Search

Future space observatories dedicated to direct imaging and spectroscopy of extra-solar planets will require ultra-low-noise detectors that are sensitive over a broad range of wavelengths. Silicon charge-coupled devices (CCDs), such as EMCCDs, Skipper CCDs, and Multi-Amplifier Sensing CCDs, have demonstrated the ability to detect and measure single photons from ultra-violet to near-infrared wavelengths, making them candidate technologies for this application. In this context, we study a relatively unexplored source of low-energy background coming from Cherenkov radiation produced by energetic charged particles traversing a silicon detector. In the intense radiation environment of space, energetic cosmic rays produce high-energy tracks and more extended halos of low-energy Cherenkov photons, which are detectable with ultra-low-noise detectors. We present a model of this effect that is calibrated to laboratory data, and we use this model to characterize the residual background rate for ultra-low noise silicon detectors in space. We find that the rate of cosmic-ray-induced Cherenkov photon production is comparable to other detector and astrophysical backgrounds that have previously been considered., Comment: SPIE Proceeding; 9 pages, 6 figures

This study is the first to explore whether multi-modal large language models (LLMs) can align their behaviors with visual personas, addressing a significant gap in the literature that predominantly focuses on text-based personas. We developed a novel dataset of 5K fictional avatar images for assignment as visual personas to LLMs, and analyzed their negotiation behaviors based on the visual traits depicted in these images, with a particular focus on aggressiveness. The results indicate that LLMs assess the aggressiveness of images in a manner similar to humans and output more aggressive negotiation behaviors when prompted with an aggressive visual persona. Interestingly, the LLM exhibited more aggressive negotiation behaviors when the opponent's image appeared less aggressive than their own, and less aggressive behaviors when the opponents image appeared more aggressive., Comment: EMNLP 2024

The observation that accelerated cosmic expansion is dominant since the Mega-parsec cosmic structure became nonlinear seems like an extraordinary coincidence, unless the acceleration is somehow driven by the emergence of the structure. That has given rise to the controversial concept of a gravitational backreaction through which inhomogeneity becomes a driver of accelerated expansion. The standard route when studying strongly inhomogeneous cosmological models is to take either a perturbative approach or a spatial averaging approach. Here we argue that because backreaction is in fact a nonlinear multiscale phenomenon, perturbative approaches may have a limited validity. The alternative is the proposed averaging approach. In this paper we demonstrate that the implied backreaction terms are artificial, that is gauge dependent, which may easily cause ambiguous estimates of its significance. In the current study, we forward a formal fully geometric framework of cosmic foliations in the context of relativistic cosmology. Here we show that fixing a foliation of spacetime determines a choice of gauge. Addressing the correspondence between the metric tensor and the foliation allows us to clarify the theoretical implications of choosing a foliation. Within the context of backreaction, this formalism allows us to discuss the complications of averaging. It reveals that spatial averaging can induce artificial backreaction terms that arise from any specific choice of gauge. Averaging methods presented so far all encounter this problem. Within our foliation framework, we can produce a gauge invariant method of averaging by considering a group of proper time foliations which any cosmic observe can agree upon. We demonstrate that this implies the gauge invariance of the averaging procedure. This makes it applicable to standard cosmological simulations., Comment: arXiv admin note: text overlap with arXiv:2310.19451

Nowadays, as the ever-increasing demand for more powerful computing resources continues, alternative advanced computing paradigms are under extensive investigation. Significant effort has been made to deviate from conventional Von Neumann architectures. In-memory computing has emerged in the field of electronics as a possible solution to the infamous bottleneck between memory and computing processors, which reduces the effective throughput of data. In photonics, novel schemes attempt to collocate the computing processor and memory in a single device. Photonics offers the flexibility of multiplexing streams of data not only spatially and in time, but also in frequency or, equivalently, in wavelength, which makes it highly suitable for parallel computing. Here, we numerically show the use of time and wavelength division multiplexing (WDM) to solve four independent tasks at the same time in a single photonic chip, serving as a proof of concept for our proposal. The system is a time-delay reservoir computing (TDRC) based on a microring resonator (MRR). The addressed tasks cover different applications: Time-series prediction, waveform signal classification, wireless channel equalization, and radar signal prediction. The system is also tested for simultaneous computing of up to 10 instances of the same task, exhibiting excellent performance. The footprint of the system is reduced by using time-division multiplexing of the nodes that act as the neurons of the studied neural network scheme. WDM is used for the parallelization of wavelength channels, each addressing a single task. By adjusting the input power and frequency of each optical channel, we can achieve levels of performance for each of the tasks that are comparable to those quoted in state-of-the-art reports focusing on single-task operation..., Comment: Main text: 11 figures, 3 tables. Supplementary material: 2 figures, 4 tables. The manuscript presented in this pre-print has been accepted for publication in Frontiers: Advanced Optical Technologies. The abstract is shorter than in the PDF file to comply with arXiv requirements

