Speaker
Description
Recent years have seen rapid progress in resonant anomaly detection for collider searches, but existing studies often rely on a limited set of signal benchmarks and face a trade-off between sensitive but model-dependent high-level observables and fully agnostic but less performant low-level representations. We address both limitations by introducing new simulated signal benchmarks, publicly released in a format compatible with the LHCO R&D benchmark, and by studying a broad high-level, yet highly agnostic, observable set combining Energy Flow Polynomials with subjettiness variables.
We evaluate this combined “kitchen sink” representation against several baseline observable sets in both an idealized anomaly-detection setting and the CWoLa hunting task. Across a broad range of signal types, the combined observable set achieves the best overall sensitivity.