Method for High Accuracy Multiplicity Correlation Measurements

Multiplicity correlation measurements provide insight into the dynamics of high energy collisions. Models describing these collisions need these correlation measurements to tune the strengths of the underlying QCD processes which influence all observables. Detectors, however, often possess limited coverage or reduced efficiency that influence correlation measurements in obscure ways. In this paper, the effects of non-uniform detection acceptance and efficiency on the measurement of multiplicity correlations between two distinct detector regions (termed forward-backward correlations) are derived. An analysis method with such effects built-in is developed and subsequently verified using different event generators. The resulting method accounts for acceptance and efficiency in a model independent manner with high accuracy thereby shedding light on the relative contributions of the underlying processes to particle production.Comment: 28 pages, 13 figures. Updated for having pseudorapidity dependent efficiency gradient

Carbon dioxide balance of subarctic tundra from plot to regional scales

Peer reviewe

The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events

The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m^3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis. In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb--Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.Comment: 55 pages, 82 figure

Methane dynamics in the subarctic tundra : combining stable isotope analyses, plot- and ecosystem-scale flux measurements

Methane (CH4) fluxes were investigated in a subarctic Russian tundra site in a multi-approach study combining plot-scale data, ecosystem-scale eddy covariance (EC) measurements, and a fine-resolution land cover classification scheme for regional upscaling. The flux data as measured by the two independent techniques resulted in a seasonal (May-October 2008) cumulative CH4 emission of 2.4 (EC) and 3.7 gCH(4) m(-2) (manual chambers) for the source area representative of the footprint of the EC instruments. Upon upscaling for the entire study region of 98.6 km(2), the chamber measured flux data yielded a regional flux estimate of 6.7 gCH(4) m(-2) yr(-1). Our upscaling efforts accounted for the large spatial variability in the distribution of the various land cover types (LCTs) predominant at our study site. Wetlands with emissions ranging from 34 to 53 gCH(4) m(-2) yr(-1) were the most dominant CH4-emitting surfaces. Emissions from thermokarst lakes were an order of magnitude lower, while the rest of the landscape (mineral tundra) was a weak sink for atmospheric methane. Vascular plant cover was a key factor in explaining the spatial variability of CH4 emissions among wetland types, as indicated by the positive correlation of emissions with the leaf area index (LAI). As elucidated through a stable isotope analysis, the dominant CH4 release pathway from wetlands to the atmosphere was plant-mediated diffusion through aerenchyma, a process that discriminates against C-13-CH4. The CH4 released to the atmosphere was lighter than that in the surface porewater, and delta C-13 in the emitted CH4 correlated negatively with the vascular plant cover (LAI). The mean value of delta C-13 obtained here for the emitted CH4, 68.2 +/- 2.0 %, is within the range of values from other wetlands, thus reinforcing the use of inverse modelling tools to better constrain the CH4 budget. Based on the IPCC A1B emission scenario, a temperature increase of 6.1 degrees C relative to the present day has been predicted for the European Russian tundra by the end of the 21st Century. A regional warming of this magnitude will have profound effects on the permafrost distribution leading to considerable changes in the regional landscape with a potential for an increase in the areal extent of CH4-emitting wet surfaces.Peer reviewe

The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events

The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis. In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb–Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.publishedVersio

Surface Energy Budgets of Arctic Tundra During Growing Season

This study analyzed summer observations of diurnal and seasonal surface energy budgets across several monitoring sites within the Arctic tundra underlain by permafrost. In these areas, latent and sensible heat fluxes have comparable magnitudes, and ground heat flux enters the subsurface during short summer intervals of the growing period, leading to seasonal thaw. The maximum entropy production (MEP) model was tested as an input and parameter parsimonious model of surface heat fluxes for the simulation of energy budgets of these permafrost‐underlain environments. Using net radiation, surface temperature, and a single parameter characterizing the thermal inertia of the heat exchanging surface, the MEP model estimates latent, sensible, and ground heat fluxes that agree closely with observations at five sites for which detailed flux data are available. The MEP potential evapotranspiration model reproduces estimates of the Penman‐Monteith potential evapotranspiration model that requires at least five input meteorological variables (net radiation, ground heat flux, air temperature, air humidity, and wind speed) and empirical parameters of surface resistance. The potential and challenges of MEP model application in sparsely monitored areas of the Arctic are discussed, highlighting the need for accurate measurements and constraints of ground heat flux.Plain Language SummaryGrowing season latent and sensible heat fluxes are nearly equal over the Arctic permafrost tundra regions. Persistent ground heat flux into the subsurface layer leads to seasonal thaw of the top permafrost layer. The maximum energy production model accurately estimates the latent, sensible, and ground heat flux of the surface energy budget of the Arctic permafrost regions.Key PointThe MEP model is parsimonious and well suited to modeling surface energy budget in data‐sparse permafrost environmentsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/1/jgrd55584.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/2/jgrd55584_am.pd

Influence of seasonality and vegetation type on suburban microclimates

Urbanization is responsible for some of the fastest rates of land-use change around the world, with important consequences for local, regional, and global climate. Vegetation, which represents a significant proportion of many urban and suburban landscapes, can modify climate by altering local exchanges of heat, water vapor, and CO2. To determine how distinct urban forest communities vary in their microclimate effects over time, we measured stand-level leaf area index, soil temperature, infrared surface temperature, and soil water content over a complete growing season at 29 sites representing the five most common vegetation types in a suburban neighborhood of Minneapolis–Saint Paul, Minnesota. We found that seasonal patterns of soil and surface temperatures were controlled more by differences in stand-level leaf area index and tree cover than by plant functional type. Across the growing season, sites with high leaf area index had soil temperatures that were 7°C lower and surface temperatures that were 6°C lower than sites with low leaf area index. Site differences in mid-season soil temperature and turfgrass ground cover were best explained by leaf area index, whereas differences in mid-season surface temperature were best explained by percent tree cover. The significant cooling effects of urban tree canopies on soil temperature imply that seasonal changes in leaf area index may also modulate CO2 efflux from urban soils, a highly temperature-dependent process, and that this should be considered in calculations of total CO2 efflux for urban carbon budgets. Field-based estimates of percent tree cover were found to better predict mid-season leaf area index than satellite-derived estimates and consequently offer an approach to scale up urban biophysical properties