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State summative assessments play an important role in measuring student learning and guiding educational improvement efforts, despite their limitations. But there is growing momentum in individual states and nationally to rethink these assessments with an eye toward reducing time spent on testing and increasing the tests' instructional relevance. "Multiple Choices: Weighing Updates to State Summative Assessments" helps policymakers and advocates understand what they may gain and what they may lose when considering potential shifts in assessments. The report examines several of the most common proposed changes -- including reducing test length, matrix sampling, student sampling, grade-band testing, performance assessment, and through-year assessment -- and summarizes the potential gains, losses, and unknowns of each. The report also offers recommendations for state policymakers, federal policymakers, and advocates working to ensure that summative assessments better address the needs of educators, families, and students.

We present a new method that successfully predicts the glass transition temperature $T_{\! \textrm{g}}$ of polymers based on their monomer structure. The model combines ideas from Group Additive Properties (GAP) and Quantitative Structure Property Relationship (QSPR) methods, where GAP (or Group Contributions) assumes that sub-monomer motifs contribute additively to $T_{\! \textrm{g}}$, and QSPR links $T_{\! \textrm{g}}$ to the physico-chemical properties of the structure through a set of molecular descriptors. This method yields fast and accurate predictions of $T_{\! \textrm{g}}$ for polymers based on chemical motifs outside the data sample, which resolves the main limitation of the GAP approach. Using a genetic algorithm, we show that only two molecular descriptors are necessary to predict $T_{\! \textrm{g}}$ for PAEK polymers. Our QSPR-GAP method is readily transferred to other physical properties, to measures of activity (QSAR), or to different classes of polymers such as conjugated or bio-polymers., Comment: 12 pages, 4 figures, 1 table; Supplementary Information: 21 pages, 20 figures, 5 tables

We explore the gravitational-wave emission from head-on collisions of equal-mass solitonic boson-star binaries from simulations spanning a two-dimensional parameter space, consisting of the central scalar-field amplitude of the stars and the solitonic potential parameter. We report the gravitational-wave energies emitted by boson-star binaries which, due to their combination of moderately high compactness with significant deformability, we often find to be louder by up to an order of magnitude than analogous black-hole collisions. The dependence of the radiated energy on the boson-star parameters exhibits striking needle-sharp features and discontinuous jumps to the value emitted by black-hole binaries. We explain these features in terms of the solitonic potential and the stability properties of the respective individual stars., Comment: 17 pages, 10 figures

The apparent angular positions of quasars are deflected on the sky by the gravitational field sourced by foreground matter. This weak lensing effect is measurable through the distortions it introduces in the lensed quasar spectra. Discrepancies in the statistics of the Lyman-$\alpha$ forest spectral absorption features can be used to reconstruct the foreground lensing potential. We extend the study of this method of Lyman-$\alpha$ forest weak gravitational lensing to lower angular forest spectrum source densities than previous work. We evaluate the performance of the Lyman-$\alpha$ lensing estimator of Metcalf et al. (2020) on mock data based on the angular forest source density ($50$ per square degree) and volume ($\sim$700,000 spectra total) of the DESI survey. We simulate the foreground galaxy distribution and lensing potentials with redshift evolution approximated by N-body simulation and simulate Gaussian-random Lyman-$\alpha$ forests to produce mock data for the entire DESI footprint. By correlating the foreground galaxy distribution with the potential reconstructed by the estimator, we find that a weak lensing detection with signal to noise of $\sim4$ will be possible with the full DESI data. We show that spectral surveys with low density and high volume are promising candidates for forest weak lensing in addition to the high resolution data that have been considered in previous work. We present forecasts for future spectral surveys and show that with larger datasets a detection with signal to noise $>10$ will be possible.

In recent years, researchers have been exploring ways to generalize Boltzmann machines (BMs) to quantum systems, leading to the development of variations such as fully-visible and restricted quantum Boltzmann machines (QBMs). Due to the non-commuting nature of their Hamiltonians, restricted QBMs face trainability issues, whereas fully-visible QBMs have emerged as a more tractable option, as recent results demonstrate their sample-efficient trainability. These results position fully-visible QBMs as a favorable choice, offering potential improvements over fully-visible BMs without suffering from the trainability issues associated with restricted QBMs. In this work, we show that low-dimensional, fully-visible QBMs can learn to generate distributions typically associated with higher-dimensional systems. We validate our findings through numerical experiments on both artificial datasets and real-world examples from the high energy physics problem of jet event generation. We find that non-commuting terms and Hamiltonian connectivity improve the learning capabilities of QBMs, providing flexible resources suitable for various hardware architectures. Furthermore, we provide strategies and future directions to maximize the learning capacity of fully-visible QBMs., Comment: 13 pages, 7 figures; supplementary material 5 pages, 5 figures

The quest for radio signals from technologically-advanced extraterrestrial intelligence has traditionally concentrated on the vicinity of 1.4 GHz. In this paper, we extend the search to unprecedented territories, detailing our extensive observations at 6 GHz and initiating the first-ever survey at 18 GHz with the Sardinia Radio Telescope (SRT). Our strategy entailed rigorous observation sessions, totaling 36 hours, directed towards the Galactic Center and 72 selected TESS targets-making this the most comprehensive high-frequency technosignature search to date. Our narrowband signal search found no definitive evidence of drifting signals that could suggest an extraterrestrial origin from the surveyed regions. Nevertheless, our efforts have enabled us to set new constraints on the presence of radio emissions from approximately $5\times 10^{5}$ stars, establishing an isotropic radiated power limit of $1.8\times 10^{19} W$. We also provide a comparative analysis of the 'hits' recorded across both frequencies to highlight the significance of pursuing technosignature searches at higher frequencies, where the spectral landscape is less congested and more conducive to detection., Comment: Submitted to Acta Astronautica

Learning from Demonstration (LfD) is a powerful type of machine learning that can allow novices to teach and program robots to complete various tasks. However, the learning process for these systems may still be difficult for novices to interpret and understand, making effective teaching challenging. Explainable artificial intelligence (XAI) aims to address this challenge by explaining a system to the user. In this work, we investigate XAI within LfD by implementing an adaptive explanatory feedback system on an inverse reinforcement learning (IRL) algorithm. The feedback is implemented by demonstrating selected learnt trajectories to users. The system adapts to user teaching by categorizing and then selectively sampling trajectories shown to a user, to show a representative sample of both successful and unsuccessful trajectories. The system was evaluated through a user study with 26 participants teaching a robot a navigation task. The results of the user study demonstrated that the proposed explanatory feedback system can improve robot performance, teaching efficiency and user understanding of the robot., Comment: 8 Pages, 9 Figures, 2 Tables

We present new results from the ASTRID simulation from $z=3$ to $z=0.5$, covering the epoch of cosmic noon. The galaxy stellar mass function, as well as the black hole mass and luminosity functions in ASTRID, exhibit good agreement with recent observational constraints. We study the $M_{\rm BH}$-$M_*$ scaling relation and its connections to AGN luminosity, galaxy color, and star formation rate, demonstrating that AGN feedback plays a crucial role in the quenching of massive galaxies ($M_*>10^{10.5} M_{\odot}$). Although AGN feedback suppresses star formation through quenching, AGN-host galaxies still exhibit statistically higher levels of star formation compared to inactive ones, due to the positive correlation between AGN activity and star formation, both fueled by a shared gas reservoir. The fraction of quiescent galaxies in ASTRID increases with both galaxy mass and redshift evolution, aligning well with observational trends. We find that different quenching mechanisms can leave distinct morphological imprints on quenched galaxies. Massive, compact quiescent galaxies typically experience shorter quenching timescales, have younger central regions, and host overmassive black holes. This is usually due to a compaction-like quenching mechanism that funnels gas into the galaxy center, leading to starbursts and triggering AGN kinetic feedback. In contrast, quiescent galaxies with more diffuse morphologies generally experience `inside-out' quenching, which is characterized by older central regions compared to the outskirts. These galaxies typically experience longer quenching timescales due to quenching processes operating on a larger halo scale, which gradually deplete the galactic star-forming gas. Data of the \astrid simulation down to $z=0.5$ is available at \url{https://astrid.psc.edu}., Comment: Summited to APJ, comments are welcome

Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly supplement low-resolution (LR) runs with statistically correct, fine details. The SR technique preserves large-scale structures by conditioning on a low-resolution (LR) version of the simulation. On smaller scales, the generative deep learning (DL) process is stochastic, resulting in numerous possible SR realizations, each with unique small-scale structures. Validation of SR then relies on making sure that a specific statistic of interest is accurately reproduced by comparing SR and high resolution (HR) runs. In this study, we develop an emulator designed to reproduce the individual small-scale structures of an HR simulation as closely as possible. We process an SR realization alongside a specific High-Resolution Initial Condition (HRIC), transforming the SR output to emulate the results of a full simulation with that HRIC. By comparing visualizations, individual halo measures and cross-correlating Fourier modes we show that the emulated SR runs closely align with the corresponding HR simulation, even on length scales an order of magnitude smaller than the LR run. Additionally, small halos are trained to match the HR simulation, and the subhalo mass function is more accurately reproduced. These results show the promise of this method for generating numerous fast and accurate simulations and mock observations for large galaxy surveys., Comment: 16 pages, 15 figures

Artificial Intelligence (AI) advancements have enabled the development of Large Language Models (LLMs) that can perform a variety of tasks with remarkable semantic understanding and accuracy. ChatGPT is one such LLM that has gained significant attention due to its impressive capabilities for assisting in various knowledge-intensive tasks. Due to the knowledge-intensive nature of engineering secure software, ChatGPT's assistance is expected to be explored for security-related tasks during the development/evolution of software. To gain an understanding of the potential of ChatGPT as an emerging technology for supporting software security, we adopted a two-fold approach. Initially, we performed an empirical study to analyse the perceptions of those who had explored the use of ChatGPT for security tasks and shared their views on Twitter. It was determined that security practitioners view ChatGPT as beneficial for various software security tasks, including vulnerability detection, information retrieval, and penetration testing. Secondly, we designed an experiment aimed at investigating the practicality of this technology when deployed as an oracle in real-world settings. In particular, we focused on vulnerability detection and qualitatively examined ChatGPT outputs for given prompts within this prominent software security task. Based on our analysis, responses from ChatGPT in this task are largely filled with generic security information and may not be appropriate for industry use. To prevent data leakage, we performed this analysis on a vulnerability dataset compiled after the OpenAI data cut-off date from real-world projects covering 40 distinct vulnerability types and 12 programming languages. We assert that the findings from this study would contribute to future research aimed at developing and evaluating LLMs dedicated to software security., Comment: Accepted for publication at International Conference on Trust, Privacy and Security - 2024

Communication is essential for successful interaction. In human-robot interaction, implicit communication enhances robots' understanding of human needs, emotions, and intentions. This paper introduces a method to foster implicit communication in HRI without explicitly modeling human intentions or relying on pre-existing knowledge. Leveraging Transfer Entropy, we modulate influence between agents in social interactions in scenarios involving either collaboration or competition. By integrating influence into agents' rewards within a partially observable Markov decision process, we demonstrate that boosting influence enhances collaboration or competition performance, while resisting influence diminishes performance. Our findings are validated through simulations and real-world experiments with human participants., Comment: 17 pages, 8 figures, preprint

The unfolding of detector effects in experimental data is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel unfolding approach using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. We test our approach by training a single cDDPM to perform multidimensional particle-wise unfolding for a variety of physics processes, including those not seen during training. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions.

Many technical, test design, and implementation questions are involved in designing new statewide assessments. These are all critical, shaping often underexamined aspects of testing: student test experience and families' perceptions of testing in this new structure. Although the state outreach to students and families is needed generally, it is especially vital to elevate the experiences and perspectives of historically marginalized students and families, such as students of color, students with disabilities, and English learners (ELs), to understand how new test designs can best meet the needs of all students and help close inequitable achievement gaps. This report identifies four states that have taken different approaches in designing new through-year assessments: Delaware, Florida, Nebraska, and Texas. In each state, the authors spoke with state assessment directors and district leaders to learn more about how the tests worked for students, families, and educators. In all states except Texas, which is in the early stages of its pilot, the authors also spoke with Black and Latino parents and parents of students with disabilities to hear about their experiences with the new assessments.

We provide an overview of experiments exploring resonances in the collision of ultracold clouds of atoms. Using a laser-based accelerator that capitalizes on the energy resolution provided by the ultracold atomic setting, we unveil resonance phenomena such as Feshbach and shape resonances in their quintessential form by literally photographing the halo of outgoing scattered atoms. We exploit the tunability of magnetic Feshbach resonances to instigate an interplay between scattering resonances. By experimentally recording the scattering in a parameter space spanned by collision energy and magnetic field, we capture the imprint of the $S$-matrix pole flow in the complex energy plane. After revisiting experiments that place a Feshbach resonance in the proximity of a shape resonance and an anti-bound state, respectively, we discuss the possibility of using $S$-matrix pole interplay between two Feshbach resonances to create a bound-state-in-the-continuum., Comment: European Conference on Few-Body Problems in Physics (EFB25) 2023---Invited Plenary Talk

Collaborative robots must effectively communicate their internal state to humans to enable a smooth interaction. Nonverbal communication is widely used to communicate information during human-robot interaction, however, such methods may also be misunderstood, leading to communication errors. In this work, we explore modulating the acoustic parameter values (pitch bend, beats per minute, beats per loop) of nonverbal auditory expressions to convey functional robot states (accomplished, progressing, stuck). We propose a reinforcement learning (RL) algorithm based on noisy human feedback to produce accurately interpreted nonverbal auditory expressions. The proposed approach was evaluated through a user study with 24 participants. The results demonstrate that: 1. Our proposed RL-based approach is able to learn suitable acoustic parameter values which improve the users' ability to correctly identify the state of the robot. 2. Algorithm initialization informed by previous user data can be used to significantly speed up the learning process. 3. The method used for algorithm initialization strongly influences whether participants converge to similar sounds for each robot state. 4. Modulation of pitch bend has the largest influence on user association between sounds and robotic states., Comment: 8 Pages, Accepted to RA-L March 2024

The Universal Dependencies (UD) project has created an invaluable collection of treebanks with contributions in over 140 languages. However, the UD annotations do not tell the full story. Grammatical constructions that convey meaning through a particular combination of several morphosyntactic elements -- for example, interrogative sentences with special markers and/or word orders -- are not labeled holistically. We argue for (i) augmenting UD annotations with a 'UCxn' annotation layer for such meaning-bearing grammatical constructions, and (ii) approaching this in a typologically informed way so that morphosyntactic strategies can be compared across languages. As a case study, we consider five construction families in ten languages, identifying instances of each construction in UD treebanks through the use of morphosyntactic patterns. In addition to findings regarding these particular constructions, our study yields important insights on methodology for describing and identifying constructions in language-general and language-particular ways, and lays the foundation for future constructional enrichment of UD treebanks., Comment: LREC-COLING 2024

High-energy neutrinos could be produced in the interaction of charged cosmic rays with matter or radiation surrounding astrophysical sources. To look for transient sources associated with neutrino emission, a follow-up program of neutrino alerts has been operating within the ANTARES Collaboration since 2009. This program, named TAToO, has triggered robotic optical telescopes (MASTER, TAROT, ROTSE and the SVOM ground based telescopes) immediately after the detection of any relevant neutrino candidate and scheduled several observations in the weeks following the detection. A subset of ANTARES events with highest probabilities of being of cosmic origin has also been followed by the Swift and the INTEGRAL satellites, the Murchison Widefield Array radio telescope and the H.E.S.S. high-energy gamma-ray telescope. The results of twelve years of observations are reported. No optical counterpart has been significantly associated with an ANTARES candidate neutrino signal during image analysis. Constraints on transient neutrino emission have been set. In September 2015, ANTARES issued a neutrino alert and during the follow-up, a potential transient counterpart was identified by Swift and MASTER. A multi-wavelength follow-up campaign has allowed to identify the nature of this source and has proven its fortuitous association with the neutrino. The return of experience is particularly important for the design of the alert system of KM3NeT, the next generation neutrino telescope in the Mediterranean Sea., Comment: 27 pages, 14 figures, submitted to JCAP

The SETI Ellipsoid is a strategy for technosignature candidate selection which assumes that extraterrestrial civilizations who have observed a galactic-scale event -- such as supernova 1987A -- may use it as a Schelling point to broadcast synchronized signals indicating their presence. Continuous wide-field surveys of the sky offer a powerful new opportunity to look for these signals, compensating for the uncertainty in their estimated time of arrival. We explore sources in the TESS continuous viewing zone, which corresponds to 5% of all TESS data, observed during the first three years of the mission. Using improved 3D locations for stars from Gaia Early Data Release 3, we identified 32 SN 1987A SETI Ellipsoid targets in the TESS continuous viewing zone with uncertainties better than 0.5 ly. We examined the TESS light curves of these stars during the Ellipsoid crossing event and found no anomalous signatures. We discuss ways to expand this methodology to other surveys, more targets, and different potential signal types., Comment: 17 pages, 6 figures, AJ published

We present mock JWST observations for more than 250,000 different galaxies from the Astrid simulation with $3 \leq z \leq 6$. The mock observations are made using the BPASS stellar SED model, and a simple dust model. They are then viewed through NIRCam filters, convolved with a PSF, have noise added, and are drizzled together to emulate the Cosmic Evolution Early Release Science (CEERS) survey. We analyse this dataset by computing a number of morphological measures and find our catalog to have comparable statistics to similar mock catalogs, and the first release of CEERS data. We find that most of the Sersic indices of galaxies in our redshift range are lower than observed, with most having n less than one. Additionally, we observe the sizes of galaxies of all masses to increase from redshift z=6 to redshift z=3 consistent with other results. The number of galaxies in our catalog allows us to examine how relationships like the mass-size relation evolve with redshift, and compare the accuracy of a variety of traditional galaxy classification techniques (Sersic fit, Asymmetry-Concentration, and Gini-$M_{20}$) within our redshift range. We find the mass-size relation to be nearly flat at redshift z=6, and consistently increases as redshift decreases, and find the galaxy classification methods have minimal correlation with each other in our redshift range. We also investigate the impact that different stages of our imaging pipeline have on these morphological measures to determine how robust mock catalogs are to different choices at each step. Finally, we test the addition of incorporating light from AGNs into our pipeline and find that while the population of galaxies that have significant AGN luminosity is low, those galaxies do tend to have higher Sersic indices once the AGN luminosity is added, rectifying some of the systematic bias towards lower Sersic indices present in our dataset., Comment: 17 pages, 14 figures

We present a novel method for anomaly detection in Solar System object data, in preparation for the Legacy Survey of Space and Time. We train a deep autoencoder for anomaly detection and use the learned latent space to search for other interesting objects. We demonstrate the efficacy of the autoencoder approach by finding interesting examples, such as interstellar objects, and show that using the autoencoder, further examples of interesting classes can be found. We also investigate the limits of classic unsupervised approaches to anomaly detection through the generation of synthetic anomalies and evaluate the feasibility of using a supervised learning approach. Future work should consider expanding the feature space to increase the variety of anomalies that can be uncovered during the survey using an autoencoder., Comment: Accepted by AJ

