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We consider the momentum formulation of the two-dimensional surface quasi-geostrophic equations forced by random noise, of both additive and linear multiplicative types. For any prescribed deterministic function under some conditions, we construct solutions to each system whose energy is the fixed function. Consequently, we prove non-uniqueness of almost sure Markov selections of suitable class of weak solutions associated to the momentum surface quasi-geostrophic equations in both cases of noise.

We introduce and study the pinnacle sets of a simple graph $G$ with $n$ vertices. Given a bijective vertex labeling $\lambda\,:\,V(G)\rightarrow [n]$, the label $\lambda(v)$ of vertex $v$ is a pinnacle of $(G, \lambda)$ if $\lambda(v)>\lambda(w)$ for all vertices $w$ in the neighborhood of $v$. The pinnacle set of $(G, \lambda)$ contains all the pinnacles of the labeled graph. A subset $S\subseteq[n]$ is a pinnacle set of $G$ if there exists a labeling $\lambda$ such that $S$ is the pinnacle set of $(G,\lambda)$. Of interest to us is the question: Which subsets of $[n]$ are the pinnacle sets of $G$? Our main results are as follows. We show that when $G$ is connected, $G$ has a size-$k$ pinnacle set if and only if $G$ has an independent set of the same size. Consequently, determining if $G$ has a size-$k$ pinnacle set and determining if $G$ has a particular subset $S$ as a pinnacle set are NP-complete problems. Nonetheless, we completely identify all the pinnacle sets of complete graphs, complete bipartite graphs, cycles and paths. We also present two techniques for deriving new pinnacle sets from old ones that imply a typical graph has many pinnacle sets. Finally, we define a poset on all the size-$k$ pinnacle sets of $G$ and show that it is a join semilattice. If, additionally, the poset has a minimum element, then it is a distributive lattice. We conclude with some open problems for further study.

We present our findings from the new deep Chandra observations ($256$ ks) of the merging galaxy cluster SPT-CL J2031-4037 at $z = 0.34$. Our observations reveal intricate structures seen in a major merger akin to the Bullet Cluster. The X-ray data confirm the existence of two shock fronts, one to the northwest and one to the southeast by directly measuring the temperature jump of gas across the surface brightness edges. The stronger shock front in the northwest has a density jump of $3.16 \pm 0.34$ across the sharp surface brightness edge and Mach number $M = 3.36^{+0.87}_{-0.48}$, which makes this cluster one of the rare merging systems with a Mach number $M > 2$. We use the northwestern shock to compare two models for shock heating - the instant heating model and the Coulomb collisional heating model, and we determine that the temperatures across the shock front agree with the Coulomb collisional model of heating. For the shock front in the southeastern region, we find a density jump of $1.53 \pm 0.14$ and a Mach number of $M = 1.36 ^{+0.09}_{-0.08}$., Comment: Accepted for publication in ApJ

Cosmological parameters such as $\Omega_{\rm{M}}$ and $\sigma_{8}$ can be measured indirectly using various methods, including galaxy cluster abundance and cosmic shear. These measurements constrain the composite parameter $S_{8}$, leading to degeneracy between $\Omega_{\rm{M}}$ and $\sigma_{8}$. However, some structural properties of galaxy clusters also correlate with cosmological parameters, due to their dependence on a cluster's accretion history. In this work, we focus on the splashback radius, an observable cluster feature that represents a boundary between a cluster and the surrounding Universe. Using a suite of cosmological simulations with a range of values for $\Omega_{\rm{M}}$ and $\sigma_{8}$, we show that the position of the splashback radius around cluster-mass halos is greater in cosmologies with smaller values of $\Omega_{\rm{M}}$ or larger values of $\sigma_{8}$. This variation breaks the degeneracy between $\Omega_{\rm{M}}$ and $\sigma_{8}$ that comes from measurements of the $S_{8}$ parameter. We also show that this variation is, in principle, measurable in observations. As the splashback radius can be determined from the same weak lensing analysis already used to estimate $S_{8}$, this new approach can tighten low-redshift constraints on cosmological parameters, either using existing data, or using upcoming data such as that from Euclid and LSST., Comment: 12 pages, 7 figures, 1 table, accepted for publication in ApJ

Ranges of the real-valued parameters $\alpha$, $a$, $b$, and $m$ are identified for which the operator $$\mathcal{A}_{\alpha}(a,b)f(x):=x^\alpha\left(f''(x)+\frac{a}{x}f'(x)+\frac{b}{x^2}f(x)\right), \quad x>0,$$ generates an analytic semigroup in $L_1((0,\infty),x^m\mathrm{d}x)$.

The Fred Young Submillimeter Telescope (FYST), on Cerro Chajnantor in the Atacama desert of Chile, will conduct wide-field and small deep-field surveys of the sky with more than 100,000 detectors on the Prime-Cam instrument. Kinetic inductance detectors (KIDs) were chosen as the primary sensor technology for their high density focal plane packing. Additionally, they benefit from low cost, ease of fabrication, and simplified cryogenic readout, which are all beneficial for successful deployment at scale. The cryogenic multiplexing complexity is pulled out of the cryostat and is instead pushed into the digital signal processing of the room temperature electronics. Using the Xilinx Radio Frequency System on a Chip (RFSoC), a highly multiplexed KID readout was developed for the first light Prime-Cam and commissioning Mod-Cam instruments. We report on the performance of the RFSoC-based readout with multiple detector arrays in various cryogenic setups. Specifically we demonstrate detector noise limited performance of the RFSoC-based readout under the expected optical loading conditions., Comment: draft submitted to SPIE

