Quantum computation is a radical new candidate for a technology that is capable to make a paradigm shift in information processing. However, current promising devices are limited in performance due to many decoherence mechanisms. Quantum computer simulators are thus important for understanding and solving existing problems of the current noisy intermediate-scale quantum (NISQ) processors. In this work, we present Psitrum – a universal gate-model based quantum computer simulator implemented on classical hardware. The simulator allows to emulate and debug quantum algorithms in form of quantum circuits for many applications with the choice of adding quantum noise that limit coherence of quantum circuits. Psitrum allows to keep track of quantum operations and density matrices, and provides variety of unique visualisation tools. The simulator allows to trace out all possible quantum states at each stage M of an N-qubit implemented quantum circuit. The design of Psitrum is flexible and allows users later to add their special quantum gates and variety of noise modules.
Quantum computation is a radical new candidate for a technology that is capable to make a paradigm shift in information processing. However, current promising devices are limited in performance due to many decoherence mechanisms. Quantum computer simulators are thus important for understanding and solving existing problems of the current noisy intermediate-scale quantum (NISQ) processors. In this work, we present Psitrum – a universal gate-model based quantum computer simulator implemented on classical hardware. The simulator allows to emulate and debug quantum algorithms in form of quantum circuits for many applications with the choice of adding quantum noise that limit coherence of quantum circuits. Psitrum allows to keep track of quantum operations and density matrices, and provides variety of unique visualisation tools. The simulator allows to trace out all possible quantum states at each stage M of an N-qubit implemented quantum circuit. The design of Psitrum is flexible and allows users later to add their special quantum gates and variety of noise modules.
Abstract Quantum computing is a radical new paradigm for a technology that is capable to revolutionize information processing. Simulators of universal quantum computer are important for understanding the basic principles and operations of the current noisy intermediate-scale quantum (NISQ) processors, and for building in future fault-tolerant quantum computers. In this work, we present simulation of universal quantum computers by introducing Psitrum – a universal gate-model quantum computer simulator implemented on classical hardware. The simulator allows to emulate and debug quantum algorithms in form of quantum circuits for many applications with the choice of adding variety of noise modules to simulate decoherence in quantum circuits. Psitrum allows to simulate all basic quantum operations and provides variety of visualization tools. The simulator allows to trace out all possible quantum states at each stage M of an N-qubit implemented quantum circuit. Psitrum software and source codes are freely available at: https://github.com/MoGhadeer/Psitrum.
Abstract Quantum computing is a radical new paradigm for a technology that is capable to revolutionise information processing. Simulators of universal quantum computer are important for understanding the basic principles and operations of the current noisy intermediate‐scale quantum processors, and for building in future fault‐tolerant quantum computers. As next‐generation quantum technologies continue to advance, it is crucial to address the impact on education and training in quantum physics. The emergence of new industries driven by progress in quantum computing and simulation will create a demand for a specialised quantum workforce. In response to these challenges, the authors present Psitrum, an open‐source simulator for universal quantum computers. Psitrum serves as a powerful educational and research tool, enabling a diverse range of stakeholders to understand the fundamental principles and operations of quantum systems. By offering a comprehensive platform for emulating and debugging quantum algorithms through quantum circuits, Psitrum aids in the exploration and analysis of various quantum applications using both MATLAB and MATLAB application programming interface to use the software on other platforms. Psitrum software and source codes are fully available at GitHub.
Quantum computing promises an exponential speedup improvement in the time required to solve certain computational problems by leveraging the principles of quantum mechanics.While the potential power of quantum computers is well-established, their practical implementation poses significant challenges ranging from scalability to decoherence and noise.This paper presents QPy, a Python-based quantum circuit simulator that I programmed and designed to track the quantum state of a model quantum computer through the application of quantum gates to qubits.By performing the requisite matrix calculations, the simulator facilitates the understanding of quantum algorithms through the visualization of the underlying mathematics.This tool enables researchers to explore and implement various quantum protocols efficiently to test and build algorithms.
