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Canard cascading (CC) is observed in dynamical networks with global adaptive coupling. It is a fast-slow phenomenon characterized by a recurrent sequence of fast transitions between distinct and slowly evolving quasi-stationary states. In this letter, we uncover the dynamical mechanisms behind CC, using an illustrative example of globally and adaptively coupled semiconductor lasers, where CC represents sequential switching on and off the lasers. Firstly, we show that CC is a robust and truly adaptive network effect that is scalable with network size and does not occur without adaptation. Secondly, we uncover multiple saddle slow manifolds (unstable quasi-stationary states) linked by heteroclinic orbits (fast transitions) in the phase space of the system. This allows us to identify CC with a novel heteroclinic canard orbit that organises different unstable quasi-stationary states into an intricate fast-slow limit cycle. Although individual quasi-stationary states are unstable (saddles), the CC cycle as a whole is attractive and robust to parameter changes.

Noninterference guarantees that an attacker cannot infer secrets by interacting with a program. Information flow control (IFC) type systems assert noninterference by tracking the level of information learned (pc) and disallowing communication to entities of lesser or unrelated level than the pc. Control flow constructs such as loops are at odds with this pattern because they necessitate downgrading the pc upon recursion to be practical. In a concurrent setting, however, downgrading is not generally safe. This paper utilizes session types to track the flow of information and contributes an IFC type system for message-passing concurrent processes that allows downgrading the pc upon recursion. To make downgrading safe, the paper introduces regrading policies. Regrading policies are expressed in terms of integrity labels, which are also key to safe composition of entities with different regrading policies. The paper develops the type system and proves progress-sensitive noninterference for well-typed processes, ruling out timing attacks that exploit the relative order of messages. The type system has been implemented in a type checker, which supports security-polymorphic processes using local security theories., Comment: Technical report of ECOOP24 paper

The validity of medical studies based on real-world clinical data, such as observational studies, depends on critical assumptions necessary for drawing causal conclusions about medical interventions. Many published studies are flawed because they violate these assumptions and entail biases such as residual confounding, selection bias, and misalignment between treatment and measurement times. Although researchers are aware of these pitfalls, they continue to occur because anticipating and addressing them in the context of a specific study can be challenging without a large, often unwieldy, interdisciplinary team with extensive expertise. To address this expertise gap, we explore the use of large language models (LLMs) as co-pilot tools to assist researchers in identifying study design flaws that undermine the validity of causal inferences. We propose a conceptual framework for LLMs as causal co-pilots that encode domain knowledge across various fields, engaging with researchers in natural language interactions to provide contextualized assistance in study design. We provide illustrative examples of how LLMs can function as causal co-pilots, propose a structured framework for their grounding in existing causal inference frameworks, and highlight the unique challenges and opportunities in adapting LLMs for reliable use in epidemiological research.

Protection of confidential data is an important security consideration of today's applications. Of particular concern is to guard against unintentional leakage to a (malicious) observer, who may interact with the program and draw inference from made observations. Information flow control (IFC) type systems address this concern by statically ruling out such leakage. This paper contributes an IFC type system for message-passing concurrent programs, the computational model of choice for many of today's applications such as cloud computing and IoT applications. Such applications typically either implicitly or explicitly codify protocols according to which message exchange must happen, and to statically ensure protocol safety, behavioral type systems such as session types can be used. This paper marries IFC with session typing and contributes over prior work in the following regards: (1) support of realistic cyclic process networks as opposed to the restriction to tree-shaped networks, (2) more permissive, yet entirely secure, IFC control, exploiting cyclic process networks, and (3) considering deadlocks as another form of side channel, and asserting deadlock-sensitive noninterference (DSNI) for well-typed programs. To prove DSNI, the paper develops a novel logical relation that accounts for cyclic process networks. The logical relation is rooted in linear logic, but drops the tree-topology restriction imposed by prior work., Comment: Extended version of ECOOP24 paper

In many randomized trials, participants are grouped into clusters, such as neighborhoods or schools, and these clusters are assumed to be the independent unit. This assumption, however, might not reflect the underlying dependence structure, with serious consequences to statistical power. First, consider a cluster randomized trial where participants are artificially grouped together for the purposes of randomization. For intervention participants the groups are the basis for intervention delivery, but for control participants the groups are dissolved. Second, consider an individually randomized group treatment trial where participants are randomized and then post-randomization, intervention participants are grouped together for intervention delivery, while the control participants continue with the standard of care. In both trial designs, outcomes among intervention participants will be dependent within each cluster, while outcomes for control participants will be effectively independent. We use causal models to non-parametrically describe the data generating process for each trial design and formalize the conditional independence in the observed data distribution. For estimation and inference, we propose a novel implementation of targeted minimum loss-based estimation (TMLE) accounting for partial clustering and the imbalanced dependence structure. TMLE is a model-robust approach, leverages covariate adjustment and machine learning to improve precision, and facilitates estimation of a large set of causal effects. In finite sample simulations, TMLE achieved comparable or markedly higher statistical power than common alternatives. Finally, application of TMLE to real data from the SEARCH-IPT trial resulted in 20-57\% efficiency gains, demonstrating the real-world consequences of our proposed approach.

