Qubit

Key Features Realistic Quantum Circuit Simulation Leverages Qiskit and AerSimulator to construct and execute realistic quantum circuits across multiple simulation methods (statevector, density_matrix, matrix_product_state, etc.). Quantum Neurons Create and manage virtual "neurons" built from configurable layers of quantum operations (RY, RX, H gates). Each neuron simulates complex entanglement and superposition behaviors across dozens of qubits. Layered Architecture Every neuron features a customizable 3-layer design: Layer 1: RY rotations for initialization Layer 2: Hadamard gates for superposition Layer 3: RX rotations for final transformation Integrated Grover’s Search Apply Grover's algorithm across all neurons or to individual ones for rapid quantum searching and oracle testing. GUI Interface Includes a fully interactive Tkinter GUI: Visual control over neuron creation, simulation settings, Grover search, and deletions Real-time logs and output via a clean and styled GUI Optimized layout for easy operation and live monitoring Logging and Debugging Tools Built-in error tracking and verbose output for all major actions, making Qubit ideal for research and development use. Use Cases Quantum AI simulations (QELM/QML integration) Educational tools for understanding qubit behavior Experimental platform for quantum algorithms Simulating neural-like networks using quantum gates Oracle testing and state searching via Grover’s algorithm Technical Specs Built with Python 3.11 Utilizes Qiskit, NumPy, and Tkinter Capable of simulating up to 64-qubit circuits (hardware dependent) Modular and extensible – integrate with larger projects easily