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We present a detailed reanalysis of the atmospheric properties of WASP-19b, an ultra-hot Jupiter (1.14 M Jup, 1.41 R Jup) orbiting an active Sun-like star every 0.79 day. We reanalyze a transit and secondary eclipse of WASP-19b observed by the Hubble Space Telescope's Wide Field Camera 3 spectrograph (1.1 - 1.7 microns). When combined with Spitzer photometry at longer wavelengths, our analyses indicate the presence of water absorption features in both the planet's transmission and emission spectra, consistent with results from previously published studies. We jointly fit WASP-19b's dayside emission and transmission spectra with a retrieval model in order to constrain its atmospheric composition, and explore the effect of stellar activity on its transmission spectrum in greater depth. We also compare our dayside emission spectrum to predictions from a general circulation model, and conclude that magnetic drag appears to be relatively unimportant in shaping WASP-19b's atmospheric circulation. Lastly, we compare the size of WASP-19b's dayside water absorption feature to the population of hot Jupiters with similar measurements, and show that it is located in the transitional irradiation regime where temperature inversions first begin to emerge. As in previous studies, we find that the current observations provide relatively weak constraints on this planet's atmospheric properties. These constraints could be significantly improved by the addition of spectroscopically resolved observations at longer wavelengths with JWST/NIRSpec PRISM.

Examining reflected light from exoplanets aids in our understanding of the scattering properties of their atmospheres and will be a primary task of future flagship space- and ground-based telescopes. We introduce an enhanced capability of Planetary Intensity Code for Atmospheric Scattering Observations (PICASO), an open-source radiative transfer model used for exoplanet and brown dwarf atmospheres, to produce reflected light phase curves from three-dimensional atmospheric models. Since PICASO is coupled to the cloud code Virga, we produce phase curves for different cloud condensate species and varying sedimentation efficiencies (fsed) and apply this new functionality to Kepler-7b, a hot Jupiter with phase curve measurements dominated by reflected starlight. We model three different cloud scenarios for Kepler-7b: MgSiO3 clouds only, Mg2SiO4 clouds only, and Mg2SiO4, Al2O3, and TiO2 clouds. All our Virga models reproduce the cloudy region west of the substellar point expected from previous studies, as well as clouds at high latitudes and near the eastern limb, which are primarily composed of magnesium silicates. Al2O3 and TiO2 clouds dominate near the substellar point. We then compare our modeled reflected light phase curves to Kepler observations and find that models with all three cloud condensate species and low sedimentation efficiencies (0.03 - 0.1) match best, though our reflected light phase curves show intensities approximately one-third of those observed by Kepler. We conclude that a better understanding of zonal transport, cloud radiative feedback, and particle scattering properties is needed to further explain the differences between the modeled and observed reflected light fluxes.

In this paper, we study the composition of two independent GCPs which we call the iterated generalized counting process (IGCP). Its distributional properties such as the transition probabilities, probability generating function, state probabilities and its corresponding L\'evy measure are obtained. We study some integrals of the IGCP. Also, we study some of its extensions, for example, the compound IGCP, the multivariate IGCP and the $q$-iterated GCP. It is shown that the IGCP and the compound IGCP are identically distributed to a compound GCP which leads to their martingale characterizations. Later, a time-changed version of the IGCP is considered where the time is changed by an inverse stable subordinator. Using its covariance structure, we establish that the time-changed IGCP exhibits long-range dependence property. Moreover, we show that its increment process exhibits short-range dependence property. Also, it is shown that its one-dimensional distributions are not infinitely divisible. Initially, some of its potential real life applications are discussed.

We study an immigration effect in the time-changed linear birth-death process where the immigration occurs only if the population goes extinct. We call this process as the time-fractional linear birth-death process with immigration (TFLBDPwI). Its transient probabilities are obtained using the Adomian decomposition method. In a particular case, we discuss the accuracy of approximation for the obtained transient probabilities. Also, the first two moments of TFLBDPwI are derived. Later, we consider some particular cases of the TFLBDPwI and study their distributional properties in detail.

We present the results of microscopic investigations of antiferromagnetic CeNiGe$_3$, using neutron powder diffraction (NPD), inelastic neutron scattering (INS), and muon spin relaxation ($\mu$SR) measurements. CeNiGe$_3$ crystallizes in a centrosymmetric orthorhombic crystal structure (space group: $Cmmm$) and undergoes antiferromagnetic (AFM) ordering. The occurrence of long-range AFM ordering at $T_{\rm N} \approx 5.2$~K is confirmed by magnetic susceptibility, heat capacity, neutron diffraction, and $\mu$SR measurements. The NPD data characterize the AFM state with an incommensurate helical magnetic structure having a propagation vector $k$ = (0, 0.41, 1/2). In addition, INS measurements at 10~K identified two crystal electric field (CEF) excitations at 9.17~meV and 18.42~meV. We analyzed the INS data using a CEF model for an orthorhombic environment of Ce$^{3+}$ ($J=5/2$) and determined the CEF parameters and ground state wavefunctions of CeNiGe$_3$. Moreover, zero-field $\mu$SR data for CeNiGe$_3$ at $T< T_{\rm N}$ show long-range AFM ordering with three distinct oscillation frequencies corresponding to three different internal fields at the muon sites. The internal fields at the muon-stopping sites have been further investigated using density functional theory calculations., Comment: 13 pages, 9 figures

