Xanadu

aid: xanadu-ai
name: Xanadu
description: Xanadu is a Canadian photonic quantum computing company building room-temperature, fault-tolerant, scalable quantum
  computers based on photonic continuous-variable (CV) and Gaussian boson sampling architectures. Xanadu maintains a large
  open-source software stack — most notably PennyLane (the cross-platform framework for quantum differentiable programming,
  quantum chemistry, and quantum machine learning), Catalyst (a JIT/MLIR compiler for hybrid quantum-classical programs),
  the PennyLane Lightning family of high-performance state-vector and tensor-network simulators, the PennyLane Plugin ecosystem
  (Qiskit/IBM, AWS Braket, Cirq, Rigetti, IonQ, AQT, Quantinuum, Qulacs, ProjectQ, and Xanadu's own Strawberry Fields), MrMustard,
  Jet, FlamingPy, The Walrus, Blackbird (the CV quantum assembly language), XIR, and the Xanadu Quantum Codebook. Xanadu hardware
  milestones include the X8 photonic chip, Borealis (quantum advantage demonstration on a 216-mode programmable Gaussian boson
  sampler), and Aurora (the first modular, networked photonic quantum computer combining server racks and kilometres of optical
  fibre). The Xanadu Cloud — the original photonic-hardware-as-a-service offering with REST/Python/CLI access to Borealis
  and X8 — has been retired (the `xanadu-cloud-client` and Strawberry Fields repos are archived), and Xanadu's developer-facing
  surface today centres on the PennyLane Python ecosystem and hardware execution via PennyLane plugins against partner cloud
  platforms.
url: https://raw.githubusercontent.com/api-evangelist/xanadu-ai/refs/heads/main/apis.yml
humanURL: https://www.xanadu.ai
deliveryModel:
  model: open-core
  license: Apache-2.0
  open_source: true
  commercial: true
  callable_host: false
  label: Open core · an OSS project plus a commercial hosted product
  confidence: high
  source:
  - license
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source:
  - security
  generated: '2026-11-13'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/xanadu-ai.png
created: '2026-05-25'
modified: '2026-05-25'
specificationVersion: '0.23'
x-docs-platform: readthedocs
x-docs-platform-confidence: high
x-docs-platform-checked: 2026-10-17
tags:
- Quantum Computing
- Photonic Quantum
- Quantum Machine Learning
- Quantum Chemistry
- Differentiable Programming
- PennyLane
- Open Source
- Compilers
- Simulator
- Continuous Variable
- Gaussian Boson Sampling
- Fault Tolerance
tags_raw:
- Quantum Computing
- Photonic Quantum
- Quantum Machine Learning
- Quantum Chemistry
- Differentiable Programming
- PennyLane
- Open Source
- Compilers
- Simulators
- Continuous Variable
- Gaussian Boson Sampling
- Fault Tolerance
- Open-Source
kind: contract
access: 3rd-Party
apis:
- aid: xanadu-ai:pennylane
  name: PennyLane
  tags:
  - Quantum Machine Learning
  - Differentiable Programming
  - Hybrid
  - Python
  humanURL: https://pennylane.ai
  properties:
  - type: Documentation
    url: https://docs.pennylane.ai/en/stable/
  - type: APIReference
    url: https://docs.pennylane.ai/en/stable/code/qml.html
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane
  - type: SDKs
    url: https://pypi.org/project/PennyLane/
  - type: Tutorials
    url: https://pennylane.ai/qml/demonstrations
  - type: CodeExamples
    url: https://github.com/PennyLaneAI/demos
  description: PennyLane is the flagship open-source Python framework for quantum differentiable programming — train and optimize
    variational quantum circuits with the same automatic differentiation engines used in classical machine learning. PennyLane
    unifies quantum machine learning, quantum chemistry, and hybrid quantum-classical workflows behind a single device-abstraction
    API, interoperates with NumPy, PyTorch, JAX, and TensorFlow/Keras, and runs against 40+ simulators and hardware backends
    through its plugin ecosystem. Apache 2.0 licensed. 3,200+ GitHub stars.
