https://github.com/apache/airflow/pull/12139 added some new params to the scheduler -- we have "cursory" docs for them in the comments in the config file, but we should have a more details docs in the scheduler.rst page.
airflow/jobs/scheduler_job.py
file_path: str,
        callback_requests: List[CallbackRequest],
        dag_ids: Optional[List[str]],
        pickle_dags: bool,
    ) -> DagFileProcessorProcess:
        """Creates DagFileProcessorProcess instance."""
        return DagFileProcessorProcess(
            file_path=file_path, pickle_dags=pickle_dags, dag_ids=dag_ids, callback_requests=callback_requests
        )
    def _run_scheduler_loop(self) -> None:
        """
        The actual scheduler loop. The main steps in the loop are:
            #. Harvest DAG parsing results through DagFileProcessorAgent
            #. Find and queue executable tasks
                #. Change task instance state in DB
                #. Queue tasks in executor
            #. Heartbeat executor
                #. Execute queued tasks in executor asynchronously
                #. Sync on the states of running tasks
        Following is a graphic representation of these steps.
        .. image:: ../docs/apache-airflow/img/scheduler_loop.jpg
        :rtype: None
        """
        if not self.processor_agent:
            raise ValueError("Processor agent is not started.")
        is_unit_test: bool = conf.getboolean('core', 'unit_test_mode')
        timers = sched.scheduler()
        def call_regular_interval(