Kagome superconductors AV$_{3}$Sb$_{5}$ provide a unique platform for studying the interplay between a variety of electronic orders, including superconductivity, charge density waves, nematic phases and more. Understanding the evolution of the electronic state from the charge density wave to the superconducting transition is essential for unraveling the interplay of charge, spin, and lattice degrees of freedom giving rise to the unusual magnetic properties of these nonmagnetic metals. Previous zero-field and high-field $\mu$SR studies revealed two anomalies in the muon spin relaxation rate, a first change at $T_{CDW} \sim 100$ K and a second steep increase at $T^{*}\sim 40$ K, further enhanced by an applied magnetic field, thus suggesting a contribution of magnetic origin. In this study, we use the avoided level crossing $\mu$SR technique to investigate charge order in near-zero applied field. By tracking the temperature dependence of quadrupolar level-crossing resonances, we examined the evolution of the electric field gradient at V nuclei in the kagome plane. Our results show a significant rearrangement of the charge density starting at $T^{*}$ indicating a transition in the charge distribution, likely electronic in origin, well below $T_{CDW}$. These findings, combined with previous $\mu$SR, STM, and NMR studies, emphasize the intertwined nature of proximate phases in these systems, with the charge rearrangement dominating the additional increase in $\mu$SR relaxation rate below $T^{*}$.

We present the mission concept "Mission to Analyze the UltraViolet universE" (MAUVE), a wide-field spectrometer and imager conceived during the inaugural NASA Astrophysics Mission Design School. MAUVE responds to the 2023 Announcement of Opportunity for Probe-class missions, with a budget cap of \$1 billion, and would hypothetically launch in 2031. However, the formulation of MAUVE was an educational exercise and the mission is not being developed further. The Principal Investigator-led science of MAUVE aligns with the priorities outlined in the 2020 Astrophysics Decadal Survey, enabling new characterizations of exoplanet atmospheres, the early-time light curves of some of the universe's most explosive transients, and the poorly-understood extragalactic background light. Because the Principal Investigator science occupies 30% of the observing time available during the mission's 5 yr lifespan, we provide an observing plan that would allow for 70% of the observing time to be used for General Observer programs, with community-solicited proposals. The onboard detector (THISTLE) claims significant heritage from the Space Telescope Imaging Spectrograph on Hubble, but extends its wavelength range down to the extreme UV. We note that MAUVE would be the first satellite in decades with the ability to access this regime of the electromagnetic spectrum. MAUVE has a field of view of 900" x 900" a photometric sensitivity extending to $m_{UV}\leq 24$, and a resolving power of $R\sim1000$. This paper provides full science and mission traceability matrices for this concept, and also outlines cost and scheduling timelines aimed at enabling a within-budget mission and an on-time launch., Comment: 21 pages, 15 figures. Published by the Publications of the Astronomical Society of the Pacific

We study a fractional birth-death process with state dependent birth and death rates. It is defined using a system of fractional differential equations that generalizes the classical birth-death process introduced by Feller (1939). We obtain the closed form expressions for its transient probabilities using Adomian decomposition method. In this way, we obtain the unknown transient probabilities for the classical birth-death process (see Feller (1968), p. 454). Its various distributional properties are studied. For the case of linear birth and death rates, the obtained results are verified with the existing results. Also, we discuss the cumulative births in the fractional linear birth-death process. Later, we consider a time-changed linear birth-death process where we discuss the asymptotic behaviour of the distribution function of its extinction time at zero.

The extreme environments of transiting close-in exoplanets in highly-eccentric orbits are ideal for testing exo-climate physics. Spectroscopically resolved phase curves not only allow for the characterization of their thermal response to irradiation changes but also unveil phase-dependent atmospheric chemistry and dynamics. We observed a partial phase curve of the highly-eccentric close-in giant planet HAT-P-2b ($e=0.51,M=9M_{\rm{Jup}}$) with the Wide Field Camera 3 aboard the Hubble Space Telescope. Using these data, we updated the planet's orbital parameters and radius, and retrieved high-frequency pulsations consistent with the planet-induced pulsations reported in Spitzer data. We found that the peak in planetary flux occurred at $6.7\pm0.6$ hr after periastron, with a heating and cooling timescales of $9.0^{+3.5}_{-2.1}$ hr, and $3.6^{+0.7}_{-0.6}$ hr, respectively. We compare the light-curve to various 1-dimensional and 3-dimensional forward models, varying the planet's chemical composition. The strong contrast in flux increase and decrease timescales before and after periapse indicates an opacity term that emerges during the planet's heating phase, potentially due to more H$^{-}$ than expected from chemical equilibrium models. The phase-resolved spectra are largely featureless, that we interpret as indicative an inhomogeneous dayside. However, we identified an anomalously high flux in the spectroscopic bin coinciding with the hydrogen Paschen $\beta$ line and that is likely connected to the planet's orbit. We interpret this as due to shock heating of the upper atmosphere given the short timescale involved, or evidence for other star-planet interactions., Comment: In review in AJ

