Microsoft Aims to Develop Quantum Supercomputer in 10 Years

This article originally appeared on Enter Quantum.

Microsoft has published a six-step quantum roadmap that it claims could lead to a quantum supercomputer within 10 years.

The technology centers around a type of stable topological qubit called Majorana that the company demonstrated last year.

Quantum Roadmap Steps

In a blog post, Microsoft technical fellow and corporate vice-president of quantum hardware Chetan Nayak set out the step to achieve the company’s goals, with the first step marked as “achieved”.

1. Create and control Majoranas. 

2. Developing a hardware-protected qubit, also known as a topological qubit

3. High-quality hardware-protected qubits.

4. Developing a multi-qubit system.

5. Making that system resilient.

6. A practical quantum supercomputer.

Quantum Implementation Levels

Microsoft described the three levels of development of quantum hardware on the route to a practical quantum computer than can deliver quantum advantage:

Level 1—Foundational

These are quantum systems that run on noisy physical qubits. This includes all of today’s noisy intermediate scale quantum (NISQ) computers, such as the IonQ, Pasqal, Quantinuum, QCI and Rigetti to which Microsoft Azure Quantum provides access.

Level 2—Resilient

These will be quantum systems that operate on reliable logical qubits, which is essential to scaling.

Related:Google Is Making Breakthroughs Much Bigger Than AI

Level 3—Scale

This represents quantum supercomputers that can solve impactful problems which even the most powerful classical supercomputers cannot, also known as quantum advantage or supremacy.

Azure Quantum Elements and Copilot

Microsoft has also introduced Azure Quantum Elements, which combines high-performance computing, AI and quantum, to speed up the research and development of new chemicals and materials.  

In March, the company introduced Copilot for Azure Quantum, a tool that taps generative AI to help scientists use natural language to reason through complex chemistry and materials science problems.