QuScope: Quantum-Assisted Processing for Electron Microscopy Data

Quantum processing offers a route to represent and analyze microscopy data on quantum hardware. This work presents QuScope, a self-contained open-source package that implements image encoding methods and simulation tools tailored for electron microscopy and related imaging modalities. QuScope implements angle, basis, amplitude, and FRQI encodings using standard Qiskit primitives and provides preprocessing pipelines, 4×4 patching, oracle construction, Grover-based pattern search, and visualization utilities. Validation on a controlled image and synthetic patterns demonstrates reliable mapping of grayscale intensities to rotation angles and normalized amplitudes and shows how thresholded oracles produce distinct measurement histograms. Quantitative analysis reports gate counts, circuit depth, qubit budgets (e.g., 16 qubits for 4×4 angle encoding, 4 qubits for amplitude encoding, 5 qubits for FRQI) and information-theoretic metrics such as outcome entropy, illustrating scaling and sparsity trade-offs. The implementation avoids external imaging dependencies for reproducibility, ships with documentation and examples, and supports simulator and near-term hardware deployment. Future work will target optimized state preparation, error mitigation, and cloud-hardware benchmarking to assess noise resilience and practical feasibility for quantum-assisted microscopy data analysis.