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When microspheres are illuminated by tightly focused vortex beams, they can be trapped in a non-equilibrium steady state where they orbit around the optical axis. By using the Mie-Debye theory for optical tweezers, we demonstrate that the orbital period strongly depends on the particle's chirality index. Taking advantage of such sensitivity, we put forth a method to experimentally characterize with high precision the chiroptical response of individual optically trapped particles. The method allows for an enhanced precision at least one order of magnitude larger than that of similar existing enantioselective approaches. It is particularly suited to probe the chiroptical response of individual particles, for which light-chiral matter interactions are typically weak.

Nontwist area-preserving maps violate the twist condition at specific orbits, resulting in shearless invariant curves that prevent chaotic transport. Plasmas and fluids with nonmonotonic equilibrium profiles may be described using nontwist systems, where even after these shearless curves breakdown, effective transport barriers persist, partially reducing transport coefficients. Some nontwist systems present multiple shearless curves in phase space, increasing the complexity of transport phenomena, which have not been thoroughly investigated until now. In this work, we examine the formation of effective transport barriers in a nontwist area-preserving mapping with multiple shearless transport barriers. By quantifying the effectiveness of each transport barrier in phase space, we identified two scenarios where particular barriers dominate over others. Our results also reveal configurations where the interplay of two transport barriers creates regions in phase space with significant orbit trapping, thereby influencing the overall transport dynamics.

Quantum transport studies of spin-dependent phenomena in solids commonly employ the Kubo or Keldysh formulas for the steady-state density matrix in the linear-response regime. Its trace with operators of interest -- such as, spin density, spin current density or spin torque -- gives expectation values of experimentally accessible observables. For such local quantities, these formulas require summing over the manifolds of {\em both} Fermi-surface and Fermi-sea quantum states. However, debates have been raging in the literature about vastly different physics the two formulations can apparently produce, even when applied to the same system. Here, we revisit this problem using a testbed of infinite-size graphene with proximity-induced spin-orbit and magnetic exchange effects. By splitting this system into semi-infinite leads and central active region, in the spirit of Landauer two-terminal setup for quantum transport, we prove the {\em numerically exact equivalence} of the Kubo and Keldysh approaches via the computation of spin Hall current density and spin-orbit torque in both clean and disordered limits. The key to reconciling the two approaches are the numerical frameworks we develop for: ({\em i}) evaluation of Kubo(-Bastin) formula for a system attached to semi-infinite leads, which ensure continuous energy spectrum and evade the need for phenomenological broadening in prior calculations; and ({\em ii}) proper evaluation of Fermi-sea term in the Keldysh approach, which {\em must} include the voltage drop across the central active region even if it is disorder free., Comment: 9 pages, 3 figures, 111 references

In nontwist systems, primary shearless curves act as barriers to chaotic transport. Surprisingly, the onset of secondary shearless curves has been reported in a few twist systems. Meanwhile, we found that, in twist systems, the onset of these secondary shearless curves is a standard process that may appear as control parameters are varied in situations where there is resonant mode coupling. Namely, we analyze these shearless bifurcations in two-harmonic systems for the standard map, the Ullmann map, and for the Walker-Ford Hamiltonian flow. The onset of shearless curves is related to bifurcations of periodic points. Furthermore, depending on the bifurcation, these shearless curves can emerge alone or in pairs, and in some cases, deform into separatrices.

In this study, we investigated Rydberg atom-based microwave electrometry using polarization spectroscopy in a room-temperature vapor cell. By measuring Autler-Townes splitting in the electromagnetically induced transparency (EIT) spectrum, we determined that the minimum measurable microwave electric field is approximately five times lower than conventional EIT techniques. The results are well reproduced by a full optical Bloch equation model, which takes into account all the hyperfine levels involved. Subsequently, the EIT setup was used to characterize a custom microwave cylindrical lens, which increases the field at the focus by a factor of three, decreasing the minimum measurable microwave electric field by the same amount. Our results indicate that the combination of polarization spectroscopy and a microwave lens may enhance microwave electrometry.

