dataesr/scientific-paragraphs-categorization huggingface dataset:
Analysis scheme The analysis measures the ratio of the charm dimuon cross-section to the inclusive CC cross-section, as a function of the kinematic variables: R µµ (x) ≡ σ µµ σ cc ≃ N µµ (x) N cc (x) , (9) where x = E ν , x B j , √ ŝ and the partonic center of mass energy squared is defined as ŝ = Q 2 (1/x Bj -1). The ratio R µµ provides a large cancellation of all systematic uncertainties affecting both the numerator and the denominator. The ν µ CC events in the data are well reconstructed and have a negligible background. Figure  3  shows good agreement between data and Monte Carlo for the reconstructed kinematic variables in ν µ CC events. The charm dimuon events are determined from the opposite sign dimuons measured in the data after subtracting the background: N (10) The background to the opposite sign dimuon process arises from muonic decays of hadrons -primarily π + and K + mesons -produced in the hadronic shower or by hadrons which punch through to the MCH, thereby being misidentified as muons.
The background events N = N DATA µµ - • N MC µµ + bg /N MC µµ - (11) where the scale factor is given by the ratio of opposite sign to like sign dimuon events originated from background events. In order to reduce the MC statistical uncertainties we generated a total of about 80 × 10 6 ν µ CC events fully reconstructed in FCAL. Figure  4  shows the distributions of the LSDM events in FCAL data and MC. The general agreement is adequate since LSDM events from MC are never directly used in our analysis. Rather, we only use the ratio of OSDM to LSDM background events in MC. This ratio is very sensitive to the details of the fragmentation of the hadronic system, in particular at low momenta. For this reason we cannot rely on the Monte Carlo simulation at the level of precision of a few percent. Instead, since the background scale is determined by the ratio of positively charged to negatively charged mesons inside the hadronic system produced by the fragmentation of partons in DIS events, we measure this ratio as a function of the meson momentum from the NOMAD data originated in the light Drift Chamber target (DCH).
We emphasize that only the use of a low density target embedded inside a magnetic spectrometer in NOMAD has allowed the use of this procedure. Figure  5  shows the measured ratio h + /h -from the DCH data, as well as a comparison with the corresponding MC simulation and the function ω h +. The calibration of the background through the re-weighting procedure is a crucial step in the analysis and allows a substantial improvement in the description of the charm dimuon data by the Monte Carlo simulation. Without the use of data from the low density DCH target it would have not been possible to lower the energy threshold on the secondary muon down to 3 GeV as well as to reduce the systematic uncertainty on the background subtraction. Figure  6  shows the background scale N MC µµ + bg /N MC µµas a function of the main kinematic variables with the re-weighting procedure according to Eq.
(  12 ). Table  2  summarizes signal and background events after each selection cut. After all cuts we retain 20,479 OSDM events in the data, of which 15,344 are genuine charm signal (75%) and 5,135 are background (25%). The final distributions of various kinematic variables for the charm data after background subtraction are given in Figure  7. Event selection for dimuon events in data and MC. The efficiency is normalized to the raw number of MC events generated in the fiducial volume, as in Table  1. All the other MC numbers have been normalized to ν µ CC data after the fiducial volume and leading muon cuts (cut 6), by taking into account the ratio of charm dimuon cross-section to the inclusive CC cross-section, which are calculated analytically. The number of background events is calculated from the LSDM data multiplied by the scale factor obtained after re-weighting for the h + /h -ratio measured in DCH data.
Unfolding procedure The detector smearing and acceptance corrections require an input model for the cross-sections and fragmentation functions. For the inclusive ν µ CC sample the model is largely independent from the NOMAD data. However, for the charm sample the NOMAD dimuon data are eventually used to determine the charm production parameters, which, themselves, are inputs to the experimental acceptance corrections. In our analysis we follow an iterative procedure. The circles give the fully calibrated ratio after re-weighting with the h + /h -ratio measured in DCH data. First, we use an input model which is fully independent from NOMAD data and we verify its consistency with the NOMAD data. After this step we add NOMAD data to the global PDF fits to improve the precision on the charm production parameters.
