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The permanent is a function, defined for a square matrix, with applications in various domains including quantum computing, statistical physics, complexity theory, combinatorics, and graph theory. Its formula is similar to that of the determinant, however unlike the determinant, its exact computation is #P-complete, i.e., there is no algorithm to compute the permanent in polynomial time unless P=NP. For an $n \times n$ matrix, the fastest algorithm has a time complexity of $O(2^{n-1}n)$. Although supercomputers have been employed for permanent computation before, there is no work and more importantly, no publicly available software that leverages cutting-edge, yet widely accessible, High-Performance Computing accelerators such as GPUs. In this work, we designed, developed, and investigated the performance of SUperman, a complete software suite that can compute matrix permanents on multiple nodes/GPUs on a cluster while handling various matrix types, e.g., real/complex/binary and sparse/dense etc., with a unique treatment for each type. Compared to a state-of-the-art parallel algorithm on 44 cores, SUperman can be $86\times$ faster on a single Nvidia A100 GPU. Combining multiple GPUs, we also showed that SUperman can compute the permanent of a $56 \times 56$ matrix which is the largest reported in the literature., Comment: 34 pages, 7 figures, 5 tables, 4 algorithms, 31 references

We report a new CO observation survey of LHAASO J0341$+$5258 using the Nobeyama Radio Observatory (NRO) 45-m telescope. LHAASO J0341$+$5258 is one of the unidentified ultra-high-energy (UHE; E $>$100 TeV) gamma-ray sources detected by LHAASO. Our CO observations were conducted in February and March 2024, with a total observation time of 36 hours, covering the LHAASO source ($\sim$0.3-0.5 degrees in radius) and its surrounding area (1$\times$1.5 degrees). Within the LHAASO source extent, we identified five compact ($<$ 2 pc) molecular clouds at nearby distances ($<$ 1-4 kpc). These clouds can serve as proton-proton collision targets, producing hadronic gamma rays via neutral pion decays. Based on the hydrogen densities (700-5000 cm$^{-3}$) estimated from our CO observations and archived HI data from the DRAO survey, we derived the total proton energy of $W_p$ (E $>$ 1 TeV) $\sim$ 10$^{45}$ erg to account for the gamma-ray flux. One of the molecular clouds appears to be likely associated with an asymptotic giant branch (AGB) star with an extended CO tail, which may indicate some particle acceleration activities. However, the estimated maximum particle energy below 100 TeV makes the AGB-like star unlikely to be a PeVatron site. We conclude that the UHE emission observed in LHAASO J0341$+$5258 could be due to hadronic interactions between the newly discovered molecular clouds and TeV-PeV protons originating from a distant SNR or due to leptonic emission from a pulsar wind nebula candidate, which is reported in our companion X-ray observation paper (DiKerby et al. 2025)., Comment: Accepted for publication in ApJ; 18 pages, 11 figures, and 4 tables

The astronomical origin of the most energetic galactic cosmic rays and gamma rays is still uncertain. X-ray followup of candidate "PeVatrons", systems producing cosmic rays with energies exceeding 1 PeV, can constrain their spatial origin, identify likely counterparts, and test particle emission models. Using 120 ks of XMM-Newton observations, we report the discovery of a candidate pulsar wind nebula, a possible counterpart for the LHAASO PeVatron J0343+5254u. This extended source has a power law X-ray spectrum with spectral index of 1.9 - softer at greater distance from the center - and asymmetric spatial extension out to 2'. We conduct leptonic modeling of the X-ray and gamma ray radiation from this complex system, showing that a fully leptonic model with elevated IR photon fields can explain the multiwavelength emission from this source, similar to other VHE pulsar wind nebulae; excess gamma ray emissivity not explained by a leptonic model may be due to hadronic interactions in nearby molecular cloud regions, which might also produce detectable astroparticle flux., Comment: 14 pages, 7 figures, 3 tables, accepted for publication in ApJ

We show that the null geodesic equation for photons is modified in the presence of a charged scalar field, with quantum fluctuations acting as an effective mass term that changes the null paths to timelike curves. This effect can be interpreted as a vacuum polarization phenomenon in curved spacetime. The resulting contribution to the Sachs-Wolfe effect varies with photon frequency, leading to frequency-dependent corrections to the cosmic microwave background (CMB) blackbody spectrum in the form of a $\mu$-distortion, as well as modifications to the CMB power spectrum. We estimate these within a standard inflationary scenario and find that while the correction to the CMB power spectrum is significant when the scalar field is light, the magnitude of the $\mu$-distortion depends strongly on the regularization prescription., Comment: 5 pages, revtex4

