matter - Statistical Mechanics, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science, Physics - Biological Physics
Abstract: Nanothermodynamics provides the theoretical foundation for understanding stable distributions of statistically independent subsystems inside larger systems. In this review it is emphasized that adapting ideas from nanothermodynamics to simplistic models improves agreement with the measured properties of many materials. Examples include non-classical critical scaling near ferromagnetic transitions, thermal and dynamic behavior near liquid-glass transitions, and the 1/f-like noise in metal films and qubits. A key feature in several models is to allow separate time steps for distinct conservation laws: one type of step conserves energy and the other conserves momentum (e.g. dipole alignment). This "orthogonal dynamics" explains how the relaxation of a single parameter can exhibit multiple responses such as primary, secondary, and microscopic peaks in the dielectric loss of supercooled liquids, and the crossover in thermal fluctuations from Johnson-Nyquist (white) noise at high frequencies to 1/f-like noise at low frequencies. Nanothermodynamics also provides new insight into three basic questions. First, it gives a novel solution to Gibbs' paradox for the entropy of the semi-classical ideal gas. Second, it yields the stable equilibrium of Ising's original model for finite-sized chains of interacting binary degrees of freedom ("spins"). Third, it confronts Loschmidt's paradox for the arrow of time, showing that an intrinsically irreversible step is required for maximum entropy and the second law of thermodynamics, not only in the thermodynamic limit but also in systems as small as N=2 particles, Comment: 32 pages, 12 figures
Published: 2024

21. Algorithms and Sum-of-Squares Certificates for Qudit Hamiltonians Over Maximally Entangles States

Author: Jorquera, Zackary, Kolla, Alexandra, Kordonowy, Steven, Sandhu, Juspreet Singh, and Wayland, Stuart
Subjects: Quantum Physics
Abstract: We introduce the Maximal Entanglement problem, a 2-local qudit Hamiltonian that we view as a quantum generalization of Unique Games and which naturally encodes the frustration present in entanglement over multiple systems. We prove monogamy of entanglement bounds by certifying the ground state energy of the Maximal Entanglement problem in terms of the maximum matching of the underlying interaction graph via low-degree sum-of-squares proofs. Algorithmically, while a random assignment achieves energy of at least $1/d^2$ times the ground state energy, we show that a simple matching-based algorithm outputs a state with energy at least $1/d$ of the ground state energy for general graphs and at least $1/d + \Theta(1/D)$ for graphs with bounded degree, $D$. Moreover, we show that this state has energy at least $1/2$ of the ground state energy on $D$-regular graphs with degree, $D \leq 5$, for any local dimension, $d$., Comment: 12 + 8 pages
Published: 2024

22. Automated Segmentation and Analysis of Cone Photoreceptors in Multimodal Adaptive Optics Imaging

Author: Shrestha, Prajol, Kulyabin, Mikhail, Sindel, Aline, Pedersen, Hilde R., Gilson, Stuart, Baraas, Rigmor, and Maier, Andreas
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: Accurate detection and segmentation of cone cells in the retina are essential for diagnosing and managing retinal diseases. In this study, we used advanced imaging techniques, including confocal and non-confocal split detector images from adaptive optics scanning light ophthalmoscopy (AOSLO), to analyze photoreceptors for improved accuracy. Precise segmentation is crucial for understanding each cone cell's shape, area, and distribution. It helps to estimate the surrounding areas occupied by rods, which allows the calculation of the density of cone photoreceptors in the area of interest. In turn, density is critical for evaluating overall retinal health and functionality. We explored two U-Net-based segmentation models: StarDist for confocal and Cellpose for calculated modalities. Analyzing cone cells in images from two modalities and achieving consistent results demonstrates the study's reliability and potential for clinical application.
Published: 2024

23. Mining Asymmetric Intertextuality

Author: Lau, Pak Kin and McManus, Stuart Michael
Subjects: Computer Science - Information Retrieval
Abstract: This paper introduces a new task in Natural Language Processing (NLP) and Digital Humanities (DH): Mining Asymmetric Intertextuality. Asymmetric intertextuality refers to one-sided relationships between texts, where one text cites, quotes, or borrows from another without reciprocation. These relationships are common in literature and historical texts, where a later work references aclassical or older text that remain static. We propose a scalable and adaptive approach for mining asymmetric intertextuality, leveraging a split-normalize-merge paradigm. In this approach, documents are split into smaller chunks, normalized into structured data using LLM-assisted metadata extraction, and merged during querying to detect both explicit and implicit intertextual relationships. Our system handles intertextuality at various levels, from direct quotations to paraphrasing and cross-document influence, using a combination of metadata filtering, vector similarity search, and LLM-based verification. This method is particularly well-suited for dynamically growing corpora, such as expanding literary archives or historical databases. By enabling the continuous integration of new documents, the system can scale efficiently, making it highly valuable for digital humanities practitioners in literacy studies, historical research and related fields.
Published: 2024

24. Small-dimensional normed barrelled spaces

Author: Brian, Will and Stuart, Christopher
Subjects: Mathematics - Functional Analysis, Mathematics - Logic
Abstract: We prove that there is a normed barrelled space with dimension $\mathrm{non}(\mathcal M)$, which denotes the smallest cardinality of a non-meager subset of $\mathbb R$. Consequently, it is consistent with $\mathsf{ZFC}$ that there is a normed barrelled space with dimension $<\!\mathfrak{c}$. This answers a question of S\'anchez Ruiz and Saxon. This is a special case of a more general theorem: for every infinite cardinal $\kappa$, every Banach space with density character $\kappa$ contains a barrelled subspace with dimension $\mathrm{cf}[\kappa]^\omega \cdot \mathrm{non}(\mathcal M)$. We also prove that if the dual of a Banach space does not contain $c_0$ or $\ell^p$ for any $p \geq 1$, then that spaces does not have a barrelled subspaces with dimension $<\!\mathrm{cov}(\mathcal N)$, which denotes the smallest cardinality of a collection of Lebesgue null sets covering $\mathbb R$. In particular, it is consistent with $\mathsf{ZFC}$ that no classical Banach spaces contain barrelled subspaces with dimension $\mathfrak{b}$. This partly answers another question of S\'anchez Ruiz and Saxon.
Published: 2024

