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Many printed electronic applications require strain-independent electrical properties to ensure deformation-independent performance. Thus, developing printed, flexible devices using 2D and other nanomaterials will require an understanding of the effect of strain on the electrical properties of nano-networks. Here we introduce novel AC electrical techniques to fully characterise the effect of strain on the resistance of high mobility printed networks, fabricated from of electrochemically exfoliated MoS2 nanosheets. These devices were initially characterised using DC piezoresistance measurements and showed good cyclability and a linear strain response, consistent with a low gauge factor of G~3. However, AC impedance spectroscopy measurements, performed as a function of strain, allowed the measurement of the effects of strain on both the nanosheets and the inter-nanosheet junctions separately. The junction resistance was found to increase linearly with strain, while the nanosheet resistance remained constant. This response is consistent with strain-induced sliding of the highly-aligned nanosheets past one another, without any strain being transferred to the sheets themselves. Our approach allows us to individually estimate the contributions of dimensional factors (G~1.4) and intrinsic factors (G~1.9) to the total gauge factor. This novel technique may provide insight into other piezoresistive systems., Comment: 3 Figures

The Workflows Community Summit gathered 111 participants from 18 countries to discuss emerging trends and challenges in scientific workflows, focusing on six key areas: time-sensitive workflows, AI-HPC convergence, multi-facility workflows, heterogeneous HPC environments, user experience, and FAIR computational workflows. The integration of AI and exascale computing has revolutionized scientific workflows, enabling higher-fidelity models and complex, time-sensitive processes, while introducing challenges in managing heterogeneous environments and multi-facility data dependencies. The rise of large language models is driving computational demands to zettaflop scales, necessitating modular, adaptable systems and cloud-service models to optimize resource utilization and ensure reproducibility. Multi-facility workflows present challenges in data movement, curation, and overcoming institutional silos, while diverse hardware architectures require integrating workflow considerations into early system design and developing standardized resource management tools. The summit emphasized improving user experience in workflow systems and ensuring FAIR workflows to enhance collaboration and accelerate scientific discovery. Key recommendations include developing standardized metrics for time-sensitive workflows, creating frameworks for cloud-HPC integration, implementing distributed-by-design workflow modeling, establishing multi-facility authentication protocols, and accelerating AI integration in HPC workflow management. The summit also called for comprehensive workflow benchmarks, workflow-specific UX principles, and a FAIR workflow maturity model, highlighting the need for continued collaboration in addressing the complex challenges posed by the convergence of AI, HPC, and multi-facility research environments.

Elementary and secondary district leaders seeking to recruit teachers and diversify their teaching workforce will find useful, research-based strategies in this brief from the Region 4 Comprehensive Center. The brief focuses on ways to develop work-based learning programs in secondary schools that engage students in considering teacher careers. Drawing on insights from 14 programs, this brief summarizes five useful strategies of teacher-focused work-based learning programs, including targeted courses, cohort model and peer supports, strategic counseling, dual enrollment, and field experiences. It also provides helpful background into the historic challenges around recruiting and retaining teachers of color.

The Radio Neutrino Observatory in Greenland (RNO-G) is the first in-ice radio array in the northern hemisphere for the detection of ultra-high energy neutrinos via the coherent radio emission from neutrino-induced particle cascades within the ice. The array is currently in phased construction near Summit Station on the Greenland ice sheet, with 7~stations deployed during the first two boreal summer field seasons of 2021 and 2022. In this paper, we describe the installation and system design of these initial RNO-G stations, and discuss the performance of the array as of summer 2024.

Emerging Large Language Model (LLM) applications require long input prompts to perform complex downstream tasks like document analysis and code generation. For these long context length applications, the length of the input prompt poses a significant challenge in terms of inference efficiency since the inference costs increase linearly with sequence length. However, for many of these applications, much of the context in the prompt is fixed across different user inputs, thereby providing the opportunity to perform offline optimizations to process user inputs quickly, as they are received. In this work, we propose Squeezed Attention as a mechanism to accelerate LLM applications where a large portion of the input prompt is fixed. We first leverage K-means clustering offline to group the keys for the fixed context based on semantic similarity and represent each cluster with a single centroid value. During inference, we compare query tokens from the user input with the centroids to predict which of the keys from the fixed context are semantically relevant and need to be loaded during inference. We then compute exact attention using only these important keys from the fixed context, thereby reducing bandwidth and computational costs. We also extend our method to use a hierarchical centroid lookup to identify important keys, which can reduce the complexity of attention from linear to logarithmic with respect to the context length. We implement optimized Triton kernels for centroid comparison and sparse FlashAttention with important keys, achieving more than 4x speedups during both the prefill and generation phases for long-context inference. Furthermore, we have extensively evaluated our method on various long-context benchmarks including LongBench, where it achieves a 3x reduction in KV cache budget without accuracy loss and up to an 8x reduction with <0.5 point accuracy gap for various models.

