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HIDSS-0002
DASHH: Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter
| Coordinator | Rohringer, Nina ; Rarey, Matthias ; Le Borne, Sabine |
| Grant period | 2019 - 2025 |
| Funding body | Helmholtz Gemeinschaft Deutscher Forschungszentren |
| HGF | |
| Further information: | Description |
| Identifier | G:(DE-HGF)2019_IVF-HIDSS-0002 |
⇧ Impuls- und Vernetzungsfonds ⇧
Note: ‘Data Science’ is the science of extracting knowledge from typically large amounts of data. The increasing level of automatization and the increasing number and resolution of sensors in scientific experiments result in large, heterogeneous and highly complex data collections. Therefore, Data Science is seen as a key technology in modern and future natural sciences. Data intensive research in experimental and theoretical science at the Forschungscampus Hamburg-Bahrenfeld requires beyond off-the-shelf software solutions for data management, processing and analysis. Tailored or even completely new computational data science methods are indispensable. At the same time, the challenges ahead will foster new innovative ideas in computer science and applied mathematics. To develop these methods, scientists have to be highly skilled in the corresponding physics domain and computer science alike. The Data Science in Hamburg – Helmholtz Graduate School for the Structure of Matter (DASHH) will be established to address this highly interdisciplinary need. DASHH bundles competences of scientists with high international reputation in basic research for the structure of matter, computer science and applied mathematics in Hamburg in a new and unique fashion. The graduate school covers data challenges from application fields such as structural biology, particle physics, material science and ultrafast X-ray science. These data challenges have in common that they cannot be addressed with standard computational methods, but require modern data science techniques instead. Several areas from computer science and mathematics play important roles, especially data management and engineering, machine learning and data analytics, signal and image processing, algorithm design, optimization and simulation, software engineering and automation and control systems.All known publications ...
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Preprint
A Review of Techniques for Ageing Detection and Monitoring on Embedded Systems
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Journal Article
Search for high-mass resonances in a final state comprising a gluon and two hadronically decaying W bosons in proton-proton collisions at $ \sqrt{s} $ = 13 TeV
Journal of high energy physics 02(2), 199 (2025) [10.1007/JHEP02(2025)199]
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Measurements of inclusive and differential Higgs boson production cross sections at $\sqrt{\text{s}}=13.6$ TeV in the H → γγ decay channel
Journal of high energy physics 09(9), 70 (2025) [10.1007/JHEP09(2025)070]
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Observation of a pseudoscalar excess at the top quark pair production threshold
Reports on progress in physics 88(8), 087801 - (2025) [10.1088/1361-6633/adf7d3]
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Search for vector-like leptons with long-lived particle decays in the CMS muon system in proton-proton collisions at $\sqrt{\text{s}}$ = 13 TeV
Journal of high energy physics 08(8), 156 (2025) [10.1007/JHEP08(2025)156]
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Probing Gluon Fluctuations in Nuclei with the First Energy-Dependent Measurement of Incoherent J/ψ Photoproduction in Ultraperipheral PbPb Collisions
Physical review letters 135(11), 112301 (2025) [10.1103/w9kp-f8xr]
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Observation of the Charged-Particle Multiplicity Dependence of σψ(2S)/σJ/ψ in p-Pb Collisions at 8.16 TeV
Physical review letters 135(9), 092301 (2025) [10.1103/c9wp-5tq3]
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Journal Article
Search for dark matter produced in association with one or two top quarks in proton-proton collisions at $\sqrt{\text{s}}$= 13 TeV
Journal of high energy physics 08(8), 85 (2025) [10.1007/JHEP08(2025)085]
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Search for heavy neutral resonances decaying to tau lepton pairs in proton-proton collisions at s=13 TeV
Physical review / D 111(11), 112004 (2025) [10.1103/PhysRevD.111.112004]
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Journal Article
Elliptic anisotropy measurement of the f$_0$(980) hadron in proton-lead collisions and evidence for its quark-antiquark composition
Nature Communications 16(1), 7990 (2025) [10.1038/s41467-025-56200-6]
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All known publications ...
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