Quantum Computing

Quantum computers could spur the development of new breakthroughs in science, medications to save lives, machine learning methods to diagnose illnesses sooner, materials to make more efficient devices and structures, financial strategies to live well in retirement, and algorithms to quickly direct resources such as ambulances. We experience the benefits of classical computing every day. However, there are challenges that today’s systems will never be able to solve. For problems above a certain size and complexity, we don’t have enough computational power on Earth to tackle them. To stand a chance at solving some of these problems, we need a new kind of computing. Universal quantum computers leverage the quantum mechanical phenomena of superposition and entanglement to create states that scale exponentially with number of qubits, or quantum bits.

How do quantum computers work?

In quantum computing, a qubit (short for quantum bit) is a unit of quantum information—similar to a classical bit. Where classical bits hold a single binary value such as a 0 or 1, a qubit can hold both values at the same time in what's known as a superposition state. When multiple qubits act coherently, they can process multiple options simultaneously. This allows them to process information in a fraction of the time it would take even the fastest nonquantum systems. There are a few different ways to create a qubit. One method uses superconductivity to create and maintain a quantum state. To work with these superconducting qubits for extended periods of time, they must be kept very cold. Any heat in the system can introduce error, which is why quantum computers operate at temperatures close to absolute zero, colder than the vacuum of space.

Quantum outperforms classical

Quantum computers are expected to be better at solving certain computational problems than classical computers. This expectation is based on conjectures in computational complexity theory, but rigorous comparisons between the capabilities of quantum and classical algorithms are difficult to perform. Bravyi et al. proved theoretically that whereas the number of steps needed by parallel quantum circuits to solve certain linear algebra problems was independent of the problem size, this number grew logarithmically with size for analogous classical circuits.This so-called quantum advantage stems from the quantum correlations present in quantum circuits that cannot be reproduced in analogous classical circuits.