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The progenitor system(s) as well as the explosion mechanism(s) of thermonuclear (Type Ia) supernovae are long-standing issues in astrophysics. Here we present ejecta masses and other physical parameters for 28 recent Type Ia supernovae inferred from multiband photometric and optical spectroscopic data. Our results confirm that the majority of SNe Ia show {\it observable} ejecta masses below the Chandrasekhar-limit (having a mean $M_{\rm ej} \approx 1.1 \pm 0.3$ M$_\odot$), consistent with the predictions of recent sub-M$_{\rm Ch}$ explosion models. They are compatible with models assuming either single- or double-degenerate progenitor configurations. We also recover a sub-sample of supernovae within $1.2 $ M$_\odot$ $< M_{\rm {ej}} < 1.5$ M$_\odot$ that are consistent with near-Chandrasekhar explosions. Taking into account the uncertainties of the inferred ejecta masses, about half of our SNe are compatible with both explosion models. We compare our results with those in previous studies, and discuss the caveats and concerns regarding the applied methodology.

Single Source Shortest Paths ($\textrm{SSSP}$) is among the most well-studied problems in computer science. In the incremental (resp. decremental) setting, the goal is to maintain distances from a fixed source in a graph undergoing edge insertions (resp. deletions). A long line of research culminated in a near-optimal deterministic $(1 + \varepsilon)$-approximate data structure with $m^{1 + o(1)}$ total update time over all $m$ updates by Bernstein, Probst Gutenberg and Saranurak [FOCS 2021]. However, there has been remarkably little progress on the exact $\textrm{SSSP}$ problem beyond Even and Shiloach's algorithm [J. ACM 1981] for unweighted graphs. For weighted graphs, there are no exact algorithms beyond recomputing $\textrm{SSSP}$ from scratch in $\widetilde{O}(m^2)$ total update time, even for the simpler Single-Source Single-Target Shortest Path problem ($\textrm{stSP}$). Despite this lack of progress, known (conditional) lower bounds only rule out algorithms with amortized update time better than $m^{1/2 - o(1)}$ in dense graphs. In this paper, we give a tight (conditional) lower bound: any partially dynamic exact $\textrm{stSP}$ algorithm requires $m^{2 - o(1)}$ total update time for any sparsity $m$. We thus resolve the complexity of partially dynamic shortest paths, and separate the hardness of exact and approximate shortest paths, giving evidence as to why no non-trivial exact algorithms have been obtained while fast approximation algorithms are known. Moreover, we give tight bounds on the complexity of combinatorial algorithms for several path problems that have been studied in the static setting since early sixties: Node-weighted shortest paths (studied alongside edge-weighted shortest paths), bottleneck paths (early work dates back to 1960), and earliest arrivals (early work dates back to 1958)., Comment: 54 pages, 4 figures, abstract shortened to meet arXiv requirements

We consider the probabilistic generation of time-bin photon number states from a train of single photon pulses. We propose a simple interferometric feedback loop setup having a beam splitter and a possibly non-idel detector. This Hong-Ou-Mandel type scheme implements iterated photon additions. Our detailed study shows that up to 4 photons this simple setup can provide reasonable success probabilities and fidelities.

Bandits with preference feedback present a powerful tool for optimizing unknown target functions when only pairwise comparisons are allowed instead of direct value queries. This model allows for incorporating human feedback into online inference and optimization and has been employed in systems for fine-tuning large language models. The problem is well understood in simplified settings with linear target functions or over finite small domains that limit practical interest. Taking the next step, we consider infinite domains and nonlinear (kernelized) rewards. In this setting, selecting a pair of actions is quite challenging and requires balancing exploration and exploitation at two levels: within the pair, and along the iterations of the algorithm. We propose MAXMINLCB, which emulates this trade-off as a zero-sum Stackelberg game, and chooses action pairs that are informative and yield favorable rewards. MAXMINLCB consistently outperforms existing algorithms and satisfies an anytime-valid rate-optimal regret guarantee. This is due to our novel preference-based confidence sequences for kernelized logistic estimators., Comment: 30 pages, 8 figures

