{"data":[{"archive":{"checksum":"effb69b22da527381d4d86e9a9ecaffa","checksumType":"MD5","creator":"dd7b509482ad0a11773b217cbbcdf32f","downloadUrl":"https://wuedata.uni-wuerzburg.de/radar/api/datasets/uc9jnzra45h4huxz/download","size":7083326976,"utcCreated":"2026-10-12T13:45:01.755035493Z"},"createdDate":"2026-09-28T08:31:21.429012301Z","descriptiveMetadata":{"additionalTitles":{"additionalTitle":[{"additionalTitleType":"SUBTITLE","value":"Terrain Slope of Bavaria at 5 m Spatial Resolution Derived from a Non-Hydrologically Conditioned DGM5"}]},"alternateIdentifiers":null,"contributors":null,"creators":{"creator":[{"creatorAffiliation":{"affiliationIdentifier":"https://ror.org/00fbnyb24","affiliationIdentifierScheme":"ROR","schemeURI":"https://ror.org/","value":"University of Würzburg"},"creatorName":"Schönbrodt-Stitt, Sarah","familyName":"Schönbrodt-Stitt","givenName":"Sarah","nameIdentifier":[{"nameIdentifierScheme":"ORCID","schemeURI":"http://orcid.org/","value":"0000-0002-7279-6242"}]},{"creatorAffiliation":{"affiliationIdentifier":"https://ror.org/00fbnyb24","affiliationIdentifierScheme":"ROR","schemeURI":"https://ror.org/","value":"University of Würzburg"},"creatorName":"Fäth, Julian","familyName":"Fäth","givenName":"Julian","nameIdentifier":[{"nameIdentifierScheme":"ORCID","schemeURI":"http://orcid.org/","value":"0000-0002-5029-9501"}]},{"creatorAffiliation":{"affiliationIdentifier":"https://ror.org/00fbnyb24","affiliationIdentifierScheme":"ROR","schemeURI":"https://ror.org/","value":"University of Würzburg"},"creatorName":"Ullmann, Tobias","familyName":"Ullmann","givenName":"Tobias","nameIdentifier":[{"nameIdentifierScheme":"ORCID","schemeURI":"http://orcid.org/","value":"0000-0002-6626-3052"}]}]},"dataSources":{"dataSource":[{"dataSourceDetail":"OTHER","value":"Digital Terrain Model of Bavaria (DGM5), 5 m spatial resolution, provided by the Bavarian Agency for Digitisation, High-Speed Internet and Surveying (LDBV), Bavarian Surveying Administration, licensed under CC BY 4.0."}]},"descriptions":{"description":[{"descriptionType":"ABSTRACT","value":"The map of terrain slope is based on the Digital Terrain Model of Bavaria with a spatial resolution of 5 m (DGM5) and characterizes the inclination of the actual terrain surface. Terrain slope was calculated\naccording to Horn (1981), considering the eight immediately adjacent raster cells, and is expressed in degrees (°). The method determines local terrain inclination based on elevation differences within a\n3 × 3 cell neighborhood. The DGM5 was used in its original terrain geometry. Consequently, both natural and anthropogenic terrain features, such as embankments, dams, or cuttings, may influence the derived slope values. \nThe dataset provides a comprehensive description of topographic conditions and enables the spatial differentiation of terrain areas with different degrees of inclination."},{"descriptionType":"TECHNICAL_INFO","value":"This dataset provides a Bavaria-wide representation of terrain slope derived from the Digital Terrain Model of Bavaria (DGM5) at 5 m spatial resolution.\nTerrain slope describes the local inclination of the terrain surface relative to the horizontal plane. It was calculated according to Horn (1981), using elevation differences within a 3 × 3 raster-cell neighbourhood comprising the eight cells immediately adjacent to each central raster cell.\nSlope is expressed in degrees (°), with 0° representing a horizontal terrain surface and increasing values indicating increasing terrain steepness. The theoretical range extends from 0° to 90°.\nThe DGM5 used as input is a preprocessed digital terrain model. No additional hydrological conditioning was applied prior to the calculation of terrain slope. In particular, the terrain was not modified specifically to enforce hydrological connectivity or drainage patterns for the purpose of this analysis.\nConsequently, the resulting slope values characterize the local inclination of the terrain surface represented in the DGM5 rather than a hydrologically conditioned terrain surface. Terrain structures represented in the DGM5, including anthropogenic features such as embankments, dams, cuttings, or other artificial modifications of the terrain, may therefore influence the calculated slope values.\nThe dataset provides a spatially comprehensive characterization of terrain inclination across Bavaria and enables the spatial differentiation of areas with different degrees of terrain steepness. It can support agricultural, forestry, ecological, climatological, geomorphological, landscape, and other environmental analyses.