Publications (24)
HEAL: Hierarchical Embedding Alignment Loss for Improved Retrieval and Representation Learning
Manish Bhattarai, Ryan Barron, Maksim Eren +8
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external document retrieval to provide domain-specific or up-to-date knowledge. The effect…
Rapid analysis of point-contact Andreev reflection spectra via machine learning with adaptive data augmentation
Dongik Lee, Valentin Stanev, Xiaohang Zhang +3
Delineating the superconducting order parameters is a pivotal task in investigating superconductivity for probing pairing mechanisms, as well as their symmetry and topology. Point-…
Time-reversal symmetry breaking state in dirty three-band superconductor
Valentin Stanev
I study the effects of disorder on the superconductivity of a three-band model with repulsive interband pairing. Such a model can support several possible superconducting order par…
High-throughput investigation of tunable superconductivity in FeSe films
Zhongpei Feng, Jie Yuan, Jun Li +19
There is an ongoing debate about the relative importance of structural change versus doping charge carriers on the mechanism of superconductivity in Fe-based materials. Elucidating…
Long range -wave proximity effect into a disordered metal
Aydin Cem Keser, Valentin Stanev, Victor Galitski
We use quasiclassical methods of superconductivity to study the superconducting proximity effect from a topological -wave superconductor into a disordered one-dimensional metall…
Machine learning modeling of superconducting critical temperature
Valentin Stanev, Corey Oses, A. Gilad Kusne +4
Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood;…