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Human Health, Innovation

Quantum Computing is Real. It Will Simulate the Subatomic World

Inside IBM's commercial “IBM Q” quantum system. Photo courtesy of IBM Research via Creative Commons.

Scientists are preparing to use quantum computers to design new drugs and biomaterials made out of proteins and peptides.

Even though computers have been getting faster and faster over the past 75 years, there’s still room for an exponential increase in speed. This boost should make it possible for machines to perform tasks that are impossible today, with particularly powerful applications in medicine and biology. To achieve it, the trick will be to make computers weirder.

Unlike conventional digital computers that process data as discrete 0s and 1s, quantum computers have bits whose values are fluid: essentially, they can be 0 and 1 at the same time. This is because the bits are made out of things that are so small—including individual atoms or electrons—that their behavior is defined by the oddities of quantum mechanics. One of these strange properties is superposition, where various possible states of a system exist at the same time. Another bizarre property is entanglement, which is when two particles act identically and a change to one also changes the other. Because quantum bits, known as qubits, have both superposition and entanglement, a quantum computer can calculate with many complex variables at the same time. Exponential power takes hold quickly. Each qubit can represent two states at once, so two qubits can represent four states (22), three qubits can represent eight (23), and so on. Just 64 qubits have the potential to represent 264 states at once: more than 18 billion billion.

Quantum computers were first proposed about 40 years ago, but they are only now becoming real machines. Making and controlling quantum computers has been elusive because their quantum weirdness arises from conditions that are hard to maintain. The most common way to produce these effects is to keep qubits extremely cold—a tiny amount above absolute zero—and they have to be shielded from electromagnetic interference. Because qubits are so fragile—they easily “decohere” into a state that doesn’t have quantum properties—their calculations are prone to mistakes. The results must be run through error-correcting algorithms, some of which require quantum calculations of their own. That uses up a sizable chunk of the machine’s processing power.

Quantum computers could offer powerful new ways to model the complexity in biological systems.

Nonetheless, even a machine with fewer than 100 stable qubits should exhibit “quantum supremacy,” which means it could solve problems in a few seconds that would take any classical machine thousands of years to crunch. That threshold is now in sight—Google announced a successful quantum supremacy experiment in October. A machine performed a very specialized computation in 200 seconds that would take the world’s fastest supercomputer 10,000 years to solve. Although quantum computers are too cumbersome and expensive to be installed everywhere (and there’s no need to replace classical digital computers for many kinds of computation), quantum calculations-on-demand will soon be widely available through big cloud-computing providers like IBM, Google, and Microsoft, as well as startups such as Rigetti Computing.

Of all the fields that will benefit from using quantum computers to model huge numbers of permutations in complex systems, medicine and biomedical research stand out.

Scientists are preparing to use quantum computers to design new drugs and biomaterials made out of proteins and peptides. Peptides and proteins are chains of amino acids (peptides are short chains; proteins longer ones) that play fundamental roles in the cellular operations of living organisms. Their function is determined by their structure, and their structure is determined by the order in which their amino acids are arranged. In theory, these and other biomolecules could be precisely designed to attack particular pathogens, carry out repairs, or trigger other beneficial effects. Modeling all the possibilities exceeds the capabilities of conventional digital supercomputers, but not in theory those of quantum computers.

Quantum computers could also offer powerful new ways to model the astounding complexity inherent in larger biological systems. The more deeply researchers delve into cancer, Alzheimer’s disease, and other disorders, the more it’s becoming clear that the causes are rarely as simple as one or two genes or proteins. From the brain to the immune system and everywhere in between, the balance between wellness and illness is tipped by a cascade of factors that influence each other. Simulating such convoluted interactions across the body and across moments in time is a task for a quantum computer.

Once quantum machines become more powerful and more widely available, countless other applications will suggest themselves. How about molecular-level simulations of how multiple prescription drugs will interact in the body? What happens if you use, say, a different isotope of copper in a biological enzyme? The answers to such questions depend on actions taking place on the level of individual atoms—actions determined by the probabilistic vagaries of quantum mechanics. Accurately modeling these events eludes the grasp of digital computers. They demand quantum machines like the ones that will be taking shape over the next decade.

Milestones in Quantum Computing

1980
In a paper in the Journal of Statistical Physics, Paul Benioff of Argonne National Laboratory describes the feasibility of a computer that uses quantum effects to make calculations.
1981
Richard Feynman shows how such a computer could be used to accurately simulate quantum processes in nature.
1985
The physicist David Deutsch shows that quantum computers could be “universal”—able to simulate any physical process.
1994
MIT’s Peter Shor demonstrates how a quantum computer could quickly determine the prime factors of very large numbers. That capability would render many contemporary cryptographic protocols useless.
1996
Lov Grover of Bell Labs develops an algorithm that a quantum computer could use to search through any database far faster than a conventional machine could.
1998
Two research groups, working independently, each carry out basic quantum calculations by making quantum bits, or qubits, out of molecules that they manipulate with radio waves.
2007
A Canadian startup, D-Wave Systems, unveils what it says is the world’s first commercial quantum computer. Whether this machine actually exploits quantum effects will be debated for several years, but even D-Wave agrees that its machines are not universal quantum computers. They are fundamentally limited to solving one kind of problem.
2012
Caltech physicist John Preskill describes "quantum supremacy": the point at which quantum computers can be controlled well enough to reliably outperform classical digital computers.
2016
Researchers at Google, Lawrence Berkeley National Laboratories, and several universities use three qubits to simulate the energy states of a hydrogen molecule.
January 2019
IBM announces the commercial release of a computer with 20 qubits. It’s meant for researchers and other early adopters but isn’t yet a game-changer. Its qubits aren’t very stable, and 20 of them can’t produce the computational power that quantum computing promises.
October 2019
Google researchers claim to have achieved quantum supremacy. They say they have used a machine with 53 qubits to solve a problem in three minutes that would have taken the fastest classical computer 10,000 years. IBM, which disputes whether Google's experiment truly proves quantum supremacy, also begins offering access to a computer with 53 qubits.

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