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In this Technical Design Report (TDR) we describe the SABRE South detector to be built at the Stawell Underground Physics Laboratory (SUPL). The SABRE South detector is designed to test the long-standing DAMA/LIBRA signal of an annually modulating rate consistent with dark matter by using the same target material. SABRE South uses seven ultra-high purity NaI(Tl) crystals (with a total target mass of either 35 kg or 50 kg), hermetically sealed in copper enclosures that are suspended within a liquid scintillator active veto. High quantum efficiency and low background Hamamatsu R11065 photomultiplier tubes are directly coupled to both ends of the crystal, and enclosed with the crystal in an oxygen free high thermal conductivity copper enclosure. The active veto system consists of 11.6 kL of linear alkylbenzene (LAB) doped with a mixture of fluorophores and contained in a steel vessel, which is instrumented with at least 18 Hamamatsu R5912 photomultipliers. The active veto tags key radiogenic backgrounds intrinsic to the crystals, such as ${^{40}}$K, and is expected to suppress the total background by 27% in the 1-6 keV region of interest. In addition to the liquid scintillator veto, a muon veto is positioned above the detector shielding. This muon veto consists of eight EJ-200 scintillator modules, with Hamamatsu R13089 photomultipliers coupled to both ends. With an expected total background of 0.72 cpd/kg/keV, SABRE South can test the DAMA/LIBRA signal with 5$\sigma$ discovery or 3$\sigma$ exclusion after two years of data taking.

As globular clusters (GCs) orbit the Milky Way, their stars are tidally stripped forming tidal tails that follow the orbit of the clusters around the Galaxy. The morphology of these tails is complex and shows correlations with the phase of the orbit and the orbital angular velocity, especially for GCs on eccentric orbits. Here, we focus on two GCs, NGC 1261 and NGC 1904, that have potentially been accreted alongside Gaia-Enceladus and that have shown signatures of having, in addition of tidal tails, structures formed by distributions of extra-tidal stars that are misaligned with the general direction of the clusters' respective orbits. To provide an explanation for the formation of these structures, we make use of spectroscopic measurements from the Southern Stellar Stream Spectroscopic Survey ($S^5$) as well as proper motion measurements from Gaia's third data release (DR3), and apply a Bayesian mixture modeling approach to isolate high-probability member stars. We recover extra-tidal features similar to those found in Shipp et al. (2018) surrounding each cluster. We conduct N-body simulations and compare the expected distribution and variation in the dynamical parameters along the orbit with those of our potential member sample. Furthermore, we use Dark Energy Camera (DECam) photometry to inspect the distribution of the member stars in the color-magnitude diagram (CMD). We find that the potential members agree reasonably with the N-body simulations and that the majority of them follow a simple stellar population-like distribution in the CMD which is characteristic of GCs. In the case of NGC 1904, we clearly detect the tidal debris escaping the inner and outer Lagrange points which are expected to be prominent when at or close to the apocenter of its orbit. Our analysis allows for further exploration of other GCs in the Milky Way that exhibit similar extra-tidal features.

Hindsight experience replay (HER) is well-known to accelerate goal-based reinforcement learning (RL). While HER is generally applied to off-policy RL algorithms, we previously showed that HER can also accelerate on-policy algorithms, such as proximal policy optimization (PPO), for goal-based Predator-Prey environments. Here, we show that we can improve the previous PPO-HER algorithm by selectively applying HER in a principled manner., Comment: 11 pages, 11 Figures

Hindsight experience replay (HER) accelerates off-policy reinforcement learning algorithms for environments that emit sparse rewards by modifying the goal of the episode post-hoc to be some state achieved during the episode. Because post-hoc modification of the observed goal violates the assumptions of on-policy algorithms, HER is not typically applied to on-policy algorithms. Here, we show that HER can dramatically accelerate proximal policy optimization (PPO), an on-policy reinforcement learning algorithm, when tested on a custom predator-prey environment., Comment: 12 pages. 10 Figures

This letter presents a dual quadrature phasemeter, an implementation of a phase-locked loop designed to track the phase of homodyne and heterodyne inter-satellite laser links. The dual quadrature phasemeters use dual quadrature optical detection to enable an alternate phase readout scheme that operates with wider bandwidths and on signals with carrier frequency differences down to DC. Analytical modeling demonstrates that dual quadrature phasemeters overcome the bandwidth limitations of conventional phasemeters. Numerical simulations of noise linearity tests found that the phase tracking error of the dual quadrature phasemeter is less than 10 microcycle/$\sqrt{\text{Hz}}$ in the presence of non-linear cyclic errors. The dual quadrature phasemeter enables exploration of a new optical configuration for retroreflector-based space geodesy missions with architecture similar to that implemented in GRACE-FO. One such alternate configuration is proposed that is capable of tracking satellite separation without requiring a frequency offset between local and incoming light, eliminating the need for optical frequency shifters.

