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We developed a facile and scalable 3-step hydrothermal, electrodeposition, and annealing technique to synthesize a variety of nanowire heterostructures. The heterojunction catalysts of CP-ZnO-MoS2 and CP-ZnO-ZnS-MoS2 both saw an increase in catalytic activity in the acidic regime, with overpotentials to reach 10 mA/cm2 of 181 mV and 154 mV respectively, over their constituent materials. The CP-ZnO-ZnS-MoS2 catalysts also saw an increase in catalytic activity in the alkaline conditions, requiring only 209 mV to reach 10 mA/cm2. This has been attributed primarily to the synergistic properties of the band alignment structure and the increased surface area afforded by the nanowire structure. The 1T phase was also noted in the CP-ZnO-MoS2 sample, suggesting that this also played a role in increasing the catalytic activity of the sample. Overall, the synthesized nanowire heterostructures were found to be high-performing and gives insight into how the changing band alignment and morphology can play a significant role in increasing the catalytic performance towards HER., Comment: 24 Pages, 14 Figures

X-ray fluorescence computed tomography (XFCT), a form of X-ray molecular imaging, offers detailed quantitative imaging capabilities for high-Z metal nanoparticles (MNPs), which are widely studied for their applications in multifunctional theranostics. Due to its affordability and accessibility, the benchtop XFCT prototype typically employs a single-pixel detector (SPD) with single-pencil-beam (SPB) X-ray excitation. While this design (resembling the first-generation CT geometry) achieves reliable detection sensitivity, it is hindered by long imaging times. The use of simultaneous multiple-pencil-beam (MPB) excitation presents a promising solution to significantly reduce imaging times. In this study, we developed a repeatable workflow that combines Monte Carlo (MC) simulations and 3D printing to design Nbeam-MPB collimator, where Nbeam is the number of beams generated by the collimator. As an initial test, we fabricated a 2-MPB collimator and evaluated the performance of 2-MPB-based XFCT imaging on a physical phantom and small animals surgically implanted with agarose pellets containing gold chloride (H[AuCl4]). The results demonstrated a 2x acceleration in image acquisition without compromising the contrast-to-noise ratio (CNR). We further investigated the concept of Nbeam-MPB acceleration on the MC computational XFCT system, which confirmed the feasibility of achieving at least 4x acceleration with 4-MPB excitation. Combined with additional system optimization, such as X-ray beam flux optimization, XFCT imaging could be further accelerated, reducing acquisition time from hours to minutes and meeting the requirements for routine MNP imaging.

The radial velocity (RV) method, also known as Doppler spectroscopy, is a powerful technique for exoplanet discovery and characterization. In recent years, progress has been made thanks to the improvements in the quality of spectra from new extreme precision RV spectrometers. However, detecting the RV signals of Earth-like exoplanets remains challenging, as the spectroscopic signatures of low-mass planets can be obscured or confused with intrinsic stellar variability. Changes in the shapes of spectral lines across time can provide valuable information for disentangling stellar activity from true Doppler shifts caused by low-mass exoplanets. In this work, we present a fixed effects linear model to estimate RV signals that controls for changes in line shapes by aggregating information from hundreds of spectral lines. Our methodology incorporates a wild-bootstrap approach for modeling uncertainty and cross-validation to control for overfitting. We evaluate the model's ability to remove stellar activity using solar observations from the NEID spectrograph, as the sun's true center-of-mass motion is precisely known. Including line shape-change covariates reduces the RV root-mean-square errors by approximately 70% (from 1.919 m s$^{-1}$ to 0.575 m s$^{-1}$) relative to using only the line-by-line Doppler shifts. The magnitude of the residuals is significantly less than that from traditional CCF-based RV estimators and comparable to other state-of-the-art methods for mitigating stellar variability., Comment: Submitted to AAS Journals. 20 pages, 5 figures, 2 tables

