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 image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/apis-json-logo.jpg created: '2026-05-25' modified: '2026-05-25' specificationVersion: '0.18' tags: - Quantum Computing - Photonic Quantum - Quantum Machine Learning - Quantum Chemistry - Differentiable Programming - PennyLane - Open Source - Compilers - Simulators - Continuous Variable - Gaussian Boson Sampling - Fault Tolerance 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: - 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 - 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 - 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 - 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: 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. maintainers: - FN: Kin Lane email: info@apievangelist.com url: https://kinlane.com