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Assigning upper elementary grade teachers to teach their strongest subjects to multiple classes ("departmentalizing"), rather than teaching all subjects to a single class, ("self-contained instruction") could mean more specialized instructional expertise in the classroom or focus for teacher planning time and professional development. This study examined the experiences of 90 schools that either voluntarily switched to departmentalized instruction for up to two years or continued with self-contained teaching in 4th and 5th grade classes beginning in fall 2019. The findings show that schools that switched were able to implement the key steps needed to departmentalize instruction but struggled with aspects of the approach. Teachers' reported experiences were consistent with some of both the benefits and challenges that prior research had hypothesized. Although the pandemic significantly disrupted instruction and the study activities, school and teacher experiences during this challenging time may inform schools and districts considering adopting departmentalized instruction.

This appendix is a companion to the report "Evaluation of Departmentalized Instruction in Elementary Schools: Exploring Implementation Experiences." The appendix provides additional information about the study, which sought to explore schools' implementation of departmentalized instruction, teachers' experiences with the strategy, and how the strategy was related to key outcomes. This additional information includes details on departmentalized instruction (Section A), study design and execution (Section B), key findings presented in the report (Section C), and additional findings that are not included in the report but provide important context (Section D).

The primary purpose of this research study was to evaluate the efficacy of BASE, a self-paced online mental health education preventive intervention with middle school students. Two hundred ninety-five adolescent students were randomly assigned to receive BASE modules (n = 156) in a regular education classroom setting over a 5-week period or to a wait-list control (CO) group (n = 139). Change in student- and teacher-report outcome measures was investigated. Students in the BASE condition showed significant gains in mental health knowledge and teacher-reported school engagement over the intervention period whereas CO students showed declines in these areas. In addition, students who spent more time engaged in the BASE intervention modules showed significantly greater gains in BASE mental health knowledge. Because our study sample included a large percentage of Hispanic students (44%), we were able to conduct follow-up analyses to test for differential intervention effects by demographic sub-groups. Findings revealed use of the BASE modules were particularly positively impactful for Hispanic students, including positive changes in self-reported self-efficacy and school engagement as well as life skills over the intervention period compared to Hispanic students in the CO group. Discussion focuses on the potential for digital universal mental health intervention in schools. Tables and figures are appended.

We propose Greedy Topology-Aware Quantum Circuit Partitioning (GTQCP), a novel quantum gate circuit partitioning method which partitions circuits by applying a greedy heuristic to the qubit dependency graph of the circuit. GTQCP is compared against three other gate partitioning methods, two of which (QuickPartitioner and ScanPartitioner) are part of the Berkley Quantum Synthesis Toolkit. GTQCP is shown to have 18% run time improvement ratio over the fastest approach (QuickPartitioner), and a 96% improvement over the highest quality approach (ScanPartitioner). The algorithm also demonstrates nearly identical result quality (number of partitions) compared with ScanPartitioner, and a 38% quality improvement over QuickPartitioner., Comment: 6 pages, 4 figures, 3 tables

Writing compelling fiction is a multifaceted process combining elements such as crafting a plot, developing interesting characters, and using evocative language. While large language models (LLMs) show promise for story writing, they currently rely heavily on intricate prompting, which limits their use. We propose Agents' Room, a generation framework inspired by narrative theory, that decomposes narrative writing into subtasks tackled by specialized agents. To illustrate our method, we introduce Tell Me A Story, a high-quality dataset of complex writing prompts and human-written stories, and a novel evaluation framework designed specifically for assessing long narratives. We show that Agents' Room generates stories that are preferred by expert evaluators over those produced by baseline systems by leveraging collaboration and specialization to decompose the complex story writing task into tractable components. We provide extensive analysis with automated and human-based metrics of the generated output., Comment: Under review as a conference paper at ICLR 2025

We have discovered a triply eclipsing triple-star system, TIC 290061484, with the shortest known outer period, Pout, of only 24.5 days. This "eclipses" the previous record set by lambda Tauri at 33.02 days, which held for 68 yr. The inner binary, with an orbital period of Pin = 1.8 days, produces primary and secondary eclipses and exhibits prominent eclipse timing variations with the same periodicity as the outer orbit. The tertiary star eclipses, and is eclipsed by, the inner binary with pronounced asymmetric profiles. The inclinations of both orbits evolve on observable timescales such that the third-body eclipses exhibit dramatic depth variations in TESS data. A photodynamical model provides a complete solution for all orbital and physical parameters of the triple system, showing that the three stars have masses of 6.85, 6.11, and 7.90 MSun, radii near those corresponding to the main sequence, and Teff in the range of 21,000-23,700 K. Remarkably, the model shows that the triple is in fact a subsystem of a hierarchical 2+1+1 quadruple with a distant fourth star. The outermost star has a period of ~3200 days and a mass comparable to the stars in the inner triple. In ~20 Myr, all three components of the triple subsystem will merge, undergo a Type II supernova explosion, and leave a single remnant neutron star. At the time of writing, TIC 290061484 is the most compact triple system and one of the tighter known compact triples (i.e., Pout/Pin = 13.7)., Comment: 27 pages, 13 figures, 6 tables

As the field of multi-agent reinforcement learning (MARL) progresses towards larger and more complex environments, achieving strong performance while maintaining memory efficiency and scalability to many agents becomes increasingly important. Although recent research has led to several advanced algorithms, to date, none fully address all of these key properties simultaneously. In this work, we introduce Sable, a novel and theoretically sound algorithm that adapts the retention mechanism from Retentive Networks to MARL. Sable's retention-based sequence modelling architecture allows for computationally efficient scaling to a large number of agents, as well as maintaining a long temporal context, making it well-suited for large-scale partially observable environments. Through extensive evaluations across six diverse environments, we demonstrate how Sable is able to significantly outperform existing state-of-the-art methods in the majority of tasks (34 out of 45, roughly 75\%). Furthermore, Sable demonstrates stable performance as we scale the number of agents, handling environments with more than a thousand agents while exhibiting a linear increase in memory usage. Finally, we conduct ablation studies to isolate the source of Sable's performance gains and confirm its efficient computational memory usage. Our results highlight Sable's performance and efficiency, positioning it as a leading approach to MARL at scale.