We introduce a second-order gyro-averaged extension to a guiding-center transport model for test particles subject to an $\mathbf{E}\times\mathbf{B}$ drift in a tokamak. Using this approximation, we numerically investigate the influence of finite Larmor radius effects on the chaotic transport and the formation of transport barriers. For non-monotonic plasma profiles, we show that the twist condition of the system is violated along a curve, usually called shearless transport barrier, which, under non-equilibrium conditions, exhibits significant resilience to destruction, thereby inhibiting chaotic transport. We analyze bifurcation diagrams of the shearless barriers and escape rates to explore the impact of the Larmor radius on controlling chaotic transport while varying the amplitude of electrostatic perturbations. Our findings show that increasing the Larmor radius enhances the robustness of transport barriers, as a larger electrostatic perturbation amplitude is required to disrupt them. Additionally, even in the absence of transport barriers, we observe a decrease in chaotic transport with an increase in the Larmor radius., Comment: Submitted to Physics of Plasmas

The ability to generate entangled states of light is a key primitive for quantum communication and distributed quantum computation. Continuously driven sources, including those based on spontaneous parametric downconversion, are usually probabilistic, whereas deterministic sources require accurate timing of the control fields. Here, we experimentally generate entangled photonic modes by continuously exciting a quantum emitter, a superconducting qubit, with a coherent drive, taking advantage of mode matching in the time and frequency domain. Using joint quantum state tomography and logarithmic negativity, we show that entanglement is generated between modes extracted from the two sidebands of the resonance fluorescence spectrum. Because the entangled photonic modes are perfectly orthogonal, they can be transferred into distinct quantum memories. Our approach can be utilized to distribute entanglement at a high rate in various physical platforms, with applications in waveguide quantum electrodynamics, distributed quantum computing, and quantum networks.

For several decades now it has been known that systems with shearless invariant tori, nontwist Hamiltonian systems, possess barriers to chaotic transport. These barriers are resilient to breakage under perturbation and therefore regions where they occur are natural places to look for barriers to transport. We describe a novel kind of effective barrier that persists after the shearless torus is broken. Because phenomena are generic, for convenience we study the Standard Nontwist Map (SNM), an area-preserving map that violates the twist condition locally in the phase space. The novel barrier occurs in nontwist systems when twin even period islands are present, which happens for a broad range of parameter values in the SNM. With a phase space composed of regular and irregular orbits, the movement of chaotic trajectories is hampered by the existence of both shearless curves, total barriers, and a network of partial barriers formed by the stable and unstable manifolds of the hyperbolic points. Being a degenerate system, the SNM has twin islands and, consequently, twin hyperbolic points. We show that the structures formed by the manifolds intrinsically depend on period parity of the twin islands. For this even scenario the novel structure, named a torus free barrier, occurs because the manifolds of different hyperbolic points form an intricate chain atop a dipole configuration and the transport of chaotic trajectories through the chain becomes a rare event. This structure impacts the emergence of transport, the escape basin for chaotic trajectories, the transport mechanism and the chaotic saddle. The case of odd periodic orbits is different: we find for this case the emergence of transport immediately after the breakup of the last invariant curve, and this leads to a scenario of higher transport, with intricate escape basin boundary and a chaotic saddle with non-uniformly distributed points.

Over a quarter of white dwarfs have photospheric metal pollution, which is evidence for recent accretion of exoplanetary material. While a wide range of mechanisms have been proposed to account for this pollution, there are currently few observational constraints to differentiate between them. To investigate the driving mechanism, we observe a sample of polluted and non-polluted white dwarfs in wide binary systems with main-sequence stars. Using the companion stars' metallicities as a proxy for the white dwarfs' primordial metallicities, we compare the metallicities of polluted and non-polluted systems. Because there is a well-known correlation between giant planet occurrence and higher metallicity (with a stronger correlation for close-in and eccentric planets), these metallicity distributions can be used to probe the role of gas giants in white dwarf accretion. We find that the metallicity distributions of polluted and non-polluted systems are consistent with the hypothesis that both samples have the same underlying metallicity distribution. However, we note that this result is likely biased by several selection effects. Additionally, we find no significant trend between white dwarf accretion rates and metallicity. These findings suggest that giant planets are not the dominant cause of white dwarf accretion events in binary systems., Comment: 17 pages, 9 figures, accepted to MNRAS

User Stories record what must be built in projects that use agile practices. User Stories serve both to estimate effort, generally measured in Story Points, and to plan what should be done in a Sprint. Therefore, it is essential to train software engineers on how to create simple, easily readable, and comprehensive User Stories. For that reason, we designed, implemented, applied, and evaluated a web application called User Story Tutor (UST). UST checks the description of a given User Story for readability, and if needed, recommends appropriate practices for improvement. UST also estimates a User Story effort in Story Points using Machine Learning techniques. As such UST may support the continuing education of agile development teams when writing and reviewing User Stories. UST's ease of use was evaluated by 40 agile practitioners according to the Technology Acceptance Model (TAM) and AttrakDiff. The TAM evaluation averages were good in almost all considered variables. Application of the AttrakDiff evaluation framework produced similar good results. Apparently, UST can be used with good reliability. Applying UST to assist in the construction of User Stories is a viable technique that, at the very least, can be used by agile developments to complement and enhance current User Story creation.

