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This paper presents a review of research on the effectiveness of educational television compared to traditional face-to-face instruction. The studies reviewed are presented under seven rubrics: TV as a catalyst for learning; two-way TV; use of commercial TV shows; simulation of a real situation; TV integrated as part of the classroom lecture; TV courses instead of lecture in the classroom; and TV courses in the home. The author concludes that while TV has proved effective for teaching basic knowledge, it is deficient for teaching cognitive skills requiring more than "level I" knowledge. A bibliography is appended (the latest reference is to a 1975 publication). (BB)

California is home to the fifth-largest population of Black people in the United States, approximately 2.8 million individuals. However, when Black Californians seek access to the state's colleges and universities, they face undue bureaucratic and financial barriers. This Equity Alert explores a legislative proposal to create a California Black-Serving Institutions (BSI) Program intended to improve how Black Californians experience and succeed in higher education. The proposal and the potential benefits are discussed, followed by critical considerations to strengthen the effectiveness of the designation and improve the ways colleges and universities in California support Black student success.

Accreditation is one of the three tickets that every college in America must punch if it wants access to federal student aid (FSA) programs for its students. The current regulatory regime for postsecondary institutions forces each college wanting to participate in FSA programs to get authorization from the state in which it operates, meet the standards set by the U.S. Department of Education, and--strange as it may seem--get a green light from a nongovernmental organization called an accreditor. The good news is that while American colleges can't shop for a different federal government, they can shop for a different accreditor. That's a new development. During the Trump administration, Secretary of Education Betsy DeVos instituted new regulations letting any accreditor do business anywhere in the country. Before this change, a small number of accreditors divided up the country into fiefdoms and did not intrude on each other's turf; they were therefore called regional accreditors. The historically regional accreditors are now all national accreditors. So, which accreditor should a college choose? This policy brief can help colleges and universities make a sound decision.

A central question in multilingual language modeling is whether large language models (LLMs) develop a universal concept representation, disentangled from specific languages. In this paper, we address this question by analyzing latent representations (latents) during a word translation task in transformer-based LLMs. We strategically extract latents from a source translation prompt and insert them into the forward pass on a target translation prompt. By doing so, we find that the output language is encoded in the latent at an earlier layer than the concept to be translated. Building on this insight, we conduct two key experiments. First, we demonstrate that we can change the concept without changing the language and vice versa through activation patching alone. Second, we show that patching with the mean over latents across different languages does not impair and instead improves the models' performance in translating the concept. Our results provide evidence for the existence of language-agnostic concept representations within the investigated models., Comment: 12 pages, 10 figures, previously published under the title "How Do Llamas Process Multilingual Text? A Latent Exploration through Activation Patching" at the ICML 2024 mechanistic interpretability workshop https://openreview.net/forum?id=0ku2hIm4BS

Hot Jupiters with close-by planetary companions are rare, with only a handful of them having been discovered so far. This could be due to their suggested dynamical histories, leading to the possible ejection of other planets. TOI-2109 b is special in this regard because it is the hot Jupiter with the closest relative separation from its host star, being separated by less than 2.3 stellar radii. Unexpectedly, transit timing measurements from recently obtained CHEOPS observations show low amplitude transit-timing variations (TTVs). We aim to search for signs of orbital decay and to characterise the apparent TTVs, trying to gain information about a possible companion. We fit the newly obtained CHEOPS light curves using TLCM and extract the resulting mid-transit timings. Successively, we use these measurements in combination with TESS and archival photometric data and radial velocity data to estimate the rate of tidal orbital decay of TOI-2109 b, as well as characterise the TTVs using the N-body code TRADES and the photodynamical approach of PyTTV. We find tentative evidence at $3\sigma$ for orbital decay in the TOI-2109 system, when we correct the mid-transit timings using the best-fitting sinusoidal model of the TTVs. We do not detect additional transits in the available photometric data, but find evidence towards the authenticity of the apparent TTVs, indicating a close-by, outer companion with $P_\mathrm{c} > 1.125\,$d. Due to the fast rotation of the star, the new planetary candidate cannot be detected in the available radial velocity (RV) measurements, and its parameters can only be loosely constrained by our joint TTV and RV modelling. TOI-2109 could join a small group of rare hot Jupiter systems that host close-by planetary companions, only one of which (WASP-47 b) has an outer companion. More high-precision photometric measurements are necessary to confirm the planetary companion., Comment: Accepted for publication in A&A. 21 pages, 21 figures

When making predictions, a language model must trade off how much it relies on its context vs. its prior knowledge. Choosing how sensitive the model is to its context is a fundamental functionality, as it enables the model to excel at tasks like retrieval-augmented generation and question-answering. In this paper, we search for a knob which controls this sensitivity, determining whether language models answer from the context or their prior knowledge. To guide this search, we design a task for controllable context sensitivity. In this task, we first feed the model a context (Paris is in England) and a question (Where is Paris?); we then instruct the model to either use its prior or contextual knowledge and evaluate whether it generates the correct answer for both intents (either France or England). When fine-tuned on this task, instruction-tuned versions of Llama-3.1, Mistral-v0.3, and Gemma-2 can solve it with high accuracy (85-95%). Analyzing these high-performing models, we narrow down which layers may be important to context sensitivity using a novel linear time algorithm. Then, in each model, we identify a 1-D subspace in a single layer that encodes whether the model follows context or prior knowledge. Interestingly, while we identify this subspace in a fine-tuned model, we find that the exact same subspace serves as an effective knob in not only that model but also non-fine-tuned instruct and base models of that model family. Finally, we show a strong correlation between a model's performance and how distinctly it separates context-agreeing from context-ignoring answers in this subspace. These results suggest a single subspace facilitates how the model chooses between context and prior knowledge, hinting at a simple fundamental mechanism that controls this behavior.

