Tootfinder

Sensitivity of nEXO to $^{136}$Xe Charged-Current Interactions: Background-free Searches for Solar Neutrinos and Fermionic Dark Matter
G. Richardson, B. G. Lenardo, D. Gallacher, R. Saldanha, P. Acharya, S. Al Kharusi, A. Amy, E. Angelico, A. Anker, I. J. Arnquist, A. Atencio, J. Bane, V. Belov, E. P. Bernard, T. Bhatta, A. Bolotnikov, J. Breslin, P. A. Breur, J. P. Brodsky, S. Bron, E. Brown, T. Brunner, B. Burnell, E. Caden, G. F. Cao, L. Q. Cao, D. Cesmecioglu, D. Chernyak, M. Chiu,…

Sensitivity of nEXO to $^{136}$Xe Charged-Current Interactions: Background-free Searches for Solar Neutrinos and Fermionic Dark Matter
We study the sensitivity of nEXO to solar neutrino charged-current interactions, $ν_e + ^{136}$Xe$\rightarrow ^{136}$Cs$^* + e^-$, as well as analogous interactions predicted by models of fermionic dark matter. Due to the recently observed low-lying isomeric states of $^{136}$Cs, these interactions will create a time-delayed coincident signal observable in the scintillation channel. Here we develop a detailed Monte Carlo of scintillation emission, propagation, and detection in the nEXO detecto…

Hedge Funds on a Swamp: Analyzing Patterns, Vulnerabilities, and Defense Measures in Blockchain Bridges [Experiment, Analysis \& Benchmark]
Poupak Azad, Jiahua Xu, Yebo Feng, Preston Strowbridge, Cuneyt Akcora
https://arxiv.org/abs/2507.06156

Hedge Funds on a Swamp: Analyzing Patterns, Vulnerabilities, and Defense Measures in Blockchain Bridges [Experiment, Analysis \& Benchmark]
Blockchain bridges have become essential infrastructure for enabling interoperability across different blockchain networks, with more than $24B monthly bridge transaction volume. However, their growing adoption has been accompanied by a disproportionate rise in security breaches, making them the single largest source of financial loss in Web3. For cross-chain ecosystems to be robust and sustainable, it is essential to understand and address these vulnerabilities. In this study, we present a com…

Ultra-pure Nickel for Structural Components of Low-Radioactivity Instruments
T. J. Roosendaal, C. T. Overman, G. S. Ortega, T. D. Schlieder, N. D. Rocco, L. K. S. Horkley, K. P. Hobbs, K. Harouaka, J. L. Orrell, P. Acharya, A. Amy, E. Angelico, A. Anker, I. J. Arnquist, A. Atencio, J. Bane, V. Belov, E. P. Bernard, T. Bhatta, A. Bolotnikov, J. Breslin, P. A. Breur, J. P. Brodsky, E. Brown, T. Brunner, B. Burnell, E. Caden, L. Q. Cao, D. Cesmecioglu, S. A. Charlebois, D. Chernyak, M. Ch…

Ultra-pure Nickel for Structural Components of Low-Radioactivity Instruments
The next generation of rare-event search experiments in nuclear and particle physics demand structural materials combining exceptional mechanical strength with ultra-low levels of radioactive contamination. This study evaluates chemical vapor deposition (CVD) nickel as a candidate structural material for such applications. Manufacturer-supplied CVD Ni grown on aluminum substrates underwent tensile testing before and after welding alongside standard Ni samples. CVD Ni exhibited a planar tensile …

Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition
Mu Yang, Szu-Jui Chen, Jiamin Xie, John Hansen
https://arxiv.org/abs/2506.05706

Bridging the Modality Gap: Softly Discretizing Audio Representation for LLM-based Automatic Speech Recognition
One challenge of integrating speech input with large language models (LLMs) stems from the discrepancy between the continuous nature of audio data and the discrete token-based paradigm of LLMs. To mitigate this gap, we propose a method for integrating vector quantization (VQ) into LLM-based automatic speech recognition (ASR). Using the LLM embedding table as the VQ codebook, the VQ module aligns the continuous representations from the audio encoder with the discrete LLM inputs, enabling the LLM…