A Quantum Algorithm for Model-Independent Searches for New Physics

We propose a novel quantum technique to search for unmodelled anomalies in multi-dimensional binned collider data.We propose associating an Ising lattice spin site with each bin, with the Ising Hamiltonian suitably constructed from the observed data and a corresponding theoretical expectation.In order to capture spatially correlated anomalies in the data, we introduce spin-spin interactions between neighboring sites, as well as self-interactions.The ground state energy of the resulting Ising Hamiltonian can be used as a new test statistic, which can be computed either classically or via adiabatic quantum optimization.We demonstrate that our test statistic outperforms some of the most commonly used goodness-of-fit tests.The new approach greatly reduces the look-elsewhere effect by exploiting the typical differences between statistical noise and genuine new physics signals.