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The current study presents the cross-section measurement of $^{181}$Ta(n,$\gamma$)$^{182}$Ta reaction at 1.37 $\pm$ 0.13, 2.06 $\pm$ 0.14, 2.56 $\pm$ 0.15, and 3.05 $\pm$ 0.17 MeV neutron energies utilizing offline $\gamma$-ray spectroscopy. The neutrons were generated through the $^{7}$Li(p,n)$^{7}$Be reaction. The $^{115}$In(n,n'$\gamma$)$^{115m}$In reaction served as a monitor reaction. The covariance analysis was used to quantify the uncertainties in the measured cross-sections for the first time for the $^{181}$Ta(n,$\gamma$)$^{182}$Ta reaction. The present study provides detailed information on the propagation of uncertainty in the overall result. The required corrections for low energy background neutron and $\gamma$-ray coincidence summing effect have been made in the present measurement. The output is compared with the pre-existing cross-section data from the EXFOR database, evaluated data libraries and theoretical model predictions.

The neutron capture cross-section for the $^{181}$Ta(n,$\gamma$)$^{182}$Ta reaction has been experimentally measured at the neutron energies 0.53 and 1.05 MeV using off-line $\gamma$-ray spectrometry. $^{115}$In(n,n'$\gamma$)$^{115m}$In is used as a reference monitor reaction cross-section. The neutron was produced via the $^{7}$Li(p,n)$^{7}$Be reaction. The present study measures the cross-sections with their uncertainties and correlation matrix. The self-attenuation process, $\gamma$-ray correction factor, and low background neutron energy contribution have been calculated. The measured neutron spectrum averaged cross-sections of $^{181}$Ta(n,$\gamma$)$^{182}$Ta are discussed and compared with the existing data from the EXFOR database and also with the ENDF/B-VIII.0, TENDL-2019, JENDL-5, JEFF-3.3 evaluated data libraries.

There is a lack of benchmarks for evaluating large language models (LLMs) in long-form medical question answering (QA). Most existing medical QA evaluation benchmarks focus on automatic metrics and multiple-choice questions. While valuable, these benchmarks fail to fully capture or assess the complexities of real-world clinical applications where LLMs are being deployed. Furthermore, existing studies on evaluating long-form answer generation in medical QA are primarily closed-source, lacking access to human medical expert annotations, which makes it difficult to reproduce results and enhance existing baselines. In this work, we introduce a new publicly available benchmark featuring real-world consumer medical questions with long-form answer evaluations annotated by medical doctors. We performed pairwise comparisons of responses from various open and closed-source medical and general-purpose LLMs based on criteria such as correctness, helpfulness, harmfulness, and bias. Additionally, we performed a comprehensive LLM-as-a-judge analysis to study the alignment between human judgments and LLMs. Our preliminary results highlight the strong potential of open LLMs in medical QA compared to leading closed models. Code & Data: https://github.com/lavita-ai/medical-eval-sphere, Comment: AIM-FM: Advancements in Medical Foundation Models Workshop, 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

Extreme ultraviolet (XUV) light sources allow for the probing of bound electron dynamics on attosecond scales, interrogation of high-energy-density matter, and access to novel regimes of strong-field quantum electrodynamics. Despite the importance of these applications, coherent XUV sources remain relatively rare, and those that do exist are limited in their peak intensity and spatio-polarization structure. Here, we demonstrate that photon acceleration of an optical vector vortex pulse in the moving density gradient of an electron beam-driven plasma wave can produce a high-intensity, tunable-wavelength XUV pulse with the same vector vortex structure as the original pulse. Quasi-3D, boosted-frame particle-in-cell simulations show the transition of optical vector vortex pulses with 800-nm wavelengths and intensities below $10^{18}$ W/cm$^2$ to XUV vector vortex pulses with 36-nm wavelengths and intensities exceeding $10^{20}$ W/cm$^2$ over a distance of 1.2 cm. The XUV pulses have sub-femtosecond durations and nearly flat phase fronts. The production of such high-quality, high-intensity XUV vector vortex pulses could expand the utility of XUV light as a diagnostic and driver of novel light-matter interactions., Comment: 25 pages, 5 figures, planned submission to scientific journal

