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A large body of evidence indicates that well-implemented social and emotional learning (SEL) programs improve academic, social, and emotional outcomes for students and educators. Education policy has the potential to influence the high-quality implementation of SEL, from the school district, to the school, to the classroom. Before and during the coronavirus disease 2019 pandemic, U.S. states enacted supportive policies and conditions to promote SEL in schools. However, curricula that foster the development of social and emotional competences have been one of many controversies about the instructional content and instructional practices schools should use to teach students. Thus, legislators in nine states have proposed bills to prohibit or inhibit SEL instruction in kindergarten through grade 12 (K-12) schools. In this report, the authors investigate whether states' SEL policies (for and against) are associated with the implementation of SEL by K-12 schools, as reported by teachers and principals. In their approach, the authors merge the survey data they collected from educators with the results of the Collaborative for Academic, Social, and Emotional Learning's (CASEL's) nationwide scan of each state's and the District of Columbia's SEL-relevant policies and conditions. The authors also study whether SEL implementation is correlated with two teacher-reported indicators of positive student experience: supportive climate and student interest in learning. The authors' findings show whether state policymakers' SEL-related policies (including legislation and guidance) connect to schools' on-the-ground decisions and implementation, as reported by principals and teachers.

The detection of a stochastic gravitational wave background by pulsar timing arrays suggests the presence of a supermassive black hole binary population. Although the observed spectrum generally aligns with predictions from orbital evolution driven by gravitational wave emission in circular orbits, there is a discernible preference for a turnover at the lowest observed frequencies. This turnover could indicate a significant hardening phase, transitioning from early environmental influences to later stages predominantly influenced by gravitational wave emission. In the vicinity of these binaries, the ejection of stars or dark matter particles through gravitational three-body slingshots efficiently extracts orbital energy, leading to a low-frequency turnover in the spectrum. By analyzing the NANOGrav 15-year data, we assess how the gravitational wave spectrum depends on the initial inner galactic profile prior to disruption by binary ejections, accounting for a range of initial binary eccentricities. Our findings suggest a parsec-scale galactic center density around $10^6\,M_\odot/\textrm{pc}^3$ across most of the parameter space, offering insights into the environmental effects on black hole evolution and combined matter density near galaxy centers., Comment: 15 pages, 5 figures

The Vela pulsar (J0835-4510) is known to exhibit variations in Faraday rotation and dispersion on multi-decade timescales due to the changing sightline through the surrounding Vela supernova remnant and the Gum Nebula. Until now, variations in Faraday rotation towards Vela have not been studied on timescales less than around a decade. We present the results of a high-cadence observing campaign carried out with the Aperture Array Verification System 2 (AAVS2), a prototype SKA-Low station, which received a significant bandwidth upgrade in 2022. We collected observations of the Vela pulsar and PSR J0630-2834 (a nearby pulsar located outside the Gum Nebula), spanning $\sim 1\,\mathrm{yr}$ and $\sim 0.3\,\mathrm{yr}$ respectively, and searched for linear trends in the rotation measure (RM) as a function of time. We do not detect any significant trends on this timescale ($\sim$months) for either pulsar, but the constraints could be greatly improved with more accurate ionospheric models. For the Vela pulsar, the combination of our data and historical data from the published literature have enabled us to model long-term correlated trends in RM and dispersion measure (DM) over the past two decades. We detect a change in DM of $\sim 0.3\,\mathrm{cm}^{-3}\,\mathrm{pc}$ which corresponds to a change in electron density of $\sim 10^5\,\mathrm{cm}^{-3}$ on a transverse length scale of $\sim$1-2 au. The apparent magnetic field strength in the time-varying region changes from $240^{+30}_{-20}\,\mu\mathrm{G}$ to $-6.2^{+0.7}_{-0.9}\,\mu\mathrm{G}$ over the time span of the data set. As well as providing an important validation of polarimetry, this work highlights the pulsar monitoring capabilities of SKA-Low stations, and the niche science opportunities they offer for high-precision polarimetry and probing the microstructure of the magneto-ionic interstellar medium., Comment: 16 pages, 9 figures, 2 tables, published in PASA

We report the discovery of the repeating fast radio burst source FRB 20240209A using the CHIME/FRB telescope. We have detected 22 bursts from this repeater between February and July 2024, six of which were also recorded at the Outrigger station KKO. The 66-km long CHIME-KKO baseline can provide single-pulse FRB localizations along one dimension with $2^{\prime\prime}$ accuracy. The high declination of $\sim$86 degrees for this repeater allowed its detection with a rotating range of baseline vectors, enabling the combined localization region size to be constrained to $1^{\prime\prime}\times2^{\prime\prime}$. We present deep Gemini observations that, combined with the FRB localization, enabled a robust association of FRB 20240209A to the outskirts of a luminous galaxy (P(O|x) = 0.99; $L \approx 5.3 \times 10^{10}\,L_{\odot}$). FRB 20240209A has a projected physical offset of $40 \pm 5$ kpc from the center of its host galaxy, making it the FRB with the largest host galaxy offset to date. When normalized by the host galaxy size, the offset of FRB 20240209A is comparable to that of FRB 20200120E, the only FRB source known to originate in a globular cluster. We consider several explanations for the large offset, including a progenitor that was kicked from the host galaxy or in situ formation in a low-luminosity satellite galaxy of the putative host, but find the most plausible scenario to be a globular cluster origin. This, coupled with the quiescent, elliptical nature of the host as demonstrated in our companion paper, provide strong evidence for a delayed formation channel for the progenitor of the FRB source., Comment: Submitted to AAS Journals