In various applications, the optimal policy in a strategic decision-making problem depends both on the environmental configuration and exogenous events. For these settings, we introduce Bilevel Optimization with Contextual Markov Decision Processes (BO-CMDP), a stochastic bilevel decision-making model, where the lower level consists of solving a contextual Markov Decision Process (CMDP). BO-CMDP can be viewed as a Stackelberg Game where the leader and a random context beyond the leader's control together decide the setup of (many) MDPs that (potentially multiple) followers best respond to. This framework extends beyond traditional bilevel optimization and finds relevance in diverse fields such as model design for MDPs, tax design, reward shaping and dynamic mechanism design. We propose a stochastic Hyper Policy Gradient Descent (HPGD) algorithm to solve BO-CMDP, and demonstrate its convergence. Notably, HPGD only utilizes observations of the followers' trajectories. Therefore, it allows followers to use any training procedure and the leader to be agnostic of the specific algorithm used, which aligns with various real-world scenarios. We further consider the setting when the leader can influence the training of followers and propose an accelerated algorithm. We empirically demonstrate the performance of our algorithm., Comment: 54 pages, 18 Figures

We estimate the fluxes of heat and antineutrinos due to primordial radioactivity within the moon. We use a radial density profile, specifying an inner core and a model-averaged crust. Thickness, density, and elevation of the lunar crust are from remote measurements of the gravitational field. Lateral and vertical variations of thorium, uranium, and potassium abundances in the crust follow from a prediction of the lunar bulk chemical composition. We constrain the total contents of thorium, uranium, and potassium using estimates for the earth's primitive mantle. These contents produce $311\pm37$ GW of radiogenic heating and a surface-averaged heat flux of $8.19\pm0.97$ mW/m$^2$. Our lunar model estimates an antineutrino flux of $(1.83\pm0.32)\times10^6$ cm$^{-2}$s$^{-1}$ and an antineutrino inverse beta decay rate of $5.8\pm1.0$ per $10^{32}$ free proton targets per year, both averaged over the surface., Comment: 5 pages, 6 figures

During the first half of the fourth observing run (O4a) of the International Gravitational Wave Network (IGWN), the Zwicky Transient Facility (ZTF) conducted a systematic search for kilonova (KN) counterparts to binary neutron star (BNS) and neutron star-black hole (NSBH) merger candidates. Here, we present a comprehensive study of the five high-significance (FAR < 1 per year) BNS and NSBH candidates in O4a. Our follow-up campaigns relied on both target-of-opportunity observations (ToO) and re-weighting of the nominal survey schedule to maximize coverage. We describe the toolkit we have been developing, Fritz, an instance of SkyPortal, instrumental in coordinating and managing our telescope scheduling, candidate vetting, and follow-up observations through a user-friendly interface. ZTF covered a total of 2841 deg$^2$ within the skymaps of the high-significance GW events, reaching a median depth of g~20.2 mag. We circulated 15 candidates, but found no viable KN counterpart to any of the GW events. Based on the ZTF non-detections of the high-significance events in O4a, we used a Bayesian approach, nimbus, to quantify the posterior probability of KN model parameters that are consistent with our non-detections. Our analysis favors KNe with initial absolute magnitude fainter than -16 mag. The joint posterior probability of a GW170817-like KN associated with all our O4a follow-ups was 64%. Additionally, we use a survey simulation software, simsurvey, to determine that our combined filtered efficiency to detect a GW170817-like KN is 36%, when considering the 5 confirmed astrophysical events in O3 (1 BNS and 4 NSBH), along with our O4a follow-ups. Following Kasliwal et al. (2020), we derived joint constraints on the underlying KN luminosity function based on our O3 and O4a follow-ups, determining that no more than 76% of KNe fading at 1 mag/day can peak at a magnitude brighter than -17.5 mag., Comment: submitted

The plastic deformation of crystalline and other heterogeneous materials often manifests in stochastic intermittent events indicating the criticality of plastic behavior. Previous studies demonstrated that the presence of short-ranged quenched disorder modifies this behavior disrupting long-range static and dynamic correlations consequently localizing dislocation avalanches. However, these observations were mostly confined to relaxed materials devoid of deformation history. In this work our focus is on how straining affects static and dynamic correlations, avalanche dynamics and local yield stresses. We demonstrate that the interplay between severe straining and confining quenched disorder induces critical behavior characterized by dislocation avalanches distinct from those at lower stresses. Namely, near the flow stress many avalanches, even if triggered locally, evolve into events affecting a larger region by exciting small clusters of dislocations all around the sample. This type of avalanches differ from the ones at low strains where plastic events typically consist of one compact cluster of dislocations which is either local or it is already quite extended at the onset of the avalanche. Furthermore, we examine the impact of avalanches on local yield stresses. It is shown in detail in this work that while some statistical features of the local yield thresholds are robust to straining, others are significantly affected by the deformation history.

