activity
20172025
most citedFree-Space Optical Spiking Neural Network

4 citations · 5 across the 9 of their papers we have counts for

collaborators

9 papers

physics.optics2025

Optical Physics-Based Generative Models

Amirreza Ahmadnejad, Somayyeh Koohi

This paper establishes a comprehensive mathematical framework connecting optical physics equations to generative models, demonstrating how light propagation dynamics inspire powerf…

physics.optics2025

All-Optical Doubly Resonant Cavities for ReLU Function in Nanophotonic Deep Learning

Amirreza Ahmadnejad, Mohmmad Mehrdad Asadi, Somayyeh Koohi

We present a novel approach to implementing all-optical Rectified Linear Unit (ReLU) activation functions using compact doubly-resonant cavities with dimensions of approximately $1…

physics.optics2025

Nontrapping Tunable Topological Photonic Memory

Amirreza Ahmadnejad, Somayyeh Koohi, Abolhassan Vaezi

We propose a novel topological photonic memory that encodes information through dynamically controllable Chern numbers in a two-band topological photonic system. Utilizing a honeyc…

cs.LG2024

Training Large-Scale Optical Neural Networks with Two-Pass Forward Propagation

Amirreza Ahmadnejad, Somayyeh Koohi

This paper addresses the limitations in Optical Neural Networks (ONNs) related to training efficiency, nonlinear function implementation, and large input data processing. We introd…

q-bio.QM2023

An Assessment of PC-mer's Performance in Alignment-Free Phylogenetic Tree Construction

Saeedeh Akbari Rokn Abadi, Melika Honarmand, Ali Hajialinaghi +1

Background: Sequence comparison is essential in bioinformatics, serving various purposes such as taxonomy, functional inference, and drug discovery. The traditional method of align…

physics.optics2023★ 4 cited

Free-Space Optical Spiking Neural Network

Reyhane Ahmadi, Amirreza Ahmadnejad, Somayyeh Koohi

Neuromorphic engineering has emerged as a promising avenue for developing brain-inspired computational systems. However, conventional electronic AI-based processors often encounter…