Energy Reconstruction Algorithms Research Articles

PERFORMANCE EVALUATION OF ENERGY RECONSTRUCTION METHODS IN HIGH ENERGY PHYSICS EXPERIMENTS

The discovery of particles that shape our universe pushes the scientific community to increasingly build sophisticated equipment. Particle accelerators are one of these complex machines that put known particle beams on a collision course at speeds close to that of light. When collisions occur, subproducts are produced and measured by the calorimeter system, which entirely absorbs these subproducts. Typically, a high-energy calorimeter is highly segmented, comprising thousands of dedicated readout channels. The present work evaluates the performance of two energy reconstruction algorithms: the OF (Optimal Filter) and MAE (Multi-Amplitude Estimator), which was recently proposed to deal with the signal superposition (pile-up). In order to evaluate the energy estimation efficiency, artificial data were used, considering several pile-up levels. The statistics from the energy estimation is employed to compare the performance achieved by each method. A second analysis is made to quantify the MAE sensitivity to the pedestal parameter. The results show that the MAE method presents a better performance than the OF method and the usage of an uncalibrated pedestal value compromises the MAE performance.

Overview of Energy Reconstruction, and Electron and Photon Performances with the CMS ECAL in Run II

The electromagnetic calorimeter (ECAL) of the Compact Muon Solenoid (CMS) Experiment is crucial for achieving high resolution measurements of electrons and photons. Maintaining and possibly improving the excellent performance achieved in Run I is vital for measurements of the Standard Model Higgs boson and searches for new higher mass resonances in final states with electrons and photons. Since spring 2015, the ECAL has operated with proton-proton collisions at 13 TeV center-of-mass energy and at a reduced bunch spacing of 25 ns. The instantaneous luminosity delivered by the LHC during Run II is expected to exceed the levels previously attained. The average number of concurrent proton-proton collisions per bunch-crossing (pileup) is expected to reach up to 40 interactions. In this summary we present new crystal energy reconstruction algorithms and clustering techniques that have been developed to maintain the excellent performance of the CMS ECAL throughout Run II. We will show first performance results from 2015 data, achieved through energy calibrations using electrons from W and Z boson decays, photons from π0/η decays, and the azimuthally symmetric energy distribution of minimum bias events. Lastly, we present an outlook on the expected Run II performance in the next years.

Precision crystal calorimetry in LHC Run II with the CMS ECAL

The electromagnetic calorimeter (ECAL) of the Compact Muon Solenoid (CMS) Experiment, based on lead tungstate scintillating crystals, is crucial for achieving high-resolution measurements of electrons and photons. Maintaining and possibly improving the excellent performance achieved in Run I is vital for measurements of the Standard Model Higgs boson and searches for new higher mass resonances in final states with electrons and photons. In Spring 2015 the LHC started “Run II”, colliding protons at 13 TeV centre-of-mass energy and with 25 ns bunch spacing. This is very close to the original design specifications of the LHC (14 TeV at 25 ns). At this higher energy, and with the rapidly growing dataset, the performance for higher electron and photon energies becomes crucial. At the same time, the instantaneous luminosity has increased and, over the coming years, is expected to surpass the design value, possibly by a factor of two to about 2×1034 cm−2 s−1. The average number of concurrent proton-proton collisions per bunch crossing (pileup) is expected to reach about 40. This pileup is a major challenge, both for calibration and for ultimate energy reconstruction. The CMS ECAL design ensures that its superb performance extends over a very wide range of energies up to electron and photon energies of 1 TeV and beyond. We present new energy reconstruction algorithms and clustering techniques, developed to maintain the excellent performance of the CMS ECAL throughout Run II. We will show first performance results from 2015 and 2016 data, including triggering efficiency, event reconstruction and calibration precision. The latter has been achieved through the measurements of electrons from W and Z boson decays, photons from π0/η decays, and the azimuthally-symmetric energy distribution of minimum bias events. We also present an outlook on the expected Run II performance in the coming years, including the impact of the ECAL on resonance searches in the mass range up to 1 TeV.

Exploration, Sampling, And Reconstruction of Free Energy Surfaces with Gaussian Process Regression

Practical free energy reconstruction algorithms involve three separate tasks: biasing, measuring some observable, and finally reconstructing the free energy surface from those measurements. In more than one dimension, adaptive schemes make it possible to explore only relatively low lying regions of the landscape by progressively building up the bias toward the negative of the free energy surface so that free energy barriers are eliminated. Most schemes use the final bias as their best estimate of the free energy surface. We show that large gains in computational efficiency, as measured by the reduction of time to solution, can be obtained by separating the bias used for dynamics from the final free energy reconstruction itself. We find that biasing with metadynamics, measuring a free energy gradient estimator, and reconstructing using Gaussian process regression can give an order of magnitude reduction in computational cost.

Performance of the CMS missing transverse momentum reconstruction in pp data at √s = 8 TeV

The performance of missing transverse energy reconstruction algorithms is presented using √s=8 TeV proton-proton (pp) data collected with the CMS detector. Events with anomalous missing transverse energy are studied, and the performance of algorithms used to identify and remove these events is presented. The scale and resolution for missing transverse energy, including the effects of multiple pp interactions (pileup), are measured using events with an identified Z boson or isolated photon, and are found to be well described by the simulation. Novel missing transverse energy reconstruction algorithms developed specifically to mitigate the effects of large numbers of pileup interactions on the missing transverse energy resolution are presented. These algorithms significantly reduce the dependence of the missing transverse energy resolution on pileup interactions. Finally, an algorithm that provides an estimate of the significance of the missing transverse energy is presented, which is used to estimate the compatibility of the reconstructed missing transverse energy with a zero nominal value.

