dataesr/scientific-paragraphs-categorization huggingface dataset:
Scalar singlet When m S < m h /2, the Higgs can decay to two singlet scalars. The partial width for this process is Γ h→SS = λ 2 hS v 2 0 32πm h 1 -4m 2 S /m 2 h 1/2. ( 10 ) Whenever this channel is kinematically open, DecayBit calculates the partial width and adds it to the existing set of SM Higgs decays, rescaling the decay branching fractions (BFs) and total width obtained for a pure SM Higgs. The decay h → SS would be entirely invisible at the LHC, so would contribute to the invisible width of the Higgs boson. Assuming SM-like couplings, as is the case for the scalar singlet model, 95% confidence level (CL) upper limits on the Higgs invisible width from LHC and Tevatron data are presently at the level of 19%  [114]. We implement this as a complete likelihood function in DecayBit, by interpolating the function shown in Fig.
width_in_GeV * Wplus. BF("e+","nu_e"); The functions set_BF() and BF() each have five different overloads, allowing the decay channel to be specified with any of the particle identifiers recognised by the GAMBIT particle database (see Sec. 10. 1 in Ref. [11] ). These are: 1. a simple argument list of strings corresponding to the final state particles' long names (as in the example above) 2. an argument list of alternating PDG codes and context integers, 3. an argument list of alternating short name strings and integer particle indices, 4. a std::vector of long name strings, and 5. a std::vector<std::pair<int,int>> of PDG codecontext integer pairs. All of these forms allow an arbitrary number of final state particles to be specified for a given decay channel. The DecayTable::Entry subclass also has a simple convenience method has_channel() that takes channels specified in any of the above forms, and returns a bool indicating whether the Entry already contains a field corresponding to that decay channel or not.
The individual entries in a full DecayTable can be accessed using semantics reminiscent of a regular C++ std::map, where the key is the decaying particle, referred to by any of the three possible designators recognised by the GAMBIT particle database. For example, // Declare a DecayTable DecayTable BosonDecays // Add entries (here are some I prepared earlier) BosonDecays("W+") = Wplus; BosonDecays("W-") = Wminus; BosonDecays("Z0") = Z; BosonDecays("h0_1") = SM_higgs; // Get the branching fraction for W → e νe double enueBF = BosonDecays("W+"). BF("e+","nu_e"); // Get underlying Entry for Higgs // six different ways DecayTable::Entry h; h = BosonDecays("h0_1"); h = BosonDecays(25, 0); h = BosonDecays("h0", 1); h = BosonDecays. at("h0_1"); h = BosonDecays. at(25, 0); h = BosonDecays. at("h0", 1); In this example, a DecayTable is created for holding the decays of SM bosons.
Acknowledgements We thank all our colleagues within  GAM-BIT  for helpful discussions, especially  Nazilla Mahmoudi  for her comments on the muon g -2 functionality of SuperIso. We would also like to thank  Margarete Mühlleitner  and  Ramona Gröber  for responding to questions regarding SDECAY, and  Sven Heynemeyer  and  Sebastian Paßehr  for doing so on Feyn-Higgs. PA would like to thank his FlexibleSUSY collaborators  Dominik Stöckinger ,  Jae-hyeon Park ,  Dylan Harries  and especially  Alexander Voigt , for many helpful discussions. We warmly thank the  Casa Matemáticas Oaxaca , affiliated with the  Banff International Research Station , for hospitality whilst part of this work was completed, and the staff at  Cyfronet , for their always helpful supercomputing support. GAMBIT has been supported by  STFC (UK ;  ST/K00414X/1 ,  ST/P000762/1 ), the  Royal Society (UK ;  UF110191 ), Glasgow University (UK; Leadership Fellowship), the  Research Council of Norway  ( FRIPRO 230546/F20 ), NOTUR (Norway;  NN9284K ), the  Knut and Alice Wallenberg Foundation (Sweden; Wallenberg Academy Fellowship) , the  Swedish Research Council  ( 621-2014-5772 ), the  Australian Research Council  ( CE110001004 ,  FT130100018 ,  FT140100244 ,  FT160100274 ),  The University of Sydney (Australia ;  IRCA-G162448 ),  PLGrid Infrastructure (Poland) ,  Polish National Science Center (Sonata   UMO-2015/17/D/ST2/03532 ), the  Swiss National Science Foundation  ( PP00P2-144674 ), the  European Commission Horizon   2020 Marie Skłodowska-Curie actions  ( H2020-MSCA-RISE-2015-691164 ), the  ERA-CAN+ Twinning Program  ( EU & Canada ), the  Netherlands Organisation for Scientific Research  ( NWO-Vidi 680-47-532 ), the  National Science Foundation (USA ;  DGE-1339067 ), the  FRQNT (Québec)  and  NSERC/The Canadian Tri-Agencies Research Councils  ( BPDF-424460-2012 ).