Supermassive black holes (SMBHs) are thought to be located at the centers of most galactic nuclei. When galaxies merge they form supermassive black hole binary (SMBHB) systems and these central SMBHs will also merge at later times, producing gravitational waves (GWs). Because galaxy mergers are likely gas-rich environments, SMBHBs are also potential sources of electromagnetic (EM) radiation. The EM signatures depend on gas dynamics, orbital dynamics, and radiation processes. The gas dynamics are governed by general relativistic magnetohydrodynamics (MHD) in a time-dependent spacetime. Numerically solving the MHD equations for a time-dependent binary spacetime is computationally expensive. Therefore, it is challenging to conduct a full exploration of the parameter space of these systems and the resulting EM signatures. We have developed an analytical accretion disk model for the mini-disks of an SMBHB system and produced images and light curves using a general relativistic ray-tracing code and a superimposed harmonic binary black hole metric. This analytical model greatly reduces the time and computational resources needed to explore these systems, while incorporating some key information from simulations. We present a parameter space exploration of the SMBHB system in which we have studied the dependence of the EM signatures on the spins of the black holes (BHs), the mass ratio, the accretion rate, the viewing angle, and the initial binary separation. Additionally, we study how the commonly used fast-light approximation affects the EM signatures and evaluate its validity in GRMHD simulations.

We overview the history of primordial black hole (PBH) research from the first papers around 50 years ago to the present epoch. The history may be divided into four periods, the dividing lines being marked by three key developments: inflation on the theoretical front and the detection of microlensing events by the MACHO project and gravitational waves by the LIGO/Virgo/KAGRA project on the observation front. However, they are also characterised by somewhat different focuses of research. The period 1967-1980 covered the groundbreaking work on PBH formation and evaporation. The period 1980-1996 mainly focussed on their formation, while the period 1996-2016 consolidated the work on formation but also collated the constraints on the PBH abundance. In the period 2016-2024 there was a shift of emphasis to the search for evidence for PBHs and - while opinions about the strength of the purported evidence vary - this has motivated more careful studies of some aspects of the subject. Certainly the soaring number of papers on PBHs in this last period indicates a growing interest in the topic., Comment: 16 pages, 5 figures. To appear (with updates) in the book "Primordial Black Holes", ed. Chris Byrnes, Gabriele Franciolini, Tomohiro Harada, Paolo Pani, Misao Sasaki; Springer (2024). v2: minor changes

Silicon microring resonators (MRRs) have shown strong potential in acting as the nonlinear nodes of photonic reservoir computing (RC) schemes. By using nonlinearities within a silicon MRR, such as the ones caused by free-carrier dispersion (FCD) and thermo-optic (TO) effects, it is possible to map the input data of the RC to a higher dimensional space. Furthermore, by adding an external waveguide between the through and add ports of the MRR, it is possible to implement a time-delay RC (TDRC) with enhanced memory. The input from the through port is fed back into the add port of the ring with the delay applied by the external waveguide effectively adding memory. In a TDRC, the nodes are multiplexed in time, and their respective time evolutions are detected at the drop port. The performance of MRR-based TDRC is highly dependent on the amount of nonlinearity in the MRR. The nonlinear effects, in turn, are dependent on the physical properties of the MRR as they determine the lifetime of the effects. Another factor to take into account is the stability of the MRR response, as strong time-domain discontinuities at the drop port are known to emerge from FCD nonlinearities due to self-pulsing (high nonlinear behaviour). However, quantifying the right amount of nonlinearity that RC needs for a certain task in order to achieve optimum performance is challenging. Therefore, further analysis is required to fully understand the nonlinear dynamics of this TDRC setup. Here, we quantify the nonlinear and linear memory capacity of the previously described microring-based TDRC scheme, as a function of the time constants of the generated carriers and the thermal of the TO effects. We analyze the properties of the TDRC dynamics that generate the parameter space, in terms of input signal power and frequency detuning range, over which conventional RC tasks can be satisfactorily performed by the TDRC scheme., Comment: 12 pages, 12 figures. Proceedings SPIE Europe 2024

