### Body

Currently `start_date` is mandatory parameter.
For DAGs with `schedule=None` we can relax this requirement as no scheduling calculation needed so the `start_date` parameter isn't used.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
"""Test that when setting an individual mapped TI that the other TIs are not affected"""
    task_id = "t1"
    with dag_maker(session=session) as dag:
        @dag.task
        def make_arg_lists():
            return [[1], [2], [{"a": "b"}]]
        def consumer(value):
            print(value)
        mapped = PythonOperator.partial(task_id=task_id, dag=dag, python_callable=consumer).expand(
            op_args=make_arg_lists()
        )
        mapped >> BaseOperator(task_id="downstream")
    dr1 = dag_maker.create_dagrun(
        run_type=DagRunType.SCHEDULED,
        state=DagRunState.FAILED,
    )
    expand_mapped_task(mapped, dr1.run_id, "make_arg_lists", length=2, session=session)
    
    dr2 = dag_maker.create_dagrun(
        run_type=DagRunType.SCHEDULED,
        state=DagRunState.FAILED,
        execution_date=DEFAULT_DATE + datetime.timedelta(days=1),
    )
    expand_mapped_task(mapped, dr2.run_id, "make_arg_lists", length=2, session=session)
    session.query(TI).filter_by(dag_id=dag.dag_id).update({"state": TaskInstanceState.FAILED})
    ti_query = (
        session.query(TI.task_id, TI.map_index, TI.run_id, TI.state)
        .filter(TI.dag_id == dag.dag_id, TI.task_id.in_([task_id, "downstream"]))