Computer Science

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August 29, 2022
News Feature
SLAC works with two small businesses to make its ACE3P software easier to use in supercomputer simulations for optimizing the shapes of accelerator structures.
A large, complex shape is seen against a blue background crisscrossed with white lines. The shape is dark blue and resembles a brick partially topped with a thick shark’s fin. Three areas of bright red, orange and green, are on the shape’s bottom edge.
July 27, 2022
News Feature
An extension of the Stanford Research Computing Facility will host several data centers to handle the unprecedented data streams that will be produced by a new generation of scientific projects.
SRCF-II
April 5, 2022
News Feature
The leaders of SLAC's Technology Innovation Directorate discuss how their group supports the lab's most innovative projects.
TID senior managers
July 15, 2021
Press Release
They discover a short-lived state that could lead to faster and more energy-efficient computing devices.
ultrafast switching
September 30, 2020
News Feature
Daniel Ratner, head of SLAC’s machine learning initiative, explains the lab’s unique opportunities to advance scientific discovery through machine learning.
Daniel Ratner
September 16, 2019
News Feature
Two projects will look for ways to link individual quantum devices into networks for quantum computing and ultrasensitive detectors.
QIS microantenna
July 18, 2019
News Feature
Maria Elena Monzani prepares an international team to search for clues to one of the biggest scientific mysteries.
Maria Elena Monzani at the LZ test facility
May 9, 2019
News Feature
Monika Schleier-Smith and Kent Irwin explain how their projects in quantum information science could help us better understand black holes and dark matter.
QIS-Schleier-Smith-Irwin
September 24, 2018
News Feature
SLAC receives three awards for the development of quantum technology for dark matter searches and quantum computing
Quantum Information Science
August 1, 2018
News Feature
Researchers from SLAC and around the world increasingly use machine learning to handle Big Data produced in modern experiments and to study some of the most fundamental properties of the universe.
Machine Learning in HEP

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