Search

The 21-cm forest signal is a promising probe of the Epoch of Reionization complementary to other 21-cm line observables and Ly$\alpha$ forest signal. Prospects of detecting it have significantly improved in the last decade thanks to the discovery of more than 30 radio-loud quasars at these redshifts, upgrades to telescope facilities, and the notion that neutral hydrogen islands persist down to $z\lesssim 5.5$. We forward-model the 21-cm forest signal using semi-numerical simulations and incorporate various instrumental features to explore the potential of detecting the 21-cm forest at $z=6$, both directly and statistically, with the currently available (uGMRT) and forthcoming (SKA1-low) observatories. We show that it is possible to detect the 1D power spectrum of the 21-cm forest spectrum, especially at large scales of $k\lesssim8.5\,\rm MHz^{-1}$ with the $500\,\rm hr$ of the uGMRT time and $k\lesssim32.4\,\rm MHz^{-1}$ with the SKA1-low over $50\,\rm hr$ if the intergalactic medium (IGM) is $25\%$ neutral and these neutral hydrogen regions have a spin temperature of $\lesssim30\,\rm K$. On the other hand, we infer that a null-detection of the signal with such observations of 10 radio-loud sources at $z\approx6$ can be translated into constraints on the thermal and ionization state of the IGM which are tighter than the currently available measurements. Moreover, a null-detection of the 1D 21-cm forest power spectrum with only $50\,\rm hr$ of the uGMRT observations of 10 radio-loud sources can already be competitive with the Ly$\alpha$ forest and 21-cm tomographic observations in disfavouring models of significantly neutral and cold IGM at $z=6$., Comment: 14 pages, 15 figures. Submitted to MNRAS. Version after addessing referee's first comments. Comments welcome

Recent JWST observations have allowed for the first time to obtain comprehensive measurements of the ionizing photon production efficiency $\xi_\text{ion} $ for a wide range of reionization-epoch galaxies. We explore implications for the inferred UV luminosity functions and escape fractions of ionizing sources in our suite of simulations. These are run with the GPU-based radiative transfer code ATON-HE and are calibrated to the XQR-30 Lyman-alpha forest data at $550$% at $z> 10$, disfavouring the oligarchic source model at very high redshift. The inferred effective clumping factors in our simulations are in the range of $3-6$, suggesting consistency between the observed ionizing properties of reionization-epoch galaxies and the ionizing photon budget in our simulations., Comment: 6 pages. 3 figures

JWST has revealed a population of compact `Little Red Dots' (LRDs) at $z\gtrsim4$, with red rest-frame optical and blue UV colors. These objects are likely compact dusty starbursts or heavily reddened AGNs, playing a pivotal role in early black hole growth, dust production, and stellar assembly. We introduce a new photometric selection to identify LRDs over a broad range in redshifts and rest-frame UV-to-NIR colors enabling a more complete census of the population. This method identifies 248 LRDs with F444W$<27$ mag over 263 arcmin$^2$ in the JADES, PRIMER-COSMOS, and UDS fields with MIRI coverage, increasing the number density by $\times$1.7 compared to previous samples, suggesting that previous census were underestimated. Most LRDs are detected in MIRI/F770W but only 7% (17) are detected in F1800W. We use MIRI-based rest-frame [1$-$3 $\mu$m] colors to trace dust emission. F1800W-detected LRDs have a median [1$-$3 $\mu$m]$=1.5$ mag, with a broad scatter indicative of diverse dust emission properties. About 20% exhibit [1$-$3 $\mu$m]$<1$ mag colors consistent with negligible dust emission, but the majority show significant dust emission at 3 $\mu$m (f$^{\rm dust}_{3\mu m}\lesssim0.8$) from the galaxy ISM or a hot-dust-deficient AGN torus. A correlation between bluer UV-to-NIR colors and stronger IR emission suggests that the bluest LRDs may resemble unobscured QSOs. We report a LRD at $z_{\rm spec}=3.1386$, detected in MIRI, Spitzer/MIPS, and Herschel/PACS. Its IR SED rises steeply at $\lambda_{\rm rest}>6~\mu$m and peaks near $\sim40~\mu$m, providing the first direct evidence of warm dust emission (T$=50-100$ K) in a LRD., Comment: The new photometric selection is shown in Figure 1. The mid-IR detected LRD is in Figure 11

Several hypothesis testing methods have been proposed to validate the assumption of isotropy in spatial point patterns. A majority of these methods are characterised by an unknown distribution of the test statistic under the null hypothesis of isotropy. Parametric approaches to approximating the distribution involve simulation of patterns from a user-specified isotropic model. Alternatively, nonparametric replicates of the test statistic under isotropy can be used to waive the need for specifying a model. In this paper, we first develop a general framework which allows for the integration of a selected nonparametric replication method into isotropy testing. We then conduct a large simulation study comprising application-like scenarios to assess the performance of tests with different parametric and nonparametric replication methods. In particular, we explore distortions in test size and power caused by model misspecification, and demonstrate the advantages of nonparametric replication in such scenarios., Comment: 20 pages, 9 figures, 3 tables

