The Cherenkov Telescope Array (CTA) will be the next generation ground-based
very-high-energy gamma-ray observatory, constituted by tens of Imaging Atmospheric
Cherenkov Telescopes at two sites once its construction and commissioning are finished.
Like its predecessors, CTA relies on Instrument Response Functions (IRFs) to relate
the observed and reconstructed properties to the true ones of the primary gamma-ray
photons.
IRFs are needed for the proper reconstruction of spectral and spatial information of
the observed sources and are thus among the data products issued to the observatory
users.
They are derived from Monte Carlo simulations, depend on observation conditions like
the telescope pointing direction or the atmospheric transparency and can evolve with
time as hardware ages or is replaced.
Producing a complete set of IRFs from simulations for every observation taken is a
time-consuming task and not feasible when releasing data products on short timescales.
Consequently, interpolation techniques on simulated IRFs are investigated to quickly
estimate IRFs for specific observation conditions.
However, as some of the IRFs constituents are given as probability distributions,
specialized methods are needed.
This contribution summarizes and compares the feasibility of multiple approaches to
interpolate IRF components in the context of the pyirf python software package and
IRFs simulated for the Large-Sized Telescope prototype (LST-1).
We will also give an overview of the current functionalities implemented in pyirf.