Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Measurements of the jet energy calibration and transverse momentum resolution in CMS are presented, performed with a data sample collected in proton-proton collisions at a centre-of-mass energy of 7TeV, corresponding to an integrated luminosity of 36pb−1. The transverse momentum balance in dijet and γ/Z+jets events is used to measure the jet energy response in the CMS detector, as well as the transverse momentum resolution. The results are presented for three different methods to reconstruct jets: a calorimeter-based approach, the ``Jet-Plus-Track'' approach, which improves the measurement of calorimeter jets by exploiting the associated tracks, and the ``Particle Flow'' approach, which attempts to reconstruct individually each particle in the event, prior to the jet clustering, based on information from all relevant subdetectors

/pdf/determination-of-jet-energy-calibration-and-transverse-2pz940qkm4.pdf

Determination of jet energy calibration and transverse momentum resolution in CMS

The area of a jet is a measure of its susceptibility to radiation, like pileup or underlying event (UE), that on average, in the jet’s neighbourhood, is uniform in rapidity and azimuth. In this article we establish a theoretical grounding for the discussion of jet areas, introducing two main definitions, passive and active areas, which respectively characterise the sensitivity to pointlike or diffuse pileup and UE radiation. We investigate the properties of jet areas for three standard jet algorithms, kt, Cambridge/Aachen and SISCone. Passive areas for single-particle jets are equal to the naive geometrical expectation πR 2 , but acquire an anomalous dimension at higher orders in the coupling, calculated here at leading order. The more physically relevant active areas differ from πR 2 even for single-particle jets, substantially so in the case of the cone algorithms like SISCone with a Tevatron Run-II split–merge procedure. We compare our results with direct measures of areas in parton-shower Monte Carlo simulations and find good agreement with the main features of the analytical predictions. We furthermore justify the use of jet areas to subtract the contamination from pileup.

/pdf/the-catchment-area-of-jets-12ebn1u1fu.pdf

The Catchment Area of Jets

http://home.thep.lu.se/~torbjorn/preprints/lutp1028.pdf

General-purpose event generators for LHC physics

Improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 fb^(-1) collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented. The corrections as a function of pseudorapidity η and transverse momentum p_T are extracted from data and simulated events combining several channels and methods. They account successively for the effects of pileup, uniformity of the detector response, and residual data-simulation jet energy scale differences. Further corrections, depending on the jet flavor and distance parameter (jet size) R, are also presented. The jet energy resolution is measured in data and simulated events and is studied as a function of pileup, jet size, and jet flavor. Typical jet energy resolutions at the central rapidities are 15–20% at 30 GeV, about 10% at 100 GeV, and 5% at 1 TeV. The studies exploit events with dijet topology, as well as photon+jet, Z+jet and multijet events. Several new techniques are used to account for the various sources of jet energy scale corrections, and a full set of uncertainties, and their correlations, are provided. The final uncertainties on the jet energy scale are below 3% across the phase space considered by most analyses (p_T > 30 GeV and 0|η| 30 GeV is reached, when excluding the jet flavor uncertainties, which are provided separately for different jet flavors. A new benchmark for jet energy scale determination at hadron colliders is achieved with 0.32% uncertainty for jets with p_T of the order of 165–330 GeV, and |η| < 0.8.

/pdf/jet-energy-scale-and-resolution-in-the-cms-experiment-in-pp-4zu72tdjps.pdf

Jet energy scale and resolution in the CMS experiment in pp collisions at 8 TeV

A precise determination of the energy scale of jets at the Collider Detector at Fermilab at the Tevatron p p ¯ collider is described. Jets are used in many analyses to estimate the energies of partons resulting from the underlying physics process. Several correction factors are developed to estimate the original parton energy from the observed jet energy in the calorimeter. The jet energy response is compared between data and Monte Carlo simulation for various physics processes, and systematic uncertainties on the jet energy scale are determined. For jets with transverse momenta above 50 GeV the jet energy scale is determined with a 3 % systematic uncertainty.

D. Hoffman

Papers

Determination of the jet energy scale at the collider detector at Fermilab