Search for strongly interacting massive particles generating trackless jets in proton-proton collisions at s = 13 TeV

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton-proton collision data corresponding to an integrated luminosity of 16.1 fb - 1 , collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100 GeV are excluded and further sensitivity is explored towards higher masses

Measurement of inclusive very forward jet cross sections in proton-lead collisions at \sqrt{sNN} = 5:02 TeV

Measurements of differential cross sections for inclusive very forward jet production in proton-lead collisions as a function of jet energy are presented. The data were collected with the CMS experiment at the LHC in the laboratory pseudorapidity range −6.6 < η < −5.2. Asymmetric beam energies of 4 TeV for protons and 1.58 TeV per nucleon for Pb nuclei were used, corresponding to a center-of-mass energy per nucleon pair of \sqrt{sNN} = 5:02 TeV. Collisions with either the proton (p+Pb) or the ion (Pb+p) traveling towards the negative η hemisphere are studied. The jet cross sections are unfolded to stable-particle level cross sections with p_{T} ≳ 3 GeV, and compared to predictions from various Monte Carlo event generators. In addition, the cross section ratio of p+Pb and Pb+p data is presented. The results are discussed in terms of the saturation of gluon densities at low fractional parton momenta. None of the models under consideration describes all the data over the full jet-energy range and for all beam configurations. Discrepancies between the differential cross sections in data and model predictions of more than two orders of magnitude are observed

Native diversity buffers against severity of non-native tree invasions.

This is the final version. Available from Nature Research via the DOI in this record. Data availability: Data used in this study can be found in cited references for the Global Naturalized Alien Flora (GloNAF) database6 (non-native status), the KEW Plants of the World database5 (native ranges) and the Global Environmental Composite63,77 (environmental data layers). Plant trait data were extracted from Maynard et al.78. Data from the Global Forest Biodiversity Initiative (GFBI) database57 are not available due to data privacy and sharing restrictions, but can be obtained upon request via Science-I (https://science-i.org/) or GFBI (gfbinitiative.org) and an approval from data contributors.Code availability All code used to complete analyses for the manuscript is available at the following link: https://github.com/thomaslauber/Global-Tree-Invasion. Data analyses were conducted and were visualizations generated in R (v. 4.2.2), Python (v. 3.9.7), Google Earth Engine (earthengine-api 0.1.306), QGIS-LTR (v. 3.16.7) and the ETH Zurich Euler cluster.Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.Swiss National Science FoundationSwiss National Science FoundationBernina FoundationDOB Ecolog

The global biogeography of tree leaf form and habit

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: Tree occurrence data from the Global Forest Biodiversity initiative (GFBi) is available upon request via Science-I (https://science-i.org) or the GFBi website (https://www.gfbiinitiative.org/). Information on leaf habit (evergreen vs deciduous) and leaf form (broadleaved vs needle-leaved) came from the TRY database (https://www.try-db.org). Additional, leaf-type data came from the Tallo dataset (https://zenodo.org/record/6637599). Plot-level soil information came from the World Soil Information Service (WOSIS) dataset (https://www.isric.org/explore/wosis).Code availability: All code is available at https://doi.org/10.5281/zenodo.7967245.Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

Measurement of the mass dependence of the transverse momentum of lepton pairs in Drell–Yan production in proton–proton collisions at √s = 13TeV

Data Availability Statement This manuscript has no associated data or the data will not be deposited. [Authors’ comment: Release and preservation of data used by the CMS Collaboration as the basis for publications is guided by the CMS policy as stated in https://cms-docdb.cern.ch/cgi-bin/PublicDocDB/RetrieveFile?docid=6032 &filename=CMSDataPolicyV1.2.pdf &version=2 CMS data preservation, re-use and open access policy.]A preprint version of the article is available at arXiv:2205.04897v2 [hep-ex], https://arxiv.org/abs/2205.04897v2. Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/SMP-20-003 (CMS Public Pages). Report number: CMS-SMP-20-003, CERN-EP-2022-053.The double differential cross sections of the Drell–Yan lepton pair (ℓ+ℓ- , dielectron or dimuon) production are measured as functions of the invariant mass mℓℓ , transverse momentum pT(ℓℓ) , and φη∗ . The φη∗ observable, derived from angular measurements of the leptons and highly correlated with pT(ℓℓ) , is used to probe the low- pT(ℓℓ) region in a complementary way. Dilepton masses up to 1 TeV are investigated. Additionally, a measurement is performed requiring at least one jet in the final state. To benefit from partial cancellation of the systematic uncertainty, the ratios of the differential cross sections for various mℓℓ ranges to those in the Z mass peak interval are presented. The collected data correspond to an integrated luminosity of 36.3 fb-1 of proton–proton collisions recorded with the CMS detector at the LHC at a centre-of-mass energy of 13 TeV . Measurements are compared with predictions based on perturbative quantum chromodynamics, including soft-gluon resummation.SCOAP3

Measurement of energy correlators inside jets and determination of the strong coupling αS(mZ)

A preprint version of this article is available at arXiv:2402.13864v2 [hep-ex], https://arxiv.org/abs/2402.13864 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/SMP-22-015 (CMS Public Pages). Report number: CMS-SMP-22-015, CERN-EP-2024-010 .Energy correlators that describe energy-weighted distances between two or three particles in a hadronic jet are measured using an event sample of √ = 13  TeV proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of 36.3  fb^−1. The measured distributions are consistent with the trends in the simulation that reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the measured three- and two-particle energy correlator distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading-logarithmic accuracy matched to a next-to-leading-order calculation, the strong coupling is determined at the boson mass: ⁡() = 0.122⁢9+0.0040 −0.0050, the most precise ⁡() value obtained using jet substructure observables.SCOAP3

Observation of electroweak W+W− pair production in association with two jets in proton-proton collisions at √s = 13 TeV

Copyright © 2022 The Author(s). An observation is reported of the electroweak production of a W+W− pair in association with two jets, with both W bosons decaying leptonically. The data sample corresponds to an integrated luminosity of 138 fb−1 of proton-proton collisions at √s = 13 TeV, collected by the CMS detector at the CERN LHC.Events are selected by requiring exactly two opposite-sign leptons (electrons or muons) and two jets with large pseudorapidity separation and high dijet invariant mass. Events are categorized based on the flavor of the final-state leptons. A signal is observed with a significance of 5.6 standard deviations (5.2 expected) with respect to the background-only hypothesis. The measured fiducial cross section is 10.2 ± 2.0 fb and this value is consistent with the standard model prediction of 9.1 ± 0.6 fb.SCOAP3