Model-Independent Detection of New Physics Signals Using Interpretable Semi-Supervised Classifier Tests

Understand

A central goal in experimental high energy physics is to detect new physics signals that are not explained by known physics.

• In this paper, we aim to search for new signals that appear as deviations from known Standard Model physics in high-dimensional particle physics data.
• To do this, we determine whether there is any statistically significant difference between the distribution of Standard Model background samples and the distribution of the experimental observations, which are a mixture of the background and a potential new signal.
• Traditionally, one also assumes access to a sample from a model for the hypothesized signal distribution.