We study dual AGN host galaxy morphologies at $z=2$ using the ASTRID simulation, selecting black hole (BH) pairs with small separation ($\Delta r<30\rm{kpc}$), high mass ($M_{\text{BH,12}}>10^7M_\odot$), and luminosity ($L_{\text{bol,12}}>10^{43}\rm{erg/s}$). We kinematically decompose (using MORDOR) $\sim1000$ dual AGN hosts into standard components - a `disk' (thin and thick disk, pseudo-bulge) and 'bulge' (bulge and halo) and define disk-dominated galaxies by the disk-to-total $D/T\geq0.5$. In ASTRID, $60.9\pm2.1\%$ of dual AGN hosts (independent of separation) are disk-dominated, with the $D/T$ distribution peaking at $\sim0.7$. Notably, hosts of BH pairs have similar morphologies (most either both disk or bulge-dominated). In dual-AGN hosts, the $D/T$ increases from $\sim17\% $ at $M_{\rm *}\sim 10^{9} M_{\odot}$ to $ 64\% $ for $M_{\rm *} \sim 10^{11.5} M_{\odot}$, and the pseudo-bulge is the dominant component of the disk fraction at the high mass end. Moreover, dual AGN hosts exhibit a higher fraction of disk/large pseudo-bulge than single-AGN hosts. The Disk-to-Total ratio is approximately constant with BH mass or AGN luminosity. We also create mock images of dual AGN host galaxies, employing morphological fitting software Statmorph to calculate morphological parameters and compare them with our kinematic decomposition results. Around $83.3\pm2.4\%$ of galaxies display disk-like profiles, of which $\sim60.7\pm2.2\%$ are kinematically confirmed as disks. Se\'rsic indices and half-mass radii of dual AGN host galaxies align with observational measurements from HST at $z\sim2$. Around $34\%$ are identified as mergers from the $\text{Gini}-M_{20}$ relation. We find two dual AGN hosted by galaxies that exhibit disk-like se\'rsic index $n_{12}<1$ and $(D/T)_{12}>0.5$, which are in remarkable agreement with properties of recently discovered dual quasars in disk galaxies at $z\sim 2$., Comment: 17 pages, 14 figures, submitted to the Open Journal of Astrophysics

The elusive massive black hole (MBH) seeds stand to be revealed by the Laser Space Antenna Interferometer through mergers. As an aftermath of galaxy mergers, MBH coalescence is a vastly multi-scale process connected to galaxy formation. We introduce the "Massive black hole Assembly in Galaxies Informed by Cosmological Simulations" (MAGICS) suite, with galaxy/MBH properties and orbits recovered from large-volume cosmological simulation ASTRID. The simulations include subgrid star formation, supernovae feedback, and MBH accretion/feedback. In this first suite, we extract fifteen representative galaxy mergers with seed MBHs to examine their dynamics at an improved mass and spatial resolution (by $\sim2000$ and $\sim20$) and follow MBH orbits down to $\sim10\,\text{pc}$. We find that the seed MBH energy loss and orbital decay are largely governed by global torques induced by the galaxy merger process on scales resolvable by cosmological simulations. Specifically, pairs sink quickly if their orbits shrink rapidly below $1\,\text{kpc}$ during the first $\sim200\,\text{Myr}$ of pairing due to effective energy loss in major galaxy mergers, whereas MBHs gaining energy in minor galaxy mergers with head-on collisions are likely to stall. High initial eccentricities ($e_\text{init}>0.5$) and high stellar densities at kpc scales ($\rho_\text{star}>0.05\,M_\odot/\text{pc}^3$) also lead to most efficient decays. $\sim50\%$ high-redshift seed MBH pairs experience consecutive galaxy mergers and are more likely to stall at $\sim1\,\text{kpc}$. For a subset of systems, we carry out N-Body re-simulations until binary formation and find that some stalled systems merge at high-z when embedded in sufficient nuclear star clusters., Comment: 21 pages, 20 Figures. Submitted to The Open Journal of Astrophysics. Comments welcome!

Never before has the detection and characterization of exoplanets via transit photometry been as promising and feasible as it is now, due to the increasing breadth and sensitivity of time domain optical surveys. Past works have made use of phase-folded stellar lightcurves in order to study the properties of exoplanet transits, because this provides the highest signal that a transit is present at a given period and ephemeris. Characterizing transits on an individual, rather than phase-folded, basis is much more challenging due to the often low signal-to-noise ratio (SNR) of lightcurves, missing data, and low sampling rates. However, by phase-folding a lightcurve we implicitly assume that all transits have the same expected properties, and lose all information about the nature and variability of the transits. We miss the natural variability in transit shapes, or even the deliberate or inadvertent modification of transit signals by an extraterrestrial civilization (for example, via laser emission or orbiting megastructures). In this work, we develop an algorithm to search stellar lightcurves for individual anomalous (in timing or depth) transits, and we report the results of that search for 218 confirmed transiting exoplanet systems from Kepler., Comment: 11 pages, 8 figures. Accepted to The Astronomical Journal