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A coherent vibrational wavepacket is launched and manipulated in the symmetric stretch (a$_1$) mode of CBr$_4$, by impulsive stimulated Raman scattering from non-resonant 400 nm laser pump pulses with various peak intensities on the order of tens of 10$^{12}$ W/cm$^2$. Extreme ultraviolet (XUV) attosecond transient absorption spectroscopy (ATAS) records the wavepacket dynamics as temporal oscillations in XUV absorption energy at the bromine M$_{4,5}$ 3d$_{3/2,5/2}$ edges around 70 eV. The results are augmented by nuclear time-dependent Schr\"odinger equation simulations. Slopes of the (Br-3d$_{3/2,5/2}$)$^{-1}$10a$_1^*$ core-excited state potential energy surface (PES) along the a$_1$ mode are calculated to be -9.4 eV/{\AA} from restricted open-shell Kohn-Sham calculations. Using analytical relations derived for the small-displacement limit with the calculated slopes of the core-excited state PES, a deeper insight into the vibrational dynamics is obtained by retrieving the experimental excursion amplitude of the vibrational wavepacket and the amount of population transferred to the vibrational first-excited state, as a function of pump-pulse peak intensity. Experimentally, the results show that XUV ATAS is capable of easily resolving oscillations in the XUV absorption energy on the order of few to tens of meV and tens of femtosecond time precision, limited only by the averaging times in the experimental scans. This corresponds to oscillations of C-Br bond length on the order of 10$^{-4}$ to 10$^{-3}$ {\AA}. The results and the analytic relationships offer a clear physical picture, on multiple levels of understanding, for how the pump-pulse intensity controls the vibrational dynamics launched by non-resonant ISRS in the small-displacement limit.

The increasing availability of GPUs for scientific computing has prompted interest in accelerating quantum chemical calculations through their use. The complexity of integral kernels for high angular momentum basis functions however often limits the utility of GPU implementations with large basis sets or for metal containing systems. In this work, we report implementation of $f$ function support in the GPU-accelerated TeraChem software package through the development of efficient kernels for the evaluation of Hamiltonian integrals. The high efficiency of the resulting code is demonstrated through density functional theory (DFT) calculations on increasingly large organic molecules and transition metal complexes, as well as coupled cluster singles and doubles (CCSD) calculations on water clusters. Preliminary investigations into Ni(I) catalysis with DFT and the photochemistry of MnH(CH$_3$) with complete active space self-consistent field (CASSCF) are also carried out. Overall, our GPU-accelerated software appears to be well-suited for fast simulation of large transition metal containing systems, as well as organic molecules., Comment: Updated benchmarks from previous version

Metagenomic studies have primarily relied on de novo assembly for reconstructing genes and genomes from microbial mixtures. While reference-guided approaches have been employed in the assembly of single organisms, they have not been used in a metagenomic context. Here we describe the first effective approach for reference-guided metagenomic assembly that can complement and improve upon de novo metagenomic assembly methods for certain organisms. Such approaches will be increasingly useful as more genomes are sequenced and made publicly available., Comment: 18 pages, 6 figures, 3 tables, one supplementary material

The fate of thymine upon excitation by ultraviolet radiation has been the subject of intense debate over the past three decades. Today, it is widely believed that its ultrafast excited state decay stems from a radiationless transition from the bright ${\pi}{\pi}^*$ state to a dark $n{\pi}^*$ state. However, conflicting theoretical predictions have made the experimental data difficult to interpret. Here we simulate the ultrafast dynamics in thymine at the highest level of theory to date, performing wavepacket dynamics with a new coupled cluster method. Our simulation confirms an ultrafast ${\pi}{\pi}^*$ to $n{\pi}^*$ transition (${\tau} = 41 \pm 14$ fs). Furthermore, the predicted oxygen-edge X-ray absorption spectra agree quantitatively with the experimental results. Our simulation also predicts an as-yet uncharacterized photochemical pathway: a ${\pi}{\sigma}^*$ channel that leads to hydrogen dissociation at one of the two N-H bonds in thymine. Similar behavior has been identified in other heteroaromatic compounds, including adenine, and several authors have speculated that a similar pathway may exist in thymine. However, this was never confirmed theoretically or experimentally. This prediction calls for renewed efforts to experimentally identify or exclude the presence of this channel., Comment: 42 pages, 23 figures

We present the optical photometric variability of 32 planet-hosting M dwarfs within 25 parsecs over timescales of months to decades. The primary goal of this project, ATLAS -- A Trail to Life Around Stars, is to follow the trail to life by revealing nearby M dwarfs with planets that are also "quiet", which may make them more amiable to habitability. There are 69 reported exoplanets orbiting the 32 stars discussed here, providing a rich sample of worlds for which environmental evaluations are needed. We examine the optical flux environments of these planets over month-long timescales for 23 stars observed by TESS, and find that 17 vary by less than 1% ($\sim$11 mmag). All 32 stars are being observed at the CTIO/SMARTS 0.9 m, with a median duration of 19.1 years of optical photometric data in the $VRI$ bands. We find over these extended timescales that six stars show optical flux variations less than 2%, 25 vary from 2--6% ($\sim$22-67 mmag), and only one, Proxima Centauri, varies by more than 6%. Overall, LHS 1678 exhibits the lowest optical variability levels measured over all timescales examined, thereby providing one of the most stable photometric environments among planets reported around M dwarfs within 25 parsecs. More than 600 of the nearest M dwarfs are being observed at the 0.9 m in the RECONS program that began in 1999, and many more planet hosts will undoubtedly be revealed, providing more destinations to be added to the ATLAS sample in the future., Comment: Published in the Astronomical Journal. 27 pages, 12 figures, 2 tables

Simulations of photochemical reaction dynamics have been a challenge to the theoretical chemistry community for some time. In an effort to determine the predictive character of current approaches, we predict the results of an upcoming ultrafast diffraction experiment on the photodynamics of cyclobutanone after excitation to the lowest lying Rydberg state (S$_2$). A picosecond of nonadiabatic dynamics is described with ab initio multiple spawning. We use both time dependent density functional theory and equation-of-motion coupled cluster for the underlying electronic structure theory. We find that the lifetime of the S$_2$ state is more than a picosecond (with both TDDFT and EOM-CCSD). The predicted UED spectrum exhibits numerous structural features, but weak time dependence over the course of the simulations.

Repetitive DNA (repeats) poses significant challenges for accurate and efficient genome assembly and sequence alignment. This is particularly true for metagenomic data, where genome dynamics such as horizontal gene transfer, gene duplication, and gene loss/gain complicate accurate genome assembly from metagenomic communities. Detecting repeats is a crucial first step in overcoming these challenges. To address this issue, we propose GraSSRep, a novel approach that leverages the assembly graph's structure through graph neural networks (GNNs) within a self-supervised learning framework to classify DNA sequences into repetitive and non-repetitive categories. Specifically, we frame this problem as a node classification task within a metagenomic assembly graph. In a self-supervised fashion, we rely on a high-precision (but low-recall) heuristic to generate pseudo-labels for a small proportion of the nodes. We then use those pseudo-labels to train a GNN embedding and a random forest classifier to propagate the labels to the remaining nodes. In this way, GraSSRep combines sequencing features with pre-defined and learned graph features to achieve state-of-the-art performance in repeat detection. We evaluate our method using simulated and synthetic metagenomic datasets. The results on the simulated data highlight our GraSSRep's robustness to repeat attributes, demonstrating its effectiveness in handling the complexity of repeated sequences. Additionally, our experiments with synthetic metagenomic datasets reveal that incorporating the graph structure and the GNN enhances our detection performance. Finally, in comparative analyses, GraSSRep outperforms existing repeat detection tools with respect to precision and recall.

Since identifying the gap in the H-R Diagram (HRD) marking the transition between partially and fully convective interiors, a unique type of slowly pulsating M dwarf has been proposed. These unstable M dwarfs provide new laboratories in which to understand how changing interior structures can produce potentially observable activity at the surface. In this work, we report the results of the largest high-resolution spectroscopic H$\alpha$ emission survey to date spanning this transition region, including 480 M dwarfs observed using the CHIRON spectrograph at CTIO/SMARTS 1.5-m. We find that M dwarfs with H$\alpha$ in emission are almost entirely found 0 to 0.5 magnitude above the top edge of the gap in the HRD, whereas effectively no stars in and below the gap show emission. Thus, the top edge of the gap marks a relatively sharp activity transition, and there is no anomalous H$\alpha$ activity for stars in the gap. We also identify a new region at 10.3 $

Goal 1 of the National Academies of Science, Engineering and Mathematics Exoplanet Science Strategy is "to understand the formation and evolution of planetary systems as products of the process of star formation, and characterize and explain the diversity of planetary system architectures, planetary compositions, and planetary environments produced by these processes", with the finding that "Current knowledge of the demographics and characteristics of planets and their systems is substantially incomplete." One significant roadblock to our ongoing efforts to improve our demographics analyses is the lack of comprehensive meta-data accompanying published exoplanet surveys. The Exoplanet Program Analysis Group (ExoPAG) Science Interest Group 2: Exoplanet Demographics has prepared this document to provide guidance to survey architects, authors, referees and funding agencies as to the most valuable such data products for five different exoplanet detection techniques - transit, radial velocity, direct imaging, microlensing and astrometry. We find that making these additional data easily available would greatly enhance the community's ability to perform robust, reproducible demographics analyses, and make progress on achieving the most important goals identified by the exoplanet and wider astronomical community., Comment: 21 pages, final report after community feedback addressed

We present light curves and flares from a seven day, multi-wavelength observational campaign of AU Mic, a young and active dM1e star with exoplanets and a debris disk. We report on 73 unique flares between the X-ray to optical data. We use high-time resolution NUV photometry and soft X-ray (SXR) data from XMM-Newton to study the empirical Neupert effect, which correlates the gradual and impulsive phase flaring emissions. We find that 65% (30 of 46) flares do not follow the Neupert effect, which is three times more excursions than seen in solar flares, and propose a four part Neupert effect classification (Neupert, Quasi-Neupert, Non-Neupert I & II) to explain the multi-wavelength responses. While the SXR emission generally lags behind the NUV as expected from the chromospheric evaporation flare models, the Neupert effect is more prevalent in larger, more impulsive flares. Preliminary flaring rate analysis with X-ray and U-band data suggests that previously estimated energy ratios hold for a collection of flares observed over the same time period, but not necessarily for an individual, multi-wavelength flare. These results imply that one model cannot explain all stellar flares and care should be taken when extrapolating between wavelength regimes. Future work will expand wavelength coverage using radio data to constrain the nonthermal empirical and theoretical Neupert effects to better refine models and bridge the gap between stellar and solar flare physics., Comment: 46 pages, 18 figures, 15 tables. Accepted for publication in The Astrophysical Journal

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network - a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. The network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted., Comment: As accepted by JINST

Directly imaging structural dynamics involving hydrogen atoms by ultrafast diffraction methods is complicated by their low scattering cross-sections. Here we demonstrate that megaelectronvolt ultrafast electron diffraction is sufficiently sensitive to follow hydrogen dynamics in isolated molecules. In a study of the photodissociation of gas phase ammonia, we simultaneously observe signatures of the nuclear and corresponding electronic structure changes resulting from the dissociation dynamics in the time-dependent diffraction. Both assignments are confirmed by ab initio simulations of the photochemical dynamics and the resulting diffraction observable. While the temporal resolution of the experiment is insufficient to resolve the dissociation in time, our results represent an important step towards the observation of proton dynamics in real space and time.

A new search for two-neutrino double-beta ($2\nu\beta\beta$) decay of $^{136}\rm Xe$ to the $0^+_1$ excited state of $^{136}\rm Ba$ is performed with the full EXO-200 dataset. A deep learning-based convolutional neural network is used to discriminate signal from background events. Signal detection efficiency is increased relative to previous searches by EXO-200 by more than a factor of two. With the addition of the Phase II dataset taken with an upgraded detector, the median 90$\%$ confidence level half-life sensitivity of $2\nu\beta\beta$ decay to the $0^+_1$ state of $^{136}\rm Ba$ is $2.9 \times 10^{24}~\rm yr$ using a total $^{136}\rm Xe$ exposure of $234.1~\rm kg~yr$. No statistically significant evidence for $2\nu\beta\beta$ decay to the $0^+_1$ state is observed, leading to a lower limit of $T^{2\nu}_{1/2}(0^+ \rightarrow 0^+_1) > 1.4\times10^{24}~\rm yr$ at 90$\%$ confidence level, improved by 70$\%$ relative to the current world's best constraint., Comment: 9 pages, 7 figures, 2 tables

Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare diseases, which involve high costs, time, and effort for annotation. Unsupervised disease detection methods, such as anomaly detection, can significantly reduce human effort in these scenarios. While anomaly detection typically focuses on learning from images of healthy subjects only, real-world situations often present unannotated datasets with a mixture of healthy and diseased subjects. Recent studies have demonstrated that utilizing such unannotated images can improve unsupervised disease and anomaly detection. However, these methods do not utilize knowledge specific to registered neuroimages, resulting in a subpar performance in neurologic disease detection. To address this limitation, we propose Brainomaly, a GAN-based image-to-image translation method specifically designed for neurologic disease detection. Brainomaly not only offers tailored image-to-image translation suitable for neuroimages but also leverages unannotated mixed images to achieve superior neurologic disease detection. Additionally, we address the issue of model selection for inference without annotated samples by proposing a pseudo-AUC metric, further enhancing Brainomaly's detection performance. Extensive experiments and ablation studies demonstrate that Brainomaly outperforms existing state-of-the-art unsupervised disease and anomaly detection methods by significant margins in Alzheimer's disease detection using a publicly available dataset and headache detection using an institutional dataset. The code is available from https://github.com/mahfuzmohammad/Brainomaly., Comment: Accepted in WACV 2024

