### 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.
"""
        Tests if fractional seconds are stored in the database
        """
        dag_id = "test_fractional_seconds"
        dag = DAG(dag_id=dag_id, schedule="@once")
        dag.add_task(BaseOperator(task_id="faketastic", owner="Also fake", start_date=TEST_DATE))
        start_date = timezone.utcnow()
        run = dag.create_dagrun(
            run_id="test_" + start_date.isoformat(),
            execution_date=start_date,
            start_date=start_date,
            state=State.RUNNING,
            external_trigger=False,
        )
        run.refresh_from_db()
        assert start_date == run.execution_date, "dag run execution_date loses precision"
        assert start_date == run.start_date, "dag run start_date loses precision "
        self._clean_up(dag_id)
    def test_pickling(self):
        test_dag_id = "test_pickling"
        args = {"owner": "airflow", "start_date": DEFAULT_DATE}
        dag = DAG(test_dag_id, default_args=args)
        dag_pickle = dag.pickle()
        assert dag_pickle.pickle.dag_id == dag.dag_id
    def test_rich_comparison_ops(self):
        test_dag_id = "test_rich_comparison_ops"
        class DAGsubclass(DAG):