The proliferation of quantum computer simulators, including leading tools such as Qiskit, BSQKit, Composer, and Quirk, highlights the growing demand for performance, usability, and accessibility in quantum computing. This project seeks to enhance an existing Java-based quantum computer simulator (QCS) developed by Naval Postgraduate School students and faculty by incorporating features that improve its accuracy, efficiency, and usability to industry standards. A comparative analysis of the performance, complexity, and usability of established simulators will provide insights into their strengths and weaknesses. Special attention will be given to understanding the intuitive design principles behind Composer and Quirk to integrate similar user-friendly features into QCS. The goal is to transform QCS into a robust and scalable simulator by introducing improvements in simulation accuracy, computational efficiency, and user interactivity, along with a valuable distinguishing feature. This initiative aims to create a tool that serves both researchers and students, offering advanced functionality while maintaining accessibility and ease of use.
The proliferation of quantum computer simulators, including leading tools such as Qiskit, BSQKit, Composer, and Quirk, highlights the growing demand for performance, usability, and accessibility in quantum computing. This project seeks to enhance an existing Java-based quantum computer simulator (QCS) developed by Naval Postgraduate School students and faculty by incorporating features that improve its accuracy, efficiency, and usability to industry standards. A comparative analysis of the performance, complexity, and usability of established simulators will provide insights into their strengths and weaknesses. Special attention will be given to understanding the intuitive design principles behind Composer and Quirk to integrate similar user-friendly features into QCS. The goal is to transform QCS into a robust and scalable simulator by introducing improvements in simulation accuracy, computational efficiency, and user interactivity, along with a valuable distinguishing feature. This initiative aims to create a tool that serves both researchers and students, offering advanced functionality while maintaining accessibility and ease of use.
Quantum computing has emerged as a transformative technological advancement with the potential to challenge the foundations of classical cryptography. Traditional cryptographic algorithms, such as RSA, rely heavily on the computational hardness of problems like integer factorization—a problem quantum algorithm like Shor's can theoretically solve efficiently. This research investigates the practical capabilities and performance limitations of three prominent quantum simulation frameworks: Qiskit, Cirq, and QuTiP. The study aims to analyze and compare their efficiency in simulating the decryption process for encrypted data of varying bit lengths—specifically 8 -bit, 16 -bit, 32 -bit, 64 -bit, 128 -bit, and 512 -bit keys. By simulating classical decryption schemes through quantum circuits, we assess the computational resources, execution time, and overall performance of each platform. This benchmarking helps to highlight how effectively these simulators can model cryptographic tasks and where they currently fall short in terms of scalability and execution time. The results offer valuable insights into the practicality of deploying quantum computing for real-world cryptographic operations and outline the current limitations imposed by simulation-based approaches, especially as key sizes grow in complexity. Ultimately, this research contributes to a deeper understanding of how existing quantum tools perform under cryptographic workloads and what improvements are necessary to make quantum-assisted cryptanalysis viable at scale.
Quantum computing is becoming increasingly relevant. Numerous research efforts are being carried out to improve quantum computers by increasing the number of qubits in their processors, mitigating noise, etc. However, the tools that exist to program these computers are not advancing at the same speed. Therefore, in this work, we propose Quirk+, a quantum circuit development tool based on Quirk. We have implemented improvements over Quirk such as the inclusion of a custom gate importer/exporter, a running circuit inspector, a translator to qasm and vice-versa, as well as other interface usability improvements. Tools such as the one we propose in this paper will facilitate the work of quantum software developers, as well as break down the barriers to access to this type of programming for classical software developers.
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 computers are still infrequent and expensive. They have a great potential for research and industry, but they are noisy, limited, and not always easy to access. All this is preventing rapid and widespread access to the whole potential of this field. To overcome this bottleneck and foster advances in quantum computing, a large plethora of Quantum Computer Simulators (QCS) have emerged, allowing quantum studies on classical machines, and ultimately on quantum devices as well. In addition to being numerous, these simulators differ from each other in an overwhelming number of aspects, which hardens any attempt to categorise/profile them: making a choice is really difficult for a researcher. This work presents a systematic literature review and a public web repository QoverC of the existing QCS for quantum computation in general, and the leading ones for optimisation in particular. To the best of the authors' knowledge, this is the largest QCS study to date, where we include 199 web, desktop, and hybrid simulators, over 22 programming languages. We also provide a comprehensive comparison spanning over 10 metrics. We aim to bring structure to this domain, foster quantum computing, study their particular features, and ease their use and research in the future.
Quantum computing is a rapidly emerging and promising field with the potential to transform various research domains including drug design, network technologies, and sustainable energy solutions. Due to the inherent complexity and divergence from classical computing, several major quantum computing libraries have been developed to implement quantum algorithms, namely IBM Qiskit, Amazon Braket, Cirq, PyQuil, and PennyLane. These libraries enable quantum simulations on classical computers and execution on corresponding quantum hardware, such as Qiskit programs on IBM quantum computers. Despite the variations among these platforms, the core concepts remain the same. One notable challenge is the absence of a Python-based quantum interpreter to connect these five frameworks, a gap that remains to be fully addressed. In response, our work introduces a tool called Qinterpreter, accessible through a user-friendly web interface, the Quantum Science Gateway QubitHub, which operates alongside Jupyter Notebooks. Built using the Python Object-Oriented Programming System, Qinterpreter unifies the five well-known quantum libraries into a single framework. Designed as an educational tool for students and researchers entering the quantum domain, Qinterpreter enables the straightforward development and execution of quantum circuits across such platforms. This work highlights the quantum programming versatility and accessibility of Qinterpreter and underscores our ultimate goal of pervading Quantum Computing through younger, less specialized, and diverse cultural and national communities.
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.