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Uniform sampling from the set G(d) of graphs with a given degree-sequence d=(d1,…,dn)∈Nn is a classical problem in the study of random graphs. We consider an analogue for temporal graphs in which the edges are labeled with integer timestamps. The input to this generation problem is a tuple D=(d,T)∈Nn×N>0 and the task is to output a uniform random sample from the set G(D) of temporal graphs with degree-sequence d and timestamps in the interval [1,T]. By allowing repeated edges with distinct timestamps, G(D) can be non-empty even if G(d) is, and as a consequence, existing algorithms are difficult to apply.
We describe an algorithm for this generation problem which runs in expected time O(M) if Δ2+ϵ=O(M) for some constant ϵ>0 and T−Δ=Ω(T) where M=∑idi and Δ=maxidi. Our algorithm applies the switching method of McKay and Wormald [1] to temporal graphs: we first generate a random temporal multigraph and then remove self-loops and duplicated edges with switching operations which rewire the edges in a degree-preserving manner.
Uniform sampling from the set G(d) of graphs with a given degree-sequence d=(d1,…,dn)∈Nn is a classical problem in the study of random graphs. We consider an analogue for temporal graphs in which the edges are labeled with integer timestamps. The input to this generation problem is a tuple D=(d,T)∈Nn×N>0 and the task is to output a uniform random sample from the set G(D) of temporal graphs with degree-sequence d and timestamps in the interval [1,T]. By allowing repeated edges with distinct timestamps, G(D) can be non-empty even if G(d) is, and as a consequence, existing algorithms are difficult to apply.
We describe an algorithm for this generation problem which runs in expected time O(M) if Δ2+ϵ=O(M) for some constant ϵ>0 and T−Δ=Ω(T) where M=∑idi and Δ=maxidi. Our algorithm applies the switching method of McKay and Wormald [1] to temporal graphs: we first generate a random temporal multigraph and then remove self-loops and duplicated edges with switching operations which rewire the edges in a degree-preserving manner.
n this paper we study invasion probabilities and invasion times of cooperative parasites spreading in spatially structured host populations. The spatial structure of the host population is given by a random geometric graph on [0,1]n, n∈N, with a Poisson(N)-distributed number of vertices and in which vertices are connected over an edge when they have a distance of at most rN∈Θ(Nβ−1n) for some 0<β<1 and N→∞. At a host infection many parasites are generated and parasites move along edges to neighbouring hosts. We assume that parasites have to cooperate to infect hosts, in the sense that at least two parasites need to attack a host simultaneously. We find lower and upper bounds on the invasion probability of the parasites in terms of survival probabilities of branching processes with cooperation. Furthermore, we characterize the asymptotic invasion time.
An important ingredient of the proofs is a comparison with infection dynamics of cooperative parasites in host populations structured according to a complete graph, i.e. in well-mixed host populations. For these infection processes we can show that invasion probabilities are asymptotically equal to survival probabilities of branching processes with cooperation.
Furthermore, we build in the proofs on techniques developed in [BP22], where an analogous invasion process has been studied for host populations structured according to a configuration model.
We substantiate our results with simulations.
Parallel global edge switching for the uniform sampling of simple graphs with prescribed degrees
(2023)
The uniform sampling of simple graphs matching a prescribed degree sequence is an important tool in network science, e.g. to construct graph generators or null-models. Here, the Edge Switching Markov Chain (ES-MC) is a common choice. Given an arbitrary simple graph with the required degree sequence, ES-MC carries out a large number of small changes, called edge switches, to eventually obtain a uniform sample. In practice, reasonably short runs efficiently yield approximate uniform samples.
In this work, we study the problem of executing edge switches in parallel. We discuss parallelizations of ES-MC, but find that this approach suffers from complex dependencies between edge switches. For this reason, we propose the Global Edge Switching Markov Chain (G-ES-MC), an ES-MC variant with simpler dependencies. We show that G-ES-MC converges to the uniform distribution and design shared-memory parallel algorithms for ES-MC and G-ES-MC. In an empirical evaluation, we provide evidence that G-ES-MC requires not more switches than ES-MC (and often fewer), and demonstrate the efficiency and scalability of our parallel G-ES-MC implementation.
