Free quantum computing software is an Open Source Fundament that maintains a curated number of available quantum software packages on GitHub. There are links towards the tool’s place, organized by software type and the language in which it was written. It includes several of the various headings here but also a number of other projects that are either fun or have been abandoned.
Additionally, there is a PLOS overview article that compares numerous open supplier that provides free quantum computing software applications based on features like documentation and discussion streams as well as issue tracking, configuration management, licenses, and automated test rigs, among other things.
Development Kit For Microsoft Quantum
Quantum Development Kit (QDK) is a promo poster version of Microsoft’s previous LIQUi|> software. There are simulators that run locally or even on the potent Azure cloud service, a recently renamed quantum computer language respondents, and a wealth of libraries as well as sample code that could be used as construction blocks.
Quantum Experimentation With IBM
For the first time, IBM has been going to allow members of the general public to apply for access to an exploratory 5 qubit entrance quantum processor. Among the four modules available just on the IBM Quantum Experience, the webpage is an instructional tutorial, a musician for configuring quantum gates again for qubits. A simulation game that allows one to test their setup before running that one on the physical machine, as well as finally, a direct link to the machine on its own, that also allows one to operate their setup and see the results.
Cloud Computing And Rigetti Forest (Qcs)
QVM (Quantum Virtual Machine) seems to be the name given to the Rigetti Forest suite, which includes an instruction programming language called Quil, an accessible Python reading room for building Quil programs, Grove, as well as a mathematical model called QVM (Quantum Virtual Machine).
Py Quil as well as Grove seem to be open-source programs that can be downloaded from GitHub.com. GitHub links, documentation, as well as other info, can be found on the Forest homepage. Its Rigetti subatomic hardware has been co-located with such a virtual traditional computing environment called QCS. You can access Rigetti’s QVM as well as QPU backends from the same place thanks to the Forest SDK.
ProjectQ
Developed in Python, ProjectQ seems to be an open-source structure for free quantum computing software. It provides a powerful as well as the intuitive syntax for implementing quantum programs in Python.
As a result of this translation, ProjectQ can run these programs on any sort of back-end, and including IBM Quantum Based on this external and any other quantum simulator. There will also be support for other hardware platforms in the future.
Its ProjectQ website provides connections to that code but also documentation, and also a library named FermiLib for solving fermionic quantum modeling problems.
Cirq
NISQ circuits can be written in Python using the Cirq open source library, which can then be run on quantum computers as well as simulators. OpenFermion-Cirq, a framework for creating quantum algorithms for laboratory problems, could also be used as this alpha discharge.
Cirq’s early adopters include a number of other software companies. Its Google AI Quantum Squad is promoting Cirq, but that is not google’s Official result.
CirqProjectQ
The two primary functions of Project Q are to connect ProjectQ and Cirq. The circuit is first and foremost a ProjectQ backend which converts an algorithm from ProjectQ to the Cirq. In addition to this, this could disintegrate ProjectQ common gates into native Xmon doors which could be used to replicate a search-free quantum computing software to ProjectQ in mind.
Pennylane & Strawberry Farms From Xanadu
Xanadu offers two different quantum computer coding software products. PennyLane, a cross-platform Python reading room for quantum computer vision, automatic differentiation, as well as enhancement of combination quantum-classical calculations, is the first one.
In addition to Xanadu’s constant various photonic new tech, PennyLane does have plug-ins for gate-based operating systems like ProjectQ as well as IBM’s Qiskit, making it an attractive platform. Another product, Cranberry Bogs, is a filled Library for python for the creation of CV quantum electro-optic circuits, like the quantum hardware being developed by Xanadu.
Open Q-Ctrl To Access Controls
Q-CTRL Using Open Controls, you can easily create and deploy error-resistant quantum control protocols that have been published in the available literature. Quantum control techniques that have been published as well as tested by that of the community are indeed the goal of this package.
Output functions allow the user to have these restrictions on specially made quantum hardware, general populace quantum cloud computer systems, or perhaps the Q-CTRL products in real.
