The upcoming Electron-Ion Collider (EIC) at Brookhaven, USA will enable high-precision studies of the internal structure of protons and nuclei, including their spin composition, parton distributions, and the dynamics of the strong force that binds them. It will also provide unique insight into the mechanisms by which partons fragment into hadrons. One of the key observables at the EIC is semi-inclusive deep inelastic scattering (SIDIS), which offers direct sensitivity to both parton distribution functions (PDFs) and fragmentation functions (FFs). In this work, I present, for the first time, the most precise perturbative predictions for SIDIS within the framework of Quantum Chromodynamics (QCD), computed up to next-to-next-to-leading order (NNLO) in the strong coupling constant. In addition, we perform the resummation of large logarithmic contributions arising in the threshold region, improving the reliability of theoretical predictions in kinematic regimes where fixed-order calculations alone are insufficient. By combining fixed-order results up to NNLO with resummed contributions, we demonstrate a significant reduction in theoretical uncertainties and analyze their phenomenological impact. The high-precision predictions presented in this work will therefore play a crucial role for understanding the spin distribution of hadron and fragmentation mechanism at EIC energies.

Gravitational waves have opened a new window into the Universe. Mergers of compact object like black holes and neutron star being detected routinely. The LIGO-Virgo-KAGRA (LVK) fourth observing run (O4) ended last year and reported over 250 compact binary mergers discovered in real time. The scale of gravitational-wave searches, inference, and alerts has increased significantly over the last observing runs. As of O4, discoveries are made every 2-3 days, with alerts being distributed in 30 seconds of merger time. This presents an incredible opportunity for multi-messenger astronomy with gravitational waves. In this talk, I will present an overview of the LVK alert infrastructure and describe the online analyses to go from data acquisition to searches and alerts. I will also talk about recent algorithm development using machine-learning and artificial intelligence for noise subtraction, search, and parameter estimation and present results of the first live binary black hole detections done by the LVK using artificial intelligence.

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