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At least 991 records · Page 55

Search for a W' boson decaying to a vector-like quark and a top or bottom quark in the all-jets final state at $\sqrt{\mathrm{s}}$ = 13 TeV

A search is presented for a heavy W' boson resonance decaying to a B or T vector-like quark and a t or a b quark, respectively. The analysis is performed using proton-proton collisions collected with the CMS detector at the LHC. The data correspond to an integrated luminosity of 138 fb -1 at a center-of-mass energy of 13 TeV. Both decay channels result in a signature with a t quark, a Higgs or Z boson, and a b quark, each produced with a significant Lorentz boost. The all-hadronic decays of the Higgs or Z boson and of the t quark are selected using jet substructure techniques to reduce standard model backgrounds, resulting in a distinct three-jet W' boson decay signature. No significant deviation in data with respect to the standard model background prediction is observed. Upper limits are set at 95% confidence level on the product of the W' boson cross section and the final state branching fraction. A W' boson with a mass below 3.1 TeV is excluded, given the benchmark model assumption of democratic branching fractions. In addition, limits are set based on generalizations of these assumptions. These are the most sensitive limits to date for this final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Transverse momentum spectra at threshold for groomed heavy quark jets

We present the transverse momentum spectrum for a heavy hadron at threshold in a groomed jet initiated by a heavy quark. The cross section is doubly differential in the energy fraction of an identified heavy hadron in the jet and its transverse momentum measured with respect to the groomed (recoil free) jet axis. The grooming is implemented using a soft-drop grooming algorithm and helps us in mitigating the effects of Non-Global logarithms and pile up. For the particular case of a B meson, we identify two distinct regimes of the transverse momentum spectrum and develop an EFT within the formalisms of Soft Collinear Effective Theory (SCET) and Heavy Quark Effective Theory (HQET) for each of these regions. We show how each region can be matched smoothly into the other to provide a prediction for the perturbative transverse momentum spectrum. The EFT also predicts the scaling behavior of the leading non-perturbative power corrections and implements a simple shape function to account for hadronization. We work in the threshold region where the heavy hadron carries most of the energy of the jet since in this regime, we have a very good discriminating power between heavy quark and gluon initiated jets. We observe that the shape of the spectrum is independent of the energy of the jet over a large range of transverse momentum. We propose that this spectrum can be used as a probe of evolution for heavy quark TMD fragmentation function. At the same time, it can be treated as a jet substructure observable for probing Quark-Gluon Plasma (QGP).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Jet charge and machine learning

Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or W boson identification or for quark/gluon discrimination. We explore these methods for the purpose of classifying jets according to their electric charge. We find that both neural networks that incorporate distance within the jet as an input and boosted decision trees including radial distance information can provide significant improvement in jet charge extraction over current methods. Specifically, convolutional, recurrent, and recursive networks can provide the largest improvement over traditional methods, in part by effectively utilizing distance within the jet or clustering history. Furthermore, the advantages of using a fixed-size input representation (as with the CNN) or a small input representation (as with the RNN) suggest that both convolutional and recurrent networks will be essential to the future of modern machine learning at colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Boosting $ H\to b\overline{b} $ with machine learning

High-p T Higgs production at hadron colliders provides a direct probe of the internal structure of the gg → H loop with the H→$b\bar{b}$ decay offering the most statistics due to the large branching ratio. Despite the overwhelming QCD background, recent advances in jet substructure have put the observation of the gg→H→$b\bar{b}$ channel at the LHC within the realm of possibility. In order to enhance the sensitivity to this process, we develop a two-stream convolutional neural network, with one stream acting on jet information and one using global event properties. The neural network significantly increases the discovery potential of a Higgs signal, both for high-p T Standard Model production as well for possible beyond the Standard Model contributions. Unlike most studies for boosted hadronically decaying massive particles, the boosted Higgs search is unique because double b-tagging rejects nearly all background processes that do not have two hard prongs. In this context — which goes beyond state-of-the-art two-prong tagging — the network is studied to identify the origin of the additional information leading to the increased significance. The procedures described here are also applicable to related final states where they can be used to identify additional sources of discrimination power that are not being exploited by current techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for resonances decaying to a pair of Higgs bosons in the $\mathrm{b\overline{b}q\overline{q}'}\ell\nu$ final state in proton-proton collisions at $\sqrt{s}=$ 13 TeV

A search for new massive particles decaying into a pair of Higgs bosons in proton-proton collisions at a center-of-mass energy of 13 TeV is presented. Data were collected with the CMS detector at the LHC, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The search is performed for resonances with a mass between 0.8 and 3.5 TeV using events in which one Higgs boson decays into a bottom quark pair and the other decays into two W bosons that subsequently decay into a lepton, a neutrino, and a quark pair. The Higgs boson decays are reconstructed with techniques that identify final state quarks as substructure within boosted jets. The data are consistent with standard model expectations. Exclusion limits are placed on the product of the cross section and branching fraction for generic spin-0 and spin-2 massive resonances. The results are interpreted in the context of radion and bulk graviton production in models with a warped extra spatial dimension. These are the best results to date from searches for an HH resonance decaying to this final state, and they are comparable to the results from searches in other channels for resonances with masses below 1.5 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Transverse momentum broadening of a jet in quark-gluon plasma: an open quantum system EFT

We utilize the technology of open quantum systems in conjunction with the recently developed effective field theory for forward scattering to address the question of massless jet propagation through a weakly-coupled quark-gluon plasma in thermal equilibrium. We discuss various possible hierarchies of scales that may appear in this problem, by comparing thermal scales of the plasma with relevant scales in the effective field theory. Starting from the Lindblad equation, we derive and solve a master equation for the trans- verse momentum distribution of a massless quark jet, at leading orders both in the strong coupling and in the power counting of the effective field theory. Markovian approximation is justified in the weak coupling limit. Using the solution to the master equation, we study the transverse momentum broadening of a jet as a function of the plasma temperature and the time of propagation. We discuss the physical origin of infrared sensitivity that arises in the solution and a way to handle it in the effective field theory formulation. We suspect that the final measurement constraint can only cut-off leading infrared singularities and the solution to the Markovian master equation resums a logarithmic series. This work is a stepping stone towards understanding jet quenching and jet substructure observables on both light and heavy quark jets as probes of the quark-gluon plasma.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The transverse momentum distribution of hadrons within jets

We study the transverse momentum distribution of hadrons within jets, where the transverse momentum is defined with respect to the standard jet axis. We consider the case where the jet substructure measurement is performed for an inclusive jet sample pp → jet + X. We demonstrate that this observable provides new opportunities to study transverse momentum dependent fragmentation functions (TMDFFs) which are currently poorly constrained from data, especially for gluons. The factorization of the cross section is obtained within Soft Collinear Effective Theory (SCET), and we show that the relevant TMDFFs are the same as for the more traditional processes semi-inclusive deep inelastic scattering (SIDIS) and electron-positron annihilation. Different than in SIDIS, the observable for the in-jet fragmentation does not depend on TMD parton distribution functions which allows for a cleaner and more direct probe of TMDFFs. We present numerical results and compare to available data from the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Resolving boosted jets with XCone

We show how the recently proposed XCone jet algorithm smoothly interpolates between resolved and boosted kinematics. When using standard jet algorithms to reconstruct the decays of hadronic resonances like top quarks and Higgs bosons, one typically needs separate analysis strategies to handle the resolved regime of well-separated jets and the boosted regime of fat jets with substructure. XCone, by contrast, is an exclusive cone jet algorithm that always returns a fixed number of jets, so jet regions remain resolved even when (sub)jets are overlapping in the boosted regime. In this paper, we perform three LHC case studies $-$ dijet resonances, Higgs decays to bottom quarks, and all-hadronic top pairs$-$ that demonstrate the physics applications of XCone over a wide kinematic range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for high-mass diboson resonances with boson-tagged jets in proton-proton collisions at √s = 8 TeV with the ATLAS detector

A search is performed for narrow resonances decaying into WW, WZ, or ZZ boson pairs using 20.3 fb -1 of proton-proton collision data at a centre-of-mass energy of √s = 8 TeV recorded with the ATLAS detector at the Large Hadron Collider. Diboson resonances with masses in the range from 1.3 to 3.0 TeV are sought after using the invariant mass distribution of dijets where both jets are tagged as a boson jet, compatible with a highly boosted W or Z boson decaying to quarks, using jet mass and substructure properties. The largest deviation from a smoothly falling background in the observed dijet invariant mass distribution occurs around 2 TeV in the WZ channel, with a global significance of 2.5 standard deviations. Exclusion limits at the 95% confidence level are set on the production cross section times branching ratio for the WZ final state of a new heavy gauge boson, W', and for the WW and ZZ final states of Kaluza-Klein excitations of the graviton in a bulk Randall-Sundrum model, as a function of the resonance mass. As a result, W' bosons with couplings predicted by the extended gauge model in the mass range from 1.3 to 1.5 TeV are excluded at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for dark matter in proton-proton collisions at 8 TeV with missing transverse momentum and vector boson tagged jets

A search is presented for an excess of events with large missing transverse momentum in association with at least one highly energetic jet, in a data sample of proton-proton collisions at a centre-of-mass energy of 8 TeV. The data correspond to an integrated luminosity of 19.7 fb$^{−1}$ collected by the CMS experiment at the LHC. The results are interpreted using a set of simplified models for the production of dark matter via a scalar, pseudoscalar, vector, or axial vector mediator. Additional sensitivity is achieved by tagging events consistent with the jets originating from a hadronically decaying vector boson. This search uses jet substructure techniques to identify hadronically decaying vector bosons in both Lorentz-boosted and resolved scenarios. This analysis yields improvements of 80% in terms of excluded signal cross sections with respect to the previous CMS analysis using the same data set. No significant excess with respect to the standard model expectation is observed and limits are placed on the parameter space of the simplified models. Mediator masses between 80 and 400 GeV in the scalar and pseudoscalar models, and up to 1.5 TeV in the vector and axial vector models, are excluded.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Inclusive search for highly boosted Higgs bosons decaying to bottom quark-antiquark pairs in proton-proton collisions at $\sqrt{s} =$ 13 TeV

A search for standard model Higgs bosons (H) produced with transverse momentum (p$_{T}$) greater than 450 GeV and decaying to bottom quark-antiquark pairs ($ \mathrm{b}\overline{\mathrm{b}} $) is performed using proton-proton collision data collected by the CMS experiment at the LHC at $ \sqrt{s} $ = 13 TeV. The data sample corresponds to an integrated luminosity of 137 fb$^{−1}$. The search is inclusive in the Higgs boson production mode. Highly Lorentz-boosted Higgs bosons decaying to $ \mathrm{b}\overline{\mathrm{b}} $ are reconstructed as single large-radius jets, and are identified using jet substructure and a dedicated b tagging technique based on a deep neural network. The method is validated with Z →$ \mathrm{b}\overline{\mathrm{b}} $ decays. For a Higgs boson mass of 125 GeV, an excess of events above the background assuming no Higgs boson production is observed with a local significance of 2.5 standard deviations (σ), while the expectation is 0.7. The corresponding signal strength and local significance with respect to the standard model expectation are μ$_{H}$ = 3.7 ± 1.2(stat)$ {}_{-0.7}^{+0.8} $(syst)$ {}_{-0.5}^{+0.8} $(theo) and 1.9 σ. Additionally, an unfolded differential cross section as a function of Higgs boson p$_{T}$ for the gluon fusion production mode is presented, assuming the other production modes occur at the expected rates.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for a heavy resonance decaying to a top quark and a W boson at $\sqrt{s}$ = 13 TeV in the fully hadronic final state

A search for a heavy resonance decaying to a top quark and a W boson in the fully hadronic final state is presented. The analysis is performed using data from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb -1 recorded by the CMS experiment at the LHC. The search is focused on heavy resonances, where the decay products of each top quark or W boson are expected to be reconstructed as a single, large-radius jet with a distinct substructure. The production of an excited bottom quark, b*, is used as a benchmark when setting limits on the cross section for a heavy resonance decaying to a top quark and a W boson. The hypotheses of b* quarks with left-handed, right-handed, and vector-like chiralities are excluded at 95% confidence level for masses below 2.6, 2.8, and 3.1 TeV, respectively. These are the most stringent limits on the b* quark mass to date, extending the previous best limits by almost a factor of two.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of boosted Higgs bosons produced via vector boson fusion or gluon fusion in the H →$ \textrm{b}\overline{\textrm{b}} $ decay mode using LHC proton-proton collision data at $ \sqrt{s} $ = 13 TeV

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$_{T}$ Higgs 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} $ and $ {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.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗

Structure/function relationships in the rosette cellulose synthesis complex illuminated by an evolutionary perspective

Cellulose microfibrils are a key component of plant cell walls, which in turn compose most of our renewable biomaterials. Consequently, there is considerable interest in understanding how cellulose microfibrils are made in living cells by the plant cellulose synthesis complex (CSC). This remarkable multi-subunit complex contains cellulose synthase (CESA) proteins, and it is often called a rosette due to its six-lobed shape. Each CSC moves within the plasma membrane as it spins a strong cellulose microfibril in its wake. To accomplish this biological manufacturing process, the CESAs harvest an activated sugar substrate from the cytoplasm for use in the polymerization of glucan chains. An elongating glucan is simultaneously translocated across the plasma membrane by each CESA, where the group of chains emanating from one CSC co-crystallizes into a cellulose microfibril that becomes part of the assembling cell wall. Here we review major advances in understanding CESA and CSC structure/function relationships since 2013, when ground-breaking insights about the structure of cellulose synthases in bacteria and plants were published. We additionally discuss: (a) the relationship of CSC substructure to the size of the fundamental cellulose fibril; (b) an evolutionary perspective on the driving force behind the existence of hetero-oligomeric CSCs that currently appear to dominate in land plants; and (c) how cellulose properties may be regulated by CESA and CSC activity. Finally, we also pose major questions that still remain in this rapidly changing and exciting research field.

59 BASIC BIOLOGICAL SCIENCES↗

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules

Abstract An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. Graphical abstract OFraMP applied to paclitaxel (ATB ID 35922).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microstructural development in DED stainless steels: applying welding models to elucidate the impact of processing and alloy composition

Austenitic stainless steel microstructures produced by directed energy deposition (DED)are analogous to those developed during welding, particularly high energy density welding. To better understand microstructural development during DED, theories of microstructural evolution,which have been established to contextualize weld microstructures, are applied in this study to microstructural development in DED austenitic stainless steels. Phenomenological welding models that describe the development of oxide inclusions, compositional microsegregation, ferrite,matrix austenite grains, and dislocation substructures are utilized to clarify microstructural evolution during deposition of austenitic stainless steels. Two different alloys, 304L and 316L, arecompared to demonstrate the broad applicability of this framework for understanding microstmctural development during the DED process. Despite differences in grain morphology and solidification mode for these two alloys (which can be attributed to compositional differences),similar tensile properties are achieved. It is the fine-scale compositional segregation and dislocation structures that ultimately determine the strength of these materials. The evolution of microsegregation and dislocation structures is shown to be dependent on the rapid solidification and thermomechanical history of the DED processing method and not the composition of the starting material.

36 MATERIALS SCIENCE↗

Influence of Thermomechanical Treatment on Structural-Phase Transformations and Mechanical Properties of the Cu–Al–Ni Shape-Memory Alloys

Using the methods of optical and electron microscopy and electron and X-ray diffraction analyses, the influence of thermomechanical treatment on the mechanical properties, average grain size, and structural and phase transformations is investigated in the Cu–Al–Ni triple alloys exhibiting a shape memory effect. In the alloys under study with a fixed content of 3wt% Ni the concentration of aluminum was varied from 9 to 14 wt%. It is shown that in the alloys subjected to thermal treatment, including forging and homogenizing annealing using controlled recrystallization in the austenitic state followed by quenching, the grain-boundary disintegration and segregation disappear. It is found out that the microstructure of the alloys in the hot-forged and hardened states with the content of aluminum 9–10 wt%. consists of the grains of the average dimensions within 60–80 μm, with the content of aluminum 10–12 wt% – 100–350 μm, while in the alloys with the content of aluminum up to 14 12 wt% the average grain size reaches 1 mm. According to the data of mechanical testing at room temperature, with a decrease in the content of aluminum the ultimate tensile strength (σ{sub UTS}), the yield strength (σ{sub М}) and the relative elongation (δ) increase. An improvement of the mechanical properties of the alloys is attributed to the grain structure refinement of the β{sub 2}-austenite and package substructure of the β'{sub 1}-and γ'{sub 1}-martensites as the content of aluminum in the alloys decreases. For instance, in the fine-grained alloys containing 9.2 and 9.5 wt% Al the value of relative elongation remains at a high level (>10%), while for the other alloys with 10–14 wt% Al it does not exceed 5%. As the content of aluminum in the alloys decreases, the character of the specimen fracture under uniaxial tension changes (from brittle to ductile).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