### Apache Airflow version

2.6.3

### What happened

When the condition in ```ShortCircuitOperator``` is truthy it is returned at
https://github.com/apache/airflow/blob/a2ae2265ce960d65bc3c4bf805ee77954a1f895c/airflow/operators/python.py#L252
but when it is falsy, the function falls through without returning anything.

If ```multiple_outputs``` is set ```true``` (with for example ```@task.short_circuit(multiple_outputs=True```) ```_handle_output``` of
```DecoratedOperator``` at
https://github.com/apache/airflow/blob/a2ae2265ce960d65bc3c4bf805ee77954a1f895c/airflow/decorators/base.py#L242
does not test for None and raises at
https://github.com/apache/airflow/blob/a2ae2265ce960d65bc3c4bf805ee77954a1f895c/airflow/decorators/base.py#L255
This makes it impossible to pass a falsy value (i.e. an empty dictionary) so ```ShortCircuitOperator``` is unusable with ```multiple_outputs=true```


### What you think should happen instead

Probably the ```xcom_push``` should not be attempted with ```None```, or possibly the condition should be returned by ```ShortCircuitOperator``` even if it is falsy

### How to reproduce

```python
@task.short_circuit(multiple_outputs=True)
def test():
  return {}
```

### Operating System

Ubuntu 22.04.2 LTS

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

],
    )
    def test_short_circuit_with_teardowns(
        self, dag_maker, ignore_downstream_trigger_rules, should_skip, with_teardown, expected
    ):
        with dag_maker() as dag:
            op1 = ShortCircuitOperator(
                task_id="op1",
                python_callable=lambda: not should_skip,
                ignore_downstream_trigger_rules=ignore_downstream_trigger_rules,
            )
            op2 = PythonOperator(task_id="op2", python_callable=print)
            op3 = PythonOperator(task_id="op3", python_callable=print)
            op4 = PythonOperator(task_id="op4", python_callable=print)
            if with_teardown:
                op4.as_teardown()
            op1 >> op2 >> op3 >> op4
            op1.skip = MagicMock()
            dagrun = dag_maker.create_dagrun()
            tis = dagrun.get_task_instances()
            ti: TaskInstance = [x for x in tis if x.task_id == "op1"][0]
            ti._run_raw_task()
            expected_tasks = {dag.task_dict[x] for x in expected}
        if should_skip:
            
            actual_skipped = set(op1.skip.call_args.kwargs["tasks"])
            assert actual_skipped == expected_tasks
        else:
            op1.skip.assert_not_called()
    @pytest.mark.parametrize("config", ["sequence", "parallel"])