25. Optomechanical self-organization in a mesoscopic atom array

Author: Ho, Jacquelyn, Lu, Yue-Hui, Xiang, Tai, Rusconi, Cosimo C., Masson, Stuart J., Asenjo-Garcia, Ana, Yan, Zhenjie, and Stamper-Kurn, Dan M.
Subjects: Quantum Physics, Condensed Matter - Quantum Gases, Physics - Atomic Physics
Abstract: A fundamental challenge in modern physics is bridging the gap between an exact description of few-body microscopic systems and the emergent description of many-body macroscopic systems. This gap may be bridged by tracing the properties of well-controlled intermediate-size mesoscopic systems. Here, we study mesoscopic signatures of a spatial self-organization phase transition in deterministically prepared arrays of between 10 and 22 atoms inside an optical cavity. Through precise engineering of the atom-cavity interactions, we reveal how critical behavior depends on atom number. We identify characteristic dynamical behaviors related to symmetry breaking and system size in the self-organized regime, and observe a finite optomechanical susceptibility at the critical point. This work opens the door to probing particle-number- and time-resolved properties of phase transitions in mesoscopic systems., Comment: 21 pages, 9 figures
Published: 2024

26. Sparse flow reconstruction methods to reduce the costs of analyzing large unsteady datasets

Author: Stahl, Spencer L. and Benton, Stuart I.
Subjects: Physics - Data Analysis, Statistics and Probability
Abstract: The cost of writing, transferring, and storing large data from unsteady simulations limits access to the entire solution, often leaving much of the flow under-sampled or unanalyzed. For example, modeling transient behavior of rare dynamic events requires 3D snapshots at high sampling rates over long periods, generating significant amounts of data and creating challenges for practical CFD workflows, especially with limited memory resources and costly GPU writing penalties. In this work, multiple sparse flow reconstruction (SFR) methods are developed to approximate a full unsteady solution using far fewer sparse measurements, thus reducing writing costs, data storage, and enabling higher sampling rates. SFR is motivated by a large-eddy simulation of rare inlet distortion events, demonstrating that down-sampling full snapshots and supplementing them with high-frequency sparse measurements can drastically cut writing time for GPU solvers and nearly eliminate this cost for CPU solvers. The simplest single-equation "snapshot" SFR method can be compressed further using Proper Orthogonal Decomposition (POD-SFR) or a more efficient double POD-SFR variant. A streaming SFR modification improves reconstruction efficiency when local memory is limited. A sensitivity study evaluates trade-offs between sparse sampling rates and reconstruction accuracy, offering best practices. To offset error of using random sparse measurements, SFR exactly preserves dynamics in key regions by prescribing sparse measurement locations, used here to capture distortion events. Distortion events are evaluated using the conditional space-time proper orthogonal decomposition (CST-POD) to pursue physical insights that characterize the upstream causality at full resolution. A validation study of CST-POD modes confirms SFR effectiveness at retaining the event dynamics with substantial computational and memory savings., Comment: 29 pages, 15 figures
Published: 2024

27. Inverse Problems and Data Assimilation: A Machine Learning Approach

Author: Bach, Eviatar, Baptista, Ricardo, Sanz-Alonso, Daniel, and Stuart, Andrew
Subjects: Statistics - Machine Learning, Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract: The aim of these notes is to demonstrate the potential for ideas in machine learning to impact on the fields of inverse problems and data assimilation. The perspective is one that is primarily aimed at researchers from inverse problems and/or data assimilation who wish to see a mathematical presentation of machine learning as it pertains to their fields. As a by-product, we include a succinct mathematical treatment of various topics in machine learning., Comment: 254 pages
Published: 2024

28. Starshade Exoplanet Data Challenge: What We Learned

Author: Damiano, Mario, Shaklan, Stuart, Hu, Renyu, Dunne, Brian, Tanner, Angelle, Nida, Aly, Carson, Joseph C., Hildebrandt, Sergi R., and Lisman, Doug
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: Starshade is one of the technologies that will enable the observation and characterization of small planets around nearby stars through direct imaging. The Starshade Exoplanetary Data Challenge (SEDC) was designed to validate starshade-imaging's noise budget and evaluate the capabilities of image-processing techniques, by inviting community participating teams to analyze >1000 simulated images of hypothetical exoplanetary systems observed through a starshade. Because the starshade would suppress the starlight so well, the dominant noise source and the main challenge for the planet detection becomes the exozodiacal disks and their structures. In this paper, we summarize the techniques used by the participating teams and compare their findings with the truth. With an independent component analysis to remove the background, about 70% of the inner planets (close to the inner working angle) have been detected and ~40% of the outer planet (fainter than the inner counterparts) have been identified. Planet detection becomes more difficult in the cases of higher disk inclination, as the false negative and false positive counts increase. Interestingly, we found little difference in the planet detection ability between 1e-10 and 1e-9 instrument contrast, confirming that the dominant limitations are from the astrophysical background and not due to the performance of the starshade. Finally, we find that a non-parametric background calibration scheme, such as the independent component analysis reported here, results in a mean residual of 10% the background brightness. This background estimation error leads to substantial false positives and negatives and systematic bias in the planet flux estimation, and should be included in the estimation of the planet detection signal-to-noise ratio for imaging using a starshade and also a coronagraph that delivers exozodi-limited imaging., Comment: Accepted for publication in Journal of Astronomical Telescopes, Instruments, and Systems
Published: 2024

