# Constraining new physics from Higgs measurements with Lilith: update to LHC Run 2 results

## TL;DR

Lilith 2.0 is a Python tool that improves constraints on new physics from Higgs measurements by incorporating advanced likelihoods and correlations, updating its database with the latest LHC Run 2 results.

## Contribution

The paper introduces Lilith 2.0 with enhanced likelihood modeling and an expanded database, enabling more accurate global fits of Higgs data for new physics scenarios.

## Key findings

- Validated implementation of ATLAS and CMS Run 2 Higgs results.
- Performed global fits for reduced Higgs couplings and Two-Higgs-doublet models.
- Demonstrated Lilith-2.0's capability to constrain new physics models.

## Abstract

Lilith is a public Python library for constraining new physics from Higgs signal strength measurements. We here present version 2.0 of Lilith together with an updated XML database which includes the current ATLAS and CMS Run 2 Higgs results for 36/fb. Both the code and the database were extended from the ordinary Gaussian approximation employed in Lilith-1.1 to using variable Gaussian and Poisson likelihoods. Moreover, Lilith can now make use of correlation matrices of arbitrary dimension. We provide detailed validations of the implemented experimental results as well as a status of global fits for reduced Higgs couplings, Two-Higgs-doublet models of Type I and Type II, and invisible Higgs decays. Lilith-2.0 is available on GitHub and ready to be used to constrain a wide class of new physics scenarios.