Identifying Galaxy Mergers in Observations and Simulations with Deep Learning

Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any differences between these two classifications. With one of the main difficulties of merger studies being the lack of a truth sample, we can use our method to test biases in visually identified merger catalogues. A convolutional neural network architecture was developed and trained in two ways: one with observations from SDSS and one with simulated galaxies from EAGLE, processed to mimic the SDSS observations. The SDSS images were also classified by the simulation trained network and the EAGLE images classified by the observation trained network. The observationally trained network achieves an accuracy of 91.5% while the simulation trained network achieves 65.2% on the visually classified SDSS and physically classified EAGLE images respectively. Classifying the SDSS images with the simulation trained network was less successful, only achieving an accuracy of 64.6%, while classifying the EAGLE images with the observation network was very poor, achieving an accuracy of only 53.0% with preferential assignment to the non-merger classification. This suggests that most of the simulated mergers do not have conspicuous merger features and visually identified merger catalogues from observations are incomplete and biased towards certain merger types. The networks trained and tested with the same data perform the best, with observations performing better than simulations, a result of the observational sample being biased towards conspicuous mergers. Classifying SDSS observations with the simulation trained network has proven to work, providing tantalizing prospects for using simulation trained networks for galaxy identification in large surveys.Comment: Submitted to A&A, revised after first referee report. 20 pages, 22 figures, 14 tables, 1 appendi

Ergodicity breaking in strong and network-forming glassy system

The temperature dependence of the non-ergodicity factor of vitreous GeO$_2$, $f_{q}(T)$, as deduced from elastic and quasi-elastic neutron scattering experiments, is analyzed. The data are collected in a wide range of temperatures from the glassy phase, up to the glass transition temperature, and well above into the undercooled liquid state. Notwithstanding the investigated system is classified as prototype of strong glass, it is found that the temperature- and the $q$-behavior of $f_{q}(T)$ follow some of the predictions of Mode Coupling Theory. The experimental data support the hypothesis of the existence of an ergodic to non-ergodic transition occurring also in network forming glassy systems

Identifying galaxy mergers in observations and simulations with deep learning

Context. Mergers are an important aspect of galaxy formation and evolution. With large upcoming surveys, such as Euclid and LSST, accurate techniques that are fast and efficient are needed to identify galaxy mergers for further study. Aims: We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any differences between these two classifications. As one of the main difficulties of merger studies is the lack of a truth sample, we can use our method to test biases in visually identified merger catalogues. Methods: We developed a convolutional neural network architecture and trained it in two ways: one with observations from SDSS and one with simulated galaxies from EAGLE, processed to mimic the SDSS observations. The SDSS images were also classified by the simulation trained network and the EAGLE images classified by the observation trained network. Results: The observationally trained network achieves an accuracy of 91.5% while the simulation trained network achieves 65.2% on the visually classified SDSS and physically classified EAGLE images respectively. Classifying the SDSS images with the simulation trained network was less successful, only achieving an accuracy of 64.6%, while classifying the EAGLE images with the observation network was very poor, achieving an accuracy of only 53.0% with preferential assignment to the non-merger classification. This suggests that most of the simulated mergers do not have conspicuous merger features and visually identified merger catalogues from observations are incomplete and biased towards certain merger types. Conclusions: The networks trained and tested with the same data perform the best, with observations performing better than simulations, a result of the observational sample being biased towards conspicuous mergers. Classifying SDSS observations with the simulation trained network has proven to work, providing tantalising prospects for using simulation trained networks for galaxy identification in large surveys

A Copper(II) Tris-imidazolylphosphine Complex as a Structural and Functional Model of Flavonol 2,4-Dioxygenase

Reaction of tetrakis(acetonitrile)copper(I) perchlorate ([Cu(NCCH3)4][ClO4]), tris-1-ethyl-4-methylimidazolylphosphine (T1Et4MeIP) (1) and 3-hydroxyflavone (flavH) under ambient conditions produces an in-situ generated flavonol bound copper(II) complex, which converts to a stable green complex that formulates to [Cu(T1Et4MeIP)(flav)][ClO4] (2). The crystal structure of 2 was determined by X-ray diffraction and crystallizes in a triclinic system (P1¯ role= presentation style= box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 14.4px; word-spacing: normal; overflow-wrap: normal; text-wrap: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative; \u3e1¯) with unit cell dimensions of a = 14.537(15) Å, b = 15.794(14) Å, c = 17.044(17) Å, α = 65.58(3)˚, β = 86.80(5)˚, γ = 73.34(4)˚, V = 3376(6) Å3 and Z = 2. While the five-coordinate copper(II) complex is stable under ambient conditions in the solid state, it undergoes oxidative scission of the flavonol pyrone ring under photolytic (300 nm) and/or thermal (120 °C) conditions in the presence of molecular oxygen. The degradative process produces the corresponding methylated products: methylbenzoate, methyl salicylate and N,N-dimethylbenzamide. In addition, the previously undisclosed single crystal X-ray structure of tris-1-ethyl-4-methylimidazolylphosphine (1), T1Et4MeIP, is also reported

