From Forbes, Jan. 14, 2021: The Dark Energy Survey recently publicly released an enormous amount of data for anyone to use. This data set contains nearly seven hundred million individual astronomical objects. Fermilab scientist Don Lincoln explains how collaborators on the Dark Energy Survey study the history of the universe and highlights a number of the scientific findings in DES’s rich trove of data.
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The international collaboration, including Fermilab, the National Center for Supercomputing Applications, NOIRLab and others, releases a massive, public collection of astronomical data and calibrated images from six years of surveys. This data release is one of the largest astronomical catalogs issued to date.
From CERN Courier, Jan. 13, 2021: The US LHC Accelerator Upgrade Project, led by Fermilab scientist Giorgio Apollinari, is now entering the production phase in the construction of magnets for the upcoming High-Luminosity LHC, an upgrade of the current Large Hadron Collider. U.S. labs are building magnets that will focus beams near the ATLAS and CMS particle detectors.
From Forbes, Jan. 11, 2021: Fermilab scientist Don Lincoln explains a result from the LHCb experiment that adds another data point on nature’s matter-antimatter imbalance.
From Interesting Engineering, Jan. 5, 2021: A recent breakthroughs in transmitting, storing, and manipulating quantum information have convinced some physicists that a simple proof of principle for a quantum network is imminent. In 2017, a number of institutions partnered with Fermilab to begin constructing a quantum network hosted at Fermilab.
From Daily Herald, Jan. 7, 2021: On Tuesday, Jan. 12, the Fermilab Art and Lecture Series will present its next virtual gallery talk on “Imagining Reality,” a photographic journey with Fermilab scientist Steve Geer. He will describe his artistic process as applied to various photographic projects that he’s exhibited in galleries and published in books and magazines.
Fermilab scientists and engineers are developing a machine learning platform to help run Fermilab’s accelerator complex alongside a fast-response machine learning application for accelerating particle beams. The programs will work in tandem to boost efficiency and energy conservation in Fermilab accelerators.
High-intensity particle beams enable researchers to probe rare physics phenomena. A proposed technique called optical stochastic cooling could achieve brighter beams 10,000 times faster than current technology allows. A proof-of-principle experiment to demonstrate OSC has begun at Fermilab’s Integrable Optics Test Accelerator.