Trapped ions provide a highly controlled platform for quantum sensors, clocks, simulators, and computers, all of which depend on cooling ions close to their motional ground state. Existing methods like Doppler, resolved sideband, and dark resonance cooling balance trade-offs between the final temperature and cooling rate. A traveling polarization gradient has been shown to cool multiple modes quickly and in parallel, but utilizing a stable polarization gradient can achieve lower ion energies, while also allowing more tailorable light-matter interactions in general. In this paper, we demonstrate cooling of a trapped ion below the Doppler limit using a phase-stable polarization gradient created using trap-integrated photonic devices. At an axial frequency of $2\pi\cdot1.45~ \rm MHz$ we achieve $\langle n \rangle = 1.3 \pm 1.1$ in $500~\mu \rm s$ and cooling rates of ${\sim}0.3 \, \rm quanta/\mu s$. We examine ion dynamics under different polarization gradient phases, detunings, and intensities, showing reasonable agreement between experimental results and a simple model. Cooling is fast and power-efficient, with improved performance compared to simulated operation under the corresponding running wave configuration., Comment: 16 pages, 11 figures

Trapped ions are a promising modality for quantum systems, with demonstrated utility as the basis for quantum processors and optical clocks. However, traditional trapped-ion systems are implemented using complex free-space optical configurations, whose large size and susceptibility to vibrations and drift inhibit scaling to large numbers of qubits. In recent years, integrated-photonics-based systems have been demonstrated as an avenue to address the challenge of scaling trapped-ion systems while maintaining high fidelities. While these previous demonstrations have implemented both Doppler and resolved-sideband cooling of trapped ions, these cooling techniques are fundamentally limited in efficiency. In contrast, polarization-gradient cooling can enable faster and more power-efficient cooling and, therefore, improved computational efficiencies in trapped-ion systems. While free-space implementations of polarization-gradient cooling have demonstrated advantages over other cooling mechanisms, polarization-gradient cooling has never previously been implemented using integrated photonics. In this paper, we design and experimentally demonstrate key polarization-diverse integrated-photonics devices and utilize them to implement a variety of integrated-photonics-based polarization-gradient-cooling systems, culminating in the first experimental demonstration of polarization-gradient cooling of a trapped ion by an integrated-photonics-based system. By demonstrating polarization-gradient cooling using an integrated-photonics-based system and, in general, opening up the field of polarization-diverse integrated-photonics-based devices and systems for trapped ions, this work facilitates new capabilities for integrated-photonics-based trapped-ion platforms.

Modern AI agents, driven by advances in large foundation models, promise to enhance our productivity and transform our lives by augmenting our knowledge and capabilities. To achieve this vision, AI agents must effectively plan, perform multi-step reasoning and actions, respond to novel observations, and recover from errors, to successfully complete complex tasks across a wide range of scenarios. In this work, we introduce Magentic-One, a high-performing open-source agentic system for solving such tasks. Magentic-One uses a multi-agent architecture where a lead agent, the Orchestrator, plans, tracks progress, and re-plans to recover from errors. Throughout task execution, the Orchestrator directs other specialized agents to perform tasks as needed, such as operating a web browser, navigating local files, or writing and executing Python code. We show that Magentic-One achieves statistically competitive performance to the state-of-the-art on three diverse and challenging agentic benchmarks: GAIA, AssistantBench, and WebArena. Magentic-One achieves these results without modification to core agent capabilities or to how they collaborate, demonstrating progress towards generalist agentic systems. Moreover, Magentic-One's modular design allows agents to be added or removed from the team without additional prompt tuning or training, easing development and making it extensible to future scenarios. We provide an open-source implementation of Magentic-One, and we include AutoGenBench, a standalone tool for agentic evaluation. AutoGenBench provides built-in controls for repetition and isolation to run agentic benchmarks in a rigorous and contained manner -- which is important when agents' actions have side-effects. Magentic-One, AutoGenBench and detailed empirical performance evaluations of Magentic-One, including ablations and error analysis are available at https://aka.ms/magentic-one