The nature of dark matter is poorly constrained on subgalactic scales. Alternative models to cold dark matter, such as warm dark matter or self-interacting dark matter, could produce very different dark haloes on these scales. One of the few known dark haloes smaller than a galaxy was discovered in the triple source plane strong lens system J0946+1006. Previous studies have found that this structure is much more concentrated than expected in $\Lambda$CDM, but have assumed the dark halo is at the same redshift as the main deflector ($z_{\rm main}=0.222$). In this paper, we fit for the redshift of this dark halo. We reconstruct the first two sources in the system using a forward modelling approach, allowing for additional complexity from multipole perturbations. We find that the perturber redshift is $z_{\rm halo} = {0.207}^{+0.019}_{-0.019}$, and lower bounds on the evidence strongly prefer a subhalo over a line-of-sight structure. Whilst modelling both background sources does not improve constraints on the redshift of the subhalo, it breaks important degeneracies affecting the reconstruction of multipole perturbations. We find that the subhalo is a more than $5\sigma$ outlier from the $\Lambda$CDM $v_{\rm max}$-$r_{\rm max}$ relation and has a steep profile with an average slope of $\gamma_{\rm 2D} = {-1.81}^{+0.15}_{-0.11}$ for radii between $0.75-1.25$ kpc. This steep slope might indicate dark matter self-interactions causing the subhalo to undergo gravothermal collapse; such collapsed haloes are expected to have $\gamma_{\rm 2D} \approx -2$., Comment: 16 pages, 10 figures, 2 tables

We propose a novel, highly efficient, second-order accurate, long-time unconditionally stable numerical scheme for a class of finite-dimensional nonlinear models that are of importance in geophysical fluid dynamics. The scheme is highly efficient in the sense that only a (fixed) symmetric positive definite linear problem (with varying right hand sides) is involved at each time-step. The solutions to the scheme are uniformly bounded for all time. We show that the scheme is able to capture the long-time dynamics of the underlying geophysical model, with the global attractors as well as the invariant measures of the scheme converge to those of the original model as the step size approaches zero. In our numerical experiments, we take an indirect approach, using long-term statistics to approximate the invariant measures. Our results suggest that the convergence rate of the long-term statistics, as a function of terminal time, is approximately first order using the Jensen-Shannon metric and half-order using the L1 metric. This implies that very long time simulation is needed in order to capture a few significant digits of long time statistics (climate) correct. Nevertheless, the second order scheme's performance remains superior to that of the first order one, requiring significantly less time to reach a small neighborhood of statistical equilibrium for a given step size.

Solution-processable 2D materials are promising candidates for a range of printed electronics applications. Yet maximising their potential requires solution-phase processing of nanosheets into high-quality networks with carrier mobility ({\mu}Net) as close as possible to that of individual nanosheets ({\mu}NS). In practise, the presence of inter-nanosheet junctions generally limits electronic conduction, such that the ratio of junction resistance (RJ) to nanosheet resistance (RNS), determines the network mobility via . Hence, achieving RJ/RNS<1 is a crucial step for implementation of 2D materials in printed electronics applications. In this work, we utilise an advanced liquid-interface deposition process to maximise nanosheet alignment and network uniformity, thus reducing RJ. We demonstrate the approach using graphene and MoS2 as model materials, achieving low RJ/RNS values of 0.5 and 0.2, respectively. The resultant graphene networks show a high conductivity of {\sigma}Net = 5 \times 104 S/m while our semiconducting MoS2 networks demonstrate record mobility of {\mu}Net = 30 cm2/Vs, both at extremely low network thickness (tNet <10 nm). Finally, we show that the deposition process is compatible with non-layered quasi-2D materials such as silver nanosheets (AgNS), achieving network conductivity close to bulk silver for networks <100 nm thick. We believe this work is the first to report nanosheet networks with RJ/RNS<1 and serves to guide future work in 2D materials-based printed electronics.

One of the most promising techniques for detecting ultra-high energy neutrinos involves the use of radio antennas to observe the 10-1000 MHz radiation generated by the showers that neutrinos induce in large volumes of ice. The expected neutrino detection rates of one neutrino or less per detector station per 10 years make the characterization of backgrounds a priority. The largest natural background comes from ultra-high energy cosmic rays which are orders of magnitude more abundant than neutrinos. Particularly crucial is the understanding of geometries in which substantial energy of the cosmic-ray-induced air shower is deposited in the ice giving rise to a compact in-ice shower close to the ice surface. We calculated the radio emission of air-shower cores using the novel CORSIKA 8 code and found it to be similar to the predictions for neutrino-induced showers. For the first time, we calculated the detection rates for O(100m) deep antennas yielding 10-100 detections per year and detector station, which makes this a useful calibration source as these downward-going signals can be differentiated from neutrino-induced showers based on the signal arrival direction. However, the presence of reflection layers in the ice confuses the arrival directions, which makes this a potentially important background. We review the existing information on reflecting layers in the South Pole glacier and, for the first time, quantify the corresponding rate of reflected air-shower signals for the proposed IceCube-Gen2 radio array and discuss mitigation strategies. The reflectivity of the layers is the dominant uncertainty resulting in rate predictions of much less than one detection to several detections per year for IceCube-Gen2 if not mitigated.

