Alkali antimonides are well established as high efficiency, low intrinsic emittance photocathodes for accelerators and photon detectors. However, conventionally grown alkali antimonide films are polycrystalline with surface disorder and roughness that can limit achievable beam brightness. Ordering the crystalline structure of alkali antimonides has the potential to deliver higher brightness electron beams by reducing surface disorder and enabling the engineering of material properties at the level of atomic layers. In this report, we demonstrate the growth of ordered Cs3Sb films on single crystal substrates 3C-SiC and graphene-coated 4H-SiC using pulsed laser deposition and conventional thermal evaporation growth techniques. The crystalline structures of the Cs3Sb films were examined using reflection high energy electron diffraction and x-ray diffraction diagnostics, while film thickness and roughness estimates were made using x-ray reflectivity. With these tools, we observed ordered domains in less than 10 nm thick films with quantum efficiencies greater than 1% at 530 nm. Moreover, we identify structural features such as Laue oscillations indicative of highly ordered films. We found that Cs3Sb films grew with flat, fiber-textured surfaces on 3C-SiC and with multiple ordered domains and sub-nanometer surface roughness on graphene-coated 4H-SiC under our growth conditions. We identify the crystallographic orientations of Cs3Sb grown on graphene-coated 4H-SiC substrates and discuss the significance of examining the crystal structure of these films for growing epitaxial heterostructures in future experiments.
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We report on the growth and characterization of a new class of photocathode structures for use as electron sources to produce high brightness electron beams for accelerator applications. The sources are realized using III-nitride materials and are designed to leverage the strong polarization field, which is characteristic of this class of materials when grown in their wurtzite crystal structure, to produce a negative electron affinity condition without the use of Cs, possibly allowing these materials to be operated in radio frequency guns. A Quantum Efficiency (QE) of about [Formula: see text] and an emitted electrons’ Mean Transverse Energy (MTE) of about 100 meV are measured at a wavelength of 265 nm. In a vacuum level of [Formula: see text] Torr, the QE does not decrease after more than 24 h of continuous operation. The lowest MTE of about 50 meV is measured at 300 nm along with a QE of [Formula: see text]. Surface characterizations reveal a possible contribution to the MTE from surface morphology, calling for more detailed studies.
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null (Ed.)ABSTRACT In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant H0. However, published state-of-the-art analyses require of order 1 yr of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic uncertainties. With this time delay lens modelling challenge, we aim to assess the level of precision and accuracy of the modelling techniques that are currently fast enough to handle of order 50 lenses, via the blind analysis of simulated data sets. The results in Rungs 1 and 2 show that methods that use only the point source positions tend to have lower precision ($10\!-\!20{{\ \rm per\ cent}}$) while remaining accurate. In Rung 2, the methods that exploit the full information of the imaging and kinematic data sets can recover H0 within the target accuracy (|A| < 2 per cent) and precision (<6 per cent per system), even in the presence of a poorly known point spread function and complex source morphology. A post-unblinding analysis of Rung 3 showed the numerical precision of the ray-traced cosmological simulations to be insufficient to test lens modelling methodology at the percent level, making the results difficult to interpret. A new challenge with improved simulations is needed to make further progress in the investigation of systematic uncertainties. For completeness, we present the Rung 3 results in an appendix and use them to discuss various approaches to mitigating against similar subtle data generation effects in future blind challenges.more » « less
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Free, publicly-accessible full text available January 1, 2026
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Abstract Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.
Free, publicly-accessible full text available December 1, 2025 -
A bstract A measurement is performed of Higgs bosons produced with high transverse momentum (
p T) via vector boson or gluon fusion in proton-proton collisions. The result is based on a data set with a center-of-mass energy of 13 TeV collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb− 1. The decay of a high-p THiggs boson to a boosted bottom quark-antiquark pair is selected using large-radius jets and employing jet substructure and heavy-flavor taggers based on machine learning techniques. Independent regions targeting the vector boson and gluon fusion mechanisms are defined based on the topology of two quark-initiated jets with large pseudorapidity separation. The signal strengths for both processes are extracted simultaneously by performing a maximum likelihood fit to data in the large-radius jet mass distribution. The observed signal strengths relative to the standard model expectation are and$$ {4.9}_{-1.6}^{+1.9} $$ for the vector boson and gluon fusion mechanisms, respectively. A differential cross section measurement is also reported in the simplified template cross section framework.$$ {1.6}_{-1.5}^{+1.7} $$ Free, publicly-accessible full text available December 1, 2025 -
Abstract This paper describes the
Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to runCombine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details ofCombine . However, the online documentation referenced within this paper provides an up-to-date and complete user guide.Free, publicly-accessible full text available December 1, 2025 -
Abstract A search is reported for charge-parity
violation in$$CP$$ decays, using data collected in proton–proton collisions at$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$ recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6$$\sqrt{s} = 13\,\text {Te}\hspace{-.08em}\text {V} $$ , which consists of about 10 billion events containing a pair of b hadrons, nearly all of which decay to charm hadrons. The flavor of the neutral D meson is determined by the pion charge in the reconstructed decays$$\,\text {fb}^{-1}$$ and$${{{\textrm{D}}}^{{*+}}} \rightarrow {{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} $$ . The$${{{\textrm{D}}}^{{*-}}} \rightarrow {\overline{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{-}}} $$ asymmetry in$$CP$$ is measured to be$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$ , where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the$$A_{CP} ({{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} ) = (6.2 \pm 3.0 \pm 0.2 \pm 0.8)\%$$ asymmetry in the$$CP$$ decay. This is the first$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} {{{\mathrm{\uppi }}}^{{-}}} $$ asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state.$$CP$$ Free, publicly-accessible full text available December 1, 2025 -
Abstract The CERN LHC provided proton and heavy ion collisions during its Run 2 operation period from 2015 to 2018. Proton-proton collisions reached a peak instantaneous luminosity of 2.1× 1034cm-2s-1, twice the initial design value, at √(
s )=13 TeV. The CMS experiment records a subset of the collisions for further processing as part of its online selection of data for physics analyses, using a two-level trigger system: the Level-1 trigger, implemented in custom-designed electronics, and the high-level trigger, a streamlined version of the offline reconstruction software running on a large computer farm. This paper presents the performance of the CMS high-level trigger system during LHC Run 2 for physics objects, such as leptons, jets, and missing transverse momentum, which meet the broad needs of the CMS physics program and the challenge of the evolving LHC and detector conditions. Sophisticated algorithms that were originally used in offline reconstruction were deployed online. Highlights include a machine-learning b tagging algorithm and a reconstruction algorithm for tau leptons that decay hadronically.Free, publicly-accessible full text available November 1, 2025 -
Free, publicly-accessible full text available November 1, 2025