BUG: to_datetime re-parsing Arrow-backed objects
- [ ] closes #52545
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Ideally, we could push this down into DTA/DTI, but that doesn't seem to support Arrow arrays ATM.
> Also, does something similar happen to `to_timedelta`?

I think so, I'll try to get at it at a followup.

I think in the future, it might also make sense for DF inputs with Arrow backed ``year``, ``month``, etc. columns to convert to Arrow Backed dt columns.

e.g.
```
>>> import pandas as pd
+ /Users/thomasli/opt/miniconda3/envs/pandas-dev/bin/ninja
[1/1] Generating write_version_file with a custom command
>>> df = pd.DataFrame({'year': [2015, 2016],
...                    'month': [2, 3],
...                    'day': [4, 5]})
>>> df = df.astype("int64[pyarrow]")
>>> pd.to_datetime(df)
0   2015-02-04
1   2016-03-05
dtype: datetime64[ns]
```
should return something with dtype: ``timestamp[ns][pyarrow]``


Main thing I'm worried about with this PR is doing the wrong thing for ``utc=True`` (e.g. localizing instead of converting and vice versa).

(cc @phofl in case any thoughts and to double check my logic). This pull request is stale because it has been open for thirty days with no activity. Please [update](https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#updating-your-pull-request) and respond to this comment if you're still interested in working on this. Thanks @lithomas1  Does the to_datetime docstring need to be updated to reflect non-DTI return?