Markov Chain Monte Carlo Analysis Research Articles

Variational inference for acceleration of SN Ia photometric distance estimation with BayeSN

Abstract Type Ia supernovae (SNe Ia) are standarizable candles whose observed light curves can be used to infer their distances, which can in turn be used in cosmological analyses. As the quantity of observed SNe Ia grows with current and upcoming surveys, increasingly scalable analyses are necessary to take full advantage of these new datasets for precise estimation of cosmological parameters. Bayesian inference methods enable fitting SN Ia light curves with robust uncertainty quantification, but traditional posterior sampling using Markov Chain Monte Carlo (MCMC) is computationally expensive. We present an implementation of variational inference (VI) to accelerate the fitting of SN Ia light curves using the BayeSN hierarchical Bayesian model for time-varying SN Ia spectral energy distributions (SEDs). We demonstrate and evaluate its performance on both simulated light curves and data from the Foundation Supernova Survey with two different forms of surrogate posterior – a multivariate normal and a custom multivariate zero-lower-truncated normal distribution – and compare them with the Laplace Approximation and full MCMC analysis. To validate of our variational approximation, we calculate the pareto-smoothed importance sampling (PSIS) diagnostic, and perform variational simulation-based calibration (VSBC). The VI approximation achieves similar results to MCMC but with an order-of-magnitude speedup for the inference of the photometric distance moduli. Overall, we show that VI is a promising method for scalable parameter inference that enables analysis of larger datasets for precision cosmology.

High Spectral Resolution Observations of Propynal (HCCCHO) toward TMC-1 from the GOTHAM Large Program on the GBT

We used new high spectral resolution observations of propynal (HCCCHO) toward TMC-1 and in the laboratory to update the spectral line catalog available for transitions of HCCCHO—specifically at frequencies lower than 30 GHz, which were previously discrepant in a publicly available catalog. The observed astronomical frequencies provided a high enough spectral resolution that, when combined with high-resolution (∼2 kHz) measurements taken in the laboratory, a new, consistent fit to both the laboratory and astronomical data was achieved. Now with a nearly exact (<1 kHz) frequency match to the J = 2–1 and 3–2 transitions in the astronomical data, using a Markov Chain Monte Carlo analysis, a best fit to the total HCCCHO column density of 7.28−1.94+4.08×1012 cm−2 was found with a surprisingly low excitation temperature of just over 3 K. This column density is around a factor of 5 times larger than reported in previous studies. Finally, this work highlights that care is needed when using publicly available spectral catalogs to characterize astronomical spectra. The availability of these catalogs is essential to the success of modern astronomical facilities and will only become more important as the next generation of facilities comes online.

Constraining the equation of state parametrization in Hořava-Lifshitz gravity

In this paper, we investigate the late-time cosmic accelerated expansion using various equations of state parametrizations within the framework of Hořava-Lifshitz gravity. We utilize Markov Chain Monte Carlo (MCMC) analysis to constrain the parameters of each proposed model, employing observational Hubble data and Type Ia supernovae. Additionally, we analyze and plot the deceleration parameters for each model. Our findings suggest that the Universe has recently transitioned from a phase of deceleration to acceleration in all the models considered. We also analyzed the behavior of the energy conditions for each proposed model within the framework of Hořava-Lifshitz gravity, specifically at the present epoch (z=0). To further assess the effectiveness of these models, we apply both the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) to compare their performance against the standard ΛCDM model. Our results provide valuable insights into how different models perform relative to ΛCDM, offering a comprehensive evaluation of their viability in describing the Universe's accelerated expansion.

Influence of scalar field in massive particle motion in JNW spacetime

In this paper, we investigated the motion of massive particles in the presence of scalar and gravitational fields, particularly focusing on the Janis-Newman-Winicour (JNW) naked singularity solution. It is shown that the innermost stable circular orbit radius strongly depends on scalar coupling parameter. Additionally, we explored the radiation reaction effects on particle dynamics, incorporating a reaction term into the motion equations. Numerical simulations indicated minimal impact on particle trajectories from radiation reaction. We also examined the oscillatory motion of particles around compact objects in the JNW spacetime, focusing on radial and vertical oscillations. Our analysis indicated that the scalar field’s coupling parameter and the spacetime deformation parameter n significantly alter the fundamental frequencies of these oscillations. Furthermore, we studied quasiperiodic oscillations (QPOs) in x-ray binaries, using the relativistic precession model to analyze upper- and lower-frequency relationships. Our results indicated that increasing parameters (n and gs) shifts the frequency ratio of 3∶2 QPOs closer to the naked singularity, with n decreasing and gs increasing both frequencies. Finally, we analyzed QPO data from four selected x-ray binary systems using Markov chain Monte Carlo analysis to constrain JNW parameters. Our findings provided insights into the mass, coupling, and deformation parameter for each system, enhancing our understanding of compact object dynamics in strong gravitational fields. Published by the American Physical Society 2024

Cosmology in f (R, T) modified gravity : unified dark matter and dark energy model constrained by current observations

The proposed cosmological model deals with modified Chaplygin gas (MCG) in f(R, T) = R + ξ(T) gravity, where R is the Ricci Scalar and T is the trace of energy-momentum tensor. The function ξ(T) is chosen as the linear combination of power law and logarithmic form under flat Friedmann-Lemaitre-Robertson-Walker space-time. The model is compatible with current observational data (Pantheon Type Ia Supernova) and confronts the deceleration and state parameters effectively. The model can predict the Big Rip in future infinity and can also tackle the difficulties related to the fine-tuning and the coincidence problem practically. Further, we have numerically solved the modified Friedmann equations in f(R, T) gravity and also performed a Markov Chain Monte Carlo analysis to obtain the best fit parameters of this current cosmological model. These best parameters are then used to compute the cosmographic parameters, i.e., the deceleration parameter, the jerk parameter and the snap parameter. Significantly, the cosmographic test has given valuable insights into the dynamics of the current cosmological model and also enriched us to understand about the cosmic evolution of the accelerated Universe. Additionally, the Statefinder diagnostics and O m diagnostics have provided deeper insights into the dynamics of the cosmic expansion and also provided information to distinguish between both the cosmological frameworks. Furthermore, these tests also reveal that at late times, the current model goes beyond the phantom region. Again, the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) have provided enough support for the current model under consideration, indicating that the present model exhibits a plausible explanation. However, the ΛCDM model has emerged with the lowest AIC value which suggests its relatively superior fit compared to the current model. Finally, our current model aligns well with several recent observations and unveils various intriguing features about the late time accelerated Universe.

Reionization Parameter Inference from 3D Minkowski Functionals of the 21 cm Signals

The Minkowski functionals (MFs), a set of topological summary statistics, have emerged as a powerful tool for extracting non-Gaussian information. We investigate the prospect of constraining the reionization parameters using the MFs of the 21 cm brightness temperature field from the epoch of reionization (EOR). Realistic effects, including thermal noise, synthesized beam, and foreground avoidance, are applied to the mock observations from radio interferometric array experiments such as the Hydrogen Epoch of Reionization Array (HERA) and the Square Kilometre Array (SKA). We demonstrate that the MFs of the 21 cm signal measured with SKA-Low can be used to distinguish different reionization models, whereas the MF measurement with a HERA-like array cannot be made accurately enough. We further forecast the accuracies with which the MF measurements can place constraints on reionization parameters, using the standard Markov Chain Monte Carlo analysis for parameter inference based on forward modeling. We find that for SKA-Low observation, MFs provide unbiased estimations of the reionization parameters with accuracies comparable to the power spectrum (PS) analysis. Furthermore, joint constraints using both MFs and PS can improve the constraint accuracies by up to 30% compared to those with the PS alone. Nevertheless, the constraint accuracies can be degraded if the EOR window is shrunk with strong foreground avoidance. Our analysis demonstrates the promise of MFs as a set of summary statistics that extract complementary information from the 21 cm EOR field to the two-point statistics, which suggests a strong motivation for incorporating the MFs into the data analysis of future 21 cm observations.

Epicyclic oscillations and particle collision with trajectories around quantum corrected black holes

The present study deals with the orbital, oscillatory motion, and trajectories of test particles around quantum-corrected black holes. The angular momentum within specific energy is calculated to discuss stable circular orbits. The effective potential through Hamiltonian is calculated around quantum-corrected black holes. The trajectories scenario around particles of considered black hole solutions are discussed. Further, we provide the mathematical formulas for both latitudinal and radial frequencies. The primary properties of test particle quasi-periodic oscillations in stable circular orbits in the black hole’s equatorial plane are investigated. We provide a Markov Chain Monte Carlo analysis of the restrictions on quantum-corrected black hole attributes. We analyze QPOs detected in X-ray binaries, namely the cores of the galaxies Sgr A∗, M82 X-1, microquasars XTE J1550-564, GRS 1915+105 and GRO J1655-40. Additionally, the process of Periastron precession is examined. We show that the velocity of particles around black holes is strongly dependent on the parameters of the model. Notably, the pictorial behavior that describes our results feasibility.