\n\nINPUT DATA\nDigital Terrain Model of Bavaria (DGM5)\n•\tSpatial resolution: 5 m\n•\tData provider: Bavarian Surveying Administration / Bayerische Vermessungsverwaltung\n•\tProduct: Digitales Geländemodell 5 m (DGM5)\n•\tLicense: CC BY 4.0\n•\tSource: Open Data Bayern\n\nDATASET SPECIFICATIONS\n•\tSpatial extent: Bavaria, Germany\n•\tSpatial resolution: 5 m\n•\tUnit: degrees (°)\n•\tVariable: terrain slope\n•\tData type: raster\n•\tFile format: GeoTIFF / Cloud Optimized GeoTIFF (COG)\n•\tCoordinate reference system: ETRS89 / UTM zone 32N\n•\tEPSG: 25832\n\nPROCESSING\nInput: Digital Terrain Model of Bavaria (DGM5), 5 m spatial resolution.\nMethod: Terrain slope was calculated according to Horn (1981).\n\nThe local inclination of the terrain surface is derived from elevation differences within a 3 × 3 raster-cell neighbourhood. The eight cells immediately adjacent to each central raster cell are considered in the calculation.\nThe resulting slope represents the magnitude of the local terrain gradient and is expressed as an inclination angle in degrees relative to the horizontal plane.\n\nProcessing environment\n•\tSoftware environment: R\n•\tPackage: terra\n•\tFunction: terrain()\n•\tProcessing platform: terrabyte\n\nThe DGM5 used as input is a preprocessed digital terrain model. No additional hydrological conditioning of the terrain was applied prior to slope calculation.\nThe derived slope values therefore represent the local inclination of the terrain geometry contained in the DGM5 rather than that of a hydrologically conditioned terrain representation. Anthropogenic terrain structures represented in the DGM5 may consequently influence the calculated slope values.\n\nPARAMETER SETTINGS\n•\tFunction: terra::terrain()\n•\tVariable: v = \"slope\"\n•\tOutput unit: unit = \"degrees\"\n•\tNeighbours: neighbors = 8\n•\tNeighbourhood: 3 × 3 raster cells\n•\tRaster cell size: 5 m\n•\tAlgorithm: Horn (1981)\n\nThe slope calculation is based on elevation differences within the immediate 3 × 3 cell neighborhood. At a raster resolution of 5 m, the calculated values therefore characterize local terrain inclination at the spatial scale represented by the DGM5.\n\nVALUE INTERPRETATION\nSlope values represent the angle of inclination of the terrain surface relative to the horizontal plane: 0° -  horizontal terrain surface,  Increasing values: increasing terrain steepness, 90° -  theoretical maximum corresponding to a vertical surface\n\nThe theoretical range of the dataset is therefore 0° to 90°.\nSlope expressed in degrees should not be confused with slope expressed as percent gradient. Conversion between degrees and percent slope is nonlinear.\n\nINTERPRETATION AND LIMITATIONS\nThe dataset represents the local geometric inclination of the terrain surface represented in the DGM5 and should be interpreted accordingly.\nIn particular:\n•\tThe slope calculation is derived from the terrain geometry represented in the DGM5.\n•\tThe input DGM5 is a preprocessed digital terrain model.\n•\tNo additional hydrological conditioning was performed specifically for the slope calculation.\n•\tThe dataset therefore does not represent slope derived from a hydrologically conditioned terrain model.\n•\tAnthropogenic terrain structures represented in the DGM5, including embankments, dams, cuttings, and similar features, may influence local slope values.\n•\tSlope is calculated locally from the immediate 3 × 3 raster-cell neighbourhood and therefore reflects terrain inclination at the spatial scale represented by the 5 m DGM5.\n•\tLocal slope values depend on the spatial resolution and properties of the underlying elevation model and should therefore not be interpreted independently of the 5 m raster resolution.\n•\tThe dataset describes terrain geometry and does not by itself provide information on hydrological connectivity, surface runoff, erosion processes, or currently active geomorphological processes.\n\nRECOMMENDED USE\nThe dataset can be used as a terrain-related spatial variable in regional and Bavaria-wide analyses, such as characterization of terrain steepness and topographic conditions, agricultural and forestry analyses,  and ecological and biodiversity modelling.\nSlope can be an important terrain-related input variable for analyses of runoff, erosion, soil moisture, or other hydrological and geomorphological processes. However, the slope dataset itself does not represent these processes or hydrological connectivity.\nFor applications requiring explicit representation of surface runoff, drainage networks, flow accumulation, or hydrological connectivity, hydrologically conditioned elevation data and dedicated hydrological terrain derivatives should be used instead.\n\nREFERENCE\nHorn, B. K. P. (1981). Hill shading and the reflectance map. Proceedings of the IEEE, 69(1), 14–47.