The electroweak corrections, including one-loop terms, are calculated according to Ref. [39]  within the framework of the parton model. The parameters related to charm production like the mass of the charm quark and the strange quark sea distribution are fixed to the ones extracted from the global PDF fit including NuTeV and CCFR charm dimuon data  [31]  at this stage. This allows a consistency check with a calculation fully independent from NOMAD data. We extract the LEPTO cross-section from the NOMAD MC by simulating 10 9 events with an input flux which is chosen to be inversely proportional to the neutrino energy ∝ 1/E ν. We then bin the events in the (E ν , x Bj , y Bj ) space and smooth the corresponding histograms with an interpolation procedure. Finally, we apply an additional re-weighting to the charm events to take into account the effect of the charm fragmentation, which is described by the Collins-Spiller parameterization  [16]  (see Eq.
Smearing matrix and efficiency correction After re-weighting the MC events to our cross-section model, we unfold the detector response from the measured data for both the inclusive ν µ CC and the charm dimuon events. To this end we first determine the smearing matrix the simulated variables are then slightly adjusted in order to keep the same statistical uncertainty as in the reconstructed variables. Since the R µµ functions vary inside the chosen bins, we need to apply a bin centering correction to the unfolded data. To this purpose we use our model calculation convoluted with the NOMAD flux. For each bin, we find the value of the kinematic variable on the horizontal axis (E ν , x Bj or √ ŝ) for which the analytical function R µµ is equal to the corresponding average value inside the bin.
The value of ε c that we obtain from E531 data is shown in Table  4  and is in good agreement with the value from the NOMAD analysis. We then use both the NOMAD and E531 data in a combined fit and obtain: ε c = 0. 165 ± 0. 025 ± 0. 002  (16)  where the first uncertainty is due to statistics and the second one to systematics (see Section 8). This is our final result, which will be used in the following analysis. It is interesting to note that this result is consistent with the expectation  16]  where k 2 T represents the size of the hadron in momentum space and m c is the charm quark mass (see  Section 9). ε c = k 2 T /m 2 c [ For the sake of comparison with previous measurements, we also performed a fit to the combined NOMAD and E531 data sets with the Peterson parameterization  [41]  of the charm fragmentation function and obtained ε p = 0.
Ratios R µµ The final results for the measured ratio R µµ = σ µµ /σ cc as a function of the kinematic variables E ν , x Bj and √ ŝ are shown in Figures  10 11 12. The curves represent our model calculation based upon the global PDF fit including only NuTeV and CCFR data  [31]. Our new NOMAD measurement is in agreement with the independent predictions obtained without any input from NOMAD data. We evaluate the overall average dimuon production rate in NOMAD by integrating the measured cross-sections after the unfolding and obtain: The solid curve represents a fit to the E531 emulsion data (points with error bars) with the function in Eq. (  17 ), while the dashed-dotted line is the result of our global fit including E531 and NOMAD data (see  Section 9). The horizontal lines show the ±1σ band obtained from a fit to NuTeV and CCFR charm dimuon data assuming a value of B µ independent of energy  [31].
The solid curve represents the result of our QCD fit to NOMAD and E531 data, while the dashed line describes an analytical calculation fully independent from NOMAD data and based upon the cross-section model of Section 6. 1. A comparison with previous measurements  [5, 8, 9]  is also given in the top plot for completeness. Final ratio R µµ between charm dimuon cross-section and inclusive ν µ CC cross-section as a function of the center of mass energy √ ŝ. Both statistical and systematic uncertainties are shown and a bin centering correction was applied. The bottom plot gives the relative statistical (black curve) and systematic (green band) uncertainties in percentage. The solid curve represents the result of our QCD fit to NOMAD and E531 data, while the dashed line describes an analytical calculation fully independent from NOMAD data and based upon the cross-section model of Section 6.
Summary We have presented a new measurement of charm dimuon production using events originated in the Front Calorimeter of the NOMAD experiment (Fe target). Our final data sample has the largest statistics -15,344 charm dimuon events -as well as the lowest energy threshold -E ν ∼ 6 GeV -among the existing measurements. We find the charm dimuon production rate, averaged over the NOMAD flux for Q 2 > 1 GeV 2 /c 2 , to be (5. 15 ± 0. 05 ± 0. 07) × 10 -3 compared to the rate of the inclusive ν µ CC interactions. A key feature of our analysis is the extraction of the whole background predictions from the data themselves, together with a substantial reduction of the minimal energy thresholds on the observed muons with respect to previous measurements. Both achievements have been possible only through the use of a low density and high resolution magnetic spectrometer, allowing a detailed reconstruction of the energy and momentum of individual secondary particles produced in neutrino interactions.
