In 2019, Google announced that its 53-qubit machine had achieved quantum supremacy – a task a traditional computer couldn’t do – but IBM denied the claim. In the same year, IBM launched its 53-bit quantum computer. In 2020, IonQ introduced a 32-qubit system that the company said was “the most powerful quantum computer in the world”. And just this week, IBM launched its new 127-qubit quantum processor, which the press release describes as a “little design marvel”. “The big news from my point of view is that it works,” said Jay Gambetta, IBM’s vice president for quantum computers.
Now QuEra claims to have made a device with far more qubits than any other rival.
The ultimate goal of quantum computing is of course not to play Tetris, but to outperform classic computers in solving practical problems. Enthusiasts believe that if these computers are powerful enough, perhaps in a decade or two, they could have transformative implications in areas like medicine and finance, neuroscience, and AI. Quantum machines will likely require thousands of qubits to deal with such complex problems.
However, the number of qubits isn’t the only factor that matters.
QuEra is also promoting the improved programmability of its device, where each qubit is a single, ultra-cold atom. These atoms are precisely arranged using a series of lasers (physicists call them optical tweezers). By positioning the qubits, the machine can be programmed in real time during the calculation process, adjusted to the problem to be investigated and even reconfigured.
“Different problems require the atoms to be placed in different configurations,” says Alex Keesling, CEO of QuEra and co-inventor of the technology. “What is unique about our machine is that every time we run it a few times per second, we can completely redefine the geometry and connectivity of the qubits.”
The atomic advantage
The QuEra machine was built according to a blueprint and technologies that were refined over several years, under the direction of Mikhail Lukin and Markus Greiner from Harvard and Vladan Vuletić and Dirk Englund from MIT (all of whom are part of the QuEra founding team). In 2017, an earlier model of the Harvard group’s device used only 51 qubits; In 2020 they demonstrated the 256 qubit machine. The QuEra team expects to reach 1,000 qubits within two years and then hopes, without changing the platform much, to continue to scale the system to over hundreds of thousands of qubits.
It is QuEra’s unique platform – the physical way the system is assembled and the method by which information is encoded and processed – that should enable such leaps in scale.
While the quantum computing systems from Google and IBM use superconducting qubits and IonQ uses trapped ions, QuEra’s platform uses arrays of neutral atoms that produce qubits with impressive coherence (ie, a high degree of “quantity”). The machine uses laser pulses to make atoms interact and stimulate them into an energy state – a “Rydberg state” described by Swedish physicist Johannes Rydberg in 1888 – in which they can robustly perform quantum logic with high accuracy. This Rydberg approach to quantum computing has been worked on for several decades, but technological advances – in lasers and photonics, for example – were required to make it work reliably.
When computer scientist Umesh Vazirani, director of the Berkeley Quantum Computation Center, first learned of Lukin’s research in this direction, he felt “irrationally exuberant” – it seemed like a wonderful approach, although Vazirani questioned whether his intuitions were with related to reality. “We had several well-developed paths, such as superconductors and ion traps, that had been worked on for a long time,” he says. “Shouldn’t we be thinking about other plans?” He reached out to John Preskill, a physicist at the California Institute of Technology and director of the Institute for Quantum Information and Matter, who assured Vazirani that his exuberance was justified.
Preskill finds Rydberg platforms (not just QuEra’s) interesting because they produce strongly interacting qubits that are strongly entangled – “and this is where quantum magic lies,” he says. “I’m pretty excited to see the potential of discovering unexpected things in a relatively short period of time.”
In addition to simulating and understanding quantum materials and dynamics – which Lukin describes as “the first examples of useful quantum advantages in scientific applications” – the researchers are also working on quantum algorithms for solving computational optimization problems that are NP-complete (ie very difficult).