- aid: xanadu-ai:pennylane-catalyst
  name: PennyLane Catalyst
  tags:
  - Compilers
  - JIT
  - MLIR
  - QIR
  humanURL: https://docs.pennylane.ai/projects/catalyst
  properties:
  - type: Documentation
    url: https://docs.pennylane.ai/projects/catalyst/en/stable/
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/catalyst
  - type: SDKs
    url: https://pypi.org/project/PennyLane-Catalyst/
  description: Catalyst is a JIT compiler for hybrid quantum programs written in PennyLane. The `@qjit` decorator compiles
    entire quantum-classical workflows — including conditionals, loops, and gradients — to a custom MLIR quantum dialect,
    then lowers to LLVM and QIR for execution against Lightning, AWS Braket, and an expanding set of QPUs. Apache 2.0.
- aid: xanadu-ai:pennylane-lightning
  name: PennyLane Lightning
  tags:
  - Simulator
  - State Vector
  - Tensor Networks
  - GPU
  - HPC
  tags_raw:
  - Simulators
  - State Vector
  - Tensor Networks
  - GPU
  - HPC
  humanURL: https://docs.pennylane.ai/projects/lightning
  properties:
  - type: Documentation
    url: https://docs.pennylane.ai/projects/lightning/en/stable/
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-lightning
  - type: SDKs
    url: https://pypi.org/project/PennyLane-Lightning/
  description: The Lightning plugin family — `lightning.qubit` (C++ CPU), `lightning.gpu` (cuQuantum), and `lightning.kokkos`
    (multi-architecture HPC) — provides Xanadu's fast state-vector and tensor-network simulators for PennyLane. Designed for
    20+ qubit research workflows and HPC integration.
- aid: xanadu-ai:pennylane-plugins
  name: PennyLane Plugins
  tags:
  - Plugins
  - Hardware
  - Devices
  - Integration
  tags_raw:
  - Plugins
  - Hardware
  - Devices
  - Integrations
  humanURL: https://pennylane.ai/plugins
  properties:
  - type: Documentation
    url: https://pennylane.ai/plugins
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-qiskit
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-cirq
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-rigetti
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/PennyLane-IonQ
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-aqt
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-honeywell
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-qulacs
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-pq
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/PennyLane-qsharp
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-orquestra
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/pennylane-sf
  description: The PennyLane plugin layer exposes a uniform `qml.device` interface across third-party quantum SDKs and QPU
    clouds — IBM Qiskit / IBM Quantum, AWS Braket, Google Cirq, Rigetti Forest, IonQ, AQT, Quantinuum (Honeywell), Microsoft
    QDK / Q#, Qulacs, ProjectQ, Zapata Orquestra, and Xanadu Strawberry Fields. Each plugin is a separate pip-installable
    Python package.
- aid: xanadu-ai:pennylane-qchem
  name: PennyLane Quantum Chemistry (qchem)
  tags:
  - Quantum Chemistry
  - VQE
  - Hamiltonian
  - Molecules
  humanURL: https://docs.pennylane.ai/en/stable/code/qml_qchem.html
  properties:
  - type: Documentation
    url: https://docs.pennylane.ai/en/stable/code/qml_qchem.html
  - type: Tutorials
    url: https://pennylane.ai/qml/whatisqchem
  description: '`qml.qchem` is PennyLane''s quantum chemistry submodule for constructing molecular Hamiltonians,

    differentiable Hartree-Fock, VQE workflows, and resource estimation against fault-tolerant algorithms,

    integrated with PennyLane''s autodiff stack.'
- aid: xanadu-ai:pennylane-datasets
  name: PennyLane Datasets
  tags:
  - Datasets
  - Benchmarks
  humanURL: https://pennylane.ai/datasets
  properties:
  - type: Documentation
    url: https://pennylane.ai/datasets
  - type: APIReference
    url: https://docs.pennylane.ai/en/stable/code/qml_data.html
  - type: GitHubRepository
    url: https://github.com/PennyLaneAI/DatasetsSource
  description: A curated catalogue of pre-computed quantum datasets — molecular Hamiltonians, spin systems, QML benchmarks
    — accessible via `qml.data.load(...)` for reproducible experiments and education.