Binary black holes (BBH) are expected to form and merge in active galactic nuclei (AGN), deep in the potential well of a supermassive black hole (SMBH), from populations that exist in a nuclear star cluster (NSC). Here we investigate the gravitational wave (GW) signature of a BBH lensed by a nearby SMBH. For a fiducial GW150914-like BBH orbiting close to a $10^{8}M_{\odot}$ SMBH located at $z=0.1$, the lensed GW signal varies in a predictable manner in and out of the LISA detectability band and across frequencies. The occurrence of such signatures has the potential to confound LISA global fit models if they are not modelled. Detection of these sources provide an independent measure of AGN inclination angles, along with detecting warping of the inner disk, and measuring the SMBH spin., Comment: 10 pages, 5 figures, ApJ (submitted)

Scalable solid-state quantum computers will require integration with analog and digital electronics. Efficiently simulating the quantum-classical electronic interface is hence of paramount importance. Here, we present Verilog-A compact models with a focus on quantum-dot-based systems, relevant to semiconductor- and Majorana-based quantum computing. Our models are capable of faithfully reproducing coherent quantum behavior within a standard electronic circuit simulator, enabling compromise-free co-simulation of hybrid quantum devices. In particular, we present results from co-simulations performed in Cadence Spectre, showcasing coherent quantum phenomena in circuits with both quantum and classical components using an industry-standard electronic design and automation tool. Our work paves the way for a new paradigm in the design of quantum systems, which leverages the many decades of development of electronic computer-aided design and automation tools in the semiconductor industry to now simulate and optimize quantum processing units, quantum-classical interfaces, and hybrid quantum-analog circuits.

PyMOLfold is a flexible and open-source plugin designed to seamlessly integrate AI-based protein structure prediction and visualization within the widely used PyMOL molecular graphics system. By leveraging state-of-the-art protein folding models such as ESM3, Boltz-1, and Chai-1, PyMOLfold allows researchers to directly predict protein tertiary structures from amino acid sequences without requiring external tools or complex workflows. Furthermore, with certain models, users can provide a SMILES string of a ligand and have the small molecule placed in the protein structure. This unique capability bridges the gap between computational folding and structural visualization, enabling users to input a primary sequence, perform a folding prediction, and immediately explore the resulting 3D structure within the same intuitive platform., Comment: GitHub Repository: https://github.com/colbyford/PyMolfold

We consider methods for optimizing the bandgap calculation of 3D materials, considering 340 sample materials. Examined are the effects of the choice of the pseudopotential to describe core electrons, the plane-wave basis set cutoff energy, and the Brillouin zone integration. Cost-saving calculations in which the structure is optimized using reduced-quality Brillouin zone integrations and cutoff energies were found to lead to experimentally significant errors exceeding 0.1 eV in 18% of cases using the PBE functional and 21% of cases using PBE0. Such cost-savings approaches are therefore not recommended for general applications. Also, the current practice of using unoptimized grids to perform the Brillouin-zone integrations in bandgap calculations is found to be unreliable for 16% of materials using PBE and for 23% using PBE0. A k-space optimization scheme is introduced that interpolates extensive PBE results to determine a generally useful approach that when used in PBE0 calculations is found to be inadequate for only 1.6% of the materials studied.

We present a 5 month NICER X-ray monitoring campaign for two low luminosity active galactic nuclei (LLAGNs) -- NGC 4594 and IC 1459 -- with complementary Swift and NuSTAR observations. Utilizing an absorbed power law and thermal source model combined with NICER's SCORPEON background model, we demonstrate the effectiveness of joint source/background modeling for constraining emission from faint, background-dominated targets. Both sources are dominated by nuclear power law emission with photon indices $\Gamma \sim 1.5 - 2$, with NGC 4594 being slightly harder than IC 1459. The thermal contribution in both sources is fainter, but constant, with $kT \sim 0.5$ keV ($\sim 5 \times 10^6$ K). The power law flux and $\Gamma$ are strongly anti-correlated in both sources, as has been seen for other LLAGNs with radiatively inefficient accretion flows. NGC 4594 is the brighter source and exhibits significant aperiodic variability. Its variability timescale with an upper limit of $5 - 7$ days indicates emission originating from $< 100 R_{g}$, at the scale of the inner accretion flow. A spectral break found at $\sim 6$ keV, while tentative, could arise from synchrotron/inverse compton emission. This high-cadence LLAGN X-ray monitoring campaign underlines the importance of multi-wavelength variability studies for a sample of LLAGNs to truly understand their accretion and outflow physics., Comment: 18 pages, 5 figures, 5 tables. Accepted to ApJ

