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Confronting measurements of the Lyman-$\alpha$ forest with cosmological hydrodynamical simulations has produced stringent constraints on models of particle dark matter and the thermal and ionization state of the intergalactic medium. We investigate the robustness of such models of the Lyman-$\alpha$ forest, focussing on the effect of particle initial conditions on the Lyman-$\alpha$ forest statistics in cosmological SPH simulations. We study multiple particle initialization algorithms in simulations that are designed to be identical in other respects. In agreement with the literature, we find that the correct linear theory evolution is obtained when a glass-like configuration is used for initial unperturbed gas particle positions alongside a regular grid configuration for dark matter particles and the use of non-identical initial density perturbations for gas and dark matter. However, we report that this introduces a large scale-dependent distortion in the one-dimensional Lyman-$\alpha$ transmission power spectrum at small scales ($k > 0.05$ s/km). The effect is close to $50\%$ at $k\sim 0.1$ s/km, and persists at higher resolution. This can severely bias inferences in parameters such as the dark matter particle mass. By considering multiple initial conditions codes and their variations, we also study the impact of a variety of other assumptions and algorithmic choices, such as adaptive softening, background radiation density, particle staggering, and perturbation theory accuracy, on the matter power spectrum, the Lyman-$\alpha$ flux power spectrum, and the Lyman-$\alpha$ flux PDF. This work reveals possible pathways towards more accurate theoretical models of the Lyman-$\alpha$ forest to match the quality of upcoming measurements., Comment: 18 pages, 16 figures, accepted for publication in MNRAS, comments welcome

We present multi-wavelength temporal and spectral characteristics of a magnetic cataclysmic variable (MCV) Swift J0503.7-2819, using far ultraviolet (FUV) and X-ray data from AstroSat, supplemented with optical data from the Southern African Large Telescope and X-ray data from the XMM-Newton and Swift observatories. The X-ray modulations at 4897.6657 s and 3932.0355 s are interpreted as the orbital ($P_{\Omega}$) and spin ($P_{\omega}$) period, respectively, and are consistent with prior reports. With a spin-orbit period ratio of 0.8 and $P_{\Omega}$ falling below the period gap (2-3 hrs) of CVs, Swift J0503.7-2819 would be the newest addition to the growing population of nearly synchronous MCVs, which we call EX Hya-like systems. Hard X-ray luminosity of $<$ $2.5\times10^{32} erg s^{-1}$, as measured with the Swift Burst Alert Telescope, identifies it to be a low-luminosity intermediate polar, similar to other EX Hya-like systems. The phenomenology of the light curves and the spectral characteristics rule out a purely disc-fed/stream-fed model and instead reveal the presence of complex accretion structures around the white dwarf. We propose a ring-like accretion flow, akin to EX Hya, using period ratio, stability arguments, and observational features. An attempt is made to differentiate between the asynchronous polar/nearly-synchronous intermediate polar nature of Swift J0503.7-2819. Further, we note that with the advent of sensitive surveys, a growing population of MCVs that exhibit characteristics of both polars and intermediate polars is beginning to be identified, likely forming a genealogical link between the two conventional classes of MCVs., Comment: Accepted for publication in MNRAS, 17 Pages, 13 Figures

Quantum estimation of parameters defining open-system dynamics may be enhanced by using ancillas that are entangled with the probe but are not submitted to the dynamics. Here we consider the important problem of estimation of transmission of light by a sample, with losses due to absorption and scattering. We show, through the determination of the quantum Fisher information, that the ancilla strategy leads to the best possible precision in single-mode estimation, the one obtained for a Fock state input, through joint photon-counting of probe and ancilla, which are modes of a bimodal squeezed state produced by an optical parametric amplifier. This proposal overcomes the challenge of producing and detecting high photon-number Fock states, and it is quite robust against additional noise: we show that it is immune to phase noise and the precision does not change if the incoming state gets disentangled. Furthermore, the quantum gain is still present under moderate photon losses of the input beams. We also discuss an alternative to joint photon counting, which is readily implementable with present technology, and approaches the quantum Fisher information result for weak absorption, even with moderate photons losses of the input beams before the sample is probed: a time-reversal procedure, placing the sample between two optical parametric amplifiers, with the second undoing the squeezing produced by the first one. The precision of estimation of the loss parameter is obtained from the average outgoing total photon number and its variance. In both procedures, the state of the probe and the detection procedure are independent of the value of the parameter., Comment: 14 pages, 7 figures