- aid: xanadu-ai:strawberry-fields
  name: Strawberry Fields
  tags:
  - Photonic
  - Continuous Variable
  - Simulator
  - Archived
  tags_raw:
  - Photonic
  - Continuous Variable
  - Simulators
  - Archived
  humanURL: https://strawberryfields.ai
  properties:
  - type: Documentation
    url: https://strawberryfields.ai/photonics/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/strawberryfields
  - type: SDKs
    url: https://pypi.org/project/StrawberryFields/
  description: Strawberry Fields is Xanadu's full-stack Python library for designing, simulating, and optimizing continuous-variable
    (CV) photonic quantum circuits. Historically the bridge from Python to Xanadu's X8 and Borealis hardware via the Xanadu
    Cloud. The repository is now archived following the Xanadu Cloud retirement; remains useful as an educational/simulator
    stack for CV quantum optics.
- aid: xanadu-ai:mrmustard
  name: MrMustard
  tags:
  - Photonic
  - Continuous Variable
  - Differentiable
  - Phase Space
  humanURL: https://mrmustard.readthedocs.io
  properties:
  - type: Documentation
    url: https://mrmustard.readthedocs.io/en/latest/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/MrMustard
  - type: SDKs
    url: https://pypi.org/project/mrmustard/
  description: MrMustard is a differentiable simulator that acts as a bridge between phase-space and Fock-space representations
    of bosonic / CV quantum systems. Built for design and optimization of photonic circuits with gradient-based methods.
- aid: xanadu-ai:thewalrus
  name: The Walrus
  tags:
  - Hafnians
  - Gaussian Boson Sampling
  - Numerical Library
  humanURL: https://the-walrus.readthedocs.io
  properties:
  - type: Documentation
    url: https://the-walrus.readthedocs.io/en/latest/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/thewalrus
  - type: SDKs
    url: https://pypi.org/project/thewalrus/
  description: The Walrus is a high-performance C++/Python library for computing hafnians, loop hafnians, Hermite polynomials,
    and Gaussian boson sampling probabilities — the numerical backbone underpinning Xanadu's photonic simulations.
- aid: xanadu-ai:jet
  name: Jet
  tags:
  - Tensor Networks
  - Simulator
  - C++
  tags_raw:
  - Tensor Networks
  - Simulators
  - C++
  humanURL: https://quantum-jet.readthedocs.io
  properties:
  - type: Documentation
    url: https://quantum-jet.readthedocs.io/en/latest/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/jet
  description: Jet is a cross-platform C++ library for simulating quantum circuits via tensor-network contractions, with task-based
    parallelism for HPC-scale workloads.
- aid: xanadu-ai:flamingpy
  name: FlamingPy
  tags:
  - Error Correction
  - Fault Tolerance
  - GKP
  - Archived
  humanURL: https://flamingpy.readthedocs.io
  properties:
  - type: Documentation
    url: https://flamingpy.readthedocs.io/en/latest/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/flamingpy
  description: FlamingPy is a Python library with multiple backends for efficient simulation of error correction in fault-tolerant
    photonic quantum architectures, including GKP-encoded qubit cluster states. Archived.
- aid: xanadu-ai:blackbird
  name: Blackbird Language
  tags:
  - Quantum Assembly
  - Continuous Variable
  - Programming Language
  humanURL: https://strawberryfields.ai/photonics/blackbird/
  properties:
  - type: Documentation
    url: https://quantum-blackbird.readthedocs.io/en/latest/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/blackbird
  description: Blackbird is Xanadu's quantum assembly language for continuous-variable photonic quantum computation. Programs
    target Strawberry Fields simulators and were historically deployed against the X8 / Borealis hardware via Xanadu Cloud.
- aid: xanadu-ai:xir
  name: XIR
  tags:
  - Intermediate Representation
  - Compilers
  humanURL: https://xir.readthedocs.io
  properties:
  - type: Documentation
    url: https://xir.readthedocs.io/en/latest/
  - type: GitHubRepository
    url: https://github.com/XanaduAI/xir
  description: XIR is an intermediate representation language for quantum circuits, designed to ferry circuits between front-end
    frameworks (Strawberry Fields, PennyLane) and backend hardware/simulators.