Luttinger liquids occupy a special place in physics as the most understood case of essentially quantum many-body systems. The experimental mission of measuring its main prediction, power laws in observable quantities, has already produced a body of exponents in different semiconductor and metallic structures. Here, we combine tunneling spectroscopy with density-dependent transport measurements in the same quantum wires over more than two orders of magnitude in temperature to very low temperatures down to $\sim$40 mK. This reveals that, when the second 1D subband becomes populated, the temperature dependence splits into two ranges with different exponents in the power-law dependence of the conductance, both dominated by the finite-size effect of the end-tunneling process. This result demonstrates the importance of measuring the Luttinger parameters as well as the number of modes independently through spectroscopy in addition to the transport exponent in the characterization of Luttinger liquids. This opens a new pathway to unambiguous interpretation of the exponents observed in quantum wires., Comment: 27 pages, 7 figures

The half-life of $^{39}$Ar is measured using the DEAP-3600 detector located 2 km underground at SNOLAB. In 2016-2020, DEAP-3600 used a target mass of (3269 $\pm$ 24) kg of liquid argon distilled from the atmosphere in a direct-detection dark matter search. Such an argon mass also enables direct measurements of argon isotope properties. The decay of $^{39}$Ar in DEAP-3600 is the dominant source of triggers by two orders of magnitude, ensuring high statistics and making DEAP-3600 well-suited for measuring this isotope's half-life. Use of the pulse-shape discrimination technique in DEAP-3600 allows for powerful discrimination between nuclear recoils and electron recoils, resulting in the selection of a clean sample of $^{39}$Ar decays. Observing over a period of 3.4 years, the $^{39}$Ar half-life is measured to be $(302 \pm 8_{\rm stat} \pm 6_{\rm sys})$ years. This new direct measurement suggests that the half-life of $^{39}$Ar may be significantly longer than the accepted value, with potential implications for measurements using this isotope's half-life as input., Comment: 11 pages, 8 figures

On July 13, 2024, at the Trump rally in Pennsylvania, someone attempted to assassinate Republican Presidential Candidate Donald Trump. This attempt sparked a large-scale discussion on social media. We collected posts from X (formerly known as Twitter) one week before and after the assassination attempt and aimed to model the short-term effects of such a ``shock'' on public opinions and discussion topics. Specifically, our study addresses three key questions: first, we investigate how public sentiment toward Donald Trump shifts over time and across regions (RQ1) and examine whether the assassination attempt itself significantly affects public attitudes, independent of the existing political alignments (RQ2). Finally, we explore the major themes in online conversations before and after the crisis, illustrating how discussion topics evolved in response to this politically charged event (RQ3). By integrating large language model-based sentiment analysis, difference-in-differences modeling, and topic modeling techniques, we find that following the attempt the public response was broadly sympathetic to Trump rather than polarizing, despite baseline ideological and regional disparities.

Many active galaxies harbor powerful relativistic jets, however, the detailed mechanisms of their formation and acceleration remain poorly understood. To investigate the area of jet acceleration and collimation with the highest available angular resolution, we study the innermost region of the bipolar jet in the nearby low-ionization nuclear emission-line region (LINER) galaxy NGC 1052. We combined observations of NGC 1052 taken with VLBA, GMVA, and EHT over one week in the spring of 2017. For the first time, NGC 1052 was detected with the EHT, providing a size of the central region in-between both jet bases of 250 RS (Schwarzschild radii) perpendicular to the jet axes. This size estimate supports previous studies of the jets expansion profile which suggest two breaks of the profile at around 300 RS and 10000 RS distances to the core. Furthermore, we estimated the magnetic field to be 1.25 Gauss at a distance of 22 {\mu}as from the central engine by fitting a synchrotron-self absorption spectrum to the innermost emission feature, which shows a spectral turn-over at about 130 GHz. Assuming a purely poloidal magnetic field, this implies an upper limit on the magnetic field strength at the event horizon of 26000 Gauss, which is consistent with previous measurements. The complex, low-brightness, double-sided jet structure in NGC 1052 makes it a challenge to detect the source at millimeter (mm) wavelengths. However, our first EHT observations have demonstrated that detection is possible up to at least 230 GHz. This study offers a glimpse through the dense surrounding torus and into the innermost central region, where the jets are formed. This has enabled us to finally resolve this region and provide improved constraints on its expansion and magnetic field strength., Comment: 22 pages, 10 figures, published in A&A

