Enhancement: Utilize array-api-compat for enp Backend

Currently, `enp` implements custom code to support JAX, PyTorch, and TensorFlow.

The `array-api-compat` library provides a uniform API for numerical computation across multiple frameworks. By leveraging this library, we could potentially:

- Eliminate the need for custom code handling framework-specific functionalities.
- Simplify updates and bug fixes by relying on a standardized API.
- Ensure uniform behavior across different frameworks.

I propose exploring the feasibility of integrating `array-api-compat` as a backend for `enp`. This might involve refactoring existing code to utilize the library's API. Popular libraries like scikit-learn (https://labs.quansight.org/blog/array-api-support-scikit-learn) and SciPy (https://labs.quansight.org/blog/scipy-array-api) have already successfully implemented this API.

Integrating `array-api-compat` would not only streamline the codebase but also broaden the number of frameworks compatible with `enp`. I'm happy to discuss this further and potentially contribute to the implementation if the maintainers agree this is a worthwhile enhancement. Please share your thoughts and suggestions on this proposal.