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This report presents the findings of a NIAC Phase I feasibility study for the Artemis-enabled Stellar Imager (AeSI), a proposed high-resolution, UV/Optical interferometer designed for deployment on the lunar surface. Its primary science goal is to image the surfaces and interiors of stars with unprecedented detail, revealing new details about their magnetic processes and dynamic evolution and enabling the creation of a truly predictive solar/stellar dynamo model. This capability will transform our understanding of stellar physics and has broad applicability across astrophysics, from resolving the cores of Active Galactic Nuclei (AGN) to studying supernovae, planetary nebulae, and the late stages of stellar evolution. By leveraging the stable vacuum environment of the Moon and the infrastructure being established for the Artemis Program, AeSI presents a compelling case for a lunar-based interferometer. In this study, the AeSI Team, working with the NASA Goddard Space Flight Center's Integrated Design Center (IDC), has firmly established the feasibility of building and operating a reconfigurable, dispersed aperture telescope (i.e., an interferometer) on the lunar surface. The collaboration produced a credible Baseline design featuring 15 primary mirrors arranged in an elliptical array with a 1 km major axis, with the potential to expand to 30 mirrors and larger array sizes through staged deployments. Additionally, this study identified numerous opportunities for optimization and the necessary trade studies to refine the design further. These will be pursued in follow-up investigations, such as a NIAC Phase II study, to advance the concept toward implementation., Comment: 128 pages, 59 figures

Maintaining a balanced diet is essential for overall health, yet many individuals struggle with meal planning due to nutritional complexity, time constraints, and lack of dietary knowledge. Personalized food recommendations can help address these challenges by tailoring meal plans to individual preferences, habits, and dietary restrictions. However, existing dietary recommendation systems often lack adaptability, fail to consider real-world constraints such as food ingredient availability, and require extensive user input, making them impractical for sustainable and scalable daily use. To address these limitations, we introduce NutriGen, a framework based on large language models (LLM) designed to generate personalized meal plans that align with user-defined dietary preferences and constraints. By building a personalized nutrition database and leveraging prompt engineering, our approach enables LLMs to incorporate reliable nutritional references like the USDA nutrition database while maintaining flexibility and ease-of-use. We demonstrate that LLMs have strong potential in generating accurate and user-friendly food recommendations, addressing key limitations in existing dietary recommendation systems by providing structured, practical, and scalable meal plans. Our evaluation shows that Llama 3.1 8B and GPT-3.5 Turbo achieve the lowest percentage errors of 1.55\% and 3.68\%, respectively, producing meal plans that closely align with user-defined caloric targets while minimizing deviation and improving precision. Additionally, we compared the performance of DeepSeek V3 against several established models to evaluate its potential in personalized nutrition planning.

In this paper, $\beta^-$ and $\beta$-delayed neutron decays of $^{46,47}$Cl are reported from an experiment carried out at the National Superconducting Cyclotron Laboratory using the Beta Counting System. The half-lives of both $^{46}$Cl and $^{47}$Cl were extracted. Based on the delayed $\gamma$-ray transitions observed, the level structure of $N = 28$ $^{46}$Ar was determined. Completely different sets of excited states above the first $2^+$ state in $^{46}$Ar were populated in the $^{46}$Cl $\beta0n$ and $^{47}$Cl $\beta1n$ decay channels. Two new $\gamma$-ray transitions in $^{47}$Ar were identified from the very weak $^{47}$Cl $\beta0n$ decay. Furthermore, $^{46}$Cl $\beta1n$ and $^{47}$Cl $\beta2n$ were also observed to yield different population patterns for levels in $^{45}$Ar, including states of different parities. The experimental results allow us to address some of the open questions related to the delayed neutron emission process. For isotopes with large neutron excess and high $Q_{\beta}$ values, delayed neutron emission remains an important decay mode and can be utilized as a powerful spectroscopic tool. Experimental results were compared with shell-model calculations using the FSU and $V_{MU}$ effective interactions.

