Changelog

All notable changes to QuScope will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.1.0] - 2025-07-09

🎉 Initial Release

Added

Core Functionality - Quantum image encoding with multiple methods (amplitude, angle, basis, FRQI) - Quantum backend management for simulators and real quantum hardware - EELS (Electron Energy Loss Spectroscopy) quantum processing tools - Quantum machine learning modules for microscopy applications

Image Processing - quscope.image_processing.quantum_encoding - Core quantum image encoding functions - quscope.image_processing.preprocessing - Classical image preprocessing utilities - quscope.image_processing.filtering - Quantum and classical filtering operations - quscope.image_processing.quantum_segmentation - Quantum image segmentation

Quantum Machine Learning - quscope.qml.image_encoding - ML-focused quantum image encoding - Support for various encoding schemes optimized for ML workflows

EELS Analysis - quscope.eels_analysis.preprocessing - EELS data preprocessing - quscope.eels_analysis.quantum_processing - Quantum algorithms for EELS analysis

Backend Management - quscope.quantum_backend - Unified interface for quantum backends - Support for Qiskit Aer simulators and IBM Quantum hardware - Error handling and retry mechanisms for robust execution

Documentation & Examples - Comprehensive API documentation with Sphinx - Interactive Jupyter notebooks demonstrating key features - Complete quantum image encoding validation examples - Step-by-step tutorials for common use cases

Package Infrastructure - PyPI-ready package structure with proper metadata - Read the Docs integration for online documentation - Comprehensive test suite with pytest - Development dependencies and linting configuration

Dependencies

  • Python >= 3.9

  • qiskit >= 0.45.0

  • qiskit-aer >= 0.13.0

  • numpy >= 1.21.0

  • pillow >= 8.0.0

  • scipy >= 1.7.0

Optional Dependencies

  • matplotlib >= 3.5.0 (visualization)

  • jupyter >= 1.0.0 (notebook examples)

  • pandas >= 1.3.0 (data analysis)

Known Issues

  • Large quantum circuits (>20 qubits) may have slow simulation times

  • Some advanced quantum hardware features require additional setup

Future Plans

  • Enhanced quantum ML algorithms

  • Real-time microscopy data processing

  • Integration with more quantum hardware backends

  • Performance optimizations for large-scale image processing