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.
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.
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.
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.
The rapid advancement of Noisy Intermediate-Scale Quantum (NISQ) devices has driven the need for efficient design automation tools that can translate complex engineering models into executable quantum circuits. This study explores the development of automated quantum circuit design frameworks focused on gate optimization and noise-aware compilation, enabling practical quantum computation for engineering applications such as optimization, simulation, and control systems. Traditional circuit design methods often fail to account for hardware constraints, decoherence, and gate infidelity, which significantly affect computational accuracy on NISQ devices. To address these challenges, this research introduces a hybrid automation approach combining quantum transpilation, variational circuit pruning, and error-aware synthesis algorithms to enhance circuit reliability and scalability. The framework integrates quantum-classical co-design principles to optimize both logical and physical circuit layers, leveraging hardware-specific calibration data to adapt compilation strategies dynamically. Through simulations and benchmark analysis, the proposed system demonstrates significant improvements in quantum resource utilization, error mitigation, and gate depth reduction compared to conventional compilation methods. This work underscores the growing importance of design automation in quantum engineering, where algorithmic efficiency must be harmonized with physical constraints to realize functional and scalable quantum workflows. By establishing a methodology for gate-level optimization and noise-adaptive design, the study contributes to bridging the gap between theoretical quantum algorithms and real-world engineering implementations within the NISQ computing era.
Quantum circuit simulation is essential for researchers to develop and evaluate novel quantum algorithms with classical computers. Although full-state quantum circuit simulations are widely utilized for prototyping and debugging, they are computationally intensive due to the exponential growth in simulation time as the system size grows. To address the performance bottlenecks associated with conventional gate-by-gate simulation, this work refines the block-by-block simulation paradigm through blocking optimization, taking into account the architectural characteristics of hardware. The primary contribution of this research is the gate block search algorithm (GBSA), which efficiently groups the maximum number of quantum gates into gate blocks. This grouping technique enhances data reuse and reduces redundant memory accesses and I/O overhead during gate application. The proposed method is evaluated using both gate-level and circuit-level benchmarks on an AMD 64-core processor. Compared to conventional gate-by-gate simulators, such as QuEST and AerSimulator, the proposed approach achieves up to a 4.7× speedup in CPU execution and a 2.9× speedup in SSD-based scenarios. Furthermore, it can lead to a remarkable 46× reduction in memory and I/O traffic. These results indicate that the proposed block-based simulation strategy substantially improves the efficiency of quantum circuit simulation and can be readily adapted to multi-device environments, thereby supporting the rapid development of next-generation quantum algorithms.
We present a new software package for efficient quantum circuit generation, designed to achieve optimal runtime performance. Despite being in an early stage of development, our implementation demonstrates significant advantages over existing tools. Using the quantum Fourier transform (QFT) as a benchmark, we show that our backend can generate circuits for systems with up to 2000 qubits faster than widely used frameworks such as Qiskit and Q#. This improvement is particularly relevant for applications where classical preprocessing time, including circuit generation, must be minimized to not diminish any potential quantum advantage - for example, in combinatorial optimization tasks. Additionally, our software provides high-level primitives for bit- and integer-level manipulations, offering a simplified interface for integration with high-level quantum programming languages.
Quantum circuit simulation is paramount to the verification and optimization of quantum algorithms, and considerable research efforts have been made towards efficient simulators. While circuits often contain high-level gates such as oracles and multi-controlled X ( C k X ) gates, existing simulation methods require compilation to a low-level gate-set before simulation. This, however, increases circuit size and incurs a considerable (typically exponential) overhead, even when the number of high-level gates is small. Here we present a gadget-based simulator which simulates high-level gates directly, thereby allowing to avoid or reduce the blowup of compilation. Our simulator uses a stabilizer decomposition of the magic state of non-stabilizer gates, with improvements in the rank of the magic state directly improving performance. We then proceed to establish a small stabilizer rank for a range of high-level gates that are common in various quantum algorithms. Using these bounds in our simulator, we improve both the theoretical complexity of simulating circuits containing such gates, and the practical running time compared to standard simulators found in IBM's Qiskit Aer library. We also derive exponential lower-bounds for the stabilizer rank of some gates under common complexity-theoretic hypotheses. In certain cases, our lower-bounds are asymptotically tight on the exponent.