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Clusters of galaxies have proven to be efficient systems in modifying various properties of galaxies, such as star formation or morphology. However, projection effects impose serious challenges in determining how, when, and to what extent galaxies are affected by the cluster environment. Using innovative techniques to classify galaxies based on their history within the cluster, we aim to determine how galaxies of different classes are affected by the cluster environment. We applied the ROGER code to select trajectories of galaxies in the phase space for 35 galaxy clusters from the OmegaWINGS survey. A new algorithm was applied to minimize contamination effects. We found that both morphological transformation and the quenching of star formation begin shortly after galaxies enter the cluster. Even though over the last $2-3$ Gyr, galaxies entering clusters have undergone significant transformations in both their star formation and morphology these transformation processes are not complete, that is, they are not completely quenched and are not early type yet. Backsplash galaxies and recent infallers show a higher fraction of jellyfish galaxies compared to older cluster members, suggesting that the timescale of this phenomenon is typically less than 3 Gyr., Comment: 9 pages, 6 figures. Accepted in A&A

Studies of galaxy populations classified according to their kinematic behaviours and dynamical state using the Projected Phase Space Diagram (PPSD) are affected by misclassification and contamination, leading to systematic errors in determining the characteristics of the different galaxy classes. We propose a method to statistically correct the determination of galaxy properties' distributions accounting for the contamination caused by misclassified galaxies from other classes. Using a sample of massive clusters and galaxies in their surroundings taken from the MultiDark Planck 2 simulation combined with the semi-analytic model of galaxy formation SAG, we compute the confusion matrix associated to a classification scheme in the PPSD. Based on positions in the PPSD, galaxies are classified as cluster members, backsplash galaxies, recent infallers, infalling galaxies, and interlopers. This classification is determined using probabilities calculated by the code ROGER, along with a threshold criterion. By inverting the confusion matrix, we are able to get better determinations of distributions of galaxy properties such as colour. Compared to a direct estimation based solely on the predicted galaxy classes, our method provides better estimates of the mass-dependent colour distribution for the galaxy classes most affected by misclassification: cluster members, backsplash galaxies, and recent infallers. We apply the method to a sample of observed X-ray clusters and galaxies. Our method can be applied to any classification of galaxies in the PPSD, and to any other galaxy property besides colour, provided an estimation of the confusion matrix. Blue, low-mass galaxies in clusters are almost exclusively recent infaller galaxies that have not yet been quenched by the environmental action of the cluster. Backsplash galaxies are on average redder than expected., Comment: 8 pages, 4 figures, accepted for publication in A&A

Context. Green valley (GV) galaxies are objects defined on a color-magnitude, or color-mass, diagram which are associated with a transition from a star-forming to a quiescent state (quenching), or vice versa (rejuvenation). Aims. We study the sub-mm emission of galaxies in the GV and link it with their physical evolutionary properties. Methods. We exploit a semi-analytic model (SAM) for galaxy evolution which includes a detailed treatment of dust production and evolution in galactic contexts. We model the observational properties of simulated galaxies by post-processing the SAM catalogs with the spectral synthesis and radiative transfer code GRASIL. Results. Our model produces a clear bimodality (and thus a GV) in the color-mass diagram, although some tensions arise when compared to observations. After having introduced a new criterion for identifying the GV in any dataset, we find that most blue and GV galaxies in our model are emitters at $250\,{\mu \rm m}$ (with fluxes $\geq 25\,{\rm mJy}$), in keeping with GAMA results. In the color-$S_{250\, \mu \rm m}$ diagram, GV galaxies exhibit intermediate colors yet maintain significant sub-mm fluxes. This occurs because, while specific star formation rates drop sharply during quenching, the dust content remains relatively high during the GV transition, powering sub-mm emission. Rejuvenating galaxies in the GV, which were previously red, have experienced a star formation burst that shifts their color to green, but their $S_{250\, \mu \rm m}$ fluxes remain low due to still low dust mass. Conclusions. Our galaxy evolution model highlights the delay between star formation and dust evolution, showing that sub-mm emission is not always a safe indicator of star formation activity, with quenching (rejuvenating) GV galaxies featuring relatively large (low) sub-mm emission., Comment: 12 pages, 13 figures. Submitted to A&A

The devices designed for the Internet-of-Things encompass a large variety of distinct processor architectures, forming a highly heterogeneous zoo. In order to tackle this, we employ a simulator to estimate the performance of the matrix-matrix multiplication (GEMM) kernel on processors designed to operate at the edge. Our simulator adheres to the modern implementations of GEMM, advocated by GotoBLAS2, BLIS, OpenBLAS, etc., to carefully account for the amount of data transfers across the memory hierarchy of different algorithmic variants of the kernel. %Armed with this tool, A small collection of experiments provide the necessary data to calibrate the simulator and deliver highly accurate estimations of the execution time for a given processor architecture., Comment: 12 pages, 2 Tables, 6 Figures