While the sources of the diffuse astrophysical neutrino flux detected by the IceCube Neutrino Observatory are still largely unknown, one of the promising methods used towards understanding this is investigating the potential temporal and spatial correlations between neutrino alerts and the electromagnetic radiation from blazars. We report on the multiwavelength target-of-opportunity observations of the blazar B3 2247+381, taken in response to an IceCube multiplet alert for a cluster of muon neutrino events compatible with the source location between May 20, 2022 and November 10, 2022. B3 2247+381 was not detected with VERITAS during this time period. The source was found to be in a low-flux state in the optical, ultraviolet and gamma-ray bands for the time interval corresponding to the neutrino event, but was detected in the hard X-ray band with NuSTAR during this period. We find the multiwavelength spectral energy distribution is well described using a simple one-zone leptonic synchrotron self-Compton radiation model. Moreover, assuming the neutrinos originate from hadronic processes within the jet, the neutrino flux would be accompanied by a photon flux from the cascade emission, and the integrated photon flux required in such a case would significantly exceed the total multiwavelength fluxes and the VERITAS upper limits presented here. The lack of flaring activity observed with VERITAS, combined with the low multiwavelength flux levels, and given the significance of the neutrino excess is at 3$\sigma$ level (uncorrected for trials), makes B3 2247+381 an unlikely source of the IceCube multiplet. We conclude that the neutrino excess is likely a background fluctuation., Comment: 26 pages, 5 figures. Accepted for publication in the Astrophysical Journal (ApJ)

We extend all known area inequalities obeyed by Ryu-Takayanagi surfaces of AdS boundary regions -- the holographic entropy cone -- to static generalized entanglement wedges of bulk regions in arbitrary spacetimes. The generalized holographic entropy cone is subject to a mutual independence condition on the bulk regions: each bulk input region must be outside the entanglement wedge of the union of all others. The condition captures when gravitating regions involve fundamentally distinct degrees of freedom despite the nonlocality inherent in the holographic principle.

Registers are the fastest memory components within the GPU's complex memory hierarchy, accessed by names rather than addresses. They are managed entirely by the compiler through a process called register allocation, during which the compiler attempts to cache predictable data from thread-local memory into thread-private registers. Computing the permanent of a sparse matrix poses a challenge for compilers, as optimizing this process is hindered by the unpredictable distribution of nonzero elements, which only become known at runtime. In this work, we employ fully-automated code generation to address this, producing highly optimized kernels tailored to the matrix's sparsity pattern. State-of-the-art permanent computation algorithms require each thread to store a private array, denoted x, of size n. We first propose a technique that fully stores these arrays in registers, with inclusion and exclusion kernels generated for each column. To minimize control divergence and reduce the number of unique kernels within a warp, we exploit the internal structure of Gray codes, which are also used in the state-of-the-art algorithm. Our second technique reduces register pressure by utilizing both registers and global memory and introduces a matrix ordering and partitioning strategy for greater efficiency. On synthetic matrices, this approach achieves a 31x speedup over state-of-the-art CPU implementations on 112 cores, and an 8x speedup compared to our traditional GPU implementation. For real-world matrices, these speedups are 24.9x and 4.9x.

Online synaptic plasticity rules derived from gradient descent achieve high accuracy on a wide range of practical tasks. However, their software implementation often requires tediously hand-derived gradients or using gradient backpropagation which sacrifices the online capability of the rules. In this work, we present a custom automatic differentiation (AD) pipeline for sparse and online implementation of gradient-based synaptic plasticity rules that generalizes to arbitrary neuron models. Our work combines the programming ease of backpropagation-type methods for forward AD while being memory-efficient. To achieve this, we exploit the advantageous compute and memory scaling of online synaptic plasticity by providing an inherently sparse implementation of AD where expensive tensor contractions are replaced with simple element-wise multiplications if the tensors are diagonal. Gradient-based synaptic plasticity rules such as eligibility propagation (e-prop) have exactly this property and thus profit immensely from this feature. We demonstrate the alignment of our gradients with respect to gradient backpropagation on an synthetic task where e-prop gradients are exact, as well as audio speech classification benchmarks. We demonstrate how memory utilization scales with network size without dependence on the sequence length, as expected from forward AD methods., Comment: 8 pages, 7 figures