The identification of extragalactic fast optical transients (eFOTs) as potential multi-messenger sources is one of the main challenges in time-domain astronomy. However, recent developments have allowed for probes of rapidly-evolving transients. With the increasing number of alert streams from optical time-domain surveys, the next paradigm is building technologies to rapidly identify the most interesting transients for follow-up. One effort to make this possible is the fitting of objects to a variety of eFOT lightcurve models such as kilonovae and $\gamma$-ray burst (GRB) afterglows. In this work, we describe a new framework designed to efficiently fit transients to light curve models and flag them for further follow-up. We describe the pipeline's workflow and a handful of performance metrics, including the nominal sampling time for each model. We highlight as examples ZTF20abwysqy, the shortest long gamma ray burst discovered to date, and ZTF21abotose, a core-collapse supernova initially identified as a potential kilonova candidate., Comment: Accepted to MNRAS, 11 pages, 9 figures

The exact value of the separating Noether number of an arbitrary finite abelian group of rank two is determined. This is done by a detailed study of the monoid of zero-sum sequences over the group., Comment: 12 pages

This paper characterizes the microdosimetric spectra of a single-energy carbon-ion pencil beam at MedAustron using a miniature solid-state silicon microdosimeter to estimate the impact of the lateral distribution of the different fragments on the microdosimetric spectra. The microdosimeter was fixed at one depth and then laterally moved away from the central beam axis in steps of approximately 2 mm. The measurements were taken in both horizontal and vertical direction in a water phantom at different depths. In a position on the distal dose fall-off beyond the Bragg peak, the frequency-mean and the dose-mean lineal energies were derived using either the entire range of y-values, or a sub-range of y values, presumingly corresponding mainly to contributions from primary particles. The measured microdosimetric spectra do not exhibit a significant change up to 4 mm away from the beam central axis. For lateral positions more than 4 mm away from the central axis, the relative contribution of the lower lineal-energy part of the spectrum increases with lateral distance due to the increased partial dose from secondary fragments. The average values yF and yD are almost constant for each partial contribution. However, when all particles are considered together, the average value of yF and yD varies with distance from the axis due to the changing dose fractions of these two components varying by 30 % and 10 % respectively up to the most off axis vertical position. Characteristic features in the microdosimetric spectra providing strong indications of the presence of helium and boron fragments have been observed downstream of the distal part of the Bragg peak. We were able to investigate the radiation quality as function of off-axis position. These measurements emphasize variation of the radiation quality within the beam and this has implications in terms of relative biological effectiveness., Comment: 19 pages, 9 figures

The dineutron as a bound chargeless nucleus of two identical nucleons has been attracting attention for many decades. In addition to the study of the formation of a bound dineutron in the outgoing channel of some specific nuclear reactions, cross section estimates have been gaining interest as research target. We used a traditional neutron activation technique to irradiate Lu samples followed by measurements of the induced activity with HPGe spectrometer in order to detect gamma-peaks of the ${}^{175}Lu (n, 2n)^{174g}Lu$ reaction product when this reaction channel is not open for incident neutron energies. Based on two measurements of the instrumental gamma ray spectra of Lu samples we reliably identified the presence of the ${}^{174g}Lu$ isotope in the outgoing channel of the ${}^{175}Lu(n, {}^2n)^{174g}Lu$ nuclear reaction. Also, the cross section for this nuclear reaction was obtained and to be equal $33.5 \pm 5.9$ mb. For the first time, the dineutron as a nuclear reaction product was indirectly detected via statistically significant observation of the induced activity of ${}^{174g}Lu$ with corresponding cross-section estimate., Comment: 6 pages, 3 figures, 1 tables

