Even if it is not quantum supremacy, Google’s findings can revolutionise computing.
In 2012, American theoretical physicist John Preskill coined the term ‘quantum supremacy’, stating it meant a point where a quantum computer could do something that classical computers, including the most advanced super computer of the day, simply couldn’t. Preskill may not have expected an announcement of quantum supremacy so soon—in his 2012 paper, he had wondered if controlling quantum systems could be achieved “after a few decades of hard work” or if we “might not succeed for centuries”—but, Google has just announced that its quantum machine Sycamore was able to perform a “target computation” in 200 seconds. This, Google researchers wrote in a blog-post, they had estimated would take the fastest supercomputer 10,000 years.
That is surely impressive, but is it quantum supremacy, as Google claims it is? IBM begs to differ, as does Preskill. While IBM maintains that an ideal simulation of the same task “can be performed on a classical system in 2.5 days and with far greater fidelity” in a conservative, worst-case scenario, Preskill, in a Quanta article, writes that what Google has is a “noisy intermediate-scale quantum” system, with ‘intermediate-scale’ emphasising that Sycamore is potentially “large enough to perform certain highly specialised tasks beyond the reach of today’s supercomputers”, and ‘noisy’ emphasising that we have “imperfect control over the qubits (the currency of quantum computing), resulting in small errors that accumulate over time; if we attempt too long a computation, we’re not likely to get the right answer.” Google’s Sycamore announcement, nevertheless, is a paradigm shift for computing.
While classical computing is based on bits—each bit represents either 0 or 1 of the binary system, and combinations are used to store more complex information—quantum computers use qubits; each qubit can simultaneously bear two states or levels of a binary system. Take, for instance, the two faces of a coin. In a stationary state, the coin represents a bit, in which only one side of the coin is visible. But, if the same coin is tossed, to the naked eye, it is impossible to tell if the coin is heads-side up or tails-side up because both sides seem to appear simultaneously, representing a qubit.
Though very remote from being a perfect analogy, the coin example demonstrates that a qubit can coherently exhibit a superposition of two states of binary system. This makes quantum systems infinitesimally faster than classical systems—if a 2-bit system in an ordinary computer can represent only one of the four binary combinations possible for this system (00, 01,10, 11) at a specific point in time, a 2-qubit register can store all four combination simultaneously. Values, thus, can be represented by protons and electrons, which may travel in waves, making them fluid. This also means these computers are challenging to make and maintain. That is the reason that despite being used in millions of experiment—IBM’s machine alone has been used to design 17 million—not much has transpired on the physical front. Quantum experiments can change the face of predictions and forecasting, and can enable solving of harder problems. Cryptography and creating unbreakable protocols is just one of the uses.
Quantum can help with space exploration, making calculations within a millisecond, predict hurricanes and other natural phenomena much more accurately and far ahead in time, run millions of scenarios, leading to the discovery of more efficient products like storage batteries. With Google having kicked off the quantum race in a meaningful manner, private and government sector companies will have to logarithmically increase efforts to yield the quantum advantage. While India announced quantum efforts last year, Google’s announcement means stepping up support in an unprecedented scale.