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Production of K0S, Λ (Λ), Ξ± and Ω± in jets and in the underlying event in pp and p–Pb collisions
(2022)
The production of strange hadrons (K0S, Λ, Ξ±, and Ω±), baryon-to-meson ratios (Λ/K0S, Ξ/K0S, and Ω/K0S), and baryon-to-baryon ratios (Ξ/Λ, Ω/Λ, and Ω/Ξ) associated with jets and the underlying event were measured as a function of transverse momentum (pT) in pp collisions at s√=13 TeV and p-Pb collisions at sNN−−−√=5.02 TeV with the ALICE detector at the LHC. The inclusive production of the same particle species and the corresponding ratios are also reported. The production of multi-strange hadrons, Ξ± and Ω±, and their associated particle ratios in jets and in the underlying event are measured for the first time. In both pp and p-Pb collisions, the baryon-to-meson and baryon-to-baryon yield ratios measured in jets differ from the inclusive particle production for low and intermediate hadron pT (0.6−6 GeV/c). Ratios measured in the underlying event are in turn similar to those measured for inclusive particle production. In pp collisions, the particle production in jets is compared with PYTHIA 8 predictions with three colour-reconnection implementation modes. None of them fully reproduces the data in the measured hadron pT region. The maximum deviation is observed for Ξ± and Ω±, which reaches a factor of about six. In p-Pb collisions, there is no significant event-multiplicity dependence for particle production in jets, in contrast to what is observed in the underlying event. The presented measurements provide novel constraints on hadronisation and its Monte Carlo description. In particular, they demonstrate that the fragmentation of jets alone is insufficient to describe the strange and multi-strange particle production in hadronic collisions at LHC energies.
Production of K0S, Λ (Λ), Ξ± and Ω± in jets and in the underlying event in pp and p–Pb collisions
(2023)
The production of strange hadrons (K0S, Λ, Ξ±, and Ω±), baryon-to-meson ratios (Λ/K0S, Ξ/K0S, and Ω/K0S), and baryon-to-baryon ratios (Ξ/Λ, Ω/Λ, and Ω/Ξ) associated with jets and the underlying event were measured as a function of transverse momentum (pT) in pp collisions at s√=13 TeV and p-Pb collisions at sNN−−−√=5.02 TeV with the ALICE detector at the LHC. The inclusive production of the same particle species and the corresponding ratios are also reported. The production of multi-strange hadrons, Ξ± and Ω±, and their associated particle ratios in jets and in the underlying event are measured for the first time. In both pp and p-Pb collisions, the baryon-to-meson and baryon-to-baryon yield ratios measured in jets differ from the inclusive particle production for low and intermediate hadron pT (0.6−6 GeV/c). Ratios measured in the underlying event are in turn similar to those measured for inclusive particle production. In pp collisions, the particle production in jets is compared with PYTHIA 8 predictions with three colour-reconnection implementation modes. None of them fully reproduces the data in the measured hadron pT region. The maximum deviation is observed for Ξ± and Ω±, which reaches a factor of about six. In p-Pb collisions, there is no significant event-multiplicity dependence for particle production in jets, in contrast to what is observed in the underlying event. The presented measurements provide novel constraints on hadronisation and its Monte Carlo description. In particular, they demonstrate that the fragmentation of jets alone is insufficient to describe the strange and multi-strange particle production in hadronic collisions at LHC energies.
