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Vitali Socks
Vitali Socks

Programming Quantum Computers

Quantum programming is the process of assembling sequences of instructions, called quantum circuits, that are capable of running on a quantum computer. Quantum programming languages help express quantum algorithms using high-level constructs.[1] The field is deeply rooted in the open-source philosophy and as a result most of the quantum software discussed in this article is freely available as open-source software.[2]

Programming Quantum Computers

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Quantum instruction sets are used to turn higher level algorithms into physical instructions that can be executed on quantum processors. Sometimes these instructions are specific to a given hardware platform, e.g. ion traps or superconducting qubits.

cQASM,[3] also known as common QASM, is a hardware-agnostic quantum assembly language which guarantees the interoperability between all the quantum compilation and simulation tools. It was introduced by the QCA Lab at TUDelft.

Quil is an instruction set architecture for quantum computing that first introduced a shared quantum/classical memory model. It was introduced by Robert Smith, Michael Curtis, and William Zeng in A Practical Quantum Instruction Set Architecture.[4] Many quantum algorithms (including quantum teleportation, quantum error correction, simulation,[5][6] and optimization algorithms[7]) require a shared memory architecture.

Blackbird[9][10] is a quantum instruction set and intermediate representation used by Xanadu Quantum Technologies and Strawberry Fields. It is designed to represent continuous-variable quantum programs that can run on photonic quantum hardware.

Quantum software development kits provide collections of tools to create and manipulate quantum programs.[11] They also provide the means to simulate the quantum programs or prepare them to be run using cloud-based quantum devices and self-hosted quantum devices.

An open-source project created by Quandela [fr] for designing photonic quantum circuits and developing quantum algorithms, based on Python. Simulations are run either on the user's own computer or on the cloud. Perceval is also used to connect to Quandela's cloud-based photonic quantum processor.[12][13]

An Open Source suite of tools developed by D-Wave. Written mostly in the Python programming language, it enables users to formulate problems in Ising Model and Quadratic Unconstrained Binary Optimization formats (QUBO). Results can be obtained by submitting to an online quantum computer in Leap, D-Wave's real-time Quantum Application Environment, customer-owned machines, or classical samplers.[citation needed]

An Open Source project developed at the Institute for Theoretical Physics at ETH, which uses the Python programming language to create and manipulate quantum circuits.[14] Results are obtained either using a simulator, or by sending jobs to IBM quantum devices.

An Open Source project developed by IBM.[15] Quantum circuits are created and manipulated using Python. Results are obtained either using simulators that run on the user's own device, simulators provided by IBM or prototype quantum devices provided by IBM. As well as the ability to create programs using basic quantum operations, higher level tools for algorithms and benchmarking are available within specialized packages.[16] Qiskit is based on the OpenQASM standard for representing quantum circuits. It also supports pulse level control of quantum systems via QiskitPulse standard.[17]

An open source full-stack API for quantum simulation, quantum hardware control and calibration developed by multiple research laboratories, including QRC, CQT and INFN. Qibo is a modular framework which includes multiple backends for quantum simulation and hardware control.[18][19] This project aims at providing a platform agnostic quantum hardware control framework with drivers for multiple instruments[20] and tools for quantum calibration, characterization and validation.[21] This framework focuses on self-hosted quantum devices by simplifying the software development required in labs.

An open source project developed by Rigetti, which uses the Python programming language to create and manipulate quantum circuits. Results are obtained either using simulators or prototype quantum devices provided by Rigetti. As well as the ability to create programs using basic quantum operations, higher level algorithms are available within the Grove package.[22] Forest is based on the Quil instruction set.

An open-source Python library developed by Xanadu Quantum Technologies for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.[24][25] Three simulators are provided - one in the Fock basis, one using the Gaussian formulation of quantum optics,[26] and one using the TensorFlow machine learning library. Strawberry Fields is also the library for executing programs on Xanadu's quantum photonic hardware.[27][28]

A project developed by Microsoft[36] as part of the .NET Framework. Quantum programs can be written and run within Visual Studio and VSCode using the quantum programming language Q#. Programs developed in the QDK can be run on Microsoft's Azure Quantum,[37] and run on quantum computers from Quantinuum,[33] IonQ, and Pasqal.[38]

An Open Source project developed by Google, which uses the Python programming language to create and manipulate quantum circuits. Programs written in Cirq can be run on IonQ, Pasqal,[38] Rigetti, and Alpine Quantum Technologies.[34]

Quantum Computation Language (QCL) is one of the first implemented quantum programming languages.[42] The most important feature of QCL is the support for user-defined operators and functions. Its syntax resembles the syntax of the C programming language and its classical data types are similar to primitive data types in C. One can combine classical code and quantum code in the same program.