JWST has revealed a large population of compact, red galaxies at $z>4$ known as Little Red Dots (LRDs). We analyze the spectral energy distributions (SEDs) of 95 LRDs from the JWST PRIMER survey with complete photometric coverage from $1-18\ \mu$m using NIRCam and MIRI imaging, representing the most extensive SED analysis on a large LRD sample with long-wavelength MIRI data. We examine SED models in which either galaxy or active galactic nucleus (AGN) emission dominates the rest-frame UV or optical continuum, extracting physical properties to explore each scenario's implications. In the galaxy-only model, we find massive, dusty stellar populations alongside unobscured, low-mass components, hinting at inhomogeneous obscuration. The AGN-only model indicates dusty, luminous AGNs with low hot dust fractions compared to typical quasars. A hybrid AGN and galaxy model suggests low-mass, unobscured galaxies in the UV, with stellar mass estimates spanning $\sim$2 dex across the different models, underscoring the need for caution in interpreting LRD stellar masses. With MIRI photometry, the galaxy-only model produces stellar masses within cosmological limits, but extremely high stellar mass densities are inferred. The hybrid model infers highly overmassive black holes exceeding those in recently reported high-redshift AGNs, hinting at a partial AGN contribution to the rest-optical continuum or widespread super-Eddington accretion. Our findings highlight the extreme conditions required for both AGN or galaxy dominated scenarios in LRDs, supporting a mixed contribution to the red continuum, or novel scenarios to explain the observed emission., Comment: 22 pages, 10 figures, submitted to ApJ. Machine-readable form of Table 2 available at: https://github.com/geneckleung/lrd_primer_miri

In the last few decades planet search surveys have been focusing on solar type stars, and only recently the high-mass regimes. This is mostly due to challenges arising from the lack of instrumental precision, and more importantly, the inherent active nature of fast rotating massive stars. Here we report NGTS-33b (TOI-6442b), a super-Jupiter planet with mass, radius and orbital period of 3.6 $\pm$ 0.3 M$_{\rm jup}$, 1.64 $\pm$ 0.07 R$_{\rm jup}$ and $2.827972 \pm 0.000001$ days, respectively. The host is a fast rotating ($0.6654 \pm 0.0006$ day) and hot (T$_{\rm eff}$ = 7437 $\pm$ 72 K) A9V type star, with a mass and radius of 1.60 $\pm$ 0.11 M$_{\odot}$ and 1.47 $\pm$ 0.06 R$_{\odot}$, respectively. Planet structure and Gyrochronology models shows that NGTS-33 is also very young with age limits of 10-50 Myr. In addition, membership analysis points towards the star being part of the Vela OB2 association, which has an age of $\sim$ 20-35 Myr, thus providing further evidences about the young nature of NGTS-33. Its low bulk density of 0.19$\pm$0.03 g cm$^{-3}$ is 13$\%$ smaller than expected when compared to transiting hot Jupiters with similar masses. Such cannot be solely explained by its age, where an up to 15$\%$ inflated atmosphere is expected from planet structure models. Finally, we found that its emission spectroscopy metric is similar to JWST community targets, making the planet an interesting target for atmospheric follow-up. Therefore, NGTS-33b's discovery will not only add to the scarce population of young, massive and hot Jupiters, but will also help place further strong constraints on current formation and evolution models for such planetary systems., Comment: 19 pages, 17 figures, 7 tables, accepted for publication in MNRAS

Portfolio optimization is a ubiquitous problem in financial mathematics that relies on accurate estimates of covariance matrices for asset returns. However, estimates of pairwise covariance could be better and calculating time-sensitive optimal portfolios is energy-intensive for digital computers. We present an energy-efficient, fast, and fully analog pipeline for solving portfolio optimization problems that overcomes these limitations. The analog paradigm leverages the fundamental principles of physics to recover accurate optimal portfolios in a two-step process. Firstly, we utilize equilibrium propagation, an analog alternative to backpropagation, to train linear autoencoder neural networks to calculate low-rank covariance matrices. Then, analog continuous Hopfield networks output the minimum variance portfolio for a given desired expected return. The entire efficient frontier may then be recovered, and an optimal portfolio selected based on risk appetite., Comment: 7 pages, 4 figures, accepted to NeurlPS 2024

This paper presents the Complex Vector Gain-Based Annealer (CoVeGA), an analog computing platform designed to overcome energy barriers in XY Hamiltonians through a higher-dimensional representation. Traditional gain-based solvers utilizing optical or photonic hardware typically represent each XY spin with a single complex field. These solvers often struggle with large energy barriers in complex landscapes, leading to relaxation into excited states. CoVeGA addresses these limitations by employing two complex fields to represent each XY spin and dynamically evolving the energy landscape through time-dependent annealing. Operating in a higher-dimensional space, CoVeGA bridges energy barriers in this expanded space during the continuous phase evolution, thus avoiding entrapment in local minima. We introduce several graph structures that pose challenges for XY minimization and use them to benchmark CoVeGA against single-dimension XY solvers, highlighting the benefits of higher-dimensional operation., Comment: 10 pages, 8 figures

Magnetic Resonance Spectroscopic Imaging (MRSI) is a non-invasive imaging technique for studying metabolism and has become a crucial tool for understanding neurological diseases, cancers and diabetes. High spatial resolution MRSI is needed to characterize lesions, but in practice MRSI is acquired at low resolution due to time and sensitivity restrictions caused by the low metabolite concentrations. Therefore, there is an imperative need for a post-processing approach to generate high-resolution MRSI from low-resolution data that can be acquired fast and with high sensitivity. Deep learning-based super-resolution methods provided promising results for improving the spatial resolution of MRSI, but they still have limited capability to generate accurate and high-quality images. Recently, diffusion models have demonstrated superior learning capability than other generative models in various tasks, but sampling from diffusion models requires iterating through a large number of diffusion steps, which is time-consuming. This work introduces a Flow-based Truncated Denoising Diffusion Model (FTDDM) for super-resolution MRSI, which shortens the diffusion process by truncating the diffusion chain, and the truncated steps are estimated using a normalizing flow-based network. The network is conditioned on upscaling factors to enable multi-scale super-resolution. To train and evaluate the deep learning models, we developed a 1H-MRSI dataset acquired from 25 high-grade glioma patients. We demonstrate that FTDDM outperforms existing generative models while speeding up the sampling process by over 9-fold compared to the baseline diffusion model. Neuroradiologists' evaluations confirmed the clinical advantages of our method, which also supports uncertainty estimation and sharpness adjustment, extending its potential clinical applications., Comment: Accepted by Medical Image Analysis (MedIA)

