Strong empiricalQuantum machine learning
Phase feature-map benchmark · 3 qubits
A fixed-data feature-map scaffold with Hadamards, local phase rotations, and pairwise ZZ encodings.
Explore quantum algorithms and circuits, with resource estimates, verification evidence, and sources.
Every record is classified by how it was verified. The badge shows the strongest tier of evidence; the chips list each method that applies.
The defining behavior was checked exactly: a mathematical identity, a full statevector or stabilizer simulation, or an exhaustive basis-state truth table.
The design was verified by construction plus measured evidence: statistical re-execution, small-instance analytic agreement, sub-block, echo, or invariant checks. Scale-specific bugs can still survive.
The record rests on external authority: peer-reviewed papers, standard textbooks, expert review, or evidence carried over from related verified entries. Nothing here was re-executed by this catalog.
Only automated (LLM-assisted) review or an unreviewed community submission backs this record so far. Treat it as a starting point, not evidence.
A fixed-data feature-map scaffold with Hadamards, local phase rotations, and pairwise ZZ encodings.
Detect anomalous, potentially fraudulent, transactions in a credit-card dataset, framed as an anomaly-detection task and compared against classical kernel-based benchmarks such as one-class support vector machines.
A quantum feature-map record paired with a classical SVM so model quality and data costs stay visible.
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