Integrating floating photovoltaic (FPV) installations into offshore wind farms has been proposed as a major opportunity to scale up offshore renewable energy generation. The interaction between these hybrid wind-solar farms and the atmospheric boundary layer (ABL) is for the first time addressed in the present study. Idealized large-eddy simulations (LES) are used to investigate the flow through both isolated wind and solar farms, as well as combined wind-solar farms, in varying configurations and under different atmospheric conditions. When the FPV modules are arranged in long strips parallel to the flow direction, secondary motions arise due to the temperature difference between the warm FPV modules and colder sea surface, significantly affecting the horizontal distribution of mean wind speed in the ABL. Associated downdrafts between the strips increase entrainment of high-speed momentum from above, thereby increasing the wind speed at these locations. LES of hybrid wind-solar farms reveals that this is beneficial for wind turbines when they are located between the FPV arrays, leading, for the cases that we considered, to a farm-averaged power increase of up to 30% compared to an isolated wind farm. It is shown that the ratio between inertial and buoyancy forces, quantified by a heterogeneity Richardson number $Ri_h$, plays a crucial role in the formation of secondary flows and the resulting wind-farm power enhancement. We further show that no significant power gains, but also no losses emerge in situations when the solar panels are aligned perpendicular to the flow. Although the present results suggest a large potential for wind-solar hybridization, future research should focus on a wider range of scenarios, obtained from a realistic distribution of wind directions and speeds to quantify the potential beneficial impact on real annual power production.

Neurosymbolic approaches can add robustness to opaque neural systems by incorporating explainable symbolic representations. However, previous approaches have not used formal logic to contextualize queries to and validate outputs of large language models (LLMs). We propose \systemname{}, a novel neurosymbolic framework, to improve the robustness and reliability of LLMs in question-answering tasks. We provide \systemname{} with a domain-specific knowledge base, a logical reasoning system, and an integration to an existing LLM. This framework has two capabilities (1) context gathering: generating explainable and relevant context for a given query, and (2) validation: confirming and validating the factual accuracy of a statement in accordance with a knowledge base (KB). Our work opens a new area of neurosymbolic generative AI text validation and user personalization., Comment: Accepted at NeSy 2024

Considering the growing prominence of production-level AI and the threat of adversarial attacks that can evade a model at run-time, evaluating the robustness of models to these evasion attacks is of critical importance. Additionally, testing model changes likely means deploying the models to (e.g. a car or a medical imaging device), or a drone to see how it affects performance, making un-tested changes a public problem that reduces development speed, increases cost of development, and makes it difficult (if not impossible) to parse cause from effect. In this work, we used survival analysis as a cloud-native, time-efficient and precise method for predicting model performance in the presence of adversarial noise. For neural networks in particular, the relationships between the learning rate, batch size, training time, convergence time, and deployment cost are highly complex, so researchers generally rely on benchmark datasets to assess the ability of a model to generalize beyond the training data. To address this, we propose using accelerated failure time models to measure the effect of hardware choice, batch size, number of epochs, and test-set accuracy by using adversarial attacks to induce failures on a reference model architecture before deploying the model to the real world. We evaluate several GPU types and use the Tree Parzen Estimator to maximize model robustness and minimize model run-time simultaneously. This provides a way to evaluate the model and optimise it in a single step, while simultaneously allowing us to model the effect of model parameters on training time, prediction time, and accuracy. Using this technique, we demonstrate that newer, more-powerful hardware does decrease the training time, but with a monetary and power cost that far outpaces the marginal gains in accuracy.

The Small-Correlated-Against-Large Estimator (SCALE) for small-scale lensing of the cosmic microwave background (CMB) provides a novel method for measuring the amplitude of CMB lensing power without the need for reconstruction of the lensing field. In our previous study, we showed that the SCALE method can outperform existing reconstruction methods to detect the presence of lensing at small scales ($\ell \gg 3000$). Here we develop a procedure to include information from SCALE in cosmological parameter inference. We construct a precise neural network emulator to quickly map cosmological parameters to desired CMB observables such as temperature and lensing power spectra and SCALE cross spectra. We also outline a method to apply SCALE to full-sky maps of the CMB temperature field, and construct a likelihood for the application of SCALE in parameter estimation. SCALE supplements conventional observables such as the CMB power spectra and baryon acoustic oscillations in constraining parameters that are sensitive to the small-scale lensing amplitude such as the neutrino mass $m_\nu$. We show that including estimates of the small-scale lensing amplitude from SCALE in such an analysis provides enough constraining information to measure the minimum neutrino mass at $4\sigma$ significance in the scenario of minimal mass, and higher significance for higher mass. Finally, we show that SCALE will play a powerful role in constraining models of clustering that generate scale-dependent modulation to the distribution of matter and the lensing power spectrum, as predicted by models of warm or fuzzy dark matter., Comment: 18 pages, 8 figures, 6 tables, submitting to Physical Review D in a few days