Many studies regarding the vasculature of biological tissues involve the segmentation of the blood vessels in a sample followed by the creation of a graph structure to model the vasculature. The graph is then used to extract relevant vascular properties. Small segmentation errors can lead to largely distinct connectivity patterns and a high degree of variability of the extracted properties. Nevertheless, global metrics such as Dice, precision, and recall are commonly applied for measuring the performance of blood vessel segmentation algorithms. These metrics might conceal important information about the accuracy at specific regions of a sample. To tackle this issue, we propose a local vessel salience (LVS) index to quantify the expected difficulty in segmenting specific blood vessel segments. The LVS index is calculated for each vessel pixel by comparing the local intensity of the vessel with the image background around the pixel. The index is then used for defining a new accuracy metric called low-salience recall (LSRecall), which quantifies the performance of segmentation algorithms on blood vessel segments having low salience. The perspective provided by the LVS index is used to define a data augmentation procedure that can be used to improve the segmentation performance of convolutional neural networks. We show that segmentation algorithms having high Dice and recall values can display very low LSRecall values, which reveals systematic errors of these algorithms for vessels having low salience. The proposed data augmentation procedure is able to improve the LSRecall of some samples by as much as 25%. The developed methodology opens up new possibilities for comparing the performance of segmentation algorithms regarding hard-to-detect blood vessels as well as their capabilities for vascular topology preservation.

The operation of the next generation of gamma-ray observatories will lead to a great advance in dark matter searches. In this paper, we use the hidden sectors hypothesis within the so-called secluded models to calculate the capabilities of the Southern Wide-field Gamma-ray Observatory (SWGO) to detect gamma-ray signatures produced by dark matter particles concentrated in the Sun. We assume the dark matter particle annihilates into metastable mediators which decay into $\gamma\gamma$, $e^+e^-$, $\tau^+\tau^-$, and $\bar{b}b$ outside the Sun. We found that the SWGO will be able to probe a spin-dependent cross-section of about $10^{-46}$ cm$^2$ for dark matter masses smaller than 5 TeV. This result shows an unprecedented sensitivity surpassing the current instruments by more than one order of magnitude., Comment: 15 pages, 3 figures

We investigate the transport of particles in the chaotic component of phase space for a two-dimensional, area-preserving nontwist map. The survival probability for particles within the chaotic sea is described by an exponential decay for regions in phase space predominantly chaotic and it is scaling invariant in this case. Alternatively, when considering mixed chaotic and regular regions, there is a deviation from the exponential decay, characterized by a power law tail for long times, a signature of the stickiness effect. Furthermore, due to the asymmetry of the chaotic component of phase space with respect to the line $I = 0$, there is an unbalanced stickiness which generates a ratchet current in phase space. Finally, we perform a phenomenological description of the diffusion of chaotic particles by identifying three scaling hypotheses, and obtaining the critical exponents via extensive numerical simulations.

This paper introduces the front-propagation algorithm, a novel eXplainable AI (XAI) technique designed to elucidate the decision-making logic of deep neural networks. Unlike other popular explainability algorithms such as Integrated Gradients or Shapley Values, the proposed algorithm is able to extract an accurate and consistent linear function explanation of the network in a single forward pass of the trained model. This nuance sets apart the time complexity of the front-propagation as it could be running real-time and in parallel with deployed models. We packaged this algorithm in a software called $\texttt{front-prop}$ and we demonstrate its efficacy in providing accurate linear functions with three different neural network architectures trained on publicly available benchmark datasets., Comment: 14 pages, 6 figures. Accepted for publication in: Barnabas Bede, Kelly Cohen, and Vladik Kreinovich (eds.), Proceedings of the NAFIPS International Conference on Fuzzy Systems, Soft Computing, and Explainable AI. NAFIPS'2024, South Padre Island, Texas, May 27-29, 2024

