Abstract. We present the basic high-level structures used for developing quantum programming languages. The presented structures are commonly used in many existing quantum programming languages and we use quantum pseudo-code based on QCL quantum programming language to describe them. We also present the implementation of introduced structures in GNU Octave language for scientific computing. Procedures used in the implementation are available as a package quantum-octave providing library of functions, which facilitates the simulation of quantum computing. This package allows also to incorporate high-level programming concepts into the simulation in GNU Octave and Matlab. As such it connects features unique for higl-level quantum programming languages, with the full palette of efficient computational routines commonly available in modern scientific computing systems. To present the major features of the described package we provide the implementation of selected quantum algorithms. We also show how quantum errors can be taken into account during the simulation of quantum algorithms using quantum-octave package. This is possible thanks to the ability to operate on density matrices implemented in quantum-octave. Key words: quantum information, quantum programming, models of quantum computation. 1.
Abstract. We present the basic high-level structures used for developing quantum programming languages. The presented structures are commonly used in many existing quantum programming languages and we use quantum pseudo-code based on QCL quantum programming language to describe them. We also present the implementation of introduced structures in GNU Octave language for scientific computing. Procedures used in the implementation are available as a package quantum-octave providing library of functions, which facilitates the simulation of quantum computing. This package allows also to incorporate high-level programming concepts into the simulation in GNU Octave and Matlab. As such it connects features unique for higl-level quantum programming languages, with the full palette of efficient computational routines commonly available in modern scientific computing systems. To present the major features of the described package we provide the implementation of selected quantum algorithms. We also show how quantum errors can be taken into account during the simulation of quantum algorithms using quantum-octave package. This is possible thanks to the ability to operate on density matrices implemented in quantum-octave. Key words: quantum information, quantum programming, models of quantum computation. 1.
We present a basic high-level structures used for developing quantum programming languages. The presented structures are commonly used in many existing quantum programming languages and we use quantum pseudo-code based on QCL quantum programming language to describe them. We also present the implementation of introduced structures in GNU Octave language for scientific computing. Procedures used in the implementation are available as a package quantum-octave, providing a library of functions, which facilitates the simulation of quantum computing. This package allows also to incorporate high-level programming concepts into the simulation in GNU Octave and Matlab. As such it connects features unique for high-level quantum programming languages, with the full palette of efficient computational routines commonly available in modern scientific computing systems. To present the major features of the described package we provide the implementation of selected quantum algorithms. We also show how quantum errors can be taken into account during the simulation of quantum algorithms using quantum-octave package. This is possible thanks to the ability to operate on density matrices.
Article presents package of functions for GNU Octave computer algebra system. Those functions were designed to perform simple but not necessary efficient simulations of quantum systems, especially quantum computers. The most important feature of this package is the ability to perform calculations with mixed states.We describe application of quantum-octave package for simulation of Grovers algorithm, which is one of the most important quantum algorithms. We also list other possible calculations, which can be performed with this package.
We propose the design of a programming language for quantum computing. Traditionally, quantum algorithms are frequently expressed at the hardware level, for instance in terms of the quantum circuit model or quantum Turing machines. These approaches do not encourage structured programming or abstractions such as data types. In this paper, we describe the syntax and semantics of a simple quantum programming language with high-level features such as loops, recursive procedures, and structured data types. The language is functional in nature, statically typed, free of run-time errors, and has an interesting denotational semantics in terms of complete partial orders of superoperators.
Quantum computing is a promising approach of computation that is based on equations from Quantum Mechanics. A simulator for quantum algorithms must be capable of performing heavy mathematical matrix transforms. The design of the simulator itself takes one of three forms: Quantum Turing Machine, Network Model or circuit model of connected gates or, Quantum Programming Language, yet, some simulators are hybrid. We studied previous simulators and then we adopt features from three simulators of different implementation languages, different paradigms, and for different platforms. They are Quantum Computing Language (QCL), QUASI, and Quantum Optics Toolbox for Matlab 5. Our simulator for quantum algorithms takes the form of a package or a programming library for Quantum computing, with a case study showing the ability of using it in the circuit model. The .NET is a promising platform for computing. VB.NET is an easy, high productive programming language with the full power and functionality provided by the .NET framework. It is highly readable, writeable, and flexible language, compared to another language such as C#.NET in many aspects. We adopted VB.NET although its shortage in built-in mathematical complex and matrix operations, compared to Matlab. For implementation, we first built a mathematical core of matrix operations. Then, we built a quantum core which contains: basic qubits and register operations, basic 1D, 2D, and 3D quantum gates, and multi-view visualization of the quantum state, then a window for demos to show you how to use and get the most of the package.
Quantum algorithms are known to be more powerful than their classical counterparts, in the sense that they offer huge speed-ups as opposed to their classical counterparts. Physical realization of quantum algorithms results in the building of quantum circuits, which are in turn used to build a quantum computer. Unfortunately, a full-scale quantum computer is yet to be realized, hence why quantum algorithms are currently modelled on classical computers. In this work, we report the simulation of quantum circuits using GNU Octave and Python Programming languages. Additionally, performance of these languages on simulating such circuits is compared. Quantum circuits simulated are: the circuit for preparing a two-qubit entanglement (Einstein-Podolsky-Rosen (EPR) state), the one for preparing a three-qubit entanglement (Greenberger-Horne-Zeilinger (GHZ) state), swap circuit and Quantum Fourier Transform (QFT).
This study considers implementations of error correction in a simulation language on a classical computer. Error correction will be necessarily in quantum computing and quantum information. We will give some examples of the implementations of some error correction codes. These implementations will be made in a more general quantum simulation language on a classical computer in the language Mathematica. The intention of this research is to develop a programming language that is able to make simulations of all quantum algorithms and error corrections in the same framework. The program code implemented on a classical computer will provide a connection between the mathematical formulation of quantum mechanics and computational methods. This gives us a clear uncomplicated language for the implementations of algorithms.