We analyzed the performance of Convolutional Autoencoders in generating reduced-order representations of 2D Rayleigh-B\'enard flows at $Pr=1$ and Rayleigh numbers extending from $10^6$ to $10^8$, capturing the range where the flow transitions to turbulence. We present a way of estimating the minimum number of dimensions needed by the Autoencoders to capture all the relevant physical scales of the system that is more apt for highly multiscale flows than previous criteria applied to lower dimensional systems. We compare our architecture with two regularized variants as well as with linear methods, and find that manually fixing the dimension of the latent space produces the best results. We show how the estimated minimum dimension presents a sharp increase around $Ra\sim 10^7$, when the flow starts to transition to turbulence. Furthermore, we show how this dimension does not follow the same scaling as the physically relevant scales, such as the dissipation lengthscale and the thermal boundary layer., Comment: 21 pages, 18 figures

Neutrinos described as an open quantum system may interact with the environment which introduces stochastic perturbations to their quantum phase. This mechanism leads to a loss of coherence along the propagation of the neutrino $-$ a phenomenon commonly referred to as decoherence $-$ and ultimately, to a modification of the oscillation probabilities. Fluctuations in space-time, as envisaged by various theories of quantum gravity, are a potential candidate for a decoherence-inducing environment. Consequently, the search for decoherence provides a rare opportunity to investigate quantum gravitational effects which are usually beyond the reach of current experiments. In this work, quantum decoherence effects are searched for in neutrino data collected by the KM3NeT/ORCA detector from January 2020 to November 2021. The analysis focuses on atmospheric neutrinos within the energy range of a few GeV to $100\,\mathrm{GeV}$. Adopting the open quantum system framework, decoherence is described in a phenomenological manner with the strength of the effect given by the parameters $\Gamma_{21}$ and $\Gamma_{31}$. Following previous studies, a dependence of the type $\Gamma_{ij} \propto (E/E_0)^n$ on the neutrino energy is assumed and the cases $n = -2,-1$ are explored. No significant deviation with respect to the standard oscillation hypothesis is observed. Therefore, $90\,\%$ CL upper limits are estimated as $\Gamma_{21} < 4.6\cdot 10^{-21}\,$GeV and $\Gamma_{31} < 8.4\cdot 10^{-21}\,$GeV for $n = -2$, and $\Gamma_{21} < 1.9\cdot 10^{-22}\,$GeV and $\Gamma_{31} < 2.7\cdot 10^{-22}\,$GeV for $n = -1$, respectively., Comment: 17 pages, 5 figures

Precise mass measurements of the $^{108, 110, 112, 114, 116}$Rh ground and isomeric states were performed using the Canadian Penning Trap at Argonne National Laboratory, showing a good agreement with recent JYFLTRAP measurements. A new possible isomeric state of $^{114}$Rh was also observed. These isotopes are part of the longest odd-odd chain of identical spin-parity assignment, of 1$^+$, spanning $^{104-118}$Rh, despite being in a region of deformation. Theoretical calculations were performed to explain this phenomenon. In addition, multiquasiparticle blocking calculations were conducted to study the configuration of low-lying states in the odd-odd Rh nuclei and elucidate the observed anomalous isomeric yield ratio of $^{114}$Rh.

We further explore the notion of Ulam words considered by Bade, Cui, Labelle, and Li. We find that when interpreted as integers in a natural way, Ulam words appear to follow a new, unexplained distribution. Gaps between words and words of special type also reveal remarkable structure. By substantially increasing the number of computed terms, we are also able to sharpen some of the conjectures made by Bade et al.

Zhu and Melnykov (2018) develop a model to fit mixture models when the components are derived from the Manly transformation. Their EM algorithm utilizes Nelder-Mead optimization in the M-step to update the skew parameter, $\boldsymbol{\lambda}_g$. An alternative EM gradient algorithm is proposed, using one step of Newton's method, when initial estimates for the model parameters are good.

We present the largest Galactic neutral hydrogen HI absorption survey to date, utilizing the Australian SKA Pathfinder Telescope at an unprecedented spatial resolution of 30''. This survey, GASKAP-HI, unbiasedly targets 2,714 continuum background sources over 250 square degrees in the direction of the Magellanic Clouds, a significant increase compared to a total of 373 sources observed by previous Galactic absorption surveys across the entire Milky Way. We aim to investigate the physical properties of cold (CNM) and warm (WNM) neutral atomic gas in the Milky Way foreground, characterized by two prominent filaments at high Galactic latitudes (between $-45^{\circ}$ and $-25^{\circ}$). We detected strong HI absorption along 462 lines of sight above the 3$\sigma$ threshold, achieving an absorption detection rate of 17%. GASKAP-HI's unprecedented angular resolution allows for simultaneous absorption and emission measurements to sample almost the same gas clouds along a line of sight. A joint Gaussian decomposition is then applied to absorption-emission spectra to provide direct estimates of HI optical depths, temperatures, and column densities for the CNM and WNM components. The thermal properties of CNM components are consistent with those previously observed along a wide range of Solar neighborhood environments, indicating that cold HI properties are widely prevalent throughout the local interstellar medium. Across our region of interest, CNM accounts for ~30% of the total HI gas, with the CNM fraction increasing with column density toward the two filaments. Our analysis reveals an anti-correlation between CNM temperature and its optical depth, which implies that CNM with lower optical depth leads to a higher temperature., Comment: Largest Galactic HI Absorption Survey To Date (GASKAP-HI): Cold Atomic Gas in the Magellanic Cloud foreground using Australian SKA Pathfinder. This paper has 19 pages, 17 figures. This paper has been accepted for publication in Monthly Notices of the Royal Astronomical Society Main Journal

Today's most advanced multimodal models remain proprietary. The strongest open-weight models rely heavily on synthetic data from proprietary VLMs to achieve good performance, effectively distilling these closed models into open ones. As a result, the community is still missing foundational knowledge about how to build performant VLMs from scratch. We present Molmo, a new family of VLMs that are state-of-the-art in their class of openness. Our key innovation is a novel, highly detailed image caption dataset collected entirely from human annotators using speech-based descriptions. To enable a wide array of user interactions, we also introduce a diverse dataset mixture for fine-tuning that includes in-the-wild Q&A and innovative 2D pointing data. The success of our approach relies on careful choices for the model architecture details, a well-tuned training pipeline, and, most critically, the quality of our newly collected datasets, all of which will be released. The best-in-class 72B model within the Molmo family not only outperforms others in the class of open weight and data models but also compares favorably against proprietary systems like GPT-4o, Claude 3.5, and Gemini 1.5 on both academic benchmarks and human evaluation. We will be releasing all of our model weights, captioning and fine-tuning data, and source code in the near future. Select model weights, inference code, and demo are available at https://molmo.allenai.org.

The most general description of quantum evolution up to a time $\tau$ is a completely positive tracing preserving map known as a dynamical map $\hat{\Lambda}(\tau)$. Here we consider $\hat{\Lambda}(\tau)$ arising from suddenly coupling a system to one or more thermal baths with a strength that is neither weak nor strong. Given no clear separation of characteristic system/bath time scales $\hat{\Lambda}(\tau)$ is generically expected to be non-Markovian, however we do assume the ensuing dynamics has a unique steady state implying the baths possess a finite memory time $\tau_{\rm m}$. By combining several techniques within a tensor network framework we directly and accurately extract $\hat{\Lambda}(\tau)$ for a small number of interacting fermionic modes coupled to infinite non-interacting Fermi baths. We employ the Choi-Jamiolkowski isomorphism so that $\hat{\Lambda}(\tau)$ can be fully reconstructed from a single pure state calculation of the unitary dynamics of the system, bath and their replica auxillary modes up to time $\tau$. From $\hat{\Lambda}(\tau)$ we also compute the time local propagator $\hat{\mathcal{L}}(\tau)$. By examining the convergence with $\tau$ of the instantaneous fixed points of these objects we establish their respective memory times $\tau^{\Lambda}_{\rm m}$ and $\tau^{\mathcal{L}}_{\rm m}$. Beyond these times, the propagator $\hat{\mathcal{L}}(\tau)$ and dynamical map $\hat{\Lambda}(\tau)$ accurately describe all the subsequent long-time relaxation dynamics up to stationarity. Our numerical examples of interacting spinless Fermi chains and the single impurity Anderson model demonstrate regimes where our approach can offer a significant speedup in determining the stationary state compared to directly simulating the long-time limit., Comment: 12 pages, 10 figures

Myoelectric prosthetic hands are typically controlled to move between discrete positions and do not provide sensory feedback to the user. In this work, we present and evaluate a closed-loop, continuous myoelectric prosthetic hand controller, that can continuously control the position of multiple degrees of freedom of a prosthesis while rendering proprioceptive feedback to the user via a haptic feedback armband. Twenty-eight participants without and ten participants with limb difference were recruited to holistically evaluate the physical and psychological effects of the controller via isolated control and sensory tasks, dexterity assessments, embodiment and task load questionnaires, and post-study interviews. The combination of proprioceptive feedback and continuous control enabled accurate positioning, to within 10% mean absolute motor position error, and grasp-force modulation, to within 20% mean absolute motor force error, and restored blindfolded object identification ability to open-loop discrete controller levels. Dexterity assessment and embodiment questionnaire results revealed no significant physical performance or psychological embodiment differences between control types, with the exception of perceived sensation, which was significantly higher (p < 0.001) for closed-loop controllers. Key differences between participants with and without upper limb difference were identified, including in perceived body completeness and frustration, which can inform future prosthesis development and rehabilitation., Comment: 17 pages, 5 figures, 1 table. Submitted to Scientific Reports

The use of machine learning (ML) in critical domains such as medicine poses risks and requires regulation. One requirement is that decisions of ML systems in high-risk applications should be human-understandable. The field of "explainable artificial intelligence" (XAI) seemingly addresses this need. However, in its current form, XAI is unfit to provide quality control for ML; it itself needs scrutiny. Popular XAI methods cannot reliably answer important questions about ML models, their training data, or a given test input. We recapitulate results demonstrating that popular XAI methods systematically attribute importance to input features that are independent of the prediction target. This limits their utility for purposes such as model and data (in)validation, model improvement, and scientific discovery. We argue that the fundamental reason for this limitation is that current XAI methods do not address well-defined problems and are not evaluated against objective criteria of explanation correctness. Researchers should formally define the problems they intend to solve first and then design methods accordingly. This will lead to notions of explanation correctness that can be theoretically verified and objective metrics of explanation performance that can be assessed using ground-truth data.

SN 2023tsz is a Type Ibn supernova (SNe Ibn) discovered in an extremely low-mass host. SNe Ibn are an uncommon subtype of stripped-envelope core-collapse SNe. They are characterised by narrow helium emission lines in their spectra and are believed to originate from the collapse of massive Wolf-Rayet (WR) stars, though their progenitor systems still remain poorly understood. In terms of energetics and spectrophotometric evolution, SN 2023tsz is largely a typical example of the class, although line profile asymmetries in the nebular phase are seen, which may indicate the presence of dust formation or unshocked circumstellar material. Intriguingly, SN 2023tsz is located in an extraordinarily low-mass host galaxy that is in the 2nd percentile for SESN host masses and star formation rates (SFR). The host has a radius of 1.0 kpc, a $g$-band absolute magnitude of $-12.73$, and an estimated metallicity of $\log(Z_{*}/Z_{\odot}$) = $-1.56$. The SFR and metallicity of the host galaxy raise questions about the progenitor of SN 2023tsz. The low SFR suggests that a star with sufficient mass to evolve into a WR would be uncommon in this galaxy. Further, the very low-metallicity is a challenge for single stellar evolution to enable H and He stripping of the progenitor and produce a SN Ibn explosion. The host galaxy of SN 2023tsz adds another piece to the ongoing puzzle of SNe Ibn progenitors, and demonstrates that they can occur in hosts too faint to be observed in contemporary sky surveys at a more typical SN Ibn redshift., Comment: 14 pages, 10 figures, submitted to MNRAS

We consider the possibility of indirect detection of dark sector processes by investigating a novel form of interaction between ambient dark matter (DM) and primordial black holes (PBHs). The basic scenario we envisage is that the ambient DM is ``dormant'', \ie, it has interactions with the SM, but its potential for an associated SM signal is not realized for various reasons. We argue that the presence of PBHs with active Hawking radiation (independent of any DM considerations) can act as a catalyst in this regard by overcoming the aforementioned bottlenecks. The central point is that PBHs radiate all types of particles, whether in the standard model (SM) or beyond (BSM), which have a mass at or below their Hawking temperature. The emission of such radiation is ``democratic" (up to the particle spin), since it is based on a coupling of sorts of gravitational origin. In particular, such shining of (possibly dark sector) particles onto ambient DM can then activate the latter into giving potentially observable SM signals. We illustrate this general mechanism with two specific models. First, we consider asymmetric DM, which is characterized by an absence of ambient anti-DM, and consequently the absence of DM indirect detection signals. In this case, PBHs can ``resurrect'' such a signal by radiating anti-DM, which then annihilates with ambient DM in order to give SM particles such as photons. In our second example, we consider the PBH emission of dark gauge bosons which can excite ambient DM into a heavier state (which is, again, not ambient otherwise), this heavier state later decays back into DM and photons. Finally, we demonstrate that we can obtain observable signals of these BSM models from asteroid-mass PBHs (Hawking radiating currently with $\sim \mathcal{O}(\mathrm{MeV})$ temperatures) at gamma-ray experiments such as AMEGO-X., Comment: 19 pages + 3 appendices, 9 figures

Following Hollins et al. [J. Phys.: Condens. Matter 29, 04LT01 (2017)], we invert the electronic ground state densities for various semiconducting and insulating solids calculated using several density functional approximations within the generalised Kohn-Sham (GKS) scheme, Hartree-Fock (HF) theory and the LDA+$U$ method, and benchmark against standard (semi-)local functionals. The band structures from the resulting local exchange-correlation (LXC) Kohn-Sham potential for these densities are then compared with the band structures of the original GKS method. We find the LXC potential obtained from the HF density systematically predicts band gaps in good agreement with experiment, even in strongly correlated transition metal monoxides (TMOs). Furthermore, we find that the HSE06 and PBE0 hybrid functionals yield similar densities and LXC potentials, and in weakly correlated systems, these potentials are similar to PBE. For LDA+$U$ densities, the LXC potential effectively reverses the flattening of bands caused by over-localisation by a large Hubbard-$U$ value, while for meta-GGAs, we find only small differences between the GKS and LXC results demonstrating that the non-locality of meta-GGAs is weak., Comment: 26 pages, 17 figures, 4 tables

Atomic masses are a foundational quantity in our understanding of nuclear structure, astrophysics and fundamental symmetries. The long-standing goal of creating a predictive global model for the binding energy of a nucleus remains a significant challenge, however, and prompts the need for precise measurements of atomic masses to serve as anchor points for model developments. We present precise mass measurements of neutron-rich Ru and Pd isotopes performed at the Californium Rare Isotope Breeder Upgrade facility at Argonne National Laboratory using the Canadian Penning Trap mass spectrometer. The masses of $^{108}$Ru, $^{110}$Ru and $^{116}$Pd were measured to a relative mass precision $\delta m/m \approx 10^{-8}$ via the phase-imaging ion-cyclotron-resonance technique, and represent an improvement of approximately an order of magnitude over previous measurements. These mass data were used in conjunction with the physically interpretable machine learning (PIML) model, which uses a mixture density neural network to model mass excesses via a mixture of Gaussian distributions. The effects of our new mass data on a Bayesian-updating of a PIML model are presented., Comment: 6 pages, 4 figures

A memory consistency model specifies the allowed behaviors of shared memory concurrent programs. At the language level, these models are known to have a non-trivial impact on the safety of program optimizations, limiting the ability to rearrange/refactor code without introducing new behaviors. Existing programming language memory models try to address this by permitting more (relaxed/weak) concurrent behaviors but are still unable to allow all the desired optimizations. A core problem is that weaker consistency models may also render optimizations unsafe, a conclusion that goes against the intuition of them allowing more behaviors. This exposes an open problem of the compositional interaction between memory consistency semantics and optimizations: which parts of the semantics correspond to allowing/disallowing which set of optimizations is unclear. In this work, we establish a formal foundation suitable enough to understand this compositional nature, decomposing optimizations into a finite set of elementary effects on program execution traces, over which aspects of safety can be assessed. We use this decomposition to identify a desirable compositional property (complete) that would guarantee the safety of optimizations from one memory model to another. We showcase its practicality by proving such a property between Sequential Consistency (SC) and $SC_{RR}$, the latter allowing independent read-read reordering over $SC$. Our work potentially paves way to a new design methodology of programming-language memory models, one that places emphasis on the optimizations desired to be performed.

Multimodal vector search offers a new paradigm for information retrieval by exposing numerous pieces of functionality which are not possible in traditional lexical search engines. While multimodal vector search can be treated as a drop in replacement for these traditional systems, the experience can be significantly enhanced by leveraging the unique capabilities of multimodal search. Central to any information retrieval system is a user who expresses an information need, traditional user interfaces with a single search bar allow users to interact with lexical search systems effectively however are not necessarily optimal for multimodal vector search. In this paper we explore novel capabilities of multimodal vector search applications utilising CLIP models and present implementations and design patterns which better allow users to express their information needs and effectively interact with these systems in an information retrieval context., Comment: 12 pages, 8 figures, CIKM 2024 MMSR Workshop

Recent psycholinguistic research has compared human reading times to surprisal estimates from language models to study the factors shaping human sentence processing difficulty. Previous studies have shown a strong fit between surprisal values from Transformers and reading times. However, standard Transformers work with a lossless representation of the entire previous linguistic context, unlike models of human language processing that include memory decay. To bridge this gap, this paper evaluates a modification of the Transformer model that uses ALiBi (Press et al., 2022), a recency bias added to attention scores. Surprisal estimates with ALiBi show an improved fit to human reading times compared to a standard Transformer baseline. A subsequent analysis of attention heads suggests that ALiBi's mixture of slopes -- which determine the rate of memory decay in each attention head -- may play a role in the improvement by helping models with ALiBi to track different kinds of linguistic dependencies.

Quantum computers can perform certain operations exponentially faster than classical computers, but designing quantum circuits is challenging. To that end, researchers used evolutionary algorithms to produce probabilistic quantum circuits that give the correct output more often than not for any input. They can be executed multiple times, with the outputs combined using a classical method (such as voting) to produce the final output, effectively creating a homogeneous ensemble of circuits (i.e., all identical). Inspired by n-version programming and ensemble learning, we developed a tool that uses an evolutionary algorithm to generate heterogeneous ensembles of circuits (i.e., all different), named QuEEn. We used it to evolve ensembles to solve the Iris classification problem. When using ideal simulation, we found the performance of heterogeneous ensembles to be greater than that of homogeneous ensembles to a statistically significant degree. When using noisy simulation, we still observed a statistically significant improvement in the majority of cases. Our results indicate that evolving heterogeneous ensembles is an effective strategy for improving the reliability of quantum circuits. This is particularly relevant in the current NISQ era of quantum computing where computers do not yet have good tolerance to quantum noise.

Understanding the role that magnetic fields play on the stage of galaxy formation requires accurate methods for inferring the properties of extragalactic magnetic fields. Radio synchrotron emission has been the most promising avenue to infer magnetic field strengths across galaxies, with the application of a central assumption: that galactic cosmic rays are in energy equipartition with the magnetic field. In this work, we leverage flexible synthetic observations of a high-resolution magnetohydrodynamic simulation of a Milky Way-like galaxy to review whether true equipartition is capable of reproducing radio observations of galaxies, and investigate its impact on the inference of magnetic field strengths when varying the properties and density distribution of the cosmic rays. We find that imposing equipartition (regardless of scale length) results in cosmic ray electron densities that are unable to generate either the amplitude or the shape of the radio intensity profiles typically observed in spiral galaxies. Instead, observationally motivated smooth distributions of cosmic ray electrons across the galaxy provide a remarkable match to observations. We further demonstrate that assuming equipartition with those mock observations can lead to significant overestimation of the magnetic field strength ($\sim10-50\times$). This overestimation varies with cosmic ray electron densities, cosmic ray spectrum power-law index, and galactic environment, aggravated in inter-arm regions and attenuated in star-forming regions. Our results promote caution when assuming equipartition in observations, and suggest that additional theoretical and numerical work is required to leverage the upcoming generation of radio observations poised to revolutionize our understanding of astrophysical magnetic fields., Comment: Submitted to ApJ, 26 pages, 12 figures

We conduct a systematic search for astrophysical transients using data from the Atacama Cosmology Telescope (ACT). The data were taken from 2017 to 2022 in three frequency bands spanning 77 GHz to 277 GHz. In this paper we present a pipeline for transient detection using single observation maps where each pixel of a map contains one observation with an integration time of approximately four minutes. We find 34 transient events at 27 unique locations. All but two of the transients are associated with Galactic stars and exhibit a wide range of properties. We also detect an event coincident with the classical nova, YZ Ret and one event consistent with a flaring active galactic nucleus. We notably do not detect any reverse shock emission from gamma ray bursts, a non-detection which is in tension with current models., Comment: 23 pages, 10 figures, 10 tables. First and second author share equal contributions. Article and accompanying data submitted to ApJ. Data tables will be made available upon publication

As Artificial Intelligence applications expand, the evaluation of models faces heightened scrutiny. Ensuring public readiness requires evaluation datasets, which differ from training data by being disjoint and ethically sourced in compliance with privacy regulations. The performance and fairness of face recognition systems depend significantly on the quality and representativeness of these evaluation datasets. This data is sometimes scraped from the internet without user's consent, causing ethical concerns that can prohibit its use without proper releases. In rare cases, data is collected in a controlled environment with consent, however, this process is time-consuming, expensive, and logistically difficult to execute. This creates a barrier for those unable to conjure the immense resources required to gather ethically sourced evaluation datasets. To address these challenges, we introduce the Synthetic Identity Generation pipeline, or SIG, that allows for the targeted creation of ethical, balanced datasets for face recognition evaluation. Our proposed and demonstrated pipeline generates high-quality images of synthetic identities with controllable pose, facial features, and demographic attributes, such as race, gender, and age. We also release an open-source evaluation dataset named ControlFace10k, consisting of 10,008 face images of 3,336 unique synthetic identities balanced across race, gender, and age, generated using the proposed SIG pipeline. We analyze ControlFace10k along with a non-synthetic BUPT dataset using state-of-the-art face recognition algorithms to demonstrate its effectiveness as an evaluation tool. This analysis highlights the dataset's characteristics and its utility in assessing algorithmic bias across different demographic groups.