Circumbinary planets - planets that orbit both stars in a binary system - offer the opportunity to study planet formation and orbital migration in a different environment compare to single stars. However, despite the fact that > 90% of binary systems in the solar neighbourhood are spectrally resolved double-lined binaries, there has been only one detection of a circumbinary planet orbitting a double-lined binary using the radial velocity method so far. Spectrally disentangling both components of a binary system is hard to do accurately. Weak spectral lines blend with one another in a time-varying way, and inaccuracy in spectral modelling can lead to an inaccurate estimation of the radial-velocity of each component. This inaccuracy adds scatter to the measurements that can hide the weak radial-velocity signature of circumbinary exoplanets. We have obtained new high signal-to-noise and high-resolution spectra with the SOPHIE spectrograph, mounted on the 193cm telescope at Observatoire de Haute-Provence (OHP) for six, bright, double-lined binaries for which a circumbinary exoplanet detection has been attempted in the past. To extract radial-velocities we use the DOLBY code, a recent method of spectral disentangling using Gaussian processes to model the time-varying components. We analyse the resulting radial-velocities with a diffusive nested sampler to seek planets, and compute sensitivity limits. We do not detect any new circumbinary planet. However, we show that the combination of new data, new radial-velocity extraction methods, and new statistical methods to determine a dataset's sensitivity to planets leads to an approximately one order of magnitude improvement compared to previous results. This improvement brings us into the range of known circumbinary exoplanets and paves the way for new campaigns of observations targeting double-lined binaries., Comment: 19 pages, 8 figures, 7 tables. Accepted for publication in MNRAS

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

We consider the effect of spin-orbit coupling on a two-dimensional Kondo Lattice model, in which conduction electrons are antiferromagnetically coupled to a Yao-Lee spin liquid. When a Rashba spin-orbit interaction and a nearest-neighbor Kondo interaction is introduced, the low-energy Majorana bands become gapped and develop Chern numbers, protecting unidirectionally propagating Majorana edge modes. Our model describes a chiral topological superconductor with fractionalized charge-$e$ order parameter and spontaneously broken time-reversal symmetry, which may be of interest for certain heavy fermion superconductors, such as UTe$_2$.

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

CORSIKA 8 is a new framework for simulations of particle cascades in air and dense media implemented in modern C++17, based on past experience with existing codes, in particular CORSIKA 7. The flexible and modular structure of the project allows the development of independent modules that can produce a fully customizable particle shower simulation. The radio module in particular is designed to treat the electric field calculation and its propagation through complex media to each observer location in an autonomous and flexible way. It already allows for the simultaneous simulation of the radio emission calculated with two independent time-domain formalisms, the "Endpoint formalism" as previously implemented in CoREAS and the "ZHS" algorithm as ported from ZHAireS. The design acts as the baseline interface for current and future development for the simulation of radio emission from particle showers in standard and complex scenarios, such as cross-media showers penetrating from air into ice. In this work, we present the design and implementation of the radio module in CORSIKA 8, along with validation studies and a direct comparison of the radio emission from air showers simulated with CORSIKA 8, CORSIKA 7 and ZHAireS. We also present the impact of simulation details such as the step size of simulated particle tracks on radio-emission simulations and perform a direct comparison of the "Endpoints" and "ZHS" formalisms for the same underlying air showers. Finally, we present an in-depth comparison of CORSIKA 8 and CORSIKA 7 for optimum simulation settings and discuss the relevance of observed differences in light of reconstruction efforts for the energy and mass of cosmic rays., Comment: 17 pages

Stabilizing vertical dynamics for on-road and off-road vehicles is an important research area that has been looked at mostly from the point of view of ride comfort. The advent of autonomous vehicles now shifts the focus more towards developing stabilizing techniques from the point of view of onboard proprioceptive and exteroceptive sensors whose real-time measurements influence the performance of an autonomous vehicle. The current solutions to this problem of managing the vertical oscillations usually limit themselves to the realm of active suspension systems without much consideration to modulating the vehicle velocity, which plays an important role by the virtue of the fact that vertical and longitudinal dynamics of a ground vehicle are coupled. The task of stabilizing vertical oscillations for military ground vehicles becomes even more challenging due lack of structured environments, like city roads or highways, in off-road scenarios. Moreover, changes in structural parameters of the vehicle, such as mass (due to changes in vehicle loading), suspension stiffness and damping values can have significant effect on the controller's performance. This demands the need for developing deep learning based control policies, that can take into account an extremely large number of input features and approximate a near optimal control action. In this work, these problems are addressed by training a deep reinforcement learning agent to minimize the vertical acceleration of a scaled vehicle travelling over bumps by controlling its velocity.

Ultra-high-energy neutrinos and cosmic rays are excellent probes of astroparticle physics phenomena. For astroparticle physics analyses, robust and accurate reconstruction of signal parameters like arrival direction and energy is essential. Current reconstruction methods ignore bin-to-bin noise correlations, which limits reconstruction resolution and so far has prevented calculations of event-by-event uncertainties. In this work, we present a likelihood description of neutrino or cosmic-ray signals in a radio detector with correlated noise, as present in all neutrino and cosmic-ray radio detectors. We demonstrate with a toy-model reconstruction that signal parameters such as energy and direction, including event-by-event uncertainties with correct coverage, can be obtained. Additionally, by correctly accounting for correlations, the likelihood description constrains the best-fit parameters better than alternative methods and thus improves experimental reconstruction capabilities., Comment: Proceedings of the 10th ARENA Workshop 2024

