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.
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