feat(qdp): add Jax support and generic DLPack fallbackc

[Sumit6307]

This PR aligns with the 2026 Q1 Roadmap for QDP (Quantum Data Plane) regarding "Integration & Release" and "Input Format Support."

Changes

• New feature
• Refactoring
• Test

Why
Currently, the Quantum Data Plane (QDP) has tight integration with PyTorch but lacks native support for the Jax ecosystem, which is a leading framework for quantum machine learning research. Furthermore, the encode method was specialized for specific frameworks, making it harder to support other DLPack-compliant libraries like Cupy. This change enables Mahout to act as a truly universal Quantum Data Plane.

How

• Jax Integration: Created a new jax.rs module that detects Jax arrays and handles asynchronous synchronization via block_until_ready() before data extraction.

• Generic DLPack Fallback: Updated the unified encode method in engine.rs to support any Python object that implements the standard DLPack protocol (__dlpack__ and __dlpack_device__).

• Framework Interoperability: Ensured that the logic is "non-invasive"—the QDP only attempts to synchronize Jax/DLPack objects when they are passed as input, maintaining zero overhead for other paths.

• Improved Validation: Added robust error handling during the DLPack extraction process to ensure device and memory alignment consistency.

• Tests: Added a new test suite in testing/qdp/test_jax.py specifically for Jax-to-QDP-to-PyTorch workflows.

[Sumit6307]

@guan404ming Sir, Plz look into this PR

[400Ping]

cc @viiccwen to take a look first before I make the final call

[400Ping]

Have a better idea for jax, closing it.