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FitTeD

Fitting Transients with Discs — a public Python package for fitting light curves and spectra of astronomical transients with evolving relativistic accretion discs.

FitTeD solves the time-dependent general relativistic disc equations, turns the resulting temperature profile into multi-band light curves and spectra, and fits them to your data. All of the relevant relativistic optics is included: Doppler shifting, gravitational energy shifting, and gravitational lensing.

Get started Tutorials

What it does

  • Time-dependent disc evolution

    Self-consistent solutions of the relativistic disc equations, not a steady-state approximation. The disc spreads, the inner edge fills in, and the whole profile cools as mass drains through the ISCO.

  • Optical, UV and X-ray together

    The optical sits on the Rayleigh–Jeans tail and declines gently; the X-ray sits on the Wien tail and is exponentially sensitive to the inner-disc temperature. Fitting both is what constrains the black hole mass.

  • Relativistic ray tracing

    A pure-Python Kerr ray tracer, so photon transport needs no compiler and no build step on any platform.

  • MCMC and posteriors

    emcee, parallelised across walkers, with convergence diagnostics, corner plots and posterior light curves built in.

What it is used for

  • Tidal disruption events — the late-time optical/UV and X-ray emission
  • X-ray binaries — soft-state light curve decays
  • Luminous fast blue optical transients — accretion-powered transients

Thirty seconds of code

import fitted

# Load a TDE by name, from the manyTDE catalogue
data = fitted.data.Data_Set(
    manyTDE_name='AT2019dsg',
    manyTDE_bands=['r.ztf', 'g.ztf', 'UVW1.uvot'],
    global_systematic=0.1,
)

# Build a disc model with an early-time component
model = fitted.models.GR_disc(data=data, decay=True, decay_type='pl', rise=True)
fit = fitted.Fit(model=model)

# Physical values in, sampling-space vector out
start = model.pack_parameters(
    log_mh=6.7, a_bh=0.01, m_disc=0.05, r0=30.0, tvi=15.0, t0=-2.0, incl=70.0,
    log_L=43.3, t_fb=67.0, p=5/3, t_peak=1.0, sigma=8.0, log_T=4.4,
)

best = fit.best_fit(start)
fit.run_chain(full_pars=best, nwalkers=100, nsteps=2000, backend_path='chain.h5')
fit.plot_corner()

Tutorial 06 is this, done properly, end to end, with real output.

Where to start

If you are new to the package, read the tutorials in this order: 00 (install), 01 (data), 03 (model), 04 (fitting), 05 (MCMC). That is a complete arc and needs no optional dependencies.

Read tutorial 03 even if you are in a hurry

It explains the difference between the parameters the physics uses (m_disc in solar masses, incl in degrees) and the parameters the sampler moves (log_m_disc, cos_incl). Confusing the two is the most common way to end up with a chain that will not start, and model.pack_parameters() makes the problem go away entirely.

Citation

Mummery et al. (2025), Fitting transients with discs (FitTeD): a public light curve and spectral fitting package based on evolving relativistic discs, MNRAS 544, 2225.

See Citing FitTeD for BibTeX.