dataesr/scientific-paragraphs-categorization huggingface dataset:
It was realized that most incidences of high background were of short duration, and that frequent beam aborts followed by beam injection contributed significantly to the absorbed radiation dose. Consequently, more emphasis was placed on detailed monitoring of BABAR background conditions, shared with PEP-II operators, and the signal for beam aborts was only activated under severe conditions extending over longer periods of time. The efficient BABAR operation was enabled by the Online System, which spanned from Detector and Run Control, Online Databases, Dataflow, to the online computer farm, servers, data switches, and networks. With the increasing demands of higher data rates and the rapid increase in speed and capacity, the hardware and software, including the operating platforms, had to be replaced, most of them more than once.
Trigger efficiencies for most physics processes of interest were maintained at over 99%, and triggers for new physics signatures were easily added. A central feature of the BABAR detector was the common architecture of the electronics. It not only reduced the number of different components, but it also unified calibration and monitoring procedures, and thereby simplified the diagnosis of problems. It also simplified many routine maintenance tasks, upgrades, and the replacement of components, thereby reducing detector down times. To cope with higher background rates and maintain the nearly dead-time-free operation, upgrades to the front-end electronics and data acquisition were successfully implemented. For the DIRC, faster TDCs were installed and a much faster feature extraction was developed, while for the SVT, the sensitive time window was narrowed.
This problem was resolved by converting the chambers to operate in avalanche mode. The scale of the offline computing and data storage requirements were unprecedented in HEP and presented enormous challenges. The implementation and continuous upgrades of the system's hardware and software required innovation in many areas and the resources of the whole collaboration. It led to the pioneering development of distributed computing supported by seven large computing centers. An elaborate system of checks assured the quality of the data and integrity of the software used by hundreds of scientists. Substantial redesigns and hardware and software adaptation continuously enhanced the capabilities of the system and were accomplished without interfering with the physics analyses. The diverse needs of the hundreds of scientists analyzing the data inspired the design of a flexible and configurable mechanism to access the results of event reconstruction and calibrations, both for events recorded by BABAR and simulated by Monte Carlo techniques.
On the basis of data recorded at higher c. m. energies and at the lower mass ϒð2SÞ and ϒð3SÞ resonances, limits for the production and decays of axions and other dark matter candidates were established. Recently, a system referred to as LTDA was installed that preserves access to the BABAR data and standard analysis and simulation software to support future analyses of the large BABAR data sample. This novel system will also be valuable for the preparation of experiments at future storage rings operating at or near the ϒð4SÞ resonance. Beyond that, the LTDA system is recognized as a flagship for data preservation for current and future high energy physics experiments.
Acknowledgments The authors are grateful for the tremendous support they have received from their home institutions over the almost 10 years of BABAR and PEP-II operation. The excellent performance of PEP-II, the data taking, the data processing and the data analysis would not have been possible without the extraordinary expertise, dedication and collaboration of the supporting staff at  SLAC  and other BABAR institutions, as well as at participating computing centers. The collaborating institutions wish to thank  SLAC  for the kind hospitality extended to them. Members of the International Finance Committee should be commended for their continued assistance in securing resources for the operation and upgrades of the experiment. This work has been supported by the  US Department of Energy and National Science Foundation , the  Natural Sciences and Engineering Research Council (Canada) , the  Commissariat à l'Energie Atomique  and  Institut National de Physique Nucléaire et de Physique des Particules (France) , the  Bundesministerium für Bildung und Forschung and Deutsche Forschungsgemeinschaft (Germany) , the  Istituto Nazionale di Fisica Nucleare (Italy) , the  Foundation for Fundamental Research on Matter  (The Netherlands), the  Research Council of Norway , the  Ministry of Education and Science of the Russian Federation, Ministerio de Economía y Competitividad (Spain) , and the  Science and Technology Facilities Council (United Kingdom).
