Search

Terawatt x-ray free-electron lasers (XFELs) represent the frontier in further development of x-ray sources and require high current densities with strong transverse focusing. In this paper, we investigate the implications/potentialities of TW XFELs on the generation of harmonics at still shorter wavelengths and higher photon energies with variable polarization. The simulations indicate that significant power levels are possible at high harmonics of the XFEL resonance and that these XFELs can be an important coherent source of hard x-rays through the gamma ray spectrum. For this purpose, we use the MINERVA simulation code which self-consistently includes harmonic generation. Both helical and planar undulators are discussed in which the fundamental is at 1.5 {\AA} and study the associated harmonic generation. While tapered undulators are needed to reach TW powers at the fundamental, the taper does not enhance the harmonics because the taper must start before saturation of the fundamental, while the harmonics saturate before this point is reached. Nevertheless, the harmonics reach substantial powers. Simulations indicate that, for the parameters under consideration, peak powers of the order of 180 MW are possible at the fifth harmonic with a photon energy of about 41 keV and still high harmonics may also be generated at substantial powers. Such high harmonic powers are certain to enable a host of enhanced applications, Comment: 7 pages, 12 figures

Tangent cones are preserved under ambient bilipschitz equivalence, but the behavior of the Nash cone is more delicate. This paper explores the behavior of the Nash cone and of exceptional rays under ambient bilipschitz equivalence for real surfaces in $\mathbb R^3$ with isolated singularity and whose tangent cone is a plane.

Modelling growth in student achievement is a significant challenge in the field of education. Understanding how interventions or experiences such as part-time work can influence this growth is also important. Traditional methods like difference-in-differences are effective for estimating causal effects from longitudinal data. Meanwhile, Bayesian non-parametric methods have recently become popular for estimating causal effects from single time point observational studies. However, there remains a scarcity of methods capable of combining the strengths of these two approaches to flexibly estimate heterogeneous causal effects from longitudinal data. Motivated by two waves of data from the High School Longitudinal Study, the NCES' most recent longitudinal study which tracks a representative sample of over 20,000 students in the US, our study introduces a longitudinal extension of Bayesian Causal Forests. This model allows for the flexible identification of both individual growth in mathematical ability and the effects of participation in part-time work. Simulation studies demonstrate the predictive performance and reliable uncertainty quantification of the proposed model. Results reveal the negative impact of part time work for most students, but hint at potential benefits for those students with an initially low sense of school belonging. Clear signs of a widening achievement gap between students with high and low academic achievement are also identified. Potential policy implications are discussed, along with promising areas for future research., Comment: 25 pages, 7 figures, 3 tables

The nature of dark matter in the Universe is still an open question in astrophysics and cosmology. Axions and axion-like particles (ALPs) offer a compelling solution, and traditionally ground-based experiments have eagerly, but to date unsuccessfully, searched for these hypothetical low-mass particles that are expected to be produced in large quantities in the strong electromagnetic fields in the interior of stars. This work offers a fresh look at axions and ALPs by leveraging their conversion into X-rays in the magnetic field of the Sun's atmosphere rather than a laboratory magnetic field. Unique data acquired with the Nuclear Spectroscopic Telescope Array (NuSTAR) during the solar minimum in 2020 allows us to set stringent limits on the coupling of axions to photons using state-of-the-art magnetic field models of the solar atmosphere. We report pioneering limits on the axion-photon coupling strength of $6.9\times 10^{-12}$ GeV$^{-1}$ at 95\% confidence level for axion masses $m_a \lesssim 2\times 10^{-7}$ eV, surpassing current ground-based searches and further probing unexplored regions of the axion-photon coupling parameter space up to axion masses of $m_a \lesssim 5\times 10^{-4}$ eV., Comment: 23 pages, 12 figures