One of the instruments aboard the Sunrise III mission, the Tunable Magnetograph (TuMag), is a tunable imaging spectropolarimeter in visible wavelengths. It is designed to probe the vector magnetic field and the line-of-sight velocity of the photosphere and the lower chromosphere. The quasi-simultaneous observation of two spectral lines provides excellent diagnostic measurements of the magnetic and dynamic coupling in these layers. The key technologies employed for TuMag are an LCVR-based polarimeter and a solid, LiNbO3 Fabry-P\'erot etalon as a spectrometer. However, it also incorporates several innovative features, such as home-made high-sensitivity scientific cameras and a double filter wheel. TuMag can sequentially observe any two out of the three spectral lines of Fe I at 525.02 and 525.06 nm and of Mg I at 517.3 nm. Laboratory measurements have demonstrated outstanding performance, including a wavefront root-mean-square error better than {\lambda}/13 for image quality, a full-width-at-half-maximum of 8.7 pm for the filtergraph transmission profile, and polarimetric efficiencies > 0.54. Here we report on the concept, design, calibration, and integration phases of the instrument, as well as on the data reduction pipeline., Comment: Contains 58 pages and 25 figures; to be published in Solar Physics Topical Collection "The Sunrise III Solar Observatory" (https://link.springer.com/collections/jegdciedig)

In July 2024, Sunrise completed its third successful science flight. The Sunrise III observatory had been upgraded significantly after the two previous successful flights in 2009 and 2013. Three completely new instruments focus on the small-scale physical processes and their complex interaction from the deepest observable layers in the photosphere up to chromospheric heights. Previously poorly explored spectral regions and lines are exploited to paint a three-dimensional picture of the solar atmosphere with unprecedented completeness and level of detail. The full polarimetric information is captured by all three instruments to reveal the interaction between the magnetic fields and the hydrodynamic processes. Two slit-based spectropolarimeters, the Sunrise UV Spectropolarimeter and Imager (SUSI) and the Sunrise Chromospheric Infrared spectro-Polarimeter (SCIP), focus on the near-ultraviolet and the near-infrared regions respectively, and the imaging spectropolarimeter Tunable Magnetograph (TuMag) simultaneously obtains maps of the full field-of-view of $46 \times 46$ Mm$^2$ in the photosphere and the chromosphere in the visible. The instruments are operated in an orchestrated mode, benefiting from a new Image Stabilization and Light Distribution unit (ISLiD), with the Correlating Wavefront Sensor (CWS) providing the autofocus control and an image stability with a root-mean-square value smaller than 0.005''. A new gondola was constructed to significantly improve the telescope pointing stability, required to achieve uninterrupted observations over many hours. Sunrise III was launched successfully on July 10, 2024, from the Esrange Space Center near Kiruna (Sweden). It reached the landing site between the Mackenzie River and the Great Bear Lake in Canada after a flight duration of 6.5 days. In this paper, we give an overview of the Sunrise III observatory and its instruments., Comment: 67 pages, 25 figures; to be published in Solar Physics Topical Collection "The Sunrise III Solar Observatory" (https://link.springer.com/collections/jegdciedig)

In this work, we introduce the No-Underrun Sampler (NURS), a locally-adaptive, gradient-free Markov chain Monte Carlo method that blends ideas from Hit-and-Run and the No-U-Turn Sampler. NURS dynamically adapts to the local scale of the target distribution without requiring gradient evaluations, making it especially suitable for applications where gradients are unavailable or costly. We establish key theoretical properties, including reversibility, formal connections to Hit-and-Run and Random Walk Metropolis, Wasserstein contraction comparable to Hit-and-Run in Gaussian targets, and bounds on the total variation distance between the transition kernels of Hit-and-Run and NURS. Empirical experiments, supported by theoretical insights, illustrate the ability of NURS to sample from Neal's funnel, a challenging multi-scale distribution from Bayesian hierarchical inference., Comment: 37 pages