We study the one-clean-qubit model of quantum communication where one qubit is in a pure state and all other qubits are maximally mixed. We demonstrate a partial function that has a quantum protocol of cost $O(\log N)$ in this model, however, every interactive randomized protocol has cost $\Omega(\sqrt{N})$, settling a conjecture of Klauck and Lim. In contrast, all prior quantum versus classical communication separations required at least $\Omega(\log N)$ clean qubits. The function demonstrating our separation also has an efficient protocol in the quantum-simultaneous-with-entanglement model of cost $O(\log N )$. We thus recover the state-of-the-art separations between quantum and classical communication complexity. Our proof is based on a recent hypercontractivity inequality introduced by Ellis, Kindler, Lifshitz, and Minzer, in conjunction with tools from the representation theory of compact Lie groups.

V1298 Tau is a young pre-main sequence star hosting four known exoplanets that are prime targets for transmission spectroscopy with current-generation instruments. This work pieces together observations from the NICER X-ray telescope, the Space Telescope Imaging Spectrograph and Cosmic Origins Spectrograph instruments aboard Hubble Space Telescope, and empirically informed models to create a panchromatic spectral energy distribution for V1298 Tau spanning 1 to 100000 Angstroms. We describe the methods and assumptions used to assemble the panchromatic spectrum and show that despite this star's brightness, its high-energy spectrum is near the limit of present X-ray and ultraviolet observatories' abilities to characterize. We conclude by using the V1298 Tau spectrum as a benchmark for the activity saturation stage of high-energy radiation from solar-mass stars to compare the lifetime cumulative high-energy irradiation of the V1298 Tau planets to other planets orbiting similarly massive stars., Comment: The V1298 Tau panchromatic SED will be available via the Data Behind the Figure feature for Figure 1 of the final journal article, will be uploaded to the Exoplanet Archive as an IPAC table, and can be provided upon request

Implicit Neural Representations (INR) or neural fields have emerged as a popular framework to encode multimedia signals such as images and radiance fields while retaining high-quality. Recently, learnable feature grids proposed by Instant-NGP have allowed significant speed-up in the training as well as the sampling of INRs by replacing a large neural network with a multi-resolution look-up table of feature vectors and a much smaller neural network. However, these feature grids come at the expense of large memory consumption which can be a bottleneck for storage and streaming applications. In this work, we propose SHACIRA, a simple yet effective task-agnostic framework for compressing such feature grids with no additional post-hoc pruning/quantization stages. We reparameterize feature grids with quantized latent weights and apply entropy regularization in the latent space to achieve high levels of compression across various domains. Quantitative and qualitative results on diverse datasets consisting of images, videos, and radiance fields, show that our approach outperforms existing INR approaches without the need for any large datasets or domain-specific heuristics. Our project page is available at http://shacira.github.io .

Multivariate time series (MTS) forecasting involves predicting future time series data based on historical observations. Existing research primarily emphasizes the development of complex spatial-temporal models that capture spatial dependencies and temporal correlations among time series variables explicitly. However, recent advances have been impeded by challenges relating to data scarcity and model robustness. To address these issues, we propose Spatial-Temporal Masked Autoencoders (STMAE), an MTS forecasting framework that leverages masked autoencoders to enhance the performance of spatial-temporal baseline models. STMAE consists of two learning stages. In the pretraining stage, an encoder-decoder architecture is employed. The encoder processes the partially visible MTS data produced by a novel dual-masking strategy, including biased random walk-based spatial masking and patch-based temporal masking. Subsequently, the decoders aim to reconstruct the masked counterparts from both spatial and temporal perspectives. The pretraining stage establishes a challenging pretext task, compelling the encoder to learn robust spatial-temporal patterns. In the fine-tuning stage, the pretrained encoder is retained, and the original decoder from existing spatial-temporal models is appended for forecasting. Extensive experiments are conducted on multiple MTS benchmarks. The promising results demonstrate that integrating STMAE into various spatial-temporal models can largely enhance their MTS forecasting capability.