The search for life beyond the Solar System remains a primary goal of current and near-future missions, including NASA's upcoming Habitable Worlds Observatory (HWO). However, research into determining the habitability of terrestrial exoplanets has been primarily focused on comparisons to modern-day Earth. Additionally, current characterization strategies focus on the unpolarized flux from these worlds, taking into account only a fraction of the informational content of the reflected light. Better understanding the changes in the reflected light spectrum of the Earth throughout its evolution, as well as analyzing its polarization, will be crucial for mapping its habitability and providing comparison templates to potentially habitable exoplanets. Here we present spectropolarimetric models of the reflected light from the Earth at six epochs across all four geologic eons. We find that the changing surface albedos and atmospheric gas concentrations across the different epochs allow the habitable and non-habitable scenarios to be distinguished, and diagnostic features of clouds and hazes are more noticeable in the polarized signals. We show that common simplifications for exoplanet modeling, including Mie scattering for fractal particles, affect the resulting planetary signals and can lead to non-physical features. Finally, our results suggest that pushing the HWO planet-to-star flux contrast limit down to 1 $\times$ 10$^{-13}$ could allow for the characterization in both unpolarized and polarized light of an Earth-like planet at any stage in its history., Comment: 26 pages, 20 figures. Submitted for publication in The Astrophysical Journal

Recent mid-infrared observations with JWST/MIRI have resulted in the first direct detections of absorption features from silicate clouds in the transmission spectra of two transiting exoplanets, WASP-17 b and WASP-107 b. In this paper, we measure the mid-infrared ($5-12$ $\mu$m) dayside emission spectrum of the benchmark hot Jupiter HD 189733 b with MIRI LRS by combining data from two secondary eclipse observations. We confirm the previous detection of H$_2$O absorption at 6.5 $\mu$m from Spitzer/IRS and additionally detect H$_2$S as well as an absorption feature at 8.7 $\mu$m in both secondary eclipse observations. The excess absorption at 8.7 $\mu$m can be explained by the presence of small ($\sim$0.01 $\mu$m) grains of SiO$_2$[s] in the uppermost layers of HD 189733 b's dayside atmosphere. This is the first direct detection of silicate clouds in HD 189733 b's atmosphere, and the first detection of a distinct absorption feature from silicate clouds on the day side of any hot Jupiter. We find that models including SiO$_2$[s] are preferred by $6-7\sigma$ over clear models and those with other potential cloud species. The high altitude location of these silicate particles is best explained by formation in the hottest regions of HD 189733 b's dayside atmosphere near the substellar point. We additionally find that HD 189733 b's emission spectrum longward of 9 $\mu$m displays residual features not well captured by our current atmospheric models. When combined with other JWST observations of HD 189733 b's transmission and emission spectrum at shorter wavelengths, these observations will provide us with the most detailed picture to date of the atmospheric composition and cloud properties of this benchmark hot Jupiter., Comment: 21 pages, 7 Figures, 3 Tables, Accepted to ApJL

We investigated the Re-based kagome superconductor Re$_2$Zr through various measurements, including resistivity, magnetization, specific heat, and muon spin rotation and relaxation spectroscopy. These results suggest that Re$_2$Zr is a moderately coupled potential two-gap superconductor. Zero-field muon relaxation data indicate the possible presence of a time-reversal symmetry-breaking state in the superconducting ground state. Our investigation identifies Re$_{2}$Zr as a new unconventional superconductor with a potential complex order parameter that warrants considerable experimental and theoretical interest., Comment: 9 pages, 6 figures

Barred galaxies exhibit boxy/peanut or X-shapes (BP/X) protruding from their disks in edge-on views. Two types of BP/X morphologies exist depending on whether the X-wings meet at the center (CX) or are off-centered (OX). Orbital studies indicate that various orbital types can generate X-shaped structures. Here, we provide a classification approach that identifies the specific orbit families responsible for generating OX and CX-shaped structures. Applying this approach to three different N-body bar models, we show that both OX and CX structures are associated with the x1 orbit family, but OX-supporting orbits possess higher angular momentum (closer to x1 orbits) than orbits in CX structures. Consequently, as the bar slows down the contribution of higher angular momentum OX-supporting orbits decreases and that of lower angular momentum orbits increases resulting in an evolution of the morphology from OX to CX. If the bar does not slow down, the shape of the BP/X structure and the fractions of OX/CX supporting orbits remain substantially unchanged. Bars that do not undergo buckling but that do slow down initially show the OX structure and are dominated by high angular momentum orbits, transitioning to a CX morphology. Bars that buckle exhibit a combination of both OX and CX supporting orbits immediately after the buckling, but become more CX dominated as their pattern speed decreases. This study demonstrates that the evolution of BP/X morphology and orbit populations strongly depends on the evolution of the bar angular momentum., Comment: 16 pages, 12 figures, Accepted for publication in ApJ