\n\nDATA SOURCE\nDigitales Geländemodell 5 m (DGM5), Bavarian Surveying Administration / Bayerische Vermessungsverwaltung, Open Data Bayern, licensed under CC BY 4.0."}]},"fundingReferences":{"fundingReference":[{"awardNumber":"EO4CAM","awardTitle":"Earth Observation Laboratory for Climate Adaptation and Mitigation","awardURI":"https://eo4cam.de","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/00rspzk45"},"funderName":"Bavarian Ministry of Economic Affairs and Media, Energy and Technology"}]},"geoLocations":{"geoLocation":[{"geoLocationBox":{"northEastPoint":{"latitude":50.564,"longitude":13.909},"southWestPoint":{"latitude":47.248,"longitude":8.945}},"geoLocationCountry":"GERMANY","geoLocationPoint":null,"geoLocationRegion":"Bayern"}]},"identifier":{"identifierType":"DOI","value":"10.58160/uc9jnzra45h4huxz"},"keywords":{"keyword":[{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Terrain Slope","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Slope","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Digital Terrain Model","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"DGM","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"DGM5","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Terrain Analysis","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Topography","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Terrain Inclination","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Terrain","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Bavaria","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Germany","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"R","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"terra","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Geospatial Data","valueURI":null}]},"language":"ENG","processing":{"dataProcessing":["The dataset was derived from the Digital Terrain Model of Bavaria (DGM5) at 5 m spatial resolution. Terrain slope was calculated according to Horn (1981) using the terrain() function of the terra package in R. The calculation considered eight neighboring raster cells within a 3 × 3 cell neighborhood. Slope values were calculated in degrees (°). The DGM5 was used in its original terrain geometry without modification prior to calculation. Processing was performed on the terrabyte platform."]},"productionYear":"2026","publicationYear":"2026","publishers":{"publisher":[{"nameIdentifier":"https://ror.org/00fbnyb24","nameIdentifierScheme":"ROR","schemeURI":"https://ror.org/","value":"University of Würzburg"}]},"relatedIdentifiers":null,"relatedInformations":{"relatedInformation":[{"relatedInformationType":null,"value":"Derivation method described in: Horn, B. K. P. (1981). Hill shading and the reflectance map. Proceedings of the IEEE, 69(1), 14–47. DOI: https://doi.org/10.1109/PROC.1981.11918"}]},"resource":{"resourceType":"DATASET","value":""},"rights":{"additionalRights":null,"controlledRights":"CC_BY_4_0_ATTRIBUTION"},"rightsHolders":{"rightsHolder":[{"nameIdentifier":"0000-0002-7279-6242","nameIdentifierScheme":"ORCID","schemeURI":"https://orcid.org/","value":"Schönbrodt-Stitt, Sarah"},{"nameIdentifier":"0000-0002-5029-9501","nameIdentifierScheme":"ORCID","schemeURI":"https://orcid.org/","value":"Fäth, Julian"},{"nameIdentifier":"0000-0002-6626-3052","nameIdentifierScheme":"ORCID","schemeURI":"https://orcid.org/","value":"Ulmann, Tobias"}]},"software":{"softwareType":[{"alternativeSoftwareName":[],"softwareName":[{"softwareVersion":"package \"terra\", function: terrain()","value":"R"}],"type":"RESOURCE_PROCESSING"}]},"subjectAreas":{"subjectArea":[{"additionalSubjectAreaName":null,"controlledSubjectAreaName":"GEOGRAPHY"},{"additionalSubjectAreaName":"Remote 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Here we report on the observation of a spin spiral state at the Gd(0001) surface. Spinpolarized scanning tunneling microscopy images show striped regions with a periodicity of about 2 nm. These stripes rearrange upon application of an external magnetic field, thereby unambiguously confirming their magnetic origin. Density functional theory calculations explain that competing exchange interactions in the surface layer of Gd(0001) together with a magnetovolume fine-tuning of the exchange interaction to the next Gd layer favor a chiral 2 nm conical spin spiral at the surface, arising as a general behavior of the Gd monolayer."},{"descriptionType":"OTHER","value":"Please read the \"README.txt\" file for further information."},{"descriptionType":"OTHER","value":"We acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), S. B. through SFB 1238 Project No. 277146847 (project C01), M. B. through Project No. 510676484 (GZ: BO 1468/29-1), and under Germany’s Excellence Strategy through the Würzburg– Dresden Cluster of Excellence on Complexity and Topology in Quantum Matter—ct.qmat (EXC 2147, Project No. 390858490). G. 