With such a high resolution detector and a control sample of more than 9 × 10 6 reconstructed ν µ CC events, we could keep the total systematic uncertainties -including 17 different sources -on the ratio of charm dimuon to inclusive CC cross-sections at the level of about 2%. This value makes our analysis the most precise measurement of charm dimuon production in neutrino interactions. Finally, we used the new NOMAD data on charm dimuon production to de-termine the charm production parameters and the strange quark sea content of the nucleon within the context of a QCD fit. For the calculation of the charm contributions to the structure functions we use the running mass in the MS scheme and include NLO (NNLO) corrections for the heavy (light) quark QCD coefficients functions. We obtain a mass of the charm quark m c (m c ) = 1.
Acknowledgments We extend our grateful appreciations to the  CERN SPS  staff for the magnificent performance of the neutrino beam. The experiment was supported by the following agencies:  ARC and DIISR of Australia ;  IN2P3  and  CEA of France, BMBF of Germany, INFN of Italy, JINR  and  INR of Russia, FNSRS of Switzerland, DOE ,  NSF , Sloan, and  Cottrell Foundations of USA , and  VP Research Office of the University of South Carolina. This work was partially supported by the  University of South Carolina , by the  DOE  grant  DE-FG02-95ER40910 , by the  Russian Federal  grant  02. 740. 11. 5220  and  MK-432. 2013. 2  and  JINR  grant  13-201-01.
Lasaga et al. , 1994; Lasaga, 1995; Pokrovsky and Schott, 2000; Van Cappellen and Qiu, 1997a; b, and references therein]. In fact, the specific effect of the saturation state and the precipitation of secondary minerals on forsterite dissolution rates (or other major silicate minerals) under field conditions are poorly constrained. Basic data for the parameterization of models and budget approaches for field conditions are needed to assess the full potential of Enhanced Weathering, specifically if the complex hydrological conditions in the soil system (e. g. , variability of soil pore water content) are taken into account. While olivine is considered to be unstable under Earth surface conditions, the solubility of forsterite is predicted to be 45-60 mmol m À3 using published constants in the LLNL, Minteq, and wateq4f databases.
There, only the purely electrostatic case was considered. To our knowledge, the present work is the first dealing with electromagnetic fields in interaction with Dirac's vacuum. Acknowledgements. M. L. and É. S. acknowledge support from the French Ministry of Research (Grant ANR-10-0101). M. L. acknowledges support from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement MNIQS 258023). We are also grateful to the referees for their careful reading of the manuscript.
ACKNOWLEDGEMENTS NEM is grateful to the  CNRS-C. E. M. H. T. I. laboratory and staff in Orléans, France , for research and financial support in performing far infrared measurements. LdelC and NEM thanks the  Berliner Elektronenspeicherring -Gesellschaft für Synchrotronstrahlung -BESSYII  for financial assistant and beamtime allocation under project  2013_1_120813. NEM also acknowledges partial financial support ( PIP 0010 ) from the  Argentinean Research Council  ( Consejo Nacional de Investigaciones Científicas y Técnicas-CONICET). Funding through Spain Ministry of Science and Innovation (Ministerio de Ciencia e Innovación)  under Project  MAT2010 Nº -16404  is acknowledged by  J AA  and MJML.
We have again verified that it stays the case when the corrections in the sbottom sector, with A b = A t , are included. We should note that for higher M A values, M A > ∼ 300 GeV, the approximation is even better as we are closer to the decoupling limit in which one has M H = M A and α = π 2 -β. Lower values, M A < ∼ 300 GeV, are disfavored by the observed h rates  [8, 9]  as seen later. In order to check more thoroughly the impact of the subleading corrections ∆M 2  11 , ∆M 2  12 , we perform a scan of the MSSM parameter space using the program SuSpect  [17]  in which the full two-loop radiative corrections to the Higgs sector are implemented. For a chosen (tan β,M A ) input set, the soft-SUSY parameters that play an important role in the Higgs sector are varied in the following ranges: |µ| ≤ 3 TeV, |A t , A b | ≤ 3M S , 1 TeV≤ M 3 ≤ 3 TeV and 0.