Stimulated emission depletion (STED) microscopy is a super-resolution technique that surpasses the diffraction limit and has contributed to the study of dynamic processes in living cells. However, high laser intensities induce fluorophore photobleaching and sample phototoxicity, limiting the number of fluorescence images obtainable from a living cell. Here, we address these challenges by using ultra-low irradiation intensities and a neural network for image restoration, enabling extensive imaging of single living cells. The endoplasmic reticulum (ER) was chosen as the target structure due to its dynamic nature over short and long timescales. The reduced irradiation intensity combined with denoising permitted continuous ER dynamics observation in living cells for up to 7 hours with a temporal resolution of seconds. This allowed for quantitative analysis of ER structural features over short (seconds) and long (hours) timescales within the same cell, and enabled fast 3D live-cell STED microscopy. Overall, the combination of ultra-low irradiation with image restoration enables comprehensive analysis of organelle dynamics over extended periods in living cells.
Heavy quarks are useful probes to investigate the properties of the Quark-Gluon Plasma (QGP) produced in heavy-ion collisions at the LHC, since they are produced in initial hard scattering processes. To single out the signals that are characteristic of the QGP, it is nevertheless crucial to understand the primordial heavy-quark production in vacuum, and to disentangle hot from cold nuclear matter effects. Moreover, observations of collective effects in high-multiplicity pp and p-Pb collisions show surprising similarities with those in heavy-ion collisions. Heavy-flavour production in such collisions could give further insight into the underlying processes. The heavy-flavour production can be studied with e+e− pairs from correlated semileptonic decays of heavy-flavour hadrons. Compared to single heavy-flavour measurements, the dielectron yield contains information about the initial kinematical correlations between the charm and anti-charm quarks, which is otherwise not accessible, and is sensitive to soft heavy-flavour production. We report results on correlated e+e− pairs in pp collisions recorded by the ALICE detector at different collision energies. The production of heavy quarks is discussed by comparing the yield of dielectrons from heavy-flavour hadron decays as a function of invariant mass, pair transverse momentum and distance of closest approach to the primary vertex with different Monte Carlo event generators. The heavy-flavour production cross sections are also presented. Results from high-multiplicity pp collisions at √s=13 TeV and the status of the p-Pb analysis at √sNN=5.02 TeV are reported as well.
The production yields of antideuterons and antiprotons are measured in pp collisions at a center-of-mass energy of √s=13 TeV, as a function of transverse momentum (pT) and rapidity (y), for the first time up to |y|=0.7. The measured spectra are used to study the pT and rapidity dependence of the coalescence parameter B2, which quantifies the coalescence probability of antideuterons. The pT and rapidity dependence of the obtained B2 is extrapolated for pT>1.7 GeV/c and |y|>0.7 using the phenomenological antideuteron production model implemented in PYTHIA 8.3 as well as a baryon coalescence afterburner model based on EPOS 3. Such measurements are of interest to the astrophysics community, since they can be used for the calculation of the flux of antinuclei from cosmic rays, in combination with coalescence models.
Measurement of beauty production via non-prompt charm hadrons in p-Pb collisions at √sNN = 5.02 TeV
(2024)
The production cross sections of D0, D+, and Λ+c hadrons originating from beauty-hadron decays (i.e. non-prompt) were measured for the first time at midrapidity in proton−lead (p−Pb) collisions at the center-of-mass energy per nucleon pair of √sNN=5.02 TeV. Nuclear modification factors (RpPb) of non-prompt D0, D+, and Λ+c are calculated as a function of the transverse momentum (pT) to investigate the modification of the momentum spectra measured in p−Pb collisions with respect to those measured in proton−proton (pp) collisions at the same energy. The RpPb measurements are compatible with unity and with the measurements in the prompt charm sector, and do not show a significant pT dependence. The pT-integrated cross sections and pT-integrated RpPb of non-prompt D0 and D+ mesons are also computed by extrapolating the visible cross sections down to pT = 0. The non-prompt D-meson RpPb integrated over pT is compatible with unity and with model calculations implementing modification of the parton distribution functions of nucleons bound in nuclei with respect to free nucleons. The non-prompt Λ+c/D0 and D+/D0 production ratios are computed to investigate hadronisation mechanisms of beauty quarks into mesons and baryons. The measured ratios as a function of pT display a similar trend to that measured for charm hadrons in the same collision system.