Chemical abundances of stellar streams can be used to determine the nature of a stream's progenitor. Here we study the progenitor of the recently discovered Leiptr stellar stream, which was previously suggested to be a tidally disrupted halo globular cluster. We obtain high-resolution spectra of five red giant branch stars selected from the Gaia DR2 STREAMFINDER catalog with Magellan/MIKE. One star is a clear non-member. The remaining four stars display chemical abundances consistent with those of a low-mass dwarf galaxy: they have a low mean metallicity, $\langle{\rm[Fe/H]}\rangle = -2.2$; they do not all have identical metallicities; and they display low [$\alpha$/Fe] $\sim 0$ and [Sr/Fe] and [Ba/Fe] $\sim -1$. This pattern of low $\alpha$ and neutron-capture element abundances is only found in intact dwarf galaxies with stellar mass $\lesssim 10^5 M_\odot$. Although more data are needed to be certain, Leiptr's chemistry is consistent with being the lowest-mass dwarf galaxy stream without a known intact progenitor, possibly in the mass range of ultra-faint dwarf galaxies. Leiptr thus preserves a record of one of the lowest-mass early accretion events into the Milky Way., Comment: 18 pages, 12 figures, 8 tables, to be submitted to The Open Journal of Astrophysics

Numerous research studies have been conducted to enhance the resilience of cyber-physical systems (CPSs) by detecting potential cyber or physical disturbances. However, the development of scalable and optimal response measures under power system contingency based on fusing cyber-physical data is still in an early stage. To address this research gap, this paper introduces a power system response engine based on reinforcement learning (RL) and role and interaction discovery (RID) techniques. RL-RID-GridResponder is designed to automatically detect the contingency and assist with the decision-making process to ensure optimal power system operation. The RL-RID-GridResponder learns via an RL-based structure and achieves enhanced scalability by integrating an RID module with reduced action and state spaces. The applicability of RL-RID-GridResponder in providing scalable and optimal responses for CPSs is demonstrated on power systems in the context of Denial of Service (DoS) attacks. Moreover, simulations are conducted on a Volt-Var regulation problem using the augmented WSCC 9-bus and augmented IEEE 24-bus systems based on fused cyber and physical data sets. The results show that the proposed RL-RID-GridResponder can provide fast and accurate responses to ensure optimal power system operation under DoS and can extend to other system contingencies such as line outages and loss of loads.

Recent work has suggested that certain neural network architectures-particularly recurrent neural networks (RNNs) and implicit neural networks (INNs) are capable of logical extrapolation. That is, one may train such a network on easy instances of a specific task and then apply it successfully to more difficult instances of the same task. In this paper, we revisit this idea and show that (i) The capacity for extrapolation is less robust than previously suggested. Specifically, in the context of a maze-solving task, we show that while INNs (and some RNNs) are capable of generalizing to larger maze instances, they fail to generalize along axes of difficulty other than maze size. (ii) Models that are explicitly trained to converge to a fixed point (e.g. the INN we test) are likely to do so when extrapolating, while models that are not (e.g. the RNN we test) may exhibit more exotic limiting behaviour such as limit cycles, even when they correctly solve the problem. Our results suggest that (i) further study into why such networks extrapolate easily along certain axes of difficulty yet struggle with others is necessary, and (ii) analyzing the dynamics of extrapolation may yield insights into designing more efficient and interpretable logical extrapolators.