Detecting non-classical light is a central requirement for photonics-based quantum technologies. Unrivaled high efficiencies and low dark counts have positioned superconducting nanowire single photon detectors (SNSPDs) as the leading detector technology for fiber and integrated photonic applications. However, a central challenge lies in their integration within photonic integrated circuits regardless of material platform or surface topography. Here, we introduce a method based on transfer printing that overcomes these constraints and allows for the integration of SNSPDs onto arbitrary photonic substrates. We prove this by integrating SNSPDs and showing through-waveguide single-photon detection in commercially manufactured silicon and lithium niobate on insulator integrated photonic circuits. Our method eliminates bottlenecks to the integration of high-quality single-photon detectors, turning them into a versatile and accessible building block for scalable quantum information processing., Comment: 11 pages, 12 figures

Recent large language models (LLMs) have enabled the development of advanced agentic systems that can integrate various tools and APIs to fulfill user queries through function calling. However, the deployment of these LLMs on the edge has not been explored since they typically require cloud-based infrastructure due to their substantial model size and computational demands. To this end, we present TinyAgent, an end-to-end framework for training and deploying task-specific small language model agents capable of function calling for driving agentic systems at the edge. We first show how to enable accurate function calling for open-source models via the LLMCompiler framework. We then systematically curate a high-quality dataset for function calling, which we use to fine-tune two small language models, TinyAgent-1.1B and 7B. For efficient inference, we introduce a novel tool retrieval method to reduce the input prompt length and utilize quantization to further accelerate the inference speed. As a driving application, we demonstrate a local Siri-like system for Apple's MacBook that can execute user commands through text or voice input. Our results show that our models can achieve, and even surpass, the function-calling capabilities of larger models like GPT-4-Turbo, while being fully deployed at the edge. We open-source our dataset, models, and installable package and provide a demo video for our MacBook assistant agent., Comment: EMNLP 2024 Demo

A pair of Direct Numerical Simulations is used to investigate curvature and pressure effects. One has a Gaussian test bump and a straight opposite wall, while the other has a straight test wall and a blowing/suction distribution on an opposite porous boundary, adjusted to produce the same pressure distribution. The calculation of the transpiration distribution is made in potential flow, ignoring the boundary layer. This problem of specifying a pressure distribution is known to be ill-posed for short waves. We address this issue by considering a pressure distribution that is very smooth compared with the distance from wall to opposite boundary. It is also ill-posed once separation occurs. The pressure distribution of the viscous flow nevertheless ended up very close to the specified one, upstream of separation, and comparisons are confined to that region. In the entry region the boundary layers have essentially the same thicknesses and are well-developed turbulence-wise, which is essential for a valid comparison. The focus is on the attached flow in the favorable and adverse gradients. The convex curvature is strong enough compared with the boundary-layer thickness to make the strain-rate tensor drop to near zero over the top of the bump. An intense internal layer forms in the favorable gradient, an order of magnitude thinner than the incoming boundary layer. The effect of curvature follows expectations: concave curvature moderately raises the skin friction, although without creating Gortler vortices, and convex curvature reduces it. The pressure gradient still dominates the physics. Common turbulence models unfortunately over-predict the skin friction in both flows near its peak, and under-predict the curvature effect even when curvature corrections are included.

The baryon cycle is crucial for understanding galaxy formation, as gas inflows and outflows vary throughout a galaxy's lifetime and affect its star formation rate. Despite the necessity of accretion for galaxy growth at high redshifts, direct observations of inflowing gas have proven elusive especially at $z\gtrsim2$. We present spectroscopic analysis of a galaxy at redshift $z=2.45$ which exhibits signs of inflow in several ultraviolet interstellar absorption lines, with no clear outflow signatures. The absorption lines are redshifted by $\sim$250 km sec$^{-1}$ with respect to the systemic redshift, and C IV shows a prominent inverse P-Cygni profile. Simple stellar population models suggest that this galaxy has a low metallicity ($\sim$5% solar), with a very young starburst of age $\sim$4 Myr dominating the ultraviolet luminosity. The gas inflow velocity and nebular velocity dispersion suggest an approximate halo mass of order $\sim 10^{11}M_{\odot}$, a regime in which simulations predict that bursty star formation is common at this redshift. We conclude that this system is likely in the beginning of a cycle of bursty star formation, where inflow and star formation rates are high, but where supernovae and other feedback processes have not yet launched strong outflows. In this scenario, we expect the inflow-dominated phase to be observable (e.g., with net redshifted ISM absorption) for only a short timescale after a starburst onset. This result represents a promising avenue for probing the full baryon cycle, including inflows, during the formative phases of low-mass galaxies at high redshifts., Comment: Accepted for publication in ApJL, 12 pages, 4 figures

We investigate nucleosynthesis in the sub-relativistic outflows from black hole (BH) accretion disks formed in failed supernovae from rapidly-rotating Wolf-Rayet stars. These disks reach the neutrino-cooled regime during a portion of their evolution, undergoing significant neutronization and thus having the potential to support the $r$-process. Here, we analyze the formation of heavy elements in the ejecta from global, axisymmetric, long-term, viscous hydrodynamic simulations of these systems that include neutrino emission and absorption, Newtonian self-gravity, a pseudo-Newtonian potential for the BH gravity, and a 19-isotope nuclear network. Tracer particles are used for post-processing with a larger network. In addition to analyzing models from a previous paper, we present new models in which we modify the rotation profile of the progenitor star, to maximize neutrino reprocessing of circularized mass shells. All of our models produce several $M_\odot$ of O, followed by about a solar mass of C, Ne, and Ni, with other alpha elements produced in smaller quantities. Only one of our models, with the lowest viscosity, yields significant amounts of first $r$-process peak elements, with negligible yields at higher nuclear masses. The rest of the set, including models with a modified rotation profile, produces very small or negligible quantities of elements beyond the iron group. Models that produce the heaviest elements (up to $A\sim200$) do so along the proton-rich side of the valley of stability at high entropy ($s/k_B\sim80$), pointing to the $rp$-process as a mechanism that operates in collapsars. The absence of neutron-rich ejecta proves to be insensitive to changes in the rotation profile of the star, suggesting that heavy $r$-process elements are difficult to produce in collapsars if no large-scale poloidal magnetic field is present in the disk to drive outflows during neutronization., Comment: Accepted by PRD, Part 2 of arXiv:2403.08877. Minor changes in the arXiv abstract to fit character limit

We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large server-based language model designed for Private Cloud Compute. These models are designed to perform a wide range of tasks efficiently, accurately, and responsibly. This report describes the model architecture, the data used to train the model, the training process, how the models are optimized for inference, and the evaluation results. We highlight our focus on Responsible AI and how the principles are applied throughout the model development.

The LIGO-Virgo-KAGRA (LVK) Collaboration has made breakthrough discoveries in gravitational-wave astronomy, a new field that provides a different means of observing our Universe. Gravitational-wave discoveries are possible thanks to the work of thousands of people from across the globe working together. In this article, we discuss the range of engagement activities used to communicate LVK gravitational-wave discoveries and the stories of the people behind the science, using the activities surrounding the release of the third Gravitational-Wave Transient Catalog as a case study., Comment: 15 pages, 7 figures, published in JCOM: https://doi.org/10.22323/2.23070803

We present an analysis of the half-filled CPT model, an analytically tractable Kondo lattice model with Yao-Lee spin-spin interactions on a 3D hyperoctagon lattice, proposed by Coleman, Panigrahi, and Tsvelik. Previous studies have established that the CPT model exhibits odd-frequency triplet superconductivity and order fractionalization. Through asymptotic analyses in the small $J$ and large $J$ Kondo coupling limits, we identify a quantum critical point at $J_c$, marking a transition from a superconductor to a Kondo insulator. By estimating the vison gap energy to account for thermal gauge fluctuations, we determine the energy scales governing the thermal breakdown of order fractionalization. Moreover, at large $J$ the Kondo insulator undergoes orbital decoupling, leading to the formation of a decoupled Kitaev orbital liquid. These findings and analogies with the $\mathbb{Z}_2$-gauged $XY$ model lead us to propose a tentative phase diagram for the CPT model at half-filling., Comment: 10 pages, 7 figures

We present the first prediction for the mass distribution function of Galactic free-floating planets (FFPs) that aims to accurately include the relative contributions of multiple formation pathways and stellar populations. We derive our predicted distribution from dedicated simulations of planet birth, growth, migration, and ejection around circumbinary systems and extend these results to also include the contributions from single and wide binary systems. Our resulting FFP mass distribution shows several distinct features, including a strong peak at $\sim 8 M_{\oplus}$ arising from the transition between pebble and gas accretion regimes and a trough at $\sim 1 M_{\oplus}$ due to the shift in the dominant ejection process from planet-planet scattering to ejection through interactions with stars in circumbinary systems. We find that interactions with the central binary in close circumbinary systems are likely the dominant progenitor for FFPs more massive than Earth, leading to a steep power-law dependence in mass that agrees well with existing observations. In contrast, we find planet-planet scattering events in single and wide binary systems likely produce the majority of planets at Mars mass and below, resulting in a shallower power-law dependence. Our results suggest that existing extrapolations into the sub-terrestrial mass range may significantly overestimate the true FFP abundance. The features we predict in the mass distribution of FFPs will be detectable by upcoming space-based microlensing surveys and, if observed, will provide key insight into the origins of FFPs and the environments in which they form., Comment: Submitted to MNRAS. 10 pages, 4 figures

Active Galactic Nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multi-messenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and ten years of neutrino data from IceCube. We also use a time-dependent approach which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are $\sim3\%$ and $\sim9\%$ for the time-averaged and time-dependent case, respectively., Comment: 14 Pages 7 Figures

We present a search for an eV-scale sterile neutrino using 7.5 years of data from the IceCube DeepCore detector. The analysis uses a sample of 21,914 events with energies between 5 and 150 GeV to search for sterile neutrinos through atmospheric muon neutrino disappearance. Improvements in event selection and treatment of systematic uncertainties provide greater statistical power compared to previous DeepCore sterile neutrino searches. Our results are compatible with the absence of mixing between active and sterile neutrino states, and we place constraints on the mixing matrix elements $|U_{\mu 4}|^2 < 0.0534$ and $|U_{\tau 4}|^2 < 0.0574$ at 90% CL under the assumption that $\Delta m^2_{41}\geq 1\;\mathrm{eV^2}$. These null results add to the growing tension between anomalous appearance results and constraints from disappearance searches in the 3+1 sterile neutrino landscape., Comment: 11 pages, 5 figures. Version accepted by Physical Review D for publication