Given that Large Language Models (LLMs) have made significant progress in writing code, can they now be used to autonomously reproduce results from research repositories? Such a capability would be a boon to the research community, helping researchers validate, understand, and extend prior work. To advance towards this goal, we introduce SUPER, the first benchmark designed to evaluate the capability of LLMs in setting up and executing tasks from research repositories. SUPERaims to capture the realistic challenges faced by researchers working with Machine Learning (ML) and Natural Language Processing (NLP) research repositories. Our benchmark comprises three distinct problem sets: 45 end-to-end problems with annotated expert solutions, 152 sub problems derived from the expert set that focus on specific challenges (e.g., configuring a trainer), and 602 automatically generated problems for larger-scale development. We introduce various evaluation measures to assess both task success and progress, utilizing gold solutions when available or approximations otherwise. We show that state-of-the-art approaches struggle to solve these problems with the best model (GPT-4o) solving only 16.3% of the end-to-end set, and 46.1% of the scenarios. This illustrates the challenge of this task, and suggests that SUPER can serve as a valuable resource for the community to make and measure progress.

Peephole optimization of quantum circuits provides a method of leveraging standard circuit synthesis approaches into scalable quantum circuit optimization. One application of this technique partitions an entire circuit into a series of peepholes and produces multiple approximations of each partitioned subcircuit. A single approximation of each subcircuit is then selected to form optimized result circuits. We propose a series of improvements to the final phase of this architecture, which include the addition of error awareness and a better method of approximating the correctness of the result. We evaluated these proposed improvements on a set of benchmark circuits using the IBMQ FakeWashington simulator. The results demonstrate that our best-performing method provides an average reduction in Total Variational Distance (TVD) and Jensen-Shannon Divergence (JSD) of 18.2% and 15.8%, respectively, compared with the Qiskit optimizer. This also constitutes an improvement in TVD of 11.4% and JSD of 9.0% over existing solutions., Comment: 8 pages, 4 figures, 1 table

We show that stable, freely suspended liquid crystal films can be made from the ferroelectric nematic ($\mathrm{N_F}$) phase and from the recently discovered polar, lamellar $\mathrm{SmZ_A}$ and $\mathrm{SmA_F}$ phases. The $\mathrm{N_F}$ films display two-dimensional, smectic-like parabolic focal conic textures comprising director/polarization bend that are a manifestation of the electrostatic suppression of director splay in the film plane. In the $\mathrm{SmZ_A}$ and $\mathrm{SmA_F}$ phases, the smectic layers orient preferentially normal to the film surfaces, a condition never found in typical thermotropic or lyotropic lamellar LC phases, with the $\mathrm{SmZ_A}$ films exhibiting focal-conic fan textures mimicking the appearance of typical smectics in glass cells when the layers are oriented normal to the plates, and the $\mathrm{SmA_F}$ films showing a texture of plaquettes of uniform in-plane orientation where both bend and splay are suppressed, separated by grain boundaries. The $\mathrm{SmA_F}$ phase can also be drawn into thin filaments, in which X-ray scattering reveals that the smectic layer planes are normal to the filament axis. Remarkably, the filaments are mechanically stable even if they break, forming free-standing, fluid filaments supported only at one end. The unique architectures of these films and filaments are stabilized by the electrostatic self-interaction of the liquid crystal polarization field, which enables the formation of confined, fluid structures that are fundamentally different from those of their counterparts made using previously known liquid crystal phases., Comment: Main paper 25 pages (5 figures); Supplement: 7 pages (7 figures)

Active grids operated with random protocols are a standard way to generate large Reynolds number turbulence in wind and water tunnels. But anomalies in the decay and third-order scaling of active-grid turbulence have been reported. We combine Laser Doppler Velocimetry and hot-wire anemometry measurements in a wind tunnel, with machine learning techniques and numerical simulations, to gain further understanding on the reasons behind these anomalies. Numerical simulations that incorporate the statistical anomalies observed in the experimental velocity field near the active grid can reproduce the experimental anomalies observed later in the decay. The results indicate that anomalies in experiments near the active grid introduce correlations in the flow that persist for long times, and result in the flow being statistically different from homogeneous and isotropic turbulence.

Building on VeriX (Verified eXplainability, arXiv:2212.01051), a system for producing optimal verified explanations for machine learning model outputs, we present VeriX+, which significantly improves both the size and the generation time of verified explanations. We introduce a bound propagation-based sensitivity technique to improve the size, and a binary search-based traversal with confidence ranking for improving time -- the two techniques are orthogonal and can be used independently or together. We also show how to adapt the QuickXplain (Junker 2004) algorithm to our setting to provide a trade-off between size and time. Experimental evaluations on standard benchmarks demonstrate significant improvements on both metrics, e.g., a size reduction of 38% on the GTSRB dataset and a time reduction of 90% on MNIST. We also explore applications of our verified explanations and show that explanation size is a useful proxy for both incorrectness detection and out-of-distribution detection.

We prove a conjecture of Graham and H\"aggkvist (1989), which states that any tree on $n$ edges decomposes the complete bipartite graph $K_{n,n}$. We do so by translating the decomposition problem into a labeling problem, namely $\vec{\beta}$-labeling (oriented beta-labeling). Our proof employs the polynomial method using a functional reformulation of the conjecture. We also introduce additional algebraic properties that the decomposition grants. A proof of the graceful tree conjecture (1967) follows as an immediate consequence of the current result., Comment: 23 pages, 6 figures

We develop a theory to analyze how structure in connectivity shapes the high-dimensional, internally generated activity of nonlinear recurrent neural networks. Using two complementary methods -- a path-integral calculation of fluctuations around the saddle point, and a recently introduced two-site cavity approach -- we derive analytic expressions that characterize important features of collective activity, including its dimensionality and temporal correlations. To model structure in the coupling matrices of real neural circuits, such as synaptic connectomes obtained through electron microscopy, we introduce the random-mode model, which parameterizes a coupling matrix using random input and output modes and a specified spectrum. This model enables systematic study of the effects of low-dimensional structure in connectivity on neural activity. These effects manifest in features of collective activity, that we calculate, and can be undetectable when analyzing only single-neuron activities. We derive a relation between the effective rank of the coupling matrix and the dimension of activity. By extending the random-mode model, we compare the effects of single-neuron heterogeneity and low-dimensional connectivity. We also investigate the impact of structured overlaps between input and output modes, a feature of biological coupling matrices. Our theory provides tools to relate neural-network architecture and collective dynamics in artificial and biological systems., Comment: 35 pages, 11 figures

We construct continuum directed polymer measures corresponding to the critical 2d stochastic heat flow (2d SHF) introduced by Caravenna, Sun, and Zygouras in their recent article [Inventiones mathematicae 233, 325--460 (2023)]. For this purpose, we prove a Chapman-Kolmogorov relation for the 2d SHF along with a related elementary conditional expectation formula. We explore some basic properties of the continuum polymer measures, with our main focus being on their second moments. In particular, we show that the form of their second moments is consistent with the family of continuum polymer measures, indexed by a disorder strength parameter, having a conditional Gaussian multiplicative chaos distributional interrelationship similar to that previously found in an analogous hierarchical toy model., Comment: 39 pages

By considering linear scattering of cold atoms inside an undriven high-finesse optical resonator, we experimentally demonstrate effects unique to a strongly coupled vacuum field. Arranging the atoms in an incommensurate lattice, with respect to the resonator mode, the scattering can be suppressed by destructive interference: resulting in a subradiant atomic array. We show however, that strong coupling leads to a drastic modification of the excitation spectrum, as evidenced by well-resolved vacuum Rabi splitting in the intensity of the fluctuations. Furthermore, we demonstrate a significant polarization rotation in the linear scattering off the subradiant array via Raman scattering induced by the strongly coupled vacuum field.

Calorimetric determination of enthalpies of mixing ($\Delta$H$_{\rm mix}$) of multicomponent molten salts often employs empirical models that lack parameters with clear physical interpretation (e.g., coordination numbers, molar volumes, and pair potentials). Although such physics informed models are not always needed, a thermodynamic understanding of the relationships between excess energies of mixing and local to intermediate solvation structures is particularly important for pyrochemical separation, as is the case for lanthanides (Ln), which are common neutron poisons and critical industrial elements found in spent nuclear fuels. Here we implement the molecular interaction volume model (MIVM) to synthesize information from experimentally measured $\Delta$H$_{\rm mix}$ (using high temperature melt drop calorimetry) and the distribution of solvation structures from ab initio molecular dynamics (AIMD) simulations. This was demonstrated by a case study of molten salt system consisted of LaCl$_3$ mixing with a eutectic LiCl-KCl (58mol% to 42mol%) at 873 K and 1133 K. The parameters modelled from MIVM were used to extrapolate excess Gibbs energy ($\Delta$G$_{\rm mix}$), and compositional dependence of La$^{3+}$ activity in the LaCl$_3$-(LiCl-KCl) system. In contrast, by AIMD or polarizable ion model (PIM) simulations, a significant deviation regarding the predicted $\Delta$H$_{\rm mix}$ was seen if computed directly from the molecular dynamic trajectories. The integrated experimental and simulation data within the MIVM formalism are generalizable to a wide variety of molten salts and demonstrate a significant improvement over currently employed methods to study molten salts for nuclear and separations sciences.

This review paper describes the energy-upgraded CEBAF accelerator. This superconducting linac has achieved 12 GeV beam energy by adding 11 new high-performance cryomodules containing eighty-eight superconducting cavities that have operated CW at an average accelerating gradient of 20 MV/m. After reviewing the attributes and performance of the previous 6 GeV CEBAF accelerator, we discuss the upgraded CEBAF accelerator system in detail with particular attention paid to the new beam acceleration systems. In addition to doubling the acceleration in each linac, the upgrade included improving the beam recirculation magnets, adding more helium cooling capacity to allow the newly installed modules to run cold, adding a new experimental hall, and improving numerous other accelerator components. We review several of the techniques deployed to operate and analyze the accelerator performance, and document system operating experience and performance. In the final portion of the document, we present much of the current planning regarding projects to improve accelerator performance and enhance operating margins, and our plans for ensuring CEBAF operates reliably into the future. For the benefit of potential users of CEBAF, the performance and quality measures for beam delivered to each of the experimental halls is summarized in the appendix., Comment: 66 pages, 73 figures, 21 tables

ARINC 429 is a ubiquitous data bus for civil avionics, enabling reliable communication between devices from disparate manufacturers. However, ARINC 429 lacks any form of encryption or authentication, making it an inherently insecure communication protocol and rendering any connected avionics vulnerable to a range of attacks. We constructed a hardware-in-the-loop simulator with ARINC 429 buses, explored these vulnerabilities, and identified their potential to deny, degrade, or disrupt aircraft capabilities. We performed a denial-of-service attack against a multi-function display via a compromised ARINC 429 bus using commercially available tools, which succeeded in disabling important navigational aids. This proven attack on physical avionics illustrates the risk inherent in ARINC 429 and the need for the ability to detect these attacks. One potential mitigation is an intrusion detection system (IDS) trained on data collected from the electrical properties of the physical bus. Although previous research has demonstrated the feasibility of an IDS on an ARINC 429 bus, no IDS has been trained on data generated by avionics hardware. To facilitate this, we recorded voltage traces and message history generated by avionics and adversarial devices on the ARINC 429 bus. To the best of our knowledge, this is the first publicly available collection of hardware-generated ARINC 429 signal data., Comment: 7 pages, 3 figures. Intended for publication in IEEE Transactions on Aerospace and Electronic Systems

Transiting giant exoplanets around M-dwarf stars (GEMS) are rare, owing to the low-mass host stars. However, the all-sky coverage of TESS has enabled the detection of an increasingly large number of them to enable statistical surveys like the \textit{Searching for GEMS} survey. As part of this endeavour, we describe the observations of six transiting giant planets, which includes precise mass measurements for two GEMS (K2-419Ab, TOI-6034b) and statistical validation for four systems, which includes validation and mass upper limits for three of them (TOI-5218b, TOI-5616b, TOI-5634Ab), while the fourth one -- TOI-5414b is classified as a `likely planet'. Our observations include radial velocities from the Habitable-zone Planet Finder on the Hobby-Eberly Telescope, and MAROON-X on Gemini-North, along with photometry and high-contrast imaging from multiple ground-based facilities. In addition to TESS photometry, K2-419Ab was also observed and statistically validated as part of the K2 mission in Campaigns 5 and 18, which provides precise orbital and planetary constraints despite the faint host star and long orbital period of $\sim 20.4$ days. With an equilibrium temperature of only 380 K, K2-419Ab is one of the coolest known well-characterized transiting planets. TOI-6034 has a late F-type companion about 40\arcsec~away, making it the first GEMS host star to have an earlier main-sequence binary companion. These confirmations add to the existing small sample of confirmed transiting GEMS., Comment: Accepted in AJ