Temporal decorrelation of collective oscillations in neural networks with local inhibition and long-range excitation

We consider two neuronal networks coupled by long-range excitatory interactions. Oscillations in the gamma frequency band are generated within each network by local inhibition. When long-range excitation is weak, these oscillations phase-lock with a phase-shift dependent on the strength of local inhibition. Increasing the strength of long-range excitation induces a transition to chaos via period-doubling or quasi-periodic scenarios. In the chaotic regime oscillatory activity undergoes fast temporal decorrelation. The generality of these dynamical properties is assessed in firing-rate models as well as in large networks of conductance-based neurons.Comment: 4 pages, 5 figures. accepted for publication in Physical Review Letter

Nonhuman gamblers: lessons from rodents, primates, and robots

The search for neuronal and psychological underpinnings of pathological gambling in humans would benefit from investigating related phenomena also outside of our species. In this paper, we present a survey of studies in three widely different populations of agents, namely rodents, non-human primates, and robots. Each of these populations offers valuable and complementary insights on the topic, as the literature demonstrates. In addition, we highlight the deep and complex connections between relevant results across these different areas of research (i.e., cognitive and computational neuroscience, neuroethology, cognitive primatology, neuropsychiatry, evolutionary robotics), to make the case for a greater degree of methodological integration in future studies on pathological gambling

Critical Review of Theoretical Models for Anomalous Effects (Cold Fusion) in Deuterated Metals

We briefly summarize the reported anomalous effects in deuterated metals at ambient temperature, commonly known as "Cold Fusion" (CF), with an emphasis on important experiments as well as the theoretical basis for the opposition to interpreting them as cold fusion. Then we critically examine more than 25 theoretical models for CF, including unusual nuclear and exotic chemical hypotheses. We conclude that they do not explain the data.Comment: 51 pages, 4 Figure

Tracking the Spread of the BA.2.86 Lineage in Italy Through Wastewater Analysis.

The emergence of new SARS-CoV-2 variants poses challenges to global surveillance efforts, necessitating swift actions in their detection, evaluation, and management. Among the most recent variants, Omicron BA.2.86 and its sub-lineages have gained attention due to their potential immune evasion properties. This study describes the development of a digital PCR assay for the rapid detection of BA.2.86 and its descendant lineages, in wastewater samples. By using this assay, we analyzed wastewater samples collected in Italy from September 2023 to January 2024. Our analysis revealed the presence of BA.2.86 lineages already in October 2023 with a minimal detection rate of 2% which then rapidly increased, becoming dominant by January 2024, accounting for a prevalence of 62%. The findings emphasize the significance of wastewater-based surveillance in tracking emerging variants and underscore the efficacy of targeted digital PCR assays for environmental monitoring

Potential conservation of circadian clock proteins in the phylum Nematoda as revealed by bioinformatic searches

Although several circadian rhythms have been described in C. elegans, its molecular clock remains elusive. In this work we employed a novel bioinformatic approach, applying probabilistic methodologies, to search for circadian clock proteins of several of the best studied circadian model organisms of different taxa (Mus musculus, Drosophila melanogaster, Neurospora crassa, Arabidopsis thaliana and Synechoccocus elongatus) in the proteomes of C. elegans and other members of the phylum Nematoda. With this approach we found that the Nematoda contain proteins most related to the core and accessory proteins of the insect and mammalian clocks, which provide new insights into the nematode clock and the evolution of the circadian system.Fil: Romanowski, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; ArgentinaFil: Garavaglia, Matías Javier. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Ing.genética y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Goya, María Eugenia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ghiringhelli, Pablo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Ing.genética y Biolog.molecular y Celular. Area Virus de Insectos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Golombek, Diego Andres. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología. Laboratorio de Cronobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Journal Staff

We present the first measurements of the differential cross section d sigma/dp(T)(gamma) for the production of an isolated photon in association with at least two b-quark jets. The measurements consider photons with rapidities vertical bar y(gamma)vertical bar < 1.0 and transverse momenta 30 < p(T)(gamma) < 200 GeV. The b-quark jets are required to have p(T)(jet) > 15 GeVand vertical bar y(jet)vertical bar < 1.5. The ratio of differential production cross sections for gamma + 2 b-jets to gamma + b-jet as a function of p(T)(gamma) is also presented. The results are based on the proton-antiproton collision data at root s = 1.96 TeV collected with the D0 detector at the Fermilab Tevatron Collider. The measured cross sections and their ratios are compared to the next- to- leading order perturbative QCD calculations as well as predictions based on the k(T)- factorization approach and those from the sherpa and pythia Monte Carlo event generators