The NANOGrav 15-year data provides compelling evidence for a stochastic gravitational-wave (GW) background at nanohertz frequencies. The simplest model-independent approach to characterizing the frequency spectrum of this signal consists in a simple power-law fit involving two parameters: an amplitude A and a spectral index \gamma. In this paper, we consider the next logical step beyond this minimal spectral model, allowing for a running (i.e., logarithmic frequency dependence) of the spectral index, \gamma_run(f) = \gamma + \beta \ln(f/f_ref). We fit this running-power-law (RPL) model to the NANOGrav 15-year data and perform a Bayesian model comparison with the minimal constant-power-law (CPL) model, which results in a 95% credible interval for the parameter \beta consistent with no running, \beta \in [-0.80,2.96], and an inconclusive Bayes factor, B(RPL vs. CPL) = 0.69 +- 0.01. We thus conclude that, at present, the minimal CPL model still suffices to adequately describe the NANOGrav signal; however, future data sets may well lead to a measurement of nonzero \beta. Finally, we interpret the RPL model as a description of primordial GWs generated during cosmic inflation, which allows us to combine our results with upper limits from big-bang nucleosynthesis, the cosmic microwave background, and LIGO-Virgo-KAGRA., Comment: 17 pages, 4 figures, 2 tables

Pulsar-timing-array experiments have reported evidence for a stochastic background of nanohertz gravitational waves consistent with the signal expected from a population of supermassive--black-hole binaries. Those analyses assume power-law spectra for intrinsic pulsar noise and for the background, as well as a Hellings--Downs cross-correlation pattern among the gravitational-wave--induced residuals across pulsars. These assumptions are idealizations that may not be realized in actuality. We test them in the NANOGrav 15 yr data set using Bayesian posterior predictive checks: after fitting our fiducial model to real data, we generate a population of simulated data-set replications, and use them to assess whether the optimal-statistic significance, inter-pulsar correlations, and spectral coefficients assume extreme values for the real data when compared to the replications. We confirm that the NANOGrav 15 yr data set is consistent with power-law and Hellings--Downs assumptions. We also evaluate the evidence for the stochastic background using posterior-predictive versions of the frequentist optimal statistic and of Bayesian model comparison, and find comparable significance (3.2\ $\sigma$ and 3\ $\sigma$ respectively) to what was previously reported for the standard statistics. We conclude with novel visualizations of the reconstructed gravitational waveforms that enter the residuals for each pulsar. Our analysis strengthens confidence in the identification and characterization of the gravitational-wave background as reported by NANOGrav., Comment: 20 pages, 14 Figures

We present a long-period radio transient (GLEAM-X J0704-37) discovered to have an optical counterpart, consistent with a cool main sequence star of spectral type M3. The radio pulsations occur at the longest period yet found, 2.9 hours, and were discovered in archival low-frequency data from the Murchison Widefield Array (MWA). High time resolution observations from MeerKAT show that pulsations from the source display complex microstructure and high linear polarisation, suggesting a pulsar-like emission mechanism occurring due to strong, ordered magnetic fields. The timing residuals, measured over more than a decade, show tentative evidence of a ~6-yr modulation. The high Galactic latitude of the system and the M-dwarf star excludes the magnetar interpretation, suggesting a more likely M-dwarf / white dwarf binary scenario for this system., Comment: 11 pages, 4 figures, submitted to ApJL

Synthetic-aperture radar images and mesoscale model results show that wind-farm wakes behave very differently than single-turbine wakes, e.g. with wakes that seemingly narrow and do not disperse over long distances. In the current work, we aim at better understanding the physical mechanisms that govern wind-farm wake behaviour and recovery. Hence, we study the wake properties of a 1.6 GW wind-farm operating in conventionally neutral boundary layers with four capping-inversion heights, i.e. 203, 319, 507 and 1001 m. In shallow boundary layers, we find strong flow decelerations which reduce the Coriolis force magnitude, leading to an anticlockwise wake deflection in the Northern Hemisphere. In deep boundary layers, the vertical turbulent entrainment of momentum adds clockwise-turning flow from aloft into the wake region, leading to a faster recovery rate and a clockwise wake deflection. To estimate the wake properties, we develop a simple model that fits the velocity magnitude profiles along the spanwise direction. Based on this, we observe that the wake narrows along the downstream direction in all cases. Further, a detailed momentum budget analysis shows that the wake is mostly replenished by turbulent vertical entrainment in deep boundary layers. In shallow boundary layers, the capping inversion limits vertical motions and wakes are mostly replenished by mean flow entrainment in the spanwise direction. Moreover, in these cases, we observe a counterclockwise flow rotation near the left edge of the wake, which persists at each location downstream of the farm, giving rise to local strong streamwise velocity gradients along the spanwise direction.

The most precise determination of the sum of neutrino masses from cosmological data, derived from analysis of the cosmic microwave background (CMB) and baryon acoustic acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI), favors a value below the minimum inferred from neutrino flavor oscillation experiments. We explore which data is most responsible of this puzzling aspect of the current constraints on neutrino mass and whether it is related to other anomalies in cosmology. We demonstrate conclusively that the preference for negative neutrino masses is a consequence of larger than expected lensing of the CMB in both the two- and four-point lensing statistics. Furthermore, we show that this preference is robust to changes in likelihoods of the BAO and CMB optical depth analyses given the available data. We then show that this excess clustering is not easily explained by changes to the expansion history and is likely distinct from the preference for for dynamical dark energy in DESI BAO data. Finally, we discuss how future data may impact these results, including an analysis of Planck CMB with mock DESI 5-year data. We conclude that the negative neutrino mass preference is likely to persist even as more cosmological data is collected in the near future., Comment: 35 pages, 12 figures, 2 tables

Neutron stars and white dwarfs are both dense remnants of post-main-sequence stars. Pulsars, magnetars and strongly magnetised white dwarfs have all been seen to been observed to exhibit coherent, pulsed radio emission in relation to their rotational period. Recently, a new type of radio long period transient (LPT) has been discovered. The bright radio emission of LPTs resembles that of radio pulsars and magnetars. However, they pulse on timescales (minutes) much longer than previously seen. While minute timescales are common rotation periods for white dwarfs, LPTs are much brighter than the known pulsating white dwarfs, and dipolar radiation from isolated (as opposed to binary) magnetic white dwarfs has yet to be observed. Here, we report the discovery of a new $\sim$421~s LPT, CHIME J0630+25, using the CHIME/FRB and CHIME/Pulsar instruments. We used standard pulsar timing techniques and obtained a phase-coherent timing solution which yielded limits on the inferred magnetic field and characteristic age. CHIME J0630+25 is remarkably nearby ($170 \pm 80$~pc), making it the closest LPT discovered to date., Comment: Submitted

Based on the rate of change of its orbital period, PSR J2043+1711 has a substantial peculiar acceleration of 3.5 $\pm$ 0.8 mm/s/yr, which deviates from the acceleration predicted by equilibrium Milky Way models at a $4\sigma$ level. The magnitude of the peculiar acceleration is too large to be explained by disequilibrium effects of the Milky Way interacting with orbiting dwarf galaxies ($\sim$1 mm/s/yr), and too small to be caused by period variations due to the pulsar being a redback. We identify and examine two plausible causes for the anomalous acceleration: a stellar flyby, and a long-period orbital companion. We identify a main-sequence star in \textit{Gaia} DR3 and Pan-STARRS DR2 with the correct mass, distance, and on-sky position to potentially explain the observed peculiar acceleration. However, the star and the pulsar system have substantially different proper motions, indicating that they are not gravitationally bound. However, it is possible that this is an unrelated star that just happens to be located near J2043+1711 along our line of sight (chance probability of 1.6\%). Therefore, we also constrain possible orbital parameters for a circumbinary companion in a hierarchical triple system with J2043+1711; the changes in the spindown rate of the pulsar are consistent with an outer object that has an orbital period of 80 kyr, a companion mass of 0.3 $M_\odot$ (indicative of a white dwarf or low-mass star), and a semi-major axis of 2000 AU. Continued timing and/or future faint optical observations of J2043+1711 may eventually allow us to differentiate between these scenarios.

We conducted extensive experiments on domain adaptation of the Meta-Llama-3-70B-Instruct model on SEC data, exploring its performance on both general and domain-specific benchmarks. Our focus included continual pre-training (CPT) and model merging, aiming to enhance the model's domain-specific capabilities while mitigating catastrophic forgetting. Through this study, we evaluated the impact of integrating financial regulatory data into a robust language model and examined the effectiveness of our model merging techniques in preserving and improving the model's instructive abilities. The model is accessible at hugging face: https://huggingface.co/arcee-ai/Llama-3-SEC-Base, arcee-ai/Llama-3-SEC-Base. This is an intermediate checkpoint of our final model, which has seen 20B tokens so far. The full model is still in the process of training. This is a preprint technical report with thorough evaluations to understand the entire process., Comment: 8 pages, 6 figures

Pulsar timing arrays (PTAs) have made tremendous progress and are now showing strong evidence for the gravitational-wave background (GWB). Further probing the origin and characteristics of the GWB will require more generalized analysis techniques. Bayesian methods are most often used but can be computationally expensive. On the other hand, frequentist methods, like the PTA Optimal Statistic (OS), are more computationally efficient and can produce results that are complementary to Bayesian methods, allowing for stronger statistical cases to be built from a confluence of different approaches. In this work we expand the capabilities of the OS through a technique we call the Per-Frequency Optimal Statistic (PFOS). The PFOS removes the underlying power-law assumption inherent in previous implementations of the OS, and allows one to estimate the GWB spectrum in a frequency-by-frequency manner. We have also adapted a recent generalization from the OS pipeline into the PFOS, making it capable of accurately characterizing the spectrum in the intermediate and strong GW signal regimes using only a small fraction of the necessary computational resources when compared with fully-correlated Bayesian methods, while also empowering many new types of analyses not possible before. We find that even in the strong GW signal regime, where the GWB dominates over noise in all frequencies, the injected value of the signal lies within the 50th-percentile of the PFOS uncertainty distribution in 41-45% of simulations, remaining 3$\sigma$-consistent with unbiased estimation., Comment: 23 pages, 9 figures,submitted to Physical Review D