Non-Hermitian topological phenomena have gained much interest among physicists in recent years. In this paper, we expound on the physics of dissipatively coupled Su-Schrieffer-Heeger (SSH) lattices, specifically in systems with bosonic and electrical constituents. In the context of electrical circuits, we demonstrate that a series of resistively coupled LCR circuits mimics the topology of a dissipatively coupled SSH model. In addition, we foreground a scheme to construct dissipatively coupled SSH lattices involving a set of non-interacting bosonic oscillators weakly coupled to engineered reservoirs of modes possessing substantially small lifetimes when compared to other system timescales. Further, by activating the coherent coupling between bosonic oscillators, we elucidate the emergence of non-reciprocal dissipative coupling which can be controlled by the phase of the coherent interaction strength precipitating in phase-dependent topological transitions and skin effect. Our analyses are generic, apropos of a large class of systems involving, for instance, optical and microwave settings, while the circuit implementation represents the most straightforward of them., Comment: 10 pages, 9 figures

This study introduces novel constraints on the free-streaming of thermal relic warm dark matter (WDM) from Lyman-$\alpha$ forest flux power spectra. Our analysis utilises a high-resolution, high-redshift sample of quasar spectra observed using the HIRES and UVES spectrographs ($z=4.2-5.0$). We employ a Bayesian inference framework and a simulation-based likelihood that encompasses various parameters including the free-streaming of dark matter, cosmological parameters, the thermal history of the intergalactic medium, and inhomogeneous reionization, to establish lower limits on the mass of a thermal relic WDM particle of $5.7\;\mathrm{keV}$ (at 95\% C.L.). This result surpasses previous limits from the Lyman-$\alpha$ forest through reduction of the measured uncertainties due to a larger statistical sample and by measuring clustering to smaller scales ($k_{\rm max}=0.2\;\mathrm{km^{-1}\,s}$). The approximately two-fold improvement due to the expanded statistical sample suggests that the effectiveness of Lyman-$\alpha$ forest constraints on WDM models at high redshifts are limited by the availability of high-quality quasar spectra. Restricting the analysis to comparable scales and thermal history priors as in prior studies ($k_{\rm max}<0.1\;\mathrm{km^{-1}\,s}$) lowers the bound on the WDM mass to $4.1\;\mathrm{keV}$. As the precision of the measurements increases, it becomes crucial to examine the instrumental and modelling systematics. On the modelling front, we argue that the impact of the thermal history uncertainty on the WDM particle mass constraint has diminished due to improved independent observations. At the smallest scales, the primary source of modeling systematic arises from the structure in the peculiar velocity of the intergalactic medium and inhomogeneous reionization., Comment: 22 pages, 14 figures, 2 tables; published in PRD on Feb 8 2024

Recently, the Lyman-$\alpha$ (Ly$\alpha$) forest flux auto-correlation function has been shown to be sensitive to the mean free path of hydrogen-ionizing photons, $\lambda_{\text{mfp}}$, for simulations at $z \geq 5.4$. Measuring $\lambda_{\text{mfp}}$ at these redshifts will give vital information on the ending of reionization. Here we present the first observational measurements of the Ly$\alpha$ forest flux auto-correlation functions in ten redshift bins from $5.1 \leq z \leq 6.0$. We use a sample of 35 quasar sightlines at $z > 5.7$ from the extended XQR-30 data set, this data has signal-to-noise ratios of $> 20$ per spectral pixel. We carefully account for systematic errors in continuum reconstruction, instrumentation, and contamination by damped Ly$\alpha$ systems. With these measurements, we introduce software tools to generate auto-correlation function measurements from any simulation. For an initial comparison, we show our auto-correlation measurements with simulation models for recently measured $\lambda_{\text{mfp}}$ values and find good agreements. Further work in modeling and understanding the covariance matrices of the data is necessary to get robust measurements of $\lambda_{\text{mfp}}$ from this data., Comment: 17 pages, 13 figures, submitted to MNRAS