Data-centric technologies provide exciting opportunities, but recent research has shown how lack of representation in datasets, often as a result of systemic inequities and socioeconomic disparities, can produce inequitable outcomes that can exclude or harm certain demographics. In this paper, we discuss preliminary insights from an ongoing effort aimed at better understanding barriers to equitable data-centric innovation. We report findings from a survey of 261 technologists and researchers who use data in their work regarding their experiences seeking adequate, representative datasets. Our findings suggest that age and identity play a significant role in the seeking and selection of representative datasets, warranting further investigation into these aspects of data-centric research and development.

The time-variable emission from the accretion flow of Sgr A*, the supermassive black hole at the Galactic Center, has long been examined in the radio-to-mm, near-infrared (NIR), and X-ray regimes of the electromagnetic spectrum. However, until now, sensitivity and angular resolution have been insufficient in the crucial mid-infrared (MIR) regime. The MIRI instrument on JWST has changed that, and we report the first MIR detection of Sgr A*. The detection was during a flare that lasted about 40 minutes, a duration similar to NIR and X-ray flares, and the source's spectral index steepened as the flare ended. The steepening suggests synchrotron cooling is an important process for Sgr A*'s variability and implies magnetic field strengths $\sim$40--70 Gauss in the emission zone. Observations at $1.3~\mathrm{mm}$ with the Submillimeter Array revealed a counterpart flare lagging the MIR flare by $\approx$10 minutes. The observations can be self-consistently explained as synchrotron radiation from a single population of gradually cooling high-energy electrons accelerated through (a combination of) magnetic reconnection and/or magnetized turbulence., Comment: Accepted for publication ApJL

The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed: the main science targets, Sgr A* and M87 along with various calibrators. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-K\"onigl (BK) jet model. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2-86 GHz range. Then, we studied the dependences of the VLBI core flux density, size, and brightness temperature on the frequency measured in the AGN host frame. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole. Our results indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations.

Using the Event Horizon Telescope (EHT), the gravitationally lensed rings around the supermassive black holes (SMBHs) in Messier 87 (M87) and Sagittarius A* (Sgr A*) have now been successfully imaged at a resolution under 10 gravitational radii (R$_{\rm g}$ $ = \rm{GM/c^2}$). To expand studies beyond M87 and Sgr A*, we have constructed the Event Horizon and Environs (ETHER) sample, a comprehensive database encompassing approximately 3.15 million SMBH mass estimates, $\sim$ 20,000 Very-Long Baseline Interferometry (VLBI) radio flux densities, and $\sim$ 36,000 hard X-ray flux densities. This database is designed to identify and optimize target selection for the EHT and its upgrades on the ground and in space. We have identified a Gold Sample (GS) of nearby low-luminosity Active Galactic Nuclei (AGNs) within it that are ideal for studying jet bases and potentially imaging black hole shadows. We observed 27 of these AGNs using the EHT from 2022 to 2024, providing an opportunity to resolve and image accretion flows and jets at resolutions of $\leq$ 100 R$_{\rm g}$. Only a few SMBHs have sufficiently high enough flux density to be imaged at scales of $\leq$ 50 R$_{\rm g}$ with the present EHT. Among these are M87, Sgr A*, NGC4594 (Sombrero/M104), NGC4261, and NGC4374 (Messier 84/M84). Of these, NGC4261, Sombrero, and M84 have been observed and/or are scheduled for deep imaging with EHT+ALMA from 2023 to 2025. Sombrero, NGC4261, M84, NGC4278, and NGC5232 are clearly detected in our EHT+ALMA observations in 2022, indicating that the 230 GHz flux density from the accretion flows is significantly high. Ongoing imaging of the ETHER GS will enable measurements of black hole mass and spin, help constrain General Relativity, and enrich our understanding of jet launching and accretion inflows across a broad multi-parameter space, including black hole mass, spin, accretion rate, and orientation., Comment: 9 pages, 6 figures, 1 table, published in Proceedings of the 16th EVN Symposium, Ed. E. Ros, P. Benke, S.A. Dzib, I. Rottmann, & J.A. Zensus, Bonn: Max-Planck-Institut f\"ur Radioastronomie, 2024, pages 75-84, https://cloud.mpifr-bonn.mpg.de/index.php/s/BkX2CC2Xjn2aKR4