The Vera C. Rubin Observatory is a unique facility for survey astronomy that will soon be commissioned and begin operations. Crucial to many of its scientific goals is the achievement of sustained high image quality, limited only by the seeing at the site. This will be maintained through an Active Optics System (AOS) that controls optical element misalignments and corrects mirror figure error to minimize aberrations caused by both thermal and gravitational distortions. However, the large number of adjustment degrees of freedom available on the Rubin Observatory introduces a range of degeneracies, including many that are \textit{noise-induced} due to imperfect measurement of the wavefront errors. We present a structured methodology for identifying these degeneracies through an analysis of image noise level. We also present a novel scaling strategy based on Truncated Singular Value Decomposition (TSVD) that mitigates the degeneracy, and optimally distributes the adjustment over the available degrees of freedom. Our approach ensures the attainment of optimal image quality, while avoiding excursions around the noise-induced subspace of degeneracies, marking a significant improvement over the previous techniques adopted for Rubin, which were based on an Optimal Integral Controller (OIC). This new approach is likely to also yield significant benefits for all telescopes that incorporate large numbers of degrees of freedom of adjustment., Comment: 19 pages, 8 figures, 4 tables. Submitted to ApJ

Studying transient phenomena, such as individual pulses from pulsars, has garnered considerable attention in the era of astronomical big data. Of specific interest to this study are Rotating Radio Transients (RRATs), nulling, and intermittent pulsars. This study introduces a new algorithm named LuNfit, tailored to correct the selection biases originating from the telescope and detection pipelines. Ultimately LuNfit estimates the intrinsic luminosity distribution and nulling fraction of the single pulses emitted by pulsars. LuNfit relies on Bayesian nested sampling so that the parameter space can be fully explored. Bayesian nested sampling also provides the additional benefit of simplifying model comparisons through the Bayes ratio. The robustness of LuNfit is shown through simulations and applying LuNfit onto pulsars with known nulling fractions. LuNfit is then applied to three RRATs, J0012+5431, J1538+1523, and J2355+1523, extracting their intrinsic luminosity distribution and burst rates. We find that their nulling fraction is 0.4(2), 0.749(5) and 0.995(2) respectively. We further find that a log-normal distribution likely describes the single pulse luminosity distribution of J0012+5431 and J1538+1523, while the Bayes ratio for J2355+1523 slightly favors an exponential distribution. We show the conventional method of correcting selection effects by "scaling up" the missed fraction of radio transients can be unreliable when the mean luminosity of the source is faint relative to the telescope sensitivity. Finally, we discuss the limitations of the current implementation of LuNfit while also delving into potential enhancements that would enable LuNfit to be applied to sources with complex pulse morphologies., Comment: Accepted by ApJ

Many accretion-powered pulsars rotate in magnetocentrifugal disequilibrium, spinning up or down secularly over multi-year intervals. The magnetic dipole moment $\mu$ of such systems cannot be inferred uniquely from the time-averaged aperiodic X-ray flux $\langle L(t) \rangle$ and pulse period $\langle P(t) \rangle$, because the radiative efficiency of the accretion is unknown and degenerate with the mass accretion rate. Here we circumvent the degeneracy by tracking the fluctuations in the unaveraged time series $L(t)$ and $P(t)$ using an unscented Kalman filter, whereupon $\mu$ can be estimated uniquely, up to the uncertainties in the mass, radius and distance of the star. The analysis is performed on Rossi X-ray Timing Explorer observations for $24$ X-ray transients in the Small Magellanic Cloud, which have been monitored regularly for $\sim 16$ years. As well as independent estimates of $\mu$, the analysis yields time-resolved histories of the mass accretion rate and the Maxwell stress at the disk-magnetosphere boundary for each star, and hence auto- and cross-correlations involving the latter two state variables. The inferred fluctuation statistics convey important information about the complex accretion physics at the disk-magnetosphere boundary., Comment: 42 pages, 10 figures, accepted for publication in The Astrophysical Journal

The stable boundary layer (SBL) subjected to large-scale subsidence is studied through large-eddy simulations (LESs) with fixed surface temperature and a linear subsidence velocity profile. These boundary layers reach a truly steady state, where thermal equilibrium is established by a balance between surface cooling and subsidence-induced heating. We identify three governing dimensionless groups by scaling the governing equations with the geostrophic wind and Coriolis frequency, and systematically investigate the impact of these external parameters on global flow properties and mean profiles in the steady state. The SBL depth, low-level jet, and the magnitude of the turbulent momentum flux are reduced when the subsidence rate or Buoyancy number increases, while surface heat flux is enhanced. The shape of normalized mean profiles of temperature and heat flux is mainly determined by the subsidence rate, while they collapse for varying buoyancy and surface Rossby numbers. We develop empirical correlations for the stability parameter $h_{\theta}/L_O$ and a thermal shape factor, and propose a new unidirectional geostrophic drag law, to form a closed set of equations that estimates relevant flow properties from external parameters. The estimation errors compared to the LES data are less than 5% for friction velocity and surface heat flux, and at most 10% for the SBL depth $h_{\theta}$. Within the surface layer, dimensionless velocity and temperature gradients in the steady SBL with subsidence show acceptable agreement to Monin-Obukhov similarity theory, while the collapse is improved when a recently proposed mixed scaling parameter, that includes $h_{\theta}/L_O$, is used.

