We work on classical computers today, but quantum computers work differently. Quantum computers are able to solve computation problems that classical computers may find challenging as the size and number of inputs involved grow. In contrast to the desktops and laptops we associate with the word ‘computer,’ quantum computers have no visible components. As opposed to these (and they are very few), such facilities look like the cool server rooms of many office buildings or the ungainly tangled wires of old computer desktops connected by ungainly tangled cables and stacked in freezing rooms.
Computing is based on bits, which are simply 1s and 0s, and is possible because of classical physics, which allows a single 1 or 0 to be processed at a time. Today’s world’s most powerful supercomputer can handle up to 148,000 trillion operations in a second with the assistance of up to 9000 IBM processors connected in a specific way.
As far as energy efficiency is concerned, quantum computers far outperform supercomputers
The world’s most powerful supercomputer uses orders of magnitude less energy than noisy intermediate-scale quantum (NISQ) computers when completing specific tasks according to US researchers who devised an energy-based benchmark for quantum advantage.
It becomes increasingly important to question whether quantum computers can perform calculations beyond the ability of conventional supercomputers as quantum computers grow in power and reliability. Quantum computers now have this capability and have moved beyond being mere scientific curiosity to being useful machines.
The debate that ensued when Google claimed to have achieved quantum advantage with its Sycamore NISQ device in September 2019 illustrates how difficult it is to measure quantum advantage. According to scientists from Google, Sycamore was capable of solving a specific problem in less than 200 seconds, while a powerful supercomputer would take up to 10,000 years to achieve the same result. IBM physicists disputed this claim months later, claiming a supercomputer could complete the job in just 2.5 days – negating the advantage theory.
Qubits in a fragile state
Even the most powerful conventional computers are not able to perform some calculations as fast as quantum computers, at least in principle, since they use the laws of quantum mechanics. Several hundred quantum bits (qubit) could be used for useful calculations – perhaps thousands – however to build a quantum computer with more than a few dozen qubits is an extremely difficult task because quantum states are fragile, short-lived, and difficult to control. Sycamore is called an NISQ because it has a medium number of qubits (54), and it is noisy, since it has poor control over the qubits.
Quantum industries are also facing challenges like a lack of consensus on the best qubit technology; some firms are developing superconducting qubits while others are working on trapped-ion computers. Another set of technologies is in development as well. Thus, quantum computers are still a few years away from being practical – and benchmarking is crucial.
While researchers are developing quantum computers, they have also found problems in which nascent quantum computers are more efficient than current conventional computers. Calculating the output of “random quantum circuits” (RQC) is clearly a task that a quantum computer can excel at. Quantum advantage has been attributed to Google using this benchmark for 2019. A quantum computer can also solve the problem by running a simulation program on a conventional supercomputer, but the crucial question is whether it can do so more efficiently than the most powerful quantum simulator.
Efficiency as a concept
Traditionally, efficiency is determined by the amount of time it takes to solve a problem. A new study by Salvatore Mandrà, Google and Oak Ridge National Lab contends that simply considering time is inappropriate. Using a four-core processor, Mandrà explains, “You can solve a problem in 30 minutes versus 1 hour using a single core.”.
They instead calculated both the energy needed to solve the RQC problem with an NISQ and a conventional supercomputer. With qFlex, they developed a quantum simulator believed to be the most efficient. Despite details of the problem the simulation applies to, Mandrà says that the simulation’s efficiency remains almost constant.
On the Summit supercomputer at Oak Ridge – the world’s most powerful supercomputer – the team implemented qFlex on the Ames Electra supercomputer and on the Summit supercomputer at Ames. Both supercomputers were compared to a NISQ in terms of energy expended in performing the calculations. According to their study, to run qFlex on Electra would require 97 MWh and on Summit would require 21 MWh, while with NISQ only 4.2104 MWh would be required. An average American household uses 11 MW hours of electricity each year.
“Lots of papers are developing classical algorithms to simulate quantum systems because there’s a lot of quantum systems around and physicists care about how they behave,” says Daniel Gottesman of the Perimeter Institute for Theoretical Physics in Waterloo, Canada, who was not involved in the research. “The specific focus on quantum supremacy is probably only temporary, but after a few years it will be assumed that we have quantum computers that are better than classical ones, and classical algorithms that simulate quantum computers will become less valuable.”
Demonstrating quantum supremacy.
Quantum computers can solve problems that classical computers can’t. This is what quantum supremacy refers to. According to Google’s research paper, a sequence of millions of numbers was generated using a 53-qubit processor. Google’s algorithm produced those numbers, which appeared to be randomly generated. The values were confirmed by a classic supercomputer. According to Google, Sycamore, their quantum computer, achieved ‘superiority’ by completing the task in 200 seconds that spent 10,000 years on a conventional supercomputer.