In 2019, Google announced that its 53-qubit machine had achieved quantum supremacy by performing a task that could not be managed by a congress computer, but IBM disputed this claim. Same year, IBM launches 53-bit quantum computer. in 2020 ionQ It unveiled a 32-qubit system that the company says is “the world’s most powerful quantum computer.” And just this week, IBM launched its new 127-qubit quantum processor, which the press release describes as a “small design marvel.” “The big news for me is that it works,” says Jay Gambetta, IBM’s vice president of quantum computing.
Now QuEra claims to have made a device with many more qubits than any of these competitors.
The ultimate goal of quantum computing, of course, is not to play Tetris, but to outperform classical computers at solving problems of practical interest. Enthusiasts speculate that once these computers become powerful enough, they will be able to bring transformative effects in fields such as medicine and finance, neuroscience and artificial intelligence, in perhaps ten or twenty years. Quantum machines would likely need thousands of qubits to manage such complex problems.
However, the number of qubits is not the only factor that matters.
QuEra also highlights the advanced programmability of its device, where each qubit is a single, ultra-cold atom. These atoms are precisely arranged with a series of lasers (physicists call them optical tweezers). Positioning qubits allows the machine to be programmed, tuned to the problem being investigated, and even reconfigured in real time during the computation process.
“Different problems will require atoms to be placed in different configurations,” says Alex Keesling, QuEra’s CEO and co-inventor of the technology. “One of the things that makes our machine unique is that we can completely redefine the geometry and connectivity of qubits every time we run it, several times a second.”
QuEra’s machine is made of a blueprint and technologies that have been refined over several years, led by Mikhail Lukin and Markus Greiner at Harvard, and Vladan Vuletić and Dirk Englund at MIT (all on QuEra’s founding team). In 2017, an older model of the device from the Harvard group only 51 qubits; In 2020 they demonstrated the 256-qubit machine. The QuEra team hopes to reach 1,000 qubits within two years and then expand the system beyond hundreds of thousands of qubits without changing the platform much.
QuEra’s unique platform—the physical way the system is put together and the way information is encoded and processed—must allow for such scale jumps.
Google and IBM’s quantum computing systems use superconducting qubits and IonQ trapped ions, while QuEra’s platform uses neutral atomic arrays that produce qubits with impressive coherence (i.e., a high degree of “quantumity”). The machine uses laser pulses to interact with atoms, stimulating them to an energy state – a “Rydberg state” described by Swedish physicist Johannes Rydberg in 1888 – they can robustly perform quantum logic with high accuracy. This Rydberg approach with quantum computing it has been in the works for several decades, but required technological advances (for example, with lasers and photonics) to operate reliably.
When computer scientist Umesh Vazirani, director of the Berkeley Center for Quantum Computing, first learned of Lukin’s research in this direction, he felt “irrationally exhilarated”—which seemed like a great approach, although Vazirani questioned whether his intuitions were in touch with reality. “We have several well-developed pathways that have been studied for a long time, such as superconductors and ion traps,” he says. “Shouldn’t we be considering different plans?” He met with John Preskill, a physicist and director of the Quantum Information and Matter Institute at the California Institute of Technology, and reassured Vazirani that his enthusiasm was justified.
Preskill finds Rydberg platforms (not just QuEra’s) interesting because they produce highly entangled, strongly interacting qubits – “and that’s where the quantum magic is,” Preskill says. “I’m pretty excited about the potential to discover the unexpected on a relatively short timescale.”
In addition to simulation and understanding quantum materials and dynamicsQuEra is working on quantum algorithms to solve computational optimization problems. NP-complete (i.e. very difficult). “These are truly the first examples of beneficial quantum advantage that includes scientific applications,” says Lukin.