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
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
- Transition of Classic to maintenance mode
- Integration of Qumat with hardened (tests, docs, CI/CD) Cirq, Qiskit, and Braket backends
- Integration with Amazon Braket
- Public talk about Qumat
2025
- FOSDEM talk
- QDP: Foundation & Infrastructure (Rust workspace, build configuration)
- QDP: Core Implementation (CUDA kernels, CPU preprocessing, GPU memory management)
- QDP: Zero-copy and Safety (DLManagedTensor, DLPack structures)
- 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.
Release files for qumat 0.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| qumat-0.6.0.tar.gz | 17.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| qumat-0.6.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 40.4 kB
Release files / qumat-0.6.0.tar.gz
| Download URL | qumat-0.6.0.tar.gz |
|---|---|
| Size | 17.8 kB |
| Tags | Source |
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Release files / qumat-0.6.0-py3-none-any.whl
| Download URL | qumat-0.6.0-py3-none-any.whl |
|---|---|
| Size | 22.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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