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Hierarchical Bayesian Operator-induced Symbolic Regression Trees for Structural Learning of Scientific Expressions
Somjit Roy, Pritam Dey, Debdeep Pati, Bani K. Mallick
https://arxiv.org/abs/2509.19710

Hierarchical Bayesian Operator-induced Symbolic Regression Trees for Structural Learning of Scientific Expressions
The advent of Scientific Machine Learning has heralded a transformative era in scientific discovery, driving progress across diverse domains. Central to this progress is uncovering scientific laws from experimental data through symbolic regression. However, existing approaches are dominated by heuristic algorithms or data-hungry black-box methods, which often demand low-noise settings and lack principled uncertainty quantification. Motivated by interpretable Statistical Artificial Intelligence,…

Radiation-induced Ionization Effects and Space Mission Requirements for Silicon Photonic Mach-Zehnder Modulators
Kellen P. Arnold, Joel B. Slaby, Nathaniel J. Karom, Anurag R. Veluri, C. Alex Kaylor, Andrew L. Sternberg, Dennis R. Ball, Ronald D. Schrimpf, Daniel M. Fleetwood, Stephen E. Ralph, Robert A. Reed, Sharon M. Weiss
https://arxiv…

Radiation-induced Ionization Effects and Space Mission Requirements for Silicon Photonic Mach-Zehnder Modulators
Photonic integrated circuits have become essential for meeting the growing global demand for high-capacity information processing and transport. Assessing their radiation tolerance is essential for deploying systems in radiation prone environments - including in space, high-energy particle accelerators, and defense radiation testing facilities - where the performance and compactness of photonic integrated circuits are increasingly advantageous. This work investigates the analog and digital radi…