### 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.
self,
        dag: DAG,
        most_recent_dag_run: None | datetime | DataInterval,
    ) -> None:
        """
        Calculate ``next_dagrun`` and `next_dagrun_create_after``
        :param dag: The DAG object
        :param most_recent_dag_run: DataInterval (or datetime) of most recent run of this dag, or none
            if not yet scheduled.
        """
        most_recent_data_interval: DataInterval | None
        if isinstance(most_recent_dag_run, datetime):
            warnings.warn(
                "Passing a datetime to `DagModel.calculate_dagrun_date_fields` is deprecated. "
                "Provide a data interval instead.",
                RemovedInAirflow3Warning,
                stacklevel=2,
            )
            most_recent_data_interval = dag.infer_automated_data_interval(most_recent_dag_run)
        else:
            most_recent_data_interval = most_recent_dag_run
        next_dagrun_info = dag.next_dagrun_info(most_recent_data_interval)
        if next_dagrun_info is None:
            self.next_dagrun_data_interval = self.next_dagrun = self.next_dagrun_create_after = None
        else:
            self.next_dagrun_data_interval = next_dagrun_info.data_interval
            self.next_dagrun = next_dagrun_info.logical_date
            self.next_dagrun_create_after = next_dagrun_info.run_after
        log.info(