Efficiently learning expectation values of a quantum state using classical shadow tomography has become a fundamental task in quantum information theory. In a classical shadows protocol, one measures a state in a chosen basis $\mathcal{W}$ after it has evolved under a unitary transformation randomly sampled from a chosen distribution $\mathcal{U}$. In this work we study the case where $\mathcal{U}$ corresponds to either local or global orthogonal Clifford gates, and $\mathcal{W}$ consists of real-valued vectors. Our results show that for various situations of interest, this ``real'' classical shadow protocol improves the sample complexity over the standard scheme based on general Clifford unitaries. For example, when one is interested in estimating the expectation values of arbitrary real-valued observables, global orthogonal Cliffords decrease the required number of samples by a factor of two. More dramatically, for $k$-local observables composed only of real-valued Pauli operators, sampling local orthogonal Cliffords leads to a reduction by an exponential-in-$k$ factor in the sample complexity over local unitary Cliffords. Finally, we show that by measuring in a basis containing complex-valued vectors, orthogonal shadows can, in the limit of large system size, exactly reproduce the original unitary shadows protocol., Comment: 7+12 pages, 1+1 figures

The synthesis of inorganic crystalline materials is essential for modern technology, especially in quantum materials development. However, designing efficient synthesis workflows remains a significant challenge due to the precise experimental conditions and extensive trial and error. Here, we present a framework using large language models (LLMs) to predict synthesis pathways for inorganic materials, including quantum materials. Our framework contains three models: LHS2RHS, predicting products from reactants; RHS2LHS, predicting reactants from products; and TGT2CEQ, generating full chemical equations for target compounds. Fine-tuned on a text-mined synthesis database, our model raises accuracy from under 40% with pretrained models, to under 80% using conventional fine-tuning, and further to around 90% with our proposed generalized Tanimoto similarity, while maintaining robust to additional synthesis steps. Our model further demonstrates comparable performance across materials with varying degrees of quantumness quantified using quantum weight, indicating that LLMs offer a powerful tool to predict balanced chemical equations for quantum materials discovery., Comment: 66 pages total, 6 main figures + 3 supplementary figures

Sparse autoencoders (SAEs) have become a core ingredient in the reverse engineering of large-language models (LLMs). For LLMs, they have been shown to decompose intermediate representations that often are not interpretable directly into sparse sums of interpretable features, facilitating better control and subsequent analysis. However, similar analyses and approaches have been lacking for text-to-image models. We investigated the possibility of using SAEs to learn interpretable features for a few-step text-to-image diffusion models, such as SDXL Turbo. To this end, we train SAEs on the updates performed by transformer blocks within SDXL Turbo's denoising U-net. We find that their learned features are interpretable, causally influence the generation process, and reveal specialization among the blocks. In particular, we find one block that deals mainly with image composition, one that is mainly responsible for adding local details, and one for color, illumination, and style. Therefore, our work is an important first step towards better understanding the internals of generative text-to-image models like SDXL Turbo and showcases the potential of features learned by SAEs for the visual domain. Code is available at https://github.com/surkovv/sdxl-unbox

We work out the unfolded formulation of the fields in the non-linear realisation of $E_{11}$. Using the connections in this formalism, we propose, at the linearised level, an infinite number of first-order duality relations between the dual fields in $E_{11}$. In this way, we introduce extra fields that do not belong to $E_{11}$ and we investigate their origin. The equations of motion of the fields are obtained by taking derivatives and higher traces of the duality relations., Comment: 89 pages, 9 tables

We introduce a dynamic model for complexity control (CC) between systems, represented by time series characterized by different temporal complexity measures, as indicated by their respective inverse power law (IPL) indices. Given the apparent straightforward character of the model and the generality of the result, we formulate a hypothesis based on the closeness of the scaling measures of the model to the empirical complexity measures of the human brain. CC is a proper model for describing the recent experimental results, such as the rehabilitation in walking arm in arm and the complexity synchronization effect. The CC effect can lead to the design of mutual-adaptive signals to restore the misaligned complexity of maladjusted organ networks or, on the other hand, to disrupt the complexity of a malicious system and lower its intelligent behavior., Comment: 12 pages

We study the sensitivity of presupernova evolution and supernova nucleosynthesis yields of massive stars to variations of the initial composition. We use the solar abundances from Lodders (2009), and compute two different initial stellar compositions: i) scaled solar abundances, and ii) the isotopic galactic chemical history model (GCH) developed by West and Heger (2013b). We run a grid of models using the KEPLER stellar evolution code, with 7 initial stellar masses, 12 initial metallicities, and two for each scaling method to explore the effects on nucleosynthesis over a metallicity range of $-4.0\leq[Z]\leq+0.3$. We find that the compositions from the GCH model better reproduce the weak \emph{s}-process peak than the scaled solar models. The model yields are then used in the OMEGA Galactic Chemical Evolution (GCE) code to assess this result further. We find that initial abundances used in computing stellar structure have more of an impact on GCE results than initial abundances used in the burn network, with the GCH model again being favored when compared to observations. Lastly, a machine learning algorithm was used to verify the free parameter values of the GCH model, which were previously found by West and Heger (2013b) using a stochastic fitting process. The updated model is provided as an accessible tool for further nucleosynthesis studies.

