The quantum algorithms could efficiently solve problems having exponential classical solutions [8]. The circuit model is considered as the most feasible implementation of the quantum algorithms [17]. This paper tries to find common ground between classical circuit design techniques and quantum computation, by identifying quantum circuit specification and simulation tools under the form of Hardware Description Languages (HDLs). The HDL-based simulation approach could reduce the complexity of quantum circuit simulation, by considering entanglement as the main source of gate-level simulation complexity, and isolating it in an automated manner. This is possible by taking advantage of the HDL feature of describing a circuit with both structural and functional architectures. We also performed an analysis of our methodology effectiveness, for the arithmetic circuits involved in Shor's algorithm and the circuits implementing Grover's algorithm. Our method is further improved by an entangled representation avoidance technique called 'bubble logic insertion'.
The quantum algorithms could efficiently solve problems having exponential classical solutions [8]. The circuit model is considered as the most feasible implementation of the quantum algorithms [17]. This paper tries to find common ground between classical circuit design techniques and quantum computation, by identifying quantum circuit specification and simulation tools under the form of Hardware Description Languages (HDLs). The HDL-based simulation approach could reduce the complexity of quantum circuit simulation, by considering entanglement as the main source of gate-level simulation complexity, and isolating it in an automated manner. This is possible by taking advantage of the HDL feature of describing a circuit with both structural and functional architectures. We also performed an analysis of our methodology effectiveness, for the arithmetic circuits involved in Shor's algorithm and the circuits implementing Grover's algorithm. Our method is further improved by an entangled representation avoidance technique called 'bubble logic insertion'.
When performed on a classical computer, the simulation of quantum circuits is usually an exponential job. The methodology based on Hardware Description Languages is able to isolate the entanglement as source of simulation complexity. However, it was shown that this methodology is not efficient in the presence of total entanglement, and the probability of such a situation grows exponentially with the number of qubits [ M. Udrescu, L. Prodan, M Vladutiu (2004) ]. The bubble bit technique is designed to avoid the entangled representation of the quantum state, thus allowing the HDL structural description of the quantum circuit, which requires polynomial resources for simulation. We provide experimental runtimes, obtained by simulation of quantum arithmetic and Grover's algorithm circuits, which indicate substantial runtime speedup.
Quantum computing emulators are widely used for testing quantum algorithms ideally before executing them on real quantum processors. Therefore, researchers are very active in developing emulators primarily on FPGAs. This project is complex and requires a long time and a specific expertise if carried out following the low-level design approach using a Hardware Description Language (HDL). This paper describes, step by step, the process of quick designing a quantum gate emulator using a much simpler high-level design approach. It begins with the development of a quantum gate simulator in the MATLAB® environment, and subsequently translates it into an HDL design for FPGA implementation by using the MATLAB’s HDL Coder toolbox. However, while code translation may seem straightforward using MATLAB toolboxes, it becomes a non-trivial task when transitioning from a quantum computing simulator to an HDL-based quantum computing emulator. Thus, it was necessary to conduct an in-depth study to implement a quantum computing simulator in MATLAB, enabling an error-free translation of HDL code. The developed method enables the designer to leverage the highly useful and straightforward model-based design approach offered by MATLAB, rather than directly the more complex HDL approach, returning a highly optimized HDL code for configuring the FPGA as a quantum computing emulator. This topic makes the design of quantum emulators on FPGA quick, reliable, optimized and without the need for specialized hardware design skills. Additionally, two implementation examples have been described using Intel FPGA on development boards DE1_SoC and DE5a-NET DDR4 provided by Terasic Inc.
