The quantum computer may seem like an almost mythical piece of technology, together with the ion thruster and the jetpack. But just like those other inventions, it is no figment of science fiction: it is real, it is powerful, and Google is looking to fully bring them into reality by the end of the decade.

But first: what is a quantum computer, and why are they so intriguing to behemoths of technology like Google? 

Stated simply, a quantum computer is a type of computer that takes advantage of the counterintuitive properties of quantum mechanics. While classical ‘bits’ encode information in binary, quantum computers use ‘qubits’. These qubits have the possibility to be either 0 or 1, due to a property called ‘quantum superposition’, but they will collapse into one of the two outcomes when measured. A functional quantum computer would allow interference to reduce the probability of the incorrect outcome, while reinforcing the probability of another. When observed, the qubit would collapse into 0 or 1, depending on what the probabilities of each were. When qubits are combined, they become ‘entangled’; that is, the probabilities attached to their states become interdependent with those of the other qubits – and processing capacity would increase exponentially. (For a more detailed explanation, see the first link in the sources.)

All of this makes quantum computers useful for problems of extreme complexity, or those that must take quantum mechanics into account. For example, chemical reactions function on the basis of quantum mechanics; although it is possible to develop classical methods of simulating some basic reactions, in order to accurately describe them, it is necessary for our computers to consider the true mechanisms that control them. By using quantum computing, we can advance our understanding of chemistry, which could lead to the invention of more effective drugs, better materials in batteries, and solar panels of greatly improved efficiency.

Chemistry is far from the only field that stands to benefit from a quantum revolution. Any field where manifold factors and conditions must be considered in a simulation, such as weather forecasting, particle physics, and even financial markets, can be improved. Cryptography could also be revolutionized, due to the inherent advantages quantum computers have when performing calculations.

But enough speculation – what progress has Google made in this field?

In October of 2019, Google announced that its quantum processor had completed a calculation in 3 minutes and 20 seconds that would have taken IBM’s Summit, one of the most powerful supercomputers in the world, 10,000 years to solve. However, IBM countered this claim, stating that with better techniques, Summit could complete the calculation in 2.5 days. In August of 2020, their 54-qubit Sycamore processor completed a calculation related to chemistry; in Google AI’s official research blog, Chief Scientists John Martinis and Sergio Boixo stated that “[o]ur [Google’s] team has already been working on near-term applications, including quantum physics simulation and quantum chemistry, as well as new applications in generative machine learning, among other areas.”

Google is just one in a race of many organizations to create a reliable quantum computer. Intel’s “Tangle Lake” processor incorporates 49 qubits, while IBM has made a variety of processors, their most powerful containing 65 qubits. But their competition is not limited to giants of Silicon Valley and New York City; On December 3, 2020, The University of Science and Technology in China (USTC) reported that its photonic quantum computer, Jiuzhang, had performed a calculation in 200 seconds that would take the world’s most powerful supercomputer more than half a billion years to perform.

However, creating a powerful quantum computer is not just a matter of stacking up greater and greater quantities of qubits. A major problem with building reliable quantum computers is that even minor interferences, such as a weak magnetic field, may cause the probabilities associated with the qubits to be changed, which would change the final result. In the mid-1990s, mathematicians proved that there existed ‘error-correcting codes’ that could be stored to protect quantum information, even if individual qubits were disturbed. However, actually finding and implementing these codes is difficult, and scaling quantum computers to thousands of qubits or more will require the use of error-correcting codes. 

Another question to consider is this: is it impossible for a classical computer to perform these calculations in a feasible amount of time, or have we simply not found the right algorithms for the tasks? Answering this question turns out to be a major hurdle in computer science.

Despite these hurdles and questions, Google and their competitors are eager to make advances as quickly as possible. Google states that we are currently in the NISQ (Noisy Intermediate-Scale Quantum) era of quantum computing, where quantum computers are powerful but not completely reliable. However, they are aiming to create a “useful, error-corrected quantum computer” by the end of the decade. Google, IBM, and the other organizations on the hunt for quantum computers most likely have their own motivations for developing the technology, but disregarding dreams of commercialization and quantum cryptography, the most important question may be this: How will quantum computers empower the overall fields of science and technology in the near and far future?