1 GeV positrons LH LikeliHood, a mathematical tool commonly used in BABAR analysis to estimate the parameters of a statistical model LM Logging Manager, a component of the online system transferring data to disks LST Limited Streamer Tube, the final technology used to instrument the barrel IFR, replacing the original BABAR RPCs LTDA Long Term Data Access, the computing system to permit access to BABAR data and software for future analyses MC Monte-Carlo, the generic method used to simulate events MIP Minimum-Ionizing Particle, a particle with an energy loss rate ðdE=dxÞ close to the minimum component of the online system to control the extraction of information from the FEEs for event building OEP Online Event Processing, the processing of complete BABAR events ORC Online Run Control, the top-level control for the detector operation and data taking pCVD Polycrystalline Chemical Vapor Deposition, the material of the two SVTRAD diamond sensors PC Prompt Calibration, the first step of the offline data reconstruction PCB Printer Circuit Board, a component of the LST modules PID charged Particle IDentification, algorithms to identify charged tracks crossing the detector (e, μ, π, K or p) ADB Analog-to-Digital converter Board, converting raw EMC signals to digital format ADC Analog-to-Digital Converter API Application Programming Interface, a communication interface between software components AToM A Time-over-threshold Machine, a radiation-hard ASIC to determine SVT pulse height in front-end electronics B1, B2 PEP-II dipole magnets in the interaction region BCM Bunch Current Monitor, a device monitoring the charge of each bunch BDT NEG Bagged Decision Tree, a multi-variate algorithm for Non-Evaporable Getter, a type of vacuum pumps used statistical classification of data samples by PEP-II BLT NIEL Binary Link Tracker, a component of the DCT Non Ionizing Energy Loss, energy causing BPM Beam Position Monitor, determining the transverse displacements in Silicon crystals NIOS positions of the beams Altera Trademark, a versatile embedded processor BW Backward, the BABAR endcap facing the incoming HER widely used in FPGAs NN beam Neural Network, a multi-variate algorithm for CCE Charge Collection Efficiency, a quantity relevant for classification of data samples ODB SVT sensors Online Databases, store detector-related info- cron time-based job scheduler in Unix-like computer rmation (configurations, conditions and calibration operating systems, enabling users to schedule jobs to constants) ODC run periodically at certain times Online Detector Control, controls and monitors the environmental detector conditions ODF Online DataFlow,.
We describe an extension of the FeynRules package dedicated to the automatic generation of the mass spectrum associated with any Lagrangian-based quantum field theory. After introducing a simplified way to implement particle mixings, we present a new class of FeynRules functions allowing both for the analytical computation of all the model mass matrices and for the generation of a C++ package, dubbed ASperGe. This program can then be further employed for a numerical evaluation of the rotation matrices necessary to diagonalize the field basis. We illustrate these features in the context of the Two-Higgs-Doublet Model, the Minimal Left-Right Symmetric Standard Model and the Minimal Supersymmetric Standard Model.
Introduction Although the Standard Model of particle physics is very well verified empirically at the current accessible energies, numerous extensions to its Lagrangian are proposed. These extensions describe new or alternative fundamental interactions that typically accommodate possible new physics phenomena at higher energies as well as at the current collider energies. In this top-down approach, the phenomenology of the proposed extensions is to be confronted with experimental observations. In order to obtain the mass spectrum of any new physics model reflected by its Lagrangian, the mixing matrices of the gauge eigenstates into the mass eigenstates are needed. An automated mass spectrum generator, ASperGe 1 is developed within the framework of the FeynRules program  [1, 2, 3, 4, 5]  to determine the mix- 1 The acronym ASperGe stands for Automated Spectrum Generation.
The FeynRules package The program FeynRules  [1, 2, 3, 4, 5]  is a Mathematica 2  package that allows for the automated extraction of Feynman rules from any Lagrangian describing the dynamics of a perturbative quantum field theory. The Feynman rules, together with general information such as the definitions of the model particles or of the Lagrangian parameters, can subsequently be exported by means of several translation interfaces to matrixelement generators. Up to now, interfaces to CompHep and CalcHep  [6, 7, 8, 9] , FeynArts and FormCalc  [10, 11, 12, 13] , MadGraph and MadEvent  [14, 15, 16, 17, 18] , Sherpa  [19, 20]  and Whizard  [21, 22]  have been developed. In addition, any model can also be converted to a Python library containing classes and objects representing particles, parameters and vertices.