Recent gain in popularity of AI conversational agents has led to their increased use for improving productivity and supporting well-being. While previous research has aimed to understand the risks associated with interactions with AI conversational agents, these studies often fall short in capturing the lived experiences. Additionally, psychological risks have often been presented as a sub-category within broader AI-related risks in past taxonomy works, leading to under-representation of the impact of psychological risks of AI use. To address these challenges, our work presents a novel risk taxonomy focusing on psychological risks of using AI gathered through lived experience of individuals. We employed a mixed-method approach, involving a comprehensive survey with 283 individuals with lived mental health experience and workshops involving lived experience experts to develop a psychological risk taxonomy. Our taxonomy features 19 AI behaviors, 21 negative psychological impacts, and 15 contexts related to individuals. Additionally, we propose a novel multi-path vignette based framework for understanding the complex interplay between AI behaviors, psychological impacts, and individual user contexts. Finally, based on the feedback obtained from the workshop sessions, we present design recommendations for developing safer and more robust AI agents. Our work offers an in-depth understanding of the psychological risks associated with AI conversational agents and provides actionable recommendations for policymakers, researchers, and developers., Comment: 25 pages, 2 figures, 4 tables; Corrected typos

The probability distribution for vacuum fluctuations of the energy flux in two dimensions will be constructed, along with the joint distribution of energy flux and energy density. Our approach will be based on previous work on probability distributions for the energy density in two dimensional conformal field theory. In both cases, the relevant stress tensor component must be averaged in time, and the results are sensitive to the form of the averaging function. Here we present results for two classes of such functions, which include the Gaussian and Lorentzian functions. The distribution for the energy flux is symmetric, unlike that for the energy density. In both cases, the distribution may possess an integrable singularity. The functional form of the flux distribution function involves a modified Bessel function, and is distinct from the shifted Gamma form for the energy density. By considering the joint distribution of energy flux and energy density, we show that the distribution of energy flux tends to be more centrally concentrated than that of the energy density. We also determine the distribution of energy fluxes, conditioned on the energy density being negative. Some applications of the results will be discussed., Comment: 12 pages, 4 figures

The search for new quantum spin liquid materials relies on systems with strong frustration such as spins on the kagome lattice. This allows lattice imperfections to have substantial effects which are not well understood. In recent work the 2D kagome system YCu$_3$(OH)$_6$[(Cl$_x$Br$_{(1-x)}$)$_{3-y}$(OH)$_y$] has emerged as a leading candidate hosting a Dirac spin liquid which appears to survive at least for x<0.4, associated with alternating-bond hexagon (ABH) disorder. Here in samples with x=0.58 we report an unusual coexistence of anti-ferromagnetic (AFM) and ferromagnetic (FM) order, and propose a semi-microscopic model to account for this order. Combined with a phenomenological model the results suggest growth of large FM clusters at intermediate temperatures which order eventually at lower temperatures. Generating these FM clusters relies on two ingredients: ABH disorder, and local-AFM FM-canting generated by small Kitaev interactions which can arise on the kagome lattice. The combination of experimental observation and theory suggests that Kitaev interactions and ABH disorder are necessary for describing the magnetic fluctuations in this family of materials, with potential implications for the proposed proximate spin liquid phase., Comment: 8 pages 7 figures main text, 7 pages 4 figures supplementary material