Self-attention is at the heart of the popular Transformer architecture, yet suffers from quadratic time and memory complexity. The breakthrough FlashAttention algorithm revealed I/O complexity as the true bottleneck in scaling Transformers. Given two levels of memory hierarchy, a fast cache (e.g. GPU on-chip SRAM) and a slow memory (e.g. GPU high-bandwidth memory), the I/O complexity measures the number of accesses to memory. FlashAttention computes attention using $\frac{N^2d^2}{M}$ I/O operations where $N$ is the dimension of the attention matrix, $d$ the head-dimension and $M$ the cache size. However, is this I/O complexity optimal? The known lower bound only rules out an I/O complexity of $o(Nd)$ when $M=\Theta(Nd)$, since the output that needs to be written to slow memory is $\Omega(Nd)$. This leads to the main question of our work: Is FlashAttention I/O optimal for all values of $M$? We resolve the above question in its full generality by showing an I/O complexity lower bound that matches the upper bound provided by FlashAttention for any values of $M \geq d^2$ within any constant factors. Further, we give a better algorithm with lower I/O complexity for $M < d^2$, and show that it is optimal as well. Moreover, our lower bounds do not rely on using combinatorial matrix multiplication for computing the attention matrix. We show even if one uses fast matrix multiplication, the above I/O complexity bounds cannot be improved. We do so by introducing a new communication complexity protocol for matrix compression, and connecting communication complexity to I/O complexity. To the best of our knowledge, this is the first work to establish a connection between communication complexity and I/O complexity, and we believe this connection could be of independent interest and will find many more applications in proving I/O complexity lower bounds in the future., Comment: 24 pages, 3 figures

Deep Learning has been successfully applied to many application domains, yet its advantages have been slow to emerge for time series forecasting. For example, in the well-known Makridakis (M) Competitions, hybrids of traditional statistical or machine learning techniques have only recently become the top performers. With the recent architectural advances in deep learning being applied to time series forecasting (e.g., encoder-decoders with attention, transformers, and graph neural networks), deep learning has begun to show significant advantages. Still, in the area of pandemic prediction, there remain challenges for deep learning models: the time series is not long enough for effective training, unawareness of accumulated scientific knowledge, and interpretability of the model. To this end, the development of foundation models (large deep learning models with extensive pre-training) allows models to understand patterns and acquire knowledge that can be applied to new related problems before extensive training data becomes available. Furthermore, there is a vast amount of knowledge available that deep learning models can tap into, including Knowledge Graphs and Large Language Models fine-tuned with scientific domain knowledge. There is ongoing research examining how to utilize or inject such knowledge into deep learning models. In this survey, several state-of-the-art modeling techniques are reviewed, and suggestions for further work are provided.

The nearby spiral galaxy NGC 3147 hosted three Type Ia supernovae (SNe Ia) in the past decades, which have been subjects of intense follow-up observations. Simultaneous analysis of their data provides a unique opportunity for testing the different light curve fitting methods and distance estimations. The detailed optical follow-up of SN 2021hpr allows us to revise the previous distance estimations to NGC 3147, and compare the widely used light curve fitting algorithms to each other. After the combination of the available and newly published data of SN 2021hpr, its physical properties can be also estimated with higher accuracy. We present and analyse new BVgriz and Swift photometry of SN 2021hpr to constrain its general physical properties. Together with its siblings, SNe 1997bq and 2008fv, we cross-compare the individual distance estimates of these three SNe given by the SALT code, and also check their consistency with the results from the MLCS2k2 method. The early spectral series of SN 2021hpr are also fit with the radiative spectral code TARDIS in order to verify the explosion properties and constrain the chemical distribution of the outer ejecta. After combining the distance estimates for the three SNe, the mean distance to their host galaxy, NGC 3127, is 42.5 $\pm$ 1.0 Mpc, which matches with the distance inferred by the most up-to-date LC fitters, SALT3 and BayeSN. We confirm that SN~2021hpr is a Branch-normal Type Ia SN that ejected $\sim 1.12 \pm 0.28$ M$_\odot$ from its progenitor white dwarf, and synthesized $\sim 0.44 \pm 0.14$ M$_\odot$ of radioactive $^{56}$Ni., Comment: 16 pages, 17 figures, 11 tables; accepted for publication in A&A

The exact value of the separating Noether number of some finite abelian groups is determined, including the direct sums of cyclic groups of the same order., Comment: 12 pages

In this study, five different time-dependent incompressible non-Newtonian boundary layer models in two dimensions are investigated, including external magnetic field effects. The power law, the Casson fluid, the Oldroyd-B model, the Walter fluid B model and the Williamson fluid are analyzed. For the first two models, analytical results are given for the velocity and pressure distributions, which can be expressed by different types of hypergeometric functions. Depending on the parameters involved in the analytical solutions of the nonlinear ordinary differential equation obtained by the similarity transformation, a very wide range of solution types is presented., Comment: 23 pages, 13 figures

We investigate diffusion equations which have concentration dependent diffusion coefficients with physically two relevant Ans\"atze, the self-similar and the traveling wave Ansatz. We found that for power-law concentration dependence some of the results can be expressed with a general analytic implicit formulas for both trial functions. For the self-similar case some of the solutions can be given with a formula containing the hypergeometric function. For the traveling wave case different analytic formulas are given for different exponents. For some physically reasonable parameter sets the direct solutions are given and analyzed in details., Comment: 13 pages 3 figures