Although exoplanetary science was not initially projected to be a substantial part of the Spitzer mission, its exoplanet observations set the stage for current and future surveys with JWST and Ariel. We present a comprehensive reduction and analysis of Spitzer's 4.5 micron phase curves of 29 hot Jupiters on low-eccentricity orbits. The analysis, performed with the Spitzer Phase Curve Analysis (SPCA) pipeline, confirms that BLISS mapping is the best detrending scheme for most, but not all, observations. Visual inspection remains necessary to ensure consistency across detrending methods due to the diversity of phase curve data and systematics. Regardless of the model selection scheme - whether using the lowest-BIC or a uniform detrending approach - we observe the same trends, or lack thereof. We explore phase curve trends as a function of irradiation temperature, orbital period, planetary radius, mass, and stellar effective temperature. We discuss the trends that are robustly detected and provide potential explanations for those that are not observed. While it is almost tautological that planets receiving greater instellation are hotter, we are still far from confirming dynamical theories of heat transport in hot Jupiter atmospheres due to the sample's diversity. Even among planets with similar temperatures, other factors like rotation and metallicity vary significantly. Larger, curated sample sizes and higher-fidelity phase curve measurements from JWST and Ariel are needed to firmly establish the parameters governing day-night heat transport on synchronously rotating planets., Comment: 16 pages, 6 figures, submitted to AAS journal

We consider a generalized birth-death process (GBDP) whose state space is a finite subset of a $q$-dimensional lattice. It is assumed that there can be a jump of finite step size in all possible directions such that the probability of simultaneous transition in more than one direction is zero. Such processes are of interest as their transition probability matrix is diagonalizable under suitable conditions. Thus, their $k$-step transition probabilities can be efficiently obtained. For GBDP on two-dimensional finite grid, we obtain a sufficient and necessary condition for the vertical and horizontal transition probability matrices to commute. Later, we extend these results to the case of $q$-dimensional finite grid. We obtain the minimum number of constraints required on transition probabilities that ensure the commutation of transition probability matrices for each possible direction.

We present the AstroSat UV Deep Field South (AUDFs), an imaging survey using the wide-field Ultraviolet Imaging Telescope on board AstroSat. AUDFs covers $\sim 236$ arcmin$^{2}$ of the sky area, including the Great Observatories Origins Deep Survey (GOODS) South field in F154W and N242W filters. The deep and shallow parts of AUDFs have exposure time $\sim 62000$ and $\sim31000$ sec respectively, in the F154W filter, while in the N242W filter, they are $\sim 64000$ and $\sim34000$ sec. These observations reached a $3\sigma$ depth of 27.2 and 27.7 AB mag with a $50\%$ completeness limit of 27 and 27.6 AB mag in the F154W and N242W filters, respectively. With the acquired depth, AUDFs is the deepest far and near-UV imaging data covering the largest area known to date at 1.2" - 1.6" spatial resolution. Two primary catalogs were constructed for the F154W and N242W filters, each containing 13495 and 19374 sources brighter than the 3$\sigma$ detection limit, respectively. Our galaxy counts power-law slope $\sim0.43$~dex~mag$^{-1}$ in the N242W filter matches well with HST/WFC3/UVIS observations. A wide range of extra-galactic science can be achieved with this unique data, such as providing a sample of galaxies emitting ionizing photons in the redshift range $z \sim 1 - 3$ and beyond; constraining the UV luminosity function, investigating the extended-UV (XUV) emission around star-forming galaxies and UV morphologies for $z < 1$. The UV catalog will enhance the legacy value of the existing optical/IR imaging and spectroscopic observations from ground and space-based telescopes on the GOODS South field., Comment: 26 pages, 19 figures, 7 tables, accepted for publication in the Astrophysical Journal Supplement Series, comments are welcome

In this paper, we consider a fractional Poisson random field (FPRF) on positive plane. It is defined as a process whose one dimensional distribution is the solution of a system of fractional partial differential equations. A time-changed representation for the FPRF is given in terms of the composition of Poisson random field with a bivariate random process. Some integrals of the FPRF are introduced and studied. Using the Adomian decomposition method, a closed form expression for its probability mass function is obtained in terms of the generalized Wright function. Some results related to the order statistics of random numbers of random variables are presented. Also, we introduce a generalization of Poisson random field on $\mathbb{R}^d_+$, $d\ge1$ which reduces to the Poisson random field in a special case. For $d=1$, it further reduces to a generalized Poisson process (GPP). A time-changed representation for the GPP is established. Moreover, we construct a time-changed linear and planer random motions of a particle driven by the GPP. The conditional distribution of the random position of particle is derived. Later, we define the compound fractional Poisson random field via FPRF. Also, a generalized version of it on $\mathbb{R}^d_+$, $d\ge1$ is discussed.