29. Aperiodic Flows on Finite Semigroups: Foundations and First Examples

Author: Margolis, Stuart and Rhodes, John
Subjects: Mathematics - Dynamical Systems, Mathematics - Group Theory, 20M20, 20M35, 20M18
Abstract: The theory of flows was used as a crucial tool in the recent proof by Margolis, Rhodes and Schilling that Krohn-Rhodes complexity is decidable. In this paper we begin a systematic study of aperiodic flows. We give the foundations of the theory of flows and give a unified approach to the Presentation Lemma and its relations to flows and the Slice Theorem. We completely describe semigroups having a flow over the trivial semigroup and connect this to classical results in inverse semigroup theory. We reinterpret Tilson's Theorem on the complexity of small monoids in terms of flows. We conclude with examples of semigroups built from the character table of Abelian Groups that have an aperiodic flows.
Published: 2024

30. WorkflowHub: a registry for computational workflows

Author: Gustafsson, Ove Johan Ragnar, Wilkinson, Sean R., Bacall, Finn, Pireddu, Luca, Soiland-Reyes, Stian, Leo, Simone, Owen, Stuart, Juty, Nick, Fernández, José M., Grüning, Björn, Brown, Tom, Ménager, Hervé, Capella-Gutierrez, Salvador, Coppens, Frederik, and Goble, Carole
Subjects: Computer Science - Digital Libraries, Computer Science - Software Engineering
Abstract: The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 700 workflows registered., Comment: 30 pages, 4 figures
Published: 2024

31. Trajectory Improvement and Reward Learning from Comparative Language Feedback

Author: Yang, Zhaojing, Jun, Miru, Tien, Jeremy, Russell, Stuart J., Dragan, Anca, and Bıyık, Erdem
Subjects: Computer Science - Robotics
Abstract: Learning from human feedback has gained traction in fields like robotics and natural language processing in recent years. While prior works mostly rely on human feedback in the form of comparisons, language is a preferable modality that provides more informative insights into user preferences. In this work, we aim to incorporate comparative language feedback to iteratively improve robot trajectories and to learn reward functions that encode human preferences. To achieve this goal, we learn a shared latent space that integrates trajectory data and language feedback, and subsequently leverage the learned latent space to improve trajectories and learn human preferences. To the best of our knowledge, we are the first to incorporate comparative language feedback into reward learning. Our simulation experiments demonstrate the effectiveness of the learned latent space and the success of our learning algorithms. We also conduct human subject studies that show our reward learning algorithm achieves a 23.9% higher subjective score on average and is 11.3% more time-efficient compared to preference-based reward learning, underscoring the superior performance of our method. Our website is at https://liralab.usc.edu/comparative-language-feedback/, Comment: 8th Annual Conference of Robot Learning (2024)
Published: 2024

32. RL, but don't do anything I wouldn't do

Author: Cohen, Michael K., Hutter, Marcus, Bengio, Yoshua, and Russell, Stuart
Subjects: Computer Science - Machine Learning
Abstract: In reinforcement learning, if the agent's reward differs from the designers' true utility, even only rarely, the state distribution resulting from the agent's policy can be very bad, in theory and in practice. When RL policies would devolve into undesired behavior, a common countermeasure is KL regularization to a trusted policy ("Don't do anything I wouldn't do"). All current cutting-edge language models are RL agents that are KL-regularized to a "base policy" that is purely predictive. Unfortunately, we demonstrate that when this base policy is a Bayesian predictive model of a trusted policy, the KL constraint is no longer reliable for controlling the behavior of an advanced RL agent. We demonstrate this theoretically using algorithmic information theory, and while systems today are too weak to exhibit this theorized failure precisely, we RL-finetune a language model and find evidence that our formal results are plausibly relevant in practice. We also propose a theoretical alternative that avoids this problem by replacing the "Don't do anything I wouldn't do" principle with "Don't do anything I mightn't do"., Comment: 10 pages, 7 page appendix, 4 figures
Published: 2024

33. Collisional and Radiative Data for Tellurium ions in Kilonovae modelling and Laboratory Benchmarks

Author: Mulholland, Leo Patrick, McNeill, Fiona, Sim, Stuart A., Ballance, Connor P., and Ramsbottom, Catherine A.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Physics - Atomic Physics
Abstract: Tellurium is a primary candidate for the identification of the 2.1 $\mu$m emission line in kilonovae (KNe) spectra AT2017gfo and GRB230307A. Despite this, there is currently an insufficient amount of atomic data available for this species. We calculate the required atomic structure and collisional data, particularly the data required for accurate Non-Local-Thermodynamic-Equilibrium (NLTE) modelling of the low temperatures and densities in KNe. We use a Multi-Configurational-Dirac-Hartree-Fock method to produce optimised one-electron orbitals for Te {\sc i}-{\sc iii}. As a result energy levels and Einstein A-coefficients for Te {\sc i}-{\sc iii} have been calculated. These orbitals are then employed within Dirac $R$-matrix collision calculations to provide electron-impact-excitation collision strengths that were subsequently averaged according to a thermal Maxwellian distribution. Subsequent \textsc{tardis} simulations using this new atomic data reveal no significant changes to the synthetic spectra due to the very minor contribution of Te at early epochs. NLTE simulations with the ColRadPy package reveal optically thin spectra consistent with the increasing prominence of the Te {\sc iii} 2.1 $\mu$m line as the KNe ejecta cools. This is reinforced by the estimation of luminosities at nebular KNe conditions. New line ratios for both observation and laboratory benchmarks of the atomic data are proposed., Comment: Accepted Manuscript
Published: 2024

