### 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.
"""Verify tasks with Duplicate task_id raises error"""
        with pytest.raises(DuplicateTaskIdFound, match="Task id 't1' has already been added to the DAG"):
            dag = DAG("test_dag", start_date=DEFAULT_DATE)
            op1 = EmptyOperator(task_id="t1", dag=dag)
            op2 = EmptyOperator(task_id="t1", dag=dag)
            op1 >> op2
        assert dag.task_dict == {op1.task_id: op1}
    def test_duplicate_task_ids_for_same_task_is_allowed(self):
        """Verify that same tasks with Duplicate task_id do not raise error"""
        with DAG("test_dag", start_date=DEFAULT_DATE) as dag:
            op1 = op2 = EmptyOperator(task_id="t1")
            op3 = EmptyOperator(task_id="t3")
            op1 >> op3
            op2 >> op3
        assert op1 == op2
        assert dag.task_dict == {op1.task_id: op1, op3.task_id: op3}
        assert dag.task_dict == {op2.task_id: op2, op3.task_id: op3}
    def test_partial_subset_updates_all_references_while_deepcopy(self):
        with DAG("test_dag", start_date=DEFAULT_DATE) as dag:
            op1 = EmptyOperator(task_id="t1")
            op2 = EmptyOperator(task_id="t2")
            op3 = EmptyOperator(task_id="t3")
            op1 >> op2
            op2 >> op3
        partial = dag.partial_subset("t2", include_upstream=True, include_downstream=False)
        assert id(partial.task_dict["t1"].downstream_list[0].dag) == id(partial)
        
        assert "t3" not in partial.task_group.used_group_ids
    def test_partial_subset_taskgroup_join_ids(self):