Tilt series were acquired using a tomography sample holder (Fischione model 2040) on a FEI Titan Themis microscope operated at 300 kV. Large magnification series were obtained from -72 to 72 degrees with a step size of 2 degrees. This was used to observe the faceted shapes of inclusions. Then, several other tilt series acquisitions were obtained at lower magnification from -54 to 54 degrees with 2 degree intervals. The purpose of these tilt series was to identify the position of inclusions inside the diamond matrix. These identified uncut inclusions were taken for EDX quantification. All reconstructions and visualizations were done using the Inspect3D and Chimera software packages, respectively.
186  [29]  for the parton shower, fragmentation and underlying event. The A14 set of tuned parameters  [30]  was used together with the NNPDF2. 3LO parton distribution function (PDF) set  [31]. The EvtGen v1. 2. 0 program was used to describe the properties of the band c-hadron decays in the signal samples. The signal production cross sections were calculated at next-to-leading order (NLO) in the strong coupling constant, adding the resummation of soft gluon emission at nextto-leading-logarithm accuracy (NLO+NLL)  [32] [33] [34] [35] [36]. The nominal cross section and its uncertainty were taken from Ref. [37]. Cross sections were evaluated assuming masses of 450 TeV for the lightflavour squarks in the case of gluino pair production. In the simulation, the total widths of gluinos and neutralinos were set to be 1 GeV, effectively making their decays prompt.
Matrix elements were calculated with up to three partons at LO, were showered with S as well, and were merged using the ME+PS@LO prescription  [41]. The CT10 PDF set  [42]  was used in conjunction with dedicated parton shower tuning developed by the S authors. For the generation of fully hadronic decays of t t events, the P -B 2 event generator  [43]  was used with the CT10 PDF set and was interfaced with PYTHIA 6. 428  [44]. The EvtGen v1. 2. 0 program  [45]  was also used to describe the properties of the band chadron decays for the background samples except those generated with S  [46]. The effect of additional p-p interactions per bunch crossing ("pile-up") as a function of the instantaneous luminosity was taken into account by overlaying simulated minimum-bias events according to the observed distribution of the number of pile-up interactions in data.
Conclusion A search for R-parity-violating SUSY signals in events with multiple jets is conducted with 36. 1 fb -1 of proton-proton collision data at √ s = 13 TeV collected by the ATLAS detector at the LHC. Distributions of events as a function of total jet mass of the four leading jets in p T are examined. No significant excess is seen in any signal region. Limits are set on the production of gluinos in the gluino direct decay and cascade decay models in the UDD scenarios of RPV SUSY. In the gluino cascade decay model, gluinos with masses between 1000 GeV and 1875 GeV are excluded at 95% CL, depending on the neutralino mass; in the gluino direct decay model, signals with a cross section of 0. 011-0. 8 fb are excluded at 95% CL, depending on the gluino mass. Model-independent limits are also set on the signal production cross section times branching ratio in five overlapping signal regions.
Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS, CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF, and MPG, Germany; GSRT, Greece; RGC, Hong Kong SAR, China; ISF, I-CORE and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russian Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, the Canada Council, CANARIE, CRC, Compute Canada, FQRNT, and the Ontario Innovation Trust, Canada; EPLANET, ERC, ERDF, FP7, Horizon 2020 and Marie Skłodowska-Curie Actions, European Union; Investissements d'Avenir Labex and Idex, ANR, Région Auvergne and Fondation Partager le Savoir, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF; BSF, GIF and Minerva, Israel; BRF, Norway; CERCA Programme Generalitat de Catalunya, Generalitat Valenciana, Spain; the Royal Society and Leverhulme Trust, United Kingdom.
