BUG: Using Series.diff() on a Series with Periods on Windows shows an overflow error

[Dr-Irv]

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Reproducible Example

>>> import pandas as pd
>>> pd.Series(
...                     [pd.Period("2012-1-1", freq="D"), pd.Period("2012-1-2", freq="D")]
...                 ).diff()
C:\Anaconda3\envs\pandasstubs\lib\site-packages\pandas\core\arrays\datetimelike.py:1306: RuntimeWarning: overflow encountered in scalar multiply
  new_data = np.array([self.freq.base * x for x in new_i8_data])
0      NaT
1    <Day>
dtype: object

Issue Description

This error only appears on Windows, not on Linux!

Discovered in a pandas-stubs pull request: https://github.com/pandas-dev/pandas-stubs/pull/907/files#r1571049325

Expected Behavior

No error message

Installed Versions

INSTALLED VERSIONS

commit : d9cdd2e
python : 3.9.16.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19045
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 68.2.2
pip : 22.3.1
Cython : None
pytest : 8.1.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : 5.2.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : None
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.3
numba : None
numexpr : 2.10.0
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 15.0.2
pyreadstat : 1.2.7
python-calamine : None
pyxlsb : 1.0.10
s3fs : None
scipy : 1.13.0
sqlalchemy : 2.0.29
tables : 3.9.1
tabulate : 0.9.0
xarray : 2024.3.0
xlrd : 2.0.1
zstandard : 0.22.0
tzdata : 2024.1
qtpy : None
pyqt5 : None

[Aloqeely]

I think what's happening internally is that the values in the PeriodArray are converted to int64 values to perform some calculations, and NaT gets converted to a very big value (largest int64 number I think), and then it does some multiplication which will result in overflow for this NaT (2^63), which doesn't really affect anything as that value gets masked right after the multiplication, but the warning is quite misleading.

I think we can solve this by either performing the masking before doing the multiplication, or by doing the multiplication for all non-NaT values.

But I don't know why it happens for Windows only