The evolution of fifth generation (5G) wireless communication networks has led to an increased need for wireless resource management solutions that provide higher data rates, wide coverage, low latency, and power efficiency. Yet, many of existing traditional approaches remain non-practical due to computational limitations, and unrealistic presumptions of static network conditions and algorithm initialization dependencies. This creates an important gap between theoretical analysis and real-time processing of algorithms. To bridge this gap, deep learning based techniques offer promising solutions with their representational capabilities for universal function approximation. We propose a novel unsupervised deep learning based joint power allocation and beamforming design for multi-user multiple-input single-output (MU-MISO) system. The objective is to enhance the spectral efficiency by maximizing the sum-rate with the proposed joint design framework, NNBF-P while also offering computationally efficient solution in contrast to conventional approaches. We conduct experiments for diverse settings to compare the performance of NNBF-P with zero-forcing beamforming (ZFBF), minimum mean square error (MMSE) beamforming, and NNBF, which is also our deep learning based beamforming design without joint power allocation scheme. Experiment results demonstrate the superiority of NNBF-P compared to ZFBF, and MMSE while NNBF can have lower performances than MMSE and ZFBF in some experiment settings. It can also demonstrate the effectiveness of joint design framework with respect to NNBF.

The prevalence of light element enhancement in the most metal-poor stars is potentially an indication that the Milky Way has a metallicity floor for star formation around $\sim$10$^{-3.5}$ Z$_{\odot}$. We propose that this metallicity floor has its origins in metal-enriched star formation in the minihalos present during the Galaxy's initial formation. To arrive at this conclusion, we analyze a cosmological radiation hydrodynamics simulation that follows the concurrent evolution of multiple Population III star-forming minihalos. The main driver for the central gas within minihalos is the steady increase in hydrostatic pressure as the halos grow. We incorporate this insight into a hybrid one-zone model that switches between pressure-confined and modified free-fall modes to evolve the gas density with time according to the ratio of the free-fall and sound-crossing timescales. This model is able to accurately reproduce the density and chemo-thermal evolution of the gas in each of the simulated minihalos up to the point of runaway collapse. We then use this model to investigate how the gas responds to the absence of H$_{2}$. Without metals, the central gas becomes increasingly stable against collapse as it grows to the atomic cooling limit. When metals are present in the halo at a level of $\sim$10$^{-3.7}$ Z$_{\odot}$, however, the gas is able to achieve gravitational instability while still in the minihalo regime. Thus, we conclude that the Galaxy's metallicity floor is set by the balance within minihalos of gas-phase metal cooling and the radiation background associated with its early formation environment., Comment: 11 pages, 5 figures, accepted for publication in MNRAS

Filaments of cold gas ($T\leq 10^{4}$ K) are found in the inner regions of many cool-core clusters. These structures are thought to play a major role in the regulation of feedback from active galactic nuclei (AGN). We study the morphology of the filaments, their formation, and their impact on the propagation of the outflowing AGN jets. We present a set of GPU-accelerated 3D (magneto)hydrodynamical simulations of an idealized Perseus-like cluster using the performance portable code AthenaPK. We include radiative cooling, and a self-regulated AGN feedback model that redistributes accreted material through kinetic, thermal and magnetic feedback. We confirm that magnetic fields play an important role in both the formation and evolution of the cold material. These suppress the formation of massive cold disks and favor magnetically supported filaments over clumpy structures. Achieving resolutions of $25-50$ pc, we find that filaments are not monolithic as they contain numerous and complex magnetically--supported substructures. We find that the mass distribution of these clumps follows a power law for all investigated filaments, consistent with previous cloud-crushing simulations of individual clumps. Studying the evolution of individual filaments, we find that their formation pathways can be diverse. We find examples of filaments forming through a combination of cold gas uplifting and condensation, as well as systems of purely infalling clumps condensing out of the intracluster medium. The density contrast between the cold gas and the outflowing hot material leads to recurring deflections of the jets, favoring inflation of bubbles., Comment: 19 pages, 19 figures, submitted to Astronomy & Astrophysics

