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The Fermion Bag Approach in the Hamiltonian Picture

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Quantum Monte Carlo methods, when applicable, offer reliable ways to extract the nonperturbative physics of strongly-correlated many-body systems. However, there are some bottlenecks to the applicability of these methods including the sign problem and algorithmic update inefficiencies. Using the t-V model Hamiltonian as the example, I demonstrate how the Fermion Bag Approach--originally developed in the context of lattice field theories--has aided in solving the sign problem for this model as well as aided in developing a more efficient algorithm to study the model. Finally, I discuss some other potential uses for the new algorithm, including for a broader class of models known to be sign-problem-free due to fermion bag ideas.