The Habitable Worlds Observatory (HWO) will seek to detect and characterize potentially Earth-like planets around other stars. To ensure that the mission achieves the Astro2020 Decadal's recommended goal of 25 exoEarth candidates (EECs), we must take into account the probabilistic nature of exoplanet detections and provide "science margin" to budget for astrophysical uncertainties with a reasonable level of confidence. In this study, we explore the probabilistic distributions of yields to be expected from a blind exoEarth survey conducted by such a mission. We identify and estimate the impact of all major known sources of astrophysical uncertainty on the exoEarth candidate yield. As expected, eta_Earth uncertainties dominate the uncertainty in EEC yield, but we show that sampling uncertainties inherent to a blind survey are another important source of uncertainty that should be budgeted for during mission design. We adopt the Large UV/Optical/IR Surveyor Design B (LUVOIR-B) as a baseline and modify the telescope diameter to estimate the science margin provided by a larger telescope. We then depart from the LUVOIR-B baseline design and identify six possible design changes that, when compiled, provide large gains in exoEarth candidate yield and more than an order of magnitude reduction in exposure times for the highest priority targets. We conclude that a combination of telescope diameter increase and design improvements could provide robust exoplanet science margins for HWO., Comment: 90 pages, 26 figures, 4 tables, Submitted to JATIS

Accurate detection of colorectal cancer and early prevention heavily rely on precise polyp identification during gastrointestinal colonoscopy. Due to limited data, many current state-of-the-art deep learning methods for polyp segmentation often rely on post-processing of masks to reduce noise and enhance results. In this study, we propose an approach that integrates mask refinement and binary semantic segmentation, leveraging a novel collaborative training strategy that surpasses current widely-used refinement strategies. We demonstrate the superiority of our approach through comprehensive evaluation on established benchmark datasets and its successful application across various medical image segmentation architectures.

Observations of transiting gas giant exoplanets have revealed a pervasive depletion of methane, which has only recently been identified atmospherically. The depletion is thought to be maintained by disequilibrium processes such as photochemistry or mixing from a hotter interior. However, the interiors are largely unconstrained along with the vertical mixing strength and only upper limits on the CH$_4$ depletion have been available. The warm Neptune WASP-107 b stands out among exoplanets with an unusually low density, reported low core mass, and temperatures amenable to CH$_4$ though previous observations have yet to find the molecule. Here we present a JWST NIRSpec transmission spectrum of WASP-107 b which shows features from both SO$_2$ and CH$_4$ along with H$_2$O, CO$_2$, and CO. We detect methane with 4.2$\sigma$ significance at an abundance of 1.0$\pm$0.5 ppm, which is depleted by 3 orders of magnitude relative to equilibrium expectations. Our results are highly constraining for the atmosphere and interior, which indicate the envelope has a super-solar metallicity of 43$\pm$8$\times$ solar, a hot interior with an intrinsic temperature of T$_{\rm int}$=460$\pm$40 K, and vigorous vertical mixing which depletes CH4 with a diffusion coefficient of Kzz = 10$^{11.6\pm0.1}$ cm$^2$/s. Photochemistry has a negligible effect on the CH$_4$ abundance, but is needed to account for the SO$_2$. We infer a core mass of 11.5$_{-3.6}^{+3.0}$ M$_{\odot}$, which is much higher than previous upper limits, releasing a tension with core-accretion models., Comment: Published in Nature at this URL, https://www.nature.com/articles/s41586-024-07395-z . This is the authors version of the manuscript, 20 pages including Methods. Data from Figs. 1, 2, and 3 are available at this URL, https://doi.org/10.5281/zenodo.10891400

We present results from a kinetic model of collisionless gyrotropic coronal hole protons heated by cyclotron and Landau resonant dissipation of critically balanced kinetic Alfv\'en waves. The model incorporates the kinetic effects of gravity, ambipolar electric field, ponderomotive force of the large-scale Alfv\'en waves and the mirror force in a super-radially expanding flux tube. The flow speed is self- consistently obtained as the bulk flow of the proton distribution. Two cases, taking the intensities of the turbulent spectra to be balanced in the parallel propagation direction or imbalanced at a ratio of 9:1 show almost no difference. The distributions develop parallel extensions outward due to the Landau resonance, but exhibit very little perpendicular heating under the parameter choices used here. The speeds and temperatures fall well short of the requirements for a fast solar wind. Rather than continuing to explore the parameter space of this system, we propose that a modified model using turbulent spectra based on the recent helicity barrier scenario would be an appropriate next step., Comment: Submitted to the Proceeding of Solar Wind 16 Conference, June 2023

Over the past decade, AI research has focused heavily on building ever-larger deep learning models. This approach has simultaneously unlocked incredible achievements in science and technology, and hindered AI from overcoming long-standing limitations with respect to explainability, ethical harms, and environmental efficiency. Drawing on qualitative interviews and computational analyses, our three-part history of AI research traces the creation of this "epistemic monoculture" back to a radical reconceptualization of scientific progress that began in the late 1980s. In the first era of AI research (1950s-late 1980s), researchers and patrons approached AI as a "basic" science that would advance through autonomous exploration and organic assessments of progress (e.g., peer-review, theoretical consensus). The failure of this approach led to a retrenchment of funding in the 1980s. Amid this "AI Winter," an intervention by the U.S. government reoriented the field towards measurable progress on tasks of military and commercial interest. A new evaluation system called "benchmarking" provided an objective way to quantify progress on tasks by focusing exclusively on increasing predictive accuracy on example datasets. Distilling science down to verifiable metrics clarified the roles of scientists, allowed the field to rapidly integrate talent, and provided clear signals of significance and progress. But history has also revealed a tradeoff to this streamlined approach to science: the consolidation around external interests and inherent conservatism of benchmarking has disincentivized exploration beyond scaling monoculture. In the discussion, we explain how AI's monoculture offers a compelling challenge to the belief that basic, exploration-driven research is needed for scientific progress. Implications for the spread of AI monoculture to other sciences in the era of generative AI are also discussed.

Large language models exhibit societal biases associated with demographic information, including race, gender, and others. Endowing such language models with personalities based on demographic data can enable generating opinions that align with those of humans. Building on this idea, we propose "random silicon sampling," a method to emulate the opinions of the human population sub-group. Our study analyzed 1) a language model that generates the survey responses that correspond with a human group based solely on its demographic distribution and 2) the applicability of our methodology across various demographic subgroups and thematic questions. Through random silicon sampling and using only group-level demographic information, we discovered that language models can generate response distributions that are remarkably similar to the actual U.S. public opinion polls. Moreover, we found that the replicability of language models varies depending on the demographic group and topic of the question, and this can be attributed to inherent societal biases in the models. Our findings demonstrate the feasibility of mirroring a group's opinion using only demographic distribution and elucidate the effect of social biases in language models on such simulations., Comment: 25 pages, 4 figures, 19 Tables

We describe a custom outlier rejection algorithm for JWST/NIRSpec integral field spectroscopy. This method uses a layered sigma clipping approach that adapts clipping thresholds based upon the spatial profile of the science target. We find that this algorithm produces a robust outlier rejection while simultaneously preserving the signal of the science target. Originally developed as a response to unsatisfactory initial performance of the jwst pipeline outlier detection step, this method works either as a standalone solution, or as a supplement to the current pipeline software. Comparing leftover (i.e., not flagged) artifacts with the current pipeline's outlier detection step, we find that our method results in one fifth as many residual artifacts as the jwst pipeline. However, we find a combination of both methods removes nearly all artifacts -- an approach that takes advantage of both our algorithm's robust outlier rejection and the pipeline's use of individual dithers. This combined approach is what the TEMPLATES Early Release Science team has converged upon for our NIRSpec observations. Finally, we publicly release the code and Jupyter notebooks for the custom outlier rejection algorithm., Comment: 10 pages, including 5 figures. Submitted to the Publications of the Astronomical Society of the Pacific (PASP). Code associated with paper released at https://github.com/aibhleog/baryon-sweep