The broader adoption of social media platforms (e.g., TikTok), combined with recent developments in Generative AI (GAI) technologies has had a transformative effect on many peoples' ability to confidently assess the veracity and meaning of information online. In this paper, building on recent related work that surfaced the social ways that young people evaluate information online, we explore the decision-making practices, challenges and heuristics involved in young adults' assessments of information online. To do so, we designed and conducted a novel digital diary study, followed by data-informed interviews with young adults. Our findings uncover the information practices of young adults including the social and emotional motivations for ignoring, avoiding, and engaging with online information and the ways this is entangled with collaborative arrangements with algorithms as agents. In our discussion we bring these findings in close dialogue with work on information sensibility and contribute rich insights into young peoples' information sensibility practices embedded within social worlds. Finally, we surface how such practices are attuned to prioritise wellbeing over convenience or other commonly associated sufficing heuristics., Comment: To be published in Proceedings of ECSCW 2024, Rimini, Italy

Strong first-order phase transitions (SFOPT) during the evolution of the Higgs potential in the early universe not only allow for the dynamical generation of the observed matter-antimatter asymmetry, they can also source a stochastic gravitational wave (GW) background possibly detectable with future space-based gravitational waves interferometers. As SFOPTs are phenomenologically incompatible with the Standard Model (SM) Higgs sector, the observation of GWs from SFOPTs provides an exciting interplay between cosmology and particle physics in the search for new physics. With the C++ code BSMPTv3, we present for the first time a tool that performs the whole chain from the particle physics model to the gravitational wave spectrum. Extending the previous versions BSMPTv1 and v2, it traces the phases of beyond-SM (BSM) Higgs potentials and is capable of treating multiple vacuum directions and multi-step phase transitions. During the tracing, it checks for discrete symmetries, flat directions, and electroweak symmetry restoration, and finally reports the transition history. The transition probability from the false to the true vacuum is obtained from the solution of the bounce equation which allows for the calculation of the nucleation, percolation and completion temperatures. The peak amplitude and frequency of the GWs originating from sound waves and turbulence, are evaluated after the calculation of the thermal parameters at the transition temperature, and finally the signal-to-noise ratio at LISA is provided. The code BSMPTv3 is a powerful self-contained tool that comes more than timely and will be of great benefit for investigations of the vacuum structure of the early universe of not only simple but also complicated Higgs potentials involving several vacuum directions, with exciting applications in the search for new physics., Comment: 78 pages, 13 figures, 4 tables

This work is concerned with the obtainment of new Carleman estimates for linear parabolic equations, where the second-order differential operator brings a super strong degeneracy in a positive measure subset of the spatial domain. In order to prove our main result, the control domain is supposed to contain the set of degeneracies. As a well-known consequence, we achieve a null controllability result in the current context.

Huge efforts have been deployed to detect dark matter (DM) in the GeV-TeV mass range involving various detection techniques, and led to strong constraints in the available parameter space. We compute here the sensitivity to sub-GeV DM that can be probed from the inevitable cosmic-ray scattering onto DM particles populating the Milky Way halo. Inelastic scattering of energetic cosmic rays off DM would produce high-energy gamma rays in the final state, providing a new avenue to probe the poorly-constrained so far sub-GeV dark matter mass range. In this work we derive sensitivity forecasts for the inelastic cosmic-ray proton - DM cross section for current and future very-high-energy gamma-ray observatories such as H.E.S.S., LHAASO, CTA and SWGO in the 100 eV to 100 MeV mass range. These inelastic cross section constraints are converted to the elastic proton - DM cross section to highlight further complementarity with cosmological, collider and direct detection searches. The sensitivity computed at 95\% confidence level on the elastic cross section reaches $\sim$2$\times$ 10$^{-32}$ cm$^2$ for a 100 keV DM mass for H.E.S.S.-like and $\sim$7$\times$ 10$^{-34}$ cm$^2$ for a $\sim$1 keV DM mass for LHAASO. The sensitivity prospects for CTA and a strawman SWGO model reach $\sim$6$\times$ 10$^{-34}$ cm$^2$ and $\sim$4$\times$ 10$^{-35}$ cm$^2$, for DM masses of 10 keV and 1 keV, respectively. The sensitivity reach of the gamma-ray observatories considered here enables to probe an uncharted region of the DM mass - cross section parameter space., Comment: 21 pages, 8 figures. Accepted for publication in JCAP