Computation of bulk viscous pressure with observational constraints via scalar field in the General relativity and [formula omitted] gravity

The present article deals with the isotropic cosmological model of f(Q) gravity filled with bulk viscous fluid, where Q is the non-metricity term and it is responsible for the gravitational interaction. Aside from the tachyon and quintessence scalar fields, the modified Einstein’s field equations have been resolved through the application of the power law form of the expansion. In this model, the Markov chain Monte Carlo (MCMC) analysis method has been utilized to obtained the best-fit value of the model parameter and it confirms that the model satisfies the recent observational data. We have also examined the EoS parameter for bulk viscosity in these cosmological contexts and it has been determined that ωeff will be located in the phantom region. The correspondence between bulk pressure and the reconstructed ωrec,Q in f(Q) gravity has also been addressed. In the presence of holographic Ricci dark energy, the reconstructed f(Q) gravity yields a transition from the quintessence era into phantom era.

RedDots: Limits on habitable and undetected planets orbiting nearby stars GJ 832, GJ 674, and Ross 128

Context. The nearby (d &lt; 5 pc) M dwarfs GJ 832, GJ 674, and Ross 128 each host a single exoplanet, with Ross 128 b located within the optimistic habitable zone. Due to their low mass and close proximity, these three systems are prime candidates for further characterization studies. Aims. Using HARPS spectroscopic data obtained by the RedDots campaign, as well as archival data from HARPS and CARMENES, supplemented with ASH2 and T90 photometry, we aim to search for additional planets in the three systems. We also aim to determine limits on possible undetected, habitable planets. We investigate (i) the reliability of the recovered orbital eccentricities and (ii) the reliability of Bayesian evidence as a diagnostic for selecting the best model. Methods. We employed Markov-chain Monte Carlo, nested sampling, and Gaussian process (GP) analyses to fit a total of 20 different models comprising 0–2 Keplerian signals and three different GP kernels for stellar activity. We used the residuals to create grids for injection-recovery simulations to obtain detection limits on potentially undiscovered planets. Results. Our refined orbital elements for GJ 832 b, GJ 674 b, and Ross 128 b confirm (GJ 832, GJ 674) or increase (Ross 128) prior eccentricity determinations. No additional planets were found in any of the systems. The detection limits obtained for all three systems are between 30 and 50 cm s−1 for orbital periods in the range of 1–10 000 days. This corresponds to habitable planet masses of &lt;1.5M⊕for GJ 832 and &lt; 1M⊕ for GJ 674 and Ross 128. Using N-body simulations, we find that undiscovered secondary planets are unlikely (Ross 128) or incapable (GJ 674) of having caused the observed eccentricities of the known planets. We find that the eccentricity of GJ 832b is not significantly different from zero. Conclusions. GJ 832 b, GJ 674 b, and Ross 128 b retain their status as hosting lonely and (for the latter two) eccentric planets (e = 0.04, 0.24, 0.21; respectively). This is unexpected in classical planet formation scenarios, which favor circular orbits and multiplanet configurations, demonstrating that planet formation in these cases is more complicated than traditionally thought. Additionally, the eccentricity of Ross 128 indicates that it spends some of its orbit outside of the optimistic habitable zone. Finally, our results show that Bayesian evidence, when used in conjunction with GP, is not a robust diagnostic for selecting the best model in cases of low- activity stars. In such cases, we advise an inspection of the shapes of the posterior distributions and to ensure that relevant simulations are performed to assess the validity of the perceived best model.

Model-independent cosmographic constraints from DESI 2024

Context. We explore model-independent constraints on the Universe kinematics up to the snap and jerk hierarchical terms, considering the latest baryon acoustic oscillation (BAO) release provided by the DESI collaboration. Aims. We intend to place novel and more stringent constraints on the cosmographic series, incorporating three combinations of data catalogs: the first made by BAO and observational cosmic chronometers, the second made by BAO and type Ia supernovae, and the last including all the cited data sets. Methods. Considering the latest BAO data provided by the DESI collaboration and tackling the rd parameter to span within the range [144,152] Mpc, with a fixed step of δrd = 2 Mpc, we employed Monte Carlo Markov chain analyses based on the Metropolis algorithm to fix novel bounds on the cosmographic series, fixing the deceleration, q0 , the jerk, j0 , and the snap, s0, parameters, up to the 2σ level. A comparison between the results of the Planck satellite with those obtained by the DESI collaboration is also reported. Results. Our findings showcase a significant departure in terms of j0 even at the 1σ confidence level, albeit compatible with the ACDM paradigm in regard to q0 and s0 at the 2σ level. Analogously, the h0 tension appears alleviated in the second hierarchy when including snap. Conclusions. Our method excludes models that significantly depart from the standard cosmological model. Particularly, direct comparisons with the ACDM and wCDM models and the Chevallier-Polarski-Linder parameterisation are explored, which definitively favour the wCDM scenario over other approaches, contradicting the findings of the original DESI collaboration.