Revealing the quantum properties of matter requires a high degree of experimental control accompanied by a profound theoretical understanding. At ultracold temperatures, quantities that appear continuous in everyday life, such as the motional angular momentum of two colliding particles, become quantized, leaving a measurable imprint on experimental results. Embedding a single particle within a larger quantum bath at lowest temperatures can result in resonant partial-wave dependent interaction, whose strength near zero energy is dictated by universal threshold scaling laws. Hybrid atom-ion systems have emerged as a novel platform in which a single charged atom in an ultracold bath serves as a well-controlled impurity of variable energy. However, entering the low-energy s-wave regime and exploring the role of higher-partial-wave scattering within has remained an open challenge. Here, we immerse a Barium ion in a cloud of ultracold spin-polarized Lithium atoms, realize tunable collision energies below the s-wave limit and explore resonant higher-partial-wave scattering by studying the energy dependence of Feshbach resonances. Utilizing precise electric field control, we tune the collision energy over four orders of magnitude, reaching from the many-parital-wave to the s-wave regime. At the lowest energies, we probe the energy dependence of an isolated s-wave Feshbach resonance and introduce a theoretical model that allows to distinguish it from higher-partial-wave resonances. Additionally, at energies around the p-wave barrier, we find and identify an open-channel f-wave resonance, consistent with threshold laws. Our findings highlight and benchmark the importance of higher-partial-wave scattering well within the s-wave regime and offer control over chemical reactions and complex many-body dynamics in atom-ion ensembles - on the level of individual angular momentum quanta.

Several sources of repeating coherent bursts of radio emission with periods of many minutes have now been reported in the literature. These "ultra-long period" (ULP) sources have no clear multi-wavelength counterparts and challenge canonical pulsar emission models, leading to debate regarding their nature. In this work we report the discovery of a bright, highly-polarised burst of radio emission at low Galactic latitude as part of a wide-field survey for transient and variable radio sources. ASKAP\,J175534.9$-$252749.1 does not appear to repeat, with only a single intense two-minute $\sim$200-mJy burst detected from 60~hours of observations. The burst morphology and polarisation properties are comparable to those of classical pulsars but the duration is more than one hundred times longer, analogous to ULPs. Combined with the existing ULP population, this suggests that these sources have a strong Galactic latitude dependence and hints at an unexplored population of transient and variable radio sources in the thin disk of the Milky Way. The resemblance of this burst with both ULPs and pulsars calls for a unified coherent emission model for objects with spin periods from milliseconds to tens of minutes. However, whether or not these are all neutron stars or have the same underlying power source remains open for debate.

Assembly theory (AT) quantifies selection using the assembly equation and identifies complex objects that occur in abundance based on two measurements, assembly index and copy number, where the assembly index is the minimum number of joining operations necessary to construct an object from basic parts, and the copy number is how many instances of the given object(s) are observed. Together these define a quantity, called Assembly, which captures the amount of causation required to produce objects in abundance in an observed sample. This contrasts with the random generation of objects. Herein we describe how AT's focus on selection as the mechanism for generating complexity offers a distinct approach, and answers different questions, than computational complexity theory with its focus on minimum descriptions via compressibility. To explore formal differences between the two approaches, we show several simple and explicit mathematical examples demonstrating that the assembly index, itself only one piece of the theoretical framework of AT, is formally not equivalent to other commonly used complexity measures from computer science and information theory including Shannon entropy, Huffman encoding, and Lempel-Ziv-Welch compression. We also include proofs that assembly index is not in the same computational complexity class as these compression algorithms and discuss fundamental differences in the ontological basis of AT, and assembly index as a physical observable, which distinguish it from theoretical approaches to formalizing life that are unmoored from measurement., Comment: 38 pages, 4 figures, 1 table, and 91 references plus supplement with proof of assembly index computational class

We present an analysis of high-resolution optical spectra recorded for 30 stars of the split extended main-sequence turnoff (eMSTO) of the young ($\sim$ 40 Myr) Small Magellanic Cloud (SMC) globular cluster NGC 330. Spectra were obtained with the M2FS and MIKE spectrographs located on the Magellan-Clay 6.5m telescope. These spectra revealed the presence of Be stars, occupying primarily the cool side of the split main sequence (MS). Rotational velocity ($v\sin{i}$) measurements for most of the targets are consistent with the presence of two populations of stars in the cluster: one made up of rapidly rotating Be stars ($ \approx 200$ $\rm km\,s^{-1}$), and {the other} consisting of warmer stars with slower rotation ($<\!v\sin{i}\!>\approx50$ $\rm km\,s^{-1}$). Core emission in the H$\delta$ photospheric lines was observed for most of the H$\alpha$ emitters. The shell parameter computed for the targets in our sample indicate that most of the observed stars should have inclinations below 75$^{\circ}$. These results confirm the detection of Be stars obtained through photometry, but also reveal the presence of narrow H$\alpha$ and H$\delta$ features for some targets that cannot be detected with low-resolution spectroscopy or photometry. Asymmetry variability of H$\alpha$ line profiles on the timescales of a few years is also observed, and could provide information on the geometry of the decretion disks. Observations revealed the presence of nebular H$\alpha$ emission, strong enough in faint targets to compromise the extraction of spectra and to impact narrow band photometry used to assess the presence of H$\alpha$ emission., Comment: 15 pages, 13 figures, accepted for publication in The Astrophysical Journal

