skip to main content

This content will become publicly available on May 1, 2023

Title: Novel approach for evaluating detector-related uncertainties in a LArTPC using MicroBooNE data
Abstract Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper presents a novel technique for assessing and propagating LArTPC detector-related systematic uncertainties. The technique makes modifications to simulation waveforms based on a parameterization of observed differences in ionization signals from the TPC between data and simulation, while remaining insensitive to the details of the detector model. The modifications are then used to quantify the systematic differences in low- and high-level reconstructed quantities. This approach could be applied to future LArTPC detectors, such as those used in SBN and DUNE.
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more » ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; « less
Award ID(s):
1913983 1801996
Publication Date:
Journal Name:
The European Physical Journal C
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Jet energy scale and resolution measurements with their associated uncertainties are reported for jets using 36–81 fb $$^{-1}$$ - 1 of proton–proton collision data with a centre-of-mass energy of $$\sqrt{s}=13$$ s = 13   $${\text {Te}}{\text {V}}$$ TeV collected by the ATLAS detector at the LHC. Jets are reconstructed using two different input types: topo-clusters formed from energy deposits in calorimeter cells, as well as an algorithmic combination of charged-particle tracks with those topo-clusters, referred to as the ATLAS particle-flow reconstruction method. The anti- $$k_t$$ k t jet algorithm with radius parameter $$R=0.4$$ R = 0.4 is the primary jet definition used for both jet types. This result presents new jet energy scale and resolution measurements in the high pile-up conditions of late LHC Run 2 as well as a full calibration of particle-flow jets in ATLAS. Jets are initially calibrated using a sequence of simulation-based corrections. Next, several in situ techniques are employed to correct for differences between data and simulation and to measure the resolution of jets. The systematic uncertainties in the jet energy scale for central jets ( $$|\eta |<1.2$$ | η | < 1.2 ) vary from 1% for a wide range of high- $$p_{{\text {T}}}$$ p Tmore »jets ( $$2502.5~{\text {Te}}{\text {V}}$$ > 2.5 TeV ). The relative jet energy resolution is measured and ranges from ( $$24 \pm 1.5$$ 24 ± 1.5 )% at 20  $${\text {Ge}}{\text {V}}$$ GeV to ( $$6 \pm 0.5$$ 6 ± 0.5 )% at 300  $${\text {Ge}}{\text {V}}$$ GeV .« less
  2. A bstract The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS,more »and DUNE.« less
  3. Abstract This paper describes a study of techniques for identifying Higgs bosons at high transverse momenta decaying into bottom-quark pairs, $$H \rightarrow b\bar{b}$$ H → b b ¯ , for proton–proton collision data collected by the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy $$\sqrt{s}=13$$ s = 13   $$\text {TeV}$$ TeV . These decays are reconstructed from calorimeter jets found with the anti- $$k_{t}$$ k t $$R = 1.0$$ R = 1.0 jet algorithm. To tag Higgs bosons, a combination of requirements is used: b -tagging of $$R = 0.2$$ R = 0.2 track-jets matched to the large- R calorimeter jet, and requirements on the jet mass and other jet substructure variables. The Higgs boson tagging efficiency and corresponding multijet and hadronic top-quark background rejections are evaluated using Monte Carlo simulation. Several benchmark tagging selections are defined for different signal efficiency targets. The modelling of the relevant input distributions used to tag Higgs bosons is studied in 36 fb $$^{-1}$$ - 1 of data collected in 2015 and 2016 using $$g\rightarrow b\bar{b}$$ g → b b ¯ and $$Z(\rightarrow b\bar{b})\gamma $$ Z ( → b b ¯ ) γ event selections in data. Both processes are foundmore »to be well modelled within the statistical and systematic uncertainties.« less
  4. Abstract We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg 2 of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 μ K arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly suboptimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be A ϕ = 0.949 ± 0.122 using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist “bias hardening” or linear bias correction, and reducing the systematic uncertainty on A ϕ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain A ϕ along with A L , the amplitude of lensing-like effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easilymore »infer parameters both from an optimal lensing reconstruction and from the delensed CMB, while exactly accounting for the correlation between the two. These results demonstrate the feasibility of the Bayesian approach on real data, and pave the way for future analysis of deep CMB polarization measurements with SPT-3G, Simons Observatory, and CMB-S4, where improvements relative to the QE can reach 1.5 times tighter constraints on A ϕ and seven times lower effective lensing reconstruction noise.« less
  5. ABSTRACT Recent systematic searches for massive black holes (BHs) in local dwarf galaxies led to the discovery of a population of faint active galactic nuclei (AGNs). We investigate the agreement of the BH and AGN populations in the Illustris, TNG, Horizon-AGN, EAGLE, and SIMBA simulations with current observational constraints in low-mass galaxies. We find that some of these simulations produce BHs that are too massive, and that the BH occupation fraction (OF) at z = 0 is not inherited from the simulation seeding modelling. The ability of BHs and their host galaxies to power an AGN depends on BH and galaxy subgrid modelling. The fraction of AGN in low-mass galaxies is not used to calibrate the simulations, and thus can be used to differentiate galaxy formation models. AGN fractions at z = 0 span two orders of magnitude at fixed galaxy stellar mass in simulations, similarly to observational constraints, but uncertainties and degeneracies affect both observations and simulations. The agreement is difficult to interpret due to differences in the masses of simulated and observed BHs, BH OF affected by numerical choices, and an unknown fraction of obscured AGN. Our work advocates for more thorough comparisons with observations to improve the modelling ofmore »cosmological simulations, and our understanding of BH and galaxy physics in the low-mass regime. The mass of BHs, their ability to efficiently accrete gas, and the AGN fraction in low-mass galaxies have important implications for the build-up of the entire BH and galaxy populations with time.« less