Fossil fuels, which meet most of humanity's energy needs, cause climate change due to their high carbon emissions. There are two types of energy sources that can replace fossil fuels: renewable and nuclear. Nuclear energy sources are more advantageous in terms of efficiency and sustainability. The use of Thorium as nuclear fuel in fusion reactors will contribute to the reduction of radioactive waste, due to the much lower production of transuranics. Fusion reactors, which are considered promising, are still in the R&D phase. In this respect, hybrid fusion-fission reactors seem more promising and the recently proposed combination of muon-catalyzed DD fusion with a cascade thorium reactor is worthy of appreciation. In this study, we show that using the DD collider instead of muonic fusion has significant advantages., Comment: 7 pages, 3 figures, 3 tables

Diffusion models have demonstrated their utility as learned priors for solving various inverse problems. However, most existing approaches are limited to linear inverse problems. This paper exploits the efficient and unsupervised posterior sampling framework of Denoising Diffusion Restoration Models (DDRM) for the solution of nonlinear phase retrieval problem, which requires reconstructing an image from its noisy intensity-only measurements such as Fourier intensity. The approach combines the model-based alternating-projection methods with the DDRM to utilize pretrained unconditional diffusion priors for phase retrieval. The performance is demonstrated through both simulations and experimental data. Results demonstrate the potential of this approach for improving the alternating-projection methods as well as its limitations.

White dwarfs (WDs) are the most abundant compact objects, and recent surveys have suggested that over a third of WDs in accreting binaries host a strong (B $\gtrsim$ 1 MG) magnetic field. However, the origin and evolution of WD magnetism remain under debate. Two WD pulsars, AR Sco and J191213.72-441045.1 (J1912), have been found, which are non-accreting binaries hosting rapidly spinning (1.97-min and 5.30-min, respectively) magnetic WDs. The WD in AR Sco is slowing down on a $P/\dot{P}\approx 5.6\times 10^6$ yr timescale. It is believed they will eventually become polars, accreting systems in which a magnetic WD (B $\approx 10-240$ MG) accretes from a Roche lobe-filling donor spinning in sync with the orbit ($\gtrsim 78$ min). Here, we present multiwavelength data and analysis of Gaia22ayj, which outbursted in March 2022. We find that Gaia22ayj is a magnetic accreting WD that is rapidly spinning down ($P/\dot{P} = 6.1^{+0.3}_{-0.2}\times 10^6$ yr) like WD pulsars, but shows clear evidence of accretion, like polars. Strong linear polarization (40%) is detected in Gaia22ayj; such high levels have only been seen in the WD pulsar AR Sco and demonstrate the WD is magnetic. High speed photometry reveals a 9.36-min period accompanying a high amplitude ($\sim 2$ mag) modulation. We associate this with a WD spin or spin-orbit beat period, not an orbital period as was previously suggested. Fast (60-s) optical spectroscopy reveals a broad ``hump'', reminiscent of cyclotron emission in polars, between 4000-8000 Angstrom. We find an X-ray luminosity of $L_X = 2.7_{-0.8}^{+6.2}\times10^{32} \textrm{ erg s}^{-1}$ in the 0.3-8 keV energy range, while two VLA radio campaigns resulted in a non-detection with a $F_r < 15.8\mu\textrm{Jy}$ 3$ \sigma$ upper limit. The shared properties of both WD pulsars and polars suggest that Gaia22ayj is a missing link between the two classes of magnetic WD binaries., Comment: Submitted to PASP; comments welcome

In the rapidly evolving field of data science, efficiently navigating the expansive body of academic literature is crucial for informed decision-making and innovation. This paper presents an enhanced Retrieval-Augmented Generation (RAG) application, an artificial intelligence (AI)-based system designed to assist data scientists in accessing precise and contextually relevant academic resources. The AI-powered application integrates advanced techniques, including the GeneRation Of BIbliographic Data (GROBID) technique for extracting bibliographic information, fine-tuned embedding models, semantic chunking, and an abstract-first retrieval method, to significantly improve the relevance and accuracy of the retrieved information. This implementation of AI specifically addresses the challenge of academic literature navigation. A comprehensive evaluation using the Retrieval-Augmented Generation Assessment System (RAGAS) framework demonstrates substantial improvements in key metrics, particularly Context Relevance, underscoring the system's effectiveness in reducing information overload and enhancing decision-making processes. Our findings highlight the potential of this enhanced Retrieval-Augmented Generation system to transform academic exploration within data science, ultimately advancing the workflow of research and innovation in the field.

