### 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)

self.log.error("DAG '%s' not found in serialized_dag table", dag_run.dag_id)
        with prohibit_commit(session) as guard:
            
            session.expunge_all()
            
            if self.job.executor.slots_available <= 0:
                
                self.log.debug("Executor full, skipping critical section")
                num_queued_tis = 0
            else:
                try:
                    timer = Stats.timer("scheduler.critical_section_duration")
                    timer.start()
                    
                    num_queued_tis = self._critical_section_enqueue_task_instances(session=session)
                    
                    
                    timer.stop(send=True)
                except OperationalError as e:
                    timer.stop(send=False)
                    if is_lock_not_available_error(error=e):
                        self.log.debug("Critical section lock held by another Scheduler")
                        Stats.incr("scheduler.critical_section_busy")
                        session.rollback()
                        return 0
                    raise
            guard.commit()
        return num_queued_tis
    @retry_db_transaction
    def _get_next_dagruns_to_examine(self, state: DagRunState, session: Session) -> Query: