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Ionospheric scintillation and fading events over low‐latitude regions are often caused by severely depleted geomagnetic field‐aligned structures known as Equatorial Plasma Bubbles. These events are subject of interest to scientific investigations and concern to technological applications. Over the past several years, most of scintillation studies have focused on the dependence of these events on density gradients, location, local time, geomagnetic conditions, and so forth. This work presents a discussion about the role of the alignment between the signal propagation path and the depleted structures or, equivalently, the geomagnetic field lines, on the observed scintillation and deep fading characteristics. Data from three stations (dip latitudes: 16.13°S, 19.87°S, and 22.05°S) located around the Equatorial Ionization Anomaly (EIA) region were used to assess the amplitude scintillation severity and the deep fading events features under aligned and nonaligned conditions. The results show that the alignment condition plays a crucial role in the occurrence of strong scintillation. The study also revealed that, as stations far from the crests of the EIA are considered, the alignment influence seems to increase, and that a combination of strong plasma density fluctuation and increased aligned path is, presumably, the configuration under which the most severe scintillation and drastic deep fading events are observed. The results indicate that this conjunction is typically met in regions somewhat distinct from that with largest plasma density background over the Brazilian region, therefore, strongest scintillation and largest deep fading rates were observed by a station slightly off‐the EIA peak.

We report the proposal and results of a low‐cost, easy‐to‐build GPS‐based sensor for detection and monitoring ionospheric irregularities through the detection of amplitude scintillation. The system is based on the Raspberry Pi single‐board computer combined with an Adafruit Ultimate GPS peripheral, which is capable of measuring (at 10‐Hz rate) the intensity of the L1 signals transmitted by GPS satellites. We introduce and discuss results of short‐ and long‐term observations obtained with a prototype of this system deployed in Presidente Prudente, a low magnetic latitude site in Brazil. The deployment and observations were carried out to test the ability of the system to detect ionospheric scintillations and, therefore, monitor the occurrence of ionospheric irregularities associated with equatorial spreadF. Our results show that this low‐cost sensor is indeed capable of detecting scintillation events associated with equatorial spreadF. Comparison with simultaneous, collocated measurements made by a commercial scintillation monitor are also presented. The joint observations allowed us to quantify the performance of the low‐cost monitor and to identify sources of potential limitations. While the sensor cannot (and it was not intended to) substitute commercial scintillation monitors, the low cost allows its use in studies of ionospheric irregularities (space weather) that require observations made by distributed arrays of small instruments (DASI). Furthermore, the simplicity of the sensor design stimulates its use in educational and citizen science initiatives.

While low and high‐latitude ionospheric scintillation have been extensively reported, significantly less information is available about the properties of and conditions leading to mid‐latitude scintillations. Here, we report and discuss scintillation observations made in the Southern United States (UT Dallas, 32.99°N, 96.76°W, 43.2°N dip latitude) on June 1st, 2013. The measurements were made by a specialized dual‐frequency GPS‐based scintillation monitor which allowed us to determine main properties of this mid‐latitude scintillation event. Additionally, simultaneous airglow observations and ionospheric total electron content (TEC) maps provided insight on the conditions leading to observed scintillations. Moderate amplitude scintillations (S₄>∼0.4) occurred in both L1 and L2C signals, and severe (S₄ > ∼0.8) events occurred in L2C signals at low (<30°) elevation angles. Phase scintillation accompanied amplitude fadings, with maximum σ_ϕvalues exceeding 0.5 radians in L2C. We also show that the observed phase scintillation magnitudes increased with amplitude scintillation severity. Decorrelation times were mostly between 0.25 and 1.25 s, with mean value around 0.65 s for both L1 and L2C. Frequency scaling of S₄matched fairly well the predictions of weak scattering theory but held for observations of moderate and strong amplitude scintillation as well. Scintillation occurred during the main phase of a modest magnetic storm that, nevertheless, prompted an extreme equatorward movement of the mid‐latitude trough and large background TEC enhancements over the US. Scintillations, however, occurred within TEC and airglow depletions observed over Texas. Finally, scintillation properties including severity and rapidity, and associated TEC signatures are comparable to those associated with equatorial spread F.

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.

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$$ {4.9}_{-1.6}^{+1.9} $$${4.9}_{-1.6}^{+1.9}$and$$ {1.6}_{-1.5}^{+1.7} $$${1.6}_{-1.5}^{+1.7}$for the vector boson and gluon fusion mechanisms, respectively. A differential cross section measurement is also reported in the simplified template cross section framework.

This paper describes theCombinesoftware 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 runCombineand 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.

A search is reported for charge-parity$$CP$$$\mathrm{CP}$violation in$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0$decays, using data collected in proton–proton collisions at$$\sqrt{s} = 13\,\text {Te}\hspace{-.08em}\text {V} $$$\sqrt{s}=13\text{Te}\text{V}$recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6$$\,\text {fb}^{-1}$$${\text{fb}}^{-1}$, 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$${{{\textrm{D}}}^{{*+}}} \rightarrow {{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} $$$\text{D}_{}^{\ast +}\to {\text{D}}^0{\pi }^{+}$and$${{{\textrm{D}}}^{{*-}}} \rightarrow {\overline{{\textrm{D}}}^{{0}}} {{{\mathrm{\uppi }}}^{{-}}} $$$\text{D}_{}^{\ast -}\to {\overline{\text{D}}}^0{\pi }^{-}$. The$$CP$$$\mathrm{CP}$asymmetry in$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} $$${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0$is measured to be$$A_{CP} ({{\textrm{K}} _{\text {S}}^{{0}}} {{\textrm{K}} _{\text {S}}^{{0}}} ) = (6.2 \pm 3.0 \pm 0.2 \pm 0.8)\%$$$A_{\mathrm{CP}}\left({\text{K}}_{\text{S}}^0{\text{K}}_{\text{S}}^0\right)=(6.2\pm 3.0\pm 0.2\pm 0.8)\%$, where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the$$CP$$$\mathrm{CP}$asymmetry in the$${{{\textrm{D}}}^{{0}}} \rightarrow {{\textrm{K}} _{\text {S}}^{{0}}} {{{\mathrm{\uppi }}}^{{+}}} {{{\mathrm{\uppi }}}^{{-}}} $$${\text{D}}^0\to {\text{K}}_{\text{S}}^0{\pi }^{+}{\pi }^{-}$decay. This is the first$$CP$$$\mathrm{CP}$asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state.