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Im Forst befinden sich auch die Stationen in Oberrimbach (Steigerwald) mit Braunerden aus Sandsteinkeuper und in Willmars (Rhön) mit Braunerden aus Buntsandstein. In den Messzeitraum fiel die dreijährige Dürre von 2018 bis 2020, das Jahr 2021 mit einem durchschnittlichen Witterungsverlauf und das Dürrejahr 2022. \nDas Langzeitmonitoring wurde im Rahmen der zur Dissertation „Auswirkungen des Klimawandels auf charakteristische Böden in Unterfranken unter Berücksichtigung bodenhydrologischer Monitoringdaten (2018 bis 2022)“ von Julian Krause durchgeführt. 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The observation period included the three-year drought from 2018 to 2020, the year 2021 with an average weather pattern and the drought year 2022.\nThe long-term monitoring was carried out as part of the dissertation “Impact of climate change on characteristic soils in Lower Franconia with consideration of soil hydrological monitoring data (2018 to 2022)” by Julian Krause. 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In this study we present the results of a spin-polarized scanning tunneling microscopy study performed on epitaxial Tb(0001) films grown on W(110). The magnetic contrast was obtained by dipping the tip directly into the Tb film, thereby creating magnetic in-plane sensitive tips. Our differential conductance dI/dU data reveal contrast levels which are in agreement with the tunneling magnetoresistance effect between an in-plane sensitive scanning tunneling microscopy tip and surface domains magnetized along basal <10-10> directions. Film-thickness-dependent studies reveal a close correlation between the structural and magnetic properties of the film. Four types of crystal defects are identified which contribute to the pinning of magnetic domains: (i) surface step edges, (ii) step dislocations, (iii) structural boundaries between differently stacked terbium (Tb) patches, and (iv) screw dislocations resulting from glide processes. As the thickness of the Tb film increases, the defect density diminishes, leading to the formation of larger domains. A detailed analysis of the domain walls leads to the conclusion that they are of Néel type and exhibit a width of w60 ≈ 1.4 nm, w120 ≈ 2.5 nm, and w180 ≈ 3 nm for 60°, 120°, and 180° domain walls, respectively."},{"descriptionType":"OTHER","value":"We acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through Project No. 510676484 (GZ: BO 1468/29-1) and under Germany’s Excellence Strategy through the Würzburg– Dresden Cluster of Excellence on Complexity and Topology in Quantum Matter, ct.qmat (EXC 2147, Project No. 390858490)"},{"descriptionType":"OTHER","value":"Please read the \"README.txt\" file for further information."}]},"fundingReferences":{"fundingReference":[{"awardNumber":"510676484","awardTitle":"Spinstruktur dünner Seltenerdmetall-Filme","awardURI":"https://gepris.dfg.de/gepris/projekt/510676484","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/018mejw64"},"funderName":"Deutsche 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We compute the current profiles directly from Quantum Monte Carlo (QMC) simulations of the microscopic tight-binding model with long-range Coulomb interactions. This allows us to get results in a clean environment with all scattering channels being controlled by the parameters of the microscopic Hamiltonian and exact results delivered by QMC without further approximations. As a consequence, we can trace the emergence of continuous hy- drodynamics in the initially discrete lattice system. Special attention is paid to the emergence of macroscopic boundary conditions from microscopic details of the sample’s edges. Another important peculiarity is the decoupling of the charge current from the momentum flow in the Lorentz symmet- ric system, since the electrons and holes propagate in opposite directions with equal distribution functions. Using Boltzmann transport theory, we derive Navier-Stokes-type equations directly for the charge current, thus eliminating the need for any mechanism coupling the velocity field and charge current to explain the experimentally observed hydrodynamic flow profiles in graphene at half-filling. In this framework, the current diffusion coefficient replaces viscosity. QMC current profiles and the extracted temperature dependence for the current diffusion coefficient are in good agreement with the aforementioned theory, thus supporting our kinetic description of hydrodynamic currents in charge neutral graphene."