Acknowledgements We thank  CERN  for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of  ANPCyT , Argentina; YerPhI, Armenia;  ARC, Australia ;  BMWFW  and  FWF , Austria; ANAS, Azerbaijan; SSTC, Belarus;  CNPq  and  FAPESP, Brazil ;  NSERC ,  NRC  and  CFI ,  Canada ; CERN; CONICYT, Chile; CAS,  MOST  and  NSFC, China ;  COLCIENCIAS ,  A. M. Zaitsev 140 ,al ,  N. Zakharchuk 44  ,  J. Zalieckas 17  ,  S. Zambito 57  ,  D. Zanzi 35  ,  C. Zeitnitz 180  ,  G. Zemaityte 131  ,  J. C. Zeng 171  ,  Q. Zeng 150  ,  O. Zenin 140  ,  D. Zerwas 128  ,  D. F. Zhang 58b  ,  D. Zhang 103  ,  F. Zhang 179  ,  G. Zhang 58a ,af ,  H. Zhang 128  ,  J. Zhang 6  ,  L. Zhang 50  ,  L.
CHEC is designed to observe in the γ-ray energy range of 1-300 TeV, and at impact distances up to ∼500 m. To accommodate this and provide full flexibility for later data analysis, full waveforms with 96 samples for all 2048 pixels can be read out at rates up to ∼900 Hz. The first prototype, CHEC-M, based on multi-anode photomultipliers (MAPMs) as photosensors, was commissioned and characterised in the laboratory and during two measurement campaigns on a telescope structure at the Paris Observatory in Meudon. In this paper, the results and conclusions from the laboratory and on-site testing of CHEC-M are presented. They have provided essential input on the system design and on operational and data analysis procedures for a camera of this type. A second full-camera prototype based on Silicon photomultipliers (SiPMs), addressing the drawbacks of CHEC-M identified during the first prototype phase, has already been built and is currently being commissioned and tested in the laboratory.
Research and development for CHEC is progressing via the development of two prototype cameras: CHEC-M, based on MAPMs, and CHEC-S, based on SiPMs. In this paper, we present results from CHEC-M, the first CHEC prototype. The prototype design and laboratory test results are presented. Onsky Cherenkov data is shown from CHEC-M installed on a GCT prototype telescope in Meudon near Paris, and upcoming prospects towards a camera design for the production phase of CTA are discussed.
Each board is based around a Xilinx Virtex-6 FPGA providing 18 GTX serial transceivers and an ARM Atmel microprocessor running an entire light-weight Linux system for managing purposes. An Ethernet connection to each DACQ board enables controlling and monitoring using a UDP server which runs on the microprocessor. The SPI control of the backplane is provided through another UDP server running only on one of the two DACQ boards. The boards are custom-made revisions of network switches based on White Rabbit technology  [25]  which are also commercially available from the company Seven Solutions.
Control software and data acquisition The camera control and readout are managed by a C++ software package referred to as CHECInterface. It is designed to be maintainable, simple, and robust, and to fulfil the following requirements: 1. The number of dependencies on external software is at a minimum. 2. Only minimal code changes are necessary when a camera hardware component is upgraded. 3. The code is written in C++. 4. Scripts and programs written in other programming languages are only allowed for user interface, test programs, and other executables, but not for core-functionality. 5. Continuously buffering and writing of events without loss is ensured up to a rate of 600 Hz (corresponding to 2. 5 Gbps). 6. The software is easy to adapt as soon as a final data format or pipeline for CTA is in place.
Two external libraries (CFITSIO  [28]  and simple network management protocol (SNMP)  [29] ) and three self-developed libraries are used within the software: TargetDriver (for control and readout of TARGET modules), TargetCalib (for applying TARGET module calibration), and TargetIO (for reading and writing data from TARGET modules). The software is structured so that each hardware component inside (e. g. TARGET modules) and outside (e. g. chiller) the camera is represented by its own lower level class. The main class CameraInterface serves as interface to all lower level classes. Fig. 5    PC in asynchronous sets of 64 UDP packets (2 packets per event per module). They are first buffered and then assembled into associated events based on the TACK in each packet header which serves as a unique event identifier.
A timeout is used to prevent the PC buffer filling up if (in an unexpected case) events with missing packets arrive or if the event building takes longer than expected. Missing packets are not requested again and incomplete events are discarded. In a subsequent step, the events are written to disk as FITS files  [28]. Once CTA is operating and a final CTA data framework exists, the data will instead be further processed in a pipeline. However, even then it is planned to continue developing and using TargetDriver and TargetIO for single test purposes. Due to the modest event rate per SST in CTA (600 Hz, cf. Sec. 2), no inter-telescope hardware array trigger is required. When a telescope triggers, all data is read out and transferred from the camera to be processed by the software array trigger system.