Since only the particle class properties introduced above are sufficient for the understanding of the present work, we omit any further detail and refer the reader to Refs. [1, 4]  for more information on particle, parameter and gauge group implementation in FeynRules. The last key ingredient to achieve a model implementation consists of its Lagrangian. It is provided using standard Mathematica commands, augmented by some special symbols representing objects such as Dirac matrices, vector field strength tensors or covariant derivatives. The user has then the possibility to perform basic checks on the Lagrangian, such as verifying its hermiticity, the normalization of kinetic terms, etc. We again refer to the FeynRules manual for more information  [1]. After having imported the FeynRules package into the current Mathematica session, the model is loaded by issuing LoadModel[ "file1.
Implementing mixings in FeynRules In this work, we propose an extension of the Feyn-Rules package aiming to simplify the declaration of the mixing relations linking the unphysical degrees of freedom of the theory to the physical fields. This new module allows to automatically fill the Definitions attribute of the fields, where relevant, and declare the mixing matrices as parameters. In addition, we have developed an interface generating a C++ code dedicated to the diagonalization of the mass matrices of the model (see Section 4) after having implemented in FeynRules a function allowing for their analytical extraction from the Lagrangian. In this way, the values of all the mixing parameters are derived numerically and can be re-imported into FeynRules.
and bc L (sdL  [3,c] ) are related to the squark gauge-eigenstates Qifc L (QLs[i,f,c]), the index i being a fundamental SU (2) L index, the index f a flavor index and the index c a fundamental color index. The corresponding declaration reads Mix["sdleft"] == { MassBasis -> {sdL[1,_], sdL[2,_], sdL[3,_]}, GaugeBasis -> {QLs[2,1,_], QLs[2,2,_], QLs[2,3,_]},. } where the mixing matrix is the identity. The underscore reflects that the same color index is carried by all fields. We now get back to weak gauge boson mixings and turn to the neutral sector. We hence focus on the rotation of the third weak boson W 3 and the hypercharge gauge boson B to the photon and Z-boson states, A µ Z µ = U w B µ W 3 µ , (2) after introducing the a priori unknown weak mixing matrix U w 4. The computation of the numerical values of its matrix elements is addressed by means of the C++ package generated by FeynRules (see Section 4) and is only possible if the mixing is declared according to the syntax Mix["AZmix"] == { MassBasis -> {A, Z}, GaugeBasis -> {B, Wi[3]}, MixingMatrix -> UW, BlockName -> WEAKMIX } The declaration of the gauge and mass bases is similar to the case of the charged W bosons, while the attribute Value has been removed as the numerical value of the mixing matrix is not known.
The ASperGe package The computation of the unknown mixing matrices necessary for diagonalizing all the model mass matrices can in general only be achieved numerically. To this end, we have developed the C++ program ASperGe. It includes a set of C++ source files (stored in the subdirectory src), coming together with the related header files (stored in the subdirectory inc), that can be split into model-independent and model-dependent files. For an efficient use of the ASperGe program, it has been entirely embedded within the FeynRules package. Therefore, only a brief discussion of the structure of the code is presented in this paper. More information, such as a doxygen documentation, can be found on the ASperGe webpage  [32]. The set of model-independent files contains, on the one hand, several tools dedicated to matrices and their diagonalization (MassMatrix.
cpp, MassMatrix. hpp as well as Matrix. hpp). On the other hand, the ASperGe code is based on an internal format for parameters, defined in the source files Par. cpp, CPar. cpp, RPar. cpp and in the associated header files. This format is inspired from a SLHA structure and the corresponding mapping is encoded into the files ParSLHA. cpp, SLHA-Block. cpp, and in the associated header files. Finally, printing and string manipulation routines are included in the files tools. cpp and tools. hpp and the program comes with a makefile. All the model dependency is included in the two files Parameters. cpp and Parameters. hpp as well as in the core program implemented in the main. cpp file. The information encompassed in the two parameter files is threefold. First, the SLHA structure ordering the external parameters is encoded in terms of blocks and counters.