34. Deterministic generation of photonic entangled states using decoherence-free subspaces

Author: Rubies-Bigorda, Oriol, Masson, Stuart J., Yelin, Susanne F., and Asenjo-Garcia, Ana
Subjects: Quantum Physics
Abstract: We propose the use of collective states of matter as a resource for the deterministic generation of quantum states of light, which are fundamental for quantum information technologies. Our minimal model consists of three emitters coupled to a half-waveguide, i.e., a one-dimensional waveguide terminated by a mirror. Photon-mediated interactions between the emitters result in the emergence of bright and dark states. The dark states form a decoherence-free subspace, protected from dissipation. Local driving of the emitters and control of their resonance frequencies allows to perform arbitrary quantum gates within the decoherence-free subspace. Coupling to bright states facilitates photon emission, thereby enabling the realization of quantum gates between light and matter. We demonstrate that sequential application of these gates leads to the generation of photonic entangled states, such as Greenberger-Horne-Zeilinger and one- and two-dimensional cluster states.
Published: 2024

35. How Meteor Showers Can Guide the Search for Long Period Comets

Author: Hemmelgarn, Samantha, Moskovitz, Nicholas, Pilorz, Stuart, and Jenniskens, Peter
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: With orbital periods longer than 200 years, most long-period comets (LPCs) remain undiscovered until they are in-bound towards perihelion. The comets that pass close to Earth's orbit are Potentially Hazardous Objects (PHOs). Those with orbital periods up to ~4000 years tend to have passed close to Earth's orbit in a previous orbit and produced a meteoroid stream dense enough to be detected at Earth as a meteor shower. In anticipation of Rubin Observatory's Legacy Survey of Space and Time (LSST), we investigate how these meteor showers can guide dedicated searches for their parent comets. Assuming search parameters informed by LSST, we calculated where the 17 known parent bodies of long-period comet meteor showers would have been discovered based on a cloud of synthetic comets generated from the shower properties as measured at Earth. We find that the synthetic comets predict the on-sky location of the parent comets at the time of their discovery. The parent comet's location on average would have been 1.51 $\pm$1.19$\deg$ from a line fit through the synthetic comet cloud. The difference between the heliocentric distance of the parent and mean heliocentric distance of synthetic comets on the line was 2.09 $\pm$1.89 au for comets with unknown absolute nuclear magnitudes and 0.96 $\pm$0.80 au for comets with known absolute nuclear magnitudes. We applied this method to the $\sigma$-Hydrids, the proposed meteor shower of Comet Nishimura, and found that it successfully matched the pre-covery location of this comet 8 months prior to Nishimura's discovery., Comment: 17 pages, 11 figures, Accepted for publication in Planetary Science Journal
Published: 2024

36. Late-Time Supernovae Radio Re-brightening in the VAST Pilot Survey

Author: Rose, Kovi, Horesh, Assaf, Murphy, Tara, Kaplan, David L., Sfaradi, Itai, Ryder, Stuart D., Aloisi, Robert J., Dobie, Dougal, Driessen, Laura, Fender, Rob, Green, David A., Leung, James K., Lenc, Emil, Qiu, Hao, and Williams-Baldwin, David
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: We present our analysis of supernovae serendipitously found to be radio-bright several years after their optical discovery. We used recent observations from the Australian SKA Pathfinder taken as part of the pilot Variables and Slow Transients and Rapid ASKAP Continuum Survey programs. We identified 29 objects by cross-matching sources from these ASKAP observations with known core-collapse supernovae below a declination of $+40^{\circ}$ and with a redshift of $z\leq0.15$. Our results focus on eight cases that show potential late-time radio emission. These supernovae exhibit significantly greater amounts of radio emission than expected from the standard model of a single shockwave propagating through a spherical circumstellar medium, with a constant density structure produced by regular stellar mass-loss. We also discuss how we can learn from future ASKAP surveys about the circumstellar environments and emission mechanisms of supernovae that undergo late-time radio re-brightening. This pilot work tested and confirmed the potential of the Variables and Slow Transients survey to discover and study late-time supernova emission., Comment: Accepted for publication in MNRAS
Published: 2024

37. ReXplain: Translating Radiology into Patient-Friendly Video Reports

Author: Luo, Luyang, Vairavamurthy, Jenanan, Zhang, Xiaoman, Kumar, Abhinav, Ter-Oganesyan, Ramon R., Schroff, Stuart T., Shilo, Dan, Hossain, Rydhwana, Moritz, Mike, and Rajpurkar, Pranav
Subjects: Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: Radiology reports often remain incomprehensible to patients, undermining patient-centered care. We present ReXplain (Radiology eXplanation), an innovative AI-driven system that generates patient-friendly video reports for radiology findings. ReXplain uniquely integrates a large language model for text simplification, an image segmentation model for anatomical region identification, and an avatar generation tool, producing comprehensive explanations with plain language, highlighted imagery, and 3D organ renderings. Our proof-of-concept study with five board-certified radiologists indicates that ReXplain could accurately deliver radiological information and effectively simulate one-on-one consultations. This work demonstrates a new paradigm in AI-assisted medical communication, potentially improving patient engagement and satisfaction in radiology care, and opens new avenues for research in multimodal medical communication., Comment: 13 pages
Published: 2024

38. The Einstein Probe transient EP240414a: Linking Fast X-ray Transients, Gamma-ray Bursts and Luminous Fast Blue Optical Transients