Low-phase-noise microwave-frequency integrated oscillators provide compact solutions for various applications in signal processing, communications, and sensing. Surface acoustic waves (SAW), featuring orders-of-magnitude shorter wavelength than electromagnetic waves at the same frequency, enable integrated microwave-frequency systems with much smaller footprint on chip. SAW devices also allow higher quality (Q) factors than electronic components at room temperature. Here, we demonstrate a low-phase-noise gigahertz-frequency SAW oscillator on 128{\deg}Y-cut lithium niobate, where the SAW resonator occupies a footprint of 0.05 mm$^2$. Leveraging phononic crystal bandgap-edge modes to balance between Q factors and insertion losses, our 1-GHz SAW oscillator features a low phase noise of -132.5 dBc/Hz at a 10 kHz offset frequency and an overlapping Hadamard deviation of $6.5\times10^{-10}$ at an analysis time of 64 ms. The SAW resonator-based oscillator holds high potential in developing low-noise sensors and acousto-optic integrated circuits.

We report on a direct search for elastic photon-photon scattering using x-ray and $\gamma$ photons from a laser-plasma based experiment. A gamma photon beam produced by a laser wakefield accelerator provided a broadband gamma spectrum extending to above $E_\gamma = 200$ MeV. These were collided with a dense x-ray field produced by the emission from a laser heated germanium foil at $E_x \approx 1.4$ keV, corresponding to an invariant mass of $\sqrt{s} = 1.22 \pm 0.22$ MeV. In these asymmetric collisions elastic scattering removes one x-ray and one high-energy $\gamma$ photon and outputs two lower energy $\gamma$ photons. No changes in the $\gamma$ photon spectrum were observed as a result of the collisions allowing us to place a 95% upper bound on the cross section of $1.5 \times 10^{15}\,\mu$b. Although far from the QED prediction, this represents the lowest upper limit obtained so far for $\sqrt{s} \lesssim 1$ MeV., Comment: 6 pages, 10 figures

Radiation reaction describes the effective force experienced by an accelerated charge due to radiation emission. Quantum effects dominate charge dynamics and radiation production[1][2] for charges accelerated by fields with strengths approaching the Schwinger field, $\mathbf{E_{sch}=}$\textbf{\SI[detect-weight]{1.3e18}{\volt\per\metre}[3]. Such fields exist in extreme astrophysical environments such as pulsar magnetospheres[4], may be accessed by high-power laser systems[5-7], dense particle beams interacting with plasma[8], crystals[9], and at the interaction point of next generation particle colliders[10]. Classical radiation reaction theories do not limit the frequency of radiation emitted by accelerating charges and omit stochastic effects inherent in photon emission[11], thus demanding a quantum treatment. Two quantum radiation reaction models, the quantum-continuous[12] and quantum-stochastic[13] models, correct the former issue, while only the quantum-stochastic model incorporates stochasticity[12]. Such models are of fundamental importance, providing insight into the effect of the electron self-force on its dynamics in electromagnetic fields. The difficulty of accessing conditions where quantum effects dominate inhibited previous efforts to observe quantum radiation reaction in charged particle dynamics with high significance. We report the first direct, high significance $(>5{\sigma})$ observation of strong-field radiation reaction on charged particles. Furthermore, we obtain strong evidence favouring the quantum radiation reaction models, which perform equivalently, over the classical model. Robust model comparison was facilitated by a novel Bayesian framework which inferred collision parameters. This framework has widespread utility for experiments where parameters governing lepton-laser collisions cannot be directly measured, including those using conventional accelerators., Comment: 31 pages, 14 figures