The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the $Gaia$ satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the full spectrum, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels for all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from $Gaia$ and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats for catalogue users. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way, but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies., Comment: 43 pages, 38 figures to be submitted to PASA. Accompanying the GALAH Data Release 4, see https://www.galah-survey.org and https://cloud.datacentral.org.au/teamdata/GALAH/public/GALAH_DR4/. All code available on http://github.com/svenbuder/GALAH_DR4/ and https://github.com/svenbuder/galah_dr4_paper. Comments welcome

Modern-day power systems have become increasingly cyber-physical due to the ongoing developments to the grid that include the rise of distributed energy generation and the increase of the deployment of many cyber devices for monitoring and control, such as the Supervisory Control and Data Acquisition (SCADA) system. Such capabilities have made the power system more vulnerable to cyber-attacks that can harm the physical components of the system. As such, it is of utmost importance to study both the physical and cyber components together, focusing on characterizing and quantifying the interdependency between these components. This paper focuses on developing an algorithm, named CyberDep, for Bayesian network generation through conditional probability calculations of cyber traffic flows between system nodes. Additionally, CyberDep is implemented on the temporal data of the cyber-physical emulation of the WSCC 9-bus power system. The results of this work provide a visual representation of the probabilistic relationships within the cyber and physical components of the system, aiding in cyber-physical interdependency quantification., Comment: Accepted and Presented at the 2024 Kansas Power and Energy Conference (KPEC 2024)

Altermagnets (AMs) are a new class of magnetic materials that combine the beneficial spintronics properties of ferromagnets and antiferromagnets, garnering significant attention recently. Here, we have identified altermagnetism in a layered intercalated transition metal diselenide, CoNb$_4$Se$_8$, which crystallizes with an ordered sublattice of intercalated Co atoms between NbSe$_2$ layers. Single crystals are synthesized, and the structural characterizations are performed using single crystal diffraction and scanning tunneling microscopy. Magnetic measurements reveal easy-axis antiferromagnetism below 168 K. Density functional theory (DFT) calculations indicate that A-type antiferromagnetic ordering with easy-axis spin direction is the ground state, which is verified through single crystal neutron diffraction experiments. Electronic band structure calculations in this magnetic state display spin-split bands, confirming altermagnetism in this compound. The layered structure of CoNb$_4$Se$_8$ presents a promising platform for testing various predicted properties associated with altermagnetism.

The persistence of the DAMA/LIBRA (DAMA) modulation over the past two decades has been a source of great contention within the dark matter community. The DAMA collaboration reports a persistent, modulating event rate within their setup of NaI(Tl) scintillating crystals at the INFN Laboratori Nazionali del Gran Sasso (LNGS) underground laboratory. A recent work alluded that this signal could have arisen due to an analysis artefact, caused by DAMA not accounting for time variation of decaying background radioisotopes in their analysis procedure. In this work, we examine in detail this 'induced modulation' effect, arguing that a number of aspects of the DAMA signal are incompatible with an induced modulation arising from decays of background isotopes over the lifetime of the experiment. Using a toy model of the DAMA/LIBRA experiment, we explore the induced modulation effect under different variations of the activities of the relevant isotopes - namely, $^3$H and $^{210}$Pb - highlighting the various inconsistencies between the resultant toy datasets and the DAMA signal. We stress the importance of the SABRE experiment, whose goal is to unambiguously test for the presence of such a modulating signal in an experiment using the same target material and comparable levels of background.

We apply the HanleRT Tenerife Inversion Code to the spectro-polarimetric observations obtained by the Chromospheric LAyer SpectroPolarimeter. This suborbital space experiment measured the variation with wavelength of the four Stokes parameters in the near-ultraviolet spectral region of the Mg II h & k lines over a solar disk area containing part of an active region plage and the edge of a sunspot penumbra. We infer the stratification of the temperature, the electron density, the line of-sight velocity, the micro-turbulent velocity, and the longitudinal component of the magnetic field from the observed intensity and circular polarization profiles. The inferred model atmosphere shows larger temperature and electron density in the plage and the superpenumbra regions than in the quiet regions. The shape of the plage region in terms of its brightness is similar to the pattern of the inferred longitudinal component of the magnetic field in the chromosphere, as well as to that of the overlying moss observed by AIA in the 171 A band, which suggests a similar magnetic origin for the heating in both the plage and the moss region. Moreover, this heating is particularly significant in the regions with larger inferred magnetic flux. In contrast, in the superpenumbra, the regions with larger electron density and temperature are usually found in between these regions with larger magnetic flux, suggesting that the details of the heating mechanism in the chromosphere of the superpenumbra may be different to those in the plage, but with the magnetic field still playing a key role., Comment: Accepted for publication in the Astrophysical Journal

