| GW |
Gravitational wave |
| LVK |
LIGO–Virgo–KAGRA, the collaboration of the ground-based GW detectors (H1 Hanford, L1 Livingston, V1 Virgo, K1 KAGRA) |
| GWTC |
Gravitational-Wave Transient Catalog: GWTC-1, -2.1, -3, -4.0, -5.0 |
| GWOSC |
Gravitational Wave Open Science Center, the public GW data portal |
| O1, O2, O3a, O3b, O4a, O4b |
Observing runs, 2015–2025; O3 and O4 are split in halves |
| ER15 |
Engineering run 15, just before O4a |
| BBH / BNS / NSBH |
Binary black hole / binary neutron star / neutron star–black hole binary |
| PE |
Parameter estimation: the Bayesian inference of one event's masses, spins, distance, sky position… |
| PE label |
One analysis in a PE file (waveform, settings), e.g. C00:IMRPhenomXPHM-SpinTaylor; Mixed combines several |
| PESummary |
The LVK file format and library for PE results (Hoy & Raymond 2021 [62]) |
| PSD |
Power spectral density, the detector noise spectrum, used to whiten the data |
| Calibration envelope |
Uncertainty of the detector calibration in amplitude and phase, marginalized in PE |
| FAR |
False-alarm rate: how often noise alone produces a candidate at least this significant (per year) |
| p_astro |
Probability that a candidate is astrophysical |
| SNR |
Signal-to-noise ratio; the matched-filter SNR compares the data with a template |
| Chirp mass |
\(\mathcal{M} = (m_1 m_2)^{3/5}/(m_1+m_2)^{1/5}\), the mass combination that sets the inspiral |
| z |
Redshift: the stretch of wavelengths and time scales by cosmic expansion |
| D_L |
Luminosity distance, measured by the GW amplitude |
| Source / detector frame |
Physical masses / redshifted masses \(m_\text{det} = (1+z)\, m_\text{src}\) seen by the detector |
| H₀ |
Hubble constant, the present expansion rate of the Universe (km/s/Mpc) |
| Planck 2015 cosmology |
Flat ΛCDM with the Planck 2015 parameters, the reference cosmology of the GW catalogs: Planck15 (astropy: H₀ = 67.74, Ω_m = 0.3075) or Planck15_LAL (LAL: H₀ = 67.90, Ω_m = 0.3065) (Planck Collaboration 2016 [32]); see How the redshift is obtained |
| ΛCDM, Ω_m |
Standard cosmological model; present matter density as a fraction of the critical density |
| Comoving volume V_c |
Volume that expands with the Universe; merger rates are given per unit comoving volume |
| Standard siren |
A GW source used as a distance indicator |
| Bright / dark / spectral siren |
Redshift from an electromagnetic counterpart / a galaxy catalog / features of the mass distribution |
| Injection |
A simulated signal added to the data (or evaluated semi-analytically) to measure the detection probability |
| p_draw |
The known density from which the injections were drawn |
| Found injection |
An injection that passes the detection criteria (FAR or SNR threshold) |
| VT, ⟨VT⟩ |
Sensitive volume × time of a population: the expected number of detections is R ⟨VT⟩ |
| ξ |
Detectable fraction of a population |
| n_eff |
Effective number of samples of a weighted Monte Carlo sum, \((\sum x)^2/\sum x^2\) |
| Hierarchical inference |
Inference of population parameters from many events, each with its own uncertain parameters |
| Hyperprior |
Prior on population (and cosmological) parameters |
| PLP |
Power Law + Peak: BBH primary-mass model, a power law with a Gaussian peak and a smooth low-mass turn-on [15] [11] |
| MLTP |
Multi Peak model: power law with two Gaussian peaks (found near 9 and 27 M☉) [29] |
| FullPop-4.0 |
GWTC-4.0 model of the full compact-binary population (neutron stars, mass gap, black holes) [13] [29] |
| Madau–Dickinson |
Shape of the merger rate with redshift: rises as (1+z)^γ, peaks near z_p, falls as (1+z)^−κ [16] |
| Nested sampling |
Bayesian sampling that computes the evidence and the posterior together (dynesty) |
| Live points |
The set of samples nested sampling evolves; more live points, finer exploration |
| ln Z |
Log Bayesian evidence |
| Seed |
Initialization of the random generator of one sampler run |
| icarogw |
Python package for population and cosmology inference with GW events (Mastrogiovanni et al. 2024 [57]) |
| bilby / dynesty |
Bayesian inference library (Ashton et al. 2019 [58]) / its nested sampler (Speagle 2020 [60]) |
| IMRPhenomXPHM |
Frequency-domain waveform model with precession and higher modes (Pratten et al. 2021 [51]) |
| XPHM-SpinTaylor |
IMRPhenomXPHM with numerically evolved spin precession (Colleoni et al. 2024 [52]) |
| q-transform |
Time–frequency representation of the strain, showing the chirp |
| Whitening |
Dividing the data by the noise amplitude spectrum, so that all frequencies have equal noise |