### 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)

"""
        Mark tasks stuck in queued for longer than `task_queued_timeout` as failed.
        Tasks can get stuck in queued for a wide variety of reasons (e.g. celery loses
        track of a task, a cluster can't further scale up its workers, etc.), but tasks
        should not be stuck in queued for a long time. This will mark tasks stuck in
        queued for longer than `self._task_queued_timeout` as failed. If the task has
        available retries, it will be retried.
        """
        self.log.debug("Calling SchedulerJob._fail_tasks_stuck_in_queued method")
        tasks_stuck_in_queued = session.scalars(
            select(TI).where(
                TI.state == TaskInstanceState.QUEUED,
                TI.queued_dttm < (timezone.utcnow() - timedelta(seconds=self._task_queued_timeout)),
                TI.queued_by_job_id == self.job.id,
            )
        ).all()
        try:
            tis_for_warning_message = self.job.executor.cleanup_stuck_queued_tasks(tis=tasks_stuck_in_queued)
            if tis_for_warning_message:
                task_instance_str = "\n\t".join(tis_for_warning_message)
                self.log.warning(
                    "Marked the following %s task instances stuck in queued as failed. "
                    "If the task instance has available retries, it will be retried.\n\t%s",
                    len(tasks_stuck_in_queued),
                    task_instance_str,
                )
        except NotImplementedError:
            self.log.debug("Executor doesn't support cleanup of stuck queued tasks. Skipping.")
            ...