Sofiya Zuykova | Polygence
Symposium presenter banner

Symposium

Of Rising Scholars

Fall 2025

Sofiya will be presenting at The Symposium of Rising Scholars on Saturday, September 27th! To attend the event and see Sofiya's presentation.

Go to Polygence Scholars page
Sofiya Zuykova's cover illustration
Polygence Scholar2025
Sofiya Zuykova's profile

Sofiya Zuykova

Class of 2026Calgary, Alberta

About

Hello! I'm Sofiya. I love drawing, reading, and most of all anything related to space!

Projects

  • "Dark matter-Neutrino coupling and varying ΔNeffective as a viable solution to light element abundance tension" with mentor Anne-Katherine (June 8, 2025)

Project Portfolio

Dark matter-Neutrino coupling and varying ΔNeffective as a viable solution to light element abundance tension

Started Dec. 2, 2024

Abstract or project description

This study investigates the impact of a dark matter species capable of interacting with neutrinos on the final abundances of Helium-4 and Deuterium which were produced during Big Bang Nucleosynthesis (BBN). Recent measurements by EMPRESS suggest discrepancies between the observed and theoretically predicted values of these primordial nuclei.  To explore whether neutrino-coupled dark matter could alleviate this tension, I used the open-source code PRyMordial to simulate BBN under modified conditions.

I tested a variety of dark matter masses in the range of 2–10 MeV and adjusted the effective number of relativistic species varying up and down from its standard cosmological value. These variations were designed to reflect plausible modifications to the energy density present in the early-universe influenced by the studied dark matter–neutrino interactions as well as the change in Neffective. The simulations show that while varying dark matter mass alone had little effect, inputting a negative 𝚫Neffective significantly reduced the Helium-4 and Deuterium abundances. A 𝚫Neffective value around −0.75 brought simulated Helium-4 levels into agreement with the EMPRESS data, while Deuterium results aligned with observed values across a wider parameter space.