- aid: xanadu-ai:xanadu-quantum-codebook
  name: Xanadu Quantum Codebook
  tags:
  - Education
  - Learning
  - Interactive
  humanURL: https://pennylane.ai/codebook
  properties:
  - type: Documentation
    url: https://pennylane.ai/codebook
  - type: GitHubRepository
    url: https://github.com/XanaduAI/Xanadu-Quantum-Codebook
  description: An interactive, free, browser-based quantum computing course built on PennyLane. Covers introductory quantum
    computing, single- and multi-qubit systems, quantum algorithms, and quantum chemistry with executable code cells.
common:
- type: Website
  url: https://www.pennylane.ai/
- type: IssueTracker
  url: https://github.com/PennyLaneAI/pennylane/issues
- type: Releases
  url: https://github.com/PennyLaneAI/pennylane/releases
- type: CodeOfConduct
  url: https://github.com/PennyLaneAI/pennylane/blob/main/.github/CODE_OF_CONDUCT.md
- type: ContributionGuide
  url: https://github.com/PennyLaneAI/pennylane/blob/main/.github/CONTRIBUTING.md
- type: License
  name: Apache-2.0
  url: https://github.com/PennyLaneAI/pennylane/blob/main/LICENSE
- type: DomainSecurity
  url: security/xanadu-ai-domain-security.yml
- url: https://www.xanadu.ai
  name: Xanadu Homepage
  type: Portal
- url: https://pennylane.ai
  name: PennyLane Portal
  type: Portal
- url: https://docs.pennylane.ai/en/stable/
  name: PennyLane Docs
  type: Documentation
- url: https://docs.pennylane.ai/en/stable/introduction/pennylane.html
  name: Getting Started with PennyLane
  type: GettingStarted
- url: https://github.com/XanaduAI
  name: Xanadu GitHub Organization
  type: GitHubOrganization
- url: https://github.com/PennyLaneAI
  name: PennyLane GitHub Organization
  type: GitHubOrganization
- url: https://pypi.org/project/PennyLane/
  name: PennyLane on PyPI
  type: SDKs
- url: https://pennylane.ai/qml/demonstrations
  name: PennyLane Demonstrations
  type: Tutorials
- url: https://pennylane.ai/codebook
  name: Xanadu Quantum Codebook
  type: Courses
- url: https://pennylane.ai/datasets
  name: PennyLane Datasets
  type: Resources
- url: https://pennylane.ai/plugins
  name: PennyLane Plugins Directory
  type: Integrations
- url: https://pennylane.ai/devices
  name: PennyLane Devices
  type: Integrations
- url: https://discuss.pennylane.ai
  name: PennyLane Discussion Forum
  type: Support
- url: https://www.xanadu.ai/blog
  name: Xanadu Blog
  type: Blog
- url: https://pennylane.ai/blog
  name: PennyLane Blog
  type: Blog
- url: https://www.youtube.com/c/XanaduAI
  name: Xanadu YouTube
  type: YouTube
- url: https://www.linkedin.com/company/xanaduai
  name: Xanadu on LinkedIn
  type: LinkedIn
- url: https://twitter.com/XanaduAI
  name: Xanadu on X
  type: X
- url: https://www.xanadu.ai/careers
  name: Xanadu Careers
  type: Resources
- url: https://www.xanadu.ai/qhack
  name: QHack — Quantum Machine Learning Hackathon
  type: Events
- url: https://docs.pennylane.ai/en/stable/development/release_notes.html
  name: PennyLane Release Notes
  type: ReleaseNotes
- url: https://docs.pennylane.ai/en/stable/development/release_notes.html
  name: PennyLane Changelog
  type: ChangeLog
- url: https://github.com/PennyLaneAI/pennylane/blob/master/LICENSE
  name: Apache License 2.0 (PennyLane)
  type: Legal
- url: https://www.xanadu.ai/privacy
  name: Privacy Policy
  type: PrivacyPolicy
- url: https://www.xanadu.ai/terms
  name: Terms of Service
  type: TermsOfService
- name: Features
  type: Features
  data:
  - name: Open-source quantum differentiable programming
    description: Train variational quantum circuits with PyTorch / JAX / TensorFlow / NumPy autodiff through PennyLane.
  - name: Hardware-agnostic device API
    description: Swap between 40+ simulators and QPU backends behind a single `qml.device(...)` interface.
  - name: JIT compilation of hybrid programs
    description: Catalyst compiles quantum + classical control flow to MLIR / LLVM / QIR for fast, gradient-aware execution.
  - name: High-performance simulators
    description: Lightning (CPU/C++), Lightning-GPU (cuQuantum), Lightning-Kokkos (HPC), and Jet (tensor-network) scale to
      research-grade workloads.