Statistical Shape Models (SSMs) excel at identifying population level anatomical variations, which is at the core of various clinical and biomedical applications, including morphology-based diagnostics and surgical planning. However, the effectiveness of SSM is often constrained by the necessity for expert-driven manual segmentation, a process that is both time-intensive and expensive, thereby restricting their broader application and utility. Recent deep learning approaches enable the direct estimation of Statistical Shape Models (SSMs) from unsegmented images. While these models can predict SSMs without segmentation during deployment, they do not address the challenge of acquiring the manual annotations needed for training, particularly in resource-limited settings. Semi-supervised and foundation models for anatomy segmentation can mitigate the annotation burden. Yet, despite the abundance of available approaches, there are no established guidelines to inform end-users on their effectiveness for the downstream task of constructing SSMs. In this study, we systematically evaluate the potential of weakly supervised methods as viable alternatives to manual segmentation's for building SSMs. We establish a new performance benchmark by employing various semi-supervised and foundational model methods for anatomy segmentation under low annotation settings, utilizing the predicted segmentation's for the task of SSM. We compare the modes of shape variation and use quantitative metrics to compare against a shape model derived from a manually annotated dataset. Our results indicate that some methods produce noisy segmentation, which is very unfavorable for SSM tasks, while others can capture the correct modes of variations in the population cohort with 60-80\% reduction in required manual annotation.

Cognitive textual and visual reasoning tasks, such as puzzles, series, and analogies, demand the ability to quickly reason, decipher, and evaluate patterns both textually and spatially. While LLMs and VLMs, through extensive training on large amounts of human-curated data, have attained a high level of pseudo-human intelligence in some common sense reasoning tasks, they still struggle with more complex reasoning tasks that require cognitive understanding. In this work, we introduce a new dataset, NTSEBench, designed to evaluate the cognitive multi-modal reasoning and problem-solving skills of large models. The dataset comprises 2,728 multiple-choice questions comprising of a total of 4,642 images across 26 categories sampled from the NTSE examination conducted nationwide in India, featuring both visual and textual general aptitude questions that do not rely on rote learning. We establish baselines on the dataset using state-of-the-art LLMs and VLMs. To facilitate a comparison between open source and propriety models, we propose four distinct modeling strategies to handle different modalities (text and images) in the dataset instances., Comment: 15 pages, 2 figures, 5 tables

We report results from 8 hours of JWST/MIRI LRS spectroscopic monitoring directly followed by 7 hours of JWST/NIRSpec prism spectroscopic monitoring of the benchmark binary brown dwarf WISE 1049AB, the closest, brightest brown dwarfs known. We find water, methane, and CO absorption features in both components, including the 3.3 $\mu$m methane absorption feature and a tentative detection of small grain ($<$ 1$\mu$m) silicate absorption at $>$8.5 $\mu$m in WISE 1049A. Both components vary significantly ($>$1$\%$), with WISE 1049B displaying larger variations than WISE 1049A. Using K-means clustering, we find three main transition points in wavelength for both components of the binary: 1) change in behavior at $\sim$2.3 $\mu$m coincident with a CO absorption bandhead, 2) change in behavior at 4.2 $\mu$m, close to the CO fundamental band at $\lambda >$ 4.4 $\mu$m, and 3) change in behavior at 8.3-8.5 $\mu$m, potentially corresponding to silicate absorption. We interpret the lightcurves observed with both NIRSpec and MIRI as likely stemming from 1) a deep pressure level driving the double-peaked variability seen in WISE 1049B at wavelengths $<$2.3 $\mu$m and $>$8.5 $\mu$m, 2) an intermediate pressure level shaping the lightcurve morphology between 2.3 and 4.2 $\mu$m, and 3) a higher-altitude pressure level producing single-peaked and plateaued lightcurve behavior between 4.2 and 8.5 $\mu$m., Comment: 28 pages, 27 figures, accepted to MNRAS

We report the detection of Lyman-continuum (LyC) photons from a massive interacting system at $z=1.097$ in the Hubble Ultra Deep Field. The LyC detection is made in the far-ultraviolet F154W band of the UVIT telescope onboard AstroSat. Both JWST and HST imaging of the system reveal signs that it is a likely merger. In particular, high-resolution imaging in the JWST bands reveals an infrared luminous object within the system that is faint in the bluer HST bands. The ionized-gas kinematics from the MUSE-UDF data supports the merger hypothesis. We estimate that the entire system is leaking more than $8 \%$ of its ionizing photons to the intergalactic medium. The SED-derived stellar masses of the two components indicate that this is a major merger with a mass ratio of ${1.13 \pm 0.37}$. This detection hints at the potential contribution of massive interacting systems at higher redshifts, when major mergers were more frequent, to the ionizing budget of the universe., Comment: 16 pages, 8 figures, 1 table (Accepted for publication in ApJ)

In this paper, we study a multivariate version of the generalized counting process (GCP) and discuss its various time-changed variants. The time is changed using random processes such as the stable subordinator, inverse stable subordinator, and their composition, tempered stable subordinator, gamma subordinator $etc.$ Several distributional properties that include the probability generating function, probability mass function and their governing differential equations are obtained for these variants. It is shown that some of these time-changed processes are L\'evy and for such processes we have derived the associated L\'evy measure. The explicit expressions for the covariance and codifference of the component processes for some of these time-changed variants are obtained. An application of the multivariate generalized space fractional counting process to shock models is discussed.

