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This study employs a qualitative research design to explore the experiences and perspectives of two experienced English teachers who adapted their writing instruction methodologies during the COVID-19 pandemic. Through semi-structured interviews, observations, and document analysis, the research delves into the challenges and innovative strategies these educators implemented in online teaching environments. The teachers adapted by incorporating methods like journaling for self-expression, collaborative writing, the dialogic method, and environmental journalism to enhance motivation and engagement. The study highlights the importance of setting specific goals and purposes for writing tasks to improve student outcomes. Ethical considerations, including informed consent and data confidentiality, were meticulously followed. The findings underscore the need for continued exploration of innovative instructional approaches and collaboration among educators, policymakers, and communities to address educational disparities and enhance writing instruction in the post-pandemic era.

The $J/\psi$ and $\psi(2S)$ charmonium states, composed of $c\bar{c}$ quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics in high-energy hadronic interactions. However, there is not yet a complete understanding of the charmonium-production mechanism. Recent measurements of $J/\psi$ production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced $J/\psi$ production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We carry out the first measurements of self-normalized $J/\psi$ yields and the $\psi(2S)$ to $J/\psi$ ratio at both forward and backward rapidities as a function of self-normalized charged-particle multiplicity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV. In addition, detailed {\sc pythia} studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by {\sc pythia} calculations that include MPI effects. The forward and backward $\psi(2S)$ to $J/\psi$ ratio, which serves as a unique and powerful approach to study final-state effects on charmonium production, is found to be less dependent on the charged-particle multiplicity., Comment: 301 authors from 69 institutions, 8 pages, 3 figures. v1 is version submitted to Physical Review D Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We introduce OLMoE, a fully open, state-of-the-art language model leveraging sparse Mixture-of-Experts (MoE). OLMoE-1B-7B has 7 billion (B) parameters but uses only 1B per input token. We pretrain it on 5 trillion tokens and further adapt it to create OLMoE-1B-7B-Instruct. Our models outperform all available models with similar active parameters, even surpassing larger ones like Llama2-13B-Chat and DeepSeekMoE-16B. We present various experiments on MoE training, analyze routing in our model showing high specialization, and open-source all aspects of our work: model weights, training data, code, and logs., Comment: 61 pages (24 main), 36 figures, 14 tables

Fingerprint examiners appear to be reluctant to adopt probabilistic reasoning, statistical models, and empirical validation. The rate of adoption of the likelihood-ratio framework by fingerprint practitioners appears to be near zero. A factor in the reluctance to adopt the likelihood-ratio framework may be a perception that it would require a radical change in practice. The present paper proposes a small step that would require minimal changes to current practice. It proposes and demonstrates a method to convert traditional fingerprint-examination outputs ("identification", "inconclusive", "exclusion") to well-calibrated Bayes factors. The method makes use of a beta-binomial model, and both uninformative and informative priors., Comment: 2022 manuscript

The broad physics reach of the LUX-ZEPLIN (LZ) experiment covers rare phenomena beyond the direct detection of dark matter. We report precise measurements of the extremely rare decay of $^{124}$Xe through the process of two-neutrino double electron capture (2$\nu$2EC), utilizing a $1.39\,\mathrm{kg} \times \mathrm{yr}$ isotopic exposure from the first LZ science run. A half-life of $T_{1/2}^{2\nu2\mathrm{EC}} = (1.09 \pm 0.14_{\text{stat}} \pm 0.05_{\text{sys}}) \times 10^{22}\,\mathrm{yr}$ is observed with a statistical significance of $8.3\,\sigma$, in agreement with literature. First empirical measurements of the KK capture fraction relative to other K-shell modes were conducted, and demonstrate consistency with respect to recent signal models at the $1.4\,\sigma$ level., Comment: 15 pages, 3 figures

The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0

Low-lying states of $^{94}$Zr were investigated via low-energy multi-step Coulomb excitation. From the measured $\gamma$-ray yields, 13 reduced transition probabilities between low-spin states were determined, together with the spectroscopic quadrupole moments of the $2_{1,2}^+$ states. Based on this information, for the first time in the Zr isotopic chain, the shapes of the $0_{1,2}^+$ states including their deformation softness were inferred in a model-independent way using the quadrupole sum rules approach. The ground state of $^{94}$Zr possesses a rather diffuse shape associated with a spherical configuration, while the $0_2^+$ state is oblate and more strongly deformed. The observed features of shape coexistence in $^{94}$Zr are in agreement with Monte-Carlo shell-model predictions, and the present results are vital to refine the IBM-CM description of the Zr isotopes around $A\approx 100$ in terms of an intertwined quantum phase transition., Comment: 6 pages, 3 figures

We present dynamical modeling of the broad-line region (BLR) for the highly variable AGN SDSS J141041.25+531849.0 ($z = 0.359$) using photometric and spectroscopic monitoring data from the Sloan Digital Sky Survey Reverberation Mapping project and the SDSS-V Black Hole Mapper program, spanning from early 2013 to early 2023. We model the geometry and kinematics of the BLR in the H$\beta$, H$\alpha$, and MgII, emission lines for three different time periods to measure the potential change of structure within the BLR across time and line species. We consistently find a moderately edge-on $(i_{\rm full-state} = 53.29^{\circ} \,{}^{+7.29}_{-6.55})$ thick-disk $(\theta_{\rm opn, \; full-state} = 54.86^{\circ} \,{}^{+5.83}_{-4.74})$ geometry for all BLRs, with a joint estimate for the mass of the supermassive black hole (SMBH) for each of three time periods, yielding $\log_{10}(M_{\rm BH} / M_{\odot}) = 7.66^{+0.12}_{-0.13}$ when using the full dataset. The inferred individual virial factor $f$ $\sim 1$ is significantly smaller than the average factor for a local sample of dynamically modeled AGNs. There is strong evidence for non-virial motion, with over $80\%$ of clouds on inflowing/outflowing orbits. We analyze the change in model parameters across emission lines, finding the radii of BLRs for the emission lines are consistent with the following relative sizes $R_{\rm H\beta} \lesssim R_{\rm MgII } \lesssim R_{\rm H\alpha}$. Comparing results across time, we find $R_{\rm low-state} \lesssim R_{\rm high-state}$, with the change in BLR size for H$\beta$, being more significant than for the other two lines. The data also reveal complex, time-evolving, and potentially transient dynamics of the BLR gas over decade-long timescales, encouraging for future dynamical modeling of fine-scale BLR kinematics., Comment: 32 pages, 16 figures, 4 tables. Submitted to ApJ

Compound graphs are networks in which vertices can be grouped into larger subsets, with these subsets capable of further grouping, resulting in a nesting that can be many levels deep. In several applications, including biological workflows, chemical equations, and computational data flow analysis, these graphs often exhibit a tree-like nesting structure, where sibling clusters are disjoint. Common compound graph layouts prioritize the lowest level of the grouping, down to the individual ungrouped vertices, which can make the higher level grouped structures more difficult to discern, especially in deeply nested networks. Leveraging the additional structure of the tree-like nesting, we contribute an overview+detail layout for this class of compound graphs that preserves the saliency of the higher level network structure when groups are expanded to show internal nested structure. Our layout draws inner structures adjacent to their parents, using a modified tree layout to place substructures. We describe our algorithm and then present case studies demonstrating the layout's utility to a domain expert working on data flow analysis. Finally, we discuss network parameters and analysis situations in which our layout is well suited., Comment: 5 pages, 7 figures. To appear at VIS2024

The UKIRT Hemisphere Survey covers the northern sky in the infrared from 0-60 degrees declination. Current data releases include both J and K bands, with H-band data forthcoming. Here we present a novel pipeline to recover asteroids from this survey data. We recover 26,138 reliable observations, corresponding to 23,399 unique asteroids, from these public data. We measure J-K colors for 601 asteroids. Our survey extends about two magnitudes deeper than 2MASS. We find that our small inner main belt objects are less red than larger inner belt objects, perhaps because smaller asteroids are collisionally younger, with surfaces that have been less affected by space weathering. In the middle and outer main belt, we find our small asteroids to be redder than larger objects in their same orbits, possibly due to observational bias or a disproportionate population of very red objects among these smaller asteroids. Future work on this project includes extracting moving object measurements from H and Y band data when it becomes available., Comment: 15 pages, 10 figures

A broad class of nonlinear acoustic wave models possess a Hamiltonian structure in their dissipation-free limit and a gradient flow structure for their dissipative dynamics. This structure may be exploited to design numerical methods which preserve the Hamiltonian structure in the dissipation-free limit, and which achieve the correct dissipation rate in the spatially-discrete dissipative dynamics. Moreover, by using spatial discretizations which preserve the de Rham cohomology, the non-evolving involution constraint for the vorticity may be exactly satisfied for all of time. Numerical examples are given using a mimetic finite difference spatial discretization.

We study the commuting graph of $n\times n$ matrices over the field of $p$-adics $\mathbb{Q}_p$, whose vertices are non-scalar $n\times n$ matrices with entries in $\mathbb{Q}_p$ and whose edges connect pairs of matrices that commute under matrix multiplication. We prove that this graph is connected if and only if $n\geq 3$, with $n$ neither prime nor a power of $p$. We also prove that in the case of $p=2$ and $n=2q$ for $q$ a prime with $q\geq 7$, the commuting graph has the maximum possible diameter of $6$; these are the first known such examples independent of the axiom of choice. We also find choices of $p$ and $n$ yielding diameter $4$ and diameter $5$ commuting graphs, and prove general bounds depending on $p$ and $n$., Comment: 9 pages

(abridged)Photometric redshifts for AGN (galaxies hosting an accreting supermassive black hole in their center) are notoriously challenging and currently better computed via SED fitting, assuming that deep photometry for many wavelengths is available. However, for AGN detected all-sky, the photometry is limited and provided by different projects. This makes the task of homogenising the data challenging and is a dramatic drawback for the millions of AGN that wide surveys like SRG/eROSITA will detect. This work aims to compute reliable photometric redshifts for X-ray-detected AGN using only one dataset that covers a large area: the 10th Data Release of the Imaging Legacy Survey (LS10) for DESI. LS10 provides deep grizW1-W4 forced photometry within various apertures, thus avoids issues related to the cross-calibration of surveys. We present the results from CircleZ, a machine-learning algorithm based on a Fully Connected Neural Network. CircleZ uses training sample of 14,000 X-ray-detected AGN and utilizes multi-aperture photometry. The accuracy and the fraction of outliers reached in a test sample of 2913 AGN are 0.067 and 11.6%, respectively. The results are comparable to or better than those obtained previously for the same field but with much less effort. We further tested the stability of the results by computing the photometric redshifts for the sources detected in CSC2 and Chandra-COSMOS Legacy, reaching comparable accuracy as in eFEDS when limiting the magnitude of the counterparts with respect to the depth of LS10. The method applies to fainter samples of AGN using deeper optical data from future surveys (e.g., LSST, Euclid), granted LS10-like information on the light distribution beyond a morphological type is provided. With the paper, we release an updated version of the photometric redshifts (including errors and probability distribution function) for eROSITA/eFEDS., Comment: A&A, paper accepted

The ability of Language Models (LMs) to understand natural language makes them a powerful tool for parsing human instructions into task plans for autonomous robots. Unlike traditional planning methods that rely on domain-specific knowledge and handcrafted rules, LMs generalize from diverse data and adapt to various tasks with minimal tuning, acting as a compressed knowledge base. However, LMs in their standard form face challenges with long-horizon tasks, particularly in partially observable multi-agent settings. We propose an LM-based Long-Horizon Planner for Multi-Agent Robotics (LLaMAR), a cognitive architecture for planning that achieves state-of-the-art results in long-horizon tasks within partially observable environments. LLaMAR employs a plan-act-correct-verify framework, allowing self-correction from action execution feedback without relying on oracles or simulators. Additionally, we present MAP-THOR, a comprehensive test suite encompassing household tasks of varying complexity within the AI2-THOR environment. Experiments show that LLaMAR achieves a 30% higher success rate compared to other state-of-the-art LM-based multi-agent planners., Comment: 27 pages, 4 figures, 5 tables

Quantum networks typically operate in the telecom wavelengths to take advantage of low-loss transmission in optical fibres. However, bright quantum dots (QDs) emitting highly indistinguishable quantum states of light, such as InGaAs QDs, often emit photons in the near infrared thus necessitating frequency conversion (FC) to the telecom band. Furthermore, the signal quality of quantum emissions is crucial for the effective performance of these networks. In this work we report a method for simultaneously implementing spectral purification and frequency shifting of single photons from QD sources to the C-band in a periodically poled Lithium Niobate waveguide. We consider difference frequency generation in the counter-propagating configuration to implement FC with the output emission bandwidth in units of GHz. Our approach establishes a clear path to integrating high-performance single-emitter sources in a hybrid quantum network.

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{s_{_{NN}}}=200$~GeV Au$+$Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by L\'evy-stable source distributions. The extracted source parameters are the correlation-strength parameter $\lambda$, the L\'evy index of stability $\alpha$, and the L\'evy-scale parameter $R$ as a function of transverse mass $m_T$ and centrality. The $\lambda(m_T)$ parameter is constant at larger values of $m_T$, but decreases as $m_T$ decreases. The L\'evy scale parameter $R(m_T)$ decreases with $m_T$ and exhibits proportionality to the length scale of the nuclear overlap region. The L\'evy exponent $\alpha(m_T)$ is independent of $m_T$ within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the L\'evy exponent $\alpha$ is significantly different from that of Gaussian ($\alpha=2$) or Cauchy ($\alpha=1$) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that in all but the most peripheral centrality class (50%-60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the $\eta'$ meson is included. In each centrality class, the best value of the in-medium $\eta'$ mass is compared to the mass of the $\eta$ meson, as well as to several theoretical predictions that consider restoration of $U_A(1)$ symmetry in hot hadronic matter., Comment: 401 authors from 75 institutions, 20 pages, 15 figures, 2 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

Fine-grained editing of speech attributes$\unicode{x2014}$such as prosody (i.e., the pitch, loudness, and phoneme durations), pronunciation, speaker identity, and formants$\unicode{x2014}$is useful for fine-tuning and fixing imperfections in human and AI-generated speech recordings for creation of podcasts, film dialogue, and video game dialogue. Existing speech synthesis systems use representations that entangle two or more of these attributes, prohibiting their use in fine-grained, disentangled editing. In this paper, we demonstrate the first disentangled and interpretable representation of speech with comparable subjective and objective vocoding reconstruction accuracy to Mel spectrograms. Our interpretable representation, combined with our proposed data augmentation method, enables training an existing neural vocoder to perform fast, accurate, and high-quality editing of pitch, duration, volume, timbral correlates of volume, pronunciation, speaker identity, and spectral balance., Comment: Interspeech 2024

This paper provides a friendly introduction to chip-firing games and graph gonality. We use graphs coming from the five Platonic solids to illustrate different tools and techniques for studying these games, including independent sets, treewidth, scramble number, and Dhar's burning algorithm. In addition to showcasing some previously known results, we present the first proofs that the dodecahedron graph has gonality $6$, and that the icosahedron graph has gonality~$9$., Comment: 22 pages, 23 figures

We identify several important and unsettled legal questions with profound ethical and societal implications arising from generative artificial intelligence (GenAI), focusing on its distinguishable characteristics from traditional software and earlier AI models. Our key contribution is formally identifying the issues that are unique to GenAI so scholars, practitioners, and others can conduct more useful investigations and discussions. While established legal frameworks, many originating from the pre-digital era, are currently employed in GenAI litigation, we question their adequacy. We argue that GenAI's unique attributes, including its general-purpose nature, reliance on massive datasets, and potential for both pervasive societal benefits and harms, necessitate a re-evaluation of existing legal paradigms. We explore potential areas for legal and regulatory adaptation, highlighting key issues around copyright, privacy, torts, contract law, criminal law, property law, and the First Amendment. Through an exploration of these multifaceted legal challenges, we aim to stimulate discourse and policy considerations surrounding GenAI, emphasizing a proactive approach to legal and ethical frameworks. While we refrain from advocating specific legal changes, we underscore the need for policymakers to carefully consider the issues raised. We conclude by summarizing key questions across these areas of law in a helpful table for easy reference., Comment: 14 pages

Consider $\boldsymbol X \sim \mathcal{N}(\boldsymbol 0, \boldsymbol \Sigma)$ and $\boldsymbol Y = (f_1(X_1), f_2(X_2),\dots, f_d(X_d))$. We call this a diagonal transformation of a multivariate normal. In this paper we compute exactly the mean vector and covariance matrix of the random vector $\boldsymbol Y.$ This is done two different ways: One approach uses a series expansion for the function $f_i$ and the other a transform method. We compute several examples, show how the covariance entries can be estimated, and compare the theoretical results with numerical ones., Comment: 21 pages

For several decades now it has been known that systems with shearless invariant tori, nontwist Hamiltonian systems, possess barriers to chaotic transport. These barriers are resilient to breakage under perturbation and therefore regions where they occur are natural places to look for barriers to transport. We describe a novel kind of effective barrier that persists after the shearless torus is broken. Because phenomena are generic, for convenience we study the Standard Nontwist Map (SNM), an area-preserving map that violates the twist condition locally in the phase space. The novel barrier occurs in nontwist systems when twin even period islands are present, which happens for a broad range of parameter values in the SNM. With a phase space composed of regular and irregular orbits, the movement of chaotic trajectories is hampered by the existence of both shearless curves, total barriers, and a network of partial barriers formed by the stable and unstable manifolds of the hyperbolic points. Being a degenerate system, the SNM has twin islands and, consequently, twin hyperbolic points. We show that the structures formed by the manifolds intrinsically depend on period parity of the twin islands. For this even scenario the novel structure, named a torus free barrier, occurs because the manifolds of different hyperbolic points form an intricate chain atop a dipole configuration and the transport of chaotic trajectories through the chain becomes a rare event. This structure impacts the emergence of transport, the escape basin for chaotic trajectories, the transport mechanism and the chaotic saddle. The case of odd periodic orbits is different: we find for this case the emergence of transport immediately after the breakup of the last invariant curve, and this leads to a scenario of higher transport, with intricate escape basin boundary and a chaotic saddle with non-uniformly distributed points.

The JWST has been collecting scientific data for over two years now. Scientists are now looking deeper into the data, which introduces the need to correct known systematic effects. Important limiting factors for the MIRI/MRS are the pointing accuracy, non-linearity, detector charge migration, detector scattering, the accuracy of the PSF model, and the complex interplay between these. The Cycle 2 programme 3779 proposed a 72-point intra-pixel dither raster of the calibration star 10-Lac. In this first work of the paper series, we aim to address the degeneracy between the non-linearity and BFE that affect the pixel voltage integration ramps of the MRS. Due to the low flux in the longer wavelengths, we only do this in the 4.9 to 11.7 micron region. We fitted the ramps per pixel and dither, in order to fold in the deviations from classical non-linearity that are caused by charge migration. The ramp shapes should be repeatable depending on the part of the PSF that is sampled. By doing so, we defined both a grid-based linearity correction, and an interpolated linearity correction. We find significant improvements compared to the uniform illumination assumption. The standard deviation on the pixel ramp residual non-linearity is between 70-90% smaller than the current standard pipeline when self-calibrating with the grid. We are able to interpolate these coefficients to apply to any unresolved source not on the grid points, resulting in an up to 70% smaller standard deviation on the residual deviation from linearity. The FWHM is up to 20% narrower. The depth of the fringes is now consistent up the ramp. Pointing-specific linearity corrections allow us to fix the systematic deviation in the slopes. We demonstrated this for unresolved sources. The discovered trends with PSF sampling suggest that, we may be able to model ramps for spatially extended and resolved illumination as well., Comment: 18 pages, 20 figures, Accepted for publication in A&A

We present the results of an investigation of a highly variable CIV broad absorption-line feature in the quasar SBS 1408+544 (z=2.337) that shows a significant shift in velocity over time. This source was observed as a part of the Sloan Digital Sky Survey Reverberation Mapping Project and the SDSS-V Black Hole Mapper Reverberation Mapping Project, and has been included in two previous studies, both of which identified significant variability in a high-velocity CIV broad absorption line (BAL) on timescales of just a few days in the quasar rest frame. Using ~130 spectra acquired over eight years of spectroscopic monitoring with SDSS, we have determined that this BAL is not only varying in strength, but is also systematically shifting to higher velocities. Using cross-correlation methods, we measure the velocity shifts (and corresponding acceleration) of the BAL on a wide range of timescales, measuring an overall velocity shift of delta v = -683 (+89, -84) km s-1 over the 8-year monitoring period. This corresponds to an average rest-frame acceleration of a=1.04 (+0.14, -0.13) cm s-2, though the magnitude of the acceleration on shorter timescales is not constant throughout. We place our measurements in the context of BAL-acceleration models and examine various possible causes of the observed velocity shift., Comment: Published in the Astrophysical Journal

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 534 authors from 83 institutions, 12 pages, 7 figures. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

We present SciRIFF (Scientific Resource for Instruction-Following and Finetuning), a dataset of 137K instruction-following demonstrations for 54 tasks covering five essential scientific literature understanding capabilities: information extraction, summarization, question answering, claim verification, and classification. SciRIFF demonstrations are notable for their long input contexts, detailed task specifications, and complex structured outputs. While instruction-following resources are available in specific domains such as clinical medicine and chemistry, SciRIFF is the first dataset focused on extracting and synthesizing information from research literature across a wide range of scientific fields. To demonstrate the utility of SciRIFF, we develop a sample-efficient strategy to adapt a general instruction-following model for science by performing additional finetuning on a mix of general-domain and SciRIFF demonstrations. In evaluations on nine held-out scientific tasks, our model -- called SciTulu -- improves over a strong LLM baseline by 28.1% and 6.5% at the 7B and 70B scales respectively, while maintaining general instruction-following performance within 2% of the baseline. We are optimistic that SciRIFF will facilitate the development and evaluation of LLMs to help researchers navigate the ever-growing body of scientific literature. We release our dataset, model checkpoints, and data processing and evaluation code to enable further research., Comment: Submitted to NeurIPS Datasets and Benchmarks 2024

We study the question of how best to assign an encouragement in a randomized encouragement study. In our setting, units arrive with covariates, receive a nudge toward treatment or control, acquire one of those statuses in a way that need not align with the nudge, and finally have a response observed. The nudge can be seen as a binary instrument that affects the response only via the treatment status. Our goal is to assign the nudge as a function of covariates in a way that best estimates the local average treatment effect (LATE). We assume a partially linear model, wherein the baseline model is non-parametric and the treatment term is linear in the covariates. Under this model, we outline a two-stage procedure to consistently estimate the LATE. Though the variance of the LATE is intractable, we derive a finite sample approximation and thus a design criterion to minimize. This criterion is convex, allowing for constraints that might arise for budgetary or ethical reasons. We prove conditions under which our solution asymptotically recovers the lowest true variance among all possible nudge propensities. We apply our method to a semi-synthetic example involving triage in an emergency department and find significant gains relative to a regression discontinuity design., Comment: 31 pages, 6 figures

Understanding the mechanisms of information storage and transfer in Transformer-based models is important for driving model understanding progress. Recent work has studied these mechanisms for Large Language Models (LLMs), revealing insights on how information is stored in a model's parameters and how information flows to and from these parameters in response to specific prompts. However, these studies have not yet been extended to Multi-modal Large Language Models (MLLMs). Given their expanding capabilities and real-world use, we start by studying one aspect of these models -- how MLLMs process information in a factual visual question answering task. We use a constraint-based formulation which views a visual question as having a set of visual or textual constraints that the model's generated answer must satisfy to be correct (e.g. What movie directed by the director in this photo has won a Golden Globe?). Under this setting, we contribute i) a method that extends causal information tracing from pure language to the multi-modal setting, and ii) VQA-Constraints, a test-bed of 9.7K visual questions annotated with constraints. We use these tools to study two open-source MLLMs, LLaVa and multi-modal Phi-2. Our key findings show that these MLLMs rely on MLP and self-attention blocks in much earlier layers for information storage, compared to LLMs whose mid-layer MLPs are more important. We also show that a consistent small subset of visual tokens output by the vision encoder are responsible for transferring information from the image to these causal blocks. We validate these mechanisms by introducing MultEdit, a model-editing algorithm that can correct errors and insert new long-tailed information into MLLMs by targeting these causal blocks., Comment: 20 pages

This work presents a novel resolution-invariant model order reduction strategy for multifidelity applications. We base our architecture on a novel neural network layer developed in this work, the graph feedforward network, which extends the concept of feedforward networks to graph-structured data by creating a direct link between the weights of a neural network and the nodes of a mesh, enhancing the interpretability of the network. We exploit the method's capability of training and testing on different mesh sizes in an autoencoder-based reduction strategy for parametrised partial differential equations. We show that this extension comes with provable guarantees on the performance via error bounds. The capabilities of the proposed methodology are tested on three challenging benchmarks, including advection-dominated phenomena and problems with a high-dimensional parameter space. The method results in a more lightweight and highly flexible strategy when compared to state-of-the-art models, while showing excellent generalisation performance in both single fidelity and multifidelity scenarios.

Weakly interacting massive particles (WIMPs) may interact with a virtual pion that is exchanged between nucleons. This interaction channel is important to consider in models where the spin-independent isoscalar channel is suppressed. Using data from the first science run of the LUX-ZEPLIN dark matter experiment, containing 60 live days of data in a 5.5~tonne fiducial mass of liquid xenon, we report the results on a search for WIMP-pion interactions. We observe no significant excess and set an upper limit of $1.5\times10^{-46}$~cm$^2$ at a 90\% confidence level for a WIMP mass of 33~GeV/c$^2$ for this interaction.

This paper introduces Fortune Analytics Language Model (FALM). FALM empowers users with direct access to comprehensive business analysis, including market trends, company performance metrics, and expert insights. Unlike generic LLMs, FALM leverages a curated knowledge base built from professional journalism, enabling it to deliver precise and in-depth answers to intricate business questions. Users can further leverage natural language queries to directly visualize financial data, generating insightful charts and graphs to understand trends across diverse business sectors clearly. FALM fosters user trust and ensures output accuracy through three novel methods: 1) Time-aware reasoning guarantees accurate event registration and prioritizes recent updates. 2) Thematic trend analysis explicitly examines topic evolution over time, providing insights into emerging business landscapes. 3) Content referencing and task decomposition enhance answer fidelity and data visualization accuracy. We conduct both automated and human evaluations, demonstrating FALM's significant performance improvements over baseline methods while prioritizing responsible AI practices. These benchmarks establish FALM as a cutting-edge LLM in the business and media domains, with exceptional accuracy and trustworthiness.

We explore optimization options for the Stream-K algorithm, a work-centric parallelization of matrix multiplication (GEMM). In our study, we investigated differences between the theoretical and practical implementations, particularly noting the impact of padding. Our debugging efforts revealed a persistent bug related to block mapping, which we could not fully resolve, but we managed to implement some optimizations. Setting the padding to zero for the M, N, and K dimensions resulted in an average 0.6% improvement in performance, achieving 1.44 ms, 89.37 TFlops, and 66.91 GB/s. However, adjusting the block size and parameters led to the process getting stuck, indicating a need for further tuning. Additionally, exploring the potential of Block2Time highlighted its promise in enhancing runtime predictions and optimizing load balancing., Comment: This work references work from the Stream-K algorithm article available at arXiv:2301.03598

Given graphs $G, H$ and an integer $q \ge 2$, the generalized Ramsey number, denoted $r(G,H,q)$, is the minimum number of colours needed to edge-colour $G$ such that every copy of $H$ receives at least $q$ colours. In this paper, we prove that for a fixed integer $k \ge 3$, we have $r(K_n,C_k,3) = n/(k-2)+o(n)$. This generalises work of Joos and Muybayi, who proved $r(K_n,C_4,3) = n/2+o(n)$. We also provide an upper bound on $r(K_{n,n}, C_k, 3)$, which generalises a result of Joos and Mubayi that $r(K_{n,n},C_4,3) = 2n/3+o(n)$. Both of our results are in fact specific cases of more general theorems concerning families of cycles.

The James Webb Space Telescope (JWST) is revolutionizing our view of the Universe through unprecedented sensitivity and resolution in the infrared, with some of the largest gains realized at its longest wavelengths. We present the Systematic Mid-infrared Instrument (MIRI) Legacy Extragalactic Survey (SMILES), an eight-band MIRI survey with Near-Infrared Spectrograph (NIRSpec) spectroscopic follow-up in the GOODS-S/HUDF region. SMILES takes full advantage of MIRI's continuous coverage from $5.6-25.5\,\mu$m over a $\sim34$ arcmin$^2$ area to greatly expand our understanding of the obscured Universe up to cosmic noon and beyond. This work, together with a companion paper by Rieke et al., covers the SMILES science drivers and technical design, early results with SMILES, data reduction, photometric catalog creation, and the first data release. As part of the discussion on early results, we additionally present a high-level science demonstration on how MIRI's wavelength coverage and resolution will advance our understanding of cosmic dust using the full range of polycyclic aromatic hydrocarbon (PAH) emission features from $3.3-18\,\mu$m. Using custom background subtraction, we produce robust reductions of the MIRI imaging that maximize the depths reached with our modest exposure times ($\sim0.6 - 2.2$ ks per filter). Included in our initial data release are (1) eight MIRI imaging mosaics reaching depths of $0.2-18\,\mu$Jy ($5\sigma$) and (2) a $5-25.5\,\mu$m photometric catalog with over 3,000 sources. Building upon the rich legacy of extensive photometric and spectroscopy coverage of GOODS-S/HUDF from the X-ray to the radio, SMILES greatly expands our investigative power in understanding the obscured Universe., Comment: 23 pages, 19 figures, submitted to ApJ. Comments welcome! Data release will go live at https://archive.stsci.edu/hlsp/smiles in the next few weeks

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. The hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described., Comment: 18 pages, 24 figures

