A circuit design interface for simulation of quantum circuits is presented. This simple but powerful tool aims to enable and improve experimentation in the field of quantum computing, either for professional or amateur usage. It provides an intuitive, automated, easy-to-use environment for building algorithms using the circuit model of quantum computation, while freeing the experimenter from technical procedures, such as coding or program installations. It provides a wide range of tools to the user, from a universal gate-set, to custom gate definitions, post-selected measurements, complex compositions of sub-circuits in a recursive way, good modularity and nice output results. Moreover, it is combined with popular backend simulators due to its circuit-parsing capabilities.
A circuit design interface for simulation of quantum circuits is presented. This simple but powerful tool aims to enable and improve experimentation in the field of quantum computing, either for professional or amateur usage. It provides an intuitive, automated, easy-to-use environment for building algorithms using the circuit model of quantum computation, while freeing the experimenter from technical procedures, such as coding or program installations. It provides a wide range of tools to the user, from a universal gate-set, to custom gate definitions, post-selected measurements, complex compositions of sub-circuits in a recursive way, good modularity and nice output results. Moreover, it is combined with popular backend simulators due to its circuit-parsing capabilities.
In this paper we introduce our new quantum circuit design tool. Based on quantum mechanical models a universal discrete-time quantum-network designer and simulator was implemented. The graphical user interface allows the user to design complex quantum networks efficiently. The component-based architecture enables independent researchers to use our simulator API (written in C), while we continue to expand and refine the C# based user interface. Future plans include components for distributed simulation and automated circuit design.
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.
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.
We introduce AriaQuanta, a powerful and flexible tool for designing, simulating, and implementing quantum circuits. This open-source software is designed to make it easy for users of all experience levels to learn and use quantum computing. The first version includes a compiler for implementing various quantum circuits and algorithms. Additionally, parametric circuits allow for the implementation of variational quantum algorithms, and various noise models are available for simulating noisy circuits. We performed numerous numerical simulations on AriaQuanta in various applications, including quantum algorithms and noisy circuits. The results, compared with popular counterparts, demonstrate the high performance of AriaQuanta.
Quantum circuit simulators play a crucial role in the design, validation, and testing of quantum algorithms on classical hardware. Although numerous simulators exist in the literature, creating complex quantum circuits, especially those with highly controlled and specialized gates, typically requires significant implementation effort and low-level programming. This study introduces KuadroSim, a developer-centric quantum circuit simulator designed to simplify and modularize the quantum circuit construction process. KuadroSim is based on statevector simulation using NumPy and employs procedural algorithms for automated multi-controlled gate synthesis, modular circuit composition, and direct custom gate integration via TFC (Toffoli–Fredkin–CNOT) modules. Rather than targeting improvements in asymptotic simulation complexity or execution speed, KuadroSim focuses on reducing circuit implementation complexity and improving developer efficiency. The effectiveness of the proposed approach is evaluated through a comparative experimental analysis, in which identical quantum circuits from the literature are implemented using KuadroSim and a conventional simulator. The results demonstrate a substantial reduction in code length and implementation effort when using KuadroSim, highlighting its advantages in terms of modularity, expressiveness, and workflow efficiency. These findings indicate that KuadroSim serves as a complementary tool to existing simulators, particularly for rapid prototyping, education, and early-stage quantum algorithm development.
With quantum computers promising advantages even in the near-term NISQ era, there is a lively community that develops software and toolkits for the design of corresponding quantum circuits. Although the underlying problems are different, expertise from the design automation community, which developed sophisticated design solutions for the conventional realm in the past decades, can help here. In this respect, decision diagrams provide a promising foundation for tackling many design tasks such as simulation, synthesis, and verification of quantum circuits. However, users of the corresponding tools often do not have a proper background or an intuition about how these methods based on decision diagrams work and what their strengths and limits are. In this work, we first review the concepts of how decision diagrams can be employed, e.g., for the simulation and verification of quantum circuits. Afterwards, in an effort to make decision diagrams for quantum computing more accessible, we then present a visualization tool for quantum decision diagrams, which allows users to explore the behavior of decision diagrams in the design tasks mentioned above. Finally, we present decision diagram-based tools for simulation and verification of quantum circuits using the methods discussed above as part of the open-source Munich Quantum Toolkit (MQT)—a set of tools for quantum computing developed at the Technical University of Munich and the Johannes Kepler University Linz and released under the MIT license. More information about the corresponding tools is available at https://github.com/cda-tum/ddsim . By this, we provide an introduction of the concepts and tools for potential users who would like to work with them as well as potential developers aiming to extend them.