To the untrained eye, a circuit built with IBM’s online Quantum Experience tool looks like something out of an introductory computer-science course. Logic gates, the building blocks of computing, are built on digital canvas, converting the input into output.
But it is a quantum circuit, and gates do not modify the common binary 1 or 0 bits, but quantum is the fundamental unit of quantum computing. Unlike binary bits, quabs can exist as a ‘superposition’ of both 1 and 0, solving only when solving one or the other. Quantum computing also exploits properties such as entanglement, in which changing the position of one changes the position of the other even at a distance.
Those properties empower quantum computers to solve certain classes of the problem more quickly than class computers. Chemists, for example, can use quantum computers to accelerate the identification of new catalysts through modeling.
Yet that possibility remains far-fetched. Even the fastest quantum computers today do not have more than 100 quabs, and suffer from random errors. In 2019, Google demonstrated that its 54-qubit quantum computer could solve a problem in minutes that would take a classical machine up to 10,000 years. But this ‘quantum gain’ applies only to a very narrow condition.
Mathematician and quantum-computing expert Peter Selinger of Dalhousie University in Halifax, Canada, predicts that computers will need several thousand qubits before they can usefully model chemical systems.
“The phase of quantum computers is now like classical computing in the late 1980s,” says quantum-computing researcher Sarah Metawali at Keo University in Tokyo. “Much of the work done now is to prove that the future may have the potential to solve quantum, interesting problems.”
Fast growing area
Nevertheless, progress is taking place at a rapid pace. IBM expects to have a 1,000-quib machine by 2023, and quantum-computing advocates have expressed enthusiasm that the field is ripe for growth. For those who want to see about the nuisance, a growing collection of online tutorials, programming languages and simulators is making it easier to dip your toes into quantum computing.
The underlying digital logic in classical computers is well known: for example 1 and 0 = 0. But quantum computers are much more fluid, and researchers must understand how qubit states are mathematically expressed to understand how they behave.
“Quantum computing is essentially matrix vector multiplication – it’s linear algebra under the hood,” says Curta Svore, chief manager of the quantum-computing group at Microsoft Research in Redmond, Washington.
Many online guides build on the basics. Physicist Michael Nielsen and software engineer Andy Matuschak in San Francisco, California, have created a walk-through resource called Quantum Computing for the Very Curious (see go.nature.com/3qazj2p). And IBM has created an interactive toolkit with its Qiskit quantum language, in which a Jupiter can be run in a computational notebook.
Scientists also need to wrap their heads around the quantum circuit, says Jeanette Garcia, senior manager of the quantum applications, algorithms, and theory team at IBM Research in San Jose, California.
Running from left to right and looking a bit like musical poles, these circuits visually represent how the logic gates are transformed – such as, nor the gates from which electronic circuits are built – to reveal their state Before being measured for.
IBM’s quantum experience allows users to drag and drop logic gates to build their circuits in a web browser and to run remotely on a real quantum computer.
From there, dedicated software frameworks and programming languages allow researchers to simulate, execute, and explore quantum circuits designed. Many of these languages were described in the 2020 review (B. Heim et al. Nature Rev. Fiz. 2, 709–722; 2020).
Microsoft, IBM, and Google have built all the tools – Q #, Qiskit and Cirq, respectively – which weighs heavily on the Python programming language, and have created a user-friendly development environment with enough documentation to help start the coder.
For example, Microsoft has created a complete Quantum Development Kit (QDK), which contains a code library, a debugger, and a resource asset, which checks in advance how many quarters an algorithm will require.
And it’s not just technology giants involved. Righetti Computing in Berkeley, California, which has its own 31-qubit machine, has released a quantum-software development kit called Forrest, which includes a Python library called Python. And UK-based Cambridge Quantum Computing has launched Tack, along with a related PocketKey library.