Quantum computing takes flight

18/12/2019

A programmable quantum computer has been reported to outperform the most powerful conventional computers in a specific task — a milestone in computing comparable in importance to the Wright brothers’ first flights.

By William D. Oliver
23 October 2019

Quantum computers promise to perform certain tasks much faster than ordinary (classical) computers. In essence, a quantum computer carefully orchestrates quantum effects (superposition, entanglement and interference) to explore a huge computational space and ultimately converge on a solution, or solutions, to a problem. If the numbers of quantum bits (qubits) and operations reach even modest levels, carrying out the same task on a state-of-the-art supercomputer becomes intractable on any reasonable timescale — a regime termed quantum computational supremacy¹. However, reaching this regime requires a robust quantum processor, because each additional imperfect operation incessantly chips away at overall performance. It has therefore been questioned whether a sufficiently large quantum computer could ever be controlled in practice. But now, in a paper in Nature, Arute et al.² report quantum supremacy using a 53-qubit processor.

Arute and colleagues chose a task that is related to random-number generation: namely, sampling the output of a pseudo-random quantum circuit. This task is implemented by a sequence of operational cycles, each of which applies operations called gates to every qubit in an n-qubit processor. These operations include randomly selected single-qubit gates and prescribed two-qubit gates. The output is then determined by measuring each qubit.

The resulting strings of 0s and 1s are not uniformly distributed over all 2ⁿ possibilities. Instead, they have a preferential, circuit-dependent structure — with certain strings being much more likely than others because of quantum entanglement and quantum interference. Repeating the experiment and sampling a sufficiently large number of these solutions results in a distribution of likely outcomes. Simulating this probability distribution on a classical computer using even today’s leading algorithms becomes exponentially more challenging as the number of qubits and operational cycles is increased.

In their experiment, Arute et al. used a quantum processor dubbed Sycamore. This processor comprises 53 individually controllable qubits, 86 couplers (links between qubits) that are used to turn nearest-neighbour two-qubit interactions on or off, and a scheme to measure all of the qubits simultaneously. In addition, the authors used 277 digital-to-analog converter devices to control the processor.

When all the qubits were operated simultaneously, each single-qubit and two-qubit gate had approximately 99–99.9% fidelity — a measure of how similar an actual outcome of an operation is to the ideal outcome. The attainment of such fidelities is one of the remarkable technical achievements that enabled this work. Arute and colleagues determined the fidelities using a protocol known as cross-entropy benchmarking (XEB). This protocol was introduced last year³ and offers certain advantages over other methods for diagnosing systematic and random errors.

* William D. Oliver is in the Departments of Electrical Engineering and Computer Science and of Physics, Research Laboratory for Electronics and Lincoln Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.

Published at https://www.nature.com/articles/d41586-019-03173-4