Acknowledgements. We are very grateful to both reviewers for useful comments and suggestions. A. V. A. is thankful to  V. V. Krasnoselskikh  for fruitful discussions related to the mechanism of electron demagnetisation in the shock waves. Authors would like to acknowledge Interball-tail and Geotail instrument teams ASPI/MIF-M, CORALL, ELECTRON, DOK-2, FGM, LEP and EPIC for excellent data. Work of A. V. A. , A. A. P. , L. M. Z. was supported by the  Russian Foundation for Basic Research  (projects no. 12-02-31127 ,  10-02-00135 ) and by the  European Union Seventh Framework Programme  [ FP7/2007[FP7/ -2013 ] ] under grant agreement no. 269198 -Geoplasmas (Marie Curie International Research Staff Exchange Scheme ). Topical Editor  R. Nakamura  thanks  A. Anastasiadis  and one anonymous referee for their help in evaluating this paper.
We also acknowledge the support received from the ERC under FP7. The Tier1 computing centers are supported by IN2P3 (France), KIT and BMBF (Germany), INFN (Italy), NWO and SURF (The Netherlands), PIC (Spain), and GridPP (United Kingdom). We are thankful for the computing resources put at our disposal by Yandex LLC (Russia), as well as to the communities behind the multiple open source software packages on which we depend.
The cluster shape is quantified using the long axis of the ellipsoidal parametrization of the energy deposit matrix : λ 2 0 = 0. 5 × (d ηη + d φφ ) + 0. 25 × (d ηη -d φφ ) 2 + d 2 ηφ , with d ii corresponding to energy distribution in the direction i. As shown in Fig. 1  (right), the long axis length, λ 0 , is fitted by the signal and background distributions using a two-component binned likelihood. The signal component is obtained from γ-jet events generated with PYTHIA and propagated through the detectors with GEANT3. The background component shape (mainly π 0 ) is extracted from data by taking the shower shape distribution of events which have failed the isolation criteria. Typical purity values extracted from fit results in the 8 to 25 GeV/c p T range go from about 5 to 70%. The x E distribution is obtained by selecting hadrons within 2π/3 < ∆Φ < 4π/3.
Conclusion & perspectives The presented measurement of the 241 Am(2n th ,f) fission yields shows that our results largely improve the experimental data on the mass yields by enlarging the range of measured mass and by reducing the experimental uncertainties. These results are in better agreement with the ENDF/B-VII. 0 library in the light mass region and are consistent with JEFF-3. 1. 1 and ENDF/B-VII. 0 in the heavy one. A good agreement was also found with the results of the GEF model. Even if the mass fission yields are of great interest on themselves, they are also a step towards the measurement of isotopic yields. These are needed for application purposes as well as for the improvement and validation of fission models. A first campaign of measurement of the isotopic yields was performed at Lohengrin.
The CTA observatories will be placed in remote locations. Thus, high-bandwidth networking is critical for remote diagnostics and speedy transfer of the data to well-connected data centres. CTA aims to support a wide scientific community, providing access to its scientific data that is archived in a standardised way. As for other projects in astronomy, a "Virtual Observatory" will provide access to the data. It is envisaged to start CTA operations during the construction phase, as soon as the first telescopes are ready to conduct competitive science observations.
The processing of CTA data is a major computational challenge. It will be necessary to reduce a volume of typically 10 TB of raw data per night to a few tens of MBytes of high-level data within a couple of hours. This first-level data processing will require hundreds of processors running in parallel on each site. All levels of data will be archived in a standardised way, to allow access and reprocessing. Access to data, support services, software and data center infrastructures will be provided through a single access point, the "VHE gamma-ray Science Gateway". It is foreseen that individual scientists using the analysis software made available by CTA can conduct the high-level analysis of CTA data. This software will follow the standards used by other observatories. All aspects of data preparation, processing, dissemination and archiving will be organised and conducted by the science data centre.
In 2011, the ATLAS experiment collected 4. 9 fb -1 of proton-proton collision data at √s = 7 TeV provided by the Large Hadron Collider. This data set allowed the search for a Standard Model Higgs Boson up to 1 TeV. In this paper, the focus is put on the searches of a low mass Higgs in the range (110-150) GeV. Using the 2011 ATLAS dataset, the combination of all the channels showed that a SM Higgs boson was restricted to live in the region (116. 6-119. 4) GeV and (122. 1-129. 2) GeV. Importantly, an excess of events has been observed around 126 GeV with a statistical significance of 2. 9 standard deviations. The present document describes the final results published by ATLAS based on the 2011 dataset alone.