Author: van Dalen, Joyce N. D., Levan, Andrew J., Jonker, Peter G., Malesani, Daniele B., Izzo, Luca, Sarin, Nikhil, Quirola-Vásquez, Jonathan, Sánchez, Daniel Mata, Postigo, Antonio de Ugarte, van Hoof, Agnes P. C., Torres, Manuel A. P., Schulze, Steve, Littlefair, Stuart P., Chrimes, Ashley, Ravasio, Maria E., Bauer, Franz E., Martin-Carrillo, Antonio, Fraser, Morgan, van der Horst, Alexander J., Jakobsson, Pall, O'Brien, Paul, De Pasquale, Massimiliano, Pugliese, Giovanna, Sollerman, Jesper, Tanvir, Nial R., Zafar, Tayyaba, Anderson, Joseph P., Galbany, Lluís, Gal-Yam, Avishay, Gromadzki, Mariusz, Muller-Bravo, Tomas E., Ragosta, Fabio, and Terwel, Jacco H.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Detections of fast X-ray transients (FXTs) have been accrued over the last few decades. However, their origin has remained mysterious. There is now rapid progress thanks to timely discoveries and localisations with the Einstein Probe mission. Early results indicate that FXTs may frequently, but not always, be associated with gamma-ray bursts (GRBs). Here, we report on the multi-wavelength counterpart of FXT EP240414a, which has no reported gamma-ray counterpart. The transient is located 25.7~kpc in projection from a massive galaxy at $z=0.40$. We perform comprehensive photometric and spectroscopic follow-up. The optical light curve shows at least three distinct emission episodes with timescales of $\sim 1, 4$ and 15 days and peak absolute magnitudes of $M_R \sim -20$, $-21$, and $-19.5$, respectively. The optical spectrum at early times is extremely blue, inconsistent with afterglow emission. It may arise from the interaction of both jet and supernova shock waves with the stellar envelope and a dense circumstellar medium, as has been suggested for some Fast Blue Optical Transients (LFBOTs). At late times, the spectrum evolves to a broad-lined~Type~Ic supernova, similar to those seen in collapsar long-GRBs. This implies that the progenitor of EP240414a is a massive star creating a jet-forming supernova inside a dense envelope, resulting in an X-ray outburst with a luminosity of $\sim 10^{48}$ erg s$^{-1}$, and the complex observed optical/IR light curves. If correct, this argues for a causal link between the progenitors of long-GRBs, FXTs and LFBOTs., Comment: 36 pages, 13 figures, submitted to ApJ
Published: 2024

39. ReviveDiff: A Universal Diffusion Model for Restoring Images in Adverse Weather Conditions

Author: Huang, Wenfeng, Xu, Guoan, Jia, Wenjing, Perry, Stuart, and Gao, Guangwei
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Images captured in challenging environments--such as nighttime, foggy, rainy weather, and underwater--often suffer from significant degradation, resulting in a substantial loss of visual quality. Effective restoration of these degraded images is critical for the subsequent vision tasks. While many existing approaches have successfully incorporated specific priors for individual tasks, these tailored solutions limit their applicability to other degradations. In this work, we propose a universal network architecture, dubbed "ReviveDiff", which can address a wide range of degradations and bring images back to life by enhancing and restoring their quality. Our approach is inspired by the observation that, unlike degradation caused by movement or electronic issues, quality degradation under adverse conditions primarily stems from natural media (such as fog, water, and low luminance), which generally preserves the original structures of objects. To restore the quality of such images, we leveraged the latest advancements in diffusion models and developed ReviveDiff to restore image quality from both macro and micro levels across some key factors determining image quality, such as sharpness, distortion, noise level, dynamic range, and color accuracy. We rigorously evaluated ReviveDiff on seven benchmark datasets covering five types of degrading conditions: Rainy, Underwater, Low-light, Smoke, and Nighttime Hazy. Our experimental results demonstrate that ReviveDiff outperforms the state-of-the-art methods both quantitatively and visually.
Published: 2024