Quantum pseudocode proposed by E. Knill is the first formalized language for description of quantum algorithms. It was introduced and, moreover, was tightly connected with a model of quantum machine called Quantum Random Access Machine (QRAM).

QSI> is a platform embedded in .Net language supporting quantum programming in a quantum extension of while-language.[41][44] This platform includes a compiler of the quantum while-language[45] and a chain of tools for the simulation of quantum computation, optimisation of quantum circuits, termination analysis of quantum programs,[46] and verification of quantum programs.[47][48]

Q Language is the second implemented imperative quantum programming language.[49] Q Language was implemented as an extension of C++ programming language. It provides classes for basic quantum operations like QHadamard, QFourier, QNot, and QSwap, which are derived from the base class Qop. New operators can be defined using C++ class mechanism.

The Logic of Quantum Programs (LQP) is a dynamic quantum logic, capable of expressing important features of quantum measurements and unitary evolutions of multi-partite states, and provides logical characterizations of various forms of entanglement. The logic has been used to specify and verify the correctness of various protocols in quantum computation. [55][56]

Efforts are underway to develop functional programming languages for quantum computing. Functional programming languages are well-suited for reasoning about programs. Examples include Selinger's QPL,[57] and the Haskell-like language QML by Altenkirch and Grattage.[58][59] Higher-order quantum programming languages, based on lambda calculus, have been proposed by van Tonder,[60] Selinger and Valiron[61] and by Arrighi and Dowek.[62]

QFC and QPL are two closely related quantum programming languages defined by Peter Selinger. They differ only in their syntax: QFC uses a flow chart syntax, whereas QPL uses a textual syntax. These languages have classical control flow but can operate on quantum or classical data. Selinger gives a denotational semantics for these languages in a category of superoperators.

An operational semantics for QML is given in terms of quantum circuits, while a denotational semantics is presented in terms of superoperators, and these are shown to agree. Both the operational and denotational semantics have been implemented (classically) in Haskell.[64]

LIQUi> (pronounced liquid) is a quantum simulation extension on the F# programming language.[65] It is currently being developed by the Quantum Architectures and Computation Group (QuArC)[66] part of the StationQ efforts at Microsoft Research. LIQUi> seeks to allow theorists to experiment with quantum algorithm design before physical quantum computers are available for use.[67]

It includes a programming language, optimization and scheduling algorithms, and quantum simulators. LIQUi> can be used to translate a quantum algorithm written in the form of a high-level program into the low-level machine instructions for a quantum device.[68]

Quantum lambda calculi are extensions of the classical lambda calculus introduced by Alonzo Church and Stephen Cole Kleene in the 1930s. The purpose of quantum lambda calculi is to extend quantum programming languages with a theory of higher-order functions.

The first attempt to define a quantum lambda calculus was made by Philip Maymin in 1996.[69]His lambda-q calculus is powerful enough to express any quantum computation. However, this language can efficiently solve NP-complete problems, and therefore appears to be strictly stronger than the standard quantum computational models (such as the quantum Turing machine or the quantum circuit model). Therefore, Maymin's lambda-q calculus is probably not implementable on a physical device[citation needed].

Quipper was published in 2013.[72][73] It is implemented as an embedded language, using Haskell as the host language.[74] For this reason, quantum programs written in Quipper are written in Haskell using provided libraries. For example, the following code implements preparation of a superposition

The field of quantum computation has made rapid progress just in the last few years. In 2016, IBM put the first quantum computer on the cloud, expanding the reach of the technology beyond research laboratories. Our goal is to make quantum computing available to anyone who is interested, and to help prepare a quantum-ready workforce that can translate industry challenges into problems that quantum computers can solve. 041b061a72


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