Dynamical Quantum Phase Transitions of the Schwinger Model: Real-Time Dynamics on IBM Quantum

Abstract

Simulating the real-time dynamics of gauge theories represents a paradigmatic use case to test the hardware capabilities of a quantum computer, since it can involve non-trivial input states’ preparation, discretized time evolution, long-distance entanglement, and measurement in a noisy environment. We implemented an algorithm to simulate the real-time dynamics of a few-qubit system that approximates the Schwinger model in the framework of lattice gauge theories, with specific attention to the occurrence of a dynamical quantum phase transition. Limitations in the simulation capabilities on IBM Quantum were imposed by noise affecting the application of single-qubit and two-qubit gates, which combine in the decomposition of Trotter evolution. The experimental results collected in quantum algorithm runs on IBM Quantum were compared with noise models to characterize the performance in the absence of error mitigation.

Quantum kernels for classifying dynamical singularities in a multiqubit system

“…In many situations, it is challenging to prepare and control a system with a large number of degrees of freedom; and therefore, experiments with small quantum systems [4,6] or quantum computers implementations [7] are designed to test dynamical singularities. Technically, the LE usually has no exact zeros for finite-size systems, except for fine-tuned post-quench parameters, which fulfill specific constraint conditions depending on the physical implementation [2].…”

Multiscale Entanglement Renormalization Ansatz: Causality and Error Correction

“…NISQ superconducting devices suffer with respect to the inclusion of entanglement among qubit triplets and more complex structures than pairs [25], thus leading to a shortrange entanglement which causes a comparable computational capability of tensor network techniques [26]. This successful application for computational complexity reduction in the quantum framework intertwines with widespread applications in data science [27][28][29][30] and hierarchical tensor geometry [31][32][33].…”