O4 Auxiliary Channel Data Release

Data Set

The LIGO instrument at each site uses a large number of sensors to track the state of both the instrument and the surrounding environment.

A subset of those sensors (channels) are used as part of astrophysical analyses by the LIGO-Virgo-KAGRA collaboration. The particular subset of channels provided here has been used to remove additional noise from LIGO data or to improve the quality of the astrophysical analyses.

Channel Names

Each channel has a name using this structure: [IFO]:[SYSTEM]-[NAME], where:

  • [IFO] is the instrument (e.g., H1 refers to LIGO Hanford)
  • [SYSTEM] is an acronym for the instrument subsystem (e.g., PEM means "Physical Environment Monitor")
  • [NAME] is a name describing the channel (often containing more acronyms).

Channel List

This data set includes 14 channels from LIGO Hanford and 11 channels from LIGO Livingston, that were used in O4 astrophysical analyses. The data set has a total size of 9 TB. This data set includes channels that were used to create data-quality flags, to subtract instrumental noise from the strain data, and to measure the amount of correlated noise between the gravitational-wave detectors. Additional details about how each of these channels was used in the data analysis can be found in the Channel List.

Channel List

Data Access

NDS2

Data may be accessed from a network data server (NDS2) using the NDS2 client or GWpy. The following code can be used to download data (substitute any channel name that is a part of this data release): 

from gwpy.timeseries import TimeSeries
data = TimeSeries.fetch('L1:CAL-PCALX_RX_PD_OUT_DQ', start=1368980000, end=1368980010, host='nds.gwosc.org')

See the Data Access Example Code for additional examples.

OSDF

This data release has frame type H1_AUX_AR1 and L1_AUX_AR1 and is available via OSDF allowing to select and download the data. To launch large dataset jobs on a computing cluster one can use HTCondor.

To search for public data osdf file URLs, one may use gw_data_find for a given frame and segment interval:

gw_data_find -r datafind.gwosc.org -o L -t L1_AUX_AR1 -s 1368980000 -e 1368980010 -u osdf

Alternatively, in python code, to download OSDF url files for a given frame type and GPS segment:

import os
import requests_pelican as rp
from gwdatafind import find_urls

url = find_urls("L", "L1_AUX_AR1", 1368980000, 1368980010, urltype='osdf', host="https://datafind.gwosc.org")

with open(os.path.basename(url[0]), mode="wb") as file:
    file.write(rp.get(url[0]).content)

Segments

The segments are divided in two phases. The first phase corresponds to the end of the engineering run (ER15) before the official start of O4a run. Time segments are selected around coincidence events for ER15 and are marked by: [H,L]1:DCH-ANALYSIS_READY_ER15_COINC. In the second phase, the O4a run, data are selected between time segments marked by: [H,L]1:DMT-ANALYSIS_READY:1.

Download Segment Lists

Tutorials

Tutorials that show examples of different applications of this data set can be found in the Tutorials Git Repository.

Additional references

DOI

This dataset is part of the O4 data release (DOI: 10.7935/kt51-6n86).

Feedback

This data release is the first of its kind. Is it useful for your research? How could it be improved? Please contact us with any feedback.

Revision History

  • Aug 26, 2025: First release