My research sits at the intersection of high-energy astrophysics, particle
physics, and computational methods. I focus primarily on understanding the
high-energy universe through neutrinos — weakly interacting particles that
travel cosmological distances unimpeded and carry information about their sources.
jlazar@uclouvain:~/research $ls -la topics/
neutrino_telescopes/
I work with the IceCube
neutrino telescope at the South Pole and contribute to next-generation
detectors including TAMBO.
My focus includes solar neutrino searches, dark matter annihilation signals,
and supernova neutrino transients.
simulation_tools/
I develop open-source software for the neutrino physics community.
Prometheus
(arXiv:2304.14526)
is a modular neutrino telescope simulation suite;
TauRunner
(arXiv:2110.14662)
propagates tau and muon neutrinos through the Earth; and
χarον
(arXiv:2007.15010)
generates neutrino spectra from WIMP annihilation. All are publicly available
and used by the community.
beyond_standard_model/
I use neutrino telescopes to look for physics the Standard Model does not
account for. Much of that is dark matter: I search for annihilation and
scattering signatures in solar neutrino data from IceCube, placing limits on
WIMP-nucleon cross sections, and I developed
χarον,
a public tool for generating neutrino flux spectra from WIMP annihilation in
the Sun. More recently I showed that the time profile of the neutrino
burst from a galactic supernova is itself a probe of new physics
(Phys. Rev. Lett. 134, 221002,
arXiv:2403.09781).
ml_reconstruction/
I apply machine learning — including graph neural networks and sparse
convolutional architectures — to neutrino event reconstruction in IceCube.
I contributed to NuBench
(GitHub,
arXiv:2511.13111),
an open benchmark for deep-learning-based reconstruction in neutrino telescopes.
quantum_computing/
I explore quantum algorithms for high-energy physics data analysis, including
quantum-encoded data representations for neutrino oscillation measurements
(arXiv:2402.19306).