Simulator For Intel’s Free Quantum Computing Software
As qHiPSTER, its Intel Quantum Simulator seems to be an open-source framework of a quantum simulator capable of simulating overall single-qubit gates as well as a controllable gate.
If you’re an algorithm development company that needs to test your software in simulation, the Intel Quantum Simulator (QS) is a great tool for you. There is an arXiv publication describing it all here, as well as a GitHub archive for it.
Mitiq
Error remediation techniques can be implemented over most existing intermediate-scale computing power using Mitiq, an open-source toolbox The Unitary Fund collaborates with the quantum software community to develop it.
Conversions to OpenQASM allow Mitiq to be used with quantum programs written for IBM Q’s Qiskit, Rigetti’s PyQuil, as well as basically anyone else quantum circuit formalism.
Using real devices or noisy simulators, researchers can reduce the noise in their race track. Zero-noise supposition techniques can be used with Mitiq to reduce errors when incorporating quantum circuit random samples with classical inference.
It is Berkeley Quantum Biosynthetic Toolkit (BQSKit) that incorporates elements from several initiatives there at Lawrence Livermore National Laboratory through an easy-to-use as well as a quickly extensible desktop application.
With this software, the primary goal should be to provide highly optimized compilations that minimize circuit intensity in comparison to certain other compilers like the ones that come with IBM’s Qiskit.” In addition to the Git repository, a web address has been set up to describe it.
Qcircuits seem to be a Python package designed to make quantum circuit simulation simple for learners to study. Predicated upon that quantum circuit model, everything just replicates the procedure of comparatively tiny quantum computers.
For input vectors as well as operators on processes with a large number of qubits, it employs tensors of type (d, 0, d) and type (d, d) instead of Kronecker products, which is more typical. Filled documentation and just a GitHub library can be found here.
Yao
Yao is indeed an open-source structure for quantum machine learning that is extensible and efficient. The quantum circuits throughout Yao can be programmed in a variety of ways. Simulating small and medium-sized quantum circuits which are pertinent to near-term application areas is achieved at the highest level of performance with this tool.
In comparison to other software platforms, it offers very competitive performance, at least for simulation studies involving 5-25 qubits. There is a lot of information about Yao available online, including the website, its GitHub repository, its benchmarking comparison news release, as well as an arXiv paper that provides a comprehensive overview.
Silq
ETH Zurich has invented a different high-level free quantum computing software language, Silq. Providing a language that allows for shorter, simplified, less error-prone, and thus more intuitive code than currently available lower-level procedural programming is the goal of this project.
On average, this one will reduce the number of lines of code inside a program by 46 percent compared to Q# and 38 percent compared to Quipper. Its most significant element would be that it automatically computes temporary values.
A reset of a momentary classical value is simpler, but this reset is more difficult so because momentary qubits are intertwined with some other qubits and thus can be reset in unexpected ways. Simulator support is the only hardware backend that Silq generates code for at this time. As the software gets better, we expect no changes. Here are the links to Silq’s official website, the GitHub page, and media releases describing it.
Take A Ride On The Quantum
PQ is indeed a quantum machine tool for learning set based on Baidu’s flying paddle. Quantum neural networks can be built and trained with the help of this software, which also allows easier quantum machine learning developer kits for applications such as quantum optimization but also quantum chemistry.
For the first time, a deep learning structure in China has support for quantum machine learning. Paddle Quantum was recently the subject of a blog post.
Tequila
TequilaFresh ideas for free quantum computing software can be implemented more quickly and easily thanks to Tequila, a Chapter will explain Quantum Knowledge and Learning Architecture (QILA). For the formulation, combination, and automatic distinctions and optimization of generalized objectives it uses abstract data structures.
It is possible for Tequila to carry out the underpinning quantum expectation value systems on cutting-edge simulators and on real quantum gadgets. Qulacs, Qiskit, Cirq, as well as PyQuil, are some of the backends that are currently supported.
Qlacs
Fast modeling of large, loud, or probit quantum circuits can be achieved using the python/C++ library Qulacs, established at the University Of Tokyo and retained by QunaSys, For example, Qulacs does have a graph on GitHub which shows that it outperforms its competitors because of its C/C++ back-end.