When running at scale, modern scientific workflows require middleware to handle allocated resources, distribute computing payloads and guarantee a resilient execution. While individual steps might not require sophisticated control methods, bringing them together as a whole workflow requires advanced management mechanisms. In this work, we used RADICAL-EnTK (Ensemble Toolkit) - one of the SDK components of the ECP ExaWorks project - to implement and execute the novel Exascale Additive Manufacturing (ExaAM) workflows on up to 8000 compute nodes of the Frontier supercomputer at the Oak Ridge Leadership Computing Facility. EnTK allowed us to address challenges such as varying resource requirements (e.g., heterogeneity, size, and runtime), different execution environment per workflow, and fault tolerance. And a native portability feature of the developed EnTK applications allowed us to adjust these applications for Frontier runs promptly, while ensuring an expected level of resource utilization (up to 90%).

This study presents a granular analysis of societal recovery from disasters at the individual level, focusing on the aftermath of Hurricane Harvey and Hurricane Ida. Societal recovery is defined as the restoration of the societal functioning of the affected community to its normal/steady-state level. It evaluates the recovery of impacted residents based on fluctuations in their lifestyle patterns in visits to points of interest. The analysis focuses on: (1) the extent of heterogeneity in lifestyle recovery of residents in the same spatial area; and (2) the extent to which variations in lifestyle recovery and its heterogeneity among users can be explained based on hazard impact extent and social vulnerability. As lifestyle recovery progresses, heterogeneity diminishes, indicating that lower lifestyle recovery rates correlate with higher heterogeneity within a spatial area. This relationship between lifestyle recovery and heterogeneity can lead to the misestimation of recovery timelines, potentially resulting in the inefficient allocation of resources and disproportionate attention to already recovering communities. Key contributions of the study are fourfold: First, it characterizes societal recovery at the finest scale by examining fluctuations in individual lifestyles, revealing heterogeneity even among neighbors. Second, it proposes using individual lifestyle as an indicator of societal functioning to measure, more human centrically, disaster impacts and recovery speeds. Third, it introduces a method for quantifying lifestyle recovery that enables near-real-time monitoring, departing from traditional survey-based methods. Fourth, it provides empirical insights into the relationship between disaster impacts and societal recovery, showing that the severity of disaster impacts and resident income levels and percentage of minority populations influence recovery durations., Comment: 41 pages, 9 Figures, 4 Tables

Reliable control of quantum information in matter-based qubits requires precisely applied external fields, and unaccounted for spatial cross-talk of these fields between adjacent qubits leads to loss of fidelity. We report a CMOS foundry-produced, micro-fabricated silicon nitride (Si3N4) optical waveguide for addressing a chain of eight, unequally-spaced trapped barium ions with crosstalk compatible with scalable quantum information processing. The crosstalk mitigation techniques incorporated into the chip design result in a reduction of the measured optical field by at least 50.8(1.3) dB between adjacent waveguide outputs near 650 nm and similar behavior for devices designed for 493 nm and 585 nm. The waveguide outputs near 650 nm, along with a global laser near 493 nm were used to laser-cool a chain of eight barium-138 ions, and a camera imaged the resulting fluorescence at 493 nm., Comment: 9 pages, 7 figures

We introduce a new method for robust beamforming, where the goal is to estimate a signal from array samples when there is uncertainty in the angle of arrival. Our method offers state-of-the-art performance on narrowband signals and is naturally applied to broadband signals. Our beamformer operates by treating the forward model for the array samples as unknown. We show that the "true" forward model lies in the linear span of a small number of fixed linear systems. As a result, we can estimate the forward operator and the signal simultaneously by solving a bilinear inverse problem using least squares. Our numerical experiments show that if the angle of arrival is known to only be within an interval of reasonable size, there is very little loss in estimation performance compared to the case where the angle is known exactly., Comment: 6 Pages, 5 figures

PSR J0740+6620 is the neutron star with the highest precisely determined mass, inferred from radio observations to be $2.08\pm0.07\,\rm M_\odot$. Measurements of its radius therefore hold promise to constrain the properties of the cold, catalyzed, high-density matter in neutron star cores. Previously, Miller et al. (2021) and Riley et al. (2021) reported measurements of the radius of PSR J0740+6620 based on Neutron Star Interior Composition Explorer (NICER) observations accumulated through 17 April 2020, and an exploratory analysis utilizing NICER background estimates and a data set accumulated through 28 December 2021 was presented in Salmi et al. (2022). Here we report an updated radius measurement, derived by fitting models of X-ray emission from the neutron star surface to NICER data accumulated through 21 April 2022, totaling $\sim1.1$ Ms additional exposure compared to the data set analyzed in Miller et al. (2021) and Riley et al. (2021), and to data from X-ray Multi-Mirror (XMM-Newton) observations. We find that the equatorial circumferential radius of PSR J0740+6620 is $12.92_{-1.13}^{+2.09}$ km (68% credibility), a fractional uncertainty $\sim83\%$ the width of that reported in Miller et al. (2021), in line with statistical expectations given the additional data. If we were to require the radius to be less than 16 km, as was done in Salmi et al. (2024), then our 68% credible region would become $R=12.76^{+1.49}_{-1.02}$ km, which is close to the headline result of Salmi et al. (2024). Our updated measurements, along with other laboratory and astrophysical constraints, imply a slightly softer equation of state than that inferred from our previous measurements., Comment: 18 pages, 8 figures, +appendices. Accepted in ApJ