Large language models (LLMs) are capable of writing grammatical text that follows instructions, answers questions, and solves problems. As they have advanced, it has become difficult to distinguish their output from human-written text. While past research has found some differences in surface features such as word choice and punctuation, and developed classifiers to detect LLM output, none has studied the rhetorical styles of LLMs. Using several variants of Llama 3 and GPT-4o, we construct two parallel corpora of human- and LLM-written texts from common prompts. Using Douglas Biber's set of lexical, grammatical, and rhetorical features, we identify systematic differences between LLMs and humans and between different LLMs. These differences persist when moving from smaller models to larger ones, and are larger for instruction-tuned models than base models. This demonstrates that despite their advanced abilities, LLMs struggle to match human styles, and hence more advanced linguistic features can detect patterns in their behavior not previously recognized., Comment: 29 pages, 4 figures, 11 tables

The line-of-sight structure of the Galactic magnetic field (GMF) can be studied using Faraday rotation measure (RM) grids. We analyze how the choice of interpolation kernel can affect the accuracy and reliability of reconstructed RM maps. We test the following kernels: inverse distance weighting (IDW), natural neighbour interpolation (NNI), inverse multiquadric interpolation (IM), thin-plate spline interpolation (TPS), and a Bayesian rotation measure sky (BRMS); all techniques were tested on two simulated Galactic foreground RMs (one assuming the GMF has patchy structures and the other assuming it has filamentary structures) using magnetohydrodynamic simulations. Both foregrounds were sampled to form RM grids with densities of $\sim$40 sources deg$^{-2}$ and area $\sim$144 deg$^2$. The techniques were tested on data sets with different noise levels and Gaussian random extragalactic RM contributions. The data set that most closely emulates expected data from current surveys, such as the POlarization Sky Survey of the Universe's Magnetism (POSSUM), had extragalactic contributions and a noise standard deviation of $\sim 1.5$ rad m$^{-2}$. For this data set, the accuracy of the techniques for the patchy structures from best to worst was: BRMS, NNI, TPS, IDW and IM; while in the filamentary simulate foreground it was: BRMS, NNI, TPS, and IDW. IDW is the most computationally expensive technique, while TPS and IM are the least expensive. BRMS and NNI have the same, intermediate computational cost. This analysis lays the groundwork for Galactic RM studies with large radio polarization sky surveys, such as POSSUM., Comment: 32 pages, 22 figures, 8 tables

Discussions regarding the dual use of foundation models and the risks they pose have overwhelmingly focused on a narrow set of use cases and national security directives-in particular, how AI may enable the efficient construction of a class of systems referred to as CBRN: chemical, biological, radiological and nuclear weapons. The overwhelming focus on these hypothetical and narrow themes has occluded a much-needed conversation regarding present uses of AI for military systems, specifically ISTAR: intelligence, surveillance, target acquisition, and reconnaissance. These are the uses most grounded in actual deployments of AI that pose life-or-death stakes for civilians, where misuses and failures pose geopolitical consequences and military escalations. This is particularly underscored by novel proliferation risks specific to the widespread availability of commercial models and the lack of effective approaches that reliably prevent them from contributing to ISTAR capabilities. In this paper, we outline the significant national security concerns emanating from current and envisioned uses of commercial foundation models outside of CBRN contexts, and critique the narrowing of the policy debate that has resulted from a CBRN focus (e.g. compute thresholds, model weight release). We demonstrate that the inability to prevent personally identifiable information from contributing to ISTAR capabilities within commercial foundation models may lead to the use and proliferation of military AI technologies by adversaries. We also show how the usage of foundation models within military settings inherently expands the attack vectors of military systems and the defense infrastructures they interface with. We conclude that in order to secure military systems and limit the proliferation of AI armaments, it may be necessary to insulate military AI systems and personal data from commercial foundation models.

Tungsten peaking is predicted in the core of a WEST plasma with total-f gyrokinetic simulations, including both collisional and turbulent transport. This prediction is validated with a synthetic diagnostic of the bolometry. Although nitrogen impurities are shown to reduce the neoclassical peaking of tungsten on-axis, the overall tungsten peaking increases when nitrogen impurities are present, as they reduce the turbulence screening off-axis. This finding is important for the plasma current ramp-up phase of ITER, where light impurities seeding will be desirable to achieve low temperatures at the plasma-facing components and reduce tungsten sputtering. It provides further argument for applying early ECRH heating to maintain margins on the core power balance. The neoclassical peaking factor is cross-verified between XGC and FACIT. The heat flux at separatrix and the heat load width are modeled by XGC and compared to WEST data., Comment: 15 pages, 17 figures

The methodology developed by McNamara and Bulland (2004) for computing Power Spectral Densities (PSDs) has gained popularity due to its low computational cost and reduction of spectral variance. This methodology is widely used in seismic noise studies and station performance evaluations and is implemented in tools like ISPAQ, MUSTANG, and PQLX. However, concerns have been raised about its appropriateness in certain contexts, particularly when high-resolution spectral detail is required. This study evaluates McNamara and Bulland's methodology by comparing it with Welch's method across three Alaskan stations with differing microseism conditions. When calculating seismic power across a band of frequencies--for example, the 5-10s secondary microseism--we find that both methodologies produce time series with nearly identical trends, albeit with slight differences in absolute power values. Our results demonstrate that McNamara and Bulland's methodology is fully appropriate for certain applications, specifically ones that rely on averaged seismic energy over a frequency band as opposed to a single discrete frequency.

