mahout

# Apache Mahout The goal of the Apache Mahout™ project is to build an environment for quickly creating scalable, performant machine learning applications.\ For additional information about Mahout, visit the [Mahout Home Page](http://mahout.apache.org/) ## Qumat

Qumat is a high-level Python library for quantum computing that provides: - **Quantum Circuit Abstraction** - Build quantum circuits with standard gates (Hadamard, CNOT, Pauli, etc.) and run them on Qiskit, Cirq, or Amazon Braket with a single unified API. Write once, execute anywhere. Check out [basic gates](https://mahout.apache.org/docs/qumat/basic-gates/) for a quick introduction to the basic gates supported across all backends. - **QDP (Quantum Data Plane)** - Encode classical data into quantum states using GPU-accelerated kernels. Zero-copy tensor transfer via DLPack lets you move data between PyTorch, NumPy, and TensorFlow without overhead. ## Quick Start ```bash pip install qumat ``` with QDP (Quantum Data Plane) support ```bash pip install qumat[qdp] ``` ### Qumat: Run a Quantum Circuit ```python from qumat import QuMat qumat = QuMat({"backend_name": "qiskit", "backend_options": {"simulator_type": "aer_simulator"}}) qumat.create_empty_circuit(num_qubits=2) qumat.apply_hadamard_gate(0) qumat.apply_cnot_gate(0, 1) qumat.execute_circuit() ``` ### QDP: Encode data for Quantum ML ```python import qumat.qdp as qdp engine = qdp.QdpEngine(device_id=0) qtensor = engine.encode([1.0, 2.0, 3.0, 4.0], num_qubits=2, encoding_method="amplitude") ``` ## Roadmap ### 2024 - [x] Transition of Classic to maintenance mode - [x] Integration of Qumat with hardened (tests, docs, CI/CD) Cirq, Qiskit, and Braket backends - [x] Integration with Amazon Braket - [x] [Public talk about Qumat](https://2024.fossy.us/schedule/presentation/265/) ### 2025 - [x] [FOSDEM talk](https://fosdem.org/2025/schedule/event/fosdem-2025-5298-introducing-qumat-an-apache-mahout-joint-/) - [x] QDP: Foundation & Infrastructure (Rust workspace, build configuration) - [x] QDP: Core Implementation (CUDA kernels, CPU preprocessing, GPU memory management) - [x] QDP: Zero-copy and Safety (DLManagedTensor, DLPack structures) - [x] QDP: Python Binding (PyO3 wrapping, DLPack protocol) ### Q1 2026 - [ ] QDP: Input Format Support (PyTorch, NumPy, TensorFlow integration) - [ ] QDP: Verification and Testing (device testing, benchmarking) - [ ] QDP: Additional Encoders (angle/basis encoding, multi-GPU optimization) - [ ] QDP: Integration & Release (documentation, example notebooks, PyPI publishing) ## Legal Please see the `NOTICE.txt` included in this directory for more information.