November 2024   |   Artificial Intelligence

We the AI trainers

A Gordon Bell-nominated team aims to put the power behind large language models into the hands of ordinary people.

AI
October 2024

AI turbocharge

With Argonne’s Polaris supercomputer, a University of Michigan-led team bets on large language models to improve batteries.

 

Biology, Computer Science
October 2024

Pandemic preparedness

A PNNL physicist turned from basic to applied research: biopreparedness.

Aeronautics, Engineering
August 2024

A heavy lift

A University of Kansas aerospace engineer aims high-performance computing at intricate airflow patterns to improve aircraft flight.

Science Highlights

June 2024

Qubits, bit by bit

Scientists simulate quantum properties in a widely used semiconductor material.

To build and deploy large-scale quantum computers, researchers need to know how to control quantum bits, or qubits, made of materials with stable electronic properties. At the Department of Energy’s Midwest Center for Computational Materials (MICCoM), Argonne National Laboratory and University of Chicago researchers conducted materials simulations using a neural network-based sampling technique. Their results suggest that a leading semiconductor candidate for qubits, silicon carbide (SiC), is indeed a promising material, with long qubit coherence times and all-optical spin initialization and read-out capabilities. These advances will help the design and fabrication of spin-based qubits with atomic precision in semiconductor materials, ultimately accelerating the development of next-generation large-scale quantum computers and quantum sensors.

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