40. The hypothetical track-length fitting algorithm for energy measurement in liquid argon TPCs

Author: DUNE Collaboration, Abud, A. Abed, Abi, B., Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Alex, N. S., Allison, K., Monsalve, S. Alonso, Alrashed, M., Alton, A., Alvarez, R., Alves, T., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anfimov, N., Ankowski, A., Antic, D., Antoniassi, M., Antonova, M., Antoshkin, A., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Balashov, N., Balasubramanian, S., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Benekos, N., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bevan, A., Bezawada, Y., Bezerra, A. T., Bezerra, T. J., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Bitadze, A., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bodek, A., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Bonini, F., Booth, A., Boran, F., Bordoni, S., Merlo, R. Borges, Borkum, A., Bostan, N., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cagnoli, I., Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chakraborty, K., Chalifour, M., Chappell, A., Charitonidis, N., Chatterjee, A., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen-Wishart, Z., Cherdack, D., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Choi, G., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chukanov, A., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Coan, T. E., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conley, E., Conrad, J. M., Convery, M., Copello, S., Cova, P., Cox, C., Cremaldi, L., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallavalle, R., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., De Bonis, I., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., Astiz, I. L. De Icaza, De Jong, P., Sanchez, P. Del Amo, De la Torre, A., De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Doering, D., Dolan, S., Dolek, F., Dolinski, M. J., Domenici, D., Domine, L., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Dragone, A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Fajt, L., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Fedoseev, D., Felix, J., Feng, Y., Fernandez-Martinez, E., Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fine, R., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M., Galizzi, F., Gallagher, H., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Ganacim, F., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauvreau, J., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghorbani-Moghaddam, Z., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Girerd, C., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonnella, F., Gonzalez-Diaz, D., Gonzalez-Lopez, M., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Groetschla, F. T., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, F. Y., Gupta, A., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Hadavand, H., Haegel, L., Haenni, R., Hagaman, L., Hahn, A., Haiston, J., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Happacher, F., Harris, D. A., Hart, A. L., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C. M., Hatcher, R., Hayrapetyan, K., Hays, J., Hazen, E., He, M., Heavey, A., Heeger, K. M., Heise, J., Hellmuth, P., Henry, S., Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Hillier, S. J., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Hoff, J., Holin, A., Holvey, T., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Hulcher, Z., Ibrahim, M., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Isenhower, L., Oliveira, M. Ismerio, Itay, R., Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jiang, L., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jollet, C., Jones, B., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Jung, K. Y., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kakorin, I., Kalitkina, A., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasai, S., Kasetti, S. P., Kashur, L., Katsioulas, I., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khabibullin, M., Khan, N., Khvedelidze, A., Kim, D., Kim, J., Kim, M. J., King, B., Kirby, B., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kolupaeva, L., Korablev, D., Kordosky, M., Kosc, T., Kose, U., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Kozhukalov, V., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kreslo, I., Kroupova, T., Kubota, S., Kubu, M., Kudenko, Y., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kulagin, S., Kumar, J., Kumar, P., Kumaran, S., Kunzmann, J., Kuravi, R., Kurita, N., Kuruppu, C., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lalău, I., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Lantwin, O., Larkin, J., Lasorak, P., Last, D., Laudrain, A., Laundrie, A., Laurenti, G., Lavaut, E., Laycock, P., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Legin, V., Miotto, G. Lehmann, Lehnert, R., de Oliveira, M. A. Leigui, Leitner, M., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lokajicek, M., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., Lord, T., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Lunday, B., Luo, X., Luppi, E., MacFarlane, D., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Maddalena, A., Madera, A., Madigan, P., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Mameli, S., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Massari, C., Mastbaum, A., Matichard, F., Matsuno, S., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mazza, R., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., Meazza, L., Meddage, V. C. N., Mefodiev, A., Mehta, B., Mehta, P., Melas, P., Mena, O., Mendez, H., Mendez, P., Méndez, D. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Micallef, J., Miccoli, A., Michna, G., Milincic, R., Miller, F., Miller, G., Miller, W., Mineev, O., Minotti, A., Miralles, L., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, P., Mishra, S. R., Mislivec, A., Mitchell, M., Mladenov, D., Mocioiu, I., Mogan, A., Moggi, N., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, Z., Moreno, D., Moreno-Palacios, O., Morescalchi, L., Moretti, D., Moretti, R., Morris, C., Mossey, C., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mukhamejanov, Y., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Nandakumar, R., Naples, D., Narita, S., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, A., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olshevskiy, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, O'Sullivan, L., Ormachea, L. Otiniano, Ott, J., Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panda, P., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papaleo, R., Papanestis, A., Papoulias, D., Paramesvaran, S., Paris, A., Parke, S., Parozzi, E., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Perez, A. Pena, Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pincha, S., Pinchault, J., Pitts, K., Plows, K., Pollack, C., Pollman, T., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Paixão, L. G. Porto, Potekhin, M., Potenza, R., Pozzato, M., Prakash, T., Pratt, C., Prest, M., Psihas, F., Pugnere, D., Qian, X., Queen, J., Raaf, J. L., Radeka, V., Rademacker, J., Radics, B., Raffaelli, F., Rafique, A., Raguzin, E., Rahaman, U., Rai, M., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Rappoldi, A., Raselli, G., Ratoff, P., Ray, R., Razafinime, H., Razakamiandra, R. F., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reichenbacher, J., Reitzner, S. D., Sfar, H. Rejeb, Renner, E., Renshaw, A., Rescia, S., Resnati, F., Restrepo, Diego, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Rivera, R., Robert, A., Rocha, J. L. Rocabado, Rochester, L., Roda, M., Rodrigues, P., Alonso, M. J. Rodriguez, Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Ross-Lonergan, M., Roy, N., Roy, P., Rubbia, C., Ruggeri, A., Ferreira, G. Ruiz, Russell, B., Ruterbories, D., Rybnikov, A., Sacerdoti, S., Saha, S., Sahoo, S. K., Sahu, N., Sala, P., Samios, N., Samoylov, O., Sanchez, M. C., Bravo, A. Sánchez, Sánchez-Castillo, A., Sanchez-Lucas, P., Sandberg, V., Sanders, D. A., Sanfilippo, S., Sankey, D., Santoro, D., Saoulidou, N., Sapienza, P., Sarasty, C., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Segade, A., Segreto, E., Selyunin, A., Senadheera, D., Senise, C. R., Sensenig, J., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Poudel, S. Sharma, Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Sheshukov, A., Shi, J., Shi, W., Shin, S., Shivakoti, S., Shoemaker, I., Shooltz, D., Shrock, R., Siddi, B., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, E., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Snowden-Ifft, D., Nunes, M. Soares, Sobel, H., Soderberg, M., Sokolov, S., Salinas, C. J. Solano, Söldner-Rembold, S., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Sotnikov, A., Soto-Oton, J., Sousa, A., Soustruznik, K., Spinella, F., Spitz, J., Spooner, N. J. C., Spurgeon, K., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stepanova, A., Stewart, J., Stillwell, B., Stock, J., Stocker, F., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutera, C. M., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Oregui, B. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thomas, S., Thompson, A., Thorn, C., Timm, S. C., Tiras, E., Tishchenko, V., Tiwari, S., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Torti, M., Tortola, M., Tortorici, F., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turnberg, S., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valder, S., Valdiviesso, G. A., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Van de Water, R. G., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Oliva, D. Vargas, Vasina, S., Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Vizarreta, R., Hernandez, A. P. Vizcaya, Vuong, Q., Waldron, A. V., Wallbank, M., Walsh, J., Walton, T., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Westerdale, S., Wetstein, M., Whalen, K., White, A., Whitehead, L. H., Whittington, D., Wilhlemi, J., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wisniewski, W., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wospakrik, M., Wresilo, K., Wret, C., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, J., Yang, K., Yang, T., Yankelevich, A., Yershov, N., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.
Subjects: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract: This paper introduces the hypothetical track-length fitting algorithm, a novel method for measuring the kinetic energies of ionizing particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.
Published: 2024

