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Scattering studies with low-energy kaon-proton femtoscopy in proton-proton collisions at the LHC
(2020)
The study of the strength and behaviour of the antikaon-nucleon (K¯¯¯¯N) interaction constitutes one of the key focuses of the strangeness sector in low-energy Quantum Chromodynamics (QCD). In this letter a unique high-precision measurement of the strong interaction between kaons and protons, close and above the kinematic threshold, is presented. The femtoscopic measurements of the correlation function at low pair-frame relative momentum of (K+ p ⊕ K− p¯¯¯) and (K− p ⊕ K+ p¯¯¯) pairs measured in pp collisions at s√ = 5, 7 and 13 TeV are reported. A structure observed around a relative momentum of 58 MeV/c in the measured correlation function of (K− p ⊕ K+ p¯¯¯) with a significance of 4.4. σ constitutes the first experimental evidence for the opening of the (K¯¯¯¯0n⊕K0n¯¯¯) isospin breaking channel due to the mass difference between charged and neutral kaons. The measured correlation functions have been compared to Jülich and Kyoto models in addition to the Coulomb potential. The high-precision data at low relative momenta presented in this work prove femtoscopy to be a powerful complementary tool to scattering experiments and provide new constraints above the K¯¯¯¯N threshold for low-energy QCD chiral models.
Scattering studies with low-energy kaon-proton femtoscopy in
proton–proton collisions at the LHC
(2019)
The study of the strength and behaviour of the antikaon-nucleon (K¯¯¯¯N) interaction constitutes one of the key focuses of the strangeness sector in low-energy Quantum Chromodynamics (QCD). In this letter a unique high-precision measurement of the strong interaction between kaons and protons, close and above the kinematic threshold, is presented. The femtoscopic measurements of the correlation function at low pair-frame relative momentum of (K+ p ⊕ K− p¯¯¯) and (K− p ⊕ K+ p¯¯¯) pairs measured in pp collisions at s√ = 5, 7 and 13 TeV are reported. A structure observed around a relative momentum of 58 MeV/c in the measured correlation function of (K− p ⊕ K+ p¯¯¯) constitutes the first experimental evidence for the opening of the (K¯¯¯¯0n⊕K0n¯¯¯) isospin breaking channel due to the mass difference between charged and neutral kaons. The measured correlation functions have been compared to several models. The high-precision data at low relative momenta presented in this work prove femtoscopy to be a powerful complementary tool to scattering experiments and provide new constraints above the K¯¯¯¯N threshold for low-energy QCD chiral models.
Scattering studies with low-energy kaon-proton femtoscopy in proton–proton collisions at the LHC
(2020)
The study of the strength and behaviour of the antikaon-nucleon (K¯¯¯¯N) interaction constitutes one of the key focuses of the strangeness sector in low-energy Quantum Chromodynamics (QCD). In this letter a unique high-precision measurement of the strong interaction between kaons and protons, close and above the kinematic threshold, is presented. The femtoscopic measurements of the correlation function at low pair-frame relative momentum of (K+ p ⊕ K− p¯¯¯) and (K− p ⊕ K+ p¯¯¯) pairs measured in pp collisions at s√ = 5, 7 and 13 TeV are reported. A structure observed around a relative momentum of 58 MeV/c in the measured correlation function of (K− p ⊕ K+ p¯¯¯) with a significance of 4.4. σ constitutes the first experimental evidence for the opening of the (K¯¯¯¯0n⊕K0n¯¯¯) isospin breaking channel due to the mass difference between charged and neutral kaons. The measured correlation functions have been compared to Jülich and Kyoto models in addition to the Coulomb potential. The high-precision data at low relative momenta presented in this work prove femtoscopy to be a powerful complementary tool to scattering experiments and provide new constraints above the K¯¯¯¯N threshold for low-energy QCD chiral models.
Direct photon production at mid-rapidity in Pb–Pb collisions at √sNN=2.76 TeV was studied in the transverse momentum range 0.9<pT<14 GeV/c. Photons were detected with the highly segmented electromagnetic calorimeter PHOS and via conversions in the ALICE detector material with the e+e− pair reconstructed in the central tracking system. The results of the two methods were combined and direct photon spectra were measured for the 0–20%, 20–40%, and 40–80% centrality classes. For all three classes, agreement was found with perturbative QCD calculations for pT≳5 GeV/c. Direct photon spectra down to pT≈1 GeV/c could be extracted for the 20–40% and 0–20% centrality classes. The significance of the direct photon signal for 0.9<pT<2.1 GeV/c is 2.6σ for the 0–20% class. The spectrum in this pT range and centrality class can be described by an exponential with an inverse slope parameter of (297±12stat±41syst) MeV. State-of-the-art models for photon production in heavy-ion collisions agree with the data within uncertainties.
