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Open-source software tools and Quantum frameworks enabling developers to build quantum computer applications in AI, machine learning, big data science, and optimisation

Goups including IBM, Google, MIT Lincoln Lab  are at the threshold of producing scalable general purpose quantum computers. The leader of Google’s quantum computing lab, has predicted that he can build chips with about 100 reliable qubits in a couple of years. Its  group has built a nine-qubit machine based on tiny, superconducting circuits and hopes to scale up to 49 within a year—an important threshold. At about 50 qubits, many say a quantum computer could achieve “quantum supremacy,” a term coined by John Preskill, a physicist at the California Institute of Technology in Pasadena, to denote a quantum computer that can do something beyond the ken of a classical computer, such as simulate molecular structures in chemistry and materials science, from code-breaking and cyber security to big data analysis and machine learning.


D-Wave is now planning to release  the new quantum chip will be able to handle some 2,000 quantum bits (qubits), roughly double the usable number found in the processor in the existing D-Wave 2X system, and be capable of solving certain problems 1,000x faster than its predecessor.  However, D-Wave Two is not a universal quantum computer, It has been designed specifically to perform a process called “quantum annealing”, which is a technique for finding the global minimum of a complicated mathematical expressions hence expected to be capable of solving optimization and sorting problems exponentially faster than a classical computer.


The technology could usher in a much-anticipated era of quantum computing, which researchers say could help scientists run complex simulations and produce rapid solutions to tricky calculations. Quantum computing and quantum information processing are next revolutionary technology expected to have immense impact. Quantum computers could accelerate the discovery of new materials, chemicals and drugs. They could dramatically reduce the current high costs and long lead times involved in developing new drugs. However, the forthcoming quantum leap in information technology depends essentially on our improved understanding of quantum algorithms and complexity.


Researchers at Microsoft are working on an entirely new topological quantum computer, which uses exotic materials to limit errors. At the same time as Microsoft is working to build a quantum computer, it is also creating the software that could run on it. The goal is to have a system that can begin to efficiently solve complex problems from day one.


Microsoft has released a preview version of their Quantum Development Kit that appears to supercede their earlier LIQUi|> software. This kit features a newly named quantum programming language called Q#, integration with their Visual Studio development environment, simulators that run on either a local system or their powerful Azure cloud platform, and rich libraries and code samples that can be used as building blocks.


“Similar to classical high-performance computing, we need not just hardware but also optimized software,” Troyer said. To the team, that makes sense: The two systems can work together to solve certain problems and the research from each can help the other side. “A quantum computer is much more than the qubits,” Reilly said. “It includes all of the classical hardware systems, interfaces and connections to the outside world.”

Sydney quantum start-up Q-CTRL launches world first product with quantum control software

Sydney start-up Q-CTRL has launched its inaugural product – Black Opal – which it describes as “the world’s first commercially available software suite designed to improve the performance of quantum computing hardware”. Quantum systems are highly susceptible to decoherence. The states of quantum bits, or qubits, in quantum computers are quickly randomised by interference from the environment. Q-CTRL’s toolkit help teams design and deploy control for their quantum hardware in order to suppress these errors.
“Quantum control has for a long time been thought of as a bit of black art. Those of us who were deeply ingrained in it understood the capabilities it brings, but many others would only dip their toes in the water and that was enough,” explains Q-CTRL founder University of Sydney Professor Michael Biercuk. “We’re aiming to remove those barriers, remove the friction points that have prevented teams from taking advantage of everything that’s possible,” he adds. The controls in the toolkit were described by Biercuk as being able to “effectively turn back the clock” on decoherence. “So all the randomisation that occurs, unwinds; it’s like unmixing the soup,” he told Computerworld last year.


While many of the major players in quantum computing will have quantum control teams working towards similar outcomes, Black Opal provides the same in a SaaS offering. The SaaS model means Q-CTRL will add new features on a “roughly weekly basis” Biercuk says. In the coming months the team will also launch Boulder Opal, focused on automation and integration of control solutions into professional workflows. Enterprise versions and API access to developers are also planned.


“Black Opal helps our team directly leverage Q-CTRL’s deep expertise in quantum control to solve some of our toughest problems building a new class of application-specific quantum computers,” said early Q-CTRL customer Dr Alexei Marchenkov, founder and CEO of Bleximo, a quantum technology company based in California. “This software – and its focus on high-quality visualisations – enables us to build intuition for very complicated concepts outside of our core areas of expertise,” Marchenkov added.

Google new open-source software will help developers experiment with the machines, including Google’s own super-powerful quantum processor.