We describe how to simulate charge diffusion in organic semiconductors using a recently introduced mixed quantum-classical method, the mapping approach to surface hopping (MASH). In contrast to standard fewest-switches surface hopping, this method propagates the classical degrees of freedom deterministically on the most populated adiabatic electronic state. This correctly preserves the equilibrium distribution of a quantum charge coupled to classical phonons, allowing one to time-average along trajectories to improve the statistical convergence of the calculation. We illustrate the method with an application to a standard model for the charge transport in the direction of maximum mobility in crystalline rubrene. Because of its consistency with the equilibrium distribution, the present method gives a time-dependent diffusion coefficient that plateaus correctly to a long-time limiting value. The resulting mobility is somewhat higher than that of the relaxation time approximation, which uses a phenomenological relaxation parameter to obtain a non-zero diffusion coefficient from a calculation with static phonon disorder. However, it is very similar to the mobility obtained from Ehrenfest dynamics, at least in the parameter regimes we have investigated here. This is somewhat surprising because Ehrenfest dynamics overheats the electronic subsystem and is therefore inconsistent with the equilibrium distribution., Comment: 13 pages, 5 figures

We experimentally demonstrate enhanced absorption of near relativistic optical vortex beams in $\mathrm{D_2O}$ plasmas to generate a record fast-neutron yield of $1.45 \times 10^6$ n/s/sr. Beams with a topological charge of 5 were shown to deliver up to a 3.3 times enhancement of fast-neutron yield over a Gaussian focused beam of the same energy but having two orders of magnitude higher intensity. This result was achieved with laser energies of 16 mJ and a pulse duration of 67 fs. The Orbital Angular Momentum (OAM) beam-target interactions in our experiment were also investigated through Particle-in-Cell (PIC) simulations. Electron density rippling resulting in enhanced plasma wave excitation on the critical surface and significantly enhanced resonance absorption is observed., Comment: 7 pages, 4 figures

One of the central objectives of contemporary neuroimaging research is to create predictive models that can disentangle the connection between patterns of functional connectivity across the entire brain and various behavioral traits. Previous studies have shown that models trained to predict behavioral features from the individual's functional connectivity have modest to poor performance. In this study, we trained models that predict observable individual traits (phenotypes) and their corresponding singular value decomposition (SVD) representations - herein referred to as latent phenotypes from resting state functional connectivity. For this task, we predicted phenotypes in two large neuroimaging datasets: the Human Connectome Project (HCP) and the Philadelphia Neurodevelopmental Cohort (PNC). We illustrate the importance of regressing out confounds, which could significantly influence phenotype prediction. Our findings reveal that both phenotypes and their corresponding latent phenotypes yield similar predictive performance. Interestingly, only the first five latent phenotypes were reliably identified, and using just these reliable phenotypes for predicting phenotypes yielded a similar performance to using all latent phenotypes. This suggests that the predictable information is present in the first latent phenotypes, allowing the remainder to be filtered out without any harm in performance. This study sheds light on the intricate relationship between functional connectivity and the predictability and reliability of phenotypic information, with potential implications for enhancing predictive modeling in the realm of neuroimaging research.

In this article we investigate novel signatures of radiation reaction via the angular deflection of an electron beam colliding at 90 degrees with an intense laser pulse. Due to the radiation reaction effect, the electrons can be deflected towards the beam axis for plane wave backgrounds, which is not possible in the absence of radiation reaction effects. The magnitude and size of the deflection angle can be controlled by tailoring the laser pulse shapes. The effect is first derived analytically using the Landau-Lifshitz equation, which allows to determine the important scaling behavior with laser intensity and particle energy. We then move on to full scale 3D Monte Carlo simulations to verify the effect is observable with present day laser technology. We investigate the opportunities for an indirect observation of laser depletion in such side scattering scenarios., Comment: 12 pages, 9 figures

Direct Laser Acceleration (DLA) of electrons during a high-energy, picosecond laser interaction with an underdense plasma has been demonstrated to be substantially enhanced by controlling the laser focusing geometry. Experiments using the OMEGA EP facility measured electrons accelerated to maximum energies exceeding 120 times the ponderomotive energy under certain laser focusing, pulse energy, and plasma density conditions. Two-dimensional particle-in-cell simulations show that the laser focusing conditions alter the laser field evolution, channel fields generation, and electron oscillation, all of which contribute to the final electron energies. The optimal laser focusing condition occurs when the transverse oscillation amplitude of the accelerated electron in the channel fields matches the laser beam width, resulting in efficient energy gain. Through this observation, a simple model was developed to calculate the optimal laser focal spot size in more general conditions and is validated by experimental data., Comment: 14 pages, 6 figures