Assessing classification confidence is critical for leveraging large language models (LLMs) in automated labeling tasks, especially in the sensitive domains presented by Computational Social Science (CSS) tasks. In this paper, we make three key contributions: (1) we propose an uncertainty quantification (UQ) performance measure tailored for data annotation tasks, (2) we compare, for the first time, five different UQ strategies across three distinct LLMs and CSS data annotation tasks, (3) we introduce a novel UQ aggregation strategy that effectively identifies low-confidence LLM annotations and disproportionately uncovers data incorrectly labeled by the LLMs. Our results demonstrate that our proposed UQ aggregation strategy improves upon existing methods andcan be used to significantly improve human-in-the-loop data annotation processes.

The ability of large language models (LLMs) to perform zero-shot classification makes them viable solutions for data annotation in rapidly evolving domains where quality labeled data is often scarce and costly to obtain. However, the large-scale deployment of LLMs can be prohibitively expensive. This paper introduces an LLM chain ensemble methodology that aligns multiple LLMs in a sequence, routing data subsets to subsequent models based on classification uncertainty. This approach leverages the strengths of individual LLMs within a broader system, allowing each model to handle data points where it exhibits the highest confidence, while forwarding more complex cases to potentially more robust models. Our results show that the chain ensemble method often exceeds the performance of the best individual model in the chain and achieves substantial cost savings, making LLM chain ensembles a practical and efficient solution for large-scale data annotation challenges.

Generating rationales that justify scoring decisions has emerged as a promising approach to enhance explainability in the development of automated scoring systems. However, the scarcity of publicly available rationale data and the high cost of annotation have resulted in existing methods typically relying on noisy rationales generated by large language models (LLMs). To address these challenges, we have developed AERA Chat, an interactive platform, to provide visually explained assessment of student answers and streamline the verification of rationales. Users can input questions and student answers to obtain automated, explainable assessment results from LLMs. The platform's innovative visualization features and robust evaluation tools make it useful for educators to assist their marking process, and for researchers to evaluate assessment performance and quality of rationales generated by different LLMs, or as a tool for efficient annotation. We evaluated three rationale generation approaches on our platform to demonstrate its capability.

Recent work has initiated the study of dense graph processing using graph sketching methods, which drastically reduce space costs by lossily compressing information about the input graph. In this paper, we explore the strange and surprising performance landscape of sketching algorithms. We highlight both their surprising advantages for processing dense graphs that were previously prohibitively expensive to study, as well as the current limitations of the technique. Most notably, we show how sketching can avoid bottlenecks that limit conventional graph processing methods. Single-machine streaming graph processing systems are typically bottlenecked by CPU performance, and distributed graph processing systems are typically bottlenecked by network latency. We present Landscape, a distributed graph-stream processing system that uses linear sketching to distribute the CPU work of computing graph properties to distributed workers with no need for worker-to-worker communication. As a result, it overcomes the CPU and network bottlenecks that limit other systems. In fact, for the connected components problem, Landscape achieves a stream ingestion rate one-fourth that of maximum sustained RAM bandwidth, and is four times faster than random access RAM bandwidth. Additionally, we prove that for any sequence of graph updates and queries Landscape consumes at most a constant factor more network bandwidth than is required to receive the input stream. We show that this system can ingest up to 332 million stream updates per second on a graph with $2^{17}$ vertices. We show that it scales well with more distributed compute power: given a cluster of 40 distributed worker machines, it can ingest updates 35 times as fast as with 1 distributed worker machine. Landscape uses heuristics to reduce its query latency by up to four orders of magnitude over the prior state of the art.

Simultaneous graphical dynamic linear models (SGDLMs) provide advances in flexibility, parsimony and scalability of multivariate time series analysis, with proven utility in forecasting. Core theoretical aspects of such models are developed, including new results linking dynamic graphical and latent factor models. Methodological developments extend existing Bayesian sequential analyses for model marginal likelihood evaluation and counterfactual forecasting. The latter, involving new Bayesian computational developments for missing data in SGDLMs, is motivated by causal applications. A detailed example illustrating the models and new methodology concerns global macroeconomic time series with complex, time-varying cross-series relationships and primary interests in potential causal effects., Comment: 22 pages and 9 figures (main paper); 16 pages and 6 figures (appendices and supplementary material)

Given the prompt "Rome is in", can we steer a language model to flip its prediction of an incorrect token "France" to a correct token "Italy" by only multiplying a few relevant activation vectors with scalars? We argue that successfully intervening on a model is a prerequisite for interpreting its internal workings. Concretely, we establish a three-term objective: a successful intervention should flip the correct with the wrong token and vice versa (effectiveness), and leave other tokens unaffected (faithfulness), all while being sparse (minimality). Using gradient-based optimization, this objective lets us learn (and later evaluate) a specific kind of efficient and interpretable intervention: activation scaling only modifies the signed magnitude of activation vectors to strengthen, weaken, or reverse the steering directions already encoded in the model. On synthetic tasks, this intervention performs comparably with steering vectors in terms of effectiveness and faithfulness, but is much more minimal allowing us to pinpoint interpretable model components. We evaluate activation scaling from different angles, compare performance on different datasets, and make activation scalars a learnable function of the activation vectors themselves to generalize to varying-length prompts., Comment: Findings of the Association for Computational Linguistics: EMNLP 2024

Links are a fundamental part of information networks, turning isolated pieces of knowledge into a network of information that is much richer than the sum of its parts. However, adding a new link to the network is not trivial: it requires not only the identification of a suitable pair of source and target entities but also the understanding of the content of the source to locate a suitable position for the link in the text. The latter problem has not been addressed effectively, particularly in the absence of text spans in the source that could serve as anchors to insert a link to the target entity. To bridge this gap, we introduce and operationalize the task of entity insertion in information networks. Focusing on the case of Wikipedia, we empirically show that this problem is, both, relevant and challenging for editors. We compile a benchmark dataset in 105 languages and develop a framework for entity insertion called LocEI (Localized Entity Insertion) and its multilingual variant XLocEI. We show that XLocEI outperforms all baseline models (including state-of-the-art prompt-based ranking with LLMs such as GPT-4) and that it can be applied in a zero-shot manner on languages not seen during training with minimal performance drop. These findings are important for applying entity insertion models in practice, e.g., to support editors in adding links across the more than 300 language versions of Wikipedia., Comment: EMNLP 2024; 24 pages; 62 figures

We used data from LexisNexis to determine the words in news media that best classifies countries as higher or lower peace. We found that higher peace news is characterized by themes of finance, daily actitivities, and health and that lower peace news is characterized by themes of politics, government, and legal issues. This work provides a starting point to measure levels of peace and identify the social processes that underly those words., Comment: 6 pages, 6 figures

This paper presents a novel approach to identifying insights of peace in global media using a Retrieval Augmented Generation (RAG) model and concepts of Positive and Negative Intergroup Reciprocity (PIR/NIR). By refining the definitions of PIR and NIR, we offer a more accurate and meaningful analysis of intergroup relations as represented in media articles. Our methodology provides insights into the dynamics that contribute to or detract from peace at a national level., Comment: 6 pages, 1 figure

This paper presents a machine learning approach to classify countries as peaceful or non-peaceful using linguistic patterns extracted from global media articles. We employ vector embeddings and cosine similarity to develop a supervised classification model that effectively identifies peaceful countries. Additionally, we explore the impact of dataset size on model performance, investigating how shrinking the dataset influences classification accuracy. Our results highlight the challenges and opportunities associated with using large-scale text data for peace studies., Comment: 5 pages, 5 figures

This paper addresses robotic peg-in-hole assembly using the framework of Elementary Dynamic Actions (EDA). Inspired by motor primitives in neuromotor control research, the method leverages three primitives: submovements, oscillations, and mechanical impedances (e.g., stiffness and damping), combined via a Norton equivalent network model. By focusing on impedance parameterization, we explore the adaptability of EDA in contact-rich tasks. Experimental results, conducted on a real robot setup with four different peg types, demonstrated a range of successful impedance parameters, challenging conventional methods that seek optimal parameters. We analyze our data in a lower-dimensional solution space. Clustering analysis shows the possibility to identify different individual strategies for each single peg, as well as common strategies across all pegs. A neural network model, trained on the experimental data, accurately predicted successful impedance parameters across all pegs. The practical utility of this work is enhanced by a success-predictor model and the public availability of all code and CAD files. These findings highlight the flexibility and robustness of EDA; show multiple equally-successful strategies for contact-rich manipulation; and offer valuable insights and tools for robotic assembly programming., Comment: 18 pages, 11 figures

Neutral hydrogen (HI) bubbles and shells are common in the interstellar medium (ISM). Studying their properties provides insight into the characteristics of the local ISM as well as the galaxy in which the bubbles reside. We report the detection of magnetic fields associated with superbubbles in the nearby irregular galaxy, the Small Magellanic Cloud (SMC). Using the Polarisation Sky Survey of the Universe's Magnetism (POSSUM) pilot survey, we obtain a high-density grid ($\approx 25 \,\rm sources\,deg^{-2}$) of Faraday rotation measure (RM) from polarized sources behind the SMC. This provides a sufficiently large number of RM measurements to study the magnetic properties of three of the largest HI shells previously identified in the SMC. The RM profiles as a function of distance from the shell centre show characteristic patterns at angular scales comparable to the shell size. We demonstrate that this can be explained by magneto-hydrodynamic simulation models of bubbles expanding in magnetised environments. From the observations, we estimate the line-of-sight magnetic field strength at the edges of the shells is enhanced by $\sim1\,\rm \mu G$ with respect to their centres. This is an order of magnitude larger than the field strength in the ambient medium ($\sim 0.1\,\rm \mu G$) estimated based on the expansion velocity of the shells. This paper highlights the power of densely mapped RM grids in studying the magnetic properties of galactic substructures beyond the Milky Way., Comment: 15 pages, 7 figures, Accepted for publication in MNRAS

