Microsoft Azure Quantum

Quantum Computing Division/Software From Wikipedia, the free encyclopedia

Microsoft Azure Quantum is a public cloud-based quantum computing platform developed by Microsoft, that offers quantum hardware, software, and solutions for developers to build quantum applications.[1][2] It supports variety of quantum hardware architectures from partners including Quantinuum, IonQ, and Atom Computing.[3] To run applications on the cloud platform, Microsoft developed the Q# quantum programming language.[4]

Quick Facts Developer(s), Initial release ...
Microsoft Azure Quantum
Developer(s)Microsoft
Initial releaseFebruary 1, 2021; 4 years ago (2021-02-01)[1]
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Azure Quantum also includes a platform for scientific research, Azure Quantum Elements. It uses artificial intelligence, high-performance computing and quantum processors to run molecular simulations and calculations in computational chemistry and materials science.[5]

Azure Quantum was first announced at Microsoft Ignite in 2019.[6] The platform was opened for public preview in 2021,[1] and Azure Quantum Elements was launched in 2023.[5]

Hardware

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Perspective

In addition to its hardware partners on the platform, Microsoft is developing a topological quantum computer with qubits that are inherently resistant to error. The approach is based on Majorana quasiparticles, which act as their own antiparticle and have a charge and energy equal to zero, making qubits that are more resilient to disturbances.[7][8]

In September 2023, Azure Quantum researchers found evidence consistent with the creation and control of Majorana quasiparticles for topological quantum computing.[8][9]

In November 2024, the qubit virtualization system created 24 entangled logical qubits – a new record – on a neutral atom processor.[10] The work demonstrated detection and correction of errors while performing computations, including the first demonstration on record of loss correction in a commercial neutral-atom system from Atom Computing.[11]

Microsoft has also introduced three levels of implementation for quantum computing: foundational (noisy intermediate-scale qubits), resilient (reliable logical qubits), and scale (quantum supercomputers).[7][12]

In 2024, Microsoft applied a qubit virtualization system to Quantinuum's trapped ion quantum computer to create 12 logical qubits, the most reliable logical qubits on record at the time.[13] The work built upon a previous demonstration that reached error rates 800 times better than the achievement of the same quantum computer without virtualization.[13][14]

Microsoft and Photonic also performed a teleported CNOT gate between qubits physically separated by 40 meters. The work confirmed remote quantum entanglement between T-centers - a requirement for long-distance quantum communication.[15]

In 2025, Microsoft reported the creation of Majorana 1,[16] which is the world's first quantum chip powered by a topological core architecture. The work created a new class of materials called topoconductors, which use topological superconductivity to control hardware-protected topological qubits.[16][17] The research utilized a method to determine fermion parity in Majorana zero modes in a single shot – validating a necessary ingredient for utility-scale topological quantum computation architectures based on measurement.[18]

Software

For quantum applications, Azure Quantum developed Q# (pronunciation: Q Sharp), a quantum programming language, and an open-source software development kit for quantum algorithm development and simulation.[1]

The Azure Quantum Resource Estimator estimates resources required to execute a given quantum algorithm on a fault-tolerant quantum computer.[19]

In 2023, Azure Quantum Elements added Microsoft Copilot, a GPT-4 based large language model tool to query and visualize data, write code, and initiate simulations.[7]

The same year, Microsoft developed Quantum Intermediate Representation (QIR) from LLVM as a common interface between programming languages and target quantum processors.[20]

Microsoft also developed gate-efficient algorithmic methods to perform faster Trotter steps with lower gate complexity, enabling efficient quantum simulations that reduce the required quantum hardware resources.[21]

Azure Quantum Elements

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Perspective

The Azure Quantum Elements platform combines artificial intelligence (AI) and traditional high-performance computing with quantum tools for materials science, chemistry and pharmaceutical research.[22] The platform uses physics-based AI models and advanced algorithms to process complex research data and draw conclusions.[23]

In January 2024, Microsoft and Pacific Northwest National Laboratory used AI and HPC to model and screen 32 million new candidate materials to develop a more efficient rechargeable battery material. The joint project generated new material candidates, then conducted a hyper-accelerated search among them to reach a single suitable candidate that could potentially replace the lithium-ion.[24]

In July 2024, Microsoft released a Generative Chemistry tool for Azure Quantum Elements that uses generative AI to identify the right molecules to use for a particular application. Microsoft also released an Accelerated Density Functional Theory tool to simulate simulations of a molecule's electronic structure using density functional theory (DFT).[25]

Microsoft also used two logical qubits integrated with AI and cloud high-performance computing to solve a practical chemistry problem.[26] According to Microsoft, this case study on catalytic reactions producing chiral molecules represents the first time an HPC system, AI, and quantum computing hardware have been deployed together to solve a specific scientific problem.[26]

In pharmaceuticals, Azure Quantum Elements and HPC platform was integrated with 1910 Gentetics' computational and wet lab biological information, laboratory automation powered by robotics and multimodal AI models for drug discovery.[27]

See also

References

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