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 computing can provide solutions to challenges that are out of reach for today's fastest computers. This new paradigm creates endless possibilities across a variety of quantum computing applications, provided the quantum computer has enough error-corrected qubits to complete algorithms successfully. Microsoft is developing a topological qubit to create a scalable quantum system that can complete the algorithms for the solutions the world needs most. While quantum computers can offer an exponential boost in computational power, they can’t be programmed in the same way as a classical computer. The instruction set and algorithms change, and the resulting output is different as well. On a classical computer, the solution is found by checking possibilities one at a time. Depending upon the problem, this can take too long. A quantum computer can explore all possibilities at the same time, but there are a few challenges. Getting the right answer out of the computer isn’t easy, and because the answers are probabilistic, you may need to do extra work to uncover the desired answer.

Finding solutions to challenges like global warming and world hunger may require a quantum system with thousands or millions of qubits. Microsoft is pursuing a topological qubit for its ability to scale—allowing us to solve more complex problems with fewer numbers of qubits overall. Paired with our full-stack solution, the topological qubit will help Microsoft offer a quantum system that scales to greater complexity, bringing solutions to some of the world's greatest challenges within reach. Microsoft is achieving its vision for scalable quantum computing through topological qubits. Qubits are fragile by nature, easily collapsing from outside interference. Topological qubits feature increased stability and resistance to interference, a performance improvement that allows the quantum computer to scale.

With the aid of quantum computers, chemists can work to identify a new catalyst for fertiliser to help reduce greenhouse emissions and improve global food production. This solution requires the ability to model molecular interactions which are too complex for classical computers, but well-suited for quantum computers. The field of chemistry is an area in which quantum computers will have significant impact.

Quantum computers will help advance materials science, creating superior new alternatives and greener technologies. One potential quantum computing application is the development of high-temperature superconductors which could enable lossless transmission of energy. New discoveries enabled by quantum computers will help identify materials with properties suitable for high-temperature superconductivity—a level of complexity that is out of reach for the computers we use today.

Quantum computing can bring speed and efficiency to complex optimisation problems in machine learning. For example, large factories aiming to maximise output require optimisation of each individual process, as well as all participating components. Quantum computers can help deliver optimisation insights for streamlined output, reduced waste, and lowered costs.
**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.