Intels efforts to build a practical quantum computer are focused on developing a scalable spin-qubit platform leveraging industrial high-volume semiconductor manufacturing expertise and 300 mm fabrication infrastructure. Here, we provide an overview of the design, fabrication, and demonstration of a new customized quantum test chip, which contains 12-quantum-dot spin-qubit linear arrays, code named Tunnel Falls. These devices are fabricated using immersion and extreme ultraviolet lithography (EUV), along with other standard high-volume manufacturing (HVM) processes, as well as production-level process control. We present key device features and fabrication details, as well as qubit characterization results confirming device functionality. These results corroborate our fabrication methods and are a crucial step towards scaling of extensible 2D qubit array schemes.

We study the hemispheric to continental scale regimes that lead to summertime heatwaves in the Northern Hemisphere. By using a powerful data mining methodology - archetype analysis - we identify characteristic spatial patterns consisting of a blocking high pressure systems embedded within a meandering upper atmosphere circulation that is longitudinally modulated by coherent Rossby Wave Packets. Periods when these atmospheric regimes are strongly expressed correspond to large increases in the likelihood of extreme surface temperature. Most strikingly, these regimes are shown to be typical of surface extremes and frequently reoccur. Three well publicised heatwaves are studied in detail - the June-July 2003 western European heatwave, the August 2010 "Russian" heatwave, and the June 2021 "Heatdome" event across western North America, and are shown to be driven by blocking high pressure systems linked to stalled Rossby Wave Packets. We discuss the implications of our work for long-range prediction or early warning, climate model assessment and post-event diagnosis., Comment: 12 figure

Ising machines are an emerging class of hardware that promises ultrafast and energy-efficient solutions to NP-hard combinatorial optimization problems. Spatial photonic Ising machines (SPIMs) exploit optical computing in free space to accelerate the computation, showcasing parallelism, scalability, and low power consumption. However, current SPIMs can implement only a restricted class of problems. This partial programmability is a critical limitation that hampers their benchmark. Achieving full programmability of the device while preserving its scalability is an open challenge. Here, we report a fully programmable SPIM achieved through a novel operation method based on the division of the focal plane. In our scheme, a general Ising problem is decomposed into a set of Mattis Hamiltonians, whose energies are simultaneously computed optically by measuring the intensity on different regions of the camera sensor. Exploiting this concept, we experimentally demonstrate the computation with high success probability of ground-state solutions of up to 32-spin Ising models on unweighted maximum cut graphs with and without ferromagnetic bias. Simulations of the hardware prove a favorable scaling of the accuracy with the number of spins. Our fully programmable SPIM enables the implementation of many quadratic unconstrained binary optimization problems, further establishing SPIMs as a leading paradigm in non von Neumann hardware.

Traditional requirements engineering tools do not readily access the SysML-defined system architecture model, often resulting in ad-hoc duplication of model elements that lacks the connectivity and expressive detail possible in a SysML-defined model. Further integration of requirements engineering activities with MBSE contributes to the Authoritative Source of Truth while facilitating deep access to system architecture model elements for V&V activities. We explore the application of MBSE to requirements engineering by extending the Model-Based Structured Requirement SysML Profile to comply with the INCOSE Guide to Writing Requirements while conforming to the ISO/IEC/IEEE 29148 standard requirement statement patterns. Rules, Characteristics, and Attributes were defined in SysML according to the Guide to facilitate requirements definition, verification & validation. The resulting SysML Profile was applied in two system architecture models at NASA Jet Propulsion Laboratory, allowing us to assess its applicability and value in real-world project environments. Initial results indicate that INCOSE-derived Model-Based Structured Requirements may rapidly improve requirement expression quality while complementing the NASA Systems Engineering Handbook checklist and guidance, but typical requirement management activities still have challenges related to automation and support in the system architecture modeling software., Comment: 19 pages; 9 figures; 3 tables; journal preprint

The ultralight dark photon is a well-motivated, hypothetical dark matter candidate. In a dilute plasma, they can resonantly convert into photons, and heat up the intergalactic medium between galaxies. In this work, we explore the dark photon dark matter parameter space by comparing synthetic Lyman-$\alpha$ forest data from cosmological hydrodynamical simulations to observational data from VLT/UVES of the quasar HE0940-1050 ($z_{\rm em}=3.09$). We use a novel flux normalization technique that targets under-dense gas, reshaping the flux probability distribution. Not only do we place robust constraints on the kinetic mixing parameter of dark photon dark matter, but notably our findings suggest that this model can still reconcile simulated and observed Doppler parameter distributions of $z\sim0$ Lyman-$\alpha$ lines, as seen by HST/COS. This work opens new pathways for the use of the Lyman-$\alpha$ forest to explore new physics, and can be extended to other scenarios such as primordial black hole evaporation, dark matter decay, and annihilation., Comment: 14 pages, 7 figures, 1 table