The large-scale environment of the cosmic web is believed to impact galaxy evolution, but there is still no consensus regarding the mechanisms. We use a semi-analytic model (SAM) galaxy catalog to study the star formation and dust content of local galaxies in different cosmic environments of the cosmic web, namely voids, filaments, walls, and nodes. We find a strong impact of the environment only for galaxies with $M_{\rm stars}\lesssim10^{10.8}\, M_\odot$: the less dense the environment, the larger the star formation rate and dust content at fixed stellar mass. This is attributed to the fact that galaxies in less dense environments typically feature younger stellar populations, a slower evolution of their stellar mass and a delayed star formation compared to galaxies in denser environments. As for galaxies with $M_{\rm stars}\gtrsim 10^{10.8}\, M_\odot$ differences among environments are milder due to the disc instability (DI) driven supermassive black hole (SMBH) growth implemented in the SAM, which makes SMBH growth, and thus galaxy quenching, environment insensitive. We qualitatively test our predictions against observations by identifying environments in the SDSS-DR16 using dust masses derived from the GAMA survey. The agreement is encouraging, particularly at ${\rm log} \, M_{\rm stars}/M_\odot\gtrsim 10.5-11$, where sSFRs and dust masses appear quite environment-insensitive. This result confirms the importance of in situ growth channels of SMBHs., Comment: 21 pages, 12 figures, 3 tables. Accepted for publication in ApJ

We explore the utilization of the Apache TVM open source framework to automatically generate a family of algorithms that follow the approach taken by popular linear algebra libraries, such as GotoBLAS2, BLIS and OpenBLAS, in order to obtain high-performance blocked formulations of the general matrix multiplication (GEMM). % In addition, we fully automatize the generation process, by also leveraging the Apache TVM framework to derive a complete variety of the processor-specific micro-kernels for GEMM. This is in contrast with the convention in high performance libraries, which hand-encode a single micro-kernel per architecture using Assembly code. % In global, the combination of our TVM-generated blocked algorithms and micro-kernels for GEMM 1)~improves portability, maintainability and, globally, streamlines the software life cycle; 2)~provides high flexibility to easily tailor and optimize the solution to different data types, processor architectures, and matrix operand shapes, yielding performance on a par (or even superior for specific matrix shapes) with that of hand-tuned libraries; and 3)~features a small memory footprint., Comment: 35 pages, 22 figures. Submitted to ACM TOMS

The success of neural language models (LMs) on many technological tasks has brought about their potential relevance as scientific theories of language despite some clear differences between LM training and child language acquisition. In this paper we argue that some of the most prominent benchmarks for evaluating the syntactic capacities of LMs may not be sufficiently rigorous. In particular, we show that the template-based benchmarks lack the structural diversity commonly found in the theoretical and psychological studies of language. When trained on small-scale data modeling child language acquisition, the LMs can be readily matched by simple baseline models. We advocate for the use of the readily available, carefully curated datasets that have been evaluated for gradient acceptability by large pools of native speakers and are designed to probe the structural basis of grammar specifically. On one such dataset, the LI-Adger dataset, LMs evaluate sentences in a way inconsistent with human language users. We conclude with suggestions for better connecting LMs with the empirical study of child language acquisition., Comment: To appear in the GenBench 2023 workshop proceedings, the first workshop on (benchmarking) generalisation in NLP. GenBench 2023 will be held at EMNLP 2023 on December 6, 2023

The optimization of the matrix multiplication (or GEMM) has been a need during the last decades. This operation is considered the flagship of current linear algebra libraries such as BLIS, OpenBLAS, or Intel OneAPI because of its widespread use in a large variety of scientific applications. The GEMM is usually implemented following the GotoBLAS philosophy, which tiles the GEMM operands and uses a series of nested loops for performance improvement. These approaches extract the maximum computational power of the architectures through small pieces of hardware-oriented, high-performance code called micro-kernel. However, this approach forces developers to generate, with a non-negligible effort, a dedicated micro-kernel for each new hardware. In this work, we present a step-by-step procedure for generating micro-kernels with the Exo compiler that performs close to (or even better than) manually developed microkernels written with intrinsic functions or assembly language. Our solution also improves the portability of the generated code, since a hardware target is fully specified by a concise library-based description of its instructions., Comment: 11 pages, 18 figures. Presented at CGO 2024. It includes a software artifact step-by-step execution

We study the population of backsplash galaxies at $z=0$ in the outskirts of massive, isolated clusters of galaxies taken from the MDPL2-SAG semi-analytic catalogue. We consider four types of backsplash galaxies according to whether they are forming stars or passive at three stagesin their lifetimes: before entering the cluster, during their first incursion through the cluster, and after they exit the cluster. We analyse several geometric, dynamic, and astrophysical aspects of the four types at the three stages. Galaxies that form stars at all stages account for the majority of the backsplash population ($58\%$) and have stellar masses typically below $M_\star\sim 3\times 10^{10} h^{-1}{\rm M}_\odot$ that avoid the innermost cluster's regions and are only mildly affected by it. In a similar mass range, galaxies that become passive after exiting the cluster ($26\%$) follow orbits characterised by small pericentric distance and a strong deflection by the cluster potential well while suffering a strong loss of both dark matter and gas content. Only a small fraction of our sample ($4\%$) become passive while orbiting inside the cluster. These galaxies have experienced heavy pre-processing and the cluster's tidal stripping and ram pressure provide the final blow to their star formation. Finally, galaxies that are passive before entering the cluster for the first time ($12\%$) are typically massive and are not affected significantly by the cluster. Using the bulge/total mass ratio as a proxy for morphology, we find that a single incursion through a cluster do not result in significant morphological changes in all four types., Comment: Accepted for publication in MNRAS. Comments are welcome

This paper advocates for an intertwined design of the dense linear algebra software stack that breaks down the strict barriers between the high-level, blocked algorithms in LAPACK (Linear Algebra PACKage) and the low-level, architecture-dependent kernels in BLAS (Basic Linear Algebra Subprograms). Specifically, we propose customizing the GEMM (general matrix multiplication) kernel, which is invoked from the blocked algorithms for relevant matrix factorizations in LAPACK, to improve performance on modern multicore processors with hierarchical cache memories. To achieve this, we leverage an analytical model to dynamically adapt the cache configuration parameters of the GEMM to the shape of the matrix operands. Additionally, we accommodate a flexible development of architecture-specific micro-kernels that allow us to further improve the utilization of the cache hierarchy. Our experiments on two platforms, equipped with ARM (NVIDIA Carmel, Neon) and x86 (AMD EPYC, AVX2) multi-core processors, demonstrate the benefits of this approach in terms of better cache utilization and, in general, higher performance. However, they also reveal the delicate balance between optimizing for multi-threaded parallelism versus cache usage.

We use the ROGER code by de los Rios et al. to classify galaxies around a sample of X-ray clusters into five classes according to their positions in the projected phase space diagram: cluster galaxies, backsplash galaxies, recent infallers, infalling galaxies, and interlopers. To understand the effects of the cluster environment to the evolution of galaxies, we compare across the five classes: stellar mass, specific star formation rate, size, and morphology. Following the guidelines of Coenda et al., a separate analysis is carried out for red and blue galaxies. For red galaxies, cluster galaxies differ from the other classes, having a suppressed specific star formation rate, smaller sizes, and are more likely to be classified as ellipticals. Differences are smaller between the other classes, however backsplash galaxies have significantly lower specific star formation rates than early or recent infalling galaxies. For blue galaxies, we find evidence that recent infallers are smaller than infalling galaxies and interlopers, while the latter two are comparable in size. Our results provide evidence that, after a single passage, the cluster environment can diminish a galaxy's star formation, modify its morphology, and can also reduce in size blue galaxies. We find evidence that quenching occurs faster than morphological transformation from spirals to ellipticals for all classes. While quenching is evidently enhanced as soon as galaxies get into clusters, significant morphological transformations require galaxies to experience the action of the physical mechanisms of the cluster for longer timescales., Comment: Accepted in MNRAS, 11 pages, 7 figures

We connect galaxy properties with their orbital classification by analysing a sample of galaxies with stellar mass $M_{\star} \geq 10^{8.5}h^{-1}M_\odot$ residing in and around massive and isolated galaxy clusters with mass $M_{200} > 10^{15}h^{-1}M_\odot$ at redshift $z=0$. The galaxy population is generated by applying the semi-analytic model of galaxy formation SAG on the cosmological simulation MultiDark Planck 2. We classify galaxies considering their real orbits (3D) and their projected phase-space position using the ROGER code (2D). We define five categories: cluster galaxies, galaxies that have recently fallen into a cluster, backsplash galaxies, infalling galaxies, and interloper galaxies. For each class, we analyse the $g-r$ colour, the specific star formation rate (sSFR), and the stellar age, as a function of the stellar mass. For the 3D classes, we find that cluster galaxies have the lowest sSFR, and are the reddest and the oldest, as expected from environmental effects. Backsplash galaxies have properties intermediate between the cluster and recent infaller galaxies. For each 2D class, we find an important contamination by other classes. We find it necessary to separate the galaxy populations in red and blue to perform a more realistic analysis of the 2D data. For the red population, the 2D results are in good agreement with the 3D predictions. Nevertheless, when the blue population is considered, the 2D analysis only provides reliable results for recent infallers, infalling galaxies and interloper galaxies., Comment: 5 figures, 12 pages, accepted for publication in Monthly Notices of the Royal Astronomical Society Main Journal