It is proposed to install an experimental setup in the fixed-target hall of the Nuclotron with the final goal to perform a research program focused on the production of strange matter in heavyion collisions at beam energies between 2 and 6 A GeV. The basic setup will comprise a large acceptance dipole magnet with inner tracking detector modules based on double-sided Silicon micro-strip sensors and GEMs. The outer tracking will be based on the drift chambers and straw tube detector. Particle identification will be based on the time-of-flight measurements. This setup will be sufficient perform a comprehensive study of strangeness production in heavy-ion collisions, including multi-strange hyperons, multi-strange hypernuclei, and exotic multi-strange heavy objects. These pioneering measurements would provide the first data on the production of these particles in heavy-ion collisions at Nuclotron beam energies, and would open an avenue to explore the third (strangeness) axis of the nuclear chart. The extension of the experimental program is related with the study of in-medium effects for vector mesons decaying in hadronic modes. The studies of the NN and NA reactions for the reference is assumed.
The search for short-lived particles is usually the final stage in the chain of event reconstruction and precedes event selection when operating in online mode or physics analysis when operating in offline mode. Most often such short-lived particles are neutral and their search and reconstruction is carried out using their daughter charged particles resulting from their decay.
The use of the missing mass method makes it possible to find and analyze also decays of charged short-lived particles, when one of the daughter particles is neutral and is not registered in the detector system. One of the most known examples of such decays is the decay Σ− → nπ−.
In this paper, we discuss in detail the missing mass method, which was implemented as part of the KF Particle Finder package for the search and analysis of short-lived particles, and describe the use of the method in the STAR experiment (BNL, USA).
The method was used to search for pion (π± → μ±ν) and kaon (K± → μ±ν and K± → π±π0) decays online on the HLT farm in the express production chain. An important feature of the express production chain in the STAR experiment is that it allows one to start calibration, production, and analysis of the data immediately after receiving them.
Here, the particular features and results of the real-time application of the method within the express processing of data obtained in the BES-II program at a beam energy of 3.85 GeV/n when working with a fixed target are presented and discussed.
Dynamic imaging of landmark organelles, such as nuclei, cell membrane, nuclear envelope, and lipid droplets enables image-based phenotyping of functional states of cells. Multispectral fluorescent imaging of landmark organelles requires labor-intensive labeling, limits throughput, and compromises cell health. Virtual staining of label-free images with deep neural networks is an emerging solution for this problem. Multiplexed imaging of cellular landmarks from scattered light and subsequent demultiplexing with virtual staining saves the light spectrum for imaging additional molecular reporters, photomanipulation, or other tasks. Published approaches for virtual staining of landmark organelles are fragile in the presence of nuisance variations in imaging, culture conditions, and cell types. This paper reports model training protocols for virtual staining of nuclei and membranes robust to cell types, cell states, and imaging parameters. We developed a flexible and scalable convolutional architecture, named UNeXt2, for supervised training and self-supervised pre-training. The strategies we report here enable robust virtual staining of nuclei and cell membranes in multiple cell types, including neuromasts of zebrafish, across a range of imaging conditions. We assess the models by comparing the intensity, segmentations, and application-specific measurements obtained from virtually stained and experimentally stained nuclei and membranes. The models rescue the missing label, non-uniform expression of labels, and photobleaching. We share three pre-trained models, named VSCyto3D, VSCyto2D, and VSNeuromast, as well as VisCy, a PyTorch-based pipeline for training, inference, and deployment that leverages the modern OME-Zarr format.
Dynamic imaging of landmark organelles, such as nuclei, cell membrane, nuclear envelope, and lipid droplets enables image-based phenotyping of functional states of cells. Multispectral fluorescent imaging of landmark organelles requires labor-intensive labeling, limits throughput, and compromises cell health. Virtual staining of label-free images with deep neural networks is an emerging solution for this problem. Multiplexed imaging of cellular landmarks from scattered light and subsequent demultiplexing with virtual staining saves the light spectrum for imaging additional molecular reporters, photomanipulation, or other tasks. Published approaches for virtual staining of landmark organelles are fragile in the presence of nuisance variations in imaging, culture conditions, and cell types. This paper reports model training protocols for virtual staining of nuclei and membranes robust to label-free imaging parameters, cell states, and cell types. We developed a flexible and scalable convolutional architecture, named UNeXt2, for supervised training and self-supervised pre-training. The strategies we report here enable robust virtual staining of nuclei and cell membranes in multiple cell types, including neuromasts of zebrafish, across a range of imaging conditions. We assess the models by comparing the intensity, segmentations, and application-specific measurements obtained from virtually stained and experimentally stained nuclei and membranes. The models rescue the missing label, non-uniform expression of labels, and photobleaching. We share three pre-trained models, named VSCyto3D, VSCyto2D, and VSNeuromast, as well as VisCy, a PyTorch-based pipeline for training, inference, and deployment that leverages the modern OME-Zarr format.