chore(deps): bump rustls-webpki from 0.103.10 to 0.103.13 in /qdp (#1288)

Bumps [rustls-webpki](https://github.com/rustls/webpki) from 0.103.10 to 0.103.13.
- [Release notes](https://github.com/rustls/webpki/releases)
- [Commits](https://github.com/rustls/webpki/compare/v/0.103.10...v/0.103.13)

---
updated-dependencies:
- dependency-name: rustls-webpki
  dependency-version: 0.103.13
  dependency-type: indirect
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
1 file changed
tree: 80572a3d4aaedfafce1c7438fad846532cfeded8
  1. .devcontainer/
  2. .github/
  3. dev/
  4. docs/
  5. examples/
  6. qdp/
  7. qumat/
  8. testing/
  9. website/
  10. .asf.yaml
  11. .cherry_picker.toml
  12. .dockerignore
  13. .gitignore
  14. .pre-commit-config.yaml
  15. CONTRIBUTING.md
  16. doap_Mahout.rdf
  17. Dockerfile.qdp-amd
  18. KEYS
  19. LICENSE
  20. lychee.toml
  21. Makefile
  22. NOTICE
  23. pyproject.toml
  24. README.md
  25. uv.lock
README.md

Apache Mahout

License Python GitHub Stars GitHub Contributors

The goal of the Apache Mahoutâ„¢ project is to build an environment for quickly creating scalable, performant machine learning applications.
For additional information about Mahout, visit the Mahout Home Page

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 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

pip install qumat

with QDP (Quantum Data Plane) support

pip install qumat[qdp]

Qumat: Run a Quantum Circuit

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

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

2025

  • [x] FOSDEM talk
  • [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.