We numerically demonstrate a silicon add-drop microring-based reservoir computing scheme that combines parallel delayed inputs and wavelength division multiplexing. The scheme solves memory-demanding tasks like time-series prediction with good performance without requiring external optical feedback., Comment: 2 pages, 2 figures. Submitted to Conference on Lasers and Electro-Optics (CLEO) 2024

The Q&U Bolometric Interferometer for Cosmology (QUBIC) is the first bolometric interferometer designed to measure the primordial B-mode polarization of the Cosmic Microwave Background (CMB). Bolometric interferometry is a novel technique that combines the sensitivity of bolometric detectors with the control of systematic effects that is typical of interferometry, both key features in the quest for the faint signal of the primordial B-modes. A unique feature is the so-called "spectral imaging", i.e., the ability to recover the sky signal in several sub-bands within the physical band during data analysis. This feature provides an in-band spectral resolution of \Delta{\nu}/{\nu} \sim 0.04 that is unattainable by a traditional imager. This is a key tool for controlling the Galactic foregrounds contamination. In this paper, we describe the principles of bolometric interferometry, the current status of the QUBIC experiment and future prospects., Comment: To appear in Proc. of the mm Universe 2023 conference, Grenoble (France), June 2023, published by F. Mayet et al. (Eds), EPJ Web of conferences, EDP Sciences

The observation that accelerated cosmic expansion appears to start around the time that nonlinear cosmic structure is appearing seems like an extraordinary coincidence, unless the acceleration is somehow driven by the emergence of the structure. That has given rise to the controversial concept of a gravitational backreaction through which inhomogeneity becomes a driver of accelerated expansion. The standard route when studying strongly inhomogeneous cosmological models is to take either a perturbative approach or a spatial averaging approach. Here we argue that because backreaction is in fact a nonlinear multiscale phenomenon, perturbative approaches may have a limited validity. With respect to the currently proposed averaging approaches we here show that they lead to gauge dependent backreaction and hence ambiguous estimates of its magnitude. In the present study, we formalise inhomogeneous cosmic evolution within the framework of foliations of spacetime. Fixing a foliation amounts to making a gauge choice. Addressing the correspondence between the metric tensor and the foliation allows us to clarify the implications of choosing a foliation for the representation of equivalent cosmologies. It is important to note that, within the context of backreaction, this formalism allows us to discuss the vagaries of averaging in the framework of spacetime foliations. It reveals that spatial averaging can induce artificial, i.e. gauge dependent, backreaction terms that arise from any specific choice of gauge. Averaging methods presented so far all encounter this problem. However, within our foliation framework, we can produce a gauge invariant method of averaging by invoking the gauge-invariant Bardeen formalism for cosmological perturbation theory. We demonstrate that this implies the gauge invariance of the averaging procedure. This makes it applicable to standard cosmological simulations., Comment: 21 pages, 3 figures, typos fixed in v2

Among the promising advantages of photonic computing over conventional computing architectures is the potential to increase computing efficiency through massive parallelism by using the many degrees of freedom provided by photonics. Here, we numerically demonstrate the simultaneous use of time and frequency (equivalently wavelength) multiplexing to solve three independent tasks at the same time on the same photonic circuit. In particular, we consider a microring-based time-delay reservoir computing (TDRC) scheme that simultaneously solves three tasks: Time-series prediction, classification, and wireless channel equalization. The scheme relies on time-division multiplexing to avoid the necessity of multiple physical nonlinear nodes, while the tasks are parallelized using wavelength division multiplexing (WDM). The input data modulated on each optical channel is mapped to a higher dimensional space by the nonlinear dynamics of the silicon microring cavity. The carrier wavelength and input power assigned to each optical channel have a high influence on the performance of its respective task. When all tasks operate under the same wavelength/power conditions, our results show that the computing nature of each task is the deciding factor of the level of performance achievable. However, it is possible to achieve good performance for all tasks simultaneously by optimizing the parameters of each optical channel. The variety of applications covered by the tasks shows the versatility of the proposed photonic TDRC scheme. Overall, this work provides insight into the potential of WDM-based schemes for improving the computing capabilities of reservoir computing schemes., Comment: 7 pages, 7 figures, Accepted for presentation at The International Joint Conference on Neural Networks (IJCNN), part of IEEE WCCI 2024

