FUTURE Ignited
11-04-20
Nearly 200 undergraduates from more than 120 colleges and universities across the country joined Caltech for FUTURE Ignited, a virtual event that aimed to encourage students of color to pursue graduate studies in science and engineering. The goal of FUTURE Ignited is to diversify STEM with students of color who will go on to become incredible graduate students and scientific leaders in their respective fields. [Caltech story]
A Molecular Approach to Quantum Computing
09-03-20
The technology behind the quantum computers of the future is fast developing, with several different approaches in progress. Many of the strategies, or "blueprints," for quantum computers rely on atoms or artificial atom-like electrical circuits. In a new theoretical study in the journal Physical Review X, Caltech demonstrates the benefits of a lesser-studied approach that relies not on atoms but molecules. One concept behind the new research comes from work performed nearly 20 years ago by Professor John Preskill, Professor Alexei Kitaev, and their colleague Daniel Gottesman. [Caltech story]
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CMS
Alexei Kitaev
John Preskill
Advancing Future Quantum Science Efforts
08-27-20
Five new Department of Energy centers will apply quantum information science to emerging technologies. The centers will develop cutting-edge quantum technologies for use in a wide range of possible applications including scientific computing; fundamental physics and chemistry research; and the design of solar cells and of new materials and pharmaceuticals. Caltech faculty will participate in four of the new science centers: the Quantum Systems Accelerator, led by the Lawrence Berkeley National Laboratory, also known as Berkeley Lab; the Quantum Science Center, led by Oak Ridge National Laboratory; Q-NEXT, led by Argonne National Laboratory; and the Co-design Center for Quantum Advantage, led by Brookhaven National Laboratory. [Caltech story]
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APhMS
EE
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CMS
Oskar Painter
Andrei Faraon
AI for a Better Prediction COVID-19 Model
08-25-20
A team of Caltech students, led by Professor Yaser Abu-Mostafa, have developed a tool to predict the impact of COVID-19 using artificial intelligence (AI). While many models to predict the spread of a disease already exist, few if any incorporate AI, which makes predications based on observations of what is actually happening as opposed to what the model's designers think should happen. AI has the power to discover patterns hidden in data that the human eye might not recognize. [Caltech story]
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EE
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CMS
Yaser Abu-Mostafa
Machine Learning Helps Robot Swarms Coordinate
07-14-20
Soon-Jo Chung, Bren Professor of Aerospace, Yisong Yue, Professor of Computing and Mathematical Sciences, postdoctoral scholar Wolfgang Hönig, and graduate students Benjamin Rivière and Guanya Shi, have designed a new data-driven method to control the movement of multiple robots through cluttered, unmapped spaces, so they do not run into one another. "Our work shows some promising results to overcome the safety, robustness, and scalability issues of conventional black-box artificial intelligence (AI) approaches for swarm motion planning with GLAS and close-proximity control for multiple drones using Neural-Swarm," says Chung. [Caltech story]
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GALCIT
CMS
Yisong Yue
Soon-Jo Chung
postdocs
Benjamin Rivière
Guanya Shi
Wolfgang Hönig