INTRODUCTION The Standard Model (SM) of particle physics is the model of elementary particles and fields that describes successfully the results in particle physics produced by several experiments since more than 50 years. Nevertheless, one of the key ingredients of this model, the Higgs mechanism introduced to explain the Electroweak Symmetry breaking  [2, 3, 4, 5, 6] , has not been verified experimentally. The main prediction of this mechanism is the existence of a new spin 0 boson called the SM Higgs boson. After intensive but inconclusive searches of this new boson at LEP  [8, 9]  and TeVatron  [10] , the Large Hadron Collider (LHC) at CERN (Geneva) is now the machine at which this research is ongoing  [10, 11]. In the present paper the search of a low mass SM Higgs boson using the ATLAS detector is reported based on the full 2011 dataset  [1].
LHC OPERATIONS AND ATLAS DATA TAKING IN 2011-2012 The ATLAS detector is a multipurpose experiment  [12, 13, 14]  installed on the LHC  [15]  at CERN, Geneva. LHC provides high intensity proton beams that collide at the center of the detector. In 2011, ATLAS collected a dataset of 4. 9 fb -1 (after quality selection) at √s = 7 TeV.
Among all those channels, two can provide an accurate mass measurement of a potential Higgs boson candidate, namely the diphoton and four leptons final states, thanks to the precise measurement of the full final state provided by the Inner Detector, the Electromagnetic Calorimeter and the external Muon Spectrometer. The 4-lepton channel has a large S/B but a small event rate whereas the diphoton final state has a S/B of few percent and a sizable statistics at the integrated luminosity delivered by the LHC up to now. The WW (*) channel is characterized by a large event rate but provides very little information about the mass itself because of the presence of undetected neutrinos in the final state that degrades the WW (*) system mass reconstruction. Other channels are included but are less informative with the analyzed data sample since they have neither a large σxBR nor a very good S/B.
In these analyses, backgrounds are measured from data whenever possible or Monte Carlo (MC) based estimated using up-to-date theoretical predictions. The accuracy of MC predictions is usually validated in signal free control regions to access systematics. A huge effort has been put to estimate all the possible systematic effects that could affect the measurement as described in details in  [1]  including background modeling. The statistical significance of this excess is estimated using a maximum likelihood fit method  [1]  where the magnitude of the signal yield (µ) in units of SM cross-section is computed for each possible mass. At the time of writing of this document, the results on the SM Higgs boson search have been updated using up to 5. 8 fb -1 of proton-proton collision data taken in 2012 at √s = 8 TeV.
Acknowledgments We thank  Allan Adams ,  Fernando Alday ,  Raphael Bousso ,  José Barbón ,  Jean-Sebastien Caux ,  Goffredo Chirco ,  Ben Freivogel ,  Micha l Heller ,  Veronika Hubeny ,  Romuald Janik ,  Juan Jottar ,  Klaus Larjo ,  Matt Lippert ,  Juan Maldacena ,  Robert Myers ,  Tatsuma Nishioka ,  Carlos Núñez ,  Kyriakos Papadodimas ,  Mark Van Raamsdonk ,  Mukund Rangamani ,  Simon Ross , and  Erik Verlinde  for valuable discussions. This project was initiated at the Holographic Thermalization workshop in Leiden and benefitted from the  Black Holes, Horizons and Quantum Information workshop at CERN. VB was supported by  DOE  grant  DE-FG02-05ER-41367  and by the  Fondation Pierre-Gilles de Gennes. The work of BDC is supported by the  ERC Advanced  Grant  268088-EMERGRAV. This work is part of the research programme of the  Foundation for Fundamental Research on Matter (FOM) , which is part of the  Netherlands Organisation for Scientific Research (NWO).
Acknowledgements We are indebted to the general staff of SOLEIL for running the facility, and in particular to  J. -F. Gil , for technical help on the DESIRS beamline. We also thank  Heloise Dossman  for her help during the data acquisition. The research reported here has received funding from the  European Community 's  Seventh Framework Program  ( FP7/2007-2013 ) under Grant Agreement No. 226716. The authors acknowledge the use of the  EPSRC UK National Service for Computational Chemistry Software.