Due to the uncontrolled and complex real-life radio propagation environments, Claude Shannon's information theory of communications describes fundamental limits to state-of-the-art 5G radio access network (RAN) capacity, with respect to fixed radio resource usage. Fortunately, recent research has found that a holographic metasurface-based new physical layer architecture may hold the key to overcome these fundamental limits of current mobile networks under a new paradigm, smart wireless environment (SWE), where the long-standing challenge of mobile communications, fading channel hostility, may be solved, leading to a step-change boost in network performance and user experience. Despite recent research activities in SWE, the best way to implement it as a network operator remains an open challenge. In this industrial review, we adopt a novel yet realistic mobile channel stabilisation perspective for network operators to understand this paradigm shift. More specifically, we provide a technical analysis of the synergy between key next-gen mobile network enablers, e.g., holographic metasurface, wireless sensing, and machine intelligence, as well as of how this synergy leads to a robust future RAN architecture. Against the as yet unclear theoretical boundaries and low technology readiness level (TRL) of SWE enhanced telecommunications, we conclude by identifying critical challenges in future commercial deployments., Comment: This work has been submitted to the IEEE for possible publication

Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers. Accurate identification/prioritization of neoantigens is highly relevant to designing clinical trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel sequencing technologies, it is now possible to predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. While computational tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates using variant, transcript and peptide information. pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings. The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org., Comment: Supplemental tables available at 10.5281/zenodo.11534338

Artificial intelligence methods are being increasingly applied across various domains, but their often opaque nature has raised concerns about accountability and trust. In response, the field of explainable AI (XAI) has emerged to address the need for human-understandable AI systems. Evolutionary computation (EC), a family of powerful optimization and learning algorithms, offers significant potential to contribute to XAI, and vice versa. This paper provides an introduction to XAI and reviews current techniques for explaining machine learning models. We then explore how EC can be leveraged in XAI and examine existing XAI approaches that incorporate EC techniques. Furthermore, we discuss the application of XAI principles within EC itself, investigating how these principles can illuminate the behavior and outcomes of EC algorithms, their (automatic) configuration, and the underlying problem landscapes they optimize. Finally, we discuss open challenges in XAI and highlight opportunities for future research at the intersection of XAI and EC. Our goal is to demonstrate EC's suitability for addressing current explainability challenges and to encourage further exploration of these methods, ultimately contributing to the development of more understandable and trustworthy ML models and EC algorithms., Comment: 24 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:2306.14786

In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich, longitudinal data for personal health monitoring. Here we present Personal Health Large Language Model (PH-LLM), fine-tuned from Gemini for understanding and reasoning over numerical time-series personal health data. We created and curated three datasets that test 1) production of personalized insights and recommendations from sleep patterns, physical activity, and physiological responses, 2) expert domain knowledge, and 3) prediction of self-reported sleep outcomes. For the first task we designed 857 case studies in collaboration with domain experts to assess real-world scenarios in sleep and fitness. Through comprehensive evaluation of domain-specific rubrics, we observed that Gemini Ultra 1.0 and PH-LLM are not statistically different from expert performance in fitness and, while experts remain superior for sleep, fine-tuning PH-LLM provided significant improvements in using relevant domain knowledge and personalizing information for sleep insights. We evaluated PH-LLM domain knowledge using multiple choice sleep medicine and fitness examinations. PH-LLM achieved 79% on sleep and 88% on fitness, exceeding average scores from a sample of human experts. Finally, we trained PH-LLM to predict self-reported sleep quality outcomes from textual and multimodal encoding representations of wearable data, and demonstrate that multimodal encoding is required to match performance of specialized discriminative models. Although further development and evaluation are necessary in the safety-critical personal health domain, these results demonstrate both the broad knowledge and capabilities of Gemini models and the benefit of contextualizing physiological data for personal health applications as done with PH-LLM., Comment: 72 pages

Despite extensive efforts to create fairer machine learning (ML) datasets, there remains a limited understanding of the practical aspects of dataset curation. Drawing from interviews with 30 ML dataset curators, we present a comprehensive taxonomy of the challenges and trade-offs encountered throughout the dataset curation lifecycle. Our findings underscore overarching issues within the broader fairness landscape that impact data curation. We conclude with recommendations aimed at fostering systemic changes to better facilitate fair dataset curation practices., Comment: NeurIPS Datasets & Benchmarks 2024 (Oral)

We present the second data release for the GaLactic and Extragalactic All-sky Murchison Widefield Array eXtended (GLEAM-X) survey. This data release is an area of 12,892-deg^2 around the South Galactic Pole region covering 20h 40m <= RA <= 6h 40m, -90deg <= Dec <= +30deg. Observations were taken in 2020 using the Phase-II configuration of the Murchison Widefield Array (MWA) and covering a frequency range of 72-231MHz with twenty frequency bands. We produce a wideband source-finding mosaic over 170-231MHz with a median root mean squared noise of 1.5 (+1.5/-0.5) mJy beam^(-1). We present a catalogue of 624,866 components, including 562,302 components which are spectrally fit. This catalogue is 98% complete at 50mJy, and a reliability of 98.7% at a 5sigma level, consistent with expectations for this survey. The catalogue is made available via Vizier and the PASA datastore and accompanying mosaics for this data release are made available via AAO Data Central and SkyView., Comment: Accepted for publication in PASA; 24 pages, 15 figures

The CCAT Collaboration's six-meter Fred Young Submillimeter Telescope is scheduled to begin observing in the Chilean Atacama in 2025, targeting a variety of science goals throughout cosmic history. Prime-Cam is a 1.8-meter diameter cryostat that will host up to seven independent instrument modules designed for simultaneous spectroscopic and broadband, polarimetric surveys at millimeter to submillimeter wavelengths. The first of these instrument modules, the 280 GHz module, will include ${\sim}$10,000 kinetic inductance detectors (KIDs) across three arrays. While the first array was fabricated out of tri-layer TiN/Ti/TiN, the other two arrays were fabricated out of a single layer of Al. This combination of materials within the same instrument provides a unique opportunity to directly compare the performance and noise properties of two different detector materials that are seeing increasing use within the field. We present preliminary comparisons here based on lab testing, along with a discussion of the potential impacts on operation when observing and translating raw data to science-grade maps., Comment: 6 pages, 3 figures, conference proceedings submitted to the Journal of Low Temperature Physics

Assembly Theory (AT) was developed to help distinguish living from non-living systems. The theory is simple as it posits that the amount of selection or Assembly is a function of the number of complex objects where their complexity can be objectively determined using assembly indices. The assembly index of a given object relates to the number of recursive joining operations required to build that object and can be not only rigorously defined mathematically but can be experimentally measured. In pervious work we outlined the theoretical basis, but also extensive experimental measurements that demonstrated the predictive power of AT. These measurements showed that is a threshold in assembly indices for organic molecules whereby abiotic chemical systems could not randomly produce molecules with an assembly index greater or equal than 15. In a recent paper by Hazen et al [1] the authors not only confused the concept of AT with the algorithms used to calculate assembly indices, but also attempted to falsify AT by calculating theoretical assembly indices for objects made from inorganic building blocks. A fundamental misunderstanding made by the authors is that the threshold is a requirement of the theory, rather than experimental observation. This means that exploration of inorganic assembly indices similarly requires an experimental observation, correlated with the theoretical calculations. Then and only then can the exploration of complex inorganic molecules be done using AT and the threshold for living systems, as expressed with such building blocks, be determined. Since Hazen et al.[1] present no experimental measurements of assembly theory, their analysis is not falsifiable., Comment: 6 pages, 11 references

We present $griz$ photometric light curves for the full 5 years of the Dark Energy Survey Supernova program (DES-SN), obtained with both forced Point Spread Function (PSF) photometry on Difference Images (DIFFIMG) performed during survey operations, and Scene Modelling Photometry (SMP) on search images processed after the survey. This release contains $31,636$ DIFFIMG and $19,706$ high-quality SMP light curves, the latter of which contains $1635$ photometrically-classified supernovae that pass cosmology quality cuts. This sample spans the largest redshift ($z$) range ever covered by a single SN survey ($0.1

We report constraints on a variety of non-standard cosmological models using the full 5-year photometrically-classified type Ia supernova sample from the Dark Energy Survey (DES-SN5YR). Both Akaike Information Criterion (AIC) and Suspiciousness calculations find no strong evidence for or against any of the non-standard models we explore. When combined with external probes, the AIC and Suspiciousness agree that 11 of the 15 models are moderately preferred over Flat-$\Lambda$CDM suggesting additional flexibility in our cosmological models may be required beyond the cosmological constant. We also provide a detailed discussion of all cosmological assumptions that appear in the DES supernova cosmology analyses, evaluate their impact, and provide guidance on using the DES Hubble diagram to test non-standard models. An approximate cosmological model, used to perform bias corrections to the data holds the biggest potential for harbouring cosmological assumptions. We show that even if the approximate cosmological model is constructed with a matter density shifted by $\Delta\Omega_m\sim0.2$ from the true matter density of a simulated data set the bias that arises is sub-dominant to statistical uncertainties. Nevertheless, we present and validate a methodology to reduce this bias., Comment: Published to MNRAS on 20 August 2024; v2 updates to the accepted version

We present a precise measurement of cosmological time dilation using the light curves of 1504 type Ia supernovae from the Dark Energy Survey spanning a redshift range $0.1\lesssim z\lesssim 1.2$. We find that the width of supernova light curves is proportional to $(1+z)$, as expected for time dilation due to the expansion of the Universe. Assuming type Ia supernovae light curves are emitted with a consistent duration $\Delta t_{\rm em}$, and parameterising the observed duration as $\Delta t_{\rm obs}=\Delta t_{\rm em}(1+z)^b$, we fit for the form of time dilation using two methods. Firstly, we find that a power of $b \approx 1$ minimises the flux scatter in stacked subsamples of light curves across different redshifts. Secondly, we fit each target supernova to a stacked light curve (stacking all supernovae with observed bandpasses matching that of the target light curve) and find $b=1.003\pm0.005$ (stat) $\pm\,0.010$ (sys). Thanks to the large number of supernovae and large redshift-range of the sample, this analysis gives the most precise measurement of cosmological time dilation to date, ruling out any non-time-dilating cosmological models at very high significance., Comment: 14 pages, 13 figures. Updated in response to reviewer feedback. Accepted for publication in the Monthly Notices of the Royal Astronomical Society (MNRAS)

We measure the current expansion rate of the Universe, Hubble's constant $H_0$, by calibrating the absolute magnitudes of supernovae to distances measured by Baryon Acoustic Oscillations. This `inverse distance ladder' technique provides an alternative to calibrating supernovae using nearby absolute distance measurements, replacing the calibration with a high-redshift anchor. We use the recent release of 1829 supernovae from the Dark Energy Survey spanning $0.01\lt z \lt1.13$ anchored to the recent Baryon Acoustic Oscillation measurements from DESI spanning $0.30 \lt z_{\mathrm{eff}} \lt 2.33$. To trace cosmology to $z=0$, we use the third-, fourth- and fifth-order cosmographic models, which, by design, are agnostic about the energy content and expansion history of the universe. With the inclusion of the higher-redshift DESI-BAO data, the third-order model is a poor fit to both data sets, with the fourth-order model being preferred by the Akaike Information Criterion. Using the fourth-order cosmographic model, we find $H_0=67.19^{+0.66}_{-0.64}\mathrm{~km} \mathrm{~s}^{-1} \mathrm{~Mpc}^{-1}$, in agreement with the value found by Planck without the need to assume Flat-$\Lambda$CDM. However the best-fitting expansion history differs from that of Planck, providing continued motivation to investigate these tensions.

Let $A \subset \mathbb{Z}^d$ be a finite set. It is known that the sumset $NA$ has predictable size ($\vert NA\vert = P_A(N)$ for some $P_A(X) \in \mathbb{Q}[X]$) and structure (all of the lattice points in some finite cone other than all of the lattice points in a finite collection of exceptional subcones), once $N$ is larger than some threshold. In previous work, joint with Shakan, the first and third named authors established the first effective bounds for both of these thresholds for an arbitrary set $A$. In this article we substantially improve each of these bounds, coming much closer to the corresponding lower bounds known., Comment: 15 pages

Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized classical simulations based on tensor network techniques, and their limitations shed light on the improvements to quantum hardware required to frustrate classical simulability. In particular, quantum computers having in excess of $\sim 50$ qubits are primarily vulnerable to classical simulation due to restrictions on their gate fidelity and their connectivity, the latter determining how many gates are required (and therefore how much infidelity is suffered) in generating highly-entangled states. Here, we describe recent hardware upgrades to Quantinuum's H2 quantum computer enabling it to operate on up to $56$ qubits with arbitrary connectivity and $99.843(5)\%$ two-qubit gate fidelity. Utilizing the flexible connectivity of H2, we present data from random circuit sampling in highly connected geometries, doing so at unprecedented fidelities and a scale that appears to be beyond the capabilities of state-of-the-art classical algorithms. The considerable difficulty of classically simulating H2 is likely limited only by qubit number, demonstrating the promise and scalability of the QCCD architecture as continued progress is made towards building larger machines., Comment: Includes minor updates to the text and an updated author list to include researchers who made technical contributions in upgrading the machine to 56 qubits but were left off the original version by mistake

We outline the development of the readout software for the Prime-Cam and Mod-Cam instruments on the CCAT Fred Young Submillimeter Telescope (FYST), primecam_readout. The instruments feature lumped-element kinetic inductance detector (LEKID) arrays driven by Xilinx ZCU111 RFSoC boards. In the current configuration, each board can drive up to 4000 KIDs, and Prime-Cam is implementing approximately 25 boards. The software runs on a centralized control computer connected to the boards via dedicated ethernet, and facilitates such tasks as frequency-multiplexed tone comb driving, comb calibration and optimization, and detector timestream establishment. The control computer utilizes dynamically generated control channels for each board, allowing for simultaneous parallel control over all, while uniquely tracking diagnostics for each. This work demonstrates a scalable RFSoC readout architecture where computational demands increase linearly with the number of detectors, enabling control of tens-of-thousands of KIDs with modest hardware, and opening the door to the next generation of KID arrays housing millions of detectors., Comment: SPIE Astronomical Telescopes + Instrumentation conference proceedings

We propose an algebraic geometric framework to study the expressivity of linear activation neural networks. A particular quantity of neural networks that has been actively studied is the number of linear regions, which gives a quantification of the information capacity of the architecture. To study and evaluate information capacity and expressivity, we work in the setting of tropical geometry - a combinatorial and polyhedral variant of algebraic geometry - where there are known connections between tropical rational maps and feedforward neural networks. Our work builds on and expands this connection to capitalize on the rich theory of tropical geometry to characterize and study various architectural aspects of neural networks. Our contributions are threefold: we provide a novel tropical geometric approach to selecting sampling domains among linear regions; an algebraic result allowing for a guided restriction of the sampling domain for network architectures with symmetries; and a new open source OSCAR library to analyze neural networks symbolically using their tropical representations, where we present a new algorithm that computes the exact number of their linear regions. We provide a comprehensive set of proof-of-concept numerical experiments demonstrating the breadth of neural network architectures to which tropical geometric theory can be applied to reveal insights on expressivity characteristics of a network. Our work provides the foundations for the adaptation of both theory and existing software from computational tropical geometry and symbolic computation to neural networks and deep learning

The Single Aperture Large Telescope for Universe Studies (SALTUS) is a deployable space telescope designed to provide the astrophysics community with an extremely large far-infrared (far-IR) space observatory to explore our cosmic origins. The SALTUS observatory can observe thousands of faint astrophysical targets, including the first galaxies, protoplanetary disks in various evolutionary states, and a wide variety of solar system objects. The SALTUS design architecture utilizes radiatively cooled, 14-m diameter unobscured aperture, and cryogenic instruments to enable both high spectral and spatial resolution at unprecedented sensitivity over a wavelength range largely unavailable to any existing ground or space observatories. The unique SALTUS optical design, utilizing a large inflatable off-axis primary mirror, provides superb sensitivity, angular resolution, and imaging performance at far-IR wavelengths over a wide +/-0.02 x 0.02 degree Field of View. SALTUS design, with its highly compact form factor, allows it to be readily stowed in available launch fairings and subsequently deployed in orbit.

