Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate
(217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (128)
- User Facilities (27)
Researcher
- Ali Passian
- Joseph Chapman
- Nicholas Peters
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Diana E Hun
- Hsuan-Hao Lu
- Joseph Lukens
- Muneer Alshowkan
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Stephen M Killough
- Vincent Paquit
- Anees Alnajjar
- Brian Williams
- Bryan Maldonado Puente
- Claire Marvinney
- Corey Cooke
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Joel Asiamah
- Joel Dawson
- Mariam Kiran
- Mark M Root
- Michael Kirka
- Nance Ericson
- Nolan Hayes
- Obaid Rahman
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Srikanth Yoginath
- Varisara Tansakul

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

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

A quantum communication system enabling two-mode squeezing distribution over standard fiber optic networks for enhanced data security.

An ultrabroadband, polarization-entangled photon source for C+L-band quantum networks, enabling adaptive, high-fidelity entanglement distribution.

Technologies directed quantum spectroscopy and imaging with Raman and surface-enhanced Raman scattering are described.

Current technology for heating, ventilation, and air conditioning (HVAC) and other uses such as vending machines rely on refrigerants that have high global warming potential (GWP).

Technologies for optimizing prefab retrofit panel installation using a real-time evaluator is described.

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.