An automated convergence diagnostic for phylogenetic MCMC analyses.

Assessing convergence of Markov chain Monte Carlo (MCMC) based analyses is crucial but challenging, especially so in high dimensional and complex spaces such as the space of phylogenetic trees (treespace). In practice, it is assumed that the target distribution is the unique stationary distribution of the MCMC and convergence is achieved when samples appear to be stationary. Here we leverage recent advances in computational geometry of the treespace and introduce a method that combines classical statistical techniques and algorithms with geometric properties of the treespace to automatically evaluate and assess practical convergence of phylogenetic MCMC analyses. Our method monitors convergence across multiple MCMC chains and achieves high accuracy in detecting both practical convergence and convergence issues within treespace. Furthermore, our approach is developed to allow for real-time evaluation during the MCMC algorithm run, eliminating any of the chain post-processing steps that are currently required. Our tool therefore improves reliability and efficiency of MCMC based phylogenetic inference methods and makes analyses easier to reproduce and compare. We demonstrate the efficacy of our diagnostic via a well-calibrated simulation study and provide examples of its performance on real data sets. Although our method performs well in practice, a significant part of the underlying treespace probability theory is still missing, which creates an excellent opportunity for future mathematical research in this area. The open source package for the phylogenetic inference framework BEAST2, called ASM, that implements these methods, making them accessible through a user-friendly GUI, is available from https://github.com/rbouckaert/asm/. The open source Python package, called tetres, that provides an interface for these methods enabling their applications beyond BEAST2 can be accessed at https://github.com/bioDS/tetres/.

Investigating early and late-time epochs in f(Q) gravity

In the following work, a new hybrid model of the form f(Q)=Q(1+a)+bQ02Q\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ f(Q)=Q(1+a)+b\\frac{Q_0^2}{Q} $$\\end{document} has been proposed and confronted using both early as well as late-time constraints. We first use conditions from the era of Big Bang Nucleosynthesis (BBN) in order to constrain the models which are further used to study the evolution of the Universe through the deceleration parameter. This methodology is employed for the hybrid model as well as a simple model of the form α1Q+α2Q0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\alpha _1 Q+\\alpha _2 Q_0 $$\\end{document} which is found to reduce to Λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Lambda $$\\end{document}CDM. The error bar plot for the Cosmic Chronometer (CC) and Pantheon+SH0ES datasets which includes the comparison with Λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Lambda $$\\end{document}CDM, has been studied for the constrained hybrid model. Additionally, we perform a Monte Carlo Markov Chain (MCMC) sampling of the model against three datasets – CC, Pantheon+SH0ES, and Baryon Acoustic Oscillations (BAO) to find the best-fit ranges of the free parameters. It is found that the constraint range of the model parameter (a) from the BBN study has a region of overlap with the ranges obtained from the MCMC analysis. Finally, we perform a statistical comparison between our model and the Λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Lambda $$\\end{document}CDM model using AIC and BIC method.

Constraining hybrid potential scalar field cosmological model in Lyra’s geometry with recent observational data

In this study, we investigate a scalar field cosmological model with Lyra’s geometry to explain the present cosmic expansion in a homogeneous and isotropic flat FRW universe. In Einstein’s field equations, we presupposed a variable displacement vector as an element of Lyra’s geometry. In the context of the conventional theory of gravity, we suggest a suitable parametrization of the scalar field’s dark energy density in the hybrid function of redshift [Formula: see text], confirming the essential transition behavior of the universe from a decelerating era to the present accelerated scenario. We present constraints on model parameters using the most recent observational datasets from OHD, BAO/CMB and Pantheon, taking Markov Chain Monte Carlo (MCMC) analysis into account. For the proposed model, the best estimated values of parameters for the combined dataset (OHD, BAO/CMB and Pantheon) are [Formula: see text][Formula: see text]km/s/Mpc, [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text]. The model exhibits a flipping nature, and the redshift transition occurs at [Formula: see text]. The current value of the decelerated parameter for the proposed model is calculated as [Formula: see text] for the combined dataset. Some dynamical properties of the model like energy density ([Formula: see text]), scalar field pressure ([Formula: see text]), EoS parameter of scalar field ([Formula: see text]), and effective EoS parameter ([Formula: see text]) are analyzed and presented. Further, we have also examined the statefinder diagnosis and jerk parameters of the derived model. The total density parameter for the derived model is found to be unity which is in nice agreement with recent standard findings.

