# Shared recipe Calling a method the best classifier is meaningless without a frozen bake-off recipe. ARCADE’s headline claim is fairness: the same traces, the same preprocessing, the same splits, the same metrics, and the same report shape for every method in a given run. ## What is frozen | Ingredient | Where it lives | Why it matters | |------------|----------------|----------------| | Trace file and keys | ``data.path``, ``data.hdf5_keys`` | Everyone sees the same shots | | Demodulation, boxcar, truncate | ``data.demodulation``, ``data.preprocessing`` | Changes the IQ geometry | | Label packing | ``data.label_format``, ``data.qubit_bit_order`` | Bit-order bugs look like bad models | | Train, validation, and test | ``data.split`` | Leakage across methods is silent | | Filter bank | ``classifiers.filter_types`` | MF, RMF, and EMF must be shared unless a method opts out | | Metrics and report | ``visualization`` settings | Comparable tables | The public reference eight-method recipe is ``configs/paper_all_methods_benchmark.yaml``. Dedicated ``configs/paper_*.yaml`` files may differ slightly when a paper needs a different protocol. Those are paper recipes, not silent edits to the reference benchmark. ## What is allowed to vary Which names appear in ``classifiers.run``. Per-method option blocks such as ``fnn.config_file``. Optional stages such as ``optimization``, ``qec``, and ``hardware.run_synthesis``. ## Pitfalls checklist
HERQULES zoo filters are typically [MF, RMF]. Claiming bit-exact paper
parity needs the paper YAML. Path-signature zoo configs may set
time_augmentation: true while the paper path is two-dimensional I and Q.
Treat Readout 2019 path-signature results as transfer under the zoo recipe.
The name mlp is the scikit-learn multilayer perceptron. It is not the
Lienhard-style fnn. The name reservoir is a deprecated alias of
ngrc. It is not a classical echo-state network.