Gravitationally lensed quasars have served as a powerful tool for studying the composition of dark matter (DM) in lensing galaxies. In this work, we propose a novel method to investigate stellar-mass primordial black holes (PBHs) by using the microlensing effect of strongly lensed Type Ia supernovae (SNe Ia). Using the parameters of the lensed quasar system PG $1115+80$, such as convergence, shear, and stellar/dark matter fractions, we generate microlensing magnification maps. A uniform brightness disk model is applied to these maps to evaluate the microlensing amplitude at different stages of the supernova explosion. We extend this analysis by employing the strong lensing parameters derived from the Vera C. Rubin Observatory’s Legacy Survey of Space and Time to create extensive image datasets of lensed SNe Ia. Utilizing these datasets and the Kolmogorov-Smirnov test, we compare two models: (1) the fiducial model, where galaxies are composed of stars and smooth DM, and (2) the alternative model, where galaxies consist of stars and compact DM, specifically PBHs. Our preliminary analysis predicts that at least 60 image datasets are required to distinguish these two scenarios at a 95% confidence level. Additionally, by incorporating the strong lensing halo model-based mock catalogs, which provide more realistic and precise image data, we refine our prediction to assess the data requirements for distinguishing cases where PBHs constitute fractions x of the total dark matter mass. Our findings indicate that 50, 55, and 65 image datasets, corresponding to compact dark matter fractions of 100%, 50%, and 25% (denoted by x), are necessary to distinguish between the specific models.

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• Dark matter
• Gravitational lenses
• Novae & supernovae