In the effort to develop useful quantum computers, simulating quantum machines with conventional classical computing resources is a key capability. Such simulations will always face limits, preventing the emulation of quantum computers at substantial scale; however, by pushing the envelope through optimal choices of algorithms and hardware, the value of simulator tools can be maximized. This work reviews state-of-the-art numerical simulation methods, i.e., classical algorithms that emulate quantum computer evolution under specific operations. We focus on the mainstream state-vector and tensor-network paradigms, while briefly mentioning alternative methods. Moreover, we review the diverse applications of simulation across different facets of quantum computer development, including understanding the fundamental differences between quantum and classical computations, exploring algorithmic design for quantum advantage, predicting quantum processor performance at the design stage, and efficiently characterizing fabricated devices for rapid iterations. This review complements recent surveys of current tools and implementations; here, we aim to provide readers with an essential understanding of the theoretical basis of classical simulation methods, a detailed discussion of their advantages and limitations, and an overview of the demands and challenges arising from practical use cases.
Quantum computers have emerged as an alternative computer paradigm that will allow to solve some complex problems of large numbers that are not tractable for classical computers, e.g. factorization. Quantum computers also have the ability to simulate quantum mechanics in a real and direct way. The development of quantum computers faces many unique obstacles. In recent years, various quantum computer prototypes have been created by com- panies such as Google and IBM, on which we can run some quantum algorithms. But these prototypes are far from the quantum computers we envision and can function like today?s classical computers. It is said that we are in the time of Noisy Intermediate-Scale Quantum (NISQ) computers. This means that current quantum computers are very noisy and their size is very small compared to classical comput- ers. The challenge with small, noisy quantum devices running quantum algorithms is that due to the hardware limitations they face which must be respected, quantum algorithm needs to be modified before their execution on quantum devices. To solve this problem in quantum computers, a mapping process is needed, which is part of the compilation step that modifies the quantum algorithms to take into account all the limitations of the targeted quantum device. After mapping process, the resulting quantum circuit usually has a higher number of gates and (execution time) latency, decreasing the algorithm?s reliability. Different mapping solutions have been already proposed. Most of them are meant for a specific quan- tum processor and different in methodology, approach and features. In addition, they are usually only compared in terms of added gates (gate overhead) or added circuit execution time (latency overhead). No thorough comparative analysis of the different mapping solutions performance and features has been performed so far. In this thesis, we apply structured Design Space Exploration to the mapping of quantum circuits. By doing so, we will be able to have a deeper understanding of this process, make a thorough comparison of the mapper approaches and even develop optimized solutions for given applications and quantum devices. Moreover, we apply Design Space Exploration to the generation of quantum algorithms used as benchmarks and start to explore profiling them in a structured approach.
The rapid advancement of quantum computing has created new opportunities for solving computationally intensive problems across diverse fields such as optimization, physical system simulation, and machine learning. However, practical implementation on Noisy Intermediate-Scale Quantum (NISQ) devices remains challenging due to hardware limitations including noise, decoherence, and restricted qubit connectivity. A fundamental constraint further complicating this effort is that all quantum operations must be unitary, while many real-world problems are naturally expressed in non-unitary forms. This discrepancy necessitates novel techniques for transforming non-unitary mathematical structures into unitary or Hamiltonian representations compatible with quantum hardware.This thesis proposes a unified framework for converting structured, sparse, or otherwise non-unitary classical matrices into unitary forms that can be executed efficiently on NISQ devices. The methodology introduces general transformation strategies such as linear combinations of unitaries, structured embeddings, and resource-aware circuit construction, enabling the deployment of quantum algorithms without incurring prohibitive overhead. Each technique is developed with an emphasis on preserving problem structure, minimizing circuit depth, and ensuring compatibility with IBM’s NISQ hardware. The proposed frameworks are validated through theoretical analysis and quantum simulations, with performance benchmarks based on gate count, circuit fidelity, convergence behavior, and scalability. This work demonstrates how non-unitary formulations arising in various computational contexts can be systematically adapted for quantum execution, advancing the practical utility of NISQ-era devices.