A unitary state $t$-design is an ensemble of pure quantum states whose moments match up to the $t$-th order those of states uniformly sampled from a $d$-dimensional Hilbert space. Typically, unitary state $t$-designs are obtained by evolving some reference pure state with unitaries from an ensemble that forms a design over the unitary group $\mathbb{U}(d)$, as unitary designs induce state designs. However, in this work we study whether Haar random symplectic states -- i.e., states obtained by evolving some reference state with unitaries sampled according to the Haar measure over $\mathbb{SP}(d/2)$ -- form unitary state $t$-designs. Importantly, we recall that random symplectic unitaries fail to be unitary designs for $t>1$, and that, while it is known that symplectic unitaries are universal, this does not imply that their Haar measure leads to a state design. Notably, our main result states that Haar random symplectic states form unitary $t$-designs for all $t$, meaning that their distribution is unconditionally indistinguishable from that of unitary Haar random states, even with tests that use infinite copies of each state. As such, our work showcases the intriguing possibility of creating state $t$-designs using ensembles of unitaries which do not constitute designs over $\mathbb{U}(d)$ themselves, such as ensembles that form $t$-designs over $\mathbb{SP}(d/2)$., Comment: 6+11 pages, 1+1 figures

For a fixed prime power $q$, let $\text{GL}_\bullet(q)$ denote the family of groups $\text{GL}_N(q)$ for $N \in \mathbb{Z}_{\geq 0}$. In this paper we study the $\mathbb{C}$-algebra of "stable" class functions of $\text{GL}_\bullet(q)$, and show it admits four different linear bases, each arising naturally in different settings. One such basis is that of stable irreducible characters, namely, the class functions spanned by the characters corresponding to finitely generated simple $\mathrm{VI}$-modules in the sense of [arXiv:1408.3694,arXiv:1602.00654]. A second one comes from characters of parabolic representations. The final two, one originally defined in [arXiv:1803.04155] and the other in [arXiv:2110.11099], are more combinatorial in nature. As corollaries, we clarify many properties of these four bases and prove a conjecture from [arXiv:2106.11587]., Comment: 25 pages

The MMT Adaptive optics exoPlanet characterization System (MAPS) is currently in its engineering phase, operating on-sky at the MMT Telescope on Mt. Hopkins in southern Arizona. The MAPS Adaptive Secondary Mirror's actuators are controlled by a closed loop modified PID control law and an open loop feed-forward law, which in combination allows for faster actuator response time. An essential element of achieving the secondary's performance goals involves the process of PID gain tuning. To start, we briefly discuss the design of the MAPS ASM and its actuators. We then describe the actuator positional control system and control law. Next, we discuss a few of the issues that make ASM tuning difficult. We then outline our initial attempts at tuning the actuator controllers and discuss the use of actuator positional power spectra for both tuning and determining the health and failure states of individual actuators. We conclude by presenting the results of our latest round of tuning configuration trials, which have been successful at decreasing mirror latency, increasing operational mirror modes and improving image PSF., Comment: To be published in Proceedings of SPIE, Optics and Photonics 2024. 24 pages, 16 figures, 5 tables. Lead Author, J. Johnson. Second Lead Author, A. Vaz. Project P.I., K. Morzinski. Project Second P.I.s, J. Patience and S. Sivanandam, Project Manager, M. Montoya

We show that the dynamics encoded in the non-linear realisation of the semi-direct product of the very extended algebra K27 with its vector representation contains the low energy effective action of the closed bosonic string., Comment: 31 pages

We show that the isometry group of a finite-volume hyperbolic 3-manifold acts simply transitively on many of its closed geodesics. Combining this observation with the Virtual Special Theorems of the first author and Wise, we show that every non-arithmetic lattice in PSL$(2,\mathbb{C})$ is the full group of orientation-preserving isometries for some other lattice and that the orientation-preserving isometry group of a finite-volume hyperbolic 3-manifold acts non-trivially on the homology of some finite-sheeted cover., Comment: 11 pages

In non-Hermitian open quantum systems, such as polariton condensates, local tailoring of gains and losses opens up an interesting possibility to realize functional optical elements. Here, we demonstrate that deliberately introducing losses via a photonic defect, realized by reducing the quality factor of a DBR mirror locally within an ultrahigh-quality microcavity, may be utilized to create directed polariton currents towards the defect. We discuss the role of polariton-polariton interactions in the process and how to tailor the effective decay time of a polariton condensate via coupling to the defect. Our results highlight the far-reaching potential of non-Hermitian physics in polaritonics., Comment: 9 pages, 4 figures

As wavefront quality demands tighten on space systems for applications such as astronomy and laser communication, mounting small optics such that the wavefront is undisturbed, positioning is adjustable and the design is producible, while surviving harsh space environments, is a continuing challenge. We designed multiple candidate flexure mounts to support small optics (up to 50 mm diameter, and over 100 grams) to survive the qualification and acceptance tests of small spacecraft and units as defined in ISO 19683 and a mounting structure which is adjustable in decenter [+/-0.5mm], tip/tilt +/-0.5deg, and piston [+/-0.25mm]. We will present design details along with measurements showing less than approximately lambda/10 wavefront contribution from the optic bonding process, along with thermal and multi-axis vibration test data showing the mounted optics survived the acceptance testing loads and are suitable for operation in a wide range of harsh environments.

