FEAT: float_power ufunc implementation

[SwayamInSync]

Copilot Summary

This pull request adds full support for the float_power ufunc to the quad-precision dtype implementation, ensuring its behavior matches NumPy's expectations for floating-point types. The changes include the implementation of the float_power operation, updates to documentation, and comprehensive tests to verify correctness and edge cases.

Quad-precision ufunc implementation:

• Added support for the float_power ufunc in init_quad_binary_ops, using the same implementation as power, since quad-precision is already a floating-point type.

Documentation and release tracking:

• Updated release_tracker.md to mark float_power as implemented and tested, reflecting its new support status.

Testing and validation:

• Added extensive parameterized tests for float_power in test_quaddtype.py, covering a wide range of cases including integer and fractional exponents, negative bases, zero and infinity handling, NaN propagation, integer promotion, and array operations. These tests ensure the quad-precision implementation matches NumPy's behavior for all relevant scenarios.

[SwayamInSync]

Nothing new implementation here, just registering power as float_power and writing test cases.

[juntyr]

LGTM

[SwayamInSync]

Thanks @juntyr , merging this