Next, the definitions of the internal parameters as functions of the other model parameters are implemented, where a proper running of the AS-perGe program is only guaranteed if the parameters do not depend on the masses and mixing matrices to be computed. Finally, the analytical formulas of the mass matrices to diagonalize are included. The main program (main. cpp) starts with the declaration of the different mass matrices of the model. Links to the relevant elements of the mass basis are then implemented by means of the associated PDG codes, which allow to assign the mass eigenvalues to each of the physical particles, the ordering of the PDG codes following the mass ordering.
Interfacing the ASperGe package to FeynRules The ASperGe package can be entirely generated, for a given particle physics model, from the FeynRules model information by means of a dedicated interface which works as for the other FeynRules interfaces. It is then called by typing, in a Mathematica session, WriteASperGe[ Lag, Output -> dirname ] where the symbol Lag stands for the model Lagrangian and Output->dirname for an optional argument indicating the name of the directory where to store all the created files. If unspecified, the directory ModelName_MD is employed, ModelName being the name of the Feyn-Rules model. The interface first extracts all the relevant mass matrices from the Lagrangian Lag by means of the function ComputeMassMatrix introduced in Section 3. 4. It then writes, in addition to model-independent files described in Section 4.
1, the three model-dependent files main. cpp, Parameters. cpp and Parameters. hpp, together with one data file Externals. dat (stored in the subdirectory input). This last file contains the numerical values of the external parameters of the model, necessary for the numerical evaluation of the mass matrices. When running the code (see Section 4. 3), the user can update this file or even employ a different file according to his needs. The numerical matrix diagonalization performed by ASperGe is based on Gsl functions relying on the hermiticity of the mass matrices which employs symmetric bi-diagonalization followed by QR reduction. This contrasts with existing diagonalization packages developed in the framework of FeynArts  [33]  and CalcHep  [34]  that are based on Jacobi-type iterative algorithms.
Running ASperGe Since the ASperGe package is based on Gsl functions, it is mandatory to have the Gsl libraries installed on the system. Then, if the g++ compiler is available, the makefile generated by FeynRules can be employed directly. Otherwise, it must be first edited accordingly to include proper compiler information. Once compiled, ASperGe can be executed by typing in a shell. /ASperGe <infile> <outfile> where the arguments indicate in which file the numerical value of the external parameters must be read (<in-file>) and where to store the output file (<outfile>). This file contains, in addition to the input parameters, the computed numerical values of the mixing matrices, split in terms of their real and imaginary parts according to the SLHA conventions, as well as all the masses of the physical states (stored in the SLHA block MASS).
In order to execute ASperGe with all the default settings as generated by the FeynRules interface, it is sufficient to type in a shell. /ASperGe input/externals. dat output/out. dat Both the compilation and the execution of the program can be performed from the Mathematica session, by issuing RunASperGe[ ] This also loads the SLHA parameter file out. dat back into the FeynRules session, so that it can be further employed, e. g. , to generate a UFO model. Information about the run of ASperGe can be found in the file ASperGe. log stored in the same folder as the executable. It is also possible to diagonalize specific mass matrices of the model by executing. /ASperGe <infile> <outfile> m1 m2. where m1, m2, etc. , are the names of the mixing matrices to be computed.
Illustrative examples In this section, we illustrate the features of the AS-perGe program and its interface to FeynRules by choosing three extensions of the Standard Model with non-trivial mixing relations, i. e. , the Two-Higgs-Doublet Model (2HDM), the Minimal Left-Right Symmetric Standard Model (LRSM) and the Minimal Supersymmetric Standard Model (MSSM). We modify their original FeynRules implementations 5   [2, 4]  to accommodate for the mixings as described in Section 3. We then employ the ASperGe program (see Section 4) to numerically calculate some of the mass and mixing matrices of these models.