Multi-plane light converters (MPLCs) - also known as linear diffractive neural networks - are an emerging optical technology, capable of converting an orthogonal set of optical fields into any other orthogonal set via a unitary transformation. MPLC design is a non-linear problem typically solved by optimising a digital model of the optical system. However, inherently high levels of design complexity mean that even a minor mismatch between this digital model and the physically realised MPLC leads to a severe reduction in real-world performance. Here we address this challenge by creating a self-configuring free-space MPLC. Despite the large number of parameters to be optimised (typically tens of thousands or more), our proof-of-principle device converges in minutes using a method in which light only needs to be transmitted in one direction through the MPLC. Two innovations make this possible. Firstly, we devise an in-situ optimisation algorithm combining wavefront shaping with the principles of wavefront matching that would conventionally be used to inverse-design MPLCs offline in simulation. Secondly, we introduce a new MPLC platform incorporating a microelectromechanical system (MEMS) phase-only light modulator - allowing rapid MPLC switching at up to kiloHertz rates. Our scheme automatically accounts for the physical characteristics of all system components and absorbs any unknown misalignments and aberrations into the final design. We demonstrate self-configured MPLCs capable of mapping random orthogonal speckle input fields to well-defined Laguerre-Gaussian and Hermite-Gaussian output modes, as well as universal mode sorters. Our work paves the way towards large-scale ultra-high-fidelity fast-switching MPLCs and diffractive neural networks, which promises to unlock new applications in areas ranging from optical communications to optical computing and imaging., Comment: 14 pages, 7 figures, 1 table

We experimentally demonstrate high-dimensional, polarization-resolved, 3D spatiotemporal toroidal beams delivered through a multimode optical fiber (MMF). Our approach leverages advanced spectral and spatial shaping techniques, combined with full polarization control, to achieve precise manipulation of the amplitude, phase, and polarization of toroidal beams. These beams feature highly customizable 3D geometries, allowing independent control of their aspect ratio and orientation. We demonstrate the ability to deliver complex toroidal beams directly at the multimode fiber output, enabling beam rotations about any 3D spatiotemporal axis and the generation of beams with specific orbital angular momentum orientations. Our work establishes a platform for creating and delivering arbitrary toroidal beams, offering new tools for exploring light-matter interactions and pushing the boundaries of ultrafast photonics science and technology., Comment: 4 figs

Planetesimal belts are ubiquitous around nearby stars, and their spatial properties hold crucial information for planetesimal and planet formation models. We present resolved dust observations of 74 planetary systems as part of the REsolved ALMA and SMA Observations of Nearby Stars (REASONS) survey and archival reanalysis. We uniformly modelled interferometric visibilities for the entire sample to obtain the basic spatial properties of each belt, and combined these with constraints from multi-wavelength photometry. We report key findings from a first exploration of this legacy dataset: (1) Belt dust masses are depleted over time in a radially dependent way, with dust being depleted faster in smaller belts, as predicted by collisional evolution. (2) Most belts are broad discs rather than narrow rings, with much broader fractional widths than rings in protoplanetary discs. We link broad belts to either unresolved substructure or broad planetesimal discs produced if protoplanetary rings migrate. (3) The vertical aspect ratios (h = H/R) of 24 belts indicate orbital inclinations of 1-20 degrees, implying relative particle velocities of 0.1-4 km/s, and no clear evolution of heights with system age. This could be explained by early stirring within the belt by large bodies (with sizes of at least 140 km to the size of the Moon), by inheritance of inclinations from the protoplanetary disc stage, or by a diversity in evolutionary pathways and gravitational stirring mechanisms. We release the REASONS legacy multidimensional sample of millimetre-resolved belts to the community as a valuable tool for follow-up multi-wavelength observations and population modelling studies., Comment: Published in A&A, 693, A151. 27 pages, 15 figures, 3 tables

We explore an AIM Photonics silicon-nitride platform to fabricate photonic-crystal resonators for generating optical parametric oscillators (OPO) and soliton microcombs. Our approach leverages the scalability and fine feature size of silicon-nitride processing on large-scale silicon wafers to achieve low-loss, high-Q microresonators, functionalized by nano-scale photonic-crystal structures. We demonstrate intrinsic microresonator quality factor up to 1.2*10^7 with complete foundry fabrication on 300 mm silicon, a 700 nm thick silicon-nitride device layer, and inclusion of complex nanophotonics. These features enable a host of nonlinear nanophotonics sources on the platform, including OPOs, microcombs, parametric amplifiers, squeezed-light generators, and single-photon sources. By fine-tuning the photonic-crystal design parameters, we achieve broad tunability in the frequency of the OPO output, spanning a significant portion of the near-infrared. Additionally, we observe the formation of soliton frequency combs, enabled by the precise dispersion engineering of the microresonators. These results highlight the potential of widely accessible, photolithographically patterned, silicon-nitride photonics to enable wide access to and complex integration of frequency-comb sources, with applications in spectroscopy, metrology, and communications.

