Today's computers, which are based on classical physics, cannot solve many of the most important problems.

Molecular simulation

Billions of dollars and years of time are lost in experimental wet-lab research, because today’s most powerful computers are incapable of simulation-driven design.

Next week’s weather

Mathematical models of big, dynamical systems like global weather have to be greatly simplified in order to fit in even a supercomputer. Accuracy suffers.

Optimal sequencing

Exact solutions require unmanageable brute-force calculations. Approximate methods leave money on the table for the organizations that use them.

And they never will. 

Transistor scaling

Moore's Law is slowing down as circuits approach fundamental limits.

Returns to parallelization

Amdahl's Law: adding more processors can only get you so far.

Energy consumption

Supercomputers are increasingly power hungry, with no end in sight.


Using quantum mechanics for computation.

Every additional quantum bit ("qubit") on a chip doubles its computing power.

A quantum computer with just 60 qubits would be able to perform calculations inaccessible to today’s most powerful computers.

Our technology is based on superconducting qubits, electrical circuits formed from thin films of aluminum on a silicon chip.

Superconducting qubits can encode quantum information in individual photons, the smallest units of energy allowed by nature.

Traditional computers store information as bits, which are either 0 or 1. Qubits can be a combination of both 0 and 1 at the same time, a property called quantum superposition. 

The difference can be visualized on a sphere. Bits are constrained to either the north pole (0) or south pole (1), while qubits can be anywhere on the surface of the sphere.

In multi-qubit systems, this leads to effects such as quantum interference and entanglement, which can be used to computational advantage.


Many important computational problems will only be solved by building quantum computers.

  • Physics, chemistry, and material science

    Nature is quantum mechanical. Because quantum computers can model physical systems at the most fundamental level, they have the potential to drive breakthroughs in a wide number of industries, from clean energy to semiconductor manufacturing, and from oil and gas to basic physics research.

  • Medicine

    Quantum computers could dramatically extend our abilities to simulate the structure and properties of molecules, including how chemicals, drugs, and hormones interact with the human body. Through large scale analytics and machine learning, they can help shed light on gene expression, and how specific mutations emerge to clinical relevance.

  • Transportation and logistics

    One of the first applications of quantum computers will be in finding solutions to complex optimization problems, such as scheduling, routing, and mission planning, creating disproportionate value for organizations that rely on operational efficiencies.

  • Neuroscience and artificial intelligence

    Many research directions in advanced AI are compute-limited. Harnessing quantum computers' ability to solve new kinds of models and compute in an exponentially large vector space has the potential to unlock a new generation of intelligent systems.