Until now, observations have caught up only a handful of galaxies in ongoing buckling action. Interestingly, N-body simulations over the past several decades show that almost every bar buckles or vertically thickens as soon as it reaches its peak strength during its evolution and leads to box$/$ peanut$/$ x (BPX) shapes. In order to understand the effect of multiple buckling events on the observable properties of galactic bar and disk, we perform an N-body simulation of a Milky Way-type disk. The axisymmetric galaxy disk forms a bar within a Gyr of its evolution and the bar undergoes two successive buckling events. We report that the time spans of these two buckling events are 220 Myr and 1 Gyr which have almost similar strengths of the bending modes. As a result of these two buckling events, the sizes of BPX shapes are around 5.8 kpc and 8.6 kpc which are around two-thirds of the bar length at the end of each buckling event. We find that the first buckling occurs at a smaller scale (radius less than 3 kpc) with a shorter time span affecting the larger length scales of the disk which is quantified in terms of changes in $m$ =2 and $m$ = 4 Fourier modes. While the second buckling occurs at larger scales (radius of around 6 kpc) affecting the inner disk the most. Finally, we provide observable kinematic signatures (for example quadrupolar patterns of the line-of-sight velocities) which can potentially differentiate the successive buckling events., Comment: 12 pages, 13 figures, Accepted in MNRAS, comments are welcome!

Large-scale video conferencing services incur significant network cost while serving surging global demands. Our work systematically explores the opportunity to offload a fraction of this traffic to the Internet, a cheaper routing option offered already by cloud providers, from WAN without drop in application performance. First, with a large-scale latency measurement study with 3.5 million data points per day spanning 241K source cities and 21 data centers across the globe, we demonstrate that Internet paths perform comparable to or better than the private WAN for parts of the world (e.g., Europe and North America). Next, we present Titan, a live (12+ months) production system that carefully moves a fraction of the conferencing traffic to the Internet using the above observation. Finally, we propose Titan-Next, a research prototype that jointly assigns the conferencing server and routing option (Internet or WAN) for individual calls. With 5 weeks of production data, we show Titan-Next reduces the sum of peak bandwidth on WAN links that defines the operational network cost by up to 61% compared to state-of-the-art baselines. We will open-source parts of the measurement data.

The dark matter halo properties, for example, mass, spin and concentration play a significant role in the formation and evolution of bars in disk galaxies. This study highlights the importance of a new parameter: the dark matter halo angular momentum distribution in the central region of disk. We experiment with N-body galaxy models having a disk and dark matter similar to Milky Way-type galaxies. In these models, we vary the discontinuity of the angular momentum distribution of the halo (the total spin is the same for all models). Our N-body experiments suggest that bar forms in all models after a few Gyr of disk evolution. However, in the secular evolution of the bar, as we evolve these models until 9.78 Gyr, the bar gains its strength in the model with the most continuous halo angular momentum distribution, and the bar loses strength for the most discontinuous halo angular momentum distribution. The secular evolution of the bar suggests that box/peanut/x-shaped bulges similar to those found in the Milky Way disk should be more pronounced in halos with continuous halo angular momentum distributions. This study demonstrates the importance of the initial condition setup of galaxy systems, namely the discontinuity in the dark matter halo angular momentum distribution for a given density distribution, on the bar secular evolution in the disk galaxy simulations. Further, this study helps reconcile the conflicting results of bar secular evolution in a high-spinning halo of the recent literature., Comment: 11 pages, 9 figures, accepted for publication in ApJ, comments are welcome

In an era increasingly influenced by artificial intelligence, the detection of fake news is crucial, especially in contexts like election seasons where misinformation can have significant societal impacts. This study evaluates the effectiveness of various LLMs in identifying and filtering fake news content. Utilizing a comparative analysis approach, we tested four large LLMs -- GPT-4, Claude 3 Sonnet, Gemini Pro 1.0, and Mistral Large -- and two smaller LLMs -- Gemma 7B and Mistral 7B. By using fake news dataset samples from Kaggle, this research not only sheds light on the current capabilities and limitations of LLMs in fake news detection but also discusses the implications for developers and policymakers in enhancing AI-driven informational integrity.

Edge-on galaxies act as the best laboratories to understand the origin of thin and thick discs in galaxies. Measurement of spatially resolved stellar population properties in such galaxies, particularly age, metallicity and [$\alpha$/Fe], are crucial to understanding the formation and evolution of disc galaxies. Such measurements are made possible from stellar population model fits to deep integral field spectroscopic (IFU) observations of resolved galaxies. We utilise archival MUSE IFU observations of the edge-on galaxy ESO 544-27 to uncover the formation history of its thin and thick discs through its stellar populations. We find the thin disc of the galaxy is dominated by an old ($>9$ Gyr) low [$\alpha$/Fe] metal-rich stellar population. Its outer thick disc is dominated by an old ($>9$ Gyr) high [$\alpha$/Fe] metal-rich component that should have formed with higher star-formation efficiency than the Milky Way thick disc. We thus find [$\alpha$/Fe] dichotomy in ESO 544-27 with its thin and thick discs dominated by low and high [$\alpha$/Fe] stellar populations respectively. However, we also find a metal-rich younger ($<2$ Gyr old) stellar population in ESO 544-27. The galaxy was nearly quenched until its star-formation was reignited recently first in the outer and inner thick disc ($\sim$1 Gyr ago) and then in the thin disc ($\sim$600 Myr ago). We thus find that both the low [$\alpha$/Fe] thin and high [$\alpha$/Fe] thick discs of ESO 544-27 are inhabited primarily by similarly old metal-rich stellar populations, a contrast to that of other galaxies with known thin and thick disc stellar population properties., Comment: 13 pages, 12 figures, submitted to MNRAS after the second referee report