We revisit the flux of chameleons (light scalar particles which could play a role in the dark energy phenomenon) produced in the interior of the Sun. Our novel analysis incorporates various important details and new processes that have previously been overlooked, including the impact of the bulk magnetic field profile, as well as Primakoff production of chameleons in the electric fields of electrons and ions. In this paper we consider only the contributions of transverse photons. The production of chameleons from longitudinal electromagnetic excitations will be presented in a dedicated follow-up work. Demanding that the total flux of chameleons does not exceed 3% of the solar luminosity leads to the stringent upper limit on the chameleon-photon conformal coupling $\beta_\gamma \lesssim 10^{10}$, assuming that the height of the chameleon potential is set to the dark energy scale $\Lambda = 2.4$ meV, and independently of other couplings to matter. Although this bound is tighter than current upper limits on $\beta_{\gamma}$ from the CAST helioscope, these limits will have to be reassessed in terms of the updated solar chameleon flux we have computed. We argue that solar chameleons, potentially detectable in next-generation helioscopes such as IAXO, can be used to probe a region of chameleon parameter space that has yet to be covered., Comment: 17 pages, 6 figures

The splashback radius is one popular method to constrain the size of galaxy clusters. It is typically measured through the logarithmic derivative of the galaxy number density profile, since doing so is more observationally viable and computationally inexpensive compared to other methods. However, measuring the splashback radius through the galaxy number density has consistently produced smaller values of the splashback radius than those measured with dark matter density or other processes. Dynamical friction has been posited as one possible reason that splashback radii measured through galaxy number densities are reduced, since it decays the orbits of subhaloes within the halo, however, the effects of dynamical friction cannot be isolated within cosmological simulations. Here, we present idealized simulations starting with isolated galaxy clusters drawn from the IllustrisTNG cosmological simulation, where we isolate dynamical friction. We show that although dynamical friction can reduce measurements of the splashback radius, it does not have a significant effect on clusters with $M_\mathrm{200,mean} > 10^{14} \mathrm{M_\odot}$, and thus cannot completely account for previously measured discrepancies., Comment: To be submitted to The Open Journal of Astrophysics, comments welcome at tmoshea@wisc.edu

This study documents several correlations observed during the first run of the plasma wakefield acceleration experiment E300 conducted at FACET-II, using a single drive electron bunch. The established correlations include those between the measured maximum energy loss of the drive electron beam and the integrated betatron x-ray signal, the calculated total beam energy deposited in the plasma and the integrated x-ray signal, among three visible light emission measuring cameras, and between the visible plasma light and x-ray signal. The integrated x-ray signal correlates almost linearly with both the maximum energy loss of the drive beam and the energy deposited into the plasma, demonstrating its usability as a measure of energy transfer from the drive beam to the plasma. Visible plasma light is found to be a useful indicator of the presence of wake at three locations that overall are two meters apart. Despite the complex dynamics and vastly different timescales, the x-ray radiation from the drive bunch and visible light emission from the plasma may prove to be effective non-invasive diagnostics for monitoring the energy transfer from the beam to the plasma in future high-repetition-rate experiments., Comment: 20 pages, 6 figures

We report the observation of a coalescing compact binary with component masses $2.5\text{-}4.5~M_\odot$ and $1.2\text{-}2.0~M_\odot$ (all measurements quoted at the 90% credible level). The gravitational-wave signal GW230529_181500 was observed during the fourth observing run of the LIGO-Virgo-KAGRA detector network on 2023 May 29 by the LIGO Livingston Observatory. The primary component of the source has a mass less than $5~M_\odot$ at 99% credibility. We cannot definitively determine from gravitational-wave data alone whether either component of the source is a neutron star or a black hole. However, given existing estimates of the maximum neutron star mass, we find the most probable interpretation of the source to be the coalescence of a neutron star with a black hole that has a mass between the most massive neutron stars and the least massive black holes observed in the Galaxy. We provisionally estimate a merger rate density of $55^{+127}_{-47}~\text{Gpc}^{-3}\,\text{yr}^{-1}$ for compact binary coalescences with properties similar to the source of GW230529_181500; assuming that the source is a neutron star-black hole merger, GW230529_181500-like sources constitute about 60% of the total merger rate inferred for neutron star-black hole coalescences. The discovery of this system implies an increase in the expected rate of neutron star-black hole mergers with electromagnetic counterparts and provides further evidence for compact objects existing within the purported lower mass gap., Comment: 45 pages (10 pages author list, 13 pages main text, 1 page acknowledgements, 13 pages appendices, 8 pages bibliography), 17 figures, 16 tables. Update to match version published in The Astrophysical Journal Letters. Data products available from https://zenodo.org/records/10845779