This paper presents a comprehensive analysis of RR Lep and BF Vel, two short-period semi-detached oscillating Algols (oEA stars), which are shown to be triple systems. Spectral types of their primaries were determined and radial velocities calculated from spectra observed with the Australian National University's 2.3 m telescope and Wide Field Spectrograph. Spectra of the Na I D doublet confirmed the presence of tertiary components which were apparent in the broadening function analyses and, with H_a spectra during primary eclipses, indicated chromospherical activity in their secondaries. Ground-based telescopes were used for observations in several pass bands for photometric analyses. These data were complemented by data from the TESS mission to enable the modelling of the light curves, followed by a detailed analysis of pulsations. Eclipse-timing variation (ETV) analyses of both systems were used to determine the most likely mechanisms modulating the orbital period. We found mass values M1 = 2.9 M_sun and M2 = 0.75 M_sun for the components of RR Lep, and M1 = 1.93 M_sun and M2 = 0.97 M_sun for those of BF Vel. By integrating information from photometry, spectroscopy and ETV analysis, we found that tertiary components revolve around both systems. The primary star of RR Lep pulsates in 36 frequencies, of which five were identified as independent modes, with the dominant one being 32.28 d^-1. The pulsating component of BF Vel oscillates in 37 frequencies, with the frequency 46.73 d^-1 revealed as the only independent mode. For both systems, many frequencies were found to be related to the orbital frequency. Their physical properties were compared with other oEA stars in Mass-Radius and H-R diagrams, and the pulsational properties of their delta Sct components were compared with currently known systems of this type within the orbital-pulsation period and logg-pulsation period diagrams., Comment: 22 pages, 21 figures, 8 tables, 3 appendices, Accepted for publication in A&A

The physics case for quarkonium-production studies accessible at the US Electron Ion Collider is described., Comment: Latex, 84 pages. Review prepared for Progress in Particle and Nuclear Physics

Regulatory functions are essential in both socioeconomic and biological systems, from corporate managers to regulatory genes in genomes. Regulatory functions come with substantial costs, but are often taken for granted. Here, we empirically examine regulatory costs across diverse systems -- biological organisms (bacteria and eukaryotic genomes), human organizations (companies, federal agencies, universities), and decentralized entities (Wikipedia, cities) -- using scaling analysis. We guide the empirical analysis with a conceptual model, which anticipates the scaling of regulatory costs to shift with the system's internal interaction structure -- well-mixed or modular. We find diverse systems exhibit consistent scaling patterns -- well-mixed systems exhibit superlinear scaling, while modular ones show sublinear or linear scaling. Further, we find that the socioeconomic systems containing more diverse occupational functions tend to have more regulatory costs than expected from their size, confirming the type of interactions also plays a role in regulatory costs. While many socioeconomic systems exhibit efficiencies of scale, regulatory costs in many social systems have grown disproportionally over time. Our finding suggests that the increasing complexity of functions may contribute to this trend. This cross-system comparison offers a framework for understanding regulatory costs and could guide future efforts to identify and mitigate regulatory inefficiencies., Comment: 12 pages, 4 figures

This paper investigates the computational mechanisms underlying a type of metacognitive monitoring known as detached mindfulness, a particularly effective therapeutic technique within cognitive psychology. While research strongly supports the capacity of detached mindfulness to reduce depression and anxiety, its cognitive and computational underpinnings remain largely unexplained. We employ a computational model of metacognitive skill to articulate the mechanisms through which a detached perception of affect reduces emotional reactivity., Comment: International Conference on Cognitive Modeling (ICCM 2024) https://mathpsych.org/presentation/1634#/abstract

The purpose of this document is to provide the reader with a general understanding regarding the roles and responsibilities of professional student support personnel in West Virginia schools and how, through a collaborative partnership, they can work together to provide a safe and supportive learning environment for WV students. Research confirms that students do better in school when they receive social-emotional and mental health support. They miss fewer classes, concentrate more, are less likely to engage in risky or antisocial behavior, and achieve higher test scores. The most effective way to implement integrated services that support school safety and student learning is through a school-wide multitiered system of support (MTSS). Effective MTSS requires: (1) adequate access to school-employed professional student support personnel and community-based services; (2) integration of services (social-emotional learning, mental health, medical health, behavioral supports, academic supports, school-based services, and community services); (3) adequate staff time for planning and problem-solving; (4) effective collection, evaluation, interpretation, and use of data; (5) patience, commitment, collaborations, and strong leadership; and (6) understanding the various roles of the many student support personnel and how they work together for the benefit of every child. The West Virginia Department of Education (WVDE) recognizes the effectiveness of a multi-tiered system of support and is committed to ensuring equitable education opportunities through the West Virginia Tiered System of Support (WVTSS), a multi-tiered systems framework. WVTSS emphasizes the integration of academics, behavior, and mental health as uniformly critical to student success and focuses on the cohesive system of support rather than interventions alone.