Enterprises grapple with the significant challenge of managing proprietary unstructured data, hindering efficient information retrieval. This has led to the emergence of AI-driven information retrieval solutions, designed to adeptly extract relevant insights to address employee inquiries. These solutions often leverage pre-trained embedding models and generative models as foundational components. While pre-trained embeddings may exhibit proximity or disparity based on their original training objectives, they might not fully align with the unique characteristics of enterprise-specific data, leading to suboptimal alignment with the retrieval goals of enterprise environments. In this paper, we propose a comprehensive methodology for contextualizing pre-trained embedding models to enterprise environments, covering the entire process from data preparation to model fine-tuning and evaluation. By adapting the embeddings to better suit the retrieval tasks prevalent in enterprises, we aim to enhance the performance of information retrieval solutions. We discuss the process of fine-tuning, its effect on retrieval accuracy, and the potential benefits for enterprise information management. Our findings demonstrate the efficacy of fine-tuned embedding models in improving the precision and relevance of search results in enterprise settings.

The prediction of crop yields internationally is a crucial objective in agricultural research. Thus, this study implements 6 regression models (Linear, Tree, Gradient Descent, Gradient Boosting, K Nearest Neighbors, and Random Forest) to predict crop yields in 37 developing countries over 27 years. Given 4 key training parameters, insecticides (tonnes), rainfall (mm), temperature (Celsius), and yield (hg/ha), it was found that our Random Forest Regression model achieved a determination coefficient (r2) of 0.94, with a margin of error (ME) of .03. The models were trained and tested using the Food and Agricultural Organization of the United Nations data, along with the World Bank Climate Change Data Catalog. Furthermore, each parameter was analyzed to understand how varying factors could impact overall yield. We used unconventional models, contrary to generally used Deep Learning (DL) and Machine Learning (ML) models, combined with recently collected data to implement a unique approach in our research. Existing scholarship would benefit from understanding the most optimal model for agricultural research, specifically using the United Nations data., Comment: 12 pages, 8 figures, 1 table, Guided by Dr. Aditya Undurti

We present comprehensive investigations into the structural, superconducting, and topological properties of Bi$_2$PdPt. Magnetization and heat capacity measurements performed on polycrystalline Bi$_2$PdPt demonstrate a superconducting transition at $\approx$ 0.8 K. Moreover, muon spin relaxation/rotation ($\mu$SR) measurements present evidence for a time reversal symmetry preserving, isotropically gapped superconducting state in Bi$_2$PdPt. We have also performed density-functional theory (DFT) calculations on Bi$_2$PdPt alongside the more general isostructural systems, BiPd$_{x}$Pt$_{1-x}$, of which Bi$_2$PdPt and $\gamma$-BiPd are special cases for $x=0.5$ and $x=1$ respectively. We have calculated the $Z_2$ topological index from our DFT calculations for a range of substitution fractions, $x$, between $x=0$ and $x=1$ characterizing the topology of the band structure. We find a non-trivial topological state when $x>0.75$ and a trivial topological state when $x<0.75$. Therefore our results indicate that BiPd$_{x}$Pt$_{1-x}$ could be a topological superconductor for $x>0.75$., Comment: 10 pages, 7 figures

Supervised methods for 3D anatomy segmentation demonstrate superior performance but are often limited by the availability of annotated data. This limitation has led to a growing interest in self-supervised approaches in tandem with the abundance of available un-annotated data. Slice propagation has emerged as an self-supervised approach that leverages slice registration as a self-supervised task to achieve full anatomy segmentation with minimal supervision. This approach significantly reduces the need for domain expertise, time, and the cost associated with building fully annotated datasets required for training segmentation networks. However, this shift toward reduced supervision via deterministic networks raises concerns about the trustworthiness and reliability of predictions, especially when compared with more accurate supervised approaches. To address this concern, we propose the integration of calibrated uncertainty quantification (UQ) into slice propagation methods, providing insights into the model's predictive reliability and confidence levels. Incorporating uncertainty measures enhances user confidence in self-supervised approaches, thereby improving their practical applicability. We conducted experiments on three datasets for 3D abdominal segmentation using five UQ methods. The results illustrate that incorporating UQ improves not only model trustworthiness, but also segmentation accuracy. Furthermore, our analysis reveals various failure modes of slice propagation methods that might not be immediately apparent to end-users. This study opens up new research avenues to improve the accuracy and trustworthiness of slice propagation methods., Comment: 13 pages including Supplementary, 4 figures