The phenomenon of pulsar nulling, where pulsars temporarily and stochastically cease their radio emission, is thought to be indicative of a `dying' pulsar, where radio emission ceases entirely. Here we report the discovery of a long-period pulsar, PSR J0452-3418, from the ongoing Southern-sky MWA Rapid Two-meter (SMART) pulsar survey. The pulsar has a rotation period of ${\sim}$1.67\,s and a dispersion measure of 19.8\,\dmu, and it exhibits both quasi-periodic nulling and sub-pulse drifting. Periodic nulling is uncommon, only reported in $<1$\% of the pulsar population, with even a smaller fraction showing periodic nulling and sub-pulse drifting. We describe the discovery and follow-up of the pulsar, including a positional determination using high-resolution imaging with the upgraded Giant Metrewave Radio Telescope (uGMRT), initial timing analysis using the combination of MWA and uGMRT data, and detailed characterisation of the nulling and drifting properties in the MWA's frequency band (140-170\,MHz). Our analysis suggests a nulling fraction of 34$\pm6$\% and a nulling periodicity of 42$^{+1.5}_{-1.3}$ pulses. We measure the phase ($P_2$) and time modulation ($P_3$) caused by the sub-pulse drifting, with an average $P_2$ of 7.1$^{+26.3}_{-3.1}$ degrees and a $P_3$ of 4.8$^{+1.5}_{-0.9}$ pulses. We compare and contrast the observed properties with those of other pulsars that exhibit sub-pulse drifting and quasi-periodic nulling phenomena, and find that the majority of these objects tend to be in the `death valley' in the period-period derivative ($P$-$\dot{P}$) diagram. We also discuss some broader implications for pulsar emission physics and the detectability of similar objects using next-generation pulsar surveys., Comment: 16 pages, 9 Figures, 4 Tables, Accepted for ApJ***

Pulsar timing arrays (PTAs) are designed to detect low-frequency gravitational waves (GWs). GWs induce achromatic signals in PTA data, meaning that the timing delays do not depend on radio-frequency. However, pulse arrival times are also affected by radio-frequency dependent "chromatic" noise from sources such as dispersion measure (DM) and scattering delay variations. Furthermore, the characterization of GW signals may be influenced by the choice of chromatic noise model for each pulsar. To better understand this effect, we assess if and how different chromatic noise models affect achromatic noise properties in each pulsar. The models we compare include existing DM models used by NANOGrav and noise models used for the European PTA Data Release 2 (EPTA DR2). We perform this comparison using a subsample of six pulsars from the NANOGrav 15 yr data set, selecting the same six pulsars as from the EPTA DR2 six-pulsar dataset. We find that the choice of chromatic noise model noticeably affects the achromatic noise properties of several pulsars. This is most dramatic for PSR J1713+0747, where the amplitude of its achromatic red noise lowers from $\log_{10}A_{\text{RN}} = -14.1^{+0.1}_{-0.1}$ to $-14.7^{+0.3}_{-0.5}$, and the spectral index broadens from $\gamma_{\text{RN}} = 2.6^{+0.5}_{-0.4}$ to $\gamma_{\text{RN}} = 3.5^{+1.2}_{-0.9}$. We also compare each pulsar's noise properties with those inferred from the EPTA DR2, using the same models. From the discrepancies, we identify potential areas where the noise models could be improved. These results highlight the potential for custom chromatic noise models to improve PTA sensitivity to GWs.

In the gravitational-wave analysis of pulsar-timing-array datasets, parameter estimation is usually performed using Markov Chain Monte Carlo methods to explore posterior probability densities. We introduce an alternative procedure that relies instead on stochastic gradient-descent Bayesian variational inference, whereby we obtain the weights of a neural-network approximation of the posterior by minimizing the Kullback-Leibler divergence of the approximation from the exact posterior. This technique is distinct from simulation-based inference with normalizing flows, since we train the network for a single dataset, rather than the population of all possible datasets, and we require the computation of the data likelihood and its gradient. Unlike Markov Chain methods, our technique can transparently exploit highly parallel computing platforms. This makes it extremely fast on modern graphical processing units, where it can analyze the NANOGrav 15-yr dataset in few tens of minutes, depending on the probabilistic model, as opposed to hours or days with the analysis codes used until now. We expect that this speed will unlock new kinds of astrophysical and cosmological studies of pulsar-timing-array datasets. Furthermore, variational inference would be viable in other contexts of gravitational-wave data analysis as long as differentiable and parallelizable likelihoods are available., Comment: 6 pages, 1 figure

