Intermediate State Prediction in the Formation of Topologically Associated Chromatin Domains using Quantum Annealing

This work explores the application of quantum annealing (QA) to sampling epigenetic states of chromatin domains. The aim is to replicate statistical properties observed in empirical biological data. Using a data-driven model, the epigenetic parameters of interest can be mapped to QUBO formulations. It is demonstrated that D-Wave machines are well suited for the chromatin sampling problem due to its structure. With the QA-based sampling model, we reproduce and compare chromatin domain statistics with classical sampling approaches and optimal annealing parameters. We study whether parallelization techniques can reduce the sampling time without compromising performance.