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Abstract Results are reported for Mn intercalated Zr 2 Te 2 P, where x-ray diffraction , energy dispersive spectroscopy, and transmission electron microscopy measurements reveal that the van der Waals bonded Te–Te layers are partially filled by Zr and Mn ions. This leads to the chemical formulas Zr 0.07 Zr 2 Te 2 P and Mn 0.06 Zr 0.03 Zr 2 Te 2 P for the parent and substituted compounds, respectively. The impact of the Mn ions is seen in the anisotropic magnetic susceptibility, where Curie–Weiss fits to the data indicate that the Mn ions are in the divalent state. Heat capacity and electrical transport measurements reveal metallic behavior, but the electronic coefficient of the heat capacity ( γ Mn ≈ 36.6 mJ (mol·K 2 ) −1 ) is enhanced by comparison to that of the parent compound. Magnetic ordering is seen at T M ≈ 4  K, where heat capacity measurements additionally show that the phase transition is broad, likely due to the disordered Mn distribution. This transition also strongly reduces the electronic scattering seen in the normalized electrical resistance. These results show that Mn substitution simultaneously introduces magnetic interactions and tunes the electronic state, which improves prospects for inducing novel behavior in Zr 2 Te 2 P and the broader family of ternary tetradymites. 

ABSTRACT Ce-based intermetallics are of interest due to the potential to study the interplay of localized magnetic moments and conduction electrons. Our work on Ce-based germanides led to the identification of a new homologous series An+1MnX3n+1 (A = rare earth, M = transition metal, X = tetrels, and n = 1–6). This work presents the single-crystal growth, structure determination, and anisotropic magnetic properties of the n = 4 member of the Cen+1ConGe3n+1 homologous series. Ce5Co4+xGe13−ySny consists of three Ce sites, three Co sites, seven Ge sites, and two Sn sites, and the crystal structure is best modeled in the orthorhombic space group Cmmm where a = 4.3031(8) Å, b = 45.608(13) Å, and c = 4.3264(8) Å, which is in close agreement with the previously reported Sn-free analog where a = 4.265(1) Å, b = 45.175(9) Å, and c = 4.293(3) Å. Anisotropic magnetic measurements show Kondo-like behavior and three magnetic transitions at 6, 4.9, and 2.4 K for Ce5Co4+xGe13−ySn 

High entropy alloys (HEA) are an unusual class of materials where mixtures of elements are stochastically arrayed on a simple crystalline lattice. These systems exhibit remarkable functionality, often along several distinct axes: e.g., the examples [TaNb]_1-x(TiZrHf)_xare high strength and damage resistant refractory metals that also exhibit superconductivity with large upper critical fields. Here we report the discovery of anf-electron containing HEA, [TaNb]_0.31(TiUHf)_0.69, which is the first to include an actinide ion. Similar to the Zr-analogue, this material crystallizes in a body-centered cubic lattice with the lattice constanta = 3.41(1) Å and exhibits phonon mediated superconductivity with a transition temperaturesT_c ≈ 3.2 K and upper critical fieldsH_c2 ≈ 6.4 T. These results expand this class of materials to include actinide elements, shows that superconductivity is robust in this sub-group, and opens the path towards leveraging HEAs as functional waste forms for a variety of radioisotopes.

 

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.

 

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.

 

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.

 

The first observation of the concurrent production of two$J/\psi$mesons in proton-nucleus collisions is presented. The analysis is based on a proton-lead ($p\mathrm{Pb}$) data sample recorded at a nucleon-nucleon center-of-mass energy of 8.16 TeV by the CMS experiment at the CERN LHC and corresponding to an integrated luminosity of$174.6{\mathrm{nb}}^{-1}$. The two$J/\psi$mesons are reconstructed in their${\mu }^{+}{\mu }^{-}$decay channels with transverse momenta$p_{\mathrm{T}}>6.5\mathrm{GeV}$and rapidity$|y|<2.4$. Events where one of the$J/\psi$mesons is reconstructed in the dielectron channel are also considered in the search. The$p\mathrm{Pb}\to J/\psi J/\psi +X$process is observed with a significance of 5.3 standard deviations. The measured inclusive fiducial cross section, using the four-muon channel alone, is$\sigma (p\mathrm{Pb}\to J/\psi J/\psi +X)=22.0\pm 8.9(\mathrm{stat})\pm 1.5(\mathrm{syst})\mathrm{nb}$. A fit of the data to the expected rapidity separation for pairs of$J/\psi$mesons produced in single (SPS) and double (DPS) parton scatterings yields${\sigma }_{\mathrm{SPS}}^{p\mathrm{Pb}\to J/\psi J/\psi +X}=16.5\pm 10.8(\mathrm{stat})\pm 0.1(\mathrm{syst})\mathrm{nb}$and${\sigma }_{\mathrm{DPS}}^{p\mathrm{Pb}\to J/\psi J/\psi +X}=5.4\pm 6.2(\mathrm{stat})\pm 0.4(\mathrm{syst})\mathrm{nb}$, respectively. This latter result can be transformed into a lower bound on the effective DPS cross section, closely related to the squared average interparton transverse separation in the collision, of${\sigma }_{\mathrm{eff}}>1.0\mathrm{mb}$at 95% confidence level.

© 2024 CERN, for the CMS Collaboration2024CERN 

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of$138{\mathrm{fb}}^{-1}$of proton-proton collision data at$\sqrt{s}=13\mathrm{TeV}$, collected in 2016–2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large ’t Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics. With no observed excess of events over the standard model expectation, limits are set on the cross section for production via gluon fusion of a scalar mediator with SUEP-like decays.

© 2024 CERN, for the CMS Collaboration2024CERN