High peak and average power free-electron lasers (FELs) in the terahertz region (THz) require small diameter, low-emittance, and high voltage electron beams. This paper presents two 1.5-2 MV, 100-200 A, thermionic cathode electron source approaches for compact megawatt range peak power, multi-kilowatt average power, high repetition rate, THz FELs. The preferred beam generation system includes grading electrodes and is quite compact compared to the other standard diode gun approaches. Both provide highly compressed beams at the waist having low values of normalized rms emittance. In particular, the new injector approach with grading electrodes, operating at a body voltage of 1.5-2 MV and 100 A, has a normalized rms emittance of roughly 10 mm-mrad at the beam waist. Power supply switching considerations are considered in the paper as well as considerations for very high-voltage multi-stage depressed collectors for device efficiency enhancement. Based on these designs, we provide performance estimates for FELs operating in the THz spectral region.

This paper addresses the gap between the capabilities and utilisation of robotics and automation in laboratory settings and builds upon the concept of Self Driving Labs (SDL). %to significantly impact laboratory operations. We introduce an innovative approach to the temporal characterisation of materials. The article discusses the challenges posed by manual methods involving established laboratory equipment and presents an automated hyperspectral characterisation station. This station integrates robot-aided hyperspectral imaging, complex material characterisation modeling, and automated data analysis, offering a non-destructive and comprehensive approach. This work explains how the proposed assembly can automatically measure the half-life of biodegradable polymers with higher throughput and accuracy than manual methods. The investigation explores the effect of pH, number of average molecular weight (Mn), end groups, and blends on the degradation rate of polylactic acid (PLA). The contributions of the paper lie in introducing an adaptable classification station for novel characterisation methods and presenting an innovative methodology for polymer degradation rate measurement. The proposed system has the potential to accelerate the development of high-throughput screening and characterisation methods in material and chemistry laboratories., Comment: 11 pages, 12 figures

Dark (hidden) photons are widely recognised as well motivated candidates for physics beyond the standard model, and have been invoked for the solution of several outstanding problems, including to account for the dark matter in the universe. In this paper, we consider a simple model for dark photons, which is coupled to ordinary matter only through kinetic mixing with ordinary photons. Within this framework, we calculate the flux of solar dark photons on Earth and revise the potential to detect it with the next generation of axion helioscopes, particularly with the International AXion Observatory (IAXO). This paper extends on previous theoretical analyses in two main ways. Firstly, it includes a more complete analysis of the possible sources of dark photons from the sun, including the contribution of the solar magnetic field and of nuclear processes, and secondly it includes predictions on the parameter space accessible in the gas-filled phase of IAXO., Comment: v2: minor changes. Included a range for the solar magnetic field strength. Matches the published version

Data-driven methods of model identification are able to discern governing dynamics of a system from data. Such methods are well suited to help us learn about systems with unpredictable evolution or systems with ambiguous governing dynamics given our current understanding. Many plasma problems of interest fall into these categories as there are a wide range of models that exist, however each model is only useful in a certain regime and often limited by computational complexity. To ensure data-driven methods align with theory, they must be consistent and predictable when acting on data whose governing dynamics are known. Weak Sparse Identification of Nonlinear Dynamics (WSINDy) is a recently developed data-driven method that has shown promise in learning governing dynamics from data with high noise levels [1]. This work examines how WSINDy acts on ideal MHD test problems as the initial conditions are varied and specifies limiting requirements for successful equation identification. It is hard to recover the governing dynamics from data that emphasize a single dominant behavior. In these low information cases, Shannon information entropy is able to pick up on the redundancies in the data that affect recoverability., Comment: 25 pages, 15 figures. Submitted to Journal of Computational Physics. Feedback welcome. Source code and data available upon request

