In-person attendance will be capped at 20 people on a first-come, first-served basis, according to the current Yale policies.
More Information: https://covid19.yale.edu/campus-life/events-gatherings-meetings
Please email the host for the Zoom connection information.
Host:Laura Havener
The validity of the Statistical Hadronization Model (SHM) has been successfully tested to adequately reproduce hadronic particle abundances over nine orders of magnitude in high energy collisions of heavy ions. Assuming a thermally equilibrated system, experimental particle yields at RHIC and the LHC serve as an anchor for the determination of common freeze-out parameters in the QCD phase diagram – namely, the baryo-chemical potential (µB) and the chemical freeze-out temperature (Tch) - via thermal fits in the SHM framework.
High-energy jets experience severe modifications along their passage through the quark-gluon plasma (QGP), a new state of matter created in ultra-relativistic heavy ion collisions. Due to the steeply falling jet spectrum, when we measure jets we are typically looking at the jets that lost the least energy. This selection bias hinders our ability to study true jet modifications, resulting in a more limited knowledge of the way the QGP interacts with the energetic partons.
Professors Bonnie Fleming and David Moore will guide participants in how to prepare for faculty positions in physics.
This event is only open to members of the Yale community. Email the host for the Zoom connection.
Host:
Victoria Misenti
Optical interferometers have begun a new era of astrophysics by measuring vast lengths to such precision that gravitational waves from distant collisions of black holes and neutron stars are now regularly observed. This past run, the global gravitational wave network itself entered a new era, whereby every detector’s sensitivity is enhanced using quantum squeezed states of light. Manipulating profound measurement precision has profound consequences – measurement back action, in LIGO taking the form of quantum radiation pressure noise on 40kg mirrors.
Unlike phase diagrams in condensed matter that can be probed in the laboratory, the Quantum Chromodynamics (QCD) phase diagram can only be mapped out through both experiments and astrophysical phenomena. At low baryon densities and high temperatures it is explored both through the big bang and the little bangs produced in heavy-ion collisions. At large baryon densities, either low-energy heavy-ion experiments or neutron star mergers can be used to map out its potential phases.
Introduction to Scientific Computing at Wright Lab, led by Thomas Langford, will cover:
In-house computing resources
YCRC HPC systems: how-to and why-to
Examples of common work-flows at Wright Lab
Support available at Wright Lab and YCRC
Register here: https://tinyurl.com/wlab-intro-computing
In-person attendance will be capped at 20 people on a first-come, first-served basis, according to the current Yale policies.
Detection of ultra-high-energy (UHE) neutrinos is the key to understanding the most energetic processes in the universe, namely, the sources of UHE cosmic rays which have been detected at earth with energies exceeding 1 Joule per nucleon. As UHE cosmic messengers, neutrinos are unparalleled for their ability to travel from source to Earth. Unfortunately, however, they are very difficult to detect, owing to their low flux and small interaction cross section.
The XENON Dark Matter Project uses xenon dual-phase time projection chambers for direct Dark Matter detection. With steadily growing target masses the XENON detectors set world-leading limits on WIMP-nucleon interactions over a broad mass range – most recently with XENON1T. Its unprecedentedly low backgrounds coupled with the tonne-year exposure also enabled searches for rare nuclear processes, the coherent elastic scattering of solar neutrinos and alternative Dark Matter candidates.
Theoretical approaches have always played an important role in biology, dating back to Mendel’s peas. In today’s era of genomics and big data in biology, statistical and computational tools are even more vital for biologists seeking to infer causation in living systems. To illustrate the range of methods, from modelling to machine learning, and how they contribute to understanding biological mechanisms, Dr. Teichmann will pick examples from some of the core problems her lab has been investigating as case studies.