The properties of the warm-hot intergalactic medium (WHIM) in the cosmic filaments are among the least quantified in modern astrophysics. eROSITA All Sky Survey (eRASS) provides us with a unique opportunity to study the X-ray emission of the WHIM. We applied both imaging and spectroscopic stacking techniques to the data of the first four eRASS scans to inspect the X-ray emissions from 7817 cosmic filaments identified from Sloan Digital Sky Survey optical galaxy samples. We obtained a 9-sigma significant detection of the total X-ray signal from filaments in the 0.3-1.2 keV band. We introduce a novel method to estimate the contamination fraction from unmasked X-ray halos, active galactic nuclei, and X-ray binaries that are associated with galaxies in filaments. We found an approximately 40% contamination fraction by these unmasked sources, suggesting that the remaining 60% of the signal could be from the WHIM and a 5.4-sigma detection significance of the WHIM. Moreover, we modeled the temperature and baryon density contrast of the detected WHIM by fitting the stacked spectrum and surface brightness profile. The best-fit temperature log(T/k)=6.84+/-0.07 obtained by using a single temperature model is marginally higher than the simulation results, which could be due to the fitting of a single temperature model on a multi-temperature spectrum. The best-fit baryon density contrast log\Delta_b=1.88+/-0.18 generally agrees with the X-ray emitting phases in the IllustrisTNG simulation, suggesting that the broadband X-ray emission traces the high temperature and density end of the entire WHIM population., Comment: 15+7 pages, 11+7 figures, submitted to A&A

We explore halo assembly bias on cluster scales using large samples of superclusters. Leveraging the largest-ever X-ray galaxy cluster and supercluster samples obtained from the first SRG/eROSITA all-sky survey, we construct two subsamples of galaxy clusters which consist of supercluster members (SC) and isolated clusters (ISO) respectively. After correcting the selection effects on redshift, mass, and survey depth, we compute the excess in the concentration of the intracluster gas of isolated clusters with respect to supercluster members, defined as $\delta c_{\rm gas} \equiv c_{\rm gas,ISO}/c_{\rm gas,SC}-1$, to investigate the environmental effect on the concentration of clusters, an inference of halo assembly bias on cluster scales. We find that the average gas mass concentration of isolated clusters is a few percent higher than that of supercluster members, with a maximum significance of $2.8\sigma$. The result on $\delta c_{\rm gas}$ varies with the overdensity ratio $f$ in supercluster identification, cluster mass proxies, and mass ranges, but remains positive in all the measurements. We measure slightly larger $\delta c_{\rm gas}$ when adopting a higher $f$ in supercluster identification. $\delta c_{\rm gas}$ is also larger for low-mass and low-redshift clusters. We perform weak lensing analyses to compare the total mass concentration of the two classes and find a similar trend as obtained from gas mass concentration. Our results are consistent with the prediction of HAB on cluster scales, where halos located in denser environments are less concentrated, and this trend is stronger for halos with lower mass and at lower redshifts. These phenomena can be interpreted by the fact that clusters in denser environments such as superclusters have experienced more mergers than isolated clusters in their assembling history., Comment: Accepted for publication in A&A

In the context of the CMS Phase-2 tracker back-end processing system, two mezzanines based on the Zynq Ultrascale+ Multi-Processor System-on-Chip (MPSoC) device have been developed to serve as centralized slow control and board management solution for the Serenity-family \textcolor{black}{Advanced Telecommunications Computing Architecture (ATCA)} blades. This paper presents the developments of the MPSoC mezzanines to execute the Intelligent Platform Management Controller (IPMC) software in the real-time capable processors of the MPSoC. In coordination with the Shelf Manager, once full-power is enabled, a CentOS-based Linux distribution is executed in the application processors of the MPSoC, on which EMPButler and the Serenity Management Shell (SMASH) are running., Comment: 6 pages, 3 figures

Recent advances in the development of cryogenic particle detectors such as magnetic microcalorimeters (MMCs) allow the fabrication of sensor arrays with an increasing number of pixels. Since these detectors must be operated at the lowest temperatures, the readout of large detector arrays is still quite challenging. This is especially true for the ECHo experiment, which presently aims to simultaneously run 6,000 two-pixel detectors to investigate the electron neutrino mass. For this reason, we developed a readout system based on a microwave SQUID multiplexer ($\mu$MUX) that is operated by a custom software-defined radio (SDR) at room-temperature. The SDR readout electronics consist of three distinct hardware units: a data processing board with a Xilinx ZynqUS+ MPSoC; a converter board that features DACs, ADCs, and a coherent clock distribution network; and a radio frequency front-end board to translate the signals between the baseband and the microwave domains. Here, we describe the characteristics of the full-scale SDR system. First, the generated frequency comb for driving the $\mu$MUX was evaluated. Subsequently, by operating the SDR in direct loopback, the crosstalk of the individual channels after frequency demultiplexing was investigated. Finally, the system was used with a 16-channel $\mu$MUX to evaluate the linearity of the SDR, and the noise contributed to the overall readout setup.

