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References

The methods FLITS implements, and the software it builds on.

Dispersion

FLITS dedisperses incoherently to the top of the band, rounding each channel's delay to a whole sample. The dispersion constant is taken as k = 1 / (2.41 × 10⁻⁴) MHz² pc⁻¹ cm³ s, the pulsar-astronomy convention rather than the exact physical value; the distinction and its history are discussed by Kulkarni.

  • Manchester, R. N. & Taylor, J. H. (1977), Pulsars. W. H. Freeman.
  • Kulkarni, S. R. (2020), Dispersion measure: confusion, constants and clarity. arXiv:2007.02886

Because shifts are rounded to samples, the achievable DM resolution is set by the time resolution of the data. FLITS derives that limit rather than assuming it — see flits.signal.dedispersion_bin_resolution and DM Optimization.

DM optimization

Two criteria are available. The integrated-event signal-to-noise metric maximizes the S/N of the summed burst profile. The structure-maximizing metric is a clean-room implementation of the DM_phase algorithm, which maximizes the coherence of the burst's Fourier phases across the band and is preferable for bursts with sharp temporal structure.

  • Seymour, A., Michilli, D. & Pleunis, Z. (2019), DM_phase: Algorithm for correcting dispersion of radio signals. Astrophysics Source Code Library, ascl:1910.004
  • Hessels, J. W. T. et al. (2019), FRB 121102 Bursts Show Complex Single-pulse Structures Consistent with Strong Propagation Effects, ApJL 876, L23. doi:10.3847/2041-8213/ab13ae

Calibration and fluence

Peak flux and fluence are calibrated through the radiometer equation using the supplied system-equivalent flux density, effective bandwidth, polarization count and sample time. Uncertainties combine the radiometer-noise statistical term with the SEFD fractional systematic in quadrature; without the latter, the result is reported as statistical-only and flagged as not publishable.

  • Cordes, J. M. & McLaughlin, M. A. (2003), Searches for Fast Radio Transients, ApJ 596, 1142. doi:10.1086/378231
  • Lorimer, D. R. & Kramer, M. (2004), Handbook of Pulsar Astronomy. Cambridge University Press.

See Measurements for how each quantity is classified.

Rotation-measure synthesis

The transform follows Brentjens & de Bruyn; RM-CLEAN follows Heald. FLITS validates its output against RM-Tools reference products.

  • Brentjens, M. A. & de Bruyn, A. G. (2005), Faraday rotation measure synthesis, A&A 441, 1217. doi:10.1051/0004-6361:20052990
  • Heald, G. (2009), The Faraday rotation measure synthesis technique, Proc. IAU 4 (S259), 591. doi:10.1017/S1743921309031421
  • Macquart, J.-P. et al. (2012), The Rotation Measure and 3-Dimensional Magnetic Field Structure, PASA 29, 82. doi:10.1071/AS11027
  • Purcell, C. R., Van Eck, C. L., West, J., Sun, X. H. & Gaensler, B. M. (2020), RM-Tools: Rotation measure synthesis and QU-fitting. Astrophysics Source Code Library, ascl:2005.003

Burst model fitting

Optional scattering and multi-component fits are delegated to fitburst.

Sub-burst drift

The drift rate is measured from the two-dimensional autocorrelation of the dynamic spectrum, the approach established for FRB 121102 and packaged by frbgui. FLITS fits the autocorrelation ellipse for a covariance rather than a rotation angle and reports the conditional-mean slope, which is well defined independently of how the time and frequency axes are scaled against each other; the major-axis slope is reported alongside it for comparison with the angle convention. Drift and dispersion measure are degenerate, and FLITS reports the DM offset that would account for the measured slope rather than choosing between them.

  • Hessels, J. W. T. et al. (2019), FRB 121102 Bursts Show Complex Single-pulse Structures Consistent with Strong Propagation Effects, ApJL 876, L23. doi:10.3847/2041-8213/ab13ae
  • Josephy, A. et al. (2019), CHIME/FRB Detection of the Original Repeating Fast Radio Burst Source FRB 121102, ApJL 882, L18. doi:10.3847/2041-8213/ab2c00
  • Chamma, M. A., Rajabi, F., Wyenberg, C. M., Mathews, A. & Houde, M. (2021), Evidence of a shared spectro-temporal law between sources of repeating fast radio bursts, MNRAS 507, 246. doi:10.1093/mnras/stab2070
  • Chamma, M. A., Rajabi, F., Kumar, A. & Houde, M. (2023), A broad survey of spectro-temporal properties from FRB 20121102A, MNRAS 522, 3036. doi:10.1093/mnras/stad1108
  • Chamma, M. A., FRBGui: a graphical interface for measuring the spectro-temporal properties of fast radio bursts. https://github.com/mef51/frbgui — cite Chamma et al. (2023) above, which the project names as its reference.

See Sub-Burst Drift for the degeneracy and how FLITS classifies the result.

Multiscale temporal structure

Excess power as a function of timescale is measured with a Haar wavelet decomposition against an empirical off-pulse floor.

  • Haar, A. (1910), Zur Theorie der orthogonalen Funktionensysteme, Mathematische Annalen 69, 331. doi:10.1007/BF01456326

Data formats

  • Lorimer, D. R. (2011), SIGPROC: Pulsar Signal Processing Programs. Astrophysics Source Code Library, ascl:1107.016
  • Hotan, A. W., van Straten, W. & Manchester, R. N. (2004), PSRCHIVE and PSRFITS: An Open Approach to Radio Pulsar Data Storage and Analysis, PASA 21, 302. doi:10.1071/AS04022
  • CHIME/FRB Collaboration (2021), The First CHIME/FRB Fast Radio Burst Catalog, ApJS 257, 59. doi:10.3847/1538-4365/ac33ab

Software FLITS depends on

Background

Citing FLITS

See CITATION.cff in the repository.