The future success of the Navy will depend, in part, on artificial intelligence. In practice, many artificially intelligent algorithms, and in particular deep learning models, rely on continual learning to maintain performance in dynamic environments. The software requires adaptation to maintain its initial level of performance in unseen situations. However, if not monitored properly, continual learning may lead to several issues including catastrophic forgetting in which a trained model forgets previously learned tasks when being retrained on new data. The authors created a new framework for safely performing continual learning with the goal of pairing this safety framework with a deep learning computer vision algorithm to allow for safe and high-performing automatic deck tracking on carriers and amphibious assault ships. The safety framework includes several features, such as an ensemble of convolutional neural networks to perform image classification, a manager to record confidences and determine the best answer from the ensemble, a model of the environment to predict when the system may fail to meet minimum performance metrics, a performance monitor to log system and domain performance and check against requirements, and a retraining component to update the ensemble and manager to maintain performance. The authors validated the proposed method using extensive simulation studies based on dynamic image classification. The authors showed the safety framework could probabilistically detect out of distribution data. The results also show the framework can detect when the system is no longer performing safely and can significantly extend the working envelope of an image classifier., Comment: 8 pages, 11 figures. Published in the Proceedings of the ASNE 2023 Technology, Systems & Ships Symposium. Reproduced with permission from the American Society of Naval Engineers. Distribution Statement A: Approved for public release; distribution is unlimited, as submitted under NAVAIR Public Release Authorization 2023-022

Radiative cooling and AGN heating are thought to form a feedback loop that regulates the evolution of low redshift cool-core galaxy clusters. Numerical simulations suggest that formation of multiphase gas in the cluster core imposes a floor on the ratio of cooling time ($t_{\rm cool}$) to free-fall time ($t_{\rm ff}$) at $\min ( t_{\rm cool} / t_{\rm ff} ) \approx 10$. Observations of galaxy clusters show evidence for such a floor, and usually the cluster cores with $\min ( t_{\rm cool} / t_{\rm ff} ) \lesssim 30$ contain abundant multiphase gas. However, there are important outliers. One of them is Abell 2029, a massive galaxy cluster ($M_{200} \gtrsim 10^{15}$ M$_\odot$) with $\min( t_{\rm cool}/t_{\rm ff}) \sim 20$, but little apparent multiphase gas. In this paper, we present high resolution 3D hydrodynamic AMR simulations of a cluster similar to A2029 and study how it evolves over a period of 1-2 Gyr. Those simulations suggest that Abell 2029 self-regulates without producing multiphase gas because the mass of its central black hole ($\sim 5\times 10^{10} \, M_\odot$) is great enough for Bondi accretion of hot ambient gas to produce enough feedback energy to compensate for radiative cooling., Comment: 8 pages, 5 figures, submitted to MNRAS

Most of the recent work in psychedelic neuroscience has been done using non-invasive neuroimaging, with data recorded from the brains of adult volunteers under the influence of a variety of drugs. While this data provides holistic insights into the effects of psychedelics on whole-brain dynamics, the effects of psychedelics on the meso-scale dynamics of cortical circuits remains much less explored. Here, we report the effects of the serotonergic psychedelic N,N-diproptyltryptamine (DPT) on information-processing dynamics in a sample of in vitro organotypic cultures made from rat cortical tissue. Three hours of spontaneous activity were recorded: an hour of pre-drug control, and hour of exposure to 10$\mu$M DPT solution, and a final hour of washout, once again under control conditions. We found that DPT reversibly alters information dynamics in multiple ways: first, the DPT condition was associated with higher entropy of spontaneous firing activity and reduced the amount of time information was stored in individual neurons. Second, DPT also reduced the reversibility of neural activity, increasing the entropy produced and suggesting a drive away from equilibrium. Third, DPT altered the structure of neuronal circuits, decreasing the overall information flow coming into each neuron, but increasing the number of weak connections, creating a dynamic that combines elements of integration and disintegration. Finally, DPT decreased the higher-order statistical synergy present in sets of three neurons. Collectively, these results paint a complex picture of how psychedelics regulate information processing in meso-scale cortical tissue. Implications for existing hypotheses of psychedelic action, such as the Entropic Brain Hypothesis, are discussed., Comment: 19 pages, 2 figures