},{"descriptionType":"OTHER","value":"MU (AR) thanks the DFG for financial support un- der the projects UL444/2-1, Project number 495044360 (AS120/19-1, Project number 530989922). FFA ac- knowledges financial support from the DFG through the W¨urzburg-Dresden Cluster of Excellence on Complex- ity and Topology in Quantum Matter - ct.qmat (EXC 2147, Project No. 390858490) as well as the SFB 1170 on Topological and Correlated Electronics at Surfaces and Interfaces (Project No. 258499086). KP acknowledges funding by the Deutsche Forschungsgemeinschaft (DFG) via the Emmy Noether Programme (Quantum Design grant, ME4844/1, project- id 327807255), project A04 of the Collaborative Research Center SFB 1143 (project- id 247310070), and the Cluster of Excellence on Com- plexity and Topology in Quantum Matter ct.qmat (EXC 2147, project-id 390858490). We gratefully acknowledge the Gauss Centre for Supercomputing e.V. (www.gauss- centre.eu) for funding this project by providing com- puting time for the computation of the current-current correlator on the GCS Supercomputer SUPERMUC- NG at the Leibniz Supercomputing Centre (www.lrz.de, project number pn73xu), as well as the scientific support and HPC resources provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universit¨at Erlangen-N¨urnberg (FAU) under the NHR project b133ae to carry out the SAC analysis. NHR funding is provided by federal and Bavarian state authorities. NHR@FAU hardware is par- tially funded by the German Research Foundation (DFG) – 440719683. JUWELS supercomputer was used for the calculation of E tensor. The numerical calcula- tions were carried out with the Algorithms for Lattice Fermions (ALF) library."}]},"fundingReferences":{"fundingReference":[{"awardNumber":"390858490","awardTitle":"EXC 2147:  Complexity and Topology in Quantum Matter (CT.QMAT)","awardURI":"https://gepris.dfg.de/gepris/projekt/390858490","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/00kkpv737"},"funderName":"Complexity and Topology in Quantum Matter"},{"awardNumber":"495044360","awardTitle":"Numerical challenges in Quantum Monte Carlo simulations in condensed matter physics","awardURI":"https://gepris.dfg.de/gepris/projekt/495044360","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/018mejw64"},"funderName":"Deutsche Forschungsgemeinschaft"},{"awardNumber":"530989922","awardTitle":"Numerical simulations of topological and exotic states of quantum matter","awardURI":"https://gepris.dfg.de/gepris/projekt/530989922","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/018mejw64"},"funderName":"Deutsche Forschungsgemeinschaft"},{"awardNumber":"247310070","awardTitle":"SFB 1143:  Correlated Magnetism: From Frustration to Topology","awardURI":"https://gepris.dfg.de/gepris/projekt/247310070","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/018mejw64"},"funderName":"Deutsche Forschungsgemeinschaft"},{"awardNumber":"327807255","awardTitle":"Quantum design: understanding, creating, and controlling novel states of matter","awardURI":"https://gepris.dfg.de/gepris/projekt/327807255","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/018mejw64"},"funderName":"Deutsche Forschungsgemeinschaft"}]},"geoLocations":null,"identifier":{"identifierType":"DOI","value":"10.58160/2epkdq7ctxtebcp2"},"keywords":{"keyword":[{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Graphene","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Electronic transport","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Hydrodynamics","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Quantum Monte Carlo","valueURI":null},{"classificationCode":null,"keywordScheme":"OTHER","ontologyId":null,"ontologyURI":null,"schemeURI":null,"value":"Boltzmann theory","valueURI":null}]},"language":"ENG","processing":null,"productionYear":"2024","publicationYear":"2024","publishers":{"publisher":[{"nameIdentifier":"https://ror.org/00fbnyb24","nameIdentifierScheme":"ROR","schemeURI":"https://ror.org/","value":"University of Würzburg"}]},"relatedIdentifiers":{"relatedIdentifier":[{"relatedIdentifierType":"DOI","relationType":"IS_SUPPLEMENT_TO","value":"10.48550/arXiv.2411.13273"}]},"relatedInformations":null,"resource":{"resourceType":"DATASET","value":""},"rights":{"additionalRights":null,"controlledRights":"CC_BY_4_0_ATTRIBUTION"},"rightsHolders":{"rightsHolder":[{"nameIdentifier":"0009-0000-0245-4186","nameIdentifierScheme":"ORCID","schemeURI":"https://orcid.org/","value":"Reingruber, Adrien"},{"nameIdentifier":"0000-0002-3302-9243","nameIdentifierScheme":"ORCID","schemeURI":"https://orcid.org/","value":"Assaad, Fakher"}]},"software":{"softwareType":[{"alternativeSoftwareName":[],"softwareName":[{"softwareVersion":"2.4","value":"Algorthims