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Robust navigation is both critical for survival and dauntingly complex: Think of the speed and agility of an airborne fly. A multidisciplinary team of researchers led by Itai Cohen, professor of physics in the College of Arts and Sciences, will use the fruit fly, Drosophila melanogaster, to study how the brain forms a coherent representation from multisensory information, corrects for errors from perturbations and generates robust behaviors.
“Measuring the position of a quantum particle changes its momentum and vice versa. Similarly, for qubits there are quantities which change one another when they are measured. We find that certain random sequences of these incompatible measurements lead to the formation of a quantum spin-glass,” said Erich Mueller, professor of physics in the College of Arts and Sciences (A&S). “One implication of our work is that some types of information are automatically protected in quantum algorithms which share the features of our model.”
Applications for the Kavli 2023 Experimental Postdoctoral Fellowships are now open! The deadline is October 14th, 2023.
In numerous strange metals, the characteristic time between electron collisions, with each other and against anything that they encounter in their path, is set by the Planck’s constant and the temperature, said Debanjan Chowdhury, assistant professor of physics in the College of Arts and Sciences and a co-author of the paper. A vast majority of the known high-temperature superconductors, when heated above their superconducting temperature, exhibit this property. This is why it has been believed for a while that the clue to understanding the origin of high-temperature superconductivity lies in understanding the common thread across these materials that leads to this universal Planckian time scale.
Applications for the Kavli 2023 Theory Postdoctoral Fellowships are now open! The deadline is September 29th, 2023.
If “femininity” and “physicist” cannot coexist even in Barbieland, how are we ever to support their coexistence in the real world, Natasha Holmes asks.
A Cornell research team has developed a new way to design complex microscale machines, one that draws inspiration from the operation of proteins and hummingbird beaks. The group’s paper, “Bifurcation Instructed Design of Multistate Machines,” published Aug. 14 in Proceedings of the National Academy of Sciences. The lead author is Itay Griniasty, a Schmidt AI postdoctoral fellow in the lab of Itai Cohen, professor of physics in the College of Arts and Sciences.
Social phenomena occur when many individuals interact. Societies develop characters that depend on demographics, population density, and the environment. In the real Quantum Realm (as opposed to that of the Marvel movies), electrons form societies whose character depends on the interaction among constituents and the effect of their environment. The characteristics of electron communities manifest through material properties. While human activities can be easily surveilled, the fundamental laws of quantum mechanics, the uncertainty principle, forbids complete surveillance of electrons. In this talk, Kim discusses how we observe and simulate the fundamentally mystical life of electrons to understand and predict the characters of various electron societies in the real quantum realm. Kim also talks about how AI tools can help in this challenging endeavor.
Cornell researchers used magnetic imaging to obtain the first direct visualization of how electrons flow in quantum anomalous Hall insulators, and by doing so they discovered the transport current moves through the interior of the material.
Like light switches, transistors control the flow of electric currents. Transistors are the fundamental building blocks of any computing device, from smartphones to the computers in cars. According to Phuong Nguyen, a PhD candidate under the direction of Kin Fai Mak, Physics, and Jie Shan, Applied Engineering and Physics, we could possibly fit billions or even trillions more transistors into a device, creating a computer that is ultrafast and consumes less energy. The key: two-dimensional materials.