Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …

An oracle that correctly predicts the outcome of every particle physics experiment, the
products of every possible chemical reaction or the function of every protein would …

Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

Symbolic regression (SR) is the study of algorithms that automate the search for analytic
expressions that fit data. While recent advances in deep learning have generated renewed …

Abstract Machine learning (ML) is becoming a new paradigm for scientific research in
various research fields due to its exciting and powerful capability of modeling tools used for …

In this white paper for the 2021 Snowmass process, we give a description of the proposed
Future Circular Collider (FCC) project and its physics program. The paper summarizes and …

A search is presented for a heavy resonance Y decaying into a Standard Model Higgs
boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider …

Microchannel heat sinks are an efficient cooling method for semiconductor packages.
However, to properly cool increasingly complex and thermally dense circuits, microchannel …

Solving materials engineering tasks is often hindered by limited information, such as in
inverse problems with only boundary data information or design tasks with a simple …

Resonant anomaly detection is a promising framework for model-independent searches for
new particles. Weakly supervised resonant anomaly detection methods compare data with a …