The all pairs shortest path problem (APSP) is one of the foundational problems in computer science. For weighted dense graphs on $n$ vertices, no truly sub-cubic algorithms exist to compute APSP exactly even for undirected graphs. This is popularly known as the APSP conjecture and has played a prominent role in developing the field of fine-grained complexity. The seminal result of Seidel uses fast matrix multiplication (FMM) to compute APSP on unweighted undirected graphs exactly in $\tilde{O}(n^{\omega})$ time, where $\omega=2.372$. Even for unweighted undirected graphs, it is not possible to obtain a $(2-\epsilon)$-approximation of APSP in $o(n^\omega)$ time. In this paper, we provide a multitude of new results for multiplicative and additive approximations of APSP in undirected graphs for both unweighted and weighted cases. We provide new algorithms for multiplicative 2-approximation of unweighted graphs: a deterministic one that runs in $\tilde{O}(n^{2.072})$ time and a randomized one that runs in $\tilde{O}(n^{2.032})$ on expectation improving upon the best known bound of $\tilde{O}(n^{2.25})$ by Roditty (STOC, 2023). For $2$-approximating paths of length $\geq k$, $k \geq 4$, we provide the first improvement after Dor, Halperin, Zwick (2000) for dense graphs even just using combinatorial methods, and then improve it further using FMM. We next consider additive approximations, and provide improved bounds for all additive $\beta$-approximations, $\beta \geq 4$. For weighted graphs, we show that by allowing small additive errors along with an $(1+\epsilon)$-multiplicative approximation, it is possible to improve upon Zwick's $\tilde{O}(n^\omega)$ algorithm. Our results point out the crucial role that FMM can play even on approximating APSP on unweighted undirected graphs, and reveal new bottlenecks towards achieving a quadratic running time to approximate APSP., Comment: 81 pages

We present extensive ultraviolet (UV) and optical photometric and optical spectroscopic follow-up of supernova (SN)~2021gno by the "Precision Observations of Infant Supernova Explosions" (POISE) project, starting less than two days after the explosion. Given its intermediate luminosity, fast photometric evolution, and quick transition to the nebular phase with spectra dominated by [Ca~II] lines, SN~2021gno belongs to the small family of Calcium-rich transients. Moreover, it shows double-peaked light curves, a phenomenon shared with only four other Calcium-rich events. The projected distance from the center of the host galaxy is not as large as other objects in this family. The initial optical light-curve peaks coincide with a very quick decline of the UV flux, indicating a fast initial cooling phase. Through hydrodynamical modelling of the bolometric light curve and line velocity evolution, we found that the observations are compatible with the explosion of a highly-stripped massive star with an ejecta mass of $0.8\,M_\odot$ and a $^{56}$Ni mass of $0.024~M_{\odot}$. The initial cooling phase (first light curve peak) is explained by the presence of an extended circumstellar material comprising $\sim$$10^{-2}\,M_{\odot}$ with an extension of $1100\,R_{\odot}$. We discuss if hydrogen features are present in both maximum-light and nebular spectra, and its implications in terms of the proposed progenitor scenarios for Calcium-rich transients., Comment: 21 pages, 13 figures, accepted for publication in MNRAS

Context. Several bright emission line regions have been observed in the central 100 parsecs of the active galaxy NGC 1068. Aims. We aim to determine the properties and ionization mechanism of three regions of NGC 1068: the nucleus (B) and two clouds located at 0.3" and 0.7" north of it (C and D). Methods. We combined SPHERE (0.95 - 1.65 um) and SINFONI (1.5 - 2.45 um) spectra for the three regions B, C, and D. We compared these spectra to several CLOUDY photoionization models and to the MAPPINGS III Library of Fast Radiative Shock Models. Results. The emission line spectra of the three regions are almost identical to each other and contribute to most of the emission line flux in the nuclear region. The emitting media contain multiple phases, the most luminous of which have temperatures ranging from 104.8 K to 106 K. Central photoionization models can reproduce some features of the spectra, but the fast radiative shock model provides the best fit to the data. Conclusions. The similarity between the three regions indicates that they belong to the same class of objects. Based on our comparisons, we conclude that they are shock regions located where the jet of the active galactic nucleus impacts massive molecular clouds., Comment: A&A, Forthcoming article, accepted for publication

