### 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.
local_tz = pendulum.timezone("Europe/Zurich")
        default_args = {"start_date": datetime.datetime(2018, 1, 1, tzinfo=local_tz)}
        dag = DAG("DAG", default_args=default_args)
        assert dag.timezone.name == local_tz.name
        dag = DAG("DAG", default_args=default_args)
        assert dag.timezone.name == local_tz.name
    def test_roots(self):
        """Verify if dag.roots returns the root tasks of a DAG."""
        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")
            op4 = EmptyOperator(task_id="t4")
            op5 = EmptyOperator(task_id="t5")
            [op1, op2] >> op3 >> [op4, op5]
            assert set(dag.roots) == {op1, op2}
    def test_leaves(self):
        """Verify if dag.leaves returns the leaf tasks of a DAG."""
        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")
            op4 = EmptyOperator(task_id="t4")
            op5 = EmptyOperator(task_id="t5")
            [op1, op2] >> op3 >> [op4, op5]
            assert set(dag.leaves) == {op4, op5}
    def test_tree_view(self):