In the next step, the overall camera trigger rate (second-level trigger) was measured as a function of the camera trigger threshold. On telescope, such measurements are typically used to identify the camera trigger threshold operating point for given background light conditions. To understand the influence not only of the NSB but also of the TARGET module sampling and data sending on the camera trigger rate, three different scenarios were investigated in the lab (results shown in Fig. 11b ): 1. Backplane hold-off (BO) time set to 80 µs as used in CHEC-M for nominal operation (BP HO on) and all TAR-GET modules configured to not sample and not send data (SD off) -blue data points in Fig. 11b, 2. BP HO on and all TARGET modules configured to sample and send data (SD on) -green data points in Fig.
Dynamic range The dynamic range of the signal recording chain (MAPM and FEE module) was assessed by illuminating the entire camera with a uniform light level ranging from below 1 p. e. /pixel to several hundreds of p. e. /pixel in calibrated steps. The measurements were done supplying all MAPMs with the maximum voltage of 1100 V to be able to resolve SPE at low illumination. Results for two camera pixels (same as used for the FWHM and risetime investigation, cf. Sec. 5. 5) and of an MAPM-only measurement for comparison are shown in Fig. 15a. For the camera pixel data points, the charge (y-axis) was reconstructed following the procedure explained in Sec. 4. 2. Its value at ∼50 p. e. /pixel was used as anchor for the illumination level on the x-axis to absolute calibrate the laser. Other points on the xaxis were then inferred from the relative calibration of the filter wheel used to adjust the laser intensity, resulting in an illumination in units of p.
e. /pixel. The MAPM data points were inferred from measurements where the MAPM signal was directly measured with an oscilloscope while the absolute calibration of the x-axis was determined from single-p. e. spectra fits at the lower end of the range and using the relative calibration of the filter wheel for the rest of the x-axis range. According to Fig. 15a , clear deviation from a linear correlation between illumination level and reconstructed charge (using the procedure described in Sec. 4. 2) starts to occur at an illumination of ∼250 p. e. /pixel for camera pixel 1825 while it is not observed in pixel 1203 over the range of laser brightnesses used in these measurements. This can again (as in Sec. 5. 5) be explained by saturation effects occurring at different illumination levels due to different gains at 1100 V and due to different quantum and collection efficiencies between the two pixels (less substantial).
LED calibration flashers The four flasher units were tested for stability and temperature dependence, as well as on their dynamic range. ated in a temperature controlled environment while their brightness was measured with an SiPM (with known temperaturegain dependence). The overall dynamic range of one flasher consisting of 10 LEDs is about four orders of magnitude with illumination levels at the camera in the range of sub-p. e. /pixel up to a few thousands of p. e. /pixel. The flasher brightness dependence on temperature is different for each combination of the 10 LEDs (pattern). It shows an increase with temperature of <1%/ • C for the brightest pattern up to 5%/ • C for the dimmest (see Fig. 18a ). Fitting this dependence with a polynomial of second order gives different fit results for each combination which can be used to correct for temperature effects in other data sets (see Fig.
Thus, this approach would cause a maximum dead time of ∼0. 8% per night (according to a very simplified calculation, assuming a linear temperature drift of 8 • C within an eight-hours night). To avoid that, a pedestal determination could be done "online" during observation instead, either with interleaved events or by using parts of the wave-forms/pixels with no signals. The latter option is the long-term plan for next camera iterations. To investigate the camera warm-up, two relevant quantities were investigated: first, the change in trigger rate with closed lid and HV off, indicating whether the trigger threshold is stable and the camera is ready for triggering, and second, a possible shift in the baseline indicating whether the camera is ready for data taking. To measure the trigger rate change during warmup, the trigger threshold was set in the electronic noise causing the trigger rate to be very sensitive to electronic noise changes expected to occur during warm-up  16.
Additionally, images at the highest energies can take many tens of nanoseconds to cross the camera, as can be seen in Figure  23d. Without a ∼100 ns readout window, such images would appear truncated, negatively impacting the analysis. With the on-sky data taken with the CHEC-M camera we proved both the technical functionality of the camera and the existence of a data calibration and analysis chain, both aspects being crucial for the camera to be used as an IACT camera. Both campaigns helped to verify interfaces and to improve operation procedures. Furthermore, the regular operation was used for understanding the system stability and reliability. In total, a few hundred meaningful Cherenkov and direct EAS particle events were recorded and analysed.
