### Body

There are some use cases where users want to trigger new DAG run as soon as one finished. This is a request I've seen several times with some variations (for example like this [Stackoverflow question](https://stackoverflow.com/q/75623153/14624409)) but the basic request is the same.

The workaround users do to get such functionality is place `TriggerDagRunOperator` as last task of their DAG invoking the same DAG:

```
from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule=None,
) as dag:
    task = EmptyOperator(task_id="first")
    trigger = TriggerDagRunOperator(
        task_id="trigger",
        trigger_dag_id="example",
    )

    task >> trigger

```

As you can see this works nicely:
![Screenshot 2023-03-03 at 14 20 51](https://user-images.githubusercontent.com/45845474/222718862-dfde8a41-24b6-4991-b318-b7f9784514f6.png)

My suggestion is to add first class support for this use case, so the above example will be changed to:

```

from datetime import datetime

from airflow import DAG
from airflow.operators.empty import EmptyOperator
from airflow.operators.trigger_dagrun import TriggerDagRunOperator

with DAG(
    dag_id="example",
    start_date=datetime(2023, 1, 1,),
    catchup=False,
    schedule="@continues",
) as dag:
    task = EmptyOperator(task_id="first")
```

I guess it won't exactly be `"@continues"` but more likely new [ScheduleArg](https://github.com/apache/airflow/blob/8b8552f5c4111fe0732067d7af06aa5285498a79/airflow/models/dag.py#L127) type but I show it like that just for simplification of the idea.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
for tii in external_tis:
                    if not dag_bag:
                        from airflow.models.dagbag import DagBag
                        dag_bag = DagBag(read_dags_from_db=True)
                    external_dag = dag_bag.get_dag(tii.dag_id, session=session)
                    if not external_dag:
                        raise AirflowException(f"Could not find dag {tii.dag_id}")
                    downstream = external_dag.partial_subset(
                        task_ids_or_regex=[tii.task_id],
                        include_upstream=False,
                        include_downstream=True,
                    )
                    result.update(
                        downstream._get_task_instances(
                            task_ids=None,
                            run_id=tii.run_id,
                            start_date=None,
                            end_date=None,
                            state=state,
                            include_subdags=include_subdags,
                            include_dependent_dags=include_dependent_dags,
                            include_parentdag=False,
                            as_pk_tuple=True,
                            exclude_task_ids=exclude_task_ids,
                            dag_bag=dag_bag,
                            session=session,
                            recursion_depth=recursion_depth + 1,
                            max_recursion_depth=max_recursion_depth,
                            visited_external_tis=visited_external_tis,
                        )