Numerical-Relativity Data

bayRing fits one complex NR multipole at a time. The [NR-data] section selects the catalogue, simulation, resolution, waveform type, fitted multipole, local paths and NR error prescription.

NR multipole picture with peak time, fit interval and error bars

The catalogue reader keeps the full multipole available for context, while inference uses only the highlighted interval and the corresponding error vector.

bayRing numerical-relativity data loading, peak reference, fit interval and error model

Catalogue Selection

The primary option is:

[NR-data]
catalog = SXS
ID = 0305

Supported catalogue names in the current parser are:

catalog

Typical data source

Notes

SXS

Simulating eXtreme Spacetimes catalog

Default catalogue. download = 1 asks the SXS tooling to fetch the simulation when needed.

RIT

RIT numerical-relativity catalogue

Uses local RIT waveform/metadata paths, with download attempts for some missing RIT files.

Teukolsky

Local Teukolsky perturbation data

Not public NR data. Supports named resolution levels or explicit res-nx/res-nl.

RWZ-env

Regge-Wheeler-Zerilli environmental simulations

Not public NR data. Developer-level path format. The tracked example uses m = 0.

C2EFT

Local C2EFT data

Not public NR data. Some resolution/extrapolation choices are currently hard-coded in the reader.

cbhdb

Charged black-hole database

Not public NR data. Uses the cbhdb Python interface and charged QNM metadata.

charged_raw

Local raw charged-waveform files

Reads raw times and cross files from NR-data dir.

fake_NR

Internal Kerr-QNM synthetic data

Builds a fake NR waveform from metadata and requested injection modes.

The default catalogue is SXS and the default simulation ID is 0305.

Local Data Paths

dir points to catalogue data when the selected backend needs local files:

[NR-data]
dir = /path/to/local/catalog/data

If an option needs data outside the installed package and the path is not explicitly supplied, bayRing can fall back to BAYRING_PREFIX for repository-relative data layouts. Set:

export BAYRING_PREFIX=/path/to/bayRing

Optional metadata tables use:

[NR-data]
properties-file = /path/to/properties.csv
fits-file = /path/to/fits.csv

properties-file supplies extra NR quantities such as peak amplitudes or noncircular variables. fits-file supplies fit coefficients for calibrated templates such as some TEOBPM workflows. Empty strings are treated as no file supplied.

Multipole Selection

The fitted NR multipole is set with:

[NR-data]
l-NR = 2
m = 2

The selected (l-NR, m) is the spherical-harmonic multipole read from the NR data. It does not force every model QNM to have the same l. In the Kerr template, multiple spheroidal QNMs with the same azimuthal index can contribute to the selected spherical multipole.

For informed-amplitude fits using the (2,2) peak time as reference, provide the time of the (2,2) peak:

[NR-data]
l-NR = 3
m = 3
t-peak-22 = 3800.6154428984305

Time Axis And Fit Window

After the waveform is loaded, bayRing computes the amplitude and phase of the complex NR multipole. It then finds a peak time:

  • for non-eccentric or very high-eccentricity waveforms, the peak is the maximum amplitude sample;

  • for eccentric waveforms with 1e-3 < ecc < 0.89, the code tries to use the last relative amplitude maximum;

  • for Teukolsky linear perturbations, dt-scd can shift the peak to a secondary reference time;

  • a nonzero t-peak-22 overrides those choices.

The fit interval is:

\[t_{\min} = t_{\mathrm{peak}} + t\mbox{-start},\qquad t_{\max} = t_{\mathrm{peak}} + t\mbox{-end}.\]

These values are set in the [Inference] section:

[Inference]
t-start = 20.0
t-end = 140.0

The code crops the NR waveform, error vector and time array to this interval before inference.

Waveform Type

waveform-type selects which waveform quantity is read where the backend supports multiple choices:

[NR-data]
waveform-type = strain

The default is strain. Some catalogue paths can also handle psi4. Make sure the selected model and post-processing interpretation match the quantity being fitted.

Resolution And Extrapolation

The main resolution options are:

Option

Meaning

res-level

Catalogue resolution level. For SXS, -1 selects the highest available resolution found by the reader.

extrap-order

SXS extrapolation order. The default is 2.

res-nx and res-nl

Teukolsky radial and angular collocation counts. When both are nonzero, they override res-level and form a resolution string such as nx_190_nl_24.

pert-order

Teukolsky perturbation order, usually lin or scd.

For Teukolsky data, integer res-level values map to specific nx/nl pairs in convert_resolution_level_Teukolsky. Explicit res-nx and res-nl are useful when the desired resolution is not one of the named levels.

NR Error Prescriptions

The likelihood compares real and imaginary residuals against the complex error vector. The real part of the error weights the real residual; the imaginary part weights the imaginary residual.

The simplest error is a constant:

[NR-data]
error = constant-0.0001

This generates a complex error with real and imaginary components both equal to 0.0001 at every time sample.

Catalogue-dependent options include:

Option

Behaviour

constant-X

Use the constant error value X for both real and imaginary parts.

late-time-const-error

Use the catalogue metadata value A_nr_error where available.

align-with-mismatch-res-only

For SXS-like resolution comparisons, align the lower-resolution waveform by minimizing mismatch and use the resolution difference.

align-with-mismatch-all

For SXS-like data, include both resolution and extrapolation differences after mismatch alignment.

align-at-peak

Align comparison waveforms at the amplitude peak rather than through a mismatch minimization.

resolution

For Teukolsky data, compare against another resolution level when available.

gaussian-X

For fake_NR, set a Gaussian-noise scale X.

from-SXS-NR

For fake_NR, reuse the SXS-derived error vector.

Mismatch-alignment options use:

[NR-data]
error-t-min = 0.3
error-t-max = 0.004

The implementation converts these fractional inputs using the peak time:

\[t_{\min}^{\mathrm{mm}} = t_{\mathrm{peak}}(1 - \mathrm{error\mbox{-}t\mbox{-}min}), \qquad t_{\max}^{\mathrm{mm}} = t_{\mathrm{peak}}(1 - \mathrm{error\mbox{-}t\mbox{-}max}).\]