Retrieval augmented generation (RAG) provides the capability to constrain generative model outputs, and mitigate the possibility of hallucination, by providing relevant in-context text. The number of tokens a generative large language model (LLM) can incorporate as context is finite, thus limiting the volume of knowledge from which to generate an answer. We propose a two-layer RAG framework for query-focused answer generation and evaluate a proof-of-concept for this framework in the context of query-focused summary generation from social media forums, focusing on emerging drug-related information. The evaluations demonstrate the effectiveness of the two-layer framework in resource constrained settings to enable researchers in obtaining near real-time data from users.

Yoshimura origami is a classical folding pattern that has inspired many deployable structure designs. Its applications span from space exploration, kinetic architectures, and soft robots to even everyday household items. However, despite its wide usage, Yoshimura has been fixated on a set of design constraints to ensure its flat-foldability. Through extensive kinematic analysis and prototype tests, this study presents a new Yoshimura that intentionally defies these constraints. Remarkably, one can impart a unique meta-stability by using the Golden Ratio angle to define the triangular facets of a generalized Yoshimura. As a result, when its facets are strategically popped out, a ``Golden Ratio Yoshimura'' boom with $m$ modules can be theoretically reconfigured into $8^m$ geometrically unique and load-bearing shapes. This result not only challenges the existing design norms but also opens up a new avenue to create deployable and versatile structural systems.

The Single Aperture Large Telescope for Universe Studies (SALTUS) is a mission concept for a far-infrared observatory developed under the recent Astrophysics Probe Explorer opportunity from NASA. The enabling element of the program is a 14 m diameter inflatable primary mirror, M1. Due to its importance to SALTUS and potentially other space observatories, this paper focuses entirely on M1. We present a historical overview of inflatable systems, illustrating that M1 is the logical next step in the evolution of such systems. The process of design and manufacture is addressed. We examine how M1 performs in its environment in terms of operating temperature, interaction with the solar wind, and shape change due to non-penetrating particles. We investigate the longevity of the inflatant in detail and show it meets mission lifetime requirements with ample margin and discuss the development and testing to realize the flight M1., Comment: Submitted to the J. Astron. Telesc. Instrum. Syst. (JATIS), 87 pages, 36 figures, 4 tables

We explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$., Comment: 28 pages, 7 figures, 4 tables

We address the long-standing problem of how to learn effective pixel-based image diffusion models at scale, introducing a remarkably simple greedy growing method for stable training of large-scale, high-resolution models. without the needs for cascaded super-resolution components. The key insight stems from careful pre-training of core components, namely, those responsible for text-to-image alignment {\it vs.} high-resolution rendering. We first demonstrate the benefits of scaling a {\it Shallow UNet}, with no down(up)-sampling enc(dec)oder. Scaling its deep core layers is shown to improve alignment, object structure, and composition. Building on this core model, we propose a greedy algorithm that grows the architecture into high-resolution end-to-end models, while preserving the integrity of the pre-trained representation, stabilizing training, and reducing the need for large high-resolution datasets. This enables a single stage model capable of generating high-resolution images without the need of a super-resolution cascade. Our key results rely on public datasets and show that we are able to train non-cascaded models up to 8B parameters with no further regularization schemes. Vermeer, our full pipeline model trained with internal datasets to produce 1024x1024 images, without cascades, is preferred by 44.0% vs. 21.4% human evaluators over SDXL.

Training diffusion models for audiovisual sequences allows for a range of generation tasks by learning conditional distributions of various input-output combinations of the two modalities. Nevertheless, this strategy often requires training a separate model for each task which is expensive. Here, we propose a novel training approach to effectively learn arbitrary conditional distributions in the audiovisual space.Our key contribution lies in how we parameterize the diffusion timestep in the forward diffusion process. Instead of the standard fixed diffusion timestep, we propose applying variable diffusion timesteps across the temporal dimension and across modalities of the inputs. This formulation offers flexibility to introduce variable noise levels for various portions of the input, hence the term mixture of noise levels. We propose a transformer-based audiovisual latent diffusion model and show that it can be trained in a task-agnostic fashion using our approach to enable a variety of audiovisual generation tasks at inference time. Experiments demonstrate the versatility of our method in tackling cross-modal and multimodal interpolation tasks in the audiovisual space. Notably, our proposed approach surpasses baselines in generating temporally and perceptually consistent samples conditioned on the input. Project page: avdit2024.github.io

The SALTUS Probe mission will provide a powerful far-infrared (far-IR) pointed space observatory to explore our cosmic origins and the possibility of life elsewhere. The observatory employs an innovative deployable 14-m aperture, with a sunshield that will radiatively cool the off-axis primary to <45K. This cooled primary reflector works in tandem with cryogenic coherent and incoherent instruments that span the 34 to 660 micron far-IR range at both high and moderate spectral resolutions., Comment: 49 pages, 10 figures, 3 tables, submitted to SPIE JATIS

The integration of artificial intelligence (AI) into military capabilities has become a norm for major military power across the globe. Understanding how these AI models operate is essential for maintaining strategic advantages and ensuring security. This paper demonstrates an open-source methodology for analyzing military AI models through a detailed examination of the Zhousidun dataset, a Chinese-originated dataset that exhaustively labels critical components on American and Allied destroyers. By demonstrating the replication of a state-of-the-art computer vision model on this dataset, we illustrate how open-source tools can be leveraged to assess and understand key military AI capabilities. This methodology offers a robust framework for evaluating the performance and potential of AI-enabled military capabilities, thus enhancing the accuracy and reliability of strategic assessments.