We describe features of the X-ray: Generate and Analyse (XGA) open-source software package that have been developed to facilitate automated hydrostatic mass ($M_{\rm hydro}$) measurements from XMM X-ray observations of clusters of galaxies. This includes describing how XGA measures global, and radial, X-ray properties of galaxy clusters. We then demonstrate the reliability of XGA by comparing simple X-ray properties, namely the X-ray temperature and gas mass, with published values presented by the XMM Cluster Survey (XCS), the Ultimate XMM eXtragaLactic survey project (XXL), and the Local Cluster Substructure Survey (LoCuSS). XGA measured values for temperature are, on average, within 1% of the values reported in the literature for each sample. XGA gas masses for XXL clusters are shown to be ${\sim}$10% lower than previous measurements (though the difference is only significant at the $\sim$1.8$\sigma$ level), LoCuSS $R_{2500}$ and $R_{500}$ gas mass re-measurements are 3% and 7% lower respectively (representing a 1.5$\sigma$ and 3.5$\sigma$ difference). Like-for-like comparisons of hydrostatic mass are made to LoCuSS results, which show that our measurements are $10{\pm}3%$ ($19{\pm}7%$) higher for $R_{2500}$ ($R_{500}$). The comparison between $R_{500}$ masses shows significant scatter. Finally, we present new $M_{\rm hydro}$ measurements for 104 clusters from the SDSS DR8 redMaPPer XCS sample (SDSSRM-XCS). Our SDSSRM-XCS hydrostatic mass measurements are in good agreement with multiple literature estimates, and represent one of the largest samples of consistently measured hydrostatic masses. We have demonstrated that XGA is a powerful tool for X-ray analysis of clusters; it will render complex-to-measure X-ray properties accessible to non-specialists., Comment: 24 pages (18 + 6 appendices), 15 figures, submitted to MNRAS; see https://github.com/DavidT3/XCS-Mass-Paper-I-Analysis for the code and samples

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version

Telecommunications and computer vision have evolved separately so far. Yet, with the shift to sub-terahertz (sub-THz) and terahertz (THz) radio communications, there is an opportunity to explore computer vision technologies together with radio communications, considering the dependency of both technologies on Line of Sight. The combination of radio sensing and computer vision can address challenges such as obstructions and poor lighting. Also, machine learning algorithms, capable of processing multimodal data, play a crucial role in deriving insights from raw and low-level sensing data, offering a new level of abstraction that can enhance various applications and use cases such as beamforming and terminal handovers. This paper introduces CONVERGE, a pioneering vision-radio paradigm that bridges this gap by leveraging Integrated Sensing and Communication (ISAC) to facilitate a dual "View-to-Communicate, Communicate-to-View" approach. CONVERGE offers tools that merge wireless communications and computer vision, establishing a novel Research Infrastructure (RI) that will be open to the scientific community and capable of providing open datasets. This new infrastructure will support future research in 6G and beyond concerning multiple verticals, such as telecommunications, automotive, manufacturing, media, and health., Comment: 6 pages, 5 figures

Spiral waves are spatial-temporal patterns that can emerge in different systems as heart tissues, chemical oscillators, ecological networks and the brain. These waves have been identified in the neocortex of turtles, rats, and humans, particularly during sleep-like states. Although their functions in cognitive activities remain until now poorly understood, these patterns are related to cortical activity modulation and contribute to cortical processing. In this work, we construct a neuronal network layer based on the spatial distribution of pyramidal neurons. Our main goal is to investigate how local connectivity and coupling strength are associated with the emergence of spiral waves. Therefore, we propose a trustworthy method capable of detecting different wave patterns, based on local and global phase order parameters. As a result, we find that the range of connection radius (R) plays a crucial role in the appearance of spiral waves. For R < 20 {\mu}m, only asynchronous activity is observed due to small number of connections. The coupling strength (gsyn ) greatly influences the pattern transitions for higher R, where spikes and bursts firing patterns can be observed in spiral and non-spiral waves. Finally, we show that for some values of R and gsyn bistable states of wave patterns are obtained.

We study three different strategies of vaccination in a SEIRS (Susceptible--Exposed--Infected--Recovered--Susceptible) seasonal forced model, which are: ($i$) continuous vaccination; ($ii$) periodic short time localized vaccination and ($iii$) periodic pulsed width campaign. Considering the first strategy, we obtain an expression for the basic reproduction number and infer a minimum vaccination rate necessary to ensure the stability of the disease-free equilibrium (DFE) solution. In the second strategy, the short duration pulses are added to a constant baseline vaccination rate. The pulse is applied according to the seasonal forcing phases. The best outcome is obtained by locating the intensive immunization at inflection of the transmissivity curve. There, a vaccination rate of $44.4\%$ of susceptible individuals is enough to ensure DFE. For the third vaccination proposal, additionally to the amplitude, the pulses have a prolonged time width. We obtain a non-linear relationship between vaccination rates and the duration of the campaign. Our simulations show that the baseline rates, as well as the pulse duration, can substantially improve the vaccination campaign effectiveness. These findings are in agreement with our analytical expression. We show a relationship between the vaccination parameters and the accumulated number of infected individuals, over the years and show the relevance of the immunisation campaign annual reaching for controlling the infection spreading. Regarding the dynamical behaviour of the model, our simulations shows that chaotic and periodic solutions, as well as bi-stable regions, depend on the vaccination parameters range.

