### 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)

session.execute(
                select(DagRun.dag_id, DagRun.execution_date).where(
                    tuple_in_condition(
                        (DagRun.dag_id, DagRun.execution_date),
                        ((dm.dag_id, dm.next_dagrun) for dm in dag_models),
                    ),
                )
            )
            .unique()
            .all()
        )
        active_runs_of_dags = Counter(
            DagRun.active_runs_of_dags(dag_ids=(dm.dag_id for dm in dag_models), session=session),
        )
        for dag_model in dag_models:
            dag = self.dagbag.get_dag(dag_model.dag_id, session=session)
            if not dag:
                self.log.error("DAG '%s' not found in serialized_dag table", dag_model.dag_id)
                continue
            dag_hash = self.dagbag.dags_hash.get(dag.dag_id)
            data_interval = dag.get_next_data_interval(dag_model)
            
            
            
            
            
            
            
            
            if (dag.dag_id, dag_model.next_dagrun) not in existing_dagruns: