Webpages tagged with «Particle physics»
Insights is a 4-year Marie Sklodowska-Curie Innovative Training Networks project for the career development of 12 Early Stage Researchers (ESRs) at 10 partner institutions across Europe. INSIGHTS is focused on applying the latest advances in statistics, and in particular machine learning, to particle physics.
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Linear Colliders are candidates for the next generation of particle colliders for high energy physics. These machines will allow particle physics to explore a new energy region in the multi-TeV range beyond the capabilities of today's particle accelerators. They will provide significant fundamental physics information complementary to the LHC, as a result of a unique combination of high energy and experimental precision.
The PLUMBIN' project is a cross-disciplinary collaboration between high-energy physics and statistics aimed at making powerful computational tools for exploring the fundamental constituents of the Universe.
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We study the universe at the smallest distance scales (corresponding to the highest energy scales). After the Higgs boson was discovered at CERN in 2012, one of the hottest goals of our research is to reveal the nature of dark matter.
Modern science usually provides both copious amounts of data and complicated models for the part of reality it is trying to describe. Often there is even so much data, and the models so complicated, that it becomes difficult to make full use of the data in deciding which models best describe the world around us, and finding their properties. The main goal of the GAMBIT project is to develop a software tool to help physicists do just that.
![Image may contain: Font, Parallel, Terrestrial plant, Slope.](https://www.mn.uio.no/fysikk/english/research/projects/ppp/ppp_slide.png?alt=listing)
The project "Pandemics, Particles and Parameter (s)paces" is a cross-disciplinary collaboration between theoretical physics at the University of Oslo and the Norwegian Institute of Public Health (NIPH/FHI) aimed at developing software to meet the United Nations Sustainable Development Goal 3, in particular Target 3.d: "Strengthen the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks."
The Z-path first started as educational material for high school students to work with data collected by the ATLAS detector at CERN's Large Hadron Collider (LHC). The Z-path and some of the accompanying tools have been developed at the University of Oslo.
Since May 2017 ZPATH receives funding from the Olav Thon Foundation as a "Student active research project".