Machine Learning for Arbitrary Single-Qubit Rotations on an Embedded Device

Autor: Bhat, Madhav Narayan, Russo, Marco, Carloni, Luca P., Di Guglielmo, Giuseppe, Fahim, Farah, Li, Andy C. Y., Perdue, Gabriel N.

Here we present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first bootstrap

Externí odkaz: http://arxiv.org/abs/2411.13037

The Fastest Path to Discovering the Second Electromagnetic Counterpart to a Gravitational Wave Event

Autor: Shah, Ved G., Foley, Ryan J., Narayan, Gautham

The discovery of a second electromagnetic counterpart to a gravitational wave event represents a critical goal in the field of multi-messenger astronomy. In order to determine the optimal strategy for achieving this goal, we perform comprehensive sim

Externí odkaz: http://arxiv.org/abs/2411.09002

Adaptive Meta-Learning for Robust Deepfake Detection: A Multi-Agent Framework to Data Drift and Model Generalization

Autor: P, Dinesh Srivasthav, Subudhi, Badri Narayan

Pioneering advancements in artificial intelligence, especially in genAI, have enabled significant possibilities for content creation, but also led to widespread misinformation and false content. The growing sophistication and realism of deepfakes is

Externí odkaz: http://arxiv.org/abs/2411.08148

A halo model approach for mock catalogs of time-variable strong gravitational lenses

Autor: Abe, Katsuya T., Oguri, Masamune, Birrer, Simon, Khadka, Narayan, Marshall, Philip J., Lemon, Cameron, More, Anupreeta, Collaboration, the LSST Dark Energy Science

Time delays in both galaxy- and cluster-scale strong gravitational lenses have recently attracted a lot of attention in the context of the Hubble tension. Future wide-field cadenced surveys, such as the LSST, are anticipated to discover strong lenses

Externí odkaz: http://arxiv.org/abs/2411.07509

Rubin ToO 2024: Envisioning the Vera C. Rubin Observatory LSST Target of Opportunity program

Autor: Andreoni, Igor, Margutti, Raffaella, Banovetz, John, Greenstreet, Sarah, Hebert, Claire-Alice, Lister, Tim, Palmese, Antonella, Piranomonte, Silvia, Smartt, S. J., Smith, Graham P., Stein, Robert, Ahumada, Tomas, Anand, Shreya, Auchettl, Katie, Bannister, Michele T., Bellm, Eric C., Bloom, Joshua S., Bolin, Bryce T., Bom, Clecio R., Brethauer, Daniel, Brucker, Melissa J., Buckley, David A. H., Chandra, Poonam, Chornock, Ryan, Christensen, Eric, Cooke, Jeff, Corsi, Alessandra, Coughlin, Michael W., Cuevas-Otahola, Bolivia, Filippo, D'Ammando, Dai, Biwei, Dhawan, S., Filippenko, Alexei V., Foley, Ryan J., Franckowiak, Anna, Gomboc, Andreja, Gompertz, Benjamin P., Guy, Leanne P., Hazra, Nandini, Hernandez, Christopher, Hosseinzadeh, Griffin, Hussaini, Maryam, Ibrahimzade, Dina, Izzo, Luca, Jones, R. Lynne, Kang, Yijung, Kasliwal, Mansi M., Knight, Matthew, Kunnumkai, Keerthi, Lamb, Gavin P, LeBaron, Natalie, Lejoly, Cassandra, Levan, Andrew J., MacBride, Sean, Mallia, Franco, Malz, Alex I., Miller, Adam A., Mora, J. C., Narayan, Gautham, J., Nayana A., Nicholl, Matt, Nichols, Tiffany, Oates, S. R., Panayada, Akshay, Ragosta, Fabio, Ribeiro, Tiago, Ryczanowski, Dan, Sarin, Nikhil, Schwamb, Megan E., Sears, Huei, Seligman, Darryl Z., Sharma, Ritwik, Shrestha, Manisha, Simran, Stroh, Michael C., Terreran, Giacomo, Thakur, Aishwarya Linesh, Trivedi, Aum, Tyson, J. Anthony, Utsumi, Yousuke, Verma, Aprajita, Villar, V. Ashley, Volk, Kathryn, Vyas, Meet J., Wasserman, Amanda R., Wheeler, J. Craig, Yoachim, Peter, Zegarelli, Angela, Bianco, Federica

The Legacy Survey of Space and Time (LSST) at Vera C. Rubin Observatory is planned to begin in the Fall of 2025. The LSST survey cadence has been designed via a community-driven process regulated by the Survey Cadence Optimization Committee (SCOC), w

Externí odkaz: http://arxiv.org/abs/2411.04793