We use the Monte Carlo For AGN (active galactic nucleus) Channel Testing and Simulation (McFACTS, https://www.github.com/mcfacts/mcfacts) code to study the effect of AGN disk and nuclear star cluster parameters on predicted mass distributions for LIGO-Virgo-KAGRA (LVK) compact binaries forming in AGN disks. The assumptions we vary include the black hole (BH) initial mass function, disk model, disk size, disk lifetime, and the prograde-to-retrograde fraction of newly formed black hole binaries. Broadly we find that dense, moderately short-lived AGN disks are preferred for producing a $(q,\chi_{\rm eff})$ anti-correlation like those identified from existing gravitational wave (GW) observations. Additionally, a BH initial mass function (MF $\propto M^{-2}$) is preferred over a more top-heavy MF ($M^{-1}$). The preferred fraction of prograde-to-retrograde is $>90\%$, to produce results consistent with observations., Comment: Submitted to ApJ, 18 pages, 9 figures, 2 tables

The Active Galactic Nuclei (AGN) channel for the formation of binary black hole (BBH) mergers has been previously studied as a potential formation channel for the merging compact binaries observed by the LIGO/Virgo/KAGRA (LVK) scientific collaboration. The first two papers in this series explored the McFACTS code for the evolution of black hole orbits in AGN accretion disks for individual galaxy models and described the characteristics of predicted BBH populations in realizations of those models (such as the correlation between mass ratio and aligned spin). In this work, we explore the impact of the properties of AGN host galaxies and assume an AGN lifetime and cosmological model for the density of AGN in a universe like our own. By sampling from an inferred population of AGN, we marginalize over galaxy mass to predict a population of BBH mergers observable by modern ground-based gravitational wave observatories. We find that for reasonable assumptions, AGN disk environments may account for massive BBH mergers such as GW190521 and GW190929_012149. We find that the majority of observable BBH mergers from our simulation are expected to originate in galaxies with a super-massive black hole between $10^{7}M_{\odot}$ and $10^{9.4}M_{\odot}$. We also find that if hierarchical mergers from AGN disks account for a substantial part of the LVK population, our current models require an AGN lifetime of 0.5 to 2.5 Myr., Comment: Submitting to ApJ

Quasars are bright active galactic nuclei powered by the accretion of matter around supermassive black holes at the center of galaxies. Their stochastic brightness variability depends on the physical properties of the accretion disk and black hole. The upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) is expected to observe tens of millions of quasars, so there is a need for efficient techniques like machine learning that can handle the large volume of data. Quasar variability is believed to be driven by an X-ray corona, which is reprocessed by the accretion disk and emitted as UV/optical variability. We are the first to introduce an auto-differentiable simulation of the accretion disk and reprocessing. We use the simulation as a direct component of our neural network to jointly model the driving variability and reprocessing to fit simulated LSST 10-year quasar light curves. The driving variability is reconstructed using a latent stochastic differential equation, a physically motivated, generative deep learning method that can model continuous-time stochastic dynamics. By embedding these physical processes into our network, we achieve a model that is more robust and interpretable. We also use transformers to scale our model to tens of millions of parameters. We demonstrate how our model outperforms a Gaussian process regression baseline and can infer accretion disk parameters and time delays between wavebands, even for out-of-distribution driving signals. Our approach provides a powerful and scalable framework that can be adapted to solve other inverse problems in multivariate time series with irregular sampling., Comment: 31 pages, 19 figures

The ability for optically active media to rotate the polarization of light is the basis of polarimetry, an illustrious technique responsible for many breakthroughs in fields as varied as astronomy, medicine and material science. Here, we recast the primary mechanism for spin readout in semiconductor-based quantum computers, Pauli spin-blockade (PSB), as the natural extension of polarimetry to the third dimension. We perform polarimetry with spins through a silicon quantum dot exchanging a hole with a boron acceptor, demonstrating the role of spin-orbit coupling in creating spin misalignment. Perfect spin alignment may be recovered by means of rotating the applied magnetic-field orientation. This work shows how spin misalignment sets a fundamental upper limit for the spin readout fidelity in quantum-computing systems based on PSB.

