Quantum computing’s possibilities

Soldiers in ancient Greece would send secret dispatches by wrapping a strip of parchment around a staff and writing across it. Their messages could be deciphered only by someone with a staff of the same thickness. It is one of the earliest examples of cryptography. Today’s secrets, such as Internet communication, digital banking, and electronic commerce, are protected from prying eyes by powerful computer algorithms. Yet these hitherto impenetrable cryptographic codes could soon be history.

Quantum computers can reach a level of optimization that would crack many of today’s encryption keys in less time than it takes to generate them using conventional digital computers. Financial institutions should future-proof their cybersecurity systems without delay. Failure to do so will imperil financial stability.

A quantum revolution

Quantum computing is the use of quantum phenomena such as superposition and entanglement to perform computations. The basic unit of a quantum computer is the quantum bit (or qubit, for short). It is typically realized by the quantum properties of subatomic particles, such as the spin of electrons or the polarization of a photon. Whereas each binary bit used in today’s digital computers represents a value of either zero or one, qubits represent both zero and one (or some combination of the two) at the same time. This phenomenon is called superposition. Quantum entanglement is a special connection between pairs or groups of quantum elements. Changing the state of one element affects other entangled elements instantly—regardless of the distance between them.

Increasing the number of qubits delivers an exponential rise in calculation processing speed. Two traditional binary bits are needed to match the power of a single qubit; four bits are required to match two qubits; eight bits are needed to match three qubits; and so on. It would take about 18 quadrillion bits of traditional memory to model a quantum computer with just 54 qubits. A 100 qubit quantum computer would require more bits than there are atoms on our planet. And a 280 qubit computer would require more bits than there are atoms in the known universe.

Quantum computers have the potential to massively out-process digital computers that follow classical laws of physics. William Phillips, the Nobel Prize–winning physicist, has compared the leap from today’s technology to quantum with that from the abacus to the digital computer itself. Until recently, this so-called quantum advantage or quantum “supremacy” was just a theory. In 2019, however, Google used a quantum computer to perform a specific computation task in just 200 seconds. The same task would, the company said, have taken the most powerful digital supercomputer at that time 10,000 years.

The possibilities

Complex computational tasks are like finding the way out of a maze. A traditional computer would try to escape by following every path in sequence until it reached the exit. Superposition, by contrast, allows a quantum computer to try all the paths at once. This drastically reduces the time to find a solution.

By solving problems with more accuracy and speed than digital computers, quantum computers have the potential to accelerate scientific discovery and innovation, revolutionize financial market modeling and simulations, and empower machine learning and artificial intelligence. They could be used to model subatomic particles, molecular interactions, and chemical reactions. This could revolutionize chemical engineering and material science and allow the design of new materials, such as solid-state batteries. Quantum computers could also help us understand climate change. 

Quantum computers could transform the financial system, too. They could perform more accurate Monte Carlo simulations—used to predict the behavior of markets through pricing and risk simulations—almost in real time. There would be no need to simplify these models with unrealistic assumptions. Quantum computers could also solve optimization tasks—such as allocating capital, determining portfolio investments, or managing the cash in ATM networks—in a fraction of the time it takes digital computers. Quantum computers could also speed the training of machine learning algorithms. The time it takes digital computers to do this increases exponentially with each dimension that is added. Not so with quantum computers.

There are risks, however. The computing power of these mighty quantum machines could threaten modern cryptography. This has far-reaching implications for financial stability and privacy. Today’s cryptography is based on three main types of algorithms: symmetric keys, asymmetric keys (also known as public keys), and hash functions. With symmetric keys, the same key is used to encrypt and decrypt a message. Asymmetric cryptography uses a pair of related keys (one private and the other public). A message encrypted by one key can be decrypted only by that key’s pair. These algorithms are widely used for digital authentication, digital signatures, and data security. Hash functions convert digital input into a unique set of bytes of fixed size. They are used to store passwords securely and to support digital identities.

IMF