We present the properties of a massive, large, dusty, metal-rich, star-forming galaxy at z_spec=6.73. GOODSN-100182 was observed with JWST/NIRSpec as part of the AURORA survey, and is also covered by public multi-wavelength HST and JWST imaging. While the large mass of GOODSN-100182 (~10^10 M_sun) was indicated prior to JWST, NIRCam rest-optical imaging now reveals the presence of an extended disk (r_eff~1.5 kpc). In addition, the NIRSpec R~1000 spectrum of GOODSN-100182 includes the detection of a large suite of rest-optical nebular emission lines ranging in wavelength from [OII]3727 up to [NII]6583. The ratios of Balmer lines suggest significant dust attenuation (E(B-V)_gas=0.40+0.10/-0.09), consistent with the red rest-UV slope inferred for GOODSN-100182 (beta=-0.50+/-0.09). The star-formation rate based on dust-corrected H-alpha emission is log(SFR(H-alpha)/ M_sun/yr)=2.02+0.13/-0.14, well above the z~7 star-forming main sequence in terms of specific SFR. Strikingly, the ratio of [NII]6583/H-alpha emission suggests almost solar metallicity, as does the ratio ([OIII]5007/H-beta)/([NII]6583/H-alpha) and the detection of the faint [FeII]4360 emission feature, whereas the [OIII]5007/[OII]3727 ratio suggests roughly 50% solar metallicity. Overall, the excitation and ionization properties of GOODSN-100182 more closely resemble those of typical star-forming galaxies at z~2-3 rather than z~7. Based on public spectroscopy of the GOODS-N field, we find that GOODSN-100182 resides within a significant galaxy overdensity, and is accompanied by a spectroscopically-confirmed neighbor galaxy. GOODSN-100182 demonstrates the existence of mature, chemically-enriched galaxies within the first billion years of cosmic time, whose properties must be explained by galaxy formation models., Comment: 16 pages, 13 figures, submitted to ApJ

The relative contribution of emission from stellar sources and accretion onto supermassive black holes to reionization has been brought into focus again by the apparent high abundance of faint AGN at $4\lesssim z\lesssim11$ uncovered by JWST. We investigate the contribution of these faint AGN to hydrogen and the early stages of helium reionization using the GPU-based radiative transfer code ATON-HE by post-processing a cosmological hydrodynamical simulation from the SHERWOOD-RELICS suite of simulations. We study four models of reionization: two previously studied galaxy-only late-end reionization models and two new models -- a QSO-assisted model and a QSO-only model. In the QSO-assisted model, 1\% of the haloes host AGN with a 10~Myr lifetime, and the AGN luminosities are scaled such that the AGN contribution to the hydrogen-ionizing emissivity is 20\% of that contributed by galaxies. In the QSO-only model, quasars account for all the hydrogen-ionizing emissivity, with 10\% of the haloes hosting AGN, each with a 10 Myr lifetime. All models are calibrated to the observed mean Lyman-$\alpha$ forest transmission at $5\lesssim z\lesssim6.2$. We find that the QSO-assisted model requires an emissivity factor of $1.8$ lower than the galaxy-only models towards the end of reionization and fits the observed distribution of the Lyman-$\alpha$ optical depths well. Our QSO-only model is inconsistent with the observed Lyman-$\alpha$ optical depths distribution. It also results in too high IGM temperatures at $z\lesssim 5$ due to an early onset of HeII reionization unless the escape fraction of HeII-ionizing photons is assumed to be low. Our results suggest that a modest contribution to reionization by faint AGN is in good agreement with the Lyman-$\alpha$ forest data. In contrast, a scenario dominated by faint AGN appears difficult to reconcile with these observations., Comment: 19 pages, 11 figures

DBSCAN is an algorithm that performs clustering in the presence of noise. In this paper, we provide two constructions that allow DBSCAN to be implemented neuromorphically, using spiking neural networks. The first construction is termed "flat," resulting in large spiking neural networks that compute the algorithm quickly, in five timesteps. Moreover, the networks allow pipelining, so that a new DBSCAN calculation may be performed every timestep. The second construction is termed "systolic", and generates much smaller networks, but requires the inputs to be spiked in over several timesteps, column by column. We provide precise specifications of the constructions and analyze them in practical neuromorphic computing settings. We also provide an open-source implementation.

We present a sample of 50 H-alpha detected broad-line active galactic nuclei (BLAGN) at redshifts 3.50), independent of the contributions of emission lines to the broadband photometry. We construct the black hole (BH) mass function at 3.5

The external environments surrounding molecular clouds vary widely across galaxies such as the Milky Way, and statistical samples of clouds from surveys are required to understand them. We present the Perseus Arm Molecular Survey (PAMS), a James Clerk Maxwell Telescope (JCMT) survey of $^{13}$CO and C$^{18}$O ($J$=3$-$2) of several molecular cloud complexes including W5 and NGC 7538 in the outer Perseus spiral arm situated at $\ell \approx 110^{\circ}$ and $\ell \approx 135^{\circ}$, with a total survey area of $\sim$6 deg$^2$. The PAMS data have an effective resolution of 17.2 arcsec, and rms sensitivity of $T_\rm{mb} = 0.7$ K in 0.3 km/s channels. We present a first look at the data, and compare the PAMS regions in the Outer Galaxy with Inner Galaxy regions from the CO Heterodyne Inner Milky Way Plane Survey (CHIMPS), incorporating archival $^{12}$CO (3$-$2) data. By comparing the various CO data with maps of H$_2$ column density from $\textit{Herschel}$, we find that the CO-to-H$_2$ column density $X$-factors do not vary significantly between Galactocentric radii of 4 and 10 kpc, and present representative values of $X_{^{12}\rm{CO} 3-2}$ and $X_{^{13}\rm{CO} 3-2}$. We find that the emission profiles, size-linewidth and mass-radius relationships of $^{13}$CO-traced structures are similar between the Inner and Outer Galaxy. Although PAMS sources are more massive than their Inner Galaxy counterparts for a given size scale, the discrepancy can be accounted for by the Galactic gradient in gas-to-dust mass ratio, uncertainties in the $X$-factors, and selection biases. We have made the PAMS data publicly available, complementing other CO surveys targeting different regions of the Galaxy in different isotopologues and transitions., Comment: Currently under review at MNRAS

