Quantum Computing

Quantum Computing Solutions

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. But what exactly is quantum computing, and what does it take to achieve these quantum breakthroughs? Here’s what you need to know.

A quantum computer harnesses some of the almost-mystical phenomena of quantum mechanics to deliver huge leaps forward in processing power. Quantum machines promise to outstrip even the most capable of today’s—and tomorrow’s—supercomputers.
They won’t wipe out conventional computers, though. Using a classical machine will still be the easiest and most economical solution for tackling most problems. But quantum computers promise to power exciting advances in various fields, from materials science to pharmaceuticals research. Companies are already experimenting with them to develop things like lighter and more powerful batteries for electric cars, and to help create novel drugs.
The secret to a quantum computer’s power lies in its ability to generate and manipulate quantum bits, or qubits.
What is quantum supremacy?
It’s the point at which a quantum computer can complete a mathematical calculation that is demonstrably beyond the reach of even the most powerful supercomputer.
It’s still unclear exactly how many qubits will be needed to achieve this because researchers keep finding new algorithms to boost the performance of classical machines, and supercomputing hardware keeps getting better. But researchers and companies are working hard to claim the title, running tests against some of the world’s most powerful supercomputers.
How Do Quantum Computers Work?

Quantum computers perform calculations based on the probability of an object's state before it is measured - instead of just 1s or 0s - which means they have the potential to process exponentially more data compared to classical computers.

Classical computers carry out logical operations using the definite position of a physical state. These are usually binary, meaning its operations are based on one of two positions. A single state - such as on or off, up or down, 1 or 0 - is called a bit.
In quantum computing, operations instead use the quantum state of an object to produce what's known as a qubit. These states are the undefined properties of an object before they've been detected, such as the spin of an electron or the polarisation of a photon.
Rather than having a clear position, unmeasured quantum states occur in a mixed 'superposition', not unlike a coin spinning through the air before it lands in your hand.
These superpositions can be entangled with those of other objects, meaning their final outcomes will be mathematically related even if we don't know yet what they are.
The complex mathematics behind these unsettled states of entangled 'spinning coins' can be plugged into special algorithms to make short work of problems that would take a classical computer a long time to work out... if they could ever calculate them at all.
Such algorithms would be useful in solving complex mathematical problems, producing hard-to-break security codes, or predicting multiple particle interactions in chemical reactions.

Areas we work

Quantum computing will revolutionize the way we work. That’s why we’ve spent more than a decade focused on ways to not only help architect this massive expansion of computational power and problem solving, but accelerate it, too. As a leading technology company, we will shape the adoption and integration of quantum information systems into the industries we serve.

Improve the efficiency of early-phase drug design and discovery


Accelerate development of new chemicals


Reduce risk through improved portfolio insight


Develop new aircraft materials and military technology


Optimize production and expedite exploration


Accelerate machine learning and analysis of large data sets.