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.
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.
Quantum computing takes significant place among the spheres of modern information technology. Quantum computation is usually expressed by the quantum circuit with its sequences of quantum gates. One of the practical applications of quantum computation is to use it in a web-based tool for variety of purposes. Thereby, this project aimed to create an educational simulator for studying quantum circuits with different gates, functions, and transformation rules. The tool would help students to learn the principles of quantum circuit in their courses during undergraduate study. The application was created on the Python based Django framework with the help of Python library packages especially Quantum Toolbox in Python (QuTiP) package. Major steps of simulator implementation included the creation of functions able to build a quantum circuit, to add and remove of quantum gates, apply transformation rules. The challenge appeared around the frontend functions, particularly with the Drag and Drop feature. The result of entire work on this project ended up in a web-based simulator applicable for educational purposes, which allows investigation of quantum circuit work, and quantum gates influence on the quantum circuit unitary matrix
As quantum computing research continues to thrive, the education of quantum computing becomes increasingly more difficult. The complexity of designing and simulating quantum circuits presents significant challenges to students, educators, and researchers. To address these challenges, we introduce QCanvas, a browser-based interactive platform for design, visualization, and simulation. QCanvas enables users to construct quantum circuits through an intuitive drag-and-drop interface while supporting multiple quantum computing paradigms including qubit-based, photonic, and variational models. The platform seamlessly integrates educational resources with practical circuit construction, allowing users to create annotated, interactive notes and simulations. Circuits designed in the visual interface are automatically translated to executable code for simulation in the cloud or, in future iterations, execution on real quantum hardware. By combining accessibility with comprehensive functionality, QCanvas bridges the gap between theoretical quantum computing concepts and practical implementation, providing a versatile tool for education, collaboration, and algorithm prototyping across the community.
Designing and prototyping quantum circuits remains challenging for beginners and intermediate users due to steep learning curves in text-based frameworks and limited features in existing visual tools. This paper introduces QuantumFlow, a web-based platform that addresses these challenges through an accessible drag-and-drop interface for constructing and simulating quantum circuits. The platform provides realtime validation, state visualization, and interactive Bloch-sphere rendering to enable both conceptual exploration and rapid prototyping. Key features include modular subcircuit design, mid-circuit measurements, export to Qiskit, Cirq, and JSON, and hardware-aware transpilation for processors such as IBM's Falcon and Google's Sycamore. Implemented with React and Redux, the platform runs entirely client-side without installation. A structured evaluation with14participants found that QuantumFlow users completed circuit construction tasks45%faster and scored 38 % higher on comprehension assessments than peers relying on textbook workflows. Exported code aligns with framework standards and incorporates optimizations including gate fusion, commutation, and device-specific mapping. Current limitations involve scalability constraints and the absence of direct backend connectivity. Overall, QuantumFlow enhances accessibility to quantum computing education, supports interactive learning, and accelerates early-stage development, effectively bridging instructional platforms with advanced frameworks.
Recently quantum computing has achieved significant results both in theoretical and experimental areas and quantum algorithms have drawn the attention of many scientists. At the present there exist several experiments that realized some parts of certain important quantum algorithms. While those experiments work with only up to seven qubits, quantum simulators allow scientists to design algorithms with many more qubits. The existing simulators have one or more of the following restrictions: either they require powerful computers and additional computation packages such as Matlab or Mathematica or they don't provide an easy method for interacting between the classical and quantum parts of an algorithm. More importantly, none of them can simulate a generic 64-qubit circuit. It is important at this stage of quantum computing development to investigate technological improvements in simulating quantum circuit design.
In this thesis we developed a specialized data structure, QSV, for quantum simulators along with new method for calculation of the new state vector after application of a quantum gate in a quantum simulator. We also developed a technique that speeds up the simulation time with our QSV vectors. With those results we built a quantum simulator that overcomes many shortcomings in other simulators and it has many advanced features.
Our simulator can simulate many 64-qubit circuits and it can directly simulate multiple qubit gates as well as allows users to define gates with up to 10 qubits. The simulation time is much less in comparison with other simulators we tested. The simulator defines specifications so that users can easily design and test quantum circuits. With the simulator we also developed some new quantum circuits and verified many designs and constructions.
n the field of quantum computing, the properties of quantum superposition offer a promising potential for solving complex problems in a few minutes, while classical computers would take years to solve the same problem. Therefore, many institutions have introduced courses related to quantum mechanics and quantum computing into their programs. However, there is currently no known web-based tool or PC application dedicated to the study of quantum computing. Quantum computers are not available for educational purposes. In the early stages of learning, students may benefit from a way to practice quantum computing with a visual tool. Quantum computing is usually expressed by a quantum circuit with its sequences of quantum gates. The article talks about the creation of an educational simulator for the study of quantum circuits with various gates, functions and transformation rules. This quantum simulator will help students learn the principles of quantum circuitry in their undergraduate and graduate courses. This tool will offer functions that allow you to build a quantum circuit, add and remove quantum gates, apply transformation rules, and observe the operation of a quantum circuit with its unitary matrix. By practicing with the quantum circuit simulator, students can strengthen their theoretical knowledge base about quantum computing and linear algebraic functions
Quantum computing is a new way of doing things that uses quantum mechanics to do things that classical systems can't. These things include superposition, entanglement, and interference. Quantum teleportation is one of the most basic protocols that shows how the full quantum state of a qubit can be sent to a different place without moving the particle. It only uses shared entanglement and a classical communication channel. Even though this protocol is theoretically beautiful, it is still hard for students and new researchers to picture and understand it on their own. This paper describes an interactive quantum circuit simulator that runs on the web and was made with Python Flask, IBM's Qiskit library, and Three.js. It was made to show quantum teleportation in real time. Through a browser interface, users can build quantum circuits, use standard gates like Hadamard, Pauli-X, Pauli-Z, CNOT, and multiqubit gates, and see dynamic Bloch sphere updates that show how the state of the qubit changes after each operation. The backend uses Qiskit's statevector simulator to make sure the math is right, and the frontend, which is powered.by Three.js, shows quantum states in three-dimensional geometric forms. Testing confirms that the simulation fidelity is close to 1 under ideal conditions, which means that the protocol was implemented correctly. The proposed framework makes it easier to get into quantum education by getting rid of complicated local setup requirements and giving immediate visual feedback. This makes it easier to go from quantum theory to hands-on experimentation