Odd radio circles (ORCs) are a newly discovered class of extended faint radio sources of unknown origin. We report the first detection of diffuse X-ray gas at the location of a low-redshift ORC (z=0.046) known as Cloverleaf ORC. This observation was performed with the XMM-Newton X-ray telescope. The physical extent of the diffuse X-ray emission corresponds to a region of approximately 230 kpc by 160 kpc, lying perpendicular to the radio emission detected by ASKAP. The X-ray spectrum shows characteristics of thermal multiphase gas with temperatures of 1.10+/-0.08 keV and 0.22+/-0.01 keV and a central density of $(4.9\pm0.6)\times10^{-4}$ cm$^{-3}$, indicating that the Cloverleaf ORC resides in a low-mass galaxy group. Using X-ray observations, with hydrostatic equilibrium and isothermal assumptions, we measure the galaxy group to have a gas mass and a total mass of $(7.7\pm 0.8) \times 10^{11}$ M$_{\rm sun}$ and $2.6\pm0.3\times10^{13}$~$M_{\rm sun}$ within the overdensity radius R$_{500}$. The presence of a high-velocity subgroup identified in optical data, the orientation of the brightest cluster galaxy, the disturbed morphologies of galaxies toward the east of the Cloverleaf ORC, and the irregular morphology of the X-ray emission suggest that this system is undergoing a galaxy group merger. The radio power of the ORC could be explained by the shock reacceleration of fossil cosmic rays generated by a previous episode of black hole activity in the central active galactic nucleus., Comment: Accepted for publication in A&A Letters. 8 pages, 6 figures, 2 tables

The evolution of the cluster mass function traces the growth of the linear density perturbations and can be utilized for constraining the parameters of cosmological and alternative gravity models. In this context, we present new constraints on potential deviations from general relativity by investigating the Hu-Sawicki parametrization of the f(R) gravity with the first SRG-eROSITA All-Sky Survey (eRASS1) cluster catalog in the Western Galactic Hemisphere in combination with the overlapping Dark Energy Survey Year 3, KiloDegree Survey and Hyper Supreme Camera data for weak lensing mass calibration. For the first time, we present constraints obtained from cluster abundances only. When we consider massless neutrinos, we find a strict upper limit of log |fR0| < -4.31 at 95% confidence level. Massive neutrinos suppress structure growth at small scales, and thus have the opposite effect of f(R) gravity. We consequently investigate the joint fit of the mass of the neutrinos with the modified gravity parameter. We obtain log |fR0| < -4.12 jointly with \sum m_\nu < 0.44 e.V. at 95% confidence level, tighter than the limits in the literature utilizing cluster counts only. At log |fR0|= - 6, the number of clusters is not significantly changed by the theory. Consequently, we do not find any statistical deviation from general relativity from the study of eRASS1 cluster abundance. Deeper surveys with eROSITA, increasing the number of detected clusters, will further improve constraints on log |fR0| and investigate alternative gravity theories., Comment: 13 pages, 6 figures, submitted to A&A

Number counts of galaxy clusters across redshift are a powerful cosmological probe, if a precise and accurate reconstruction of the underlying mass distribution is performed -- a challenge called mass calibration. With the advent of wide and deep photometric surveys, weak gravitational lensing by clusters has become the method of choice to perform this measurement. We measure and validate the weak gravitational lensing (WL) signature in the shape of galaxies observed in the first 3 years of the DES Y3 caused by galaxy clusters selected in the first all-sky survey performed by SRG/eROSITA. These data are then used to determine the scaling between X-ray photon count rate of the clusters and their halo mass and redshift. We empirically determine the degree of cluster member contamination in our background source sample. The individual cluster shear profiles are then analysed with a Bayesian population model that self-consistently accounts for the lens sample selection and contamination, and includes marginalization over a host of instrumental and astrophysical systematics. To quantify the accuracy of the mass extraction of that model, we perform mass measurements on mock cluster catalogs with realistic synthetic shear profiles. This allows us to establish that hydro-dynamical modelling uncertainties at low lens redshifts ($z<0.6$) are the dominant systematic limitation. At high lens redshift the uncertainties of the sources' photometric redshift calibration dominate. With regard to the X-ray count rate to halo mass relation, we constrain all its parameters. This work sets the stage for a joint analysis with the number counts of eRASS1 clusters to constrain a host of cosmological parameters. We demonstrate that WL mass calibration of galaxy clusters can be performed successfully with source galaxies whose calibration was performed primarily for cosmic shear experiments., Comment: 27 pages, 18 figures, 2 appendices, submitted to A\&A

Characterising galaxy cluster populations from catalog of sources selected in astronomical surveys requires knowledge of sample incompleteness, known as selection function. The first All-Sky Survey (eRASS1) by eROSITA onboard Spectrum Roentgen Gamma (SRG) has enabled the collection of large samples of galaxy clusters detected in the soft X-ray band over the Western Galactic hemisphere. The driving goal consists in constraining cosmological parameters, which puts stringent requirements on accuracy, flexibility and explainability of the selection function models. We use a large set of mock observations of the eRASS1 survey and we process simulated data identically to the real eRASS1 events. We match detected sources to simulated clusters and we associate detections to intrinsic cluster properties. We train a series of models to build selection functions depending only on observable surface brightness data. We develop a second series of models relying on global cluster characteristics such as X-ray luminosity, flux, and expected instrumental count-rate as well as on morphological properties. We validate our models using our simulations and we rank them according to selected performance metrics. We validate the models with datasets of clusters detected in X-rays and via the Sunyaev-Zeldovich effect. We present the complete Bayesian population modelling framework developed for this purpose. Our results reveal the surface brightness characteristics most relevant to cluster selection in the eRASS1 sample, in particular the ambiguous role of central surface brightness at the scale of the instrument resolution. We have produced a series of user-friendly selection function models and demonstrated their validity and their limitations. Our selection function for bright sources reproduces well the catalog matches with external datasets. (abridged), Comment: 24 pages, 31 figures, 2 tables. Submitted to A&A

The cluster mass function traces the growth of linear density perturbations and provides valuable insights into the growth of structures, the nature of dark matter, and the cosmological parameters governing the Universe. The primary science goal of eROSITA, on board the {\it Spectrum Roentgen Gamma (SRG)} mission, launched in 2019, is to constrain cosmology through the evolution of cluster mass function. In this paper, we present the cosmological constraints obtained from 5259 clusters of galaxies detected over an area of 12791~deg$^2$ in the Western Galactic Hemisphere of the eROSITA's first All-Sky Survey (eRASS1). The common footprint region between the eROSITA Survey and DES, KiDS, and HSC surveys is used for calibration of the scaling between X-ray count rate and their total mass through measurements of their weak gravitational lensing signal. eRASS1 cluster abundances constrain the $\Lambda$CDM parameters, which are the energy density of the total matter to $\Omega_{\mathrm{m}}=0.29^{+0.01}_{-0.02}$, and the normalization of the density fluctuations to $\sigma_8=0.88\pm0.02$ and their combination yields $S_8=\sigma_8 (\Omega_\mathrm{m} / 0.3)^{0.5}=0.86\pm0.01$, consistent and at a similar precision with the state-of-the-art CMB measurements. eRASS1 cosmological experiment places a most stringent upper limit on the summed masses of left-handed light neutrinos to $\sum m_\nu< 0.22\mathrm{~eV}$ (95\% confidence interval). Combining eRASS1 cluster abundance measurements with CMB and ground-based neutrino oscillation experiments, we measure the summed neutrino masses to be $\sum m_\nu=0.08_{-0.02}^{+0.03}\mathrm{~eV}$ or $\sum m_\nu=0.12_{-0.01}^{+0.03}\mathrm{~eV}$ depending on the mass hierarchy scenario for neutrino eigenstates. eRASS1 cluster abundances significantly improve the constraints on the dark energy equation of state parameter to $w=-1.12\pm0.12$. (ABRIDGED), Comment: 41 pages, 22 figures, Accepted for publication by A&A

We aim to participate in the calibration of the X-ray photon count rate to halo mass scaling relation of galaxy clusters selected in the first eROSITA All-Sky Survey on the Western Galactic Hemisphere (eRASS1) using KiDS-1000 weak-lensing (WL) data. We measure the radial shear profiles around eRASS1 galaxy clusters using background galaxies in KiDS-1000, as well as the cluster member contamination. Furthermore we provide consistency checks with the other stage-III WL surveys who take part in the eRASS1 mass calibration, DES Y3 and HSC-Y3. We determine the cluster member contamination of eRASS1 clusters present in KiDS-1000 based on source number density profiles, where we account for the obscuration caused by cluster galaxies. The extracted shear profiles, together with the contamination model and the lens sample selection, are then analysed through a Bayesian population model. We calibrate the WL mass bias parameter by analysing realistic synthetic shear profiles from mock cluster catalogues. Our consistency checks between KiDS-1000 and DES Y3 & HSC-Y3 include the comparison of contamination-corrected density contrast profiles employing the union of background sources around common clusters, as well as the individual scaling relation results. We present a global contamination model for eRASS1 clusters in KiDS-1000 and the calibration results of the X-ray photon count rate to halo mass relation. The results of the WL mass bias parameter show that the uncertainty of the multiplicative shear bias dominates the systematic error budget at low clusters redshifts while the uncertainty of our contamination model does at high ones. The cross-checks between the three WL surveys show that they are statistically consistent with each other. This enables for the first time cosmological constraints from clusters calibrated by three state-of-the-art WL surveys. (abridged), Comment: 22 pages, 23 figures

Superclusters of galaxies mark the large-scale overdense regions in the Universe. Superclusters provide an ideal environment to study structure formation and to search for the emission of the intergalactic medium such as cosmic filaments and WHIM. In this work, we present the largest-to-date catalog of X-ray-selected superclusters identified in the first SRG/eROSITA All-Sky Survey (eRASS1). By applying the Friends-of-Friends method on the galaxy clusters detected in eRASS1, we identified 1338 supercluster systems in the western Galactic hemisphere up to redshift 0.8, including 818 cluster pairs and 520 rich superclusters with $\ge 3$ members. The most massive and richest supercluster system is the Shapley supercluster at redshift 0.05 with 45 members and a total mass of $2.58\pm0.51 \times10^{16} M_{\odot}$. The most extensive system has a projected length of 127~Mpc. The sizes of the superclusters we identified in this work are comparable to the structures found with galaxy survey data. We also found a good association between the eRASS1 superclusters and the large-scale structures formed by optical galaxies. 3948 clusters, corresponding to $45\%$ of the cluster sample, were identified as supercluster members. The reliability of each supercluster was estimated by considering the uncertainties in cluster redshifts and peculiar velocities. 63\% of the systems have a reliability larger than 0.7. The eRASS1 supercluster catalog provided in this work represents the most extensive sample of superclusters selected in the X-ray band in terms of the unprecedented sample volume, sky coverage, redshift range, the availability of X-ray properties, and the well-understood selection function of the parent cluster sample, which enables direct comparisons with numerical simulations. This legacy catalog will greatly advance our understanding of superclusters and the cosmic large-scale structure., Comment: A&A in press

The first SRG/eROSITA All-Sky Survey (eRASS1) provides the largest intracluster medium-selected galaxy cluster and group catalog covering the western galactic hemisphere. Compared to samples selected purely on X-ray extent, the sample purity can be enhanced by identifying cluster candidates using optical and near-infrared data from the DESI Legacy Imaging Surveys. Using the red-sequence-based cluster finder eROMaPPer, we measured individual photometric properties (redshift $z_\lambda$, richness $\lambda$, optical center, and BCG position) for 12,000 eRASS1 clusters over a sky area of 13,116 deg$^2$, augmented by 247 cases identified by matching the candidates with known clusters from the literature. The median redshift of the identified eRASS1 sample is $z=0.31$, with 10% of the clusters at $z>0.72$. The photometric redshifts have an accuracy of $\delta z/(1+z)<0.005$ for $0.0595% for $z>0.05$. For these and further quality assessments of the eRASS1 identified catalog, we applied our identification method to a collection of galaxy cluster catalogs in the literature, as well as blindly on the full Legacy Surveys covering 24,069 deg$^2$. Using a combination of these cluster samples, we investigated the velocity dispersion-richness relation, finding $\log(\lambda)=2.401\times\log(\sigma)-5.074$ with an intrinsic scatter of $0.10\pm0.01$ dex. Our main result is the identified eRASS1 cluster catalog with a high purity and a well-defined X-ray selection process, enabling precise cosmological analyses presented in companion papers., Comment: 36 pages, 23 figures, 6 tables. Accepted for publication in A&A

Clusters of galaxies can be used as powerful probes to study astrophysical processes on large scales, test theories of the growth of structure, and constrain cosmological models. The driving science goal of the SRG/eROSITA All-Sky Survey (eRASS) is to assemble a large sample of X-ray-selected clusters with a well-defined selection function to determine the evolution of the mass function and, hence, the cosmological parameters. We present here a catalog of 12247 optically confirmed galaxy groups and clusters detected in the 0.2-2.3 keV as extended X-ray sources in a 13,116deg$^2$ region in the western Galactic hemisphere of the sky, which eROSITA surveyed in its first six months of operation. The clusters in the sample span the redshift range $0.003

Galaxy cluster gas temperatures ($T$) play a crucial role in many cosmological and astrophysical studies. However, it has been shown that $T$ measurements can vary between different X-ray telescopes. These $T$ biases can propagate to several cluster applications for which $T$ can be used. Thus, it is important to accurately cross-calibrate X-ray instruments to account for systematic biases. In this work, we present the cross-calibration between SRG/eROSITA and Chandra/ACIS, and between SRG/eROSITA and XMM-Newton/EPIC, using for the first time a large sample of galaxy cluster $T$. To do so, we use the first eROSITA All-Sky Survey data and a large X-ray flux-limited cluster catalog. We measure X-ray $T$ for 186 independent cluster regions with both SRG/eROSITA and Chandra/ACIS in a self-consistent way, for three energy bands; 0.7-7 keV (full), 0.5-4 keV (soft), and 1.5-7 keV (hard). We do the same with SRG/eROSITA and XMM-Newton/EPIC for 71 different cluster regions and all three bands. We find that SRG/eROSITA measures systematically lower $T$ than the other two instruments. For the full band, SRG/eROSITA returns 20$\%$ and 14$\%$ lower $T$ than Chandra/ACIS and XMM-Newton/EPIC respectively, when the two latter instruments measure $k_{\text{B}}T\approx 3$ keV each. The discrepancy increases to 38\% and 32\% when Chandra/ACIS and XMM-Newton/EPIC measure $k_{\text{B}}T\approx 10$ keV respectively. For low-$T$ galaxy groups, the discrepancy becomes milder. The soft band shows a marginally lower discrepancy than the full band. In the hard band, the cross-calibration of SRG/eROSITA and the other instruments show stronger differences. We could not identify any possible systematic biases that significantly alleviated the tension. Finally, we provide conversion factors between SRG/eROSITA, Chandra/ACIS, and XMM-Newton/EPIC $T$ which will be beneficial for future cluster studies., Comment: 24 pages, 15 figures, accepted in A&A (updated published version, replaced the submitted version v1)

We investigate the impact of AGN feedback, on the entropy and characteristic temperature measurements of galaxy groups detected in the SRG/eROSITA's first All-Sky Survey (eRASS1) to shed light on the characteristics of the feedback mechanisms. We analyze deeper eROSITA observations of 1178 galaxy groups detected in eRASS1. We divide the sample into 271 subsamples and extract average thermodynamic properties, including electron density, temperature, and entropy at three characteristic radii along with the integrated temperature by jointly analyzing X-ray images and spectra following a Bayesian approach. We present the tightest constraints on the impact of AGN feedback through our average entropy and characteristic temperature measurements of the largest group sample used in X-ray studies, incorporating major systematics in our analysis. We find that entropy shows an increasing trend with temperature in the form of a power-law-like relation at the higher intra-group medium temperatures, while for the low mass groups, a slight flattening is observed on the average entropy. Overall, the observed entropy measurements agree well with the earlier measurements in the literature. The comparisons with the state-of-the-art cosmological hydrodynamic simulations (MillenniumTNG, Magneticum, OWL simulations) after the applications of the selection function calibrated for our galaxy groups reveal that observed entropy profiles in the cores are below the predictions of simulations. At the mid-region, the entropy measurements agree well with the Magneticum simulations, whereas the predictions of MillenniumTNG and OWL simulations fall below observations. At the outskirts, the overall agreement between the observations and simulations improves, with Magneticum simulations reproducing the observations the best. Our measurements will pave the way for more realistic AGN feedback implementations in simulations., Comment: 25 pages, 16 figures, 3 tables, Submitted to A&A

The eROSITA telescope array aboard the Spektrum Roentgen Gamma (SRG) satellite began surveying the sky in December 2019, with the aim of producing all-sky X-ray source lists and sky maps of an unprecedented depth. Here we present catalogues of both point-like and extended sources using the data acquired in the first six months of survey operations (eRASS1; completed June 2020) over the half sky whose proprietary data rights lie with the German eROSITA Consortium. We describe the observation process, the data analysis pipelines, and the characteristics of the X-ray sources. With nearly 930000 entries detected in the most sensitive 0.2-2.3 keV energy range, the eRASS1 main catalogue presented here increases the number of known X-ray sources in the published literature by more than 60%, and provides a comprehensive inventory of all classes of X-ray celestial objects, covering a wide range of physical processes. A smaller catalogue of 5466 sources detected in the less sensitive but harder 2.3-5 keV band is the result of the first true imaging survey of the entire sky above 2 keV. We show that the number counts of X-ray sources in eRASS1 are consistent with those derived over narrower fields by past X-ray surveys of a similar depth, and we explore the number counts variation as a function of the location in the sky. Adopting a uniform all-sky flux limit (at 50% completeness) of F_{0.5-2 keV} > 5 \times 10^{-14}$ erg\,s$^{-1}$\,cm$^{-2}$, we estimate that the eROSITA all-sky survey resolves into individual sources about 20% of the cosmic X-ray background in the 1-2 keV range. The catalogues presented here form part of the first data release (DR1) of the SRG/eROSITA all-sky survey. Beyond the X-ray catalogues, DR1 contains all detected and calibrated event files, source products (light curves and spectra), and all-sky maps. Illustrative examples of these are provided., Comment: 39 pages, 23 figures. Accepted for publication in A&A. Accompanying eROSITA-DE Data Release 1

Perinatal epidemiology often aims to evaluate exposures on infant outcomes. When the exposure affects the composition of people who give birth to live infants (e.g., by affecting fertility, behavior, or birth outcomes), this "live birth process" mediates the exposure effect on infant outcomes. Causal estimands previously proposed for this setting include the total exposure effect on composite birth and infant outcomes, controlled direct effects (e.g., enforcing birth), and principal stratum direct effects. Using perinatal HIV transmission in the SEARCH Study as a motivating example, we present two alternative causal estimands: 1) conditional total effects; and 2) conditional stochastic direct effects, formulated under a hypothetical intervention to draw mediator values from some distribution (possibly conditional on covariates). The proposed conditional total effect includes impacts of an intervention that operate by changing the types of people who have a live birth and the timing of births. The proposed conditional stochastic direct effects isolate the effect of an exposure on infant outcomes excluding any impacts through this live birth process. In SEARCH, this approach quantifies the impact of a universal testing and treatment intervention on infant HIV-free survival absent any effect of the intervention on the live birth process, within a clearly defined target population of women of reproductive age with HIV at study baseline. Our approach has implications for the evaluation of intervention effects in perinatal epidemiology broadly, and whenever causal effects within a subgroup are of interest and exposure affects membership in the subgroup.

The theory of Nonequilibrium Green functions (NEGF) has seen a rapid development over the recent three decades. Applications include diverse correlated many-body systems in and out of equilibrium. Very good agreement with experiments and available exact theoretical results could be demonstrated if the proper selfenergy approximations were used. However, full two-time NEGF simulations are computationally costly, as they suffer from a cubic scaling of the computation time with the simulation duration. Recently we have introduced the G1-G2 scheme that exactly reformulates the Kadanoff-Baym ansatz with Hartree-Fock propagators (HF-GKBA) into time-local equations, allowing for a dramatic reduction of the scaling to time-linear scaling [Schluenzen et al., Phys. Rev. Lett. \textbf{124}, 076601 (2020)]. Remarkably, this scaling is achieved quickly, and also for high-level selfenergies, including the nonequilibrium $GW$ and $T$-matrix approximations [Joost et al., Phys. Rev. B \textbf{101}, 245101 (2020)]. Even the dynamically screened ladder approximation is now feasible [Joost et al., Phys. Rev. B \textbf{105}, 165155 (2022)], and also applications to electron-boson systems were demonstrated. Here we present an overview on recent results that were achieved with the G1--G2 scheme. We discuss problems and open questions and present further ideas how to overcome the current limitations of the scheme.We illustrate the G1--G2 scheme by presenting applying it to the excitation dynamics of Hubbard clusters, to optical excitation of graphene, and to charge transfer during stopping of ions by correlated materials.