Spatiotemporal control encompasses a variety of techniques for producing laser pulses with dynamic intensity peaks that move independently of the group velocity. This controlled motion of the intensity peak offers a new approach to optimizing laser-based applications and enhancing signatures of fundamental phenomena. Here, we demonstrate spatiotemporal control with a plasma optic. A chirped laser pulse focused by a plasma lens exhibits a moving focal point, or "flying focus," that can travel at an arbitrary, predetermined velocity. Unlike currently used conventional or adaptive optics, a plasma lens can be located close to the interaction region and can operate at an orders of magnitude higher, near-relativistic intensity.

Radiative cooling of electron beams interacting with counter-propagating electromagnetic waves is analyzed, taking into account the quantum modification of the radiation friction force. Central attention is paid to the evolution of the energy spectrum of electrons accelerated by the laser wake field acceleration mechanism. As an electron beam loses energy to radiation, the mean energy decreases and the form of the energy distribution also changes due to quantum-mechanical spectral broadening., Comment: 27 pages, 9 figures

Resilient operation of interdependent infrastructures against compound hazard events is essential for maintaining societal well-being. To address consequence assessment challenges in this problem space, we propose a novel tri-level optimization model applied to a proof-of-concept case study with fuel distribution and transportation networks -- encompassing one realistic network; one fictitious, yet realistic network; as well as networks drawn from three synthetic distributions. Mathematically, our approach takes the form of a defender-attacker-defender (DAD) model -- a multi-agent tri-level optimization, comprised of a defender, attacker, and an operator acting in sequence. Here, our notional operator may choose proxy actions to operate an interdependent system comprised of fuel terminals and gas stations (functioning as supplies) and a transportation network with traffic flow (functioning as demand) to minimize unmet demand at gas stations. A notional attacker aims to hypothetically disrupt normal operations by reducing supply at the supply terminals, and the notional defender aims to identify best proxy defense policy options which include hardening supply terminals or allowing alternative distribution methods such as trucking reserve supplies. We solve our DAD formulation at a metropolitan scale and present practical defense policy insights against hypothetical compound hazards. We demonstrate the generalizability of our framework by presenting results for a realistic network; a fictitious, yet realistic network; as well as for three networks drawn from synthetic distributions. Additionally, we demonstrate the scalability of the framework by investigating runtime performance as a function of the network size. Steps for future research are also discussed.

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.

Magnetic field generation in ultra-intense laser-solid interactions is studied over a range of laser intensities relevant to next-generation laser facilities ($a_0 = 50-500$) using 2D particle-in-cell simulations. It is found that fields on the order of 0.1 MT (1 GigaGauss) may be generated by relativistic electrons traveling along the surface of the target. However a significant fraction of the energy budget is converted to high-energy photons, ~38% at $a_0=500$, greatly reducing the available energy for field generation. A model for the evolution of the target-surface fields and their scaling with $a_0$ is developed using laser parameters and assumed values for the average radial electron velocity and reflectivity. The model and empirical scaling allow for the estimation of field strengths on the next generation of laser facilities, a necessary component to the proposal of any future magnetized experiment., Comment: 8 pages, 8 figures

The investigation of spin and polarization effects in ultra-high intensity laser-plasma and laser-beam interactions has become an emergent topic in high-field science recently. In this paper we derive a relativistic kinetic description of spin-polarized plasmas, where QED effects are taken into account via Boltzmann-type collision operators under the local constant field approximation. The emergence of anomalous precession is derived from one-loop self-energy contributions in a strong background field. We are interested, in particular, in the interplay between radiation reaction effects and the spin polarization of the radiating particles. For this we derive equations for spin-polarized quantum radiation reaction from moments of the spin-polarized kinetic equations. By comparing with the classical theory, we identify and discuss the spin-dependent radiation reaction terms, and radiative contributions to spin dynamics., Comment: 18 pages, 3 figures, to appear in POP special issue "Relativistic Plasma in Supercritical Electromagnetic Fields"