A near memory hardware accelerator, based on a novel direct path computational model, for real-time emulation of radio frequency systems is demonstrated. Our evaluation of hardware performance uses both application-specific integrated circuits (ASIC) and field programmable gate arrays (FPGA) methodologies: 1). The ASIC testchip implementation, using TSMC 28nm CMOS, leverages distributed autonomous control to extract concurrency in compute as well as low latency. It achieves a $518$ MHz per channel bandwidth in a prototype $4$-node system. The maximum emulation range supported in this paradigm is $9.5$ km with $0.24$ $\mu$s of per-sample emulation latency. 2). The FPGA-based implementation, evaluated on a Xilinx ZCU104 board, demonstrates a $9$-node test case (two Transmitters, one Receiver, and $6$ passive reflectors) with an emulation range of $1.13$ km to $27.3$ km at $215$ MHz bandwidth.

In this paper we consider the problem of developing a computational model for emulating an RF channel. The motivation for this is that an accurate and scalable emulator has the potential to minimize the need for field testing, which is expensive, slow, and difficult to replicate. Traditionally, emulators are built using a tapped delay line model where long filters modeling the physical interactions of objects are implemented directly. For an emulation scenario consisting of $M$ objects all interacting with one another, the tapped delay line model's computational requirements scale as $O(M^3)$ per sample: there are $O(M^2)$ channels, each with $O(M)$ complexity. In this paper, we develop a new ``direct path" model that, while remaining physically faithful, allows us to carefully factor the emulator operations, resulting in an $O(M^2)$ per sample scaling of the computational requirements. The impact of this is drastic, a $200$ object scenario sees about a $100\times$ reduction in the number of per sample computations. Furthermore, the direct path model gives us a natural way to distribute the computations for an emulation: each object is mapped to a computational node, and these nodes are networked in a fully connected communication graph. Alongside a discussion of the model and the physical phenomena it emulates, we show how to efficiently parameterize antenna responses and scattering profiles within this direct path framework. To verify the model and demonstrate its viability in hardware, we provide several numerical experiments produced using a cycle level C++ simulator of a hardware implementation of the model.

The recent IceCube detection of TeV neutrino emission from the nearby active galaxy NGC 1068 suggests that active galactic nuclei (AGN) could make a sizable contribution to the diffuse flux of astrophysical neutrinos. The absence of TeV $\gamma$-rays from NGC 1068 indicates neutrino production in the vicinity of the supermassive black hole, where the high radiation density leads to $\gamma$-ray attenuation. Therefore, any potential neutrino emission from similar sources is not expected to correlate with high-energy $\gamma$-rays. Disk-corona models predict neutrino emission from Seyfert galaxies to correlate with keV X-rays, as they are tracers of coronal activity. Using through-going track events from the Northern Sky recorded by IceCube between 2011 and 2021, we report results from a search for individual and aggregated neutrino signals from 27 additional Seyfert galaxies that are contained in the BAT AGN Spectroscopic Survey (BASS). Besides the generic single power-law, we evaluate the spectra predicted by the disk-corona model. Assuming all sources to be intrinsically similar to NGC 1068, our findings constrain the collective neutrino emission from X-ray bright Seyfert galaxies in the Northern Hemisphere, but, at the same time, show excesses of neutrinos that could be associated with the objects NGC 4151 and CGCG 420-015. These excesses result in a 2.7$\sigma$ significance with respect to background expectations., Comment: 17 pages, 9 figures

Pulse Profile Modeling (PPM), the technique used to infer mass, radius and geometric parameters for rotation-powered millisecond pulsars using data from the Neutron Star Interior Composition Explorer (NICER), relies on relativistic ray-tracing of thermal X-ray photons from hot spots on the neutron star surface to the observer. To verify our ray-tracing codes we have in the past conducted cross-tests for simple hot spot geometries, focusing primarily on the implementation of the space-time model. In this paper, we present verification for test problems that explore the more complex hot spot geometries that are now being employed in the NICER PPM analyses. We conclude that the accuracy of our computed waveforms is in general sufficiently high for analyses of current NICER data sets. We have however identified some extreme configurations where extra care may be needed., Comment: Updated to version accepted by The Astrophysical Journal following their review process

Active Galactic Nuclei (AGN) are promising candidate sources of high-energy astrophysical neutrinos since they provide environments rich in matter and photon targets where cosmic ray interactions may lead to the production of gamma rays and neutrinos. We searched for high-energy neutrino emission from AGN using the $\textit{Swift}$-BAT Spectroscopic Survey (BASS) catalog of hard X-ray sources and 12 years of IceCube muon track data. First, upon performing a stacked search, no significant emission was found. Second, we searched for neutrinos from a list of 43 candidate sources and found an excess from the direction of two sources, Seyfert galaxies NGC 1068 and NGC 4151. We observed NGC 1068 at flux $\phi_{\nu_{\mu}+\bar{\nu}_{\mu}}$ = $4.02_{-1.52}^{+1.58} \times 10^{-11}$ TeV$^{-1}$ cm$^{-2}$ s$^{-1}$ normalized at 1 TeV, with power-law spectral index, $\gamma$ = 3.10$^{+0.26}_{-0.22}$, consistent with previous IceCube results. The observation of a neutrino excess from the direction of NGC 4151 is at a post-trial significance of 2.9$\sigma$. If interpreted as an astrophysical signal, the excess observed from NGC 4151 corresponds to a flux $\phi_{\nu_{\mu}+\bar{\nu}_{\mu}}$ = $1.51_{-0.81}^{+0.99} \times 10^{-11}$ TeV$^{-1}$ cm$^{-2}$ s$^{-1}$ normalized at 1 TeV and $\gamma$ = 2.83$^{+0.35}_{-0.28}$.

