Quantum richness and diversity of hardware discourage collaboration

Quantum richness and diversity of hardware discourage collaboration

Quantum computing has been considered a technology for generations, and the payoffs for winners are huge, but the diversity of technologies discourages collaboration, an Intel executive said last week.

About five to six quantum computing technologies are in development, and they all require different levels of expertise or optimization at the top of the system, said Jim Clarke, director of quantum hardware at Intel Labs. HPCwire.

“It makes it difficult to have common projects in such disparate programs,” Clarke said.

Intel’s version of quantum bits, which it called spin qubits, differs from other technologies that include superconducting qubits, which are being pursued by Google and IBM. IonQ, which made news last week with a deal to provide quantum computing services through Dell, is working on trapped ion qubits.

“Companies see quantum as the technology of the next 100 years and want to share the spoils. Companies just aren’t interested in working [together]. I think that might be one of the flaws. There is no collaboration in the industry,” Clarke said.

This is unlike how the conventional chip market has evolved, spurred on by SEMATECH, a DARPA-backed incubator where chip technologies were developed and tested, with the winner being widely adopted.

“We brought all these companies together to work on some pretty competitive ideas. Once you’ve had an idea through this pre-competition, whoever took the idea, adopted it, and quickly optimized it is the winner,” Clarke said.

Intel is working on creating its universal quantum computer and last month produced stable quantum dots at its existing factories. By next year, the company hopes to make its 12-qubit hardware system accessible so developers can start writing apps. Intel has a mass manufacturing advantage because it has shown it can manufacture quantum chips in its existing factories.

“Our philosophy is to make our qubits look exactly like transistors. The closer we can get these two transistors, both in terms of manufacturing and design…and layout, the easier it will be for us,” Clarke said.

Beyond the quantum processing unit, Intel’s quantum portfolio includes the controller called Horse Ridge and a software development kit that includes the compiler, runtime, mapper, and scheduler. It has a quantum simulator to sample the computing environment. Intel’s next step is to upgrade the quantum simulator to represent the spin qubit hardware the company plans to ship.

Developers of quantum computing hardware have largely been courteous to each other and focused on their own technologies. But it wasn’t always like that. About nine years ago, IBM and D-Wave, who were the first developers of quantum hardware, had a public battle that challenged the very concept of quantum computing.

IBM, in a 2014 paper, argued that D-Wave’s quantum annealing system should not be scientifically classified as a quantum computer, which was counter-argued by D-Wave. IBM, which was developing a superconducting qubit, eventually had to go back and recognize that D-Wave’s system was a quantum computer.

D-Wave was a pioneer with its quantum annealing system, which is specifically used for optimization. IBM, on the other hand, was working on building a universal quantum computer with error correction, which researchers now agree will require a minimum of one million qubits. But technological developments and research have since evolved, with the recognition that quantum hardware and topologies will be diverse, with different kinds of systems solving different kinds of problems.

Governments are now trying to bring order to the chaotic quantum computing industry to expand markets and preserve national security. The United States, China, and Europe have put quantum computing on their priority lists of technologies to keep domestically, along with AI and high-performance computer chips.

The National Quantum Initiative Act of 2018 stimulated quantum research and collaboration between 70 organizations, including universities and private sector companies. The initiative also prioritizes the development of algorithms to protect US infrastructure against cyberattacks from quantum systems, which could crack current encryption schemes in seconds. The National Institute of Standards and Technology tests quantum-resistant algorithms developed by companies such as Intel, Microsoft and IBM.

Argonne National Laboratory tests quantum hardware and software technologies from many companies through its Q-NEXT program, which lists Intel, IBM, Microsoft, ColdQuanta and others as members. Argonne will test Intel’s quantum hardware.

Last month, the EU-funded European Joint Undertaking for High-Performance Computing (EuroHPC JU) announced that it would deploy quantum computers in Czechia, Germany, Spain, France, Italy and Poland. . The systems will be connected to the continent’s wider supercomputing network. The deployment will be completed in the second half of 2023 and will cost around 100 million euros.

Last month, Chinese President Xi Jinping listed the development of native quantum computing technologies as one of his top priorities, according to an article in Nature.

Notable companies in the financial, pharmaceutical, and transportation industries are testing quantum chips or simulators to find the best types of qubits for applications. But the confusion around quantum computing resources has given rise to companies like Classiq, which has a software development platform that allows customers to write quantum applications without knowing the hardware.

“The industry programs at the assembly language level, and anyone who’s ever programmed at the assembly level knows that’s not a sustainable thing,” said Erik Garcell, technical marketing manager at Classiq, during the SC22 conference in Dallas earlier this month.

Classiq’s software, which is funded by HPE, also allows users to compare quantum systems, either against classical hardware or against other quantum hardware, so they can find the best qubits. The customer can then deploy the application and get results without learning new languages ​​or datasets.

“We want to save our users from having to decide in advance what hardware to run on or what assembly language program to learn. We want them to build efficient quantum circuits and then decide whether to run on AWS or IBM,” Garcell said.

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