Kimball Smith Series: Nuclear Weapons Today: Physics and Politics
Join us on April 22nd from 10:30am-12pm in ESC 110 (21 Sachem St.) for a moderated panel followed by small group discussions on nuclear weapons.
Join us on April 22nd from 10:30am-12pm in ESC 110 (21 Sachem St.) for a moderated panel followed by small group discussions on nuclear weapons.
Microspheres have been the first objects optically levitated by Arthur Ashkin in the 1970s. While the technology itself was successfully used to trap atoms to explore new physics, the actual utilization of microspheres and other macroscopic objects as a useful tool for physics has emerged in the recent years. The unique properties of those levitated objects allows to deploy them as sensors with unmatched properties and advantages.
Join us for a Yale Science and Engineering Association virtual conversation with Dr. Alvin M. Saperstein ’56 PhD, professor of physics emeritus and executive board member of the Center for Peace and Conflict Studies at Wayne State University as well as the former editor of the Physics and Society, a quarterly journal of the Forum on Physics and Society of the American Physical Society. He has been a Foster Fellow at the U.S.
Wright Lab will host 1-hour Environmental Health and Safety (EHS) Shop Orientations. The EHS shop orientation is offered each semester and is required to be taken once by anyone who would like to gain access and make use of the research and teaching shops at Wright Lab.
For more information on the shop facilities at Wright Lab see: https://wlab.yale.edu/facilities
Register here: https://forms.gle/MzVDERoSrtmwp8579
Jets are collimated sprays of hadrons produced in high energy collider experiments, such as
Why is the universe dominated by matter, and not antimatter? Neutrinos, with their changing flavors and tiny masses, could provide an answer. If the neutrino is a Majorana particle, meaning that it is its own antiparticle, it would reveal the origin of the neutrino’s mass, demonstrate that lepton number is not a conserved symmetry of nature, and provide a path to leptogenesis in the early universe. To discover whether this is the case, we must search for neutrinoless double-beta decay, a theorized process that would occur in some nuclei.
In Life’s Edge, Carl Zimmer explores the nature of life and investigates why scientists have struggled to draw its boundaries. He handles pythons, goes spelunking to visit hibernating bats, and even tries his hand at evolution. Zimmer visits scientists making miniature human brains to ask when life begins, and follows a voyage that delivered microscopic animals to the moon, where they now exist in a state between life and death. From the coronavirus to consciousness, Zimmer demonstrates that biology, for all its advances, has yet to achieve its greatest triumph: a full theory of life.
The sciences are replete with high-fidelity simulators: computational manifestations of causal, mechanistic models. Ironically, while these simulators provide our highest-fidelity physical models, they are not well suited for inferring properties of the model from data. Professor Kyle Cranmer of New York University will describe the emerging area of simulation-based inference and describe how machine learning is being brought to bear on these challenging problems.
Abstract: The possible existence of beyond Standard Model physics at the TeV scale or below has important implications for the thermal history of electroweak symmetry-breaking. A first order phase transition – not possible in the minimal Standard Model with a 125 GeV Higgs boson – would provide the preconditions for electroweak baryogenesis and the generation of primordial gravitational radiation. I discuss recent developments in assessing this possibility that rely on the combination of EFT methods and non-perturbative (lattice) computations.
The sciences are replete with high-fidelity simulators: computational manifestations of causal, mechanistic models. Ironically, while these simulators provide our highest-fidelity physical models, they are not well suited for inferring properties of the model from data. Professor Kyle Cranmer of New York University will describe the emerging area of simulation-based inference and describe how machine learning is being brought to bear on these challenging problems.