The Serenity-S1 is a Xilinx Virtex Ultrascale+ based Advanced Telecommunications Computing Architecture (ATCA) processing blade that has been optimised for production. It incorporates many developments from the Serenity-A and Serenity-Z prototype cards and, where possible, adopts solutions being used across CERN. It also uses many new parts because commonly used parts have disappeared from the market during the semiconductor crisis, with only some returning. Improvements to simplify manufacture, the performance of new components, some of the more difficult aspects of procurement, the performance of production-grade Samtec 25\,Gb/s optical firefly parts, and issues with the rack cooling infrastructure are discussed., Comment: 5 pages, 4 figures, TWEPP 2023

The Causal Roadmap outlines a systematic approach to asking and answering questions of cause-and-effect: define the quantity of interest, evaluate needed assumptions, conduct statistical estimation, and carefully interpret results. To protect research integrity, it is essential that the algorithm for statistical estimation and inference be pre-specified prior to conducting any effectiveness analyses. However, it is often unclear which algorithm will perform optimally for the real-data application. Instead, there is a temptation to simply implement one's favorite algorithm -- recycling prior code or relying on the default settings of a computing package. Here, we call for the use of simulations that realistically reflect the application, including key characteristics such as strong confounding and dependent or missing outcomes, to objectively compare candidate estimators and facilitate full specification of the Statistical Analysis Plan. Such simulations are informed by the Causal Roadmap and conducted after data collection but prior to effect estimation. We illustrate with two worked examples. First, in an observational longitudinal study, outcome-blind simulations are used to inform nuisance parameter estimation and variance estimation for longitudinal targeted minimum loss-based estimation (TMLE). Second, in a cluster randomized trial with missing outcomes, treatment-blind simulations are used to examine Type-I error control in Two-Stage TMLE. In both examples, realistic simulations empower us to pre-specify an estimation approach that is expected to have strong finite sample performance and also yield quality-controlled computing code for the actual analysis. Together, this process helps to improve the rigor and reproducibility of our research.

Early detection of cardiac dysfunction through routine screening is vital for diagnosing cardiovascular diseases. An important metric of cardiac function is the left ventricular ejection fraction (EF), where lower EF is associated with cardiomyopathy. Echocardiography is a popular diagnostic tool in cardiology, with ultrasound being a low-cost, real-time, and non-ionizing technology. However, human assessment of echocardiograms for calculating EF is time-consuming and expertise-demanding, raising the need for an automated approach. In this work, we propose using the M(otion)-mode of echocardiograms for estimating the EF and classifying cardiomyopathy. We generate multiple artificial M-mode images from a single echocardiogram and combine them using off-the-shelf model architectures. Additionally, we extend contrastive learning (CL) to cardiac imaging to learn meaningful representations from exploiting structures in unlabeled data allowing the model to achieve high accuracy, even with limited annotations. Our experiments show that the supervised setting converges with only ten modes and is comparable to the baseline method while bypassing its cumbersome training process and being computationally much more efficient. Furthermore, CL using M-mode images is helpful for limited data scenarios, such as having labels for only 200 patients, which is common in medical applications., Comment: Accepted at GCPR 2023

Program equivalence is the fulcrum for reasoning about and proving properties of programs. For noninterference, for example, program equivalence up to the secrecy level of an observer is shown. A powerful enabler for such proofs are logical relations. Logical relations only recently were adopted for session types -- but exclusively for terminating languages. This paper scales logical relations to general recursive session types. It develops a logical relation for progress-sensitive noninterference (PSNI) for intuitionistic linear logic session types (ILLST), tackling the challenges non-termination and concurrency pose, and shows that logical equivalence is sound and complete with regard to closure of weak bisimilarity under parallel composition, using a biorthogonality argument. A distinguishing feature of the logical relation is its stratification with an observation index (as opposed to a step or unfolding index), a crucial shift to make the logical relation closed under parallel composition in a concurrent setting. To demonstrate practicality of the logical relation, the paper develops an information flow control (IFC) refinement type system for ILLST, with support of secrecy-polymorphic processes, and shows that well-typed programs are self-related by the logical relation and thus enjoy PSNI. The refinement type system has been implemented in a type checker, featuring local security theories to support secrecy-polymorphic processes., Comment: arXiv admin note: text overlap with arXiv:2208.13741