The upgraded Facility for Advanced Accelerator Experimental Tests (FACET-II) at SLAC National Accelerator Laboratory has been designed to deliver ultra-relativistic electron and positron beams with unprecedented parameters, especially in terms of high peak current and low emittance. For most of the foreseen experimental campaigns hosted at this facility, the high energy radiation produced by these beams at the Interaction Point will be a valuable diagnostic to assess the different physical processes under study. This article describes the X-ray and {\gamma}-ray detectors installed for the initial phase of FACET-II. Furthermore, experimental measurements obtained with these detectors during the first commissioning and user runs are presented and discussed, illustrating the working principles and potential applications of these detectors., Comment: Proceedings of the Advanced Accelerator Concepts (AAC) Workshop 2022

Plasma Wakefield Acceleration (PWFA) provides ultrahigh acceleration gradients of 10s of GeV/m, providing a novel path towards efficient, compact, TeV-scale linear colliders and high brightness free electron lasers. Critical to the success of these applications is demonstrating simultaneously high gradient acceleration, high energy transfer efficiency, and preservation of emittance, charge, and energy spread. Experiments at the FACET-II National User Facility at SLAC National Accelerator Laboratory aim to achieve all of these milestones in a single stage plasma wakefield accelerator, providing a 10 GeV energy gain in a <1 m plasma with high energy transfer efficiency. Such a demonstration depends critically on diagnostics able to measure emittance with mm-mrad accuracy, energy spectra to determine both %-level energy spread and broadband energy gain and loss, incoming longitudinal phase space, and matching dynamics. This paper discusses the experimental setup at FACET-II, including the incoming beam parameters from the FACET-II linac, plasma sources, and diagnostics developed to meet this challenge. Initial progress on the generation of beam ionized wakes in meter-scale hydrogen gas is discussed, as well as commissioning of the plasma sources and diagnostics.

High repetition rates and efficient energy transfer to the accelerating beam are important for a future linear collider based on the beam-driven plasma wakefield acceleration scheme (PWFA-LC). This paper reports the first results from the Plasma Wakefield Acceleration Collaboration (E300) that are beginning to address both of these issues using the recently commissioned FACET-II facility at SLAC. We have generated meter-scale hydrogen plasmas using time-structured 10 GeV electron bunches from FACET-II, which hold the promise of dramatically increasing the repetition rate of PWFA by rapidly replenishing the gas between each shot compared to the hitherto used lithium plasmas that operate at 1-10 Hz. Furthermore, we have excited wakes in such plasmas that are suitable for high gradient particle acceleration with high drive-bunch to wake energy transfer efficiency -- a first step in achieving a high overall energy transfer efficiency. We have done this by using time-structured electron drive bunches that typically have one or more ultra-high current (>30 kA) femtosecond spike(s) superimposed on a longer (~0.4 ps) lower current (<10 kA) bunch structure. The first spike effectively field-ionizes the gas and produces a meter-scale (30-160 cm) plasma, whereas the subsequent beam charge creates a wake. The length and amplitude of the wake depends on the longitudinal current profile of the bunch and plasma density. We find that the onset of pump depletion, when some of the drive beam electrons are nearly fully depleted of their energy, occurs for hydrogen pressure >1.5 Torr. We also show that some electrons in the rear of the bunch can gain several GeV energies from the wake. These results are reproduced by particle-in-cell simulations using the QPAD code. At a pressure of ~2 Torr, simulations results and experimental data show that the beam transfers about 60% of its energy to the wake.