Mackenzie Graduate creates the fastest Algorithm for Conductivity Calculation in Nanomaterials

A Brazilian scientist has developed an innovative algorithm to accelerate the calculation of conductivity in nanomaterials. Santiago Giménez de Castro, who obtained his Ph.D. in Electrical Engineering from Mackenzie Presbyterian University in 2023, created the algorithm during his studies in the computing field at MPU.

Giménez de Castro described his findings in the article "Fast Fourier-Chebyshev Approach to Real-Space Simulations of the Kubo Formula," published in the Physical Review Letters (PRL) in February 2024. He explained that the algorithm was conceived during his first weeks of work with these methods, but only after a period at York University in the UK did he fully understand its importance.

Giménez de Castro's new method mixes approaches from different papers, providing a more efficient way to calculate the conductivity of nanomaterials, such as graphene, using the Kernel Polynomial Method (KPM). Instead of multiplying large matrices, his algorithm relies on Fast Fourier Transforms (FFT), significantly reducing the time required for the calculation.

Currently, at the Catalan Institute of Nanoscience and Nanotechnology (ICN2), Giménez de Castro continues to explore new contributions to understanding and improving algorithms and computational methods in physics.