A Learning-Oriented Quantum Circuit Simulator with Classical Problem Extensions

Abstract

Quantum computing introduces new paradigms for solving complex computational problems. In this paper, we present the development of a full-stack quantum computing simulator that enables users to design, simulate, and visualize quantum circuits, while also integrating classical NP problem solvers. Built using Python, Qiskit, React, and Flask/FastAPI, the simulator supports up to 20 qubits and includes features like quantum gate editing, Bloch sphere visualization, and classical algorithms for 3-SAT and Knapsack. The project aims to bridge accessibility and functionality in quantum computing education and experimentation.

Introduction

This paper introduces a modular, full-stack quantum simulator that integrates quantum circuit simulation with classical NP-complete problem solving in a single web-based platform. Designed for both educational and prototyping use, the simulator features a visual frontend (built with React.js and Tailwind CSS) and a Python-based backend (using FastAPI, Flask, and Qiskit). It enables:

• Visual circuit building with drag-and-drop gate placement.

• Quantum state simulation and Bloch sphere visualization.

• Classical problem solving for NP-complete problems like 3-SAT and 0/1 Knapsack.

• User account management and data storage via SQLite.

The literature review highlights gaps in existing tools—particularly the lack of integration between quantum and classical problem solvers and the absence of full-stack educational platforms.

System Features

• Frontend GUI: Circuit editor, NP problem forms, real-time visualization.

• Backend Engine: Quantum simulations with Qiskit, NP solvers using Python, JWT-based authentication.

• Database Layer: User data and saved experiments stored in SQLite.

• Key Functionalities:

  • Up to 20-qubit simulations (tested effectively up to 5 qubits).

  • Bloch sphere and histogram visualizations.

  • Classical NP solvers with intuitive output.

  • Offline functionality for educational accessibility.

Results & Discussion

The simulator successfully executed standard quantum algorithms like Bell state creation and Grover’s search, with accurate results and interactive visual feedback. It outperformed many existing tools in usability and integration but is currently limited by the exponential resource demands of quantum simulations. Future enhancements include GPU acceleration, noise modeling, and improved scalability.

References

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Copyright

Copyright © 2025 Navyasri J, Dr. S. Ajitha. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.