We explore models where single new exotic states interact with the Standard Model through an asymmetric Standard Model portal with couplings to at least one quark and one lepton. We write down all effective operators up to dimension six where such interactions couple the SM to spin 0 and spin 1/2 particles. We identify the exotic states accessible through the portal and find the interactions couple the SM to new particles with exotic combinations of baryon and lepton number, and particles with unusual SM charge, including states in higher dimensional representations of both SU(3) and SU(2), and states of higher electric charge. We discuss the phenomenology of these interactions including novel particle decays, and we classify some of the collider production modes for exotic states at LHC, LHeC and the muon collider., Comment: 30 pages 10 figures 25 tables

We study a novel production and decay mechanism for a bi-adjoint spin zero particle in the (8,3,0) representation of the Standard Model gauge groups. This work is part of a series studying new production processes for exotic particles in higher representations of Standard Model color and weak charge. We study a new dimension 5 effective operator model which couples an exotic bi-adjoint scalar field to the SU(3) and SU(2) field strength tensors. We explore the W-gluon resonant decay of the charged component of this new exotic field. We discuss LHC production modes of the charged and neutral bi-adjoint state and find a new single production mode for the charged state that is the dominant LHC production mode for TeV-scale masses. We introduce a new HL-LHC search in this asymmetric W-gluon fusion process in which a single bi-adjoint is produced in association with a hard forward quark jet. We have 5 sigma discovery potential for bi-adjoint masses up to 3 TeV for 10 TeV scalar effective operator cutoffs. We also find 2 sigma sensitivity of HL-LHC for bi-adjoint masses up to 4 TeV and effective cut-offs in the 15 TeV range for the full 3 inverse atto-barn data set., Comment: 19 pages 13 figures 3 tables

We measure the average spin of $^{144}$Ba, a common fragment produced in $^{252}$Cf(sf), as a function of the total kinetic energy (TKE). We combined for the first time a twin Frisch-gridded ionization chamber with a world-class $\gamma$-ray spectrometer that was designed to measure high-multiplicity $\gamma$-ray events, Gammasphere. The chamber, loaded with a $^{252}$Cf(sf) source, provides a fission trigger, the TKE of the fragments, the approximate fragment masses, and the polar angle of the fission axis. Gammasphere provides the total $\gamma$-ray yield, fragment identification through the tagging of decay $\gamma$ rays, and the feeding of rotational bands in the fragments. We determine the dependence of the average spin of $^{144}$Ba on the fragments' TKE by correlating the fragment properties with the distribution of discrete levels that are fed. We find that the average spin only changes by about $0.5$ $\hbar$ across the TKE range of 158-203 MeV. The virtual independence of the spin on TKE suggests that spin is not solely generated through the statistical excitation of rotational modes, and more complex mechanisms are required., Comment: Accepted for publication in Phys. Rev. C

The James Webb Space Telescope (JWST) has recently discovered a new population of objects at high redshift referred to as `Little Red Dots' (LRDs). Their nature currently remains elusive, despite their surprisingly high inferred number densities. This emerging population of red point-like sources is reshaping our view of the early Universe and may shed light on the formation of high-redshift supermassive black holes. Here we present a spectroscopically confirmed LRD CANUCS-LRD-z8.6 at $z_{\rm spec}=8.6319\pm 0.0005$ hosting an Active Galactic Nucleus (AGN), using JWST data. This source shows the typical spectral shape of an LRD (blue UV and red optical continuum, unresolved in JWST imaging), along with broad H$\beta$ line emission, detection of high-ionization emission lines (CIV, NIV]) and very high electron temperature indicative of the presence of AGN. This is also combined with a very low metallicity ($Z<0.1 Z_\odot$). The presence of all these diverse features in one source makes CANUCS-LRD-z8.6 unique. We show that the inferred black hole mass of CANUCS-LRD-z8.6 ($M_{\rm BH}=1.0^{+0.6}_{-0.4}\times 10^{8}\rm ~M_\odot$) strongly challenges current standard theoretical models and simulations of black hole formation, and forces us to adopt `ad hoc' prescriptions. Indeed if massive seeds, or light seeds with super-Eddington accretion, are considered, the observed BH mass of CANUCS-LRD-z8.6 at $z=8.6$ can be reproduced. Moreover, the black hole is over-massive compared to its host, relative to the local $M_{\rm BH}-M_*$ relations, pointing towards an earlier and faster evolution of the black hole compared to its host galaxy., Comment: 4 main figures; 8 supplementary figures; 5 supplementary tables

Field emission can cause significant problems in superconducting radio-frequency linear accelerators (linacs). When cavity gradients are pushed higher, radiation levels within the linacs may rise exponentially, causing degradation of many nearby systems. This research aims to utilize machine learning with uncertainty quantification to predict radiation levels at multiple locations throughout the linacs and ultimately optimize cavity gradients to reduce field emission induced radiation while maintaining the total linac energy gain necessary for the experimental physics program. The optimized solutions show over 40% reductions for both neutron and gamma radiation from the standard operational settings., Comment: 14 pages, 6 figures, 10 tables

Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-Objective Optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithm (GA), have been leveraged for many optimization problems, however, they do not apply to complex control problems by design. This paper demonstrates the power of differentiability for solving MOO problems using a Deep Differentiable Reinforcement Learning (DDRL) algorithm in particle accelerators. We compare DDRL algorithm with Model Free Reinforcement Learning (MFRL), GA and Bayesian Optimization (BO) for simultaneous optimization of heat load and trip rates in the Continuous Electron Beam Accelerator Facility (CEBAF). The underlying problem enforces strict constraints on both individual states and actions as well as cumulative (global) constraint for energy requirements of the beam. A physics-based surrogate model based on real data is developed. This surrogate model is differentiable and allows back-propagation of gradients. The results are evaluated in the form of a Pareto-front for two objectives. We show that the DDRL outperforms MFRL, BO, and GA on high dimensional problems.

Quantifying the global reach of planetarium dome shows presents significant challenges due to the lack of standardized viewership tracking mechanisms across diverse planetarium venues. We present an analysis of the global impact of dome shows, presenting data regarding four documentary films from a single visualization lab. Specifically, we designed and administered a viewership survey of four long-running shows that contained cinematic scientific visualizations. Reported survey data shows that between 1.2 - 2.6 million people have viewed these four films across the 68 responding planetariums (mean: 1.9 million). When we include estimates and extrapolate for the 315 planetariums that licensed these shows, we arrive at an estimate of 16.5 - 24.1 million people having seen these films (mean: 20.3 million).

We present ALMA Band 7 continuum (340 GHz) and CO J=3-2 observations for an extended sample of disks in the Upper Scorpius OB Association (Upper Sco, age ~ 10 Myr). The targets were selected from previous studies that identified new members of Upper Sco using photometry and astrometry from the Gaia mission, and the presence of a disk has been inferred from mid-infrared excess emission. The new ALMA observations are combined with previous ALMA data to define a sample of 202 Upper Sco members with disks that have spectral types between G0 and M5.5. Among these sources, 120 (59%) have been detected in the continuum with a signal-to-noise ratio >= 3, and 83 (41%) have been detected in CO J=3-2. Both the continuum and CO J=3-2 fluxes show a strong correlation with the spectral type of the central star and the type of disk inferred from the shape of the infrared spectral energy distribution, where disks around earlier type stars and full disks are more luminous than disks around later type stars and evolved and debris disks. The median dust continuum luminosity is lower for disks in Upper Sco than in younger regions, as found in previous studies, where the differences are more pronounced in later spectral types (M4-M5) than in earlier spectral types., Comment: Accepted for publication in ApJ; 53 pages, 13 figures

Efficiently retrieving and synthesizing information from large-scale multimodal collections has become a critical challenge. However, existing video retrieval datasets suffer from scope limitations, primarily focusing on matching descriptive but vague queries with small collections of professionally edited, English-centric videos. To address this gap, we introduce $\textbf{MultiVENT 2.0}$, a large-scale, multilingual event-centric video retrieval benchmark featuring a collection of more than 218,000 news videos and 3,906 queries targeting specific world events. These queries specifically target information found in the visual content, audio, embedded text, and text metadata of the videos, requiring systems leverage all these sources to succeed at the task. Preliminary results show that state-of-the-art vision-language models struggle significantly with this task, and while alternative approaches show promise, they are still insufficient to adequately address this problem. These findings underscore the need for more robust multimodal retrieval systems, as effective video retrieval is a crucial step towards multimodal content understanding and generation.