Molecular line emissions are commonly used to trace the distribution and properties of molecular Interstellar Medium (ISM). However, the emissions are heavily blended on the Galactic disk toward the inner Galaxy because of the relatively large line widths and the velocity overlaps of spiral arms. Structure identification methods based on voxel connectivity in PPV data cubes often produce unrealistically large structures, which is the ``over-linking'' problem. Therefore, identifying molecular cloud structures in these directions is not trivial. We propose a new method based on Gaussian decomposition and graph theory to solve the over-linking problem, named ISMGCC (InterStellar Medium Gaussian Component Clustering). Using the MWISP ${}^{13}\mathrm{CO}~(1-0)$ data in the range of $13.5^{\circ} \leq l \leq 14.5^{\circ}, |b| \leq 0.5^{\circ}$, and $-100\leq V_{\mathrm{LSR}} \leq +200~\mathrm{km~s^{-1}}$, our method identified three hundred molecular gas structures with at least 16 pixels. These structures contain $92\%$ of the total flux in the raw data cube and show single-peaked line profiles on more than $93\%$ of their pixels. The ISMGCC method could distinguish gas structures in crowded regions and retain most of the flux without global data clipping or assumptions on the structure geometry, meanwhile, allowing multiple Gaussian components for complicated line profiles., Comment: 25 pages, 14 figures, accepted for publication in Research in Astronomy and Astrophysics

Integral field spectroscopy (IFS) is a powerful tool for understanding the formation of galaxies across cosmic history. We present the observing strategy and first results of MSA-3D, a novel JWST program using multi-object spectroscopy in a slit-stepping strategy to produce IFS data cubes. The program observed 43 normal star-forming galaxies at redshifts $0.5 \lesssim z \lesssim 1.5$, corresponding to the epoch when spiral thin-disk galaxies of the modern Hubble sequence are thought to emerge, obtaining kpc-scale maps of rest-frame optical nebular emission lines with spectral resolution $R\simeq2700$. Here we describe the multiplexed slit-stepping method which is $>15$ times more efficient than the NIRSpec IFS mode for our program. As an example of the data quality, we present a case study of an individual galaxy at $z=1.104$ (stellar mass $M_{*} = 10^{10.3}~M_{\odot}$, star formation rate~$=3~M_{\odot}$ yr$^{-1}$) with prominent face-on spiral structure. We show that the galaxy exhibits a rotationally supported disk with moderate velocity dispersion ($\sigma = 36^{+5}_{-4}$~\kms), a negative radial metallicity gradient ($-0.020\pm0.002$~dex\,kpc$^{-1}$), a dust attenuation gradient, and an exponential star formation rate density profile which closely matches the stellar continuum. These properties are characteristic of local spirals, indicating that mature galaxies are in place at $z\sim1$. We also describe the customized data reduction and original cube-building software pipelines which we have developed to exploit the powerful slit-stepping technique. Our results demonstrate the ability of JWST slit-stepping to study galaxy populations at intermediate to high redshifts, with data quality similar to current surveys of the $z\sim0.1$ universe., Comment: 24 pages, 12 figures, 1 table; submitted to ApJ, comments welcome. Our custom designed data reduction pipeline (MSA3D) and example processed data-cube will be publicly released before the JWST Cycle 4 deadline. MSA3D package on GitHub: https://github.com/barisiciv/msa3d.git

We use JWST/NIRSpec observations from the Assembly of Ultradeep Rest-optical Observations Revealing Astrophysics (AURORA) survey to constrain the shape of the nebular attenuation curve of a star-forming galaxy at z=4.41, GOODSN-17940. We utilize 11 unblended HI recombination lines to derive the attenuation curve spanning optical to near-infrared wavelengths (3751-9550 \r{A}). We then leverage a high-S/N spectroscopic detection of the rest-frame ultraviolet continuum in combination with rest-UV photometric measurements to constrain the shape of the curve at ultraviolet wavelengths. While this UV constraint is predominantly based on stellar emission, the large measured equivalent widths of H$\alpha$ and H$\beta$ indicate that GOODSN-17940 is dominated by an extremely young stellar population <10 Myr in age such that the UV stellar continuum experiences the same attenuation as the nebular emission. The resulting combined nebular attenuation curve spans 1400-9550 \r{A} and has a shape that deviates significantly from commonly assumed dust curves in high-redshift studies. Relative to the Milky Way, SMC, and Calzetti curves, the new curve has a steeper slope at long wavelengths ($\lambda>5000$ \r{A}) while displaying a similar slope across blue-optical wavelengths ($\lambda=3750-5000$ \r{A}). In the ultraviolet, the new curve is shallower than the SMC and Calzetti curves and displays no significant 2175 \r{A} bump. This work demonstrates that the most commonly assumed dust curves are not appropriate for all high-redshift galaxies. These results highlight the ability to derive nebular attenuation curves for individual high-redshift sources with deep JWST/NIRSpec spectroscopy, thereby improving the accuracy of physical properties inferred from nebular emission lines., Comment: 21 pages, 6 figures, 1 table, submitted to ApJ