Over the past several decades, conventional spectral analysis techniques of polluted white dwarfs have become powerful tools to learn about the geology and chemistry of extrasolar bodies. Despite their proven capabilities and extensive legacy of scientific discoveries, these techniques are however still limited by their manual, time-intensive, and iterative nature. As a result, they are susceptible to human errors and are difficult to scale up to population-wide studies of metal pollution. This paper seeks to address this problem by presenting cecilia, the first Machine Learning (ML)-powered spectral modeling code designed to measure the metal abundances of intermediate-temperature (10,000$\leq T_{\rm eff} \leq$20,000 K), Helium-rich polluted white dwarfs. Trained with more than 22,000 randomly drawn atmosphere models and stellar parameters, our pipeline aims to overcome the limitations of classical methods by replacing the generation of synthetic spectra from computationally expensive codes and uniformly spaced model grids, with a fast, automated, and efficient neural-network-based interpolator. More specifically, cecilia combines state-of-the-art atmosphere models, powerful artificial intelligence tools, and robust statistical techniques to rapidly generate synthetic spectra of polluted white dwarfs in high-dimensional space, and enable accurate ($\lesssim$0.1 dex) and simultaneous measurements of 14 stellar parameters -- including 11 elemental abundances -- from real spectroscopic observations. As massively multiplexed astronomical surveys begin scientific operations, cecilia's performance has the potential to unlock large-scale studies of extrasolar geochemistry and propel the field of white dwarf science into the era of Big Data. In doing so, we aspire to uncover new statistical insights that were previously impractical with traditional white dwarf characterisation techniques., Comment: 28 pages, 16 figures, 5 tables. Accepted for publication in MNRAS

In the present work, Raman and photoluminescence spectroscopies were used to study the dynamics of phonons and different excitons of MoS$_2$ bilayer under a rotation of 29$^{\circ}$ dependent of the temperature. The twisted bilayer (T-2L) of MoS$_2$ was obtained through mechanical exfoliation, and subsequently rotated using a dimethyl polysiloxane (PDMS) substrate and deterministic transferred to a SiO$_2$ substrate. The Raman spectrum of the twisted bilayer presents three peaks E$'$ (386 cm$^{-1}$), A$'_{1}$ (405 cm$^{-1}$) and an FA$'$ peak at approximately 409 cm$^{-1}$ linked to the A$'_{1}$ mode, which is attributed to a Moir\'e pattern phonon. Both modes (A$'_{1}$ and FA$'$) are dependent of light polarization in a way that demonstrates an effective coupling between the layers. It was also verified through the Gr\"uneisen parameter, an increase in the anharmonicity of the mode in the E$'$ plane and a decrease the same for A$'_{1}$. In the PL measurements, the appearance of an exciton in T-2L was verified, which generated a second shoulder measured at $\approx$1.58 eV attributed to an indirect transition of an I trion. The interaction between the rotated monolayers of MoS$_{2}$ proved to be an important parameter for possible fine-tuning of the properties of bilayer samples., Comment: 9 pages, 4 figures, article

New technologies for acquiring biological information such as eDNA, acoustic or optical sensors, make it possible to generate spatial community observations at unprecedented scales. The potential of these novel community data to standardize community observations at high spatial, temporal, and taxonomic resolution and at large spatial scale ('many rows and many columns') has been widely discussed, but so far, there has been little integration of these data with ecological models and theory. Here, we review these developments and highlight emerging solutions, focusing on statistical methods for analyzing novel community data, in particular joint species distribution models; the new ecological questions that can be answered with these data; and the potential implications of these developments for policy and conservation.

The set $S(n)$ of all elementary symmetric polynomials in $n$ variables is a minimal generating set for the algebra of symmetric polynomials in $n$ variables, but over a finite field ${\mathbb F}_q$ the set $S(n)$ is not a minimal separating set for symmetric polynomials in general. We determined when $S(n)$ is a minimal separating set for the algebra of symmetric polynomials having the least possible number of elements., Comment: 8 pages