Division Scientific Computing, Theory and DataSCD
By July 1, 2021, the new research division "Scientific Computing, Theory and Data" has been established at PSI.
Its goals are:
- to provide modeling know-how and computing resources for the science, engineering, and accelerator program at PSI
- to provide conceptual and practical input to new science initiatives at PSI like SwissFEL
- to link new opportunities of computational materials modeling (NCCR MARVEL) and data science (SDSC) to PSI’s unique large research facilities
- to establish an international role model for the data chain at large research facilities
Highlights & News
Scientific Highlights
Rezeptorproteinen beim Verbiegen zuschauen
G-Protein-gekoppelte Rezeptoren vermitteln unzählige Prozesse im Körper. Im Interview erzählt PSI-Forscher Ramon Guixà, wie er die Rezeptormoleküle auf dem Bildschirm lebendig werden lässt.
Neuer Bauplan für stabilere Quantencomputer
PSI-Forscher haben gezeigt, wie sich schnellere und genauere Quantenbits erschaffen liessen. Die zentralen Elemente sind dabei magnetische Atome aus der Klasse der sogenannten Seltenen Erden, die gezielt in das Kristallgitter eines Materials eingebracht würden.
Fellow Award for Dr. Mantzaras
The prestigious Fellow Award “Fellow of The Combustion Institute” was allotted to Dr. Mantzaras for “Pioneering Experimental and Modeling Research in Hetero-/Homogeneous and Catalytic Combustion”. The combustion activities at LSM emphasize on non-intrusive laser-based measurements in a high-pressure optically accessible catalytic reactor, while the modeling activities encompass advanced multidimensional numerical simulations and theoretical work based on activation energy asymptotics.
Benefit of random testing
With the imminent relaxation of socio-economic restrictions, it becomes vital to assess its effect on the prevalence of acute infections within the population, as rapidly as possible. Currently available monitoring instruments for the COVID-19 pandemic have an inherent time delay of about 14 days, as they rely on confirmed infections, hospitalizations, and death numbers. These methods give Reff(t) (the number of infections caused by a single infected person), but their delay is a significant disadvantage when restrictions are released. If after relaxation, Reff(t) rises above 1, one will not be able to react adequately before two weeks have passed during which time the prevalence could significantly rise. Here, we propose the use of random testing to shorten this reaction time, by obtaining direct and modeling dependent information on Reff(t). Through random testing of between 2500 and 20000 people per day, we find that over periods significantly shorter than two weeks, it becomes possible to detect a dangerous increase in Reff with reasonable confidence.
Die Simulation: Das dritte Standbein der Wissenschaft
Forschenden des PSI simulieren und modellieren sowohl Grossforschungsanlagen als auch Experimente, zum Beispiel in den Material- und Biowissenschaften. Wie sie dabei vorgehen erklärt Andreas Adelmann, Leiter des PSI Labors für Simulation und Modellierung.