for Lattice Fermions (ALF) - 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This decoupling is known to have a saddle-point structure that shows a remarkable regularity: The field configuration at each saddle point can be understood in terms of a set of elementary field configurations localized in space and imaginary time which we coin instantons. The interaction between instantons is short ranged. Here, we formulate a classical partition function for the instanton gas that has predictive power. For a given set of physical parameters, we can predict the distribution of instantons and show that the instanton number is sharply defined in the thermodynamic limit, thereby defining a unique dominant saddle point. Decoupling in the charge channel conserves SU(2) spin symmetry for each field configurations. Hence, the instanton approach provides an SU(2) spin-symmetric approximation to the Hubbard model. It fails, however, to capture the magnetic transition inherent to the Hubbard model on the honeycomb lattice despite being able to describe local moment formation. In fact, the instanton itself corresponds to local moment formation and concomitant short-ranged antiferromagnetic correlations. This aspect is also seen in the single particle spectral function that shows clear signs of the upper and lower Hubbard bands. Our instanton approach bears remarkable similarities to local dynamical approaches, such as dynamical mean-field theory, in the sense that it has the unique property of allowing for local moment formation without breaking the SU(2) spin symmetry. In contrast to local approaches, it captures short-ranged magnetic fluctuations. Furthermore, it also offers possibilities for systematic improvements by taking into account fluctuations around the dominant saddle point. Finally, we show that the saddle point structure depends upon the choice of lattice geometry. For the square lattice at half filling, the saddle-point structure reflects the itinerant to localized nature of the magnetism as a function of the coupling strength. The implications of our results for Lefschetz thimble approaches to alleviate the sign problem are also discussed."},{"descriptionType":"TECHNICAL_INFO","value":"Please read the ReadMe.txt file in the provided .zip file for technical details about data processing and plotting."},{"descriptionType":"OTHER","value":"Funding was provided partially by Cluster of Excellence ct-qmat (Complexity and Topology in Quantum Matter)"}]},"fundingReferences":{"fundingReference":[{"awardNumber":"390858490","awardTitle":"EXC 2147: Complexity and Topology in Quantum Matter (CT.QMAT)","awardURI":"https://gepris.dfg.de/gepris/projekt/390858490","funderIdentifier":{"schemeURI":"https://ror.org/","type":"ROR","value":"https://ror.org/00kkpv737"},"funderName":"Complexity and Topology in Quantum Matter"},{"awardNumber":"495044360","awardTitle":"Numerical challenges in Quantum Monte Carlo simulations in condensed matter 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Almost all of the gold there occurs in the 2.90 – 2.79 Ga Central Rand Group, whereas the underlying 2.95 - 2.91 Ga West Rand Group, despite similar sedimentology, is essentially barren. This has been explained by differing degrees of chemical weathering, with intense weathering in Central Rand Group times having facilitated gold leaching from the Archaean hinterland. However, the drivers of this climatic change remain unsolved. To investigate this, we performed 140 simulations using the Planet Simulator, an Earth system model of intermediate complexity. We systematically assessed the effects of varying land distributions (diagonal, central, polar), land surface fractions (8–28 %), atmospheric CO₂-equivalent concentrations (3–30 %), and surface albedo (0.15–0.30). In addition to the expected strong dependence of global mean temperature on atmospheric greenhouse gas concentration, our results show reduced seasonality at higher atm. CO₂-equivalents. Increasing land area generally leads to cooling, except at low CO2-equivalent concentrations (3-5 %) and low albedo (<0.2). When land exceeds ~13 % of total Earth’s surface, it starts to have a pronounced effect on global climate. Among the spatial configurations, diagonal land distribution shows the highest climate sensitivity. The climatic shift around 2.9 Ga may be linked to emergence of extensive low-albedo (<0.2) surfaces (e.g., mafic/ultramafic rocks) and/or to the latitudinal drift of the Kaapvaal Craton into a more radiatively sensitive zone.\n\nThis dataset contains global 2-meter above the ground temperature (tas) at a horizontal resolution of T21 (64 x 32 grid points). 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