Active galactic nuclei (AGN) are a promising source of the binary black hole (BBH) mergers observed in gravitational waves with LIGO-Virgo-Kagra (LVK). Constraining the AGN channel allows us to limit AGN parameter space (disk density, size, average lifetime) and nuclear star cluster (NSC) parameter space. Constraints on AGN and NSCs have implications for $\Lambda$CDM models of AGN feedback and models of AGN-driven SMBH merger and growth. Here we present several qualitative studies of the AGN channel using new public, open-source, fast, reproducible code \texttt{McFACTS}\footnote{https://github.com/mcfacts}:Monte Carlo for AGN channel Testing \& Simulation. We demonstrate several important features for testing the AGN channel, including: i) growth to large mass IMBH is helped by the presence of migration traps or disk boundaries, ii) flat BH initial mass functions highlight hierarchical merger features in the mass spectrum, iii) high rates of dynamical encounters strongly inhibit BBH formation and merger at migration traps, iv) the ($q,\chi_{\rm eff}$) anti-correlation is a strong test of the bias to prograde mergers in the AGN channel, v) spheroid encounters can drive a fraction of mergers with high in-plane spin components ($\chi_{\rm p}$), vi) a high rate of extreme mass ratio inspirals (EMRIs) are driven by an initial population of embedded retrograde BH, vii) Both LVK and LISA are powerful probes of models of AGN disks and their embedded populations., Comment: 21 pages, 12 figures, 1 table, ApJ (submitted)

Monte Carlo (MC) simulations, particularly using FLUKA, are essential for replicating real-world scenarios across scientific and engineering fields. Despite the robustness and versatility, FLUKA faces significant limitations in automation and integration with external post-processing tools, leading to workflows with a steep learning curve, which are time-consuming and prone to human errors. Traditional methods involving the use of shell and Python scripts, MATLAB, and Microsoft Excel require extensive manual intervention and lack flexibility, adding complexity to evolving scenarios. This study explores the potential of Large Language Models (LLMs) and AI agents to address these limitations. AI agents, integrate natural language processing with autonomous reasoning for decision-making and adaptive planning, making them ideal for automation. We introduce AutoFLUKA, an AI agent application developed using the LangChain Python Framework to automate typical MC simulation workflows in FLUKA. AutoFLUKA can modify FLUKA input files, execute simulations, and efficiently process results for visualization, significantly reducing human labor and error. Our case studies demonstrate that AutoFLUKA can handle both generalized and domain-specific cases, such as Microdosimetry, with an streamlined automated workflow, showcasing its scalability and flexibility. The study also highlights the potential of Retrieval Augmentation Generation (RAG) tools to act as virtual assistants for FLUKA, further improving user experience, time and efficiency. In conclusion, AutoFLUKA represents a significant advancement in automating MC simulation workflows, offering a robust solution to the inherent limitations. This innovation not only saves time and resources but also opens new paradigms for research and development in high energy physics, medical physics, nuclear engineering space and environmental science., Comment: 58 pages including text, figures, references and appendices

Planning and performing interactive tasks, such as conducting experiments to determine the melting point of an unknown substance, is straightforward for humans but poses significant challenges for autonomous agents. We introduce ReasonPlanner, a novel generalist agent designed for reflective thinking, planning, and interactive reasoning. This agent leverages LLMs to plan hypothetical trajectories by building a World Model based on a Temporal Knowledge Graph. The agent interacts with the environment using a natural language actor-critic module, where the actor translates the imagined trajectory into a sequence of actionable steps, and the critic determines if replanning is necessary. ReasonPlanner significantly outperforms previous state-of-the-art prompting-based methods on the ScienceWorld benchmark by more than 1.8 times, while being more sample-efficient and interpretable. It relies solely on frozen weights thus requiring no gradient updates. ReasonPlanner can be deployed and utilized without specialized knowledge of Machine Learning, making it accessible to a wide range of users.

The High Energy Modular Array (HEMA) is one of three instruments that compose the STROBE-X mission concept. The HEMA is a large-area, high-throughput non-imaging pointed instrument based on the Large Area Detector developed as part of the LOFT mission concept. It is designed for spectral timing measurements of a broad range of sources and provides a transformative increase in sensitivity to X-rays in the energy range of 2--30 keV compared to previous instruments, with an effective area of 3.4 m$^{2}$ at 8.5 keV and an energy resolution of better than 300 eV at 6 keV in its nominal field of regard., Comment: 16 pages, 10 figures

We give an overview of the science objectives and mission design of the Spectroscopic Time-Resolving Observatory for Broadband Energy X-rays (STROBE-X) observatory, which has been proposed as a NASA probe-class (~$1.5B) mission in response to the Astro2020 recommendation for an X-ray probe., Comment: 11 pages, 5 figures, accepted for publication in JATIS

