Filter Results
Researcher
- Hsuan-Hao Lu
- Joseph Lukens
- Nicholas Peters
- Joseph Chapman
- Muneer Alshowkan
- Anees Alnajjar
- Chad Steed
- Chris Tyler
- Jaydeep Karandikar
- Junghoon Chae
- Kyle Kelley
- Mingyan Li
- Travis Humble
- Aaron Myers
- Akash Jag Prasad
- Alex Miloshevsky
- Bogdan Dryzhakov
- Brian Williams
- Burak Ozpineci
- Calen Kimmell
- Corey Cooke
- Craig A Bridges
- Gui-Jia Su
- Isaac Sikkema
- Jian Chen
- Joseph Olatt
- Justin Cazares
- Kunal Mondal
- Liam Collins
- Mahim Mathur
- Mariam Kiran
- Marti Checa Nualart
- Matt Larson
- Nageswara Rao
- Neus Domingo Marimon
- Oscar Martinez
- Pablo Moriano Salazar
- Pedro Ribeiro
- Rama K Vasudevan
- Sam Hollifield
- Samudra Dasgupta
- Sheng Dai
- Stephen Jesse
- Steven Randolph
- Subho Mukherjee
- Vandana Rallabandi
- Vasiliy Morozov
- Vladimir Orlyanchik
- Zhili Feng

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

Finite element (FE) numerical computation method is widely used to facilitate the design and optimization of manufacturing processes using two types of solvers, implicit and explicit.

Electrochemistry synthesis and characterization testing typically occurs manually at a research facility.

ORNL's fully on-chip CMOS-fabricated integrated photonic circuit can generate polarization or frequency entangled photons for use in quantum communications and networking.

Photonic hyperentanglement involves pairs of photons entangled in multiple degrees of freedom (DoF), which hold promise for quantum communication protocols. However, the frequency DoF has received less attention due to constraints in evaluating such hyperentangled states.

There is a strong drive to improve the electrical performance of a power module for power electronics applications including transportation, buildings, renewables, and power delivery.

This invention utilizes new techniques in machine learning to accelerate the training of ML-based communication receivers.

Technologies are described for privacy-preserving, reduced bias system that identifies faces. The disclosed technologies can be used for national security purposes, or other civilian purposes.