open-standards/wai/wai-web/Cargo.toml
Transaction Science f37bc12642
Some checks failed
WAI conformance / cargo-class corpora · linux (push) Successful in 28s
WAI conformance / cross-arch byte-equality · linux (push) Successful in 14s
WAI conformance / cargo-class corpora · linux-arm64 (push) Successful in 1m11s
WAI conformance / cross-arch byte-equality · linux-arm64 (push) Successful in 46s
WAI conformance / cargo-class corpora · macos (push) Successful in 1m19s
WAI conformance / cross-arch byte-equality · macos (push) Successful in 41s
WAI conformance / cargo-class corpora · windows (push) Has been cancelled
WAI conformance / cross-arch byte-equality · windows (push) Has been cancelled
wai: learning from quantum data — the surviving moat (wai.quantum.qdata)
The exponential sample-complexity separation for Pauli-channel learning
(Chen-Cotler-Huang-Li / Huang Science 2022), surfaced as a first-class quantum-ML
capability: estimating an n-qubit channel's 2^n fidelities to accuracy epsilon needs
Omega(2^n) copies WITHOUT quantum memory but O(1/eps^2) n-independent copies WITH a
two-copy Bell measurement. Both estimators simulated exactly (deterministic in seed);
the demo shows Bell resolving all fidelities in a fixed copy budget while the
entanglement-free strategy is starved. A data-access advantage that survives
dequantization — and exactly why noise_learn's Bell/CB sampling is data-efficient.
wai-web QDataSeparation; live /quantum-ml panel tying the separation to the deployed
wai.quantum.cal.noise_learn (verified receipt + byte-exact model hash).

Co-Authored-By: Claude Opus 4.8 <[email protected]>
2026-08-29 11:46:45 -04:00

36 lines
2 KiB
TOML

[package]
name = "wai-web"
version = "0.3.0"
edition = "2021"
license = "Apache-2.0"
description = "WAI envelope parser + capability dispatch for the browser. Wasm-bindgen surface over the standard's container format. NOT a codec backend — backends are pluggable, the deployer chooses (WASM / WebGPU / WebNN / native ONNX / transformers.js / etc.)."
[lib]
crate-type = ["cdylib"]
[dependencies]
wasm-bindgen = { version = "0.2", features = ["serde-serialize"] }
serde-wasm-bindgen = "0.6"
serde = { version = "1", features = ["derive"] }
serde_json = { version = "1", features = ["preserve_order"] }
js-sys = "0.3"
# THE world engine — the same crate native sinks run, compiled to wasm32
# with the codec chain off. No second implementation: replay-equivalence
# in the browser is the identical Rust that generated the conformance
# corpus hashes.
wai = { path = "../wai-rs", default-features = false, features = ["world", "audio_scene", "haptic", "splat4d", "provenance", "score", "film", "neural_int", "generate", "video_int", "audio_int", "world_model", "world_int", "splat_int", "quantum", "quantum_ops", "quantum_cal", "quantum_mitigate", "quantum_qec", "quantum_control", "quantum_noise", "quantum_compile", "quantum_atom", "quantum_qbom", "quantum_receipt", "quantum_toolchain", "quantum_mps", "quantum_stabilizer", "quantum_pauli", "quantum_vml", "quantum_phasor", "quantum_qfhrr", "quantum_kernel", "quantum_phasor_meter", "quantum_qdata"] }
ed25519-dalek = "2" # actor keys for browser-side op authoring (same version as wai-rs)
blake3 = "1" # in-page receipt check: hash a decoded image against a pinned digest
[profile.release]
opt-level = "s" # size, not speed — runtime is parse-only
lto = true
codegen-units = 1
strip = "symbols"
[package.metadata.wasm-pack.profile.release]
# The host's wasm-opt (binaryen) is behind the Rust toolchain's emitted
# wasm features; rustc already runs LTO + size opts so skipping wasm-opt
# costs little. Re-enable when binaryen catches up.
wasm-opt = false