We examine the low-energy excitations in the vicinity of the quantum critical point in LiHoF$_4$, a physical realization of the Transverse Field Ising Model, focusing on the long-range fluctuations which soften to zero energy at the ferromagnetic quantum phase transition. Microwave spectroscopy in tunable loop-gap resonator structures identifies and characterizes the soft mode and higher-energy electronuclear states. We study these modes as a function of frequency and magnetic fields applied transverse and parallel to the Ising axis. These are understood in the context of a theoretical model of a soft electronuclear mode that interacts with soft photons as well as soft phonons. We identify competing infrared divergences at the quantum critical point, coming from the photons and the electronuclear soft mode. It is an incomplete cancellation of these divergences that leads to the muted but distinct signatures observed in the experiments. The application of a longitudinal magnetic field gaps the soft mode. Measurements well away from the quantum critical point reveal a set of ``Walker'' modes associated with ferromagnetic domain dynamics., Comment: 20 pages, 14 figures

Language models exhibit scaling laws, whereby increasing model and dataset size yields predictable decreases in negative log likelihood, unlocking a dazzling array of capabilities. This phenomenon spurs many companies to train ever larger models in pursuit of ever improved performance. Yet, these models are vulnerable to adversarial inputs such as ``jailbreaks'' and prompt injections that induce models to perform undesired behaviors, posing a growing risk as models become more capable. Prior work indicates that computer vision models become more robust with model and data scaling, raising the question: does language model robustness also improve with scale? We study this question empirically in the classification setting, finding that without explicit defense training, larger models tend to be modestly more robust on most tasks, though the effect is not reliable. Even with the advantage conferred by scale, undefended models remain easy to attack in absolute terms, and we thus turn our attention to explicitly training models for adversarial robustness, which we show to be a much more compute-efficient defense than scaling model size alone. In this setting, we also observe that adversarially trained larger models generalize faster and better to modified attacks not seen during training when compared with smaller models. Finally, we analyze the offense/defense balance of increasing compute, finding parity in some settings and an advantage for offense in others, suggesting that adversarial training alone is not sufficient to solve robustness, even at greater model scales., Comment: 36 pages; updated to include new results and analysis

Human-Centric Software Engineering (HCSE) refers to the software engineering (SE) processes that put human needs and requirements as core practice throughout the software development life cycle. A large majority of software projects fail to cater to human needs and consequently run into budget, delivery, and usability issues. To support human-centric software engineering practices, it is important for universities to train their students on how to consider human needs. But what topics from HCSE should be provided in the undergraduate curriculum? Curriculum guidelines for software engineering are available, however do not represent update to date considerations for human-factors. To address this issue, this paper presents a scoping review to identify the topics and curriculum approaches suitable for teaching HCSE to undergraduate software engineering students. The scoping review was conducted according to the protocol by PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Through PRISMA-ScR, a total of 36 conference or journal papers were identified as viable for analysis,with 5 common themes found that describe topics and curriculum approaches relevant for teaching software engineering. Using the outcomes of the scoping review, this paper also analyses the Australian Software Engineering curriculum to understand the extent at which human centred software engineering topics are scaffolded into course structures. This paper concludes by suggesting topic scaffolding for the undergraduate curriculum that aligns with the software engineering process. Overall, by providing a focus on HCSE topics and curriculum approaches, the education of HCSE among current and future software engineers can increase, leading to long-term impact on the success of software projects for all stakeholders., Comment: The dataset associated with this paper is not going to be available and the work is incomplete without the dataset

This paper presents a scoping review of literature to examine who is reviewing educational immersive or extended reality - eduXR experiences and why. EduXR experiences in augmented, virtual or mixed reality take many forms, from supporting manual training, engaging learners in conservation, to provide opportunities for social connection. For users of eduXR, reviews of an experience can provide information that helps them determine whether it will meet their learning needs or not. The source of the review, that is, who they are and why they have conducted the review, is critical in helping the user judge the reviews quality and relevance. At present, there is no settled review system in place for eduXR, though relevant frameworks exist for serious games review with relevance and overlap for some, but not all, eduXR experiences. While some authors have engaged in preparing a detailed review structure for eduXR, there remains a need for a clear and simple way for users of eduXR to know details about reviewers, e.g., who and why, to help make it easier for users to identify relevant reviews and gain useful insight about eduXR experiences. To help address this issue, we conducted a scoping review asking the question; Who is creating eduXR reviews, and why? We identified 16 papers that present an academic evaluation on the review process of eduXR reviews. The 16 papers were analysed, coding for who themes and why themes over two separate cycles, using thematic analysis. An analysis looked to examine what we know regarding who is providing the reviews, and why, to help us to understand what enables, inhibits and what is yet unknown about how the eduXR community goes about making informed choices regarding the eduXR experiences they engage with., Comment: 14 pages

Let $\mathsf{KP}$ denote Kripke-Platek Set Theory and let $\mathsf{M}$ be the weak set theory obtained from $\mathsf{ZF}$ by removing the collection scheme, restricting separation to $\Delta_0$-formulae and adding an axiom asserting that every set is contained in a transitive set ($\mathsf{TCo}$). A result due to Kaufmann shows that every countable model, $\mathcal{M}$, of $\mathsf{KP}+\Pi_n\textsf{-Collection}$ has a proper $\Sigma_{n+1}$-elementary end extension. Here we show that there are limits to the amount of the theory of $\mathcal{M}$ that can be transferred to the end extensions that are guaranteed by Kaufmann's Theorem. Using admissible covers and the Barwise Compactness Theorem, we show that if $\mathcal{M}$ is a countable model $\mathsf{KP}+\Pi_n\textsf{-Collection}+\Sigma_{n+1}\textsf{-Foundation}$ and $T$ is a recursive theory that holds in $\mathcal{M}$, then there exists a proper $\Sigma_n$-elementary end extension of $\mathcal{M}$ that satisfies $T$. We use this result to show that the theory $\mathsf{M}+\Pi_n\textsf{-Collection}+\Pi_{n+1}\textsf{-Foundation}$ proves $\Sigma_{n+1}\textsf{-Separation}$., Comment: 23 pages. This is a later draft of arXiv:2201.04817

Laser frequency noise suppression is a critical requirement for the Laser Interferometer Space Antenna (LISA) mission to detect gravitational waves. The baseline laser stabilization is achieved using cavity pre-stabilization and a post-processing technique called Time-Delay-Interferometry (TDI). To enhance the margins for TDI, alternate laser locking schemes should be investigated. A novel stabilisation blending the excellent stability of the arm with the existing cavity reference has been shown theoretically to meet the first-generation TDI margins. This locking system was designed to be implemented as a firmware change and have minimal or no changes to the LISA hardware. This paper experimentally verifies the hybrid laser locking technique by utilizing two references - an optical cavity, and an interferometer with delay imparted using 10 km of optical fiber. The results indicate the viability of the combination of arm-cavity locking system for LISA. They show the key benefits envisioned by this technique; suppression of the cavity fluctuations by the arm sensor (by 21 dB in this demonstration) and reduction of Doppler pulling of the laser frequency, a key technical challenge for arm locking., Comment: 11 pages, 13 figures

Consciousness is notoriously hard to define with objective terms. An objective definition of consciousness is critically needed so that we might accurately understand how consciousness and resultant choice behaviour may arise in biological or artificial systems. Many theories have integrated neurobiological and psychological research to explain how consciousness might arise, but few, if any, outline what is fundamentally required to generate consciousness. To identify such requirements, I examine current theories of consciousness and corresponding scientific research to generate a new definition of consciousness from first principles. Critically, consciousness is the apparatus that provides the ability to make decisions, but it is not defined by the decision itself. As such, a definition of consciousness does not require choice behaviour or an explicit awareness of temporality despite both being well-characterised outcomes of conscious thought. Rather, requirements for consciousness include: at least some capability for perception, a memory for the storage of such perceptual information which in turn provides a framework for an imagination with which a sense of self can be capable of making decisions based on possible and desired futures. Thought experiments and observable neurological phenomena demonstrate that these components are fundamentally required of consciousness, whereby the loss of any one component removes the capability for conscious thought. Identifying these requirements provides a new definition for consciousness by which we can objectively determine consciousness in any conceivable agent, such as non-human animals and artificially intelligent systems., Comment: 16 pages, 1 figure, 2 tables, 74 references

There is considerable debate and evidence about how governments should regulate contractors and other firms, but little on how government should regulate schools. In the first phase of this study, we focus on the correlation between indices of state charter school policies and measures of charter quantity (market share) and three measures of quality: statewide student achievement growth from CREDO, closure of low-performing charter schools, and charter entry into low-performing school districts. States with no charter caps, multiple charter authorizers, and stronger contract renewal standards have higher charter market shares. We also see evidence of a quality-quantity trade-off. The regression coefficients on eight of the 11 policy variables are of opposite signs in the quality and quantity analyses. The positive correlation between charter market share and the number of charter authorizers motivates a follow-up analysis in which we test whether this correlation reflects causation. Using difference-in-differences analysis, we find evidence that adding a statewide authorizing body increased the statewide charter market share gradually over time.

Charter schools are privately operated public schools funded by the government with oversight from school districts, state education departments, or other government authorizers. This gives charter schools autonomy from many government rules and regulations, allows them to specialize and innovate in particular types of education, and gives parents more choices. With this autonomy also comes some additional accountability. If a charter school is not meeting the terms of its agreement, the government can close it or turn control over to another charter operator. However, there is little evidence about the appropriate mix of policies, the balance between autonomy and government oversight, and the trade-offs involved. This brief describes how charter regulation varies across states, shows how those regulations are related to charter school outcomes, and provides evidence of their policy effects. The purpose is to help address the larger question: how should the government regulate charter schools?

In this article, we construct codes with hierarchical locality using natural geometric structures in Artin-Schreier surfaces of the form $y^p-y=f(x,z)$. Our main theorem describes the codes, their hierarchical structure and recovery algorithms, and gives parameters. We also develop a family of examples using codes defined over $\mathbb{F}_{p^2}$ on the surface $y^p-y=x^{p+1}z^2+x^2z^{p+1}$. We use elementary methods to count the $\mathbb{F}_{p^2}$-rational points on the surface, enabling us to provide explicit hierarchical parameters and a better bound on minimum distance for these codes. An additional example and some generalizations are also considered.

In geostatistics, traditional spatial models often rely on the Gaussian Process (GP) to fit stationary covariances to data. It is well known that this approach becomes computationally infeasible when dealing with large data volumes, necessitating the use of approximate methods. A powerful class of methods approximate the GP as a sum of basis functions with random coefficients. Although this technique offers computational efficiency, it does not inherently guarantee a stationary covariance. To mitigate this issue, the basis functions can be "normalized" to maintain a constant marginal variance, avoiding unwanted artifacts and edge effects. This allows for the fitting of nearly stationary models to large, potentially non-stationary datasets, providing a rigorous base to extend to more complex problems. Unfortunately, the process of normalizing these basis functions is computationally demanding. To address this, we introduce two fast and accurate algorithms to the normalization step, allowing for efficient prediction on fine grids. The practical value of these algorithms is showcased in the context of a spatial analysis on a large dataset, where significant computational speedups are achieved. While implementation and testing are done specifically within the LatticeKrig framework, these algorithms can be adapted to other basis function methods operating on regular grids., Comment: Version 3

Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq 3$, and denote the eigenvalues as $\lambda_1=d/\sqrt{d-1}\geq \lambda_2\geq\lambda_3\cdots\geq \lambda_N$. We prove that the optimal (up to an extra $N^{{\rm o}_N(1)}$ factor, where ${\rm o}_N(1)$ can be arbitrarily small) eigenvalue rigidity holds. More precisely, denote $\gamma_i$ as the classical location of the $i$-th eigenvalue under the Kesten-Mckay law in decreasing order. Then with probability $1-N^{-1+{\rm o}_N(1)}$, \begin{align*} |\lambda_i-\gamma_i|\leq \frac{N^{{\rm o}_N(1)}}{N^{2/3} (\min\{i,N-i+1\})^{1/3}},\quad \text{ for all } i\in \{2,3,\cdots,N\}. \end{align*} In particular, the fluctuations of extreme eigenvalues are bounded by $N^{-2/3+{\rm o}_N(1)}$. This gives the same order of fluctuation as for the eigenvalues of matrices from the Gaussian Orthogonal Ensemble., Comment: 62 pages, 2 figures

We combine stellar orbits with the abundances of the heavy, $r$-process element europium and the light, $\alpha$-element, silicon to separate in-situ and accreted populations in the Milky Way across all metallicities. At high orbital energy, the accretion-dominated halo shows elevated values of [Eu/Si], while at lower energies, where many of the stars were born in-situ, the levels of [Eu/Si] are lower. These systematically different levels of [Eu/Si] in the MW and the accreted halo imply that the scatter in [Eu/$\alpha$] within a single galaxy is smaller than previously thought. At the lowest metallicities, we find that both accreted and in-situ populations trend down in [Eu/Si], consistent with enrichment via neutron star mergers. Through compiling a large dataset of abundances for 46 globular clusters (GCs), we show that differences in [Eu/Si] extend to populations of in-situ/accreted GCs. We interpret this consistency as evidence that in $r$-process elements, GCs trace the star formation history of their hosts, motivating their use as sub-Gyr timers of galactic evolution. Furthermore, fitting the trends in [Eu/Si] using a simple galactic chemical evolution model, we find that differences in [Eu/Si] between accreted and in-situ MW field stars cannot be explained through star formation efficiency alone. Finally, we show that the use of [Eu/Si] as a chemical tag between GCs and their host galaxies extends beyond the Local Group, to the halo of M31 - potentially offering the opportunity to do Galactic Archaeology in an external galaxy., Comment: Accepted for publication in MNRAS. Some edits, new figures and the discussion on GCE modeling made clearer following referee report. Core science results remain unchanged

Neuroscientists have worked on the problem of estimating synaptic properties, such as connectivity and strength, from simultaneously recorded spike trains since the 1960s. Recent years have seen renewed interest in the problem, coinciding with rapid advances in the technology of high-density neural recordings and optogenetics, which can be used to calibrate causal hypotheses about functional connectivity. Here, a rigorous causal inference framework for pairwise excitatory and inhibitory monosynaptic effects between spike trains is developed. Causal interactions are identified by separating spike interactions in pairwise spike trains by their timescales. Fast algorithms for computing accurate estimates of associated quantities are also developed. Through the lens of this framework, the link between biophysical parameters and statistical definitions of causality between spike trains is examined across a spectrum of dynamical systems simulations. In an idealized setting, we demonstrate a correspondence between the synaptic causal metric developed here and the probabilities of causation developed by Tian and Pearl. Since the probabilities of causation are derived under distinct assumptions and include data from experimental randomization, this opens up the possibility of testing the synaptic inference framework's assumptions with juxtacellular or optogenetic stimulation. We simulate such an experiment with a biophysically detailed channelrhodopsin model and show that randomization is not achieved; strong confounding persists even with strong stimulations. A principal goal is to ask how carefully articulated causal assumptions might better inform the design of neural stimulation experiments and, in turn, support experimental tests of those assumptions.

Educators, developers, and other stakeholders face challenges when creating, adapting, and utilizing virtual and augmented reality (XR) experiences for teaching curriculum topics. User created reviews of these applications provide important information about their relevance and effectiveness in supporting achievement of educational outcomes. To make these reviews accessible, relevant, and useful, they must be readily available and presented in a format that supports decision-making by educators. This paper identifies best practices for developing a new review ecosystem by analyzing existing approaches to providing reviews of interactive experiences. It focuses on the form and format of these reviews, as well as the mechanisms for sharing information about experiences and identifying which ones are most effective. The paper also examines the incentives that drive review creation and maintenance, ensuring that new experiences receive attention from reviewers and that relevant information is updated when necessary. The strategies and opportunities for developing an educational XR (eduXR) review ecosystem include methods for measuring properties such as quality metrics, engaging a broad range of stakeholders in the review process, and structuring the system as a closed loop managed by feedback and incentive structures to ensure stability and productivity. Computing educators are well-positioned to lead the development of these review ecosystems, which can relate XR experiences to the potential opportunities for teaching and learning that they offer., Comment: 29 pages, 13 figures

Field emission or dark current from RF electron guns is problematic for accelerators for several reasons, and can be more difficult to predict, measure and understand, compared to the main beam. The work presented here is a study of the dark current emitted from the CLARA 3GHz 2.5 cell electron gun with exchangeable photocathode, which is a type of gun used for single pass high quality low emittance beams for uses such as Free Electron Lasers. The main purpose of these studies was to identify sources of dark current emission within the gun, by examining the dark current distribution and patterns on scintillating screens. It is shown that the features of the patterns can be reproduced qualitatively, and to some extent quantitatively, by finite element simulations. Thus, certain surfaces within the gun and cathode apparatus which contribute most significantly to problematic dark current can be identified, and further development and preparation of the guns and their cathodes can be informed to minimise dark current.