### What do you see as an issue?

The documentation for zombie tasks https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html#zombie-undead-tasks is a bit abstract at the moment. There is a scope for enhancing the document by explaining how Airflow detects tasks as zombies

### Solving the problem

We can enhance the documentation by translating this query https://github.com/astronomer/airflow/blob/main/airflow/jobs/scheduler_job_runner.py#L1721 to a layman readable text in our documentation.

### Anything else

It might also help to add developer contribution steps to reproduce zombies locally.

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
        Find zombie task instances and create a TaskCallbackRequest to be handled by the DAG processor.
        Zombie instances are tasks haven't heartbeated for too long or have a no-longer-running LocalTaskJob.
        """
        from airflow.jobs.job import Job
        self.log.debug("Finding 'running' jobs without a recent heartbeat")
        limit_dttm = timezone.utcnow() - timedelta(seconds=self._zombie_threshold_secs)
        with create_session() as session:
            zombies: list[tuple[TI, str, str]] = (
                session.execute(
                    select(TI, DM.fileloc, DM.processor_subdir)
                    .with_hint(TI, "USE INDEX (ti_state)", dialect_name="mysql")
                    .join(Job, TI.job_id == Job.id)
                    .join(DM, TI.dag_id == DM.dag_id)
                    .where(TI.state == TaskInstanceState.RUNNING)
                    .where(
                        or_(