activity
20142026
most citedParallel convolution processing using an integrated photonic tensor core

1.9k citations · 3.5k across the 16 of their papers we have counts for

collaborators

17 papers

physics.optics2026

Ultra-Thin Aluminum-Doped Silver for Transmissive Thermally Reconfigurable Visible Photonics

Hongyi Sun, Yi-Siou Huang, Junyeob Song +7

Functional materials with high electrical conductivity and optical transmittance are vital for thermally tunable free-space photonic systems. Conventional transparent conductors su…

physics.optics2023

Nonvolatile Tuning of Bragg Structures Using Transparent Phase-Change Materials

Nicholas A. Nobile, Chuanyu Lian, Hongyi Sun +7

Bragg gratings offer high-performance filtering and routing of light on-chip through a periodic modulation of a waveguide's effective refractive index. Here, we model and experimen…

physics.app-ph2023★ 167 cited

In-memory photonic dot-product engine with electrically programmable weight banks

Wen Zhou, Bowei Dong, Nikolaos Farmakidis +7

Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid…

physics.optics2022

Time-resolved temperature mapping leveraging the strong thermo-optic effect in phase-change devices

Nicholas A. Nobile, John R. Erickson, Carlos Ríos +5

Optical phase-change materials are highly promising for emerging applications such as tunable metasurfaces, reconfigurable photonic circuits, and non-von Neumann computing. However…

cs.LG2022★ 11 cited

AnalogVNN: A fully modular framework for modeling and optimizing photonic neural networks

Vivswan Shah, Nathan Youngblood

AnalogVNN, a simulation framework built on PyTorch which can simulate the effects of optoelectronic noise, limited precision, and signal normalization present in photonic neural ne…

physics.optics2021

All-optical spiking neurosynaptic networks with self-learning capabilities

J. Feldmann, N. Youngblood, C. D. Wright +2

Software-implementation, via neural networks, of brain-inspired computing approaches underlie many important modern-day computational tasks, from image processing to speech recogni…

physics.optics2020★ 29 cited

Monadic Pavlovian associative learning in a backpropagation-free photonic network

James Y. S. Tan, Zengguang Cheng, Johannes Feldmann +6

Over a century ago, Ivan P. Pavlov, in a classic experiment, demonstrated how dogs can learn to associate a ringing bell with food, thereby causing a ring to result in salivation.…

physics.optics2020★ 28 cited

Engineering photonic environments for two-dimensional materials

Xuezhi Ma, Nathan Youngblood, Xiaoze Liu +5

A fascinating photonic platform with a small device scale, fast operating speed, as well as low energy consumption is two-dimensional (2D) materials, thanks to their in-plane cryst…

physics.optics2020★ 1.9k cited

Parallel convolution processing using an integrated photonic tensor core

Johannes Feldmann, Nathan Youngblood, Maxim Karpov +13

With the proliferation of ultra-high-speed mobile networks and internet-connected devices, along with the rise of artificial intelligence, the world is generating exponentially inc…

physics.app-ph2019★ 4 cited

Broadly-tunable smart glazing using an ultra-thin phase-change material

Nathan Youngblood, Clément Talagrand, Benjamin Porter +8

For many applications, a method for controlling the optical properties of a solid-state film over a broad wavelength range is highly desirable and could have significant commercial…

physics.optics2019★ 1 cited

Non-volatile silicon photonic memory with more than 4-bit per cell capability

Xuan Li, Nathan Youngblood, C. David Wright +2

We present the first demonstration of an integrated photonic phase-change memory using GeSbTe-225 on silicon-on-insulator and demonstrate reliable multilevel operation with a singl…

physics.optics2018

Plasmonic nanogap enhanced phase change devices with dual electrical-optical functionality

Nikolaos Farmakidis, Nathan Youngblood, Xuan Li +6

Modern-day computers use electrical signaling for processing and storing data which is bandwidth limited and power-hungry. These limitations are bypassed in the field of communicat…

cs.ET2018

In-memory computing on a photonic platform

Carlos Ríos, Nathan Youngblood, Zengguang Cheng +5

Collocated data processing and storage are the norm in biological systems. Indeed, the von Neumann computing architecture, that physically and temporally separates processing and m…

physics.optics2017★ 118 cited

Mid-infrared Electro-Optic Modulation in Few-layer Black Phosphorus

Ruoming Peng, Kaveh Khaliji, Nathan Youngblood +3

Black phosphorus stands out from the family of two-dimensional materials as a semiconductor with a direct, layer-dependent bandgap in energy corresponding to the spectral range fro…

cond-mat.mtrl-sci2016★ 8 cited

Layer Tunable Third-Harmonic Generation in Multilayer Black Phosphorus

Nathan Youngblood, Ruoming Peng, Andrei Nemilentsau +2

Black phosphorus has been the subject of growing interest due to its unique band structure that is both layer dependent and anisotropic. While many have studied the linear optical…

physics.optics2014★ 956 cited

Waveguide-integrated black phosphorus photodetector with high responsivity and low dark current

Nathan Youngblood, Che Chen, Steven J. Koester +1

Layered two-dimensional materials have shown novel optoelectronic properties and are well suited to be integrated in planar photonic circuits. For example, graphene has been utiliz…

physics.optics2014★ 238 cited

Multifunctional graphene optical modulator and photodetector integrated on silicon waveguides

Nathan Youngblood, Yoska Anugrah, Rui Ma +2

For optical communication, information is converted between optical and electrical signal domains at a high rate. The devices to achieve such a conversion are various types of elec…