Google  has just released Cirq, a software toolkit that lets developers create algorithms without needing a background in quantum physics. Cirq is an open-source initiative, which means anyone can access and modify the software. Google likens it to its popular TensorFlow open source toolkit that has made it easier to build machine-learning software. For now, developers can use Cirq to create quantum algorithms that run on simulators. But the goal is to have it help build software that will run on a wide range of real machines in the future.


The tech giant has also released OpenFermion-Cirq, a toolkit for creating algorithms that simulate molecules and properties of materials. Indeed, chemistry is among the applications in which quantum computers are likely to be of most use in the short term. One of the companies that worked with Google on Cirq’s development is Zapata Computing, whose early focus is on software for chemistry and materials (see “The world’s first quantum superstore—or so it hopes—is here”).

Zapata boasts of quantum optimisation breakthrough

Harvard University spin-out Zapata Computing claimed that  using Google’s Cirq quantum framework it has implemented a new algorithm dubbed CUSP which could reduce complex problems to a level where they can be implemented on near-term minimal-cubit quantum processors.


CUSP is a quantum circuit optimiser that dramatically improves quantum algorithm efficiency. This algorithm and others like it will hasten breakthroughs and enable the next generation of discoveries in chemistry, materials, and artificial intelligence.’


Designed for algorithms too complex to fit on the smaller quantum computers we can build with today’s technology and too large to be optimised by hand, Zapata’s CUSP could potentially allow for a leapfrog in quantum computing technology by allowing scientists to implement workloads that would otherwise have had to wait for higher-qubit hardware to become available.



ProjectQ is an open-source software framework for quantum computing implemented in Python. It allows users to implement their quantum programs in Python using a powerful and intuitive syntax. ProjectQ can then translate these programs to any type of back-end, be it a simulator run on a classical computer or an actual quantum chip including the IBM Quantum Experience platform. Other hardware platforms will be supported in the future. Links to all the code and documentation as well as well as a library called FermiLib to analyze fermionic quantum simulation problems can be found at the ProjectQ web site here.

QX Quantum Computing Simulator

The QX Simulator is a universal quantum computer simulator developed at QuTech. The QX allows quantum algorithm designers to simulate the execution of their quantum circuits on a quantum computer. The simulator defines a low-level quantum assembly language namely Quantum Code which allows the users to describe their circuits in a simple textual source code file. The source code file is then used as the input of the simulator which executes its content.


Raytheon BBN Open Source Software

Raytheon BBN is make available three open source software programs related to Quantum Computing.

Qlab – A MATLAB control framework for superconducting qubit systems.
PySimulator – A python/C++ framework for master equation simluation of qubit systems.
PyQLab – A python framework for superconducting qubit systems. Includes Quantum Gate Language (QGL) for compactly writing QIP pulse programs


Quantum Algorithm Zoo

Stephen Jordan from NIST has cataloged dozens of different algorithms that could theoretically offer substantial speedup when run on a quantum computer. Each algorithm is described in a single paragraph that also includes an estimate of the speedup and links to references and technical papers that described the algorithm in more detail. The link to this comprehensive catalog is here.



IBM makes available five qubit general purpose quantum computer for developing Quantum software

IBM Research has also made quantum computing available to members of the public, who can access and run experiments on IBM’s quantum processor. IBM scientists have built a quantum processor that users can access through a first-of-a-kind quantum computing platform delivered via the IBM Cloud onto any desktop or mobile device. The cloud-enabled quantum computing platform, called IBM Quantum Experience, will allow users to run algorithms and experiments on IBM’s quantum processor, work with the individual quantum bits (qubits), and explore tutorials and simulations around what might be possible with quantum computing.


At the IBM Quantum Experience website there are four modules; a short tutorial that explains the basics of quantum computation and instructions on how to use it, a quantum composer that allows one to configure quantum gates for the qubits, a simulator which allows one to simulate their configuration before running it on the actual machine, and finally access to the machine itself which allows one to run their configuration and view the results.


IBM have developed the Quantum Information Software Kit (QISKit), which is a full-stack library to write, simulate and run quantum programs. Recently, they have divided it in four pieces: Terra, which allows to program at the level of quantum gates and pulses (quantum gates are implemented with sequences of pulses); Aqua, a higher level of programming to run algorithms used in quantum chemistry, optimization problems and A.I.; Ignis, to characterize errors and improve gate implementation; Aer, to study the limits of quantum computation using simulations in classical devices. QISKit translates quantum programs into a lower level language called QASM, which is its quantum instruction language





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