The Super-Kamiokande and T2K collaborations present a joint measurement of neutrino oscillation parameters from their atmospheric and beam neutrino data. It uses a common interaction model for events overlapping in neutrino energy and correlated detector systematic uncertainties between the two datasets, which are found to be compatible. Using 3244.4 days of atmospheric data and a beam exposure of $19.7(16.3) \times 10^{20}$ protons on target in (anti)neutrino mode, the analysis finds a 1.9$\sigma$ exclusion of CP-conservation (defined as $J_{CP}=0$) and a preference for the normal mass ordering., Comment: 10 pages, 3 figures

Last-level cache side-channel attacks have been mostly demonstrated in highly-controlled, quiescent local environments. Hence, it is unclear whether such attacks are feasible in a production cloud environment. In the cloud, side channels are flooded with noise from activities of other tenants and, in Function-as-a-Service (FaaS) workloads, the attacker has a very limited time window to mount the attack. In this paper, we show that such attacks are feasible in practice, although they require new techniques. We present an end-to-end, cross-tenant attack on a vulnerable ECDSA implementation in the public FaaS Google Cloud Run environment. We introduce several new techniques to improve every step of the attack. First, to speed-up the generation of eviction sets, we introduce L2-driven candidate address filtering and a Binary Search-based algorithm for address pruning. Second, to monitor victim memory accesses with high time resolution, we introduce Parallel Probing. Finally, we leverage power spectral density from signal processing to easily identify the victim's target cache set in the frequency domain. Overall, using these mechanisms, we extract a median value of 81% of the secret ECDSA nonce bits from a victim container in 19 seconds on average.

This paper explores the value of archival theory as a means of grappling with bias in algorithmic design. Rather than seek to mitigate biases perpetuated by datasets and algorithmic systems, archival theory offers a reframing of bias itself. Drawing on a range of archival theory from the fields of history, literary and cultural studies, Black studies, and feminist STS, we propose absence-as power, presence, and productive-as a concept that might more securely anchor investigations into the causes of algorithmic bias, and that can prompt more capacious, creative, and joyful future work. This essay, in turn, can intervene into the technical as well as the social, historical, and political structures that serve as sources of bias., Comment: 16 pages, to be published in the 2024 ACM Conference on Designing Interactive Systems (DIS '24)

Nasogastric tubes (NGTs) are feeding tubes that are inserted through the nose into the stomach to deliver nutrition or medication. If not placed correctly, they can cause serious harm, even death to patients. Recent AI developments demonstrate the feasibility of robustly detecting NGT placement from Chest X-ray images to reduce risks of sub-optimally or critically placed NGTs being missed or delayed in their detection, but gaps remain in clinical practice integration. In this study, we present a human-centered approach to the problem and describe insights derived following contextual inquiry and in-depth interviews with 15 clinical stakeholders. The interviews helped understand challenges in existing workflows, and how best to align technical capabilities with user needs and expectations. We discovered the trade-offs and complexities that need consideration when choosing suitable workflow stages, target users, and design configurations for different AI proposals. We explored how to balance AI benefits and risks for healthcare staff and patients within broader organizational and medical-legal constraints. We also identified data issues related to edge cases and data biases that affect model training and evaluation; how data documentation practices influence data preparation and labelling; and how to measure relevant AI outcomes reliably in future evaluations. We discuss how our work informs design and development of AI applications that are clinically useful, ethical, and acceptable in real-world healthcare services.

The inclusion of spatial smoothing in finite-dimensional particle-based Hamiltonian reductions of the Vlasov equation are considered. In the context of the Vlasov-Poisson equation (and other mean-field Lie-Poisson systems), smoothing amounts to a convolutive regularization of the Hamiltonian. This regularization may be interpreted as a change of the inner product structure used to identify the dual space in the Lie-Poisson Hamiltonian formulation. In particular, the shape function used for spatial smoothing may be identified as the kernel function of a reproducing kernel Hilbert space whose inner product is used to define the Lie-Poisson Hamiltonian structure. It is likewise possible to introduce smoothing in the Vlasov-Maxwell system, but in this case the Poisson bracket must be modified rather than the Hamiltonian. The smoothing applied to the Vlasov-Maxwell system is incorporated by inserting smoothing in the map from canonical to kinematic coordinates. In the filtered system, the Lorentz force law and the current, the two terms coupling the Vlasov equation with Maxwell's equations, are spatially smoothed.