We present the photometric and spectroscopic evolution of SN 2022oqm, a nearby multi-peaked hydrogen- and helium-weak calcium-rich transient (CaRT). SN 2022oqm was detected 13.1 kpc from its host galaxy, the face-on spiral galaxy NGC 5875. Extensive spectroscopic coverage reveals an early hot (T >= 40,000 K) continuum and carbon features observed $\sim$1~day after discovery, SN Ic-like photospheric-phase spectra, and strong forbidden calcium emission starting 38 days after discovery. SN 2022oqm has a relatively high peak luminosity (MB = -17 mag) for (CaRTs), making it an outlier in the population. We determine that three power sources are necessary to explain the light curve (LC), with each corresponding to a distinct peak. The first peak is powered by an expanding blackbody with a power law luminosity, suggesting shock cooling by circumstellar material (CSM). Subsequent LC evolution is powered by a double radioactive decay model, consistent with two sources of photons diffusing through optically thick ejecta. From the LC, we derive an ejecta mass and 56Ni mass of ~0.6 solar masses and ~0.09 solar masses. Spectroscopic modeling suggests 0.6 solar masses of ejecta, and with well-mixed Fe-peak elements throughout. We discuss several physical origins for SN 2022oqm and find either a surprisingly massive white dwarf progenitor or a peculiar stripped envelope model could explain SN 2022oqm. A stripped envelope explosion inside a dense, hydrogen- and helium-poor CSM, akin to SNe Icn, but with a large 56Ni mass and small CSM mass could explain SN 2022oqm. Alternatively, helium detonation on an unexpectedly massive white dwarf could also explain SN 2022oqm., Comment: 35 pages, 17 figures, 7 tables, Accepted for Publication in ApJ

Nebular-phase observations of peculiar Type Ia supernovae (SNe Ia) provide important constraints on progenitor scenarios and explosion dynamics for both these rare SNe and the more common, cosmologically useful SNe Ia. We present observations from an extensive ground-based and space-based follow-up campaign to characterize SN 2022pul, a "super-Chandrasekhar" mass SN Ia (alternatively "03fg-like" SN), from before peak brightness to well into the nebular phase across optical to mid-infrared (MIR) wavelengths. The early rise of the light curve is atypical, exhibiting two distinct components, consistent with SN Ia ejecta interacting with dense carbon-oxygen rich circumstellar material (CSM). In the optical, SN 2022pul is most similar to SN 2012dn, having a low estimated peak luminosity ($M_{B}=-18.9$ mag) and high photospheric velocity relative to other 03fg-like SNe. In the nebular phase, SN 2022pul adds to the increasing diversity of the 03fg-like subclass. From 168 to 336 days after peak $B$-band brightness, SN 2022pul exhibits asymmetric and narrow emission from [O I] $\lambda\lambda 6300,\ 6364$ (${\rm FWHM} \approx 2{,}000$ km s$^{-1}$), strong, broad emission from [Ca II] $\lambda\lambda 7291,\ 7323$ (${\rm FWHM} \approx 7{,}300$ km s$^{-1}$), and a rapid Fe III to Fe II ionization change. Finally, we present the first-ever optical-to-mid-infrared (MIR) nebular spectrum of an 03fg-like SN Ia using data from JWST. In the MIR, strong lines of neon and argon, weak emission from stable nickel, and strong thermal dust emission (with $T \approx 500$ K), combined with prominent [O I] in the optical, suggest that SN 2022pul was produced by a white dwarf merger within carbon/oxygen-rich CSM., Comment: 23 pages, 11 figures, submitted to ApJ

We present an analysis of ground-based and JWST observations of SN~2022pul, a peculiar "03fg-like" (or "super-Chandrasekhar") Type Ia supernova (SN Ia), in the nebular phase at 338d post explosion. Our combined spectrum continuously covers 0.4--14 $\mu$m and includes the first mid-infrared spectrum of an 03fg-like SN Ia. Compared to normal SN Ia 2021aefx, SN 2022pul exhibits a lower mean ionization state, asymmetric emission-line profiles, stronger emission from the intermediate-mass elements (IMEs) argon and calcium, weaker emission from iron-group elements (IGEs), and the first unambiguous detection of neon in a SN Ia. Strong, broad, centrally peaked [Ne II] line at 12.81 $\mu$m was previously predicted as a hallmark of "violent merger'' SN Ia models, where dynamical interaction between two sub-$M_{ch}$ white dwarfs (WDs) causes disruption of the lower mass WD and detonation of the other. The violent merger scenario was already a leading hypothesis for 03fg-like SNe Ia; in SN 2022pul it can explain the large-scale ejecta asymmetries seen between the IMEs and IGEs and the central location of narrow oxygen and broad neon. We modify extant models to add clumping of the ejecta to better reproduce the optical iron emission, and add mass in the innermost region ($< 2000$ km s$^{-1}$) to account for the observed narrow [O I]~$\lambda\lambda6300$, 6364 emission. A violent WD-WD merger explains many of the observations of SN 2022pul, and our results favor this model interpretation for the subclass of 03fg-like SN Ia., Comment: 20 pages, 10 figures, published in ApJ