With the rapid development of high-power petawatt class lasers worldwide, exploring physics in the strong field QED regime will become one of the frontiers for laser-plasma interactions research. Particle-in-cell codes, including quantum emission processes, are powerful tools for predicting and analyzing future experiments where the physics of relativistic plasma is strongly affected by strong-field QED processes. The spin/polarization dependence of these quantum processes has been of recent interest. In this article, we perform a parametric study of the interaction of two laser pulses with an ultrarelativistic electron beam. The first pulse is optimized to generate high-energy photons by nonlinear Compton scattering and efficiently decelerate the electron beam through quantum radiation reaction. The second pulse is optimized to generate electron-positron pairs by nonlinear Breit-Wheeler decay of the photons with the maximum polarization dependence. This may be experimentally realized as a verification of the strong field QED framework, including the spin/polarization rates., Comment: 15 pages, 13 figures

Inferring the mechanisms underlying physiological and pathological processes in the brain from recorded electrical activity is challenging. Bayesian model selection and dynamic causal modelling aim to identify likely biophysical models to explain data and to fit the model parameters. Here, we use data generated by simulations to investigate the effectiveness of Bayesian model selection and dynamic causal modelling when applied at steady state in the frequency domain to identify and fit Jansen-Rit models. We first investigate the impact of the necessary assumption of linearity on the dynamics of the Jansen-Rit model. We then apply dynamic causal modelling and Bayesian model selection to data generated from simulations of linear neural mass models, non-linear neural mass models, and networks of discrete spiking neurons. Action potentials are a characteristic feature of neuronal dynamics but have not previously been explicitly included in simulations used to test Bayesian model selection or dynamic causal modelling. We find that the assumption of linearity abolishes the qualitative transitions seen as a function of the connectivity parameter in the original Jansen-Rit model. As with previous work, we find that the recovery procedures are effective when applied to data from linear Jansen-Rit neural mass models, however, when applying them to non-linear neural mass models and networks of discrete spiking neurons we find that their effectiveness is significantly reduced, suggesting caution is required when applying these methods., Comment: 18 pages, 15 figures

Solving fluid dynamics equations often requires the use of closure relations that account for missing microphysics. For example, when solving equations related to fluid dynamics for systems with a large Reynolds number, sub-grid effects become important and a turbulence closure is required, and in systems with a large Knudsen number, kinetic effects become important and a kinetic closure is required. By adding an equation governing the growth and transport of the quantity requiring the closure relation, it becomes possible to capture microphysics through the introduction of ``hidden variables'' that are non-local in space and time. The behavior of the ``hidden variables'' in response to the fluid conditions can be learned from a higher fidelity or ab-initio model that contains all the microphysics. In our study, a partial differential equation simulator that is end-to-end differentiable is used to train judiciously placed neural networks against ground-truth simulations. We show that this method enables an Euler equation based approach to reproduce non-linear, large Knudsen number plasma physics that can otherwise only be modeled using Boltzmann-like equation simulators such as Vlasov or Particle-In-Cell modeling.

Laser-driven compact particle accelerators can provide ultrashort pulses of broadband X-rays, well suited for undertaking X-ray absorption spectroscopy measurements on a femtosecond timescale. Here the Extended X-ray Absorption Fine Structure (EXAFS) features of the K-edge of a copper sample have been observed over a 250 eV window in a single shot using a laser wakefield accelerator, providing information on both the electronic and ionic structure simultaneously. This unique capability will allow the investigation of ultrafast processes, and in particular, probing high-energy-density matter and physics far-from-equilibrium where the sample refresh rate is slow and shot number is limited. For example, states that replicate the tremendous pressures and temperatures of planetary bodies or the conditions inside nuclear fusion reactions. Using high-power lasers to pump these samples also has the advantage of being inherently synchronised to the laser-driven X-ray probe. A perspective on the additional strengths of a laboratory-based ultrafast X-ray absorption source is presented.

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimisation of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimisation. Here, an automated, HRR-compatible system produced high fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimisation of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually-optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimisation of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources., Comment: 11 pages