We present the first $\textit{NuSTAR}$ X-ray observation of EF Eri, a well-known polar system. The $\textit{NuSTAR}$ observation was conducted in conjunction with $\textit{NICER}$, shortly after EF Eri entered a high accretion state following an unprecedented period of low activity lasting 26 years since 1997. $\textit{NuSTAR}$ detected hard X-ray emission up to 50 keV with an X-ray flux of $1.2\times10^{-10}$ ergs s$^{-1}$ cm$^{-2}$ ($3\rm{-}50 keV$). Folded X-ray lightcurves exhibit a single peak with $\sim65\%$ spin modulation throughout the $3\rm{-}50$ keV band. We found no evidence of QPO signals at $\nu = 0.1\rm{-}100$ Hz with an upper limit on the QPO amplitude below $5\%$ ($90\%$ CL) at $\nu \sim 0.5$ Hz where the optical QPO was previously detected. Our 1-D accretion column model, called ${\tt MCVSPEC}$, was fitted to the $\textit{NuSTAR}$ spectral data, yielding an accurate WD mass measurement of $M = (0.55\rm{-}0.58) M_\odot$. $\texttt{MCVSPEC}$ accounts for radiative cooling by thermal bremsstrahlung and cyclotron emission, X-ray reflection off the WD surface, and a previously constrained range of the accretion column area. The derived WD mass range is in excellent agreement with the previous measurement of $M = (0.55\rm{-}0.60) M_\odot$ in the optical band. This demonstrates a combination of broadband X-ray spectral analysis and the ${\tt MCVSPEC}$ model that can be employed in our ongoing $\textit{NuSTAR}$ observation campaign of other polars to determine their WD masses accurately., Comment: 17 pages, 10 figures, 3 tables. Submitted to ApJ

A recent report on the detection of very-high-energy gamma rays from V4641 Sagittarii (V4641 Sgr) up to ~0.8 peta-electronvolt has made it the second confirmed "PeVatron" microquasar. Here we report on the observation of V4641 Sgr with X-Ray Imaging and Spectroscopy Mission (XRISM) in September 2024. Thanks to the large field of view and low background, the CCD imager Xtend successfully detected for the first time X-ray extended emission around V4641 Sgr with a significance of > 4.5 sigma and > 10 sigma based on our imaging and spectral analysis, respectively. The spatial extent is estimated to have a radius of $7 \pm 3$ arcmin ($13 \pm 5$ pc at a distance of 6.2 kpc) assuming a Gaussian-like radial distribution, which suggests that the particle acceleration site is within ~10 pc of the microquasar. If the X-ray morphology traces the diffusion of accelerated electrons, this spatial extent can be explained by either an enhanced magnetic field (~80 uG) or a suppressed diffusion coefficient (~$10^{27}$ cm$^2$ s$^{-1}$ at 100 TeV). The integrated X-ray flux, (4-6)$\times 10^{-12}$ erg s$^{-1}$ cm$^{-2}$ (2-10 keV), would require a magnetic field strength higher than the galactic mean (> 8 uG) if the diffuse X-ray emission originates from synchrotron radiation and the gamma-ray emission is predominantly hadronic. If the X-rays are of thermal origin, the measured extension, temperature, and plasma density can be explained by a jet with a luminosity of ~$2\times 10^{39}$ erg s$^{-1}$, which is comparable to the Eddington luminosity of this system., Comment: 9 pages, 5 figures, accepted for publication in ApJL

We present a spectrally accurate, automatically differentiable bounce-averaging operator implemented in the DESC stellarator optimization suite. Using this operator, we can perform efficient optimization of many objectives to improve stellarator performance, such as the $\epsilon_{\mathrm{eff}}^{3/2}$ proxy for the neoclassical transport coefficient in the $1/\nu$ regime. By employing this differentiable approximation, for the first time, we directly optimize a finite-$\beta$ stellarator to reduce neoclassical transport using reverse-mode differentiation, ensuring that the computational cost of determining the gradients is independent of the number of input parameters.