We summarize the properties and initial data release of the JADES Origins Field (JOF), which will soon be the deepest imaging field yet observed with the James Webb Space Telescope (JWST). This field falls within the GOODS-S region about 8' south-west of the Hubble Ultra Deep Field (HUDF), where it was formed initially in Cycle 1 as a parallel field of HUDF spectroscopic observations within the JWST Advanced Deep Extragalactic Survey (JADES). This imaging will be greatly extended in Cycle 2 program 3215, which will observe the JOF for 5 days in six medium-band filters, seeking robust candidates for z>15 galaxies. This program will also include ultra-deep parallel NIRSpec spectroscopy (up to 104 hours on-source, summing over the dispersion modes) on the HUDF. Cycle 3 observations from program 4540 will add 20 hours of NIRCam slitless spectroscopy to the JOF. With these three campaigns, the JOF will be observed for 380 open-shutter hours with NIRCam using 15 imaging filters and 2 grism bandpasses. Further, parts of the JOF have deep 43 hr MIRI observations in F770W. Taken together, the JOF will soon be one of the most compelling deep fields available with JWST and a powerful window into the early Universe. This paper presents the second data release from JADES, featuring the imaging and catalogs from the year 1 JOF observations., Comment: Submitted to ApJ Supplement. Images and catalogs are available at https://archive.stsci.edu/hlsp/jades . A FITSmap portal to view the images is at https://jades.idies.jhu.edu

Microring resonators (MRRs) are promising devices for time-delay photonic reservoir computing, but the impact of the different physical effects taking place in the MRRs on the reservoir computing performance is yet to be fully understood. We numerically analyze the impact of linear losses as well as thermo-optic and free-carrier effects relaxation times on the prediction error of the time-series task NARMA-10. We demonstrate the existence of three regions, defined by the input power and the frequency detuning between the optical source and the microring resonance, that reveal the cavity transition from linear to nonlinear regimes. One of these regions offers very low error in time-series prediction under relatively low input power and number of nodes while the other regions either lack nonlinearity or become unstable. This study provides insight into the design of the MRR and the optimization of its physical properties for improving the prediction performance of time-delay reservoir computing., Comment: 20 pages, 11 figures, submitted to Optics Express (reviewed version)

We quantify the impact of thermo-optic and free-carrier effects on time-delay reservoir computing using a silicon microring resonator. We identify pump power and frequency detuning ranges with NMSE less than 0.05 for the NARMA-10 task depending on the time constants of the two considered effects., Comment: 2 pages, 2 figures. Submitted to IEEE Photonics Conference 2023

NSClean is an algorithm and associated python package for removing faint vertical banding and ``picture frame noise'' from JWST Near Infrared Spectrograph (NIRSpec) images. NSClean uses known dark areas to fit a background model to each exposure in Fourier space. When the model is subtracted, it removes nearly all correlated noise. Compared to simpler strategies like subtracting the rolling median, NSClean is more thorough and uniform. NSClean is computationally undemanding, requiring only a few seconds to clean an image on a typical laptop. The NSClean package is freely available from the NASA JWST website (https://webb.nasa.gov/content/forScientists/publications.html)., Comment: 9 pages, 5 figures, in preparation for an astrophysics journal

We describe the NIRSpec component of the JWST Deep Extragalactic Survey (JADES), and provide deep spectroscopy of 253 sources targeted with the NIRSpec micro-shutter assembly in the Hubble Ultra Deep Field and surrounding GOODS-South. The multi-object spectra presented here are the deepest so far obtained with JWST, amounting to up to 28 hours in the low-dispersion ($R\sim 30-300$) prism, and up to 7 hours in each of the three medium-resolution $R\approx 1000$ gratings and one high-dispersion grating, G395H ($R\approx2700$). Our low-dispersion and medium-dispersion spectra cover the wavelength range $0.6-5.3\mu$m. We describe the selection of the spectroscopic targets, the strategy for the allocation of targets to micro-shutters, and the design of the observations. We present the public release of the reduced 2D and 1D spectra, and a description of the reduction and calibration process. We measure spectroscopic redshifts for 178 of the objects targeted extending up to $z=13.2$. We present a catalog of all emission lines detected at $S/N>5$, and our redshift determinations for the targets. Combined with the first JADES NIRCam data release, these public JADES spectroscopic and imaging datasets provide a new foundation for discoveries of the infrared universe by the worldwide scientific community., Comment: Accepted for publication in A&A. Data products available from https://archive.stsci.edu/hlsp/jades