Self-assembly of matter in solution generally relies on attractive interactions that overcome entropy and drive the formation of higher-order molecular and particulate structures. Such interactions play key roles in a variety of contexts, e.g., crystallisation, biomolecular folding and condensation, pathological protein aggregation, pharmaceuticals and fine chemicals. The electrosolvation force entails a new conceptual paradigm in the known palette of interactions that drive the spontaneous accretion and organisation of matter. However, an understanding of the underlying physical chemistry, and therefore the ability to exert control over and tune the interaction, remains incomplete. Here we demonstrate that this force arises from the structure of the interfacial electrolyte. Neutral molecules such as a different solvent, osmolytes or surfactants, can - even at very low concentrations in the medium - disrupt or reinforce pre-existing interfacial solvent structure, thereby furnishing unanticipated chemical tuning of the ability of matter to self-assemble. The observations further present unexpected mechanistic elements that may explain the impact of co-solvents and osmolytes on protein structure, stability and pathological protein condensation. Our findings shed new light on microscopic mechanisms that drive the emergence of order and structure from molecular to macroscopic scales in the solution phase.

The energy coupling efficiency of active galactic nucleus (AGN) outbursts is known to differ significantly with factors including the jet kinetic power, duration of the outburst, and properties of the host galaxy cluster. As such, constraints on their jet power and lifetime functions are crucial to quantify the role of kinetic-mode AGN feedback on the evolution of galaxies since $z \sim 1$. In this work, we address this issue by measuring the energetics of a sample of 79 low-redshift (0.02 $< z <$ 0.2) remnant radio galaxies compiled from large-sky radio surveys - these objects uniquely probe the full duration of an AGN outburst. The jet kinetic power and outburst duration of each remnant are determined using the RAiSE dynamical model based on the surface brightness distribution observed in multi-frequency radio images. We compare the energetics constrained for this sample to those predicted for mock radio source populations - with various intrinsic functions for jet power and lifetime distributions - to correct for sample selection biases imposed on our sample. The intrinsic jet power and lifetime functions that yield a selection-biased mock population most similar to our observed sample are found using Bayesian inference. Our analysis places robust constraints on assumed power-law indices for the intrinsic jet power and lifetime functions: $p(Q)\propto Q^{-1.49\pm0.07}$ and $p(t_{\mathrm{on}})\propto t_{\mathrm{on}}^{-0.97\pm0.12}$ respectively. We discuss the implication of these findings for feedback-regulated accretion and the self-regulating nature of jet activity. The methodology proposed in this work can be extended to active radio galaxies in future studies., Comment: 19 pages, 9 figures, 2 tables; submitted to MNRAS

We describe the space observatory architecture and mission design of the SALTUS mission, a NASA Astrophysics Probe Explorer concept. SALTUS will address key far-infrared science using a 14-m diameter <45 K primary reflector (M1) and will provide unprecedented levels of spectral sensitivity for planet, solar system, and galactic evolution studies, and cosmic origins. Drawing from Northrop Grumman's extensive NASA mission heritage, the observatory flight system is based on the LEOStar-3 spacecraft platform to carry the SALTUS Payload. The Payload is comprised of the inflation control system (ICS), Sunshield Module (SM), Cold Corrector Module (CCM), Warm Instrument Electronics Module, and Primary Reflector Module (PRM). The 14-m M1 is an off-axis inflatable membrane radiatively cooled by a two-layer sunshield (~1,000 m2 per layer). The CCM corrects for residual aberration from M1 and delivers a focused beam to two instruments - High Resolution Receiver (HiRX) and SAFARI-Lite. The CCM and PRM reside atop a truss-based composite deck which also provides a platform for the attitude control system. The 5-year mission lifetime is driven by a two-consumable architecture: the propellant system and the ICS. The Core Interface Module (CIM), a multi-faceted composite truss structure, provides a load path with high stiffness, mechanical attachment, and thermal separation between the Payload and spacecraft. The SM attaches outside the CIM with its aft end integrating directly to the bus. The spacecraft maintains an attitude off M1's boresight with respect to the Sun line to facilitate the <45 K thermal environment. SALTUS will reside in a Sun-Earth halo L2 orbit with a maximum Earth slant range of 1.8 million km thereby reducing orbit transfer delta-v. The instantaneous field of regard provides two continuous 20-deg viewing zones around the ecliptic poles resulting in full sky coverage in six months., Comment: Submitted to the J. Astron. Telesc. Instrum. Syst. (JATIS), 67 pages, 16 figures, 12 tables

The generation of shaped laser beams, or structured light, is of interest in a wide range of fields, from microscopy to fundamental physics. There are several ways to make shaped beams, most commonly using spatial light modulators comprised of pixels of liquid crystals. These methods have limitations on the wavelength, pulse duration, and average power that can be used. Here we present a method to generate shaped light that can be used at any wavelength from the UV to IR, on ultrafast pulses, and a large range of optical powers. By exploiting the frequency difference between higher order modes, a result of the Gouy phase, and cavity mode matching, we can selectively couple into a variety of pure and composite higher order modes. Optical cavities are used as a spatial filter and then combined with sum frequency generation in a nonlinear crystal as the output coupler to the cavity to create ultrafast, frequency comb structured light., Comment: 4 pages, 4 figures

