Microsoft

Random Circuit Sampling, Quantum Echoes, and Phase Transitions (MBQC vs Circuit Model)

This project developed a simulator-first framework for studying measurement-based quantum computing (MBQC) workflows and comparing them with standard circuit-model baselines. Using Qiskit and Cirq, the system supports cluster and graph states on linear chains and grids, adaptive single-qubit measurements, and configurable noise models including depolarizing, damping, and readout error. The student team focused on three benchmark tasks: random circuit sampling, quantum echoes for OTOC behavior, and measurement-induced phase transitions. The framework was designed to quantify sampling statistics, echo decay, entropy and mutual information indicators, runtime, and shot-count efficiency across different graph topologies, measurement rules, and noise settings, enabling reproducible analysis without requiring cloud quantum hardware.