Tootfinder

Prompt atmospheric leptons and the potential role of intrinsic charm
Laksha Pradip Das, Diksha Garg, Maria Vittoria Garzelli, Mary Hall Reno, G\"unter Sigl
https://arxiv.org/abs/2508.06473

Prompt atmospheric leptons and the potential role of intrinsic charm
The all-sky very-high energy ($10^4-10^6$ GeV) atmospheric muon flux is most recently measured by IceCube, where in the higher energy range, the spectrum hardens indicating a prompt component. IceCube also measures the atmospheric muon neutrino flux at high energy. Since this is dominated by the astrophysical flux, they are only able to set an upper bound on the prompt atmospheric muon neutrino flux contribution. We provide a new evaluation of the prompt atmospheric muon flux including for the …

SuperSONIC: Cloud-Native Infrastructure for ML Inferencing
Dmitry Kondratyev, Benedikt Riedel, Yuan-Tang Chou, Miles Cochran-Branson, Noah Paladino, David Schultz, Mia Liu, Javier Duarte, Philip Harris, Shih-Chieh Hsu
https://arxiv.org/abs/2506.20657

SuperSONIC: Cloud-Native Infrastructure for ML Inferencing
The increasing computational demand from growing data rates and complex machine learning (ML) algorithms in large-scale scientific experiments has driven the adoption of the Services for Optimized Network Inference on Coprocessors (SONIC) approach. SONIC accelerates ML inference by offloading it to local or remote coprocessors to optimize resource utilization. Leveraging its portability to different types of coprocessors, SONIC enhances data processing and model deployment efficiency for cuttin…

Leveraging AM and FM Rhythm Spectrograms for Dementia Classification and Assessment
Parismita Gogoi, Vishwanath Pratap Singh, Seema Khadirnaikar, Soma Siddhartha, Sishir Kalita, Jagabandhu Mishra, Md Sahidullah, Priyankoo Sarmah, S. R. M. Prasanna
https://arxiv.org/abs/2506.00861

Leveraging AM and FM Rhythm Spectrograms for Dementia Classification and Assessment
This study explores the potential of Rhythm Formant Analysis (RFA) to capture long-term temporal modulations in dementia speech. Specifically, we introduce RFA-derived rhythm spectrograms as novel features for dementia classification and regression tasks. We propose two methodologies: (1) handcrafted features derived from rhythm spectrograms, and (2) a data-driven fusion approach, integrating proposed RFA-derived rhythm spectrograms with vision transformer (ViT) for acoustic representations alo…