Migraine is a high-prevalence and disabling neurological disorder. However, information migraine management in real-world settings could be limited to traditional health information sources. In this paper, we (i) verify that there is substantial migraine-related chatter available on social media (Twitter and Reddit), self-reported by migraine sufferers; (ii) develop a platform-independent text classification system for automatically detecting self-reported migraine-related posts, and (iii) conduct analyses of the self-reported posts to assess the utility of social media for studying this problem. We manually annotated 5750 Twitter posts and 302 Reddit posts. Our system achieved an F1 score of 0.90 on Twitter and 0.93 on Reddit. Analysis of information posted by our 'migraine cohort' revealed the presence of a plethora of relevant information about migraine therapies and patient sentiments associated with them. Our study forms the foundation for conducting an in-depth analysis of migraine-related information using social media data., Comment: Accepted by AMIA 2023 Informatics Summit

The introduction of the Rossby number (R$_0$), which incorporates the convective turnover time ($\tau$), in 1984 was a pioneering idea for understanding the correlation between stellar rotation and activity. The convective turnover time, which cannot be measured directly, is often inferred using existing $\tau$-mass or $\tau$-color relations, typically established based on an ensemble of different types of stars by assuming that $\tau$ is a function of mass. In this work, we use {\it Gaia} Early Data Release 3 to demonstrate that the masses used to establish one of the most cited $\tau$-mass relations are overestimated for G type dwarfs and significantly underestimated for late M dwarfs, offsets that affect studies using this $\tau$-mass relation to draw conclusions. We discuss the challenges of creating such relations then and now. In the era of {\it Gaia} and other large datasets, stars used to establish these relations require characterization in a multi-dimensional space, rather than via the single-characteristic relations of the past. We propose that new multi-dimensional relations should be established based on updated theoretical models and all available stellar parameters for different interior structures from a set of carefully vetted single stars, so that the convective turnover time can be estimated more accurately., Comment: 8 pages, 2 figures, 1 table. One of the figures is a 3D interactive plot, which is available in the online journal or at https://www.chara.gsu.edu/~jao/3D.html

As part of a comprehensive effort to characterize the nearest stars, the CHIRON echelle spectrograph on the CTIO/SMARTS 1.5m telescope is being used to acquire high resolution (R = 80000) spectra of K dwarfs within 50 parsecs. This paper provides spectral details about 35 K dwarfs from five benchmark sets with estimated ages spanning 20 Myr -- 5.7 Gyr. Four spectral age and activity indicators are tested, three of which aligned with the estimated ages of the benchmark groups -- the Na I doublet (5889.95 $\r{A}$ and 5895.92 $\r{A}$), the H$\alpha$ line (6562.8 $\r{A}$), and the Li I resonance line (6707.8 $\r{A}$). The benchmark stars are then used to evaluate seven field K dwarfs exhibiting variable radial velocities for which initial CHIRON data did not show obvious companions. Two of these stars are estimated to be younger than 700 Myr, while one exhibits stellar activity unusual for older K dwarf field stars and is possibly young. The four remaining stars turn out to be spectroscopic binaries, two of which are being reported here for the first time with orbital periods found using CHIRON data. Spectral analysis of the combined sample of 42 benchmark and variable radial velocity stars indicates temperatures ranging from 3900--5300 K and metallicities from $-$0.4 $<$ [Fe/H] $<$ $+$0.2. We also determine $log g$ = 4.5--4.7 for main sequence K dwarfs. Ultimately, this study will target several thousand of the nearest K dwarfs, and provide results that will serve present and future studies of stellar astrophysics and exoplanet habitability., Comment: 20 pages, 11 figures, 4 tables, accepted to AJ

Electrocyclic reactions are characterized by the concerted formation and cleavage of both {\sigma} and {\pi} bonds through a cyclic structure. This structure is known as a pericyclic transition state for thermal reactions and a pericyclic minimum in the excited state for photochemical reactions. However, the structure of the pericyclic geometry has yet to be observed experimentally. We use a combination of ultrafast electron diffraction and excited state wavepacket simulations to image structural dynamics through the pericyclic minimum of a photochemical electrocyclic ring-opening reaction in the molecule {\alpha}-terpinene. The structural motion into the pericyclic minimum is dominated by rehybridization of two carbon atoms, which is required for the transformation from two to three conjugated {\pi} bonds. The {\sigma} bond dissociation largely happens after internal conversion from the pericyclic minimum to the electronic ground state. These findings may be transferrable to electrocyclic reactions in general., Comment: Combined manuscript and supplementary information