41. Switching of magnetic domains in a noncollinear antiferromagnet at the nanoscale

Author: Pandey, Atul, Rigvedi, Prajwal, Lesne, Edouard, Deka, Jitul, Yoon, Jiho, Hoppe, Wolfgang, Koerner, Chris, Pal, Banabir, Taylor, James M., Parkin, Stuart S. P., and Woltersdorf, Georg
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract: Antiferromagnets that display very small stray magnetic field are ideal for spintronic applications. Of particular interest are non-collinear, chiral antiferromagnets of the type Mn3X (X=Sn, Ge), which display a large magnetotransport response that is correlated with their antiferromagnetic ordering. The ability to read out and manipulate this ordering is crucial for their integration into spintronic devices. These materials exhibit a tiny unbalanced magnetic moment such that a large external magnetic field can, in principle, be used to set the material into a single antiferromagnetic domain. However, in thin films of Mn3Sn, we find that such fields induce only a partial magnetic ordering. By detecting two orthogonal in-plane components of the magnetic order vector, we find that the non-switchable fraction has a unidirectional anisotropy. This also enables us to visualize switching along multiple easy axes in Mn3Sn. Studying the switching at the nanoscale allows us to correlate the pining behavior to crystal grain boundaries in the Mn3Sn nanowire structures.
Published: 2024

42. FOCQS: Feedback Optimally Controlled Quantum States

Author: Brady, Lucas T. and Hadfield, Stuart
Subjects: Quantum Physics
Abstract: Quantum optimization, both for classical and quantum functions, is one of the most well-studied applications of quantum computing, but recent trends have relied on hybrid methods that push much of the fine-tuning off onto costly classical algorithms. Feedback-based quantum algorithms, such as FALQON, avoid these fine-tuning problems but at the cost of additional circuit depth and a lack of convergence guarantees. In this work, we take the local greedy information collected by Lyapunov feedback control and develop an analytic framework to use it to perturbatively update previous control layers, similar to the global optimal control achievable using Pontryagin optimal control. This perturbative methodology, which we call Feedback Optimally Controlled Quantum States (FOCQS), can be used to improve the results of feedback-based algorithms, like FALQON. Furthermore, this perturbative method can be used to push smooth annealing-like control protocol closer to the control optimum, even providing and iterative approach, albeit with diminishing returns. In numerical testing, we show improvements in convergence and required depth due to these methods over existing quantum feedback control methods., Comment: 13 pages, 3 figures
Published: 2024

43. Asking an AI for salary negotiation advice is a matter of concern: Controlled experimental perturbation of ChatGPT for protected and non-protected group discrimination on a contextual task with no clear ground truth answers

Author: Geiger, R. Stuart, O'Sullivan, Flynn, Wang, Elsie, and Lo, Jonathan
Subjects: Computer Science - Computers and Society, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract: We conducted controlled experimental bias audits for four versions of ChatGPT, which we asked to recommend an opening offer in salary negotiations for a new hire. We submitted 98,800 prompts to each version, systematically varying the employee's gender, university, and major, and tested prompts in voice of each side of the negotiation: the employee versus employer. We find ChatGPT as a multi-model platform is not robust and consistent enough to be trusted for such a task. We observed statistically significant salary offers when varying gender for all four models, although with smaller gaps than for other attributes tested. The largest gaps were different model versions and between the employee- vs employer-voiced prompts. We also observed substantial gaps when varying university and major, but many of the biases were not consistent across model versions. We tested for fictional and fraudulent universities and found wildly inconsistent results across cases and model versions. We make broader contributions to the AI/ML fairness literature. Our scenario and our experimental design differ from mainstream AI/ML auditing efforts in key ways. Bias audits typically test discrimination for protected classes like gender, which we contrast with testing non-protected classes of university and major. Asking for negotiation advice includes how aggressive one ought to be in a negotiation relative to known empirical salary distributions and scales, which is a deeply contextual and personalized task that has no objective ground truth to validate. These results raise concerns for the specific model versions we tested and ChatGPT as a multi-model platform in continuous development. Our epistemology does not permit us to definitively certify these models as either generally biased or unbiased on the attributes we test, but our study raises matters of concern for stakeholders to further investigate.
Published: 2024

44. Nuclear dimension of extensions of commutative C*-algebras by Kirchberg algebras

Author: Evington, Samuel, Ng, Abraham C. S., Sims, Aidan, and White, Stuart
Subjects: Mathematics - Operator Algebras, 46L05, 46L35
Abstract: We compute the nuclear dimension of extensions of C*-algebras involving commutative unital quotients and stable Kirchberg ideals. We identify the finite directed graphs whose C*-algebras are covered by this theorem., Comment: 30 pages
Published: 2024

45. Progress towards efficient 4-level photon echo memories

Author: Stuart, James, Smith, Kieran, Hedges, Morgan, Ahlefeldt, Rose, and Sellars, Matthew
Subjects: Quantum Physics
Abstract: Quantum memories could benefit many devices in quantum information processing. For a quantum to be useful in real-world applications, the quantum memory must have a high recall efficiency. Here we demonstrate an efficient (up to 80%) spin-storage quantum memory in Er:YSO, using the 4-level rephased amplified spontaneous emission protocol. We show non-classical correlations between the ASE and RASE fields produced by the quantum memory. Also, we demonstrate the storage of 70 temporal modes, with a write time of 150 us, and a storage time of 25 us. Finally, a clear pathway is presented to improve the efficiency, storage time, and mode capacity. Such a device would have applications in quantum networking and measurement-based quantum computing., Comment: 9 pages, 10 figures
Published: 2024

