The 2024 Motile Active Matter Roadmap

Autor: Gompper, Gerhard, Stone, Howard A., Kurzthaler, Christina, Saintillan, David, Peruani, Fernado, Fedosov, Dmitry A., Auth, Thorsten, Cottin-Bizonne, Cecile, Ybert, Christophe, Clement, Eric, Darnige, Thierry, Lindner, Anke, Goldstein, Raymond E., Liebchen, Benno, Binysh, Jack, Souslov, Anton, Isa, Lucio, di Leonardo, Roberto, Frangipane, Giacomo, Gu, Hongri, Nelson, Bradley J., Brauns, Fridtjof, Marchetti, M. Cristina, Cichos, Frank, Heuthe, Veit-Lorenz, Bechinger, Clemens, Korman, Amos, Feinerman, Ofer, Cavagna, Andrea, Giardina, Irene, Jeckel, Hannah, Drescher, Knut

Activity and autonomous motion are fundamental aspects of many living and engineering systems. Here, the scale of biological agents covers a wide range, from nanomotors, cytoskeleton, and cells, to insects, fish, birds, and people. Inspired by biolog

Externí odkaz: http://arxiv.org/abs/2411.19783

Ion Temperature Measurements in the MAST-U Divertor During Steady State Plasmas and ELM Burn Through Phenomena

Autor: Damizia, Y., Elmore, S., Verhaegh, K., Ryan, P., Allan, S., Federici, F., Osborne, N., Bradley, J. W., Team, the MAST-U, Team, the EUROfusion Tokamak Exploitation

This study presents ion temperature (\(T_i\)) measurements in the MAST-U divertor, using a Retarding Field Energy Analyzer (RFEA). Steady state measurements were made during an L-Mode plasma with the strike point on the RFEA. ELM measurements were ma

Externí odkaz: http://arxiv.org/abs/2411.07881

First Ion Temperature Measurements in the MAST-U Divertor via Retarding Field Energy Analyzer

Autor: Damizia, Y., Elmore, S., Ryan, P., Allan, S., Federici, F., Osborne, N., Bradley, J. W., Team, the MAST-U

This study presents the first ion temperature (\(T_i\)) measurements from the MAST-U divertor using a Retarding Field Energy Analyzer (RFEA). Embedded within the flat tile of the closed divertor chamber, the RFEA captures \(T_i\) profiles across vari

Externí odkaz: http://arxiv.org/abs/2407.01246

The Lunar Gravitational-wave Antenna: Mission Studies and Science Case

Autor: Ajith, Parameswaran, Seoane, Pau Amaro, Sedda, Manuel Arca, Arcodia, Riccardo, Badaracco, Francesca, Banerjee, Biswajit, Belgacem, Enis, Benetti, Giovanni, Benetti, Stefano, Bobrick, Alexey, Bonforte, Alessandro, Bortolas, Elisa, Braito, Valentina, Branchesi, Marica, Burrows, Adam, Cappellaro, Enrico, Della Ceca, Roberto, Chakraborty, Chandrachur, Subrahmanya, Shreevathsa Chalathadka, Coughlin, Michael W., Covino, Stefano, Derdzinski, Andrea, Doshi, Aayushi, Falanga, Maurizio, Foffa, Stefano, Franchini, Alessia, Frigeri, Alessandro, Futaana, Yoshifumi, Gerberding, Oliver, Gill, Kiranjyot, Di Giovanni, Matteo, Giudice, Ines Francesca, Giustini, Margherita, Gläser, Philipp, Harms, Jan, van Heijningen, Joris, Iacovelli, Francesco, Kavanagh, Bradley J., Kawamura, Taichi, Kenath, Arun, Keppler, Elisabeth-Adelheid, Kobayashi, Chiaki, Komatsu, Goro, Korol, Valeriya, Krishnendu, N. V., Kumar, Prayush, Longo, Francesco, Maggiore, Michele, Mancarella, Michele, Maselli, Andrea, Mastrobuono-Battisti, Alessandra, Mazzarini, Francesco, Melandri, Andrea, Melini, Daniele, Menina, Sabrina, Miniutti, Giovanni, Mitra, Deeshani, Morán-Fraile, Javier, Mukherjee, Suvodip, Muttoni, Niccolò, Olivieri, Marco, Onori, Francesca, Papa, Maria Alessandra, Patat, Ferdinando, Perali, Andrea, Piran, Tsvi, Piranomonte, Silvia, Pol, Alberto Roper, Pookkillath, Masroor C., Prasad, R., Prasad, Vaishak, De Rosa, Alessandra, Chowdhury, Sourav Roy, Serafinelli, Roberto, Sesana, Alberto, Severgnini, Paola, Stallone, Angela, Tissino, Jacopo, Tkalčić, Hrvoje, Tomasella, Lina, Toscani, Martina, Vartanyan, David, Vignali, Cristian, Zaccarelli, Lucia, Zeoli, Morgane, Zuccarello, Luciano

The Lunar Gravitational-wave Antenna (LGWA) is a proposed array of next-generation inertial sensors to monitor the response of the Moon to gravitational waves (GWs). Given the size of the Moon and the expected noise produced by the lunar seismic back

Externí odkaz: http://arxiv.org/abs/2404.09181

CONFLARE: CONFormal LArge language model REtrieval

Autor: Rouzrokh, Pouria, Faghani, Shahriar, Gamble, Cooper U., Shariatnia, Moein, Erickson, Bradley J.

Retrieval-augmented generation (RAG) frameworks enable large language models (LLMs) to retrieve relevant information from a knowledge base and incorporate it into the context for generating responses. This mitigates hallucinations and allows for the

Externí odkaz: http://arxiv.org/abs/2404.04287