Polytropic gas cosmology and late-time acceleration

The accelerated expansion of the Universe has sparked significant interest in the mysterious concept of dark energy within cosmology. Various theories have been proposed to explain dark energy, and many models have been developed to understand its origins and properties. This research explores cosmic expansion using the Polytropic Gas (PG) approach, which combines Dark Matter (DM) and Dark Energy (DE) into a single mysterious fluid. We used the principles of general relativity and built our model within the homogeneous and isotropic framework of Friedmann-Lemaître-Robertson-Walker (FLRW) spacetime. We revised the Original Polytropic Gas (OPG) model to expand its applicability beyond the OPG, to the ΛCDM model. Our model's parameters were carefully adjusted to reflect key cosmological features of the variable PG approach. To validate our model, we performed a Markov chain Monte Carlo analysis using recent Supernova data from the Pantheon+ survey, 36 observational data points, 162 Gamma-Ray Bursts, and 24 binned Quasars distance modulus data. The AIC and BIC criteria indicate that our model is slightly preferred over the ΛCDM model based on observational data. We also tested our model with data, Supernova, Gamma-Ray Bursts, and Quasars and found that it exhibits a transition from a quintessential to phantom regime. The Polytropic dark fluid model (PDFM) is a promising candidate that effectively addresses the interplay between cosmic acceleration and dark energy.

FLRW cosmology in metric-affine F(R,Q) gravity* *Supported by the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP14870191)

We investigated some Friedmann-Lemaître-Robertson-Walker (FLRW) cosmological models in the context of metric-affine gravity, as proposed in [arXiv: 1205.5266v6]. Here, R and Q are the curvature and nonmetricity scalars using non-special connections, respectively. We obtained the modified field equations using a flat FLRW metric. We then found a connection between the Hubble constant , density parameter , and other model parameters in two different situations involving scalars u and w. Next, we used new observational datasets, such as the cosmic chronometer (CC) Hubble and Pantheon SNe Ia datasets, to determine the optimal model parameter values through a Markov chain Monte Carlo (MCMC) analysis. Using these best-fit values of the model parameters, we discussed the results and behavior of the derived models. Further, we discussed the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for the derived models in the context of the Lambda cold dark matter (ΛCDM). We found that the geometrical sector dark equation of state parameter behaves just like a dark energy candidate. We also found that both models are transit phase models. Model-I approaches the ΛCDM model in the late-time universe, whereas Model-II approaches quintessence scenarios.

Weak lensing constraints on dark matter-baryon interactions with 𝖭-body simulations and machine learning

We investigate the elastic scattering cross section between dark matter and protons using the DES Year 3 weak lensing data. This scattering induces a dark acoustic oscillation structure in the matter power spectra. To address non-linear effects at low redshift, we utilize principal component analysis alongside a limited set of N-body simulations, improving the reliability of our matter power spectrum prediction. We further perform a robust Markov Chain Monte Carlo analysis to derive the upper bounds on the DM-proton elastic scattering cross-section, assuming different velocity dependencies. Our results, presented as the first Frequentist upper limits, are compared with the ones obtained by Bayesian approach. Compared with the upper limits derived from the Planck cosmic microwave background data, our findings from DES Year 3 data exhibit improvements of up to a factor of five. In addition, we forecast the future sensitivities of the China Space Station Telescope, the upcoming capabilities of this telescope could improve the current limits by approximately one order of magnitude.

