On Feb 13 2015 there was a massive earthquake in the Atlantic Ocean, that should have had an impact on LIGO operations, I’d like to find out.
First: we import the objects we need, one for getting the data:
from gwpy.timeseries import TimeSeriesDict
and one for plotting the data:
from gwpy.plot import Plot
Next we define the channels we want, namely the 0.03Hz-1Hz ground motion band-limited RMS channels (1-second average trends). We do this using string-replacement so we can substitute the interferometer prefix easily when we need to:
channels = [
'{ifo}:ISI-BS_ST1_SENSCOR_GND_STS_X_BLRMS_30M_100M.mean,s-trend',
'{ifo}:ISI-BS_ST1_SENSCOR_GND_STS_Y_BLRMS_30M_100M.mean,s-trend',
'{ifo}:ISI-BS_ST1_SENSCOR_GND_STS_Z_BLRMS_30M_100M.mean,s-trend',
]
At last we can get()
12 hours of data for each
interferometer:
lho = TimeSeriesDict.get([c.format(ifo='H1') for c in channels],
'Feb 13 2015 16:00', 'Feb 14 2015 04:00')
llo = TimeSeriesDict.get([c.format(ifo='L1') for c in channels],
'Feb 13 2015 16:00', 'Feb 14 2015 04:00')
Next we can plot the data, with a separate Axes
for each
instrument:
plot = Plot(lho, llo, figsize=(12, 6), sharex=True, yscale='log')
ax1, ax2 = plot.axes
for ifo, ax in zip(('Hanford', 'Livingston'), (ax1, ax2)):
ax.legend(['X', 'Y', 'Z'])
ax.text(1.01, 0.5, ifo, ha='left', va='center', transform=ax.transAxes,
fontsize=18)
ax1.set_ylabel(r'$1-3$\,Hz motion [nm/s]', y=-0.1)
ax2.set_ylabel('')
ax1.set_title('Magnitude 7.1 earthquake impact on LIGO')
plot.show()
(png)
As we can see, the earthquake had a huge impact on the LIGO observatories, severly imparing operations for several hours.