The Galactic center lobe (GCL) is a $\sim 1^\circ$ object located north of the Galactic center. In the mid-infrared (MIR), the GCL appears as two 8.0-micron filaments that roughly define an ellipse. There is strong 24-micron and radio continuum emission in the interior of the ellipse. Due to its morphology and location in the sky, previous authors have argued that the GCL is created by outflows from star formation in the central molecular zone or by activity of the central black hole Sgr~A$^*$. We present images of the GCL from the GaLactic and Extragalactic All-sky Murchison Widefield Array survey in radio continuum that show thermal absorption against the Galactic center, incompatible with an interpretation of synchrotron self-absorption. Estimates of the cosmic ray emissivity in this direction allow us to place a distance constraint on the GCL. To be consistent with standard emissivity assumptions, the GCL would be located 2kpc away. At a distance of 8kpc, the synchrotron background emissivity is enhanced by $\sim75$% in the direction of the GCL. We also present radio recombination line data from the Green Bank Telescope that constrains the electron temperature and line widths in this region, which are also more explicable if the GCL lies relatively close., Comment: 6 figures, accepted to ApJ

We describe some features of the A100 memory architecture. In particular, we give a technique to reverse-engineer some hardware layout information. Using this information, we show how to avoid TLB issues to obtain full-speed random HBM access to the entire memory, as long as we constrain any particular thread to a reduced access window of less than 64GB., Comment: 6 pages, 6 figures

One of the keys to the success of collaborative learning is balanced participation by all learners, but this does not always happen naturally. Pedagogical robots have the potential to facilitate balance. However, it remains unclear what participation balance robots should aim at; various metrics have been proposed, but it is still an open question whether we should balance human participation in human-human interactions (HHI) or human-robot interactions (HRI) and whether we should consider robots' participation in collaborative learning involving multiple humans and a robot. This paper examines collaborative learning between a pair of students and a teachable robot that acts as a peer tutee to answer the aforementioned question. Through an exploratory study, we hypothesize which balance metrics in the literature and which portions of dialogues (including vs. excluding robots' participation and human participation in HHI vs. HRI) will better predict learning as a group. We test the hypotheses with another study and replicate them with automatically obtained units of participation to simulate the information available to robots when they adaptively fix imbalances in real-time. Finally, we discuss recommendations on which metrics learning science researchers should choose when trying to understand how to facilitate collaboration., Comment: To appear in Seventeenth International Conference on Educational Data Mining (EDM 2024)

The Galactic center lobe (GCL) is an object ~1{\deg} across that is located north of the Galactic center. In the mid-infrared (MIR) the GCL appears as two 8.0${\mu}$m filaments between which is strong 24${\mu}$m and radio continuum emission. Due to its morphology and location in the sky, previous authors have argued that the GCL is located in the Galactic center region, created by outflows from star formation or by activity of the central black hole Sagittarius A*. In an associated paper (Hurley-Walker et al., 2024, in press), low-frequency radio emission indicates that the GCL must instead lie foreground to the Galactic center. If the GCL is foreground to the Galactic center, it is likely to be a type of object common throughout the Galactic disk; we here investigate whether its properties are similar to those of Galactic HII regions. We find that the GCL's MIR morphology, MIR flux densities, dust temperatures, and radio recombination line (RRL) properties as traced by the GBT Diffuse Ionized Gas Survey (GDIGS) are consistent with those of known Galactic HII regions, although the derived electron temperature is low. We search for the ionizing source(s) of the possible HII region and identify a stellar cluster candidate (Camargo #1092/Ryu & Lee #532) and a cluster of young stellar objects (SPICY G359.3+0.3) whose members have Gaia parallaxes distances of 1.7${\pm}$0.4kpc. Taken together, the results of our companion paper and those shown here suggest that the GCL has properties consistent with those of an HII region located ~2kpc from the Sun., Comment: Accepted to ApJ

Animated logos are a compelling and ubiquitous way individuals and brands represent themselves online. Manually authoring these logos can require significant artistic skill and effort. To help novice designers animate logos, design tools currently offer templates and animation presets. However, these solutions can be limited in their expressive range. Large language models have the potential to help novice designers create animated logos by generating animation code that is tailored to their content. In this paper, we introduce LogoMotion, an LLM-based system that takes in a layered document and generates animated logos through visually-grounded program synthesis. We introduce techniques to create an HTML representation of a canvas, identify primary and secondary elements, synthesize animation code, and visually debug animation errors. When compared with an industry standard tool, we find that LogoMotion produces animations that are more content-aware and are on par in terms of quality. We conclude with a discussion of the implications of LLM-generated animation for motion design.

In stars that lie on the main sequence in the Hertzsprung-Russel diagram, like our sun, hydrogen is fused to helium in a number of nuclear reaction chains and series, such as the proton-proton chain and the carbon-nitrogen-oxygen cycles. Precisely determined thermonuclear rates of these reactions lie at the foundation of the standard solar model. This review, the third decadal evaluation of the nuclear physics of hydrogen-burning stars, is motivated by the great advances made in recent years by solar neutrino observatories, putting experimental knowledge of the proton-proton chain neutrino fluxes in the few-percent precision range. The basis of the review is a one-week community meeting held in July 2022 in Berkeley, California, and many subsequent digital meetings and exchanges. The relevant reactions of solar and stellar hydrogen burning are reviewed here, from both theoretical and experimental perspectives. Recommendations for the state of the art of the astrophysical S-factor and its uncertainty are formulated for each of them. Several other topics of paramount importance for the solar model are reviewed, as well: recent and future neutrino experiments, electron screening, radiative opacities, and current and upcoming experimental facilities. In addition to reaction-specific recommendations, also general recommendations are formed., Comment: 101 pages, 25 figures, including supplementary material. Revised version submitted to Reviews of Modern Physics