The production of π±, K±, and (p¯¯¯)p is measured in pp collisions at s√=13 TeV in different topological regions. Particle transverse momentum (pT) spectra are measured in the ``toward'', ``transverse'', and ``away'' angular regions defined with respect to the direction of the leading particle in the event. While the toward and away regions contain the fragmentation products of the near-side and away-side jets, respectively, the transverse region is dominated by particles from the Underlying Event (UE). The relative transverse activity classifier, RT=NT/⟨NT⟩, is used to group events according to their UE activity, where NT is the measured charged-particle multiplicity per event in the transverse region and ⟨NT⟩ is the mean value over all the analysed events. The first measurements of identified particle pT spectra as a function of RT in the three topological regions are reported. The yield of high transverse momentum particles relative to the RT-integrated measurement decreases with increasing RT in both the toward and away regions, indicating that the softer UE dominates particle production as RT increases and validating that RT can be used to control the magnitude of the UE. Conversely, the spectral shapes in the transverse region harden significantly with increasing RT. This hardening follows a mass ordering, being more significant for heavier particles. The pT-differential particle ratios (p+p¯¯¯)/(π++π−) and (K++K−)/(π++π−) in the low UE limit (RT→0) approach expectations from Monte Carlo generators such as PYTHIA 8 with Monash 2013 tune and EPOS LHC, where the jet-fragmentation models have been tuned to reproduce e+e− results.
The production of π±, K±, and (p¯¯¯)p is measured in pp collisions at s√=13 TeV in different topological regions. Particle transverse momentum (pT) spectra are measured in the ``toward'', ``transverse'', and ``away'' angular regions defined with respect to the direction of the leading particle in the event. While the toward and away regions contain the fragmentation products of the near-side and away-side jets, respectively, the transverse region is dominated by particles from the Underlying Event (UE). The relative transverse activity classifier, RT=NT/⟨NT⟩, is used to group events according to their UE activity, where NT is the measured charged-particle multiplicity per event in the transverse region and ⟨NT⟩ is the mean value over all the analysed events. The first measurements of identified particle pT spectra as a function of RT in the three topological regions are reported. The yield of high transverse momentum particles relative to the RT-integrated measurement decreases with increasing RT in both the toward and away regions, indicating that the softer UE dominates particle production as RT increases and validating that RT can be used to control the magnitude of the UE. Conversely, the spectral shapes in the transverse region harden significantly with increasing RT. This hardening follows a mass ordering, being more significant for heavier particles. The pT-differential particle ratios (p+p¯¯¯)/(π++π−) and (K++K−)/(π++π−) in the low UE limit (RT→0) approach expectations from Monte Carlo generators such as PYTHIA 8 with Monash 2013 tune and EPOS LHC, where the jet-fragmentation models have been tuned to reproduce e+e− results.
This article reports measurements of the angle between differently defined jet axes in pp collisions at s√=5.02 TeV carried out by the ALICE Collaboration. Charged particles at midrapidity are clustered into jets with resolution parameters R=0.2 and 0.4. The jet axis, before and after Soft Drop grooming, is compared to the jet axis from the Winner-Takes-All (WTA) recombination scheme. The angle between these axes, ΔRaxis, probes a wide phase space of the jet formation and evolution, ranging from the initial high-momentum-transfer scattering to the hadronization process. The ΔRaxis observable is presented for 20<pchjetT<100 GeV/c, and compared to predictions from the PYTHIA 8 and Herwig 7 event generators. The distributions can also be calculated analytically with a leading hadronization correction related to the non-perturbative component of the Collins−Soper−Sterman (CSS) evolution kernel. Comparisons to analytical predictions at next-to-leading-logarithmic accuracy with leading hadronization correction implemented from experimental extractions of the CSS kernel in Drell−Yan measurements are presented. The analytical predictions describe the measured data within 20% in the perturbative regime, with surprising agreement in the non-perturbative regime as well. These results are compatible with the universality of the CSS kernel in the context of jet substructure.
The ALICE Collaboration has made the first measurement at the LHC of J/ψ photoproduction in ultra-peripheral Pb–Pb collisions at sNN=2.76 TeV. The J/ψ is identified via its dimuon decay in the forward rapidity region with the muon spectrometer for events where the hadronic activity is required to be minimal. The analysis is based on an event sample corresponding to an integrated luminosity of about 55 μb−1. The cross section for coherent J/ψ production in the rapidity interval −3.6<y<−2.6 is measured to be dσJ/ψcoh/dy=1.00±0.18(stat)−0.26+0.24(syst) mb. The result is compared to theoretical models for coherent J/ψ production and found to be in good agreement with those models which include nuclear gluon shadowing.