Summary and outlook CHEC-M is an invaluable step towards a reliable and highperformance product for CTA. Regular operation of CHEC-M has shown that the camera control and data acquisition using the software CHECInterface and the calibration and waveform processing chain are robust and reliable. Intensive lab tests led to a detailed characterisation of the camera performance as well as a detailed understanding of the factors limiting the performance, thus being a critical input to the design of the next camera prototype CHEC-S, see below). Main results are: • CHEC-M can be read out at an efficiency of 95% at a mean random rate of 600 Hz. The efficiency is expected to be 100% at this rate with the next TARGET-5 ASIC generation used in CHEC-S. • While commissioning and testing of CHEC-M, 128 TAR-GET ASICs have been tested and tuned simultaneously confirming the results obtained in single TARGET ASIC tests (cf.
Acknowledgements This work was conducted in the context of the  CTA GCT  project. We gratefully acknowledge financial support from the agencies and organisations listed here: http://www. ctaobservatory. org/consortiumacknowledgments Furthermore, we thank the  Paris Observatory  as well as the  DT-INSU  for their support during the on-sky campaigns in Meudon. This study was also supported by  JSPS KAKENHI  Grant Numbers  JP17H04838 ,  JP25610040 ,  JP15H02086 , and  JP23244051. A. Okumura was supported by a  Grant-in-Aid for JSPS Fellows. This paper has gone through internal review by the  CTA Consortium.
A small Allan deviation indicates a high precision in the frequency read-out. Magnetometers can be characterized in the very same way, the signal S being proportional to the magnetic moment. Here, we compute σ A (τ ) for the pulsed-CPT and Ramsey-CPT schemes and quantify their performances as a function of the number of steps and for various decoherence rates in the ground state. To avoid optimization complications related to the choice of probe intensity, we chose to use fluorescence instead of transmission read-out for both schemes and use Ω 1 = Ω 2 as in  [19]. Further, we use a pulse area far below 2π to be in the EIT regime. The analytical solutions presented earlier cannot be used here since we need to compute the excited state population instead of the coherence |1 3|. We thus we resort to numerical simulations and use the XMDS package to solve the full Bloch equations  [24].
ACKNOWLEDGMENTS We acknowledge the support from  CNPq  and  CAPES, Brazil , and from  AFOSR, USA , under research Grant No. FA9550-16-1-0280. S. M. acknowledges the support from Grant No. ANR-11-IDEX-0004-02  Plas@Par. D. A. B. and R. A. C. are supported by the  UK Science and Engineering Research Council  Grant No. EP/N028694/1. We thank the referees for their useful suggestions. All of the results can be fully reproduced using the methods described in the paper.
Quantum Stark broadening of 12 lines of the Ar VII ion have been calculated using 9 configurations (1s 2 2s 2 2p 6 : 3s 2 , 3s3p, 3p 2 , 3s3d, 3p3d, 3s4s, 3s4p, 3s4d, and 3s5s). Our calculations have been made for a set of temperatures ranging from 2 × 10 4 to 5 × 10 5 K. These parameters will be useful for a more accurate determination of photospheric properties. We perform also a semiclassical calculations for these lines using our atomic data from the code SUPERSTRUCTURE. We compare these results to the semiclassical ones  [12] , for which the atomic structure has been calculated with the Bates and Damgaard approximation  [13].
The calculation starts with the study of the atomic structure. The structure problem has been treated using the SUPERSTRUCTURE (SST) code described in Eissner et al. [14] , taking into account configuration interaction, where each individual configuration is an expansion in terms of Slater states built from orthonormal orbitals. The radial functions were calculated assuming a scaled Thomas-Fermi-Dirac-Amaldi (TFDA) potential. The potential depends upon parameters λ l which are determined variationally by optimizing the weighted sum of the term energies. Relativistic corrections (spin-orbit, mass, Darwin, and one-body) are introduced according to the Breit-Pauli approach  [15]  as a perturbation to the non-relativistic Hamiltonian. The SST program also produces the term coupling coefficients (TCCs), which are used to transform the scattering S or reactance R-matrices to intermediate coupling  [7].