Xanadu
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.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles Xanadu the way a machine reads it — 44 machine-readable artifacts across 14 APIs, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Xanadu scores 24.0/100 (emerging), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance.
Kin Score
How this is scored →scored 2026-07-27 · rubric v0.5
How we profile Xanadu
Each block below is one kind of artifact we hold for Xanadu. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
APIs 14
Each API is captured as its own OpenAPI definition — every operation, parameter, and response. This is the single most useful machine-readable description of what an API does, and it's what lets us score, lint, mock, and generate against it without asking the provider for anything.
Individual APIs this provider publishes, each with its own machine-readable definition.
PennyLane
PennyLane is the flagship open-source Python framework for quantum differentiable programming — train and optimize variational quantum circuits with the same automatic different...
PennyLane Catalyst
Catalyst is a JIT compiler for hybrid quantum programs written in PennyLane. The `@qjit` decorator compiles entire quantum-classical workflows — including conditionals, loops, a...
PennyLane Lightning
The Lightning plugin family — `lightning.qubit` (C++ CPU), `lightning.gpu` (cuQuantum), and `lightning.kokkos` (multi-architecture HPC) — provides Xanadu's fast state-vector and...
PennyLane Plugins
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 F...
PennyLane Quantum Chemistry (qchem)
`qml.qchem` is PennyLane's quantum chemistry submodule for constructing molecular Hamiltonians, differentiable Hartree-Fock, VQE workflows, and resource estimation against fault...
PennyLane Datasets
A curated catalogue of pre-computed quantum datasets — molecular Hamiltonians, spin systems, QML benchmarks — accessible via `qml.data.load(...)` for reproducible experiments an...
Strawberry Fields
Strawberry Fields is Xanadu's full-stack Python library for designing, simulating, and optimizing continuous-variable (CV) photonic quantum circuits. Historically the bridge fro...
MrMustard
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 optimizati...
The Walrus
The Walrus is a high-performance C++/Python library for computing hafnians, loop hafnians, Hermite polynomials, and Gaussian boson sampling probabilities — the numerical backbon...
Jet
Jet is a cross-platform C++ library for simulating quantum circuits via tensor-network contractions, with task-based parallelism for HPC-scale workloads.
FlamingPy
FlamingPy is a Python library with multiple backends for efficient simulation of error correction in fault-tolerant photonic quantum architectures, including GKP-encoded qubit c...
Blackbird Language
Blackbird is Xanadu's quantum assembly language for continuous-variable photonic quantum computation. Programs target Strawberry Fields simulators and were historically deployed...
XIR
XIR is an intermediate representation language for quantum circuits, designed to ferry circuits between front-end frameworks (Strawberry Fields, PennyLane) and backend hardware/...
Xanadu Quantum Codebook
An interactive, free, browser-based quantum computing course built on PennyLane. Covers introductory quantum computing, single- and multi-qubit systems, quantum algorithms, and ...
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Features 8
The notable capabilities this provider advertises, captured as structured features so they can be searched and compared instead of read one landing page at a time.
Notable capabilities this provider offers.
Open-source quantum differentiable programming
Train variational quantum circuits with PyTorch / JAX / TensorFlow / NumPy autodiff through PennyLane.
Hardware-agnostic device API
Swap between 40+ simulators and QPU backends behind a single `qml.device(...)` interface.
JIT compilation of hybrid programs
Catalyst compiles quantum + classical control flow to MLIR / LLVM / QIR for fast, gradient-aware execution.
High-performance simulators
Lightning (CPU/C++), Lightning-GPU (cuQuantum), Lightning-Kokkos (HPC), and Jet (tensor-network) scale to research-grade workloads.
Quantum chemistry built in
`qml.qchem` provides differentiable Hartree-Fock, VQE, and Hamiltonian construction.
Curated datasets and codebook
PennyLane Datasets and the Xanadu Quantum Codebook deliver standardized benchmarks and an interactive learning curriculum.
Photonic continuous-variable tooling
Strawberry Fields, MrMustard, The Walrus, Blackbird, and FlamingPy form a complete CV photonic stack — simulation, optimization, fault-tolerant codes.
Hardware milestones
X8 (8-mode squeezed-light chip), Borealis (216-mode programmable Gaussian boson sampler; Nature 2022 quantum advantage), Aurora (modular networked photonic computer, 2025).
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Security Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Use Cases 6
What developers actually build with this provider — captured so the catalogue answers 'what is this for', not just 'what does this expose'.
What developers build with this provider.
Quantum Machine Learning
Variational classifiers, quantum kernels, generative quantum models, hybrid quantum-classical neural networks.
Quantum Chemistry
Molecular ground-state energies via VQE, differentiable Hartree-Fock, resource estimation for fault-tolerant electronic-structure algorithms.
Quantum Algorithm Research
Rapid prototyping of QAOA, amplitude estimation, quantum signal processing, and error-correction protocols.
Hybrid HPC Workloads
Catalyst + Lightning-GPU / Lightning-Kokkos for scaling hybrid quantum-classical workloads on HPC clusters.
Quantum Education
PennyLane Codebook, demos, and datasets for university courses and self-directed learners.
Hardware Benchmarking
Cross-vendor execution and benchmarking via the plugin ecosystem (IBM, IonQ, Rigetti, AWS Braket, AQT, Quantinuum).
Integrations 15
Pre-built integrations with other platforms tell you where this provider already fits in a stack.
Pre-built integrations with other platforms and tools.
IBM Quantum / Qiskit
`pennylane-qiskit` plugin — run circuits on IBM Quantum hardware and Qiskit simulators.
AWS Braket
Amazon Braket plugin — execute on Rigetti, IonQ, OQC, Quera, and the SV1/DM1/TN1 managed simulators.
Google Cirq
`pennylane-cirq` plugin for Cirq simulators and Google Quantum AI workflows.
Rigetti Forest
`pennylane-rigetti` plugin for Rigetti QPUs, QVM, and wavefunction simulator.
IonQ
`PennyLane-IonQ` plugin for IonQ simulators and trapped-ion hardware.
AQT (Alpine Quantum Technologies)
`pennylane-aqt` plugin for AQT ion-trap hardware.
Quantinuum (Honeywell)
`pennylane-honeywell` plugin for Quantinuum / Honeywell ion-trap hardware.
Microsoft Q# / QDK
`PennyLane-qsharp` plugin for the Microsoft Quantum Development Kit full state simulator.
Qulacs
`pennylane-qulacs` plugin — high-performance C++ simulator.
ProjectQ
`pennylane-pq` plugin — IBM, simulator, and classical-simulator devices via ProjectQ.
Strawberry Fields
`pennylane-sf` plugin — drive Xanadu's continuous-variable photonic simulators.
PyTorch
PennyLane's `torch` interface for gradient-based optimization with PyTorch tensors.
JAX
PennyLane's `jax` interface and Catalyst JAX support.
TensorFlow / Keras
PennyLane's `tf` interface for seamless integration with TensorFlow models.
NumPy / Autograd
Default PennyLane interface for classical autodiff with NumPy.
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Resources
Every other property we hold for Xanadu — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Get Started 3
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Build 3
SDKs, sample code, and the tooling you integrate with
Access & Security 1
Authentication, authorization, and security posture
Learn 3
Tutorials, courses, talks, and written guidance
Operate 3
Status, limits, changes, and where to get help
Commercial 3
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
Other 4
Properties that don't map to a standard resource type
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