The Supersonic Project: Lighting up the faint end of the JWST UV luminosity function

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Claire E. Williams, William Lake, Smadar Naoz, Blakesley Burkhart, Tommaso Treu | Summary: The James Webb Space Telescope (JWST) is capable of probing extremely early eras of our Universe when the supersonic relative motions between dark matter and baryonic overdensities modulate structure formation ($z>sim 10$). We study […]


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Looking in the axion mirror: An all-sky analysis of stimulated decay

Kavli Affiliate: Kiyoshi Wesley Masui | First 5 Authors: Yitian Sun, Katelin Schutz, Harper Sewalls, Calvin Leung, Kiyoshi Wesley Masui | Summary: Axion dark matter (DM) produces echo images of bright radio sources via stimulated decay. These images appear as a faint radio line centered at half the axion mass, with the line width set […]


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The THESAN project: connecting ionized bubble sizes to their local environments during the Epoch of Reionization

Kavli Affiliate: Mark Vogelsberger | First 5 Authors: Meredith Neyer, Aaron Smith, Rahul Kannan, Mark Vogelsberger, Enrico Garaldi | Summary: An important characteristic of cosmic reionization is the growth of ionized gas bubbles surrounding early luminous objects. Understanding the connections between the formation and coalescence of these bubbles and their originating astrophysical sources is equally […]


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Certifiably Robust Graph Contrastive Learning

Kavli Affiliate: Xiang Zhang | First 5 Authors: Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang | Summary: Graph Contrastive Learning (GCL) has emerged as a popular unsupervised graph representation learning method. However, it has been shown that GCL is vulnerable to adversarial attacks on both the graph structure and node attributes. Although […]


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Dual Prompt Tuning for Domain-Aware Federated Learning

Kavli Affiliate: Feng Wang | First 5 Authors: Guoyizhe Wei, Feng Wang, Anshul Shah, Rama Chellappa, | Summary: Federated learning is a distributed machine learning paradigm that allows multiple clients to collaboratively train a shared model with their local data. Nonetheless, conventional federated learning algorithms often struggle to generalize well due to the ubiquitous domain […]


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A surprisingly high number of dual active galactic nuclei in the early Universe

Kavli Affiliate: Roberto Maiolino | First 5 Authors: Michele Perna, Santiago Arribas, Isabella Lamperti, Chiara Circosta, Elena Bertola | Summary: Merger events can trigger gas accretion onto supermassive black holes (SMBHs) sitting at the centre of galaxies, and form close pairs of active galactic nuclei (AGN). The fraction of AGN in pairs gives key information […]


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Fe-TAMLs as a new class of small molecule peroxidase probes for correlated light and electron microscopy

Kavli Affiliate: Mark Ellisman | Authors: Stephen R Adams, Mason R Mackey, Ranjan Ramachandra, Thomas J Deerinck, Guillaume A Castillon, Sebastien Phan, Junru Hu, Daniela Boassa, John T Ngo and Mark H Ellisman | Summary: We introduce Fe-TAML, a small molecule-based peroxidase as a versatile new member of the correlated fluorescence and electron microscopy toolkit. […]


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A Neural Scaling Law from Lottery Ticket Ensembling

Kavli Affiliate: Max Tegmark | First 5 Authors: Ziming Liu, Max Tegmark, , , | Summary: Neural scaling laws (NSL) refer to the phenomenon where model performance improves with scale. Sharma & Kaplan analyzed NSL using approximation theory and predict that MSE losses decay as $N^{-alpha}$, $alpha=4/d$, where $N$ is the number of model parameters, […]


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Integrability of Large-Charge Sectors in Generic 2D EFTs

Kavli Affiliate: Simeon Hellerman | First 5 Authors: Matthew Dodelson, Simeon Hellerman, Masataka Watanabe, Masahito Yamazaki, | Summary: It is shown that integrability is an accidental property of generic two-dimensional $O(2)$-symmetric asymptotically-free theories in the regime where the charge density is much larger than the dynamical scale. We show this by constructing an infinite tower […]


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