Die folgende Arbeit handelt von einem Human Computer Interaction Interface, welches es gestattet, mit Hilfe von Gesten zu schreiben. Das System ermöglicht seinen Nutzern, neue Gesten hinzuzufügen und zu verwenden. Da Gesten besser erkannt werden können, je genauer die Darstellung der Hände ist, wird diese durch Datenhandschuhe an den Computer übertragen. Die Hände werden einerseits in der Virtual Reality (VR) dargestellt, damit sie der Nutzer sieht. Andererseits werden die Daten, die die Gestenerkennung benötigt, an das Interface weitergeleitet. Die Erkennung der Gesten wird mit Hilfe eines Neuronales Netz (NN) implementiert. Dieses ist in der Lage, Gesten zu unterscheiden, sofern es genügend Trainingsdaten erhalten hat. Die genutzten Gesten sind entweder einhändig oder beidhändig auszuführen. Die Aussagen der Gesten beziehen sich in dieser Arbeit vor allem auf relationale Operatoren, die Beziehungen zwischen Objekten ausdrücken, wie beispielsweise „gleich“ oder „größer gleich“. Abschließend wird in dieser Arbeit ein System geschaffen, das es ermöglicht, mit Gesten Sätze auszudrücken. Dies betrifft das sogenannte gestische Schreiben nach Mehler, Lücking und Abrami 2014. Zu diesem Zweck befindet sich der Nutzer in einem virtuellen Raum mit Objekten, die er verknüpfen kann, wobei er Sätze in einem relationalen Kontext manifestiert.
Die folgende Arbeit handelt von einer Text2Scene Anwendung, welche in der Virtual Reality (VR) umgesetzt wurde. Das System ermöglicht es den Usern aus einer Beschreibung einer Szene, diese virtuell nachzustellen. Dies bietet eine neue Art der Interaktion mit einem Text, die die visuelle Komponente hervorhebt und somit eine Geschichte auf neue Wege erfahrbar macht.
Dazu kann der User einen fertigen Text entweder vom Server zu laden oder einen eigenen erstellen, der dann automatisch verarbeitet wird. Dabei werden die vorhanden physischen Objekte im Text automatisch erkannt und dem User als 3D-Objekte in der virtuellen Umgebung zur Verfügung gestellt. Diese können dann manuell platziert werden und erzeugen dadurch die Szene, die im Ausgangstext beschrieben wurde. Das Ziel der Textverarbeitung ist eine möglichst genaue Beschreibung der Objekte, damit diese zielgerichtet in der Objektdatenbank gesucht werden können.
Bei der Textverarbeitung wird besonderer Wert auf das Erkennen von Teil-Ganz Beziehungen gelegt. Sodass Objekte, die im Text vorkommen und ein Holonym besitzen, automatisch mit diesem verknüpft werden. Gleichzeitig wird die Teil-Ganz Beziehung aber auch in die andere Richtung genauer betrachtet. Die Textverarbeitung soll ferner dazu in der Lage sein, Objekte genauer zu spezifizieren und an den Kontext des Textes anzupassen. Weiterhin wurde das Natural Language Processing (NLP) so ausgebaut, dass der Kontext des Textes erkannt wird und die Objekte entsprechend kategorisiert werden. Die Textverarbeitung wird mithilfe eines Neuronalen Netzes implementiert. Die verwendeten Tools zur Erkennung von Teil-Ganz Beziehungen, Kontext und Spezifikation von Objekten wurden anhand von Texteingaben nach der Genauigkeit der Ausgabe evaluiert.
Zur Nutzung der Textverarbeitung wurde eine virtuelle Szene entwickelt, die das Erstellen von eigenen Szenen aus vorher geladenen beziehungsweise eingegebenen Texten ermöglicht.
Dazu kann der Nutzer manuell oder automatisch Objekte laden lassen, die er dann platzieren kann.