The corrosion of metallic surfaces poses significant challenges across industries such as petroleum, energy, and biomedical sectors, leading to structural degradation, safety risks, and substantial maintenance costs. Traditional organic and metallic coatings provide some protection, but their limited durability and susceptibility to harsh environmental conditions necessitate the development of more advanced and efficient solutions. This has driven significant interest in two-dimensional (2D) materials, with graphene extensively studied for its exceptional mechanical strength and impermeability to gases and ions. However, while graphene offers short-term corrosion protection, its high electrical conductivity presents a long-term issue by promoting galvanic corrosion on metal surfaces. In contrast, hexagonal boron nitride (h-BN) has emerged as a promising alternative for anticorrosion coatings. h-BN combines exceptional chemical stability, impermeability, and electrical insulation, making it particularly suited for long-term protection in highly corrosive or high-temperature environments. While h-BN holds promise as anticorrosion material, challenges such as structural defects, agglomeration of nanosheets, and poor dispersion within coatings limit its performance. This review provides a comprehensive analysis of recent advancements in addressing these challenges, including novel functionalization strategies, scalable synthesis methods, and hybrid systems that integrate h-BN with complementary materials. By bridging the gap between fundamental research and industrial applications, this review outlines the potential for h-BN to revolutionize anticorrosion technologies. These obstacles necessitate advanced strategies such as surface functionalization to improve compatibility with polymer matrices and dispersion optimization to minimize agglomeration., Comment: 28 pages, 3 figures

Spacelike intrinsic rotational surfaces with constant mean curvature in the Lorentz-Minkowski space $\E_1^3$ have been recently investigated by Brander et al., extending the known Smyth's surfaces in Euclidean space. Assuming that the surface is intrinsic rotational with coordinates $(u,v)$ and conformal factor $\rho(u)^2$, we replace the constancy of the mean curvature with the property that the Weingarten endomorphism $A$ can be expressed as $\Phi_{-\alpha(v)}\left(\begin{array}{ll}\lambda_1(u)&0\\ 0&\lambda_2(u)\end{array}\right)\Phi_{\alpha(v)}$, where $\Phi_{\alpha(v)}$ is the (Euclidean or hyperbolic) rotation of angle $\alpha(v)$ at each tangent plane and $\lambda_i$ are the principal curvatures. Under these conditions, it is proved that the mean curvature is constant and $\alpha$ is a linear function. This result also covers the case that the surface is timelike. If the mean curvature is zero, we determine all spacelike and timelike intrinsic rotational surfaces with rotational angle $\alpha$. This family of surfaces includes the spacelike and timelike Enneper surfaces., Comment: 28 pages, 3 figures. Accepted to publish in Hacettepe Journal of Mathematics and Statistics

In multi-state models based on high-dimensional data, effective modeling strategies are required to determine an optimal, ideally parsimonious model. In particular, linking covariate effects across transitions is needed to conduct joint variable selection. A useful technique to reduce model complexity is to address homogeneous covariate effects for distinct transitions. We integrate this approach to data-driven variable selection by extended regularization methods within multi-state model building. We propose the fused sparse-group lasso (FSGL) penalized Cox-type regression in the framework of multi-state models combining the penalization concepts of pairwise differences of covariate effects along with transition grouping. For optimization, we adapt the alternating direction method of multipliers (ADMM) algorithm to transition-specific hazards regression in the multi-state setting. In a simulation study and application to acute myeloid leukemia (AML) data, we evaluate the algorithm's ability to select a sparse model incorporating relevant transition-specific effects and similar cross-transition effects. We investigate settings in which the combined penalty is beneficial compared to global lasso regularization.