Tropical Logistic Regression Model on Space of Phylogenetic Trees

Classification of gene trees is an important task both in the analysis of multi-locus phylogenetic data, and assessment of the convergence of Markov Chain Monte Carlo (MCMC) analyses used in Bayesian phylogenetic tree reconstruction. The logistic regression model is one of the most popular classification models in statistical learning, thanks to its computational speed and interpretability. However, it is not appropriate to directly apply the standard logistic regression model to a set of phylogenetic trees, as the space of phylogenetic trees is non-Euclidean and thus contradicts the standard assumptions on covariates. It is well-known in tropical geometry and phylogenetics that the space of phylogenetic trees is a tropical linear space in terms of the max-plus algebra. Therefore, in this paper, we propose an analogue approach of the logistic regression model in the setting of tropical geometry. Our proposed method outperforms classical logistic regression in terms of Area under the ROC Curve in numerical examples, including with data generated by the multi-species coalescent model. Theoretical properties such as statistical consistency have been proved and generalization error rates have been derived. Finally, our classification algorithm is proposed as an MCMC convergence criterion for Mr Bayes. Unlike the convergence metric used by Mr Bayes which is only dependent on tree topologies, our method is sensitive to branch lengths and therefore provides a more robust metric for convergence. In a test case, it is illustrated that the tropical logistic regression can differentiate between two independently run MCMC chains, even when the standard metric cannot.

Niche modelling and landscape genetics of the yellow-legged hornet (Vespa velutina): An integrative approach for evaluating central-marginal population dynamics in Europe.

Genetic diversity is an important biological trait for a successful invasion. During the expansion across a new territory, an invasive species may face unprecedented ecological conditions that will determine its demography and genetic diversity. The first record of the yellow-legged hornet (Vespa velutina) in Europe dates back to 2004 in France, from where it has successfully spread through a large territory in the continent, including Italy, Spain and Portugal. Integrative approaches offer a powerful strategy to detect and understand patterns of genetic variation in central and marginal populations. Here, we have analysed the relationship between genetic diversity parameters inferred from 15 V. velutina nuclear DNA microsatellite loci, and geographical and environmental drivers, such as the distance to the introduction focus, environmental suitability and distance to native and invasive niche centroids. Our results revealed a central-marginal dynamic, where allelic richness decreased towards the edge of the expansion range. The low environmental suitability of the territories invaded by marginal populations could prevent a diverse population from establishing and reducing the genetic diversity in populations at the expansion edge. Moreover, Markov chain Monte Carlo analysis showed both geographical and environmental distances were influencing population genetic differentiation. This study highlights the importance of combining genetic analysis with geographical and environmental drivers to understand genetic trends of invasive species to new environment.

Constraining Extended Teleparallel Gravity via Cosmography: A Model-independent Approach

As a classical approach, the dynamics of the Universe, influenced by its dark components, are unveiled through prior modifications of Einstein’s equations. Cosmography, on the other hand, is a highly efficient tool for reconstructing any modified theory in a model-independent manner. By employing kinematic variables, it offers a profound explanation for cosmic expansion. Although the cosmographical approach has been highly successful in several geometric theories in recent years, it has not been extensively explored in coupled gravities. With this in mind, we intend to constrain an extended teleparallel gravity model, f(T,T) , through cosmographic parameters. We utilize Taylor series expansion, assuming a minimally coupled form, to constrain the unknowns involved in the series. To achieve this, we conduct a Markov Chain Monte Carlo (MCMC) analysis using three different data sets (cosmic chronometers, baryon acoustic oscillations, and Pantheon+SH0ES). The constrained results obtained from MCMC are then compared and verified using various cosmological parameters. Finally, we compare the resulting models with three well-known f(T,T) models.

Kinetic modeling of microwave-assisted esterification for biofuel additive production: conversion of levulinic acid with pentanol using Dowex® 50WX8 catalyst

This study explores the esterification of levulinic acid with 1-pentanol, employing Dowex® 50WX8 as a catalyst under microwave irradiation. Key parameters such as the pentanol/acid molar ratio, temperature, and catalyst loading were evaluated and utilized for kinetic modeling. The kinetic behavior of the reaction was investigated using a dual-model approach: a pseudo-homogeneous model to account for the microwave effect and catalytic contributions modeled through LHHW and Eley–Rideal mechanisms. The best model was chosen based on statistical results obtained from Markov Chain Monte Carlo (MCMC) analysis, which involved an LHHW model with the surface reaction as the limiting step, resulting in an activation energy of 50.6 kJ mol−1 for the catalytic synthesis of pentyl levulinate. The role of the alcohol in the esterification route was explained, and catalytic stability was confirmed, with the catalyst maintaining activity over multiple cycles. The absence of mass transfer limitations was proved using the Weisz–Prater criterion. A plausible reaction pathway was proposed for the levulinic acid esterification over the 50WX8 catalyst.Graphical abstract