In the domain of time series analysis, particularly in event detection tasks, current methodologies predominantly rely on segmentation-based approaches, which predict the class label for each individual timesteps and use the changepoints of these labels to detect events. However, these approaches may not effectively detect the precise onset and offset of events within the data and suffer from class imbalance problems. This study introduces a generalized regression-based approach to reframe the time-interval-defined event detection problem. Inspired by heatmap regression techniques from computer vision, our approach aims to predict probability densities at event locations rather than class labels across the entire time series. The primary aim of this approach is to improve the accuracy of event detection methods, particularly for long-duration events where identifying the onset and offset is more critical than classifying individual event states. We demonstrate that regression-based approaches outperform segmentation-based methods across various state-of-the-art baseline networks and datasets, offering a more effective solution for specific event detection tasks.

We present new JWST observations of the nearby, prototypical edge-on, spiral galaxy NGC 891. The northern half of the disk was observed with NIRCam in its F150W and F277W filters. Absorption is clearly visible in the mid-plane of the F150W image, along with vertical dusty plumes that closely resemble the ones seen in the optical. A $\sim 10 \times 3~{\rm kpc}^2$ area of the lower circumgalactic medium (CGM) was mapped with MIRI F770W at 12 pc scales. Thanks to the sensitivity and resolution of JWST, we detect dust emission out to $\sim 4$ kpc from the disk, in the form of filaments, arcs, and super-bubbles. Some of these filaments can be traced back to regions with recent star formation activity, suggesting that feedback-driven galactic winds play an important role in regulating baryonic cycling. The presence of dust at these altitudes raises questions about the transport mechanisms at play and suggests that small dust grains are able to survive for several tens of million years after having been ejected by galactic winds in the disk-halo interface. We lay out several scenarios that could explain this emission: dust grains may be shielded in the outer layers of cool dense clouds expelled from the galaxy disk, and/or the emission comes from the mixing layers around these cool clumps where material from the hot gas is able to cool down and mix with these cool cloudlets. This first set of data and upcoming spectroscopy will be very helpful to understand the survival of dust grains in energetic environments, and their contribution to recycling baryonic material in the mid-plane of galaxies., Comment: Accepted for publication in Astronomy & Astrophysics; 16 pages, 8 figures

The background index is an important quantity which is used in projecting and calculating the half-life sensitivity of neutrinoless double-beta decay ($0\nu\beta\beta$) experiments. A novel analysis framework is presented to calculate the background index using the specific activities, masses and simulated efficiencies of an experiment's components as distributions. This Bayesian framework includes a unified approach to combine specific activities from assay. Monte Carlo uncertainty propagation is used to build a background index distribution from the specific activity, mass and efficiency distributions. This analysis method is applied to the MAJORANA DEMONSTRATOR, which deployed arrays of high-purity Ge detectors enriched in $^{76}$Ge to search for $0\nu\beta\beta$. The framework projects a mean background index of $\left[8.95 \pm 0.36\right] \times 10^{-4}$cts/(keV kg yr) from $^{232}$Th and $^{238}$U in the DEMONSTRATOR's components., Comment: 9 pages, 3 figures

KM3NeT/ORCA is a water Cherenkov neutrino detector under construction and anchored at the bottom of the Mediterranean Sea. The detector is designed to study oscillations of atmospheric neutrinos and determine the neutrino mass ordering. This paper focuses on an initial configuration of ORCA, referred to as ORCA6, which comprises six out of the foreseen 115 detection units of photo-sensors. A high-purity neutrino sample was extracted, corresponding to an exposure of 433 kton-years. The sample of 5828 neutrino candidates is analysed following a binned log-likelihood method in the reconstructed energy and cosine of the zenith angle. The atmospheric oscillation parameters are measured to be $\sin^2\theta_{23}= 0.51^{+0.04}_{-0.05}$, and $ \Delta m^2_{31} = 2.18^{+0.25}_{-0.35}\times 10^{-3}~\mathrm{eV^2} \cup \{-2.25,-1.76\}\times 10^{-3}~\mathrm{eV^2}$ at 68\% CL. The inverted neutrino mass ordering hypothesis is disfavoured with a p-value of 0.25., Comment: 29 pages, 12 figures

We extend the dust-filament-based model presented in Herv\'ias-Caimapo & Huffenberger 2022 to produce parity-violating foreground spectra by manipulating the filament orientations relative to the magnetic field. We calibrate our model to observations of the misalignment angle using cross-correlations of Planck and HI 21-cm line data, producing a fiducial model that predicts a $\mathcal{D}_{\ell}^{EB}\sim$few $\mu$K$^2$ dust signal at 353 GHz and where $\sim 56$% of filaments have a positive misalignment angle. The main purpose of this model is to be used as dust with non-zero parity-violating emission in forecasting a measurement of cosmic birefringence by upcoming experiments. Here, we also use our fiducial model to assess the impact of dust in measurements of the isotropic cosmic birefringence angle $\beta$ with Planck data by measuring the misalignment angle as a function of scale, as well as directly using our model's $\mathcal{D}_{\ell}^{EB}$ prediction as a template. In both cases, we measure $\beta$ to be consistent within $0.83\sigma$ of the equivalent measurements with Planck data and its derivatives., Comment: 30 pages, 17 figures, 5 tables, 3 apendices. To be submitted to PRD