Similarly, we can employ the mixing infrastructure to map the charged components of φ 1 and φ 2 to the physical fields G + and H + by means of a 1 × 1 identity matrix. Since this procedure is trivial, we omit any further details from the present manuscript and refer to the model implementation  [32]. In a second stage, the rotation to the physical fields, represented by the symbols h1, h2 and h3, is declared as Mix["1s"] == { MassBasis -> { h1, h2, h3 }, GaugeBasis -> { H0, R0, I0 }, MixingMatrix -> NH, BlockName -> NHMIX } where we associate the symbol NH to the corresponding mixing matrix and assign the Les Houches block (IM)NHMIX to the numerical value of its elements. The neutral squared mass matrix M 2 can then be derived from the model Lagrangian (represented by the symbol L2HDM) by typing, in the Mathematica session,.
Acknowledgements The authors are grateful to  N. D. Christensen ,  C. Degrande  and  C. Duhr  for useful discussions on the project. This work has been partially supported by a Ph. D. fellowship of the French ministry for education and research, by the  Theory-LHC France-initiative  of the  CNRS/IN2P3 , by the  French ANR   12 JS05 002 01 BATS@LHC , by the  Concerted Research action 'Supersymmetric Models  and their Signatures at the  Large Hadron Collider ' and the  Strategic Research Program 'High Energy Physics' of the Vrije Universiteit Brussel (VUB) , by the  Belgian Federal Science Policy Office  through the  Interuniversity Attraction Pole IAP   VI/11  and  P7/37  and by a ' FWO-Vlaanderen ' aspirant fellowship.
Then we compare the results of both methods The photogrammetric protocol has been elaborated by choosing the most accurate software, 123DCatch, which asks for about 60 pictures, and defining the settings needed to obtain exploitable photographs. In the same way, we defined the devices and settings needed for the laser scan acquisition method. In a second part, we segment the 3D meshes in planes by using Geomagic, which has been chosen between several programs, for its accurate resulting geometry.
Comparison of software We have been looking for a tool that would automate to the maximum the meshing process. Previously, we used Photomodeler Scanner, software that used photogrammetric methods in manual ways. Now that the technologies have evolved in this field, many software programs exist. We have tested several photogrammetrical software that use different algorithms and different protocols for taking pictures, to select the most appropriate to our need. To do it wisely, we followed the main instructions for each software program to have a proper set of pictures, rather than providing an identical set for all software. Elements of comparison have already been made, on real buildings  (Grussenmeyer et al. , 2008). We considered these researches to make our experiments, but the tested software often ask for manual intervention.
Also, others photogrammetric programs appeared recently. Tested softwares are: Autodesk 123DCatch, Agisoft Photoscan, EOS System Photomodeler. Other softwares, as Pistou (a research program in MAP-Gamsau, or Topcon's Imagemaster Pro have been considered, but we excluded them for their apparent complexity. Here are the results of our comparison; each one tested on the 3D printed scale model of Toul: As seen on table 1, 123DCatch asks for about 60 pictures, with a maximum of 80. Photoscan needs pictures as much as possible, the user manual mentioning 100 to 500. Photomodeler is mainly usable manually, but an automation exists, which demands for couples of pictures, to work with stereogrammetry. After experiments, the most appropriate software to acquire high quality 3D meshes from scale models using photogrammetry appeared to be Autodesk 123DCatch.
Protocol for taking pictures In the case of our study, we used a Canon EOS 6D, offering high quality pictures of 16 megapixels, equipped with a 24-70 lens. We had a laptop on the shooting place, to download and verify pictures. Also, we had the possibility to start a test with 123DCatch granting us a preview for exploitable results or not. Have been tested aperture, sensibility, shutter speed settings and different lightning conditions, with some help from a professional photographer. This protocol was only applied and verified on the Autodesk 123DCatch software. It has been provided by our own tests, but also by following the user manual, the user experiences and previous related works on photogrammetry in the Digital Heritage domain. The Single-Lens Reflex is set on manual mode, assembled with the flash device and its reflector.