The first very long baseline interferometry (VLBI) detections at 870$\mu$m wavelength (345$\,$GHz frequency) are reported, achieving the highest diffraction-limited angular resolution yet obtained from the surface of the Earth, and the highest-frequency example of the VLBI technique to date. These include strong detections for multiple sources observed on inter-continental baselines between telescopes in Chile, Hawaii, and Spain, obtained during observations in October 2018. The longest-baseline detections approach 11$\,$G$\lambda$ corresponding to an angular resolution, or fringe spacing, of 19$\mu$as. The Allan deviation of the visibility phase at 870$\mu$m is comparable to that at 1.3$\,$mm on the relevant integration time scales between 2 and 100$\,$s. The detections confirm that the sensitivity and signal chain stability of stations in the Event Horizon Telescope (EHT) array are suitable for VLBI observations at 870$\mu$m. Operation at this short wavelength, combined with anticipated enhancements of the EHT, will lead to a unique high angular resolution instrument for black hole studies, capable of resolving the event horizons of supermassive black holes in both space and time., Comment: Corresponding author: S. Doeleman

Let $\delta(p)$ tend to zero arbitrarily slowly as $p\to\infty$. We exhibit an explicit set $\mathcal{S}$ of primes $p$, defined in terms of simple functions of the prime factors of $p-1$, for which the least primitive root of $p$ is $\le p^{1/4-\delta(p)}$ for all $p\in \mathcal{S}$, where $\#\{p\leq x: p\in \mathcal{S}\} \sim \pi(x)$ as $x\to\infty$.

Several heavy fermion materials, including UPt$_3$, exhibit a rapid but gradual rise in the magnetization at a critical field, without an apparent phase transition at any temperature $T>0$, with the possibility of a first order transition at $T \equiv0$. To model such a quantum phase transition it is most appropriate to develop approaches considering the quantum nature of the spins. Within a fully classical framework, we show that it is sufficient to start from a Landau-type free energy with an added Bragg-Williams entropy term to arrive at a number of key experimental features as seen in UPt$_3$. In particular, we show that correctly arriving at the measured (low-field) higher order susceptibilities necessarily invokes an isobestic (crossing) point at a high field in the magnetization isotherms. We also present a full analysis of the angular dependence of the (low-field) linear and nonlinear susceptibilities which when extended also capture the anisotropic high field response of the magnetization. Key to this success is the proper conversion of the evaluated magnetization from constant volume to a constant pressure situation relevant at high fields in heavy fermion materials., Comment: Main paper: 7 pages, 6 figures Supp info: 4 pages, 5 figures

HCI research to date has only scratched the surface of the unique approaches racially minoritized communities take to building, designing, and using technology systems. While there has been an increase in understanding how people across racial groups create community across different platforms, there is still a lack of studies that explicitly center on how Black technologists design with and for their own communities. In this paper, we present findings from a series of semi-structured interviews with Black technologists who have used, created, or curated resources to support lived Black experiences. From their experiences, we find a multifaceted approach to design as a means of survival, to stay connected, for cultural significance, and to bask in celebratory joy. Further, we provide considerations that emphasize the need for centering lived Black experiences in design and share approaches that can empower the broader research community to conduct further inquiries into design focused on those in the margins., Comment: 15 pages, 2 tables

Across domains, metrics and measurements are fundamental to identifying challenges, informing decisions, and resolving conflicts. Despite the abundance of data available in this information age, not only can it be challenging for a single expert to work across multi-disciplinary data, but non-experts can also find it unintuitive to create effective measures or transform theories into context-specific metrics that are chosen appropriately. This technical report addresses this challenge by examining software communities within large software corporations, where different measures are used as proxies to locate counterparts within the organization to transfer tacit knowledge. We propose a prompt-engineering framework inspired by neural activities, demonstrating that generative models can extract and summarize theories and perform basic reasoning, thereby transforming concepts into context-aware metrics to support software communities given software repository data. While this research zoomed in on software communities, we believe the framework's applicability extends across various fields, showcasing expert-theory-inspired metrics that aid in triaging complex challenges., Comment: 29 pages, 3 figures