Particle production as a function of charged-particle flattenicity in pp collisions at √s = 13 TeV
(2024)
This paper reports the first measurement of the transverse momentum (pT) spectra of primary charged pions, kaons, (anti)protons, and unidentified particles as a function of the charged-particle flattenicity in pp collisions at s√=13 TeV. Flattenicity is a novel event shape observable that is measured in the pseudorapidity intervals covered by the V0 detector, 2.8<η<5.1 and −3.7<η<−1.7. According to QCD-inspired phenomenological models, it shows sensitivity to multiparton interactions and is less affected by biases towards larger pT due to local multiplicity fluctuations in the V0 acceptance than multiplicity. The analysis is performed in minimum-bias (MB) as well as in high-multiplicity events up to pT=20 GeV/c. The event selection requires at least one charged particle produced in the pseudorapidity interval |η|<1. The measured pT distributions, average pT, kaon-to-pion and proton-to-pion particle ratios, presented in this paper, are compared to model calculations using PYTHIA 8 based on color strings and EPOS LHC. The modification of the pT-spectral shapes in low-flattenicity events that have large event activity with respect to those measured in MB events develops a pronounced peak at intermediate pT (2<pT<8 GeV/c), and approaches the vicinity of unity at higher pT. The results are qualitatively described by PYTHIA, and they show different behavior than those measured as a function of charged-particle multiplicity based on the V0M estimator.
A Large Ion Collider Experiment (ALICE) is a high-energy physics experiment, designed to study heavy ion collisions at the European Organization for Nuclear Research (CERN)Large Hadron Collider (LHC). ALICE is built to study the fundamental properties of matter as it existed shortly after the big bang. This requires reading out millions of sensors with high frequency, enabling high statistics for physics analysis, resulting in a considerable computing demand concerning network throughput and processing power. With the ALICE Run 3 upgrade [14], requirements for a High Throughput Computing
(HTC) online processing cluster increased significantly, due to more than an order of magnitude more data than in Run 2, resulting in a processing input rate of up to 900 GB/s. Online (real-time) event reconstruction allows for the compression of the data stream to 130 GB/s, which is stored on disk for physics analysis.
This thesis presents the implementation of the ALICE Event Processing Node (EPN) compute farm, to cope with the Run 3 online computing challenges. Building a Data Centre tailored to ALICE requirements for the Run 3 and Run 4 EPN farm. Providing the operational conditions for a dynamic compute environment of a High Performance Computing (HPC) cluster, with significant load changes in a short time span, when starting or stopping a data-taking run. EPN servers provide the required computing resources for online reconstruction and data compression. The farm includes network connectivity towards First Level Processors (FLPs), requiring reliable throughput of 900 GB/s between FLPs and EPNs and connectivity from the internal InfiniBand network to the CERN Exabyte Object Storage (EOS) Ethernet network, with more than 100 GB/s.
The results of operating the EPN computing infrastructure during the first year of Run 3 LHC collisions are described in the context of the ALICE experiment. The EPN farm was delivering the expected performance for ALICE data-taking. Data Centre environmental conditions remained stable during the last more than two years, in particular during starting and stopping runs, which include significant changes in IT load. Several unforeseen external circumstances lead to increasing demands for the Online Offline System (O2). Higher data rates than anticipated required network performance to exceed the initial design specifications, for the throughput between FLPs and EPNs. In particular, the high throughput from an internal EPN InfiniBand network towards the storage Ethernet network was one of the challenges to overcome.