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Creators/Authors contains: "Liao, H."

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  1. Abstract

    We present a new volatility basis set (VBS) representation of aromatic secondary organic aerosol (SOA) for atmospheric chemistry models by fitting a statistical oxidation model with aerosol microphysics (SOM‐TOMAS) to results from laboratory chamber experiments. The resulting SOM‐VBS scheme also including previous work on SOA formation from semi‐ and intermediate volatile organic compounds (S/IVOCs) is implemented in the GEOS‐Chem chemical transport model and applied to simulation of observations from the Korea‐United States Air Quality Study (KORUS‐AQ) field campaign over South Korea in May–June 2016. Our SOM‐VBS scheme can simulate the KORUS‐AQ organic aerosol (OA) observations from aircraft and surface sites better than the default schemes used in GEOS‐Chem including for vertical profiles, diurnal cycle, and partitioning between hydrocarbon‐like OA and oxidized OA. Our results confirm the important contributions of oxidized primary OA and aromatic SOA found in previous analyses of the KORUS‐AQ data and further show a large contribution from S/IVOCs. Model source attribution of OA in surface air over South Korea indicates one third from domestic anthropogenic emissions, with a large contribution from toluene and xylenes, one third from external anthropogenic emissions, and one third from natural emissions.

     
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  2. Example-guided image synthesis has been recently attempted to synthesize an image from a semantic label map and an exemplary image. In the task, the additional exemplary image serves to provide style guidance that controls the appearance of the synthesized output. Despite the controllability advantage, the previous models are designed on datasets with specific and roughly aligned objects. In this paper, we tackle a more challenging and general task, where the exemplar is an arbitrary scene image that is semantically unaligned to the given label map. To this end, we first propose a new Masked Spatial-Channel Attention (MSCA) module which models the correspondence between two unstructured scenes via cross-attention. Next, we propose an end-to-end network for joint global and local feature alignment and synthesis. In addition, we propose a novel patch-based self-supervision scheme to enable training. Experiments on the large-scale CCOO-stuff dataset show significant improvements over existing methods. Moreover, our approach provides interpretability and can be readily extended to other tasks including style and spatial interpolation or extrapolation, as well as other content manipulation. 
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  3. Abstract

    Since the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger.

     
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    Free, publicly-accessible full text available May 1, 2025
  4. A<sc>bstract</sc>

    A search for new physics in top quark production with additional final-state leptons is performed using data collected by the CMS experiment in proton-proton collisions at$$ \sqrt{s} $$s= 13 TeV at the LHC during 2016–2018. The data set corresponds to an integrated luminosity of 138 fb1. Using the framework of effective field theory (EFT), potential new physics effects are parametrized in terms of 26 dimension-six EFT operators. The impacts of EFT operators are incorporated through the event-level reweighting of Monte Carlo simulations, which allows for detector-level predictions. The events are divided into several categories based on lepton multiplicity, total lepton charge, jet multiplicity, and b-tagged jet multiplicity. Kinematic variables corresponding to the transverse momentum (pT) of the leading pair of leptons and/or jets as well as thepTof on-shell Z bosons are used to extract the 95% confidence intervals of the 26 Wilson coefficients corresponding to these EFT operators. No significant deviation with respect to the standard model prediction is found.

     
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    Free, publicly-accessible full text available December 1, 2024
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  8. Abstract

    A description is presented of the algorithms used to reconstruct energy deposited in the CMS hadron calorimeter during Run 2 (2015–2018) of the LHC. During Run 2, the characteristic bunch-crossing spacing for proton-proton collisions was 25 ns, which resulted in overlapping signals from adjacent crossings. The energy corresponding to a particular bunch crossing of interest is estimated using the known pulse shapes of energy depositions in the calorimeter, which are measured as functions of both energy and time. A variety of algorithms were developed to mitigate the effects of adjacent bunch crossings on local energy reconstruction in the hadron calorimeter in Run 2, and their performance is compared.

     
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    Free, publicly-accessible full text available November 1, 2024
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  10. Free, publicly-accessible full text available November 1, 2024