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publications in premier vision conferences as well as the growing popularity of ShapeNet (about 51,300 models) and Princeton ModelNet (127,915 models). For the medical domain, we present a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems. As a unique feature, we directly model the majority of shapes on the imaging data of real patients. As of today, MedShapeNet includes 23 dataset with more than 100,000 shapes that are paired with annotations (ground truth). Our data is freely accessible via a web interface and a Python application programming interface (API) and can be used for discriminative, reconstructive, and variational benchmarks as well as various applications in virtual, augmented, or mixed reality, and 3D printing. Exemplary, we present use cases in the fields of classification of brain tumors, facial and skull reconstructions, multi-class anatomy completion, education, and 3D printing. In future, we will extend the data and improve the interfaces. The project pages are: https://medshapenet.ikim.nrw/ and https://github.com/Jianningli/medshapenet-feedback, Comment: 16 pages

Organic photovoltaics (OPVs) are promising candidates for solar-energy conversion, with device efficiencies continuing to increase. However, the precise mechanism of how charges separate in OPVs is not well understood because low dielectric constants produce a strong attraction between the charges, which they must overcome to separate. Separation has been thought to require energetic offsets at donor-acceptor interfaces, but recent materials have enabled efficient charge generation with small offsets, or with none at all in neat materials. Here, we extend delocalised kinetic Monte Carlo (dKMC) to develop a three-dimensional model of charge generation that includes disorder, delocalisation, and polaron formation in every step from photoexcitation to charge separation. Our simulations show that delocalisation dramatically increases charge-generation efficiency, partly by enabling excitons to dissociate in the bulk. Therefore, charge generation can be efficient even in devices with little to no energetic offset, including neat materials. Our findings demonstrate that the underlying quantum-mechanical effect that improves the charge-separation kinetics is faster and longer-distance hops between delocalised states, mediated by hybridised states of exciton and charge-transfer character.

Accurate computational screening of candidate materials promises to accelerate the discovery of higher-efficiency organic photovoltaics (OPVs). However, modelling charge separation in OPVs is challenging because accurate models must include disorder, polaron formation, and charge delocalisation. Delocalised kinetic Monte Carlo (dKMC) includes these three essential ingredients, but it suffers from high computational cost. Recently, we developed jumping kinetic Monte Carlo (jKMC), a computationally cheap and accurate model of delocalised charge transport that models transport over a lattice of identical, spherical polarons. Here, we extend jKMC to describe the separation of a charge-transfer state, showing that this simplified approach can reproduce the considerable improvements in charge-separation efficiencies caused by delocalisation and first seen in dKMC. The low computational cost and simplicity of jKMC allows it to be applied to parameter regimes intractable by dKMC, and ensures jKMC can be easily incorporated into any existing KMC model.

The extended ROentgen Survey with an Imaging Telescope Array (eROSITA) telescope onboard the Spectrum-Roentgen-Gamma (SRG) mission has finished the first eROSITA All-Sky Survey (eRASS:1), and detected 10$^4$ galaxy clusters in the western Galactic hemisphere. In the radio band, the Australian Square Kilometre Array Pathfinder (ASKAP) telescope finished its pilot 1 phase of the project 'Evolutionary Map of the Universe' (EMU) with 220.000 sources in a 270 deg$^2$ field overlapping with eRASS:1. These two surveys are used to study radio-mode Active Galactic Nuclei (AGN) in clusters. In order to understand the efficiency of radio-mode feedback at the centers of galaxy clusters, we relate the radio properties of brightest cluster galaxies (BCG) to the X-ray properties of the host clusters. We identify the central radio sources in eRASS:1 clusters or calculate corresponding upper limits on the radio luminosity. Then, we derive relations between the X-ray properties of the clusters and the radio properties of the corresponding central radio source. We also apply a mid-infrared color criterion using WISE colors to identify AGN. In total we investigate a sample of 75 clusters. We find a statistically significant correlation between the X-ray luminosity of the cluster and the 944 MHz radio luminosity of the corresponding central radio galaxy. There is also a positive trend between the radio power and the largest linear size (LLS) of the radio source. The density and the LLS do not show any correlation. We find that in high luminosity clusters with L_X > $10^{43}$ erg s$^{-1}$ the kinetic luminosity of the radio jets is not longer correlated with the X-ray luminosity and discuss various reasons. We find an anti-correlation between the central cooling time t_cool and the radio luminosity L_R indicating a need for more powerful AGN in clusters with short central cooling times., Comment: 16 pages, 12 figures, accepted for publication in A&A

Environmental neutrons are a source of background for rare event searches (e.g., dark matter direct detection and neutrinoless double beta decay experiments) taking place in deep underground laboratories. The overwhelming majority of these neutrons are produced in the cavern walls by means of intrinsic radioactivity of the rock and concrete. Their flux and spectrum depend on time and location. Precise knowledge of this background is necessary to devise sufficient shielding and veto mechanisms, improving the sensitivity of the neutron-susceptible underground experiments. In this report, we present the design and the expected performance of a mobile neutron detector for the LNGS underground laboratory. The detector is based on capture-gated spectroscopy technique and comprises essentially a stack of plastic scintillator bars wrapped by gadolinium foils. The extensive simulation studies demonstrate that the detector will be capable of measuring ambient neutrons at low flux levels ($\sim$$10^{-6}\,\mathrm{n/cm^2/s}$) at LNGS, where the ambient gamma flux is by about 5 orders of magnitude larger., Comment: Published at JINST