Neuromorphic computing aims to mimic both the function and structure of biological neural networks to provide artificial intelligence with extreme efficiency. Conventional approaches store synaptic weights in non-volatile memory devices with analog resistance states, permitting in-memory computation of neural network operations while avoiding the costs associated with transferring synaptic weights from a memory array. However, the use of analog resistance states for storing weights in neuromorphic systems is impeded by stochastic writing, weights drifting over time through stochastic processes, and limited endurance that reduces the precision of synapse weights. Here we propose and experimentally demonstrate neuromorphic networks that provide high-accuracy inference thanks to the binary resistance states of magnetic tunnel junctions (MTJs), while leveraging the analog nature of their stochastic spin-transfer torque (STT) switching for unsupervised Hebbian learning. We performed the first experimental demonstration of a neuromorphic network directly implemented with MTJ synapses, for both inference and spike-timing-dependent plasticity learning. We also demonstrated through simulation that the proposed system for unsupervised Hebbian learning with stochastic STT-MTJ synapses can achieve competitive accuracies for MNIST handwritten digit recognition. By appropriately applying neuromorphic principles through hardware-aware design, the proposed STT-MTJ neuromorphic learning networks provide a pathway toward artificial intelligence hardware that learns autonomously with extreme efficiency.

{\em Algorithms with predictions} incorporate machine learning predictions into algorithm design. A plethora of recent works incorporated predictions to improve on worst-case optimal bounds for online problems. In this paper, we initiate the study of complexity of dynamic data structures with predictions, including dynamic graph algorithms. Unlike in online algorithms, the main goal in dynamic data structures is to maintain the solution {\em efficiently} with every update. Motivated by work in online algorithms, we investigate three natural models of predictions: (1) $\varepsilon$-accurate predictions where each predicted request matches the true request with probability at least $\varepsilon$, (2) list-accurate predictions where a true request comes from a list of possible requests, and (3) bounded delay predictions where the true requests are some (unknown) permutations of the predicted requests. For $\varepsilon$-accurate predictions, we show that lower bounds from the non-prediction setting of a problem carry over, up to a $1-\varepsilon$ factor. Then we give general reductions among the prediction models for a problem, showing that lower bounds for bounded delay imply lower bounds for list-accurate predictions, which imply lower bounds for $\varepsilon$-accurate predictions. Further, we identify two broad problem classes based on lower bounds due to the Online Matrix Vector (OMv) conjecture. Specifically, we show that dynamic problems that are {\em locally correctable} have strong conditional lower bounds for list-accurate predictions that are equivalent to the non-prediction setting, unless list-accurate predictions are perfect. Moreover, dynamic problems that are {\em locally reducible} have a smooth transition in the running time. We categorize problems accordingly and give upper bounds that show that our lower bounds are almost tight, including problems in dynamic graphs., Comment: Abstract shortened to meet arXiv requirements

The edit distance is a fundamental measure of sequence similarity, defined as the minimum number of character insertions, deletions, and substitutions needed to transform one string into the other. Given two strings of length at most $n$, simple dynamic programming computes their edit distance exactly in $O(n^2)$ time, which is also the best possible (up to subpolynomial factors) assuming the Strong Exponential Time Hypothesis (SETH). The last few decades have seen tremendous progress in edit distance approximation, where the runtime has been brought down to subquadratic, near-linear, and even sublinear at the cost of approximation. In this paper, we study the dynamic edit distance problem, where the strings change dynamically as the characters are substituted, inserted, or deleted over time. Each change may happen at any location of either of the two strings. The goal is to maintain the (exact or approximate) edit distance of such dynamic strings while minimizing the update time. The exact edit distance can be maintained in $\tilde{O}(n)$ time per update (Charalampopoulos, Kociumaka, Mozes; 2020), which is again tight assuming SETH. Unfortunately, even with the unprecedented progress in edit distance approximation in the static setting, strikingly little is known regarding dynamic edit distance approximation. Utilizing the off-the-shelf tools, it is possible to achieve an $O(n^{c})$-approximation in $n^{0.5-c+o(1)}$ update time for any constant $c\in [0,\frac16]$. Improving upon this trade-off remains open. The contribution of this work is a dynamic $n^{o(1)}$-approximation algorithm with amortized expected update time of $n^{o(1)}$. In other words, we bring the approximation-ratio and update-time product down to $n^{o(1)}$. Our solution utilizes an elegant framework of precision sampling tree for edit distance approximation (Andoni, Krauthgamer, Onak; 2010)., Comment: Accepted to FOCS 2022