We report the discovery of the most eccentric transiting brown dwarf in the brown dwarf desert, TOI02490b. The brown dwarf desert is the lack of brown dwarfs around main sequence stars within $\sim3$~AU and is thought to be caused by differences in formation mechanisms between a star and planet. To date, only $\sim40$ transiting brown dwarfs have been confirmed. \systemt is a $73.6\pm2.4$ \mjupnospace, $1.00\pm0.02$ \rjup brown dwarf orbiting a $1.004_{-0.022}^{+0.031}$ \msunnospace, $1.105_{-0.012}^{+0.012}$ \rsun sun-like star on a 60.33~d orbit with an eccentricity of $0.77989\pm0.00049$. The discovery was detected within \tess sectors 5 (30 minute cadence) and 32 (2 minute and 20 second cadence). It was then confirmed with 31 radial velocity measurements with \feros by the WINE collaboration and photometric observations with the Next Generation Transit Survey. Stellar modelling of the host star estimates an age of $\sim8$~Gyr, which is supported by estimations from kinematics likely placing the object within the thin disc. However, this is not consistent with model brown dwarf isochrones for the system age suggesting an inflated radius. Only one other transiting brown dwarf with an eccentricity higher than 0.6 is currently known in the brown dwarf desert. Demographic studies of brown dwarfs have suggested such high eccentricity is indicative of stellar formation mechanisms., Comment: Accepted for publication in MNRAS, 18 pages, 14 figures

Whispering gallery mode (WGM) optomechanical resonators are a promising technology for the simultaneous control and measurement of optical and mechanical degrees of freedom at the nanoscale. They offer potential for use across a wide range of applications such as sensors and quantum transducers. Double-disk WGM resonators, which host strongly interacting mechanical and optical modes co-localized around their circumference, are particularly attractive due to their high optomechanical coupling. Large-scale integrated fabrication of silicon double-disk WGM resonators has not previously been demonstrated. In this work we present a process for the fabrication of double-layer silicon-on-insulator wafers, which we then use to fabricate functional optomechanical double silicon disk resonators with on-chip optical coupling. The integrated devices present an experimentally observed optical quality factors of the order of 10^5 and a single-photon optomechanical coupling of approximately 15 kHz.

The recent discoveries of Neptune-sized ultra-short period planets (USPs) challenge existing planet formation theories. It is unclear whether these residents of the Hot Neptune Desert have similar origins to smaller, rocky USPs, or if this discrete population is evidence of a different formation pathway altogether. We report the discovery of TOI-3261b, an ultra-hot Neptune with an orbital period $P$ = 0.88 days. The host star is a $V = 13.2$ magnitude, slightly super-solar metallicity ([Fe/H] $\simeq$ 0.15), inactive K1.5 main sequence star at $d = 300$ pc. Using data from the Transiting Exoplanet Survey Satellite and the Las Cumbres Observatory Global Telescope, we find that TOI-3261b has a radius of $3.82_{-0.35}^{+0.42}$ $R_{\oplus}$. Moreover, radial velocities from ESPRESSO and HARPS reveal a mass of $30.3_{-2.4}^{+2.2}$ $M_{\oplus}$, more than twice the median mass of Neptune-sized planets on longer orbits. We investigate multiple mechanisms of mass loss that can reproduce the current-day properties of TOI-3261b, simulating the evolution of the planet via tidal stripping and photoevaporation. Thermal evolution models suggest that TOI-3261b should retain an envelope potentially enriched with volatiles constituting $\sim$5% of its total mass. This is the second highest envelope mass fraction among ultra-hot Neptunes discovered to date, making TOI-3261b an ideal candidate for atmospheric follow-up observations., Comment: 20 pages, 11 figures, accepted to AJ

Network point processes often exhibit latent structure that govern the behaviour of the sub-processes. It is not always reasonable to assume that this latent structure is static, and detecting when and how this driving structure changes is often of interest. In this paper, we introduce a novel online methodology for detecting changes within the latent structure of a network point process. We focus on block-homogeneous Poisson processes, where latent node memberships determine the rates of the edge processes. We propose a scalable variational procedure which can be applied on large networks in an online fashion via a Bayesian forgetting factor applied to sequential variational approximations to the posterior distribution. The proposed framework is tested on simulated and real-world data, and it rapidly and accurately detects changes to the latent edge process rates, and to the latent node group memberships, both in an online manner. In particular, in an application on the Santander Cycles bike-sharing network in central London, we detect changes within the network related to holiday periods and lockdown restrictions between 2019 and 2020., Comment: 34 pages, 17 figures

Recent observations with the James Webb Space Telescope (JWST) have uncovered unexpectedly high cosmic star formation activity in the early Universe, mere hundreds of millions of years after the Big Bang. These observations are often understood to reflect an evolutionary shift in star formation efficiency (SFE) caused by changing galactic conditions during these early epochs. We present FIREbox-HR, a high-resolution, cosmological hydrodynamical simulation from the Feedback in Realistic Environments project, which offers insights into the SFE of galaxies during the first billion years of cosmic time. FIREbox-HR re-simulates the cosmic volume (L = 22.1 cMpc) of the original FIREbox run with eight times higher mass resolution (m_b ~ 7800 M_sun), but with identical physics, down to z ~ 6. FIREbox-HR predicts ultraviolet (UV) luminosity functions in good agreement with available observational data. The simulation also successfully reproduces the observed cosmic UV luminosity density at z ~ 6 - 14, demonstrating that relatively high star formation activity in the early Universe is a natural outcome of the baryonic processes encoded in the FIRE-2 model. According to FIREbox-HR, the SFE - halo mass relation for intermediate mass halos (M_halo ~ 10^9 - 10^11 M_sun) does not significantly evolve with redshift and is only weakly mass-dependent. These properties of the SFE - halo mass relation lead to a larger contribution from lower mass halos at higher z, driving the gradual evolution of the observed cosmic UV luminosity density. A theoretical model based on the SFE - halo mass relation inferred from FIREbox-HR allows us to explore implications for galaxy evolution. Future observations of UV faint galaxies at z > 12 will provide an opportunity to further test these predictions and deepen our understanding of star formation during Cosmic Dawn., Comment: 28 pages, 14 figures, 5 tables, revised to match version accepted by MNRAS, Appendix D added, UV LF shown in Fig. 1 provided as txt file

We investigated the effectiveness of a sustained and spiraled content literacy intervention that emphasizes building domain and topic knowledge schemas and vocabulary for elementary-grade students. The Model of Reading Engagement (MORE) intervention underscores thematic lessons that provide an intellectual structure for helping students connect new learning to a general schema in Grade 1 (animal survival), Grade 2 (scientific investigation of past events like dinosaur mass extinctions), and Grade 3 (scientific investigation of living systems). A total of 30 elementary schools (N = 2,870 students) were randomized to a treatment or control condition. In the treatment condition (i.e., full spiral curriculum), students participated in content literacy lessons from Grades 1 to 3 during the school year and wide reading of thematically related informational texts in the summer following Grades 1 and 2. In the control condition (i.e., partial spiral curriculum), students participated in lessons in only Grade 3. The Grade 3 lessons for both conditions were implemented online during the COVID-19 pandemic school year. Results reveal that treatment students outperformed control students on science vocabulary knowledge across all three grades. Furthermore, intent-to-treat analyses revealed positive transfer effects on Grade 3 science reading (ES = 0.14), domain-general reading comprehension (ES = 0.11), and mathematics achievement (ES = 0.12). Treatment impacts were sustained at 14-month follow-up on Grade 4 reading comprehension (ES = 0.12) and mathematics achievement (ES = 0.16). Findings indicate that a content literacy intervention that spirals topics and vocabulary across grades can improve students' long-term academic achievement outcomes.

Aortic stenosis (AS) is the most common valvular heart disease in developed countries. High-fidelity preclinical models can improve AS management by enabling therapeutic innovation, early diagnosis, and tailored treatment planning. However, their use is currently limited by complex workflows necessitating lengthy expert-driven manual operations. Here, we propose an AI-powered computational framework for accelerated and democratized patient-specific modeling of AS hemodynamics from computed tomography. First, we demonstrate that our automated meshing algorithms can generate task-ready geometries for both computational and benchtop simulations with higher accuracy and 100 times faster than existing approaches. Then, we show that our approach can be integrated with fluid-structure interaction and soft robotics models to accurately recapitulate a broad spectrum of clinical hemodynamic measurements of diverse AS patients. The efficiency and reliability of these algorithms make them an ideal complementary tool for personalized high-fidelity modeling of AS biomechanics, hemodynamics, and treatment planning., Comment: CO and DHP contributed equally to this work. JSD and ETR are corresponding authors

We present results on the emission-line properties of z=1.4-7.5 star-forming galaxies in the Assembly of Ultradeep Rest-optical Observations Revealing Astrophysics (AURORA) Cycle 1 JWST/NIRSpec program. Based on its depth, continuous wavelength coverage from 1--5 microns, and medium spectral resolution (R~1000), AURORA includes detections of a large suite of nebular emission lines spanning a broad range in rest wavelength. We investigate the locations of AURORA galaxies in multiple different emission-line diagrams, including traditional "BPT" diagrams of [OIII]/Hbeta vs. [NII]/Halpha, [SII]/Halpha, and [OI]/Halpha, and the "ionization-metallicity" diagram of [OIII]/[OII] (O32) vs. ([OIII]+[OII])/Hbeta (R23). We also consider a bluer rest-frame "ionization-metallicity" diagram introduced recently to characterize z>10 galaxies: [NeIII]/[OII] vs. ([NeIII]+[OII])/Hdelta; as well as longer-wavelength diagnostic diagrams extending into the rest-frame near-IR: [OIII]/Hbeta vs. [SIII]/[SII] (S32); and HeI/Pagamma and [SIII]/Pagamma vs. [FeII]/Pabeta. With a significant boost in signal-to-noise and large, representative samples of individual galaxy detections, the AURORA emission-line diagrams presented here definitively confirm a physical picture in which chemically-young, alpha-enhanced, massive stars photoionize the ISM in distant galaxies with a harder ionizing spectrum at fixed nebular metallicity than in their z~0 counterparts. We also uncover previously unseen evolution prior to z~2 in the [OIII]/Hbeta vs. [NII]/Halpha diagram, which motivates deep NIRSpec observations at even higher redshift. Finally, we present the first statistical sample of rest-frame near-IR emission-line diagnostics in star-forming galaxies at high redshift. In order to truly interpret rest-frame near-IR line ratios including [FeII], we must obtain better constraints on dust depletion in the high-redshift ISM., Comment: 17 pages, 8 figures, submitted to ApJ

Recent evidence supporting reionisation ending at redshift z<6 includes the rapid redshift evolution of the mean free path for Lyman-limit photons through the intergalactic medium at 510 discovered with JWST., Comment: 17 pages, 14 figures, accepted to MNRAS

Background: We propose a novel method to identify who may likely have clonal hematopoiesis of indeterminate potential (CHIP), a condition characterized by the presence of somatic mutations in hematopoietic stem cells without detectable hematologic malignancy, using deep learning techniques. Methods: We developed a convolutional neural network (CNN) to predict CHIP status using 4 different views from standard delayed gadolinium-enhanced cardiac magnetic resonance imaging (CMR). We used 5-fold cross validation on 82 cardio-oncology patients to assess the performance of our model. Different algorithms were compared to find the optimal patient-level prediction method using the image-level CNN predictions. Results: We found that the best model had an area under the receiver operating characteristic curve of 0.85 and an accuracy of 82%. Conclusions: We conclude that a deep learning-based diagnostic approach for CHIP using CMR is promising.