While thousands of experimental physicists and chemists are currently trying to build scalable quantum computers, it appears that simulation of quantum computation will be at least as critical as circuit simulation in classical VLSI design. However, since the work of Richard Feynman in the early 1980s little progress was made in practical quantum simulation. Most researchers focused on polynomial-time simulation of restricted types of quantum circuits that fall short of the full power of quantum computation. Simulating quantum computing devices and useful quantum algorithms on classical hardware now requires excessive computational resources, making many important simulation tasks infeasible. In this work we propose a new technique for gate-level simulation of quantum circuits which greatly reduces the difficulty and cost of such simulations. The proposed technique is implemented in a simulation tool called the Quantum Information Decision Diagram (QuIDD) and evaluated by simulating Grover's quantum search algorithm. The back-end of our package, QuIDD Pro, is based on Binary Decision Diagrams, well-known for their ability to efficiently represent many seemingly intractable combinatorial structures. This reliance on a well-established area of research allows us to take advantage of existing software for BDD manipulation and achieve unparalleled empirical results for quantum simulation.
Abstract-Quantum theory of computation establishes that there are problems for which quantum algorithms are far more efficient than their classical counterpart. Advances in quantum computing have initiated the design of systems based on quantum logic gates. Quantum computer hardware being primarily available in research laboratories at present, it mandates the ability to design, develop and test quantum logic operations by simulation of quantum logic circuits on classical computers. In this paper, we have defined a programming model for the design of a quantum circuit simulator, which can simulate a given quantum circuit obeying the rules of quantum gate operations. The quantum gate operations on both pure and superposed quantum states are being done with the help of effective data structures. The proposed quantum circuit simulator also incorporates the simulation of quantum circuit error under the action of certain quantum faults.
Quantum computing is increasingly recognized as a promising approach for tackling computationally intractable problems. However, achieving the scalability necessary for real-world applications requires substantial advancements in the quantum software stack. In this work, we introduce a compiler toolchain based on a Multi-Level Intermediate Representation (MLIR) that automatically synthesizes quantum circuits from Hardware Description Language (HDL) specifications of classical functions into quantum assembly languages. Many quantum algorithms rely on combinatorial circuits as subroutines, which traditionally require extensive resources in terms of quantum gates and qubits and are often manually optimized. Our toolchain integrates a sequence of optimization passes that combine classical compiler techniques with quantum-specific improvements, resulting in an average qubit reduction of 30% and an average gate-count reduction of 20% in widely adopted benchmark circuits, including those used in cryptographic applications.
Quantum-mechanical phenomena are playing an increasing role in information processing as transistor sizes approach the nanometer level, while the securest forms of communication rely on quantum data encoding. When they involve a finite number of basis states, these phenomena can be modeled as quantum circuits, the quantum analogue of conventional or classical logic circuits. Simulation of quantum circuits can therefore be used as a tool to evaluate issues in the design of quantum information processors. Unfortunately, simulating such phenomena efficiently is exceedingly difficult. The matrices representing quantum operators (gates) and vectors modeling quantum states grow exponentially with the number of quantum bits. The information represented by quantum states and operators often exhibits structure that can be exploited when simulating certain classes of quantum circuits. We study the development of simulation methods that run on classical computers and take advantage of such repetitions and redundancies. In particular, we define a new data structure for simulating quantum circuits called the quantum information decision diagram (QuIDD). A QuIDD is a compressed graph representation of a vector or matrix and permits computations to be performed directly on the compressed data. We develop a comprehensive set of algorithms for operating on QuIDDs in both the state-vector and density-matrix formats, and evaluate their complexity. These algorithms have been implemented in a general-purpose simulator program for quantum-mechanical applications called QuIDDPro. Through extensive experiments conducted on representative quantum simulation applications, including Grover's search algorithm, error characterization, and reversible circuits, we demonstrate that QuIDDPro is faster than other existing quantum-mechanical simulators such as the National Institute of Standards and Technology's QCSim program, and is far more memory-efficient. Using QuIDDPro, we explore the advantages of quantum computation over classical computation, simulate quantum errors and error correction, and study the impact of numerical precision on the fidelity of simulations. We also develop several novel algorithms for testing quantum circuit equivalence and compare them empirically. The QuIDDPro software is equipped with a user-friendly interface and is distributed with numerous example scripts. It has been used as a laboratory supplement for quantum computing courses at several universities.