ryankert01 opened a new issue, #1008: URL: https://github.com/apache/mahout/issues/1008
## Background ZZFeatureMap is the most widely-used data encoding in quantum machine learning. It's the default in Qiskit and PennyLane for quantum kernel methods and variational classifiers. QDP currently supports amplitude, angle, basis, and IQP encodings. Adding ZZFeatureMap completes our QML encoding suite. ## What is ZZFeatureMap? Maps classical features to quantum states using: 1. Hadamard gates (superposition) 2. RZ gates (single-qubit rotations) 3. ZZ interactions (two-qubit entanglement) 4. Repetition layers for expressivity ## Deliverables - [ ] Rust encoder implementing `QuantumEncoder` trait - [ ] CUDA kernel for GPU-accelerated state vector computation - [ ] Support for entanglement patterns: full, linear, circular - [ ] Configurable repetition layers - [ ] Python bindings via existing QDP API - [ ] Tests validating against Qiskit reference ## Files to Create ``` qdp/qdp-core/src/gpu/encodings/zzfeaturemap.rs qdp/qdp-kernels/src/zzfeaturemap.cu testing/qdp/test_zzfeaturemap.py ``` ## References - [Qiskit ZZFeatureMap](https://qiskit.org/documentation/stubs/qiskit.circuit.library.ZZFeatureMap.html) - [Havlíček et al. "Supervised learning with quantum-enhanced feature spaces"](https://www.nature.com/articles/s41586-019-0980-2) - Existing IQP encoder as implementation reference: `qdp/qdp-core/src/gpu/encodings/iqp.rs` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