We present the number densities and physical properties of the bright galaxies spectroscopically confirmed at $z\sim7-14$. Our sample is composed of 60 galaxies at $z_\mathrm{spec}\sim7-14$, including recently-confirmed galaxies at $z_\mathrm{spec}=12.34-14.32$ with JWST, as well as new confirmations at $z_\mathrm{spec}=6.583-7.643$ with $-24< M_\mathrm{UV}< -21$ mag using ALMA and Keck. Our JWST/NIRSpec observations have also revealed that very bright galaxy candidates at $z\sim10-13$ identified from ground-based telescope images before JWST are passive galaxies at $z\sim3-4$, emphasizing the necessity of strict screening and spectroscopy in the selection of the brightest galaxies at $z>10$. The UV luminosity functions derived from these spectroscopic results are consistent with a double power-law function, showing tensions with theoretical models at the bright end. To understand the origin of the overabundance of bright galaxies, we investigate their morphologies using JWST/NIRCam high-resolution images obtained in various surveys including PRIMER and COSMOS-Web. We find that $\sim70\%$ of the bright galaxies at $z\sim7$ exhibit clumpy morphologies with multiple sub-components, suggesting merger-induced starburst activity, which is consistent with SED fitting results showing bursty star formation histories. At $z\gtrsim10$, bright galaxies are classified into two types of galaxies; extended ones with weak high-ionization emission lines, and compact ones with strong high-ionization lines including NIV]$\lambda$1486, indicating that at least two different processes (e.g., merger-induced starburst and compact star formation/AGN) are shaping the physical properties of the brightest galaxies at $z\gtrsim10$ and are responsible for their overabundance., Comment: 34 pages, 22 figures, Accepted for Publication in ApJ

Task-based fMRI uses actions or stimuli to trigger task-specific brain responses and measures them using BOLD contrast. Despite the significant task-induced spatiotemporal brain activation fluctuations, most studies on task-based fMRI ignore the task context information aligned with fMRI and consider task-based fMRI a coherent sequence. In this paper, we show that using the task structures as data-driven guidance is effective for spatiotemporal analysis. We propose STNAGNN, a GNN-based spatiotemporal architecture, and validate its performance in an autism classification task. The trained model is also interpreted for identifying autism-related spatiotemporal brain biomarkers.

The stellar structures of star-forming galaxies (SFGs) undergo significant size growth during their mass assembly and must pass through a compaction phase as they evolve into quiescent galaxies (QGs). To shed light on the mechanisms behind this structural evolution, we study the morphology of the star-forming components of 665 SFGs at 010^{10.5}M_\odot$). The compact star-forming components of these galaxies are also concentrated and slightly spheroidal, suggesting that this compaction phase can build dense bulge in-situ. Finally, we identify a third population of SFGs (19%), with both compact stellar and star-forming components. The density of their stellar cores resemble those of QGs and are compatible with being the descendants of EC galaxy. Overall, the structural evolution of SFGs is mainly dominated by a secular inside-out growth, which can, however, be interrupted by violent compaction phase(s) that can build dominant stellar bulges like those in massive SFGs or QGs., Comment: 24 pages, 17 figures, submitted to A&A, comments are welcome

El Ni\~no-Southern Oscillation global (ENSO) imprint on sea surface temperature comes in many guises. To identify its tropical fingerprints and impacts on the rest of the climate system, we propose a global approach based on archetypal analysis (AA), a pattern recognition method based on the identification of extreme configurations in the dataset under investigation. Relying on detrended sea surface temperature monthly anomalies over the 1982 to 2022 period, the technique recovers central and eastern Pacific ENSO types identified by more traditional methods and allows one to hierarchically add extra flavours and nuances to both persistent and transient phases of the phenomenon. Archetypal patterns found compare favorably to phase identification from K-means, fuzzy C-means and recently published network-based machine-learning algorithms. The AA implementation is modified for the identification of ENSO phases in sub-seasonal-to-seasonal prediction systems and complements current alert systems in characterising the diversity of ENSO and its teleconnections. Tropical and extra-tropical teleconnection composites from various oceanic and atmospheric fields derived from the analysis are shown to be robust and physically relevant. Extending AA to sub-surface ocean fields improves the discrimination between phases when the characterisation of ENSO based on sea surface temperature is uncertain. We show that AA on detrended sea-level monthly anomalies provides a clearer expression of ENSO types., Comment: 59 pages, 16 figures and supplementary materials with 41 pages and 23 figurs

Positron Emission Tomography (PET) is an important clinical imaging tool but inevitably introduces radiation hazards to patients and healthcare providers. Reducing the tracer injection dose and eliminating the CT acquisition for attenuation correction can reduce the overall radiation dose, but often results in PET with high noise and bias. Thus, it is desirable to develop 3D methods to translate the non-attenuation-corrected low-dose PET (NAC-LDPET) into attenuation-corrected standard-dose PET (AC-SDPET). Recently, diffusion models have emerged as a new state-of-the-art deep learning method for image-to-image translation, better than traditional CNN-based methods. However, due to the high computation cost and memory burden, it is largely limited to 2D applications. To address these challenges, we developed a novel 2.5D Multi-view Averaging Diffusion Model (MADM) for 3D image-to-image translation with application on NAC-LDPET to AC-SDPET translation. Specifically, MADM employs separate diffusion models for axial, coronal, and sagittal views, whose outputs are averaged in each sampling step to ensure the 3D generation quality from multiple views. To accelerate the 3D sampling process, we also proposed a strategy to use the CNN-based 3D generation as a prior for the diffusion model. Our experimental results on human patient studies suggested that MADM can generate high-quality 3D translation images, outperforming previous CNN-based and Diffusion-based baseline methods., Comment: 15 pages, 7 figures

This is an elementary exposition of the basic descent theorems for algebraic schemes over fields (Grothendieck, Weil, ...)., Comment: 27 pages