The baryon acoustic oscillation (BAO) analysis from the first year of data from the Dark Energy Spectroscopic Instrument (DESI), when combined with data from the cosmic microwave background (CMB), has placed an upper-limit on the sum of neutrino masses, $\sum m_\nu < 70$ meV (95%). In addition to excluding the minimum sum associated with the inverted hierarchy, the posterior is peaked at $\sum m_\nu = 0$ and is close to excluding even the minumum sum, 58 meV at 2$\sigma$. In this paper, we explore the implications of this data for cosmology and particle physics. The sum of neutrino mass is determined in cosmology from the suppression of clustering in the late universe. Allowing the clustering to be enhanced, we extended the DESI analysis to $\sum m_\nu < 0$ and find $\sum m_\nu = - 160 \pm 90$ meV (68%), and that the suppression of power from the minimum sum of neutrino masses is excluded at 99% confidence. We show this preference for negative masses makes it challenging to explain the result by a shift of cosmic parameters, such as the optical depth or matter density. We then show how a result of $\sum m_\nu =0$ could arise from new physics in the neutrino sector, including decay, cooling, and/or time-dependent masses. These models are consistent with current observations but imply new physics that is accessible in a wide range of experiments. In addition, we discuss how an apparent signal with $\sum m_\nu < 0$ can arise from new long range forces in the dark sector or from a primordial trispectrum that resembles the signal of CMB lensing., Comment: 42 pages, 6 figures, 1 table; v2: minor corrections

The Radio Neutrino Observatory - Greenland (RNO-G) seeks discovery of ultra-high energy neutrinos from the cosmos through their interactions in ice. The science program extends beyond particle astrophysics to include radioglaciology and, as we show herein, solar observations, as well. Currently seven of 35 planned radio-receiver stations (24 antennas/station) are operational. These stations are sensitive to impulsive radio signals with frequencies between 80 and 700 MHz and feature a neutrino trigger threshold for recording data close to the thermal floor. RNO-G can also trigger on elevated signals from the Sun, resulting in nanosecond resolution time-domain flare data; such temporal resolution is significantly shorter than from most dedicated solar observatories. In addition to possible RNO-G solar flare polarization measurements, the Sun also represents an extremely useful above-surface calibration source. Using RNO-G data recorded during the summers of 2022 and 2023, we find signal excesses during solar flares reported by the solar-observing Callisto network and also in coincidence with $\sim$2/3 of the brightest excesses recorded by the SWAVES satellite. These observed flares are characterized by significant time-domain impulsivity. Using the known position of the Sun, the flare sample is used to calibrate the RNO-G absolute pointing on the radio signal arrival direction to sub-degree resolution. We thus establish the Sun as a regularly observed astronomical calibration source to provide the accurate absolute pointing required for neutrino astronomy.

Extreme rainfall in the Indian summer monsoon can be destructive and deadly. Although El Ni\~no/ events in the equatorial Pacific make dry days and whole summers more likely throughout India, their influence on daily extremes is not well established. Despite this summer-mean drying effect, we show using observational data spanning 1901-2020 that El Ni\~no increases extreme rainfall likelihoods within monsoonal India, especially in the the summer's core rainy areas of central-eastern India and the narrow southwestern coastal band. Conversely, extremes are broadly suppressed in the drier southeast and far northwest, and more moderate accumulations are inhibited throughout the domain. These rainfall signals appear driven by corresponding ones in convective buoyancy, provided both the undilute instability of near-surface air and its dilution by mixing with drier air above are accounted for. When the summer ENSO state is predicted from a seasonal forecast ensemble initialized in May, the extreme rainfall patterns broadly persist, suggesting the potential for skillful seasonal forecasts. The framework of analyzing the full distributions of rainfall and convective buoyancy could be usefully applied to hourly extremes, other tropical regions under ENSO, other variability modes, and to trends in extreme rainfall under climate change., Comment: 43 pages, 13 figures

The cosmic merger history of supermassive black hole binaries (SMBHBs) is expected to produce a low-frequency gravitational wave background (GWB). Here we investigate how signs of the discrete nature of this GWB can manifest in pulsar timing arrays through excursions from, and breaks in, the expected $f_{\mathrm{GW}}^{-2/3}$ power-law of the GWB strain spectrum. To do this, we create a semi-analytic SMBHB population model, fit to NANOGrav's 15 yr GWB amplitude, and with 1,000 realizations we study the populations' characteristic strain and residual spectra. Comparing our models to the NANOGrav 15 yr spectrum, we find two interesting excursions from the power-law. The first, at $2 \; \mathrm{nHz}$, is below our GWB realizations with $p$-value significance $p = 0.05$ to $0.06$ ($\approx 1.8 \sigma - 1.9 \sigma$). The second, at $16 \; \mathrm{nHz}$, is above our GWB realizations with $p = 0.04$ to $0.15$ ($\approx 1.4 \sigma - 2.1 \sigma$). We explore the properties of a loud SMBHB which could cause such an excursion. Our simulations also show that the expected number of SMBHBs decreases by three orders of magnitude, from $\sim 10^6$ to $\sim 10^3$, between $2\; \mathrm{nHz}$ and $20 \; \mathrm{nHz}$. This causes a break in the strain spectrum as the stochasticity of the background breaks down at $26^{+28}_{-19} \; \mathrm{nHz}$, consistent with predictions pre-dating GWB measurements. The diminished GWB signal from SMBHBs at frequencies above the $26$~nHz break opens a window for PTAs to detect continuous GWs from individual SMBHBs or GWs from the early universe., Comment: 10 pages, 8 figures, 1 appendix, submitted to ApJ

