CLN use default_index more
- [ ] closes #xxxx (Replace xxxx with the GitHub issue number)
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [ ] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.

why?  no strong opinion, just curious If `default_index` was to change (e.g. under an option), then this would align the default index across these different methods

The only one here where it changes the type is in `merge` not on index. Currently, pandas returns an `Int64Index` - would it be better to return `RangeIndex`?

upstream/main:
```
In [6]: df = pd.DataFrame({'a': [1,2,3]})

In [7]: df.merge(df, on='a').index
Out[7]: Int64Index([0, 1, 2], dtype='int64')
```

here:
```
In [1]: df = pd.DataFrame({'a': [1,2,3]})

In [2]: df.merge(df, on='a').index
Out[2]: RangeIndex(start=0, stop=3, step=1)
``` Would `default_index` help prime optional Index work as well?

The only one here where it changes the type is in merge not on index. Currently, pandas returns an Int64Index - would it be better to return RangeIndex?

+1 to generally return RangeIndex when possible > Would default_index help prime optional Index work as well?

yup (that's how I came across this) Could use a whatsnew (perf maybe) regarding the merge `Int64Index` -> `RangeIndex` change otherwise LGTM A-OK Thanks @MarcoGorelli 