  - name: Quantum chemistry built in
    description: '`qml.qchem` provides differentiable Hartree-Fock, VQE, and Hamiltonian construction.'
  - name: Curated datasets and codebook
    description: PennyLane Datasets and the Xanadu Quantum Codebook deliver standardized benchmarks and an interactive learning
      curriculum.
  - name: Photonic continuous-variable tooling
    description: Strawberry Fields, MrMustard, The Walrus, Blackbird, and FlamingPy form a complete CV photonic stack — simulation,
      optimization, fault-tolerant codes.
  - name: Hardware milestones
    description: X8 (8-mode squeezed-light chip), Borealis (216-mode programmable Gaussian boson sampler; Nature 2022 quantum
      advantage), Aurora (modular networked photonic computer, 2025).
- name: UseCases
  type: UseCases
  data:
  - name: Quantum Machine Learning
    description: Variational classifiers, quantum kernels, generative quantum models, hybrid quantum-classical neural networks.
  - name: Quantum Chemistry
    description: Molecular ground-state energies via VQE, differentiable Hartree-Fock, resource estimation for fault-tolerant
      electronic-structure algorithms.
  - name: Quantum Algorithm Research
    description: Rapid prototyping of QAOA, amplitude estimation, quantum signal processing, and error-correction protocols.
  - name: Hybrid HPC Workloads
    description: Catalyst + Lightning-GPU / Lightning-Kokkos for scaling hybrid quantum-classical workloads on HPC clusters.
  - name: Quantum Education
    description: PennyLane Codebook, demos, and datasets for university courses and self-directed learners.
  - name: Hardware Benchmarking
    description: Cross-vendor execution and benchmarking via the plugin ecosystem (IBM, IonQ, Rigetti, AWS Braket, AQT, Quantinuum).
- name: Integrations
  type: Integrations
  data:
  - name: IBM Quantum / Qiskit
    description: '`pennylane-qiskit` plugin — run circuits on IBM Quantum hardware and Qiskit simulators.'
  - name: AWS Braket
    description: Amazon Braket plugin — execute on Rigetti, IonQ, OQC, Quera, and the SV1/DM1/TN1 managed simulators.
  - name: Google Cirq
    description: '`pennylane-cirq` plugin for Cirq simulators and Google Quantum AI workflows.'
  - name: Rigetti Forest
    description: '`pennylane-rigetti` plugin for Rigetti QPUs, QVM, and wavefunction simulator.'
  - name: IonQ
    description: '`PennyLane-IonQ` plugin for IonQ simulators and trapped-ion hardware.'
  - name: AQT (Alpine Quantum Technologies)
    description: '`pennylane-aqt` plugin for AQT ion-trap hardware.'
  - name: Quantinuum (Honeywell)
    description: '`pennylane-honeywell` plugin for Quantinuum / Honeywell ion-trap hardware.'
  - name: Microsoft Q# / QDK
    description: '`PennyLane-qsharp` plugin for the Microsoft Quantum Development Kit full state simulator.'
  - name: Qulacs
    description: '`pennylane-qulacs` plugin — high-performance C++ simulator.'
  - name: ProjectQ
    description: '`pennylane-pq` plugin — IBM, simulator, and classical-simulator devices via ProjectQ.'
  - name: Strawberry Fields
    description: '`pennylane-sf` plugin — drive Xanadu''s continuous-variable photonic simulators.'
  - name: PyTorch
    description: PennyLane's `torch` interface for gradient-based optimization with PyTorch tensors.
  - name: JAX
    description: PennyLane's `jax` interface and Catalyst JAX support.
  - name: TensorFlow / Keras
    description: PennyLane's `tf` interface for seamless integration with TensorFlow models.
  - name: NumPy / Autograd
    description: Default PennyLane interface for classical autodiff with NumPy.
- type: UsageTerms
  url: terms/xanadu-ai-terms-of-service.yml
- type: DataProcessing
  url: privacy/xanadu-ai-privacy-policy.yml
- type: Eligibility
  url: eligibility/xanadu-ai-eligibility.yml
- type: AIPreferences
  url: ai-preferences/xanadu-ai-ai-preferences.yml
- type: DataLicense
  url: data-license/xanadu-ai-data-license.yml
maintainers:
- FN: Kin Lane
  email: info@apievangelist.com
  url: https://kinlane.com