Working on hardware doesn’t come easily to all physicists, but Francesca Ricci-Tam has learned that what matters most is a willingness to put in the practice.
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Żurek shares her experiences at the 2019 Lindau Nobel Laureate Meeting —from a blimp flight with Ada E. Yonath, who won the Nobel Prize in Chemistry in 2009, to a panel discussion she participated in with three Nobel laureates about navigating a career path in science.
From Kane County Connects, Sept. 3, 2019: As part of a number of grants to national laboratories and universities offered through its QuantISED program, DOE’s recent round of funding to Fermilab covers three initiatives related to quantum science. It also funds Fermilab’s participation in a fourth initiative led by Argonne National Laboratory.
From Washington Post, Aug. 31, 2019: The social media network is packed with great science photos, and the granddaddy of all labs, CERN, also runs a behemoth of an Insta feed. The world’s largest particle physics lab, CERN is home to the Large Hadron Collider, a mammoth particle accelerator that is surprisingly photogenic.
The Cherenkov Telescope Array will combine experimental and observatory-style approaches to investigate the universe’s highest energies.
A composer has given new life to an amplifier used within a historically significant particle accelerator.
Fermilab scientist Jessica Esquivel donned a superhero costume to celebrate diversity in STEM, nerdiness and science at Wakandacon in Chicago.
A holography class at the Ohio State University combines art and physics to provide a more complete picture of how we understand the world around us.
In science, making data open means making available, free of charge, the observations or other information collected in a scientific study for the purpose of allowing other researchers to examine it for themselves, either to verify it or to conduct new analyses. There are barriers to making scientific data open, but doing so has already contributed to scientific progress.
From MIT News, Aug. 19, 2019: A new prototype machine-learning technology co-developed by Fermilab and MIT scientists speeds Large Hadron Collider data processing by up to 175 times over traditional methods.