Generate comprehensive release notes for numerax 1.0.0

[Copilot]

This PR addresses the request to generate release notes for the numerax 1.0.0 release by creating comprehensive documentation that highlights the first stable release of this JAX-compatible numerical computation library.

What's Added

Release Documentation Files

• RELEASE_NOTES_1.0.0.md - Complete release notes with detailed feature descriptions, technical highlights, and usage examples
• RELEASE_NOTES_1.0.0_SHORT.md - Concise version suitable for GitHub release descriptions
• CHANGELOG.md - Structured project changelog following Keep a Changelog format with version history
• RELEASE_NOTES_SUMMARY.md - Guide explaining the purpose and usage of each documentation file

Key Features Documented

The release notes comprehensively cover numerax 1.0.0's three main modules:

Special Functions (numerax.special)

• gammap_inverse(p, a) - Inverse regularized incomplete gamma function with Halley's method and custom JVP gradients
• erfcinv(x) - Inverse complementary error function with full JAX differentiability

Statistical Methods (numerax.stats)

• Complete chi-squared distribution interface with high-precision percent point function (PPF)
• make_profile_llh() - Profile likelihood factory using L-BFGS optimization for statistical inference

Utilities (numerax.utils)

• preserve_metadata() - Decorator wrapper ensuring function metadata survives JAX transformations

Technical Validation

All code examples in the release notes have been tested and verified to work correctly:

import numerax

# Examples from release notes - all verified working
x = numerax.special.gammap_inverse(0.5, 2.0)  # Returns: 1.6783478260040283
y = numerax.special.erfcinv(0.5)              # Returns: 0.4769362807273865
quantile = numerax.stats.chi2.ppf(0.95, 1)   # Returns: 3.841458797454834

The documentation emphasizes numerax's key strengths: full JAX transformation compatibility (JIT, grad, vmap), numerical stability through custom derivatives, and production-ready performance for scientific computing applications.

This documentation package provides everything needed for the 1.0.0 release announcement, from GitHub release descriptions to detailed technical documentation for users and contributors.

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