Quantum Algorithms for Many-Body Chaos Simulation

In quantum dynamics, the eigenstate thermalization hypothesis (ETH) implies that out-of-equilibrium systems will relax toward thermal equilibrium over time for generic initial states. This is also true for quantum chaotic systems. However, some quantum chaotic systems can host atypical eigenstates exhibiting ergodicity-breaking features. Quantum many-body scars are an example of atypical eigenstates with an enhanced probability density along regions associated with unstable and periodic orbits within an otherwise thermalizing spectrum. Initializing the system in a state with strong overlap with scarred eigenstates can lead to quantum revival, which is the system’s close return to its initial state during time evolution. The system retains memory of its initial state through time, which goes against the ergodic nature of quantum chaotic systems.

We explore scarring and non-thermal features in condensed matter systems through simulations inspired by quantum computational algorithms. We leverage the power of quantum-inspired algorithms to simulate and control the dynamics of many-body chaotic systems. This study will help us uncover novel properties and applications for disordered materials and chaotic spin chains as quantum memory systems.