### 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)

)
                        continue
                    task_concurrency_limit: int | None = None
                    if serialized_dag.has_task(task_instance.task_id):
                        task_concurrency_limit = serialized_dag.get_task(
                            task_instance.task_id
                        ).max_active_tis_per_dag
                    if task_concurrency_limit is not None:
                        current_task_concurrency = concurrency_map.task_concurrency_map[
                            (task_instance.dag_id, task_instance.task_id)
                        ]
                        if current_task_concurrency >= task_concurrency_limit:
                            self.log.info(
                                "Not executing %s since the task concurrency for"
                                " this task has been reached.",
                                task_instance,
                            )
                            starved_tasks.add((task_instance.dag_id, task_instance.task_id))
                            continue
                    task_dagrun_concurrency_limit: int | None = None
                    if serialized_dag.has_task(task_instance.task_id):
                        task_dagrun_concurrency_limit = serialized_dag.get_task(
                            task_instance.task_id
                        ).max_active_tis_per_dagrun
                    if task_dagrun_concurrency_limit is not None:
                        current_task_dagrun_concurrency = concurrency_map.task_dagrun_concurrency_map[
                            (task_instance.dag_id, task_instance.run_id, task_instance.task_id)
                        ]
                        if current_task_dagrun_concurrency >= task_dagrun_concurrency_limit:
                            self.log.info(