Motivated by problems in categorical database theory, we introduce and compare two notions of presentation for profunctors, uncurried and curried, which arise intuitively from thinking of profunctors either as functors $\mathcal{C}^\text{op} \times \mathcal{D} \to \textbf{Set}$ or $\mathcal{C}^\text{op} \to \textbf{Set}^{\mathcal{D}}$. Although the Cartesian closure of $\textbf{Cat}$ means these two perspectives can be used interchangeably at the semantic level, a surprising amount of subtlety is revealed when looking through the lens of syntax. Indeed, we prove that finite uncurried presentations are strictly more expressive than finite curried presentations, hence the two notions do not induce the same class of finitely presentable profunctors. Moreover, an explicit construction for the composite of two curried presentations shows that the class of finitely curried presentable profunctors is closed under composition, in contrast with the larger class of finitely uncurried presentable profunctors, which is not. This shows that curried profunctor presentations are more appropriate for computational tasks that use profunctor composition. We package our results on curried profunctor presentations into a double equivalence from a syntactic double category into the double category of profunctors. Finally, we study the relationship between curried and uncurried presentations, leading to the introduction of curryable presentations. These constitute a subcategory of uncurried presentations which is equivalent to the category of curried presentations, therefore acting as a bridge between the two syntactic choices., Comment: 12 pages + Bibliography and Appendices. Comments welcome!

Very different processes characterize the decoupling of neutrinos to form the cosmic neutrino background (C$\nu$B) and the much later decoupling of photons from thermal equilibrium to form the cosmic microwave background (CMB). The C$\nu$B emerges from the fuzzy, energy-dependent neutrinosphere and encodes the physics operating in the early universe in the temperature range $T\sim 10\,{\rm MeV}$ to $T\sim10\,{\rm keV}$. This is the epoch where beyond Standard Model (BSM) physics may be influential in setting the light element abundances and the necessarily distorted fossil neutrino energy spectra. Here we use techniques honed in extensive CMB studies to analyze the C$\nu$B as calculated in detailed neutrino energy transport and nuclear reaction simulations. Our moment method, relative entropy, and differential visibility approach can leverage future high precision CMB and primordial abundance measurements to provide new insights into the C$\nu$B and any BSM physics it encodes. We demonstrate that the evolution of the energy spectrum of the C$\nu$B throughout the weak decoupling epoch is accurately captured in the Standard Model by only three parameters per species, a non-trivial conclusion given the deviation from thermal equilibrium. Furthermore, we can interpret each of the three parameters as physical characteristics of a non-equilibrium system. The success of our compact description within the Standard Model motivates its use also in BSM scenarios. We demonstrate how observations of primordial light element abundances can be used to place constraints on the C$\nu$B energy spectrum, deriving response functions that can be applied for general C$\nu$B spectral distortions. Combined with the description of those deviations that we develop here, our methods provide a convenient and powerful framework to constrain the impact of BSM physics on the C$\nu$B., Comment: v2: Added Figure 9, Appendix B, and references; Updated to match published version; v1: 50 pages, 14 figures

In the standard two-component crust-superfluid model of a neutron star, timing noise can arise when the two components are perturbed by stochastic torques. Here it is demonstrated how to analyse fluctuations in radio pulse times of arrival with a Kalman filter to measure physical properties of the two-component model, including the crust-superfluid coupling time-scale and the variances of the crust and superfluid torques. The analysis technique, validated previously on synthetic data, is applied to observations with the Molonglo Observatory Synthesis Telescope of the representative pulsar PSR J1359$-$6038. It is shown that the two-component model is preferred to a one-component model, with log Bayes factor $6.81 \pm 0.02$. The coupling time-scale and the torque variances on the crust and superfluid are measured with $90\%$ confidence to be $10^{7.1^{+0.8}_{-0.5}}$ $\rm{s}$ and $10^{-24.0^{+0.4}_{-5.6}}$ $\rm{rad^2~s^{-3}}$ and $10^{-21.7^{+3.5}_{-0.9}}$ $\rm{rad^2~s^{-3}}$ respectively., Comment: 18 pages, 13 figures. Accepted for publication in MNRAS

The rapid expansion of the open-source language model landscape presents an opportunity to merge the competencies of these model checkpoints by combining their parameters. Advances in transfer learning, the process of fine-tuning pretrained models for specific tasks, has resulted in the development of vast amounts of task-specific models, typically specialized in individual tasks and unable to utilize each other's strengths. Model merging facilitates the creation of multitask models without the need for additional training, offering a promising avenue for enhancing model performance and versatility. By preserving the intrinsic capabilities of the original models, model merging addresses complex challenges in AI - including the difficulties of catastrophic forgetting and multitask learning. To support this expanding area of research, we introduce MergeKit, a comprehensive, open-source library designed to facilitate the application of model merging strategies. MergeKit offers an extensible framework to efficiently merge models on any hardware, providing utility to researchers and practitioners. To date, thousands of models have been merged by the open-source community, leading to the creation of some of the worlds most powerful open-source model checkpoints, as assessed by the Open LLM Leaderboard. The library is accessible at https://github.com/arcee-ai/MergeKit., Comment: 11 pages, 4 figures