The increasing volume of papers and proposals that undergo peer review emphasizes the pressing need for greater automation to effectively manage the growing scale. In this study, we present the deployment and evaluation of machine learning and optimization techniques to assign proposals to reviewers that were developed for the Atacama Large Millimeter/submillimeter Array (ALMA) during the Cycle 10 Call for Proposals issued in 2023. Using topic modeling algorithms, we identify the proposal topics and assess reviewers' expertise based on their previous ALMA proposal submissions. We then apply an adapted version of the assignment optimization algorithm from PeerReview4All (Stelmakh et al. 2021) to maximize the alignment between proposal topics and reviewer expertise. Our evaluation shows a significant improvement in matching reviewer expertise: the median similarity score between the proposal topic and reviewer expertise increased by 51 percentage points compared to the previous cycle, and the percentage of reviewers reporting expertise in their assigned proposals rose by 20 percentage points. Furthermore, the assignment process proved highly effective in that no proposals required reassignment due to significant mismatches, resulting in a savings of 3 to 5 days of manual effort., Comment: 16 pages, 5 figures, revised version accepted by PASP

We explore models where new light exotic states interact with the Standard Model through an asymmetric di-boson portal with one gluon and one W boson. We consider the complete set of effective operators up to dimension 6 which couple a single light exotic (LEX) state to at least one W boson and 1 gluon. Other Standard Model particles may also be present in the interactions. We discover that the W-gluon portal allows us to access a large array of exotic states in non-trivial representations of SU(3) and SU(2). We discuss new single production collider modes and phenomenological signatures for these light exotic states at LHC and e-p colliders., Comment: 29 pages, 16 figures, 9 tables

The advancement of robotic systems has revolutionized numerous industries, yet their operation often demands specialized technical knowledge, limiting accessibility for non-expert users. This paper introduces ROSA (Robot Operating System Agent), an AI-powered agent that bridges the gap between the Robot Operating System (ROS) and natural language interfaces. By leveraging state-of-the-art language models and integrating open-source frameworks, ROSA enables operators to interact with robots using natural language, translating commands into actions and interfacing with ROS through well-defined tools. ROSA's design is modular and extensible, offering seamless integration with both ROS1 and ROS2, along with safety mechanisms like parameter validation and constraint enforcement to ensure secure, reliable operations. While ROSA is originally designed for ROS, it can be extended to work with other robotics middle-wares to maximize compatibility across missions. ROSA enhances human-robot interaction by democratizing access to complex robotic systems, empowering users of all expertise levels with multi-modal capabilities such as speech integration and visual perception. Ethical considerations are thoroughly addressed, guided by foundational principles like Asimov's Three Laws of Robotics, ensuring that AI integration promotes safety, transparency, privacy, and accountability. By making robotic technology more user-friendly and accessible, ROSA not only improves operational efficiency but also sets a new standard for responsible AI use in robotics and potentially future mission operations. This paper introduces ROSA's architecture and showcases initial mock-up operations in JPL's Mars Yard, a laboratory, and a simulation using three different robots. The core ROSA library is available as open-source., Comment: Preprint. Accepted at IEEE Aerospace Conference 2025, 16 pages, 12 figures

How are we able to learn about complex current events just from short snippets of video? While natural language enables straightforward ways to represent under-specified, partially observable events, visual data does not facilitate analogous methods and, consequently, introduces unique challenges in event understanding. With the growing prevalence of vision-capable AI agents, these systems must be able to model events from collections of unstructured video data. To tackle robust event modeling in multimodal settings, we introduce a multimodal formulation for partially-defined events and cast the extraction of these events as a three-stage span retrieval task. We propose a corresponding benchmark for this task, MultiVENT-G, that consists of 14.5 hours of densely annotated current event videos and 1,168 text documents, containing 22.8K labeled event-centric entities. We propose a collection of LLM-driven approaches to the task of multimodal event analysis, and evaluate them on MultiVENT-G. Results illustrate the challenges that abstract event understanding poses and demonstrates promise in event-centric video-language systems., Comment: Preprint; 9 pages; 2024 EMNLP Findings