In cross-modal music processing, translation between visual, auditory, and semantic content opens up new possibilities as well as challenges. The construction of such a transformative scheme depends upon a benchmark corpus with a comprehensive data infrastructure. In particular, the assembly of a large-scale cross-modal dataset presents major challenges. In this paper, we present the MOSA (Music mOtion with Semantic Annotation) dataset, which contains high quality 3-D motion capture data, aligned audio recordings, and note-by-note semantic annotations of pitch, beat, phrase, dynamic, articulation, and harmony for 742 professional music performances by 23 professional musicians, comprising more than 30 hours and 570 K notes of data. To our knowledge, this is the largest cross-modal music dataset with note-level annotations to date. To demonstrate the usage of the MOSA dataset, we present several innovative cross-modal music information retrieval (MIR) and musical content generation tasks, including the detection of beats, downbeats, phrase, and expressive contents from audio, video and motion data, and the generation of musicians' body motion from given music audio. The dataset and codes are available alongside this publication (https://github.com/yufenhuang/MOSA-Music-mOtion-and-Semantic-Annotation-dataset)., Comment: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2024. 14 pages, 7 figures. Dataset is available on: https://github.com/yufenhuang/MOSA-Music-mOtion-and-Semantic-Annotation-dataset/tree/main and https://zenodo.org/records/11393449

Planets orbiting binary systems are relatively unexplored compared to those around single stars. Detections of circumbinary planets and planetary systems offer a first detailed view into our understanding of circumbinary planet formation and dynamical evolution. The BEBOP (Binaries Escorted by Orbiting Planets) radial velocity survey plays a special role in this adventure as it focuses on eclipsing single-lined binaries with an FGK dwarf primary and M dwarf secondary allowing for the highest-radial velocity precision using the HARPS and SOPHIE spectrographs. We obtained 4512 high-resolution spectra for the 179 targets in the BEBOP survey which we used to derive the stellar atmospheric parameters using both equivalent widths and spectral synthesis. We furthermore derive stellar masses, radii, and ages for all targets. With this work, we present the first homogeneous catalogue of precise stellar parameters for these eclipsing single-lined binaries., Comment: accepted for publication in MNRAS

We present the first three-parameter fit to a 3+1 sterile neutrino model using 7.634 years of data from the IceCube Neutrino Observatory on $\nu_\mu+\overline{\nu}_\mu$ charged-current interactions in the energy range 500--9976 GeV. Our analysis is sensitive to the mass-squared splitting between the heaviest and lightest mass state ($\Delta m_{41}^2$), the mixing matrix element connecting muon flavor to the fourth mass state ($|U_{\mu4}|^2$), and the element connecting tau flavor to the fourth mass state ($|U_{\tau4}|^2$). Predicted propagation effects in matter enhance the signature through a resonance as atmospheric neutrinos from the Northern Hemisphere traverse the Earth to the IceCube detector at the South Pole. The remaining sterile neutrino matrix elements are left fixed, with $|U_{e4}|^2= 0$ and $\delta_{14}=0$, as they have a negligible effect, and $\delta_{24}=\pi$ is set to give the most conservative limits. The result is consistent with the no-sterile neutrino hypothesis with a probability of 4.3%. Profiling the likelihood of each parameter yields the 90\% confidence levels: $ 2.4\,\mathrm{eV}^{2} < \Delta m_{41}^2 <9.6\,\mathrm{eV}^{2} $ , $0.0081 < |U_{\mu4}|^2 < 0.10$ , and $|U_{\tau4}|^2< 0.035$, which narrows the allowed parameter-space for $|U_{\tau4}|^2$. However, the primary result of this analysis is the first map of the 3+1 parameter space exploring the interdependence of $\Delta m_{41}^2$, $|U_{\mu4}|^2$, and $|U_{\tau4}|^2$., Comment: 14 pages, 8 figures. Published in PLB

On June 29, 2023, in Students for "Fair Admissions vs. Harvard" and "Students for Fair Admissions v. University of North Carolina," the U.S. Supreme Court ruled in a consolidated opinion that Harvard University and the University of North Carolina (UNC) violated federal non-discrimination law by considering race as one factor among many in their undergraduate admissions programs in order to promote the educational benefits of a diverse student body. Much has been written about this ruling. The purpose of this paper is to go behind the headlines to address the ruling's practical implications for higher education institutions. The aim is to highlight what is clearly permissible in light of the new admissions restrictions imposed by the court. The authors also provide an overview of enrollment strategies not addressed by the court that should be central to these higher education institutions' efforts to advance diversity, equity, and inclusion and to mitigate the harm stemming from the ruling.[Eileen and Harold Brown provided additional funding for this series of briefs.]