Performance data from the ZEPLIN-III second science run

ZEPLIN-III is a two-phase xenon direct dark matter experiment located at the Boulby Mine (U.K.). After its first science run in 2008 it was upgraded with: an array of low background photomultipliers, a new anti-coincidence detector system with plastic scintillator and an improved calibration system. After 319 days of data taking the second science run ended in May 2011. In this paper we describe the instrument performance with emphasis on the position and energy reconstruction algorithm and summarise the final science results.

Exact dual energy material decomposition from inconsistent rays (MDIR)

Dual energy CT (DECT) allows calculating images that show the spatial distribution of the electron density and the atomic number or, more common, images of two basis material densities. In contrast, the Hounsfield unit that is shown in standard CT images is a measure of the x-ray attenuation, which is a function of the atomic number and electron density. To acquire additional information, DECT measures the object of interest using two different detected x-ray spectra. Most clinical CT scanners realize dual energy CT by fast tube voltage switching or by dual source dual detector arrangements and therefore do not allow measuring geometrically identical lines with each spectrum. Then, it is not possible to preprocess the raw data and calculate dual energy-specific raw data sets. The combination of the information of both spectra rather needs to be carried out in image domain after image reconstruction. Compared to the ideal raw data-based dual energy approaches, those image-based DECT methods are inferior because they are not able to correctly deal with the polychromatic nature of the x-rays. This article proposes a dedicated dual energy reconstruction algorithm for inconsistent rays that correctly accounts for all spectral effects. Material decomposition from inconsistent rays (MDIR) is an iterative method to indirectly perform raw data-based DECT even though different lines were measured for both spectra. Its iterative nature allows treating the x-ray polychromaticity correctly. The iterative process is initialized by density images that were obtained from an image-based material decomposition. Those images suffer from errors that originate from the polychromatic nature of the spectra. These errors are calculated by polychromatic forward projection of each measured line. After correction of the initial material density images, the polychromatic forward projection is repeated with more accurate material density images, yielding a more accurate error calculation. To demonstrate the proposed method, simulations and measurements were performed using clinical and preclinical dual source dual energy CT scanners. Two iterations of MDIR are sufficient to greatly improve the qualitative and quantitative information in material density images. It is shown that banding artifacts, cupping artifacts, and mean density errors can be completely eliminated. Simulations with high geometrical inconsistency between the rays of different spectra indicate that nearly exact material decomposition is possible with MDIR. Furthermore, simulations show that the method works well in the presence of materials with K-edges within the detected spectrum. Phantom measurements using a clinical dual source CT scanner show the elimination of artifacts, which cause up to 4% mean density error. At moderate computational burden, the proposed MDIR algorithm yields images of the same high quality as direct raw data-based DECT methods. In contrast to those, MDIR is applicable to the case of inconsistent rays, as it often occurs in clinical or preclinical CT. Compared to image-based methods MDIR reduces artifacts and improves mean density errors in material density images. All dual energy postprocessing methods that are in use today, such as bone removal, virtual noncontrast images, etc., can be applied to the images provided by MDIR.

ATLAS Tile Calorimeter performance for single particles in beam tests

The modules of the ATLAS Tile hadronic calorimeter underwent extensive tests in the test beams at CERN. Studies were carried out with electrons, muons and hadrons ranging in energy from 10 GeV to 350 GeV. The Tilecal calibration systems and energy reconstruction algorithms were also studied in great details, the associated systematics has been evaluated. The updated calibration scheme led to improved linearity and uniformity of the response.Electrons and muons were used to set and understand the electromagnetic (EM) scale and the uniformity of the calorimeter. The pion response shows the expected behaviour with energy. The performance of the real Tile calorimeter modules to pions in terms of linearity and resolution corresponds well to that of earlier Tilecal prototype modules, after accounting for the different lengths and segmentations of the calorimeters. The experimental results are also compared to MC simulation samples.

Search for a light standard model Higgs boson in the channel

A prospective analysis for the discovery of a light standard model Higgs boson in the CMS experiment at the large hadron collider is presented. The analysis focuses on the inclusive single production p + p → H + X and the Higgs boson decay channel , for a Higgs boson mass MH in the range 120 < MH < 160GeV/c2. A full simulation of the detector response is performed and detailed electron, jet and missing transverse energy reconstruction algorithms are used. Emphasis is put on a realistic treatment of background contamination and systematics. A Higgs boson of mass MH ≳ 134GeV/c2 would be observed with a significance above three standard deviations in the channel alone for an integrated LHC luminosity above 30 fb−1.

Hadron energy measurement with a highly non compensating quartz fiber calorimeter

The HF calorimeter is a hadronic calorimeter composed of iron absorber with quartz fibers as active medium. The Cerenkov light generated by the relativistic components of the shower is detected by an array of photomultipliers. The construction of the calorimeter, which will cover the pseudorapidity interval 2.8-5.2 (0.6-7 degrees) in the CMS experiment at LHC is being completed at CERN. The main physics goal of the HF calorimeter is to tag high energy jets generated by boson-boson fusion events at LHC. In this paper the results from a test beam exposure at the CERN north area test beam will be presented. Details about the energy response and the response uniformity to electrons and hadrons will be presented. The main part of the talk will be devoted to the studies done to optimize the energy reconstruction algorithm for pions in the energy range 20 to 300 GeV. Special care has to be devoted to this task given that, with its e/h=5, this calorimeter is probably one of the most non compensating hadron calorimeters ever built.

Innovative energy reconstruction algorithm for a hadron calorimeter

We suggest a new non-parametrical hadron energy reconstruction algorithm for a combined calorimeter. It uses only the known values of non-compensation (e/h ratios) and the electron calibration constants of the electromagnetic and hadronic compartments of a calorimeter. We demonstrate its performance using the experimental data of the ATLAS prototype combined calorimeter.