Hematoxylin and Eosin (H&E) staining is the most commonly used for disease diagnosis and tumor recurrence tracking. Hematoxylin excels at highlighting nuclei, whereas eosin stains the cytoplasm. However, H&E stain lacks details for differentiating different types of cells relevant to identifying the grade of the disease or response to specific treatment variations. Pathologists require special immunohistochemical (IHC) stains that highlight different cell types. These stains help in accurately identifying different regions of disease growth and their interactions with the cell's microenvironment. The advent of deep learning models has made Image-to-Image (I2I) translation a key research area, reducing the need for expensive physical staining processes. Pix2Pix and CycleGAN are still the most commonly used methods for virtual staining applications. However, both suffer from hallucinations or staining irregularities when H&E stain has less discriminate information about the underlying cells IHC needs to highlight (e.g.,CD3 lymphocytes). Diffusion models are currently the state-of-the-art models for image generation and conditional generation tasks. However, they require extensive and diverse datasets (millions of samples) to converge, which is less feasible for virtual staining applications.Inspired by the success of multitask deep learning models for limited dataset size, we propose StainDiffuser, a novel multitask dual diffusion architecture for virtual staining that converges under a limited training budget. StainDiffuser trains two diffusion processes simultaneously: (a) generation of cell-specific IHC stain from H&E and (b) H&E-based cell segmentation using coarse segmentation only during training. Our results show that StainDiffuser produces high-quality results for easier (CK8/18,epithelial marker) and difficult stains(CD3, Lymphocytes).

Transformers have emerged as the state-of-the-art architecture in medical image registration, outperforming convolutional neural networks (CNNs) by addressing their limited receptive fields and overcoming gradient instability in deeper models. Despite their success, transformer-based models require substantial resources for training, including data, memory, and computational power, which may restrict their applicability for end users with limited resources. In particular, existing transformer-based 3D image registration architectures face two critical gaps that challenge their efficiency and effectiveness. Firstly, although window-based attention mechanisms reduce the quadratic complexity of full attention by focusing on local regions, they often struggle to effectively integrate both local and global information. Secondly, the granularity of tokenization, a crucial factor in registration accuracy, presents a performance trade-off: smaller voxel-size tokens enhance detail capture but come with increased computational complexity, higher memory usage, and a greater risk of overfitting. We present \name, a transformer-based architecture for unsupervised 3D image registration that balances local and global attention in 3D volumes through a plane-based attention mechanism and employs a Hi-Res tokenization strategy with merging operations, thus capturing finer details without compromising computational efficiency. Notably, \name sets a new benchmark for performance on the OASIS dataset with 16-27x fewer parameters. https://github.com/MedVIC-Lab/Efficient_Morph_Registration, Comment: *Equal Contribution, **Corresponding Author

Statistical Shape Modeling (SSM) effectively analyzes anatomical variations within populations but is limited by the need for manual localization and segmentation, which relies on scarce medical expertise. Recent advances in deep learning have provided a promising approach that automatically generates statistical representations (as point distribution models or PDMs) from unsegmented images. Once trained, these deep learning-based models eliminate the need for manual segmentation for new subjects. Most deep learning methods still require manual pre-alignment of image volumes and bounding box specification around the target anatomy, leading to a partially manual inference process. Recent approaches facilitate anatomy localization but only estimate population-level statistical representations and cannot directly delineate anatomy in images. Additionally, they are limited to modeling a single anatomy. We introduce MASSM, a novel end-to-end deep learning framework that simultaneously localizes multiple anatomies, estimates population-level statistical representations, and delineates shape representations directly in image space. Our results show that MASSM, which delineates anatomy in image space and handles multiple anatomies through a multitask network, provides superior shape information compared to segmentation networks for medical imaging tasks. Estimating Statistical Shape Models (SSM) is a stronger task than segmentation, as it encodes a more robust statistical prior for the objects to be detected and delineated. MASSM allows for more accurate and comprehensive shape representations, surpassing the capabilities of traditional pixel-wise segmentation.

Previous attempts have been made to characterize the atmospheres of directly imaged planets at low-resolution (R$\sim$10s-100s), but the presence of clouds has often led to degeneracies in the retrieved atmospheric abundances with cloud opacity and temperature structure that bias retrieved compositions. In this study, we perform retrievals on the ultra-young ($\lesssim$ 5 Myr) directly imaged planet ROXs 42B b with both a downsampled low-resolution $JHK$-band spectrum from Gemini/NIFS and Keck/OSIRIS, and a high-resolution $K$-band spectrum from pre-upgrade Keck/NIRSPAO. Using the atmospheric retrieval framework of petitRADTRANS, we analyze both data sets individually and combined. We additionally fit for the stellar abundances and other physical properties of the host stars, a young M spectral type binary, using the SPHINX model grid. We find that the measured C/O, $0.50\pm0.05$, and metallicity, [Fe/H] = $-0.67\pm0.35$, for ROXs 42B b from our high-resolution spectrum agree with that of its host stars within 1$\sigma$. The retrieved parameters from the high-resolution spectrum are also independent of our choice of cloud model. In contrast, the retrieved parameters from the low-resolution spectrum show strong degeneracies between the clouds and the retrieved metallicity and temperature structure. When we retrieve on both data sets together, we find that these degeneracies are reduced but not eliminated, and the final results remain highly sensitive to cloud modeling choices. We conclude that high-resolution spectroscopy offers the most promising path for reliably determining atmospheric compositions of directly imaged companions independent of their cloud properties., Comment: Accepted to the Astronomical Journal, 25 pages, 12 figures, 3 tables