Recently, a class of long-period radio transients (LPTs) has been discovered, exhibiting emission on timescales thousands of times longer than radio pulsars. Several models had been proposed implicating either a strong magnetic field neutron star, isolated white dwarf pulsar, or a white dwarf binary system with a low-mass companion. While several models for LPTs also predict X-ray emission, no LPTs have been detected in X-rays despite extensive searches. Here we report the discovery of an extremely bright LPT (10-20 Jy in radio), ASKAP J1832-0911, which has coincident radio and X-ray emission, both with a 44.2-minute period. The X-ray and radio luminosities are correlated and vary by several orders of magnitude. These properties are unique amongst known Galactic objects and require a new explanation. We consider a $\gtrsim0.5$ Myr old magnetar with a $\gtrsim 10^{13}$ G crustal field, or an extremely magnetised white dwarf in a binary system with a dwarf companion, to be plausible explanations for ASKAP J1832-0911, although both explanations pose significant challenges to formation and emission theories. The X-ray detection also establishes a new class of hour-scale periodic X-ray transients of luminosity $\sim10^{33}$ erg/s associated with exceptionally bright coherent radio emission., Comment: 52 pages, 17 figures, 3 tables

We present a detailed X-ray investigation of a region (S1) exhibiting non-thermal X-ray emission within the supernova remnant (SNR) CTB 37B hosting the magnetar CXOU J171405.7$-$381031. Previous analyses modeled this emission with a power law (PL), inferring various values for the photon index ($\Gamma$) and absorbing column density ($N_{\rm H}$). Based on these, S1 was suggested to be the SNR shell, a background pulsar wind nebula (PWN), or an interaction region between the SNR and a molecular cloud. Our analysis of a larger dataset favors a steepening (broken or curved PL) spectrum over a straight PL, with the best-fit broken power-law (BPL) parameters of $\Gamma=1.23\pm0.23$ and $2.24\pm0.16$ below and above a break at $5.57\pm0.52$ keV, respectively. However, a simple PL or srcut model cannot be definitively ruled out. For the BPL model, the inferred $N_{\rm H}=(4.08\pm0.72)\times 10^{22}\rm \ cm^{-2}$ towards S1 is consistent with that of the SNR, suggesting a physical association. The BPL-inferred spectral break $\Delta \Gamma \approx 1$ and hard $\Gamma$ can be naturally explained by a non-thermal bremsstrahlung (NTB) model. We present an evolutionary NTB model that reproduces the observed spectrum, which indicates the presence of sub-relativistic electrons within S1. However, alternate explanations for S1, an unrelated PWN or the SNR shock with unusually efficient acceleration, cannot be ruled out. We discuss these explanations and their implications for gamma-ray emission from CTB 37B, and describe future observations that could settle the origin of S1., Comment: 11 pages. 4 figures, Accepted for publication in Apj

We develop a new theoretical scheme for charge transport and thermoelectric response in two-dimensional disordered systems exhibiting crossover from weak localization (WL) to strong localization (SL). The scheme is based on the scaling theory for Anderson localization combined with the Kubo-Luttinger theory. Key aspects of the scheme include introducing a unified $\beta$ function that seamlessly connects the WL and SL regimes, as well as describing the temperature ($T$) dependence of the conductance from high to low $T$ regions on the basis of the dephasing length. We found that the Seebeck coefficient, $S$, behaves as $S\propto T$ in the WL limit and as $S\propto T^{1-p}$ ($p < 1$) in the SL limit, both with possible logarithmic corrections. The scheme is applied to analyze experimental data for thin films of the p-type organic semiconductor poly[2,5-bis(3-alkylthiophen-2-yl)thieno(3,2-b)thiophene] (PBTTT)., Comment: 6 pages, 2 figures

Young supernova remnants (SNRs) are believed to be the origin of energetic cosmic rays (CRs) below the "knee" of their spectrum at $\sim3$ petaelectronvolt (PeV, $10^{15}$ eV). Nevertheless, the precise location, duration, and operation of CR acceleration in young SNRs are open questions. Here, we report on multi-epoch X-ray observations of Cassiopeia A (Cas A), a 350-year-old SNR, in the 15-50 keV band that probes the most energetic CR electrons. The observed X-ray flux decrease $(15\pm1\%)$, contrary to the expected $>$90\% decrease based on previous radio, X-ray, and gamma-ray observations, provides unambiguous evidence for CR electron acceleration operating in Cas A. A temporal model for the radio and X-ray data accounting for electron cooling and continuous injection finds that the freshly injected electron spectrum is significantly harder (exponential cutoff power law index $q=2.15$), and its cutoff energy is much higher ($E_{cut}=36$ TeV) than the relic electron spectrum ($q=2.44\pm0.03$, $E_{cut}=4\pm1$ TeV). Both electron spectra are naturally explained by the recently developed modified nonlinear diffusive shock acceleration (mNLDSA) mechanism. The CR protons producing the observed gamma rays are likely accelerated at the same location by the same mechanism as those for the injected electron. The Cas A observations and spectral modeling represent the first time radio, X-ray, gamma ray and CR spectra have been self-consistently tied to a specific acceleration mechanism -- mNLDSA -- in a young SNR., Comment: Accepted for publication in ApJ. 14 pages, 4 figures, 2 tables

