Simulit

Simulit is a Python package for simulating UVIT-like photon event lists from astrophysical source models.

It is designed for developing, testing, and validating software for source detection, photometry, variability analysis, PSF improvement, and other UVIT data analysis applications.

Current source models include:

• Gaussian point sources
• Elliptical exponential galaxies
• Uniform circular sources

Simulit can also:

• Generate detector images from simulated event lists
• Create truth catalogues for validation and benchmarking

Installation

pip install simulit

Quick start

import numpy as np
import simulit as sm

rng = np.random.default_rng(42)

observation = sm.Observation(
    exposure=2000,
)

centre = observation.detector.detector_size / 2

sources = sm.generate_gaussian_sources(
    n_sources=100,
    rate=0.1,
    fwhm=3,
    x0=centre,
    y0=centre,
    radius=2048,
    rng=rng,
)

times, x, y = observation.simulate_events(
    sources,
    rng=rng,
)

truth = sm.create_truth_catalogue(sources)

sm.save_events(times, x, y)
sm.save_truth_catalogue(truth)

sm.make_image_from_events(
    x,
    y,
    exposure=observation.exposure,
    detector_size=observation.detector.detector_size,
)

Source models

GaussianSource

A Gaussian point source.

sm.GaussianSource(
    rate=1.0,
    x=2400,
    y=2400,
    fwhm=3,
)

ExponentialGalaxy

An elliptical exponential galaxy with an exponential surface brightness profile.

sm.ExponentialGalaxy(
    rate=0.5,
    x=2400,
    y=2400,
    r0=3.0,
    q=0.7,
    pa=np.pi / 4,
)

UniformDisk

A uniformly illuminated circular source.

sm.UniformDisk(
    rate=5.0,
    x=2400,
    y=2400,
    radius=200,
)

Observation

An Observation combines

• exposure time
• detector configuration
• optional pointing drift

observation = sm.Observation(
    exposure=2000,
)

A pointing drift model can also be supplied.

drift = sm.Drift(
    x_offset=x_shift,
    y_offset=y_shift,
)

observation = sm.Observation(
    exposure=2000,
    drift=drift,
)

Output products

Simulit can generate

• simulated photon event lists
• detector images
• truth catalogues

Examples

The examples/ directory contains complete working examples.

• mixed_sources.py — mixed populations of point sources, galaxies, and diffuse background
• synthetic_drift.py — simulate observations with synthetic UVIT-inspired pointing drift
• inject_sources_into_uvit_events.py — inject simulated sources into an existing UVIT Level-2 events list.

Planned features

Future development is expected to include:

• additional source models
• realistic background models
• cosmic ray simulations
• detector artefacts
• UVIT slitless spectroscopy
• filter-dependent simulations