We have found that the 2+2 quadruple star system BU CMi is currently the most compact quadruple system known, with an extremely short outer period of only 121 days. The previous record holder was TIC 219006972 (Kostov et al. 2023), with a period of 168 days. The quadruple nature of BU CMi was established by Volkov et al. (2021), but they misidentified the outer period as 6.6 years. BU CMi contains two eclipsing binaries (EBs), each with a period near 3 days, and a substantial eccentricity of about 0.22. All four stars are within about 0.1 solar mass of 2.4 solar masses. Both binaries exhibit dynamically driven apsidal motion with fairly short apsidal periods of about 30 years, thanks to the short outer orbital period. The outer period of 121 days is found both from the dynamical perturbations, with this period imprinted on the eclipse timing variations (ETV) curve of each EB by the other binary, and by modeling the complex line profiles in a collection of spectra. We find that the three orbital planes are all mutually aligned to within 1 degree, but the overall system has an inclination angle near 83.5 degrees. We utilize a complex spectro-photodynamical analysis to compute and tabulate all the interesting stellar and orbital parameters of the system. Finally, we also find an unexpected dynamical perturbation on a timescale of several years whose origin we explore. This latter effect was misinterpreted by Volkov et al. (2021) and led them to conclude that the outer period was 6.6 years rather than the 121 days that we establish here., Comment: 19 pages, 8 pages, accepted to MNRAS

Many applications, e.g., in shared mobility, require coordinating a large number of agents. Mean-field reinforcement learning addresses the resulting scalability challenge by optimizing the policy of a representative agent interacting with the infinite population of identical agents instead of considering individual pairwise interactions. In this paper, we address an important generalization where there exist global constraints on the distribution of agents (e.g., requiring capacity constraints or minimum coverage requirements to be met). We propose Safe-M$^3$-UCRL, the first model-based mean-field reinforcement learning algorithm that attains safe policies even in the case of unknown transitions. As a key ingredient, it uses epistemic uncertainty in the transition model within a log-barrier approach to ensure pessimistic constraints satisfaction with high probability. Beyond the synthetic swarm motion benchmark, we showcase Safe-M$^3$-UCRL on the vehicle repositioning problem faced by many shared mobility operators and evaluate its performance through simulations built on vehicle trajectory data from a service provider in Shenzhen. Our algorithm effectively meets the demand in critical areas while ensuring service accessibility in regions with low demand., Comment: 23 pages, 26 figures, 6 tables

Aims. We aim to characterize the properties of the stellar populations in the central few hundred parsecs of nearby galactic nuclei; specifically their age, mass, and 3D geometry. Methods. We use spatially resolved spectroscopic observations of NGC 1433, NGC 1566, and NGC 1808 obtained with SINFONI to constrain a 3D model composed of a spherically symmetric nuclear star cluster (NSC) and an extended thick stellar disk. We computed UV to mid-infrared single stellar population (UMISSP) spectra to determine the age of the stellar populations and construct synthetic observations for our model. To overcome degeneracies between key parameters, we simultaneously fit the spatially resolved line-of-sight velocity, line-of-sight-velocity-dispersion, low-spectral-resolution NIR continuum, and high-spectral-resolution CO absorption features for each pixel. Results. For the three objects, we derive the age and mass of the young and old stellar populations in the NSC and surrounding disk, as well as their 3D geometry: radius for the NSC; thickness, inclination, and position angle for the disk. These results are consistent with published independent measurements when available. Conclusions. The proposed method allows us to derive a consistent 3D model of the stellar populations in nearby galactic centers solely based on a near-infrared IFU observation.

We present the optical photometric and spectroscopic analysis of two type