46. Nonlocal phase-change metaoptics for reconfigurable nonvolatile image processing

Author: Yang, Guoce, Wang, Mengyun, Lee, June Sang, Farmakidis, Nikolaos, Shields, Joe, de Galarreta, Carlota Ruiz, Kendall, Stuart, Bertolotti, Jacopo, Moskalenko, Andriy, Huang, Kairan, Alù, Andrea, Wright, C. David, and Bhaskaran, Harish
Subjects: Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Applied Physics
Abstract: The next generation of smart imaging and vision systems will require compact and tunable optical computing hardware to perform high-speed and low-power image processing. These requirements are driving the development of computing metasurfaces to realize efficient front-end analog optical pre-processors, especially for edge-detection capability. Yet, there is still a lack of reconfigurable or programmable schemes, which may drastically enhance the impact of these devices at the system level. Here, we propose and experimentally demonstrate a reconfigurable flat optical image processor using low-loss phase-change nonlocal metasurfaces. The metasurface is configured to realize different transfer functions in spatial frequency space, when transitioning the phase-change material between its amorphous and crystalline phases. This enables edge detection and bright-field imaging modes on the same device. The metasurface is compatible with a large numerical aperture of ~0.5, making it suitable for high resolution coherent optical imaging microscopy. The concept of phase-change reconfigurable nonlocal metasurfaces may enable emerging applications of artificial intelligence-assisted imaging and vision devices with switchable multitasking., Comment: 20 pages, 5 figures
Published: 2024

47. Accuracy of the Ensemble Kalman Filter in the Near-Linear Setting

Author: Calvello, Edoardo, Monmarché, Pierre, Stuart, Andrew M., and Vaes, Urbain
Subjects: Mathematics - Statistics Theory, Mathematics - Dynamical Systems, Mathematics - Numerical Analysis, Mathematics - Optimization and Control
Abstract: The filtering distribution captures the statistics of the state of a dynamical system from partial and noisy observations. Classical particle filters provably approximate this distribution in quite general settings; however they behave poorly for high dimensional problems, suffering weight collapse. This issue is circumvented by the ensemble Kalman filter which is an equal-weight interacting particle system. However, this finite particle system is only proven to approximate the true filter in the linear Gaussian case. In practice, however, it is applied in much broader settings; as a result, establishing its approximation properties more generally is important. There has been recent progress in the theoretical analysis of the algorithm, establishing stability and error estimates in non-Gaussian settings, but the assumptions on the dynamics and observation models rule out the unbounded vector fields that arise in practice and the analysis applies only to the mean field limit of the ensemble Kalman filter. The present work establishes error bounds between the filtering distribution and the finite particle ensemble Kalman filter when the model exhibits linear growth.
Published: 2024

48. Memoir

Author: Crandall, Laura B. Stuart
Abstract: Memoir from the wife of SIO Business Manager Wesley C. Crandall,
Published: 2024

49. Sybil Detection using Graph Neural Networks

Author: Heeb, Stuart, Plesner, Andreas, and Wattenhofer, Roger
Subjects: Computer Science - Social and Information Networks, Computer Science - Artificial Intelligence
Abstract: This paper presents SYBILGAT, a novel approach to Sybil detection in social networks using Graph Attention Networks (GATs). Traditional methods for Sybil detection primarily leverage structural properties of networks; however, they tend to struggle with a large number of attack edges and are often unable to simultaneously utilize both known Sybil and honest nodes. Our proposed method addresses these limitations by dynamically assigning attention weights to different nodes during aggregations, enhancing detection performance. We conducted extensive experiments in various scenarios, including pretraining in sampled subgraphs, synthetic networks, and networks under targeted attacks. The results show that SYBILGAT significantly outperforms the state-of-the-art algorithms, particularly in scenarios with high attack complexity and when the number of attack edges increases. Our approach shows robust performance across different network models and sizes, even as the detection task becomes more challenging. We successfully applied the model to a real-world Twitter graph with more than 269k nodes and 6.8M edges. The flexibility and generalizability of SYBILGAT make it a promising tool to defend against Sybil attacks in online social networks with only structural information., Comment: 9 pages, 1 figure, 6 tables
Published: 2024

50. Reionization morphology and intrinsic velocity offsets allow transmission of Lyman-{\alpha} emission from JADES-GS-z13-1-LA

Author: Qin, Yuxiang and Wyithe, J. Stuart B.
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: We investigate the detectability of Lyman-$\alpha$ (Ly$\alpha$) emission from galaxies at the onset of cosmic reionization, aiming to understand the conditions necessary for detecting high-redshift sources like JADES-GS-z13-1-LA at $z=13$. By integrating galaxy formation models with detailed intergalactic medium (IGM) reionization simulations, we construct high-redshift galaxy catalogs to model intrinsic Ly$\alpha$ profiles and assess their transmission through the IGM. For a galaxy with $M_{\rm UV}\sim -18.5$ like JADES-GS-z13-1-LA, our fiducial model predicts a Ly$\alpha$ transmission of ${\sim}13$% and there is a probability of observing Ly$\alpha$ emission with an equivalent width >40A of up to 10%. We also explore how variations in the UV ionizing escape fraction, dependent on host halo mass, impact Ly$\alpha$ detectability. Our findings reveal that reionization morphology significantly influences detection chances -- models where reionization is driven by low-mass galaxies can boost the detection probability to as much as 12%, while those driven by massive galaxies tend to reduce ionized regions around faint emitters, limiting their detectability. This study underscores the importance of reionization morphology in interpreting high-redshift Ly$\alpha$ observations., Comment: 7 pages, 3 figures, a theory follow up on 2408.16608, comments welcome
Published: 2024

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