Spanning Centrality is a measure used in network analysis to determine the importance of an edge in a graph based on its contribution to the connectivity of the entire network. Specifically, it quantifies how critical an edge is in terms of the number of spanning trees that include that edge. The current state-of-the-art for All Edges Spanning Centrality~(AESC), which computes the exact centrality values for all the edges, has a time complexity of $\mathcal{O}(mn^{3/2})$ for $n$ vertices and $m$ edges. This makes the computation infeasible even for moderately sized graphs. Instead, there exist approximation algorithms which process a large number of random walks to estimate edge centralities. However, even the approximation algorithms can be computationally overwhelming, especially if the approximation error bound is small. In this work, we propose a novel, hash-based sampling method and a vectorized algorithm which greatly improves the execution time by clustering random walks into {\it Bouquets}. On synthetic random walk benchmarks, {\it Bouquets} performs $7.8\times$ faster compared to naive, traditional random-walk generation. We also show that the proposed technique is scalable by employing it within a state-of-the-art AESC approximation algorithm, {\sc TGT+}. The experiments show that using Bouquets yields more than $100\times$ speed-up via parallelization with 16 threads.

Influence Maximization (IM) aims to find a given number of "seed" vertices that can effectively maximize the expected spread under a given diffusion model. Due to the NP-Hardness of finding an optimal seed set, approximation algorithms are often used for IM. However, these algorithms require a large number of simulations to find good seed sets. In this work, we propose DiFuseR, a blazing-fast, high-quality IM algorithm that can run on multiple GPUs in a distributed setting. DiFuseR is designed to increase GPU utilization, reduce inter-node communication, and minimize overlapping data/computation among the nodes. Based on the experiments with various graphs, containing some of the largest networks available, and diffusion settings, the proposed approach is found to be 3.2x and 12x faster on average on a single GPU and 8 GPUs, respectively. It can achieve up to 8x and 233.7x speedup on the same hardware settings. Furthermore, thanks to its smart load-balancing mechanism, on 8 GPUs, it is on average 5.6x faster compared to its single-GPU performance.

To build an economically viable stellarator, it is essential to find a configuration that satisfies a set of favorable properties to achieve efficient steady-state nuclear fusion. One such property is omnigenity, which ensures confinement of trapped particles. After creating an omnigenous equilibrium, one must also ensure reduced transport resulting from kinetic and magnetohydrodynamic (MHD) instabilities. This study introduces and leverages the GPU-accelerated DESC optimization suite, which is used to design stable high-$\beta$ omnigenous equilibria, achieving Mercier, ideal ballooning, and enhanced kinetic ballooning stability. We explain the link between ideal and kinetic ballooning modes and discover stellarators with second stability, a regime of large pressure gradient where an equilibria becomes ideal ballooning stable., Comment: Supplementary material appended after the appendix. 33 pages + 10 pages supplementary material, 13 figures, 4 tables

The ability to plan a course of action that achieves a desired state of affairs has long been considered a core competence of intelligent agents and has been an integral part of AI research since its inception. With the advent of large language models (LLMs), there has been considerable interest in the question of whether or not they possess such planning abilities, but -- despite the slew of new private and open source LLMs since GPT3 -- progress has remained slow. OpenAI claims that their recent o1 (Strawberry) model has been specifically constructed and trained to escape the normal limitations of autoregressive LLMs -- making it a new kind of model: a Large Reasoning Model (LRM). In this paper, we evaluate the planning capabilities of two LRMs (o1-preview and o1-mini) on both planning and scheduling benchmarks. We see that while o1 does seem to offer significant improvements over autoregressive LLMs, this comes at a steep inference cost, while still failing to provide any guarantees over what it generates. We also show that combining o1 models with external verifiers -- in a so-called LRM-Modulo system -- guarantees the correctness of the combined system's output while further improving performance., Comment: arXiv admin note: text overlap with arXiv:2409.13373