feat: implement approximate equality of tensors with floating point scalars (#137)

[dlyongemallo]

No description provided.

[Copilot]

Pull Request Overview

This PR implements approximate equality comparison for tensors containing floating-point scalars to handle rounding errors in quantum circuit computations. This addresses numerical precision issues where mathematically equivalent operations may produce slightly different floating-point results.

• Replaces exact tensor equality with approximate equality using the approx crate
• Adds AbsDiffEq trait import and enables the "approx" feature for ndarray
• Includes a test demonstrating floating-point tolerance for equivalent circuits with different computation paths

Reviewed Changes

Copilot reviewed 2 out of 3 changed files in this pull request and generated 1 comment.

File	Description
quizx/src/equality.rs	Updated tensor comparison to use approximate equality with default epsilon tolerance
quizx/Cargo.toml	Added "approx" feature to ndarray dependency to enable approximate equality traits

---

_{Tip: Customize your code reviews with copilot-instructions.md. Create the file or learn how to get started.}

[Copilot]

[nitpick] The Scalar4 import is used only for default_epsilon(). Consider making the epsilon configurable as a parameter to equal_graph_tensor to allow callers to specify their own tolerance levels based on their precision requirements.