Published February 10, 2025 | Version v1
Dataset Open

Potential impact of noise correlation in next-generation gravitational wave detectors — Data release

  • 1. ROR icon KU Leuven
  • 2. ROR icon Utrecht University
  • 3. ROR icon National Institute for Subatomic Physics
  • 4. ROR icon University of Pisa
  • 5. ROR icon Istituto Nazionale di Fisica Nucleare

Description

Paper Reference:

This dataset accompanies the preprint "Potential impact of noise correlation in next-generation gravitational wave detectors" (arXiv:2407.08728), which presents the methodology and results associated with this data. A peer-reviewed version is forthcoming.


Description:


This dataset contains the raw outputs from the Fisher analysis. The data was generated as part of research on the impact of noise correlation in parameter estimation of gravitational-wave transients for next-generation gravitational wave detectors. It includes:

  1. BBH_{corr_coef}_fhigh10_{network}_snr.npy: A 1D array of the signal-to-noise-ratio of the injections.
  2. BBH_{corr_coef}_fhigh10_{network}_cov.npy: A 3D array of the Fisher covariance matrix for the injections. The first dimension is the injection. The second and the third dimensions are the covariance matrix.
  3. BBH_{corr_coef}_fhigh10_{network}_errs.npy: A 2D array of the Fisher standard deviation for the injections. The first dimension is the injection. The second dimension is the standard deviation.

Definition of the labels:

  • corr_coef: The correlation coefficient. E.g. 0p1 indicates a correlation coefficient of 0.1.
  • network: The detector network configuration.
    • LA1: A detector located at Limburg.
    • LM1: A detector located at Limburg with a 45-degree misalignment with LA1.
    • S1: A detector located at Sardinia.
    • H1: A detector located at Hanford.

File Formats:

The dataset is provided in NPY format. The files can be read using the numpy function np.load.

Usage Notes:

Users are encouraged to refer to the associated paper for details on the data generation process and its interpretation. Example scripts for loading and processing the data are included in the Github repository.

To download the dataset, we recommend zenodo_get:

pip install zenodo_get
zenodo_get RECORD_ID_OR_DOI

where the record ID for the most recent version of this page is 14842436 and IDs for other versions can be found in the Versions section at the side of this page.

 

Files

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Additional details

Related works

Is referenced by
Software: 10.5281/zenodo.14844558 (DOI)
Is supplement to
Preprint: arXiv:2407.08728 (arXiv)