Diagnostic investigation has an important role in risk stratification and clinical decision making of patients with suspected and documented Coronary Artery Disease (CAD). However, the majority of existing tools are primarily focused on the selection of gatekeeper tests, whereas only a handful of systems contain information regarding the downstream testing or treatment. We propose a multi-task deep learning model to support risk stratification and down-stream test selection for patients undergoing Coronary Computed Tomography Angiography (CCTA). The analysis included 14,021 patients who underwent CCTA between 2006 and 2017. Our novel multitask deep learning framework extends the state-of-the art Perceiver model to deal with real-world CCTA report data. Our model achieved an Area Under the receiver operating characteristic Curve (AUC) of 0.76 in CAD risk stratification, and 0.72 AUC in predicting downstream tests. Our proposed deep learning model can accurately estimate the likelihood of CAD and provide recommended downstream tests based on prior CCTA data. In clinical practice, the utilization of such an approach could bring a paradigm shift in risk stratification and downstream management. Despite significant progress using deep learning models for tabular data, they do not outperform gradient boosting decision trees, and further research is required in this area. However, neural networks appear to benefit more readily from multi-task learning than tree-based models. This could offset the shortcomings of using single task learning approach when working with tabular data.

Ly$\alpha$ damping wings in the spectra of bright objects at high redshift are a useful probe of the ionization state of the intergalactic medium during the reionization epoch. It has recently been noted that, despite the inhomogeneous nature of reionization, these damping wings have a characteristic shape which is a strong function of the volume-weighted average neutral hydrogen fraction of the intergalactic medium. We present here a closer examination of this finding using a simulation of patchy reionization from the Sherwood-Relics simulation suite. We show that the characteristic shape and scatter of the damping wings are determined by the average neutral hydrogen density along the line of sight, weighted by its contribution to the optical depth producing the damping wing. We find that there is a redshift dependence in the characteristic shape due to the expansion of the Universe. Finally, we show that it is possible to differentiate between the shapes of damping wings in galaxies and young (or faint) quasars at different points in the reionization history at large velocity offsets from the point where the transmission first reaches zero., Comment: 5 pages, 4 figures. Submitted to MNRAS Letters

Spatial variations in the Lyman-$\alpha$ forest opacity at $z<6$ seem to require a late end to cosmic reionization. In this picture, the universe contains neutral hydrogen 'islands' of up to 100 cMpc$/h$ in extent down to redshifts as low as $z\sim 5.3$. This delayed end to reionization also seems to be corroborated by various other observables. An implication of this scenario is that the power spectrum of the cosmological 21-cm signal at $z<6$ is enhanced relative to conventional reionization models by orders of magnitude. However, these neutral hydrogen islands are also predicted to be at the locations of the deepest voids in the cosmological large-scale structure. As a result, the distribution of the 21-cm signal from them is highly non-Gaussian. We derive the 21-cm bispectrum signal from these regions using high-dynamic-range radiative transfer simulations of reionization. We find that relative to conventional models in which reionization is complete at $z>6$, our model has a significantly larger value of the 21-cm bispectrum. The neutral islands also imprint a feature in the isosceles bispectrum at a characteristic scale of $\sim 1$ cMpc$^{-1}$. We also study the 21-cm bispectrum for general triangle configuration by defining a triangle index. It should be possible to detect the 21-cm bispectrum signal at $\nu\gtrsim 200$ MHz using SKA1-LOW for 1080 hours of observation, assuming optimistic foreground removal., Comment: 12 pages, 12 figures

Eosinophilic esophagitis (EoE) is a chronic and relapsing disease characterized by esophageal inflammation. Symptoms of EoE include difficulty swallowing, food impaction, and chest pain which significantly impact the quality of life, resulting in nutritional impairments, social limitations, and psychological distress. The diagnosis of EoE is typically performed with a threshold (15 to 20) of eosinophils (Eos) per high-power field (HPF). Since the current counting process of Eos is a resource-intensive process for human pathologists, automatic methods are desired. Circle representation has been shown as a more precise, yet less complicated, representation for automatic instance cell segmentation such as CircleSnake approach. However, the CircleSnake was designed as a single-label model, which is not able to deal with multi-label scenarios. In this paper, we propose the multi-label CircleSnake model for instance segmentation on Eos. It extends the original CircleSnake model from a single-label design to a multi-label model, allowing segmentation of multiple object types. Experimental results illustrate the CircleSnake model's superiority over the traditional Mask R-CNN model and DeepSnake model in terms of average precision (AP) in identifying and segmenting eosinophils, thereby enabling enhanced characterization of EoE. This automated approach holds promise for streamlining the assessment process and improving diagnostic accuracy in EoE analysis. The source code has been made publicly available at https://github.com/yilinliu610730/EoE.

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI.

Eosinophilic Esophagitis (EoE) is a chronic, immune/antigen-mediated esophageal disease, characterized by symptoms related to esophageal dysfunction and histological evidence of eosinophil-dominant inflammation. Owing to the intricate microscopic representation of EoE in imaging, current methodologies which depend on manual identification are not only labor-intensive but also prone to inaccuracies. In this study, we develop an open-source toolkit, named Open-EoE, to perform end-to-end whole slide image (WSI) level eosinophil (Eos) detection using one line of command via Docker. Specifically, the toolkit supports three state-of-the-art deep learning-based object detection models. Furthermore, Open-EoE further optimizes the performance by implementing an ensemble learning strategy, and enhancing the precision and reliability of our results. The experimental results demonstrated that the Open-EoE toolkit can efficiently detect Eos on a testing set with 289 WSIs. At the widely accepted threshold of >= 15 Eos per high power field (HPF) for diagnosing EoE, the Open-EoE achieved an accuracy of 91%, showing decent consistency with pathologist evaluations. This suggests a promising avenue for integrating machine learning methodologies into the diagnostic process for EoE. The docker and source code has been made publicly available at https://github.com/hrlblab/Open-EoE.

Spectra of the highest redshift galaxies taken with JWST are now allowing us to see into the heart of the reionization epoch. Many of these observed galaxies exhibit strong damping wing absorption redward of their Lyman-$\alpha$ emission. These observations have been used to measure the redshift evolution of the neutral fraction of the intergalactic medium and sizes of ionized bubbles. However, these estimates have been made using a simple analytic model for the intergalactic damping wing. We explore the recent observations with models of inhomogeneous reionization from the Sherwood-Relics simulation suite. We carry out a comparison between the damping wings calculated from the simulations and from the analytic model. We find that although the agreement is good on the red side of the Lyman-$\alpha$ emission, there is a discrepancy on the blue side due to residual neutral hydrogen present in the simulations, which saturates the intergalactic absorption. For this reason, we find that it is difficult to reproduce the claimed observations of large bubble sizes at z ~ 7, which are driven by a detection of transmitted flux blueward of the Lyman-$\alpha$ emission. We suggest instead that the observations can be explained by a model with smaller ionized bubbles and larger intrinsic Lyman-$\alpha$ emission from the host galaxy., Comment: 13 pages, 7 figures. Submitted to MNRAS

Baryon asymmetry of the Universe offers one of the strongest hints for physics Beyond the Standard Model (BSM). Remarkably, in the general two Higgs Doublet Model (g2HDM) that possesses a second set of Yukawa matrices, one can have electroweak baryogenesis (EWBG) while the electron electric dipole moment (eEDM) is evaded by a natural flavor tuning that echoes SM. We show that eEDM may first emerge around $10^{-30}\,e$ cm or so, followed by neutron EDM (nEDM) down to $10^{-27}\,e$ cm. We illustrate a cancellation mechanism for nEDM itself, which in turn can be probed when a facility capable of pushing down to $10^{-28}\,e$ cm becomes available., Comment: 4 pages, 4 labeled figures

The mean free path of ionizing photons, $\lambda_{\rm mfp}$, is a critical parameter for modeling the intergalactic medium (IGM) both during and after reionization. We present direct measurements of $\lambda_{\rm mfp}$ from QSO spectra over the redshift range $5

We study a two-player game on a graph between an attacker and a defender. To begin with, the defender places guards on a subset of vertices. In each move, the attacker attacks an edge. The defender must move at least one guard across the attacked edge to defend the attack. The defender wins if and only if the defender can defend an infinite sequence of attacks. The smallest number of guards with which the defender has a winning strategy is called the eternal vertex cover number of a graph $G$ and is denoted by $evc(G)$. It is clear that $evc(G)$ is at least $mvc(G)$, the size of a minimum vertex cover of $G$. We say that $G$ is Spartan if $evc(G) = mvc(G)$. The characterization of Spartan graphs has been largely open. In the setting of bipartite graphs on $2n$ vertices where every edge belongs to a perfect matching, an easy strategy is to have $n$ guards that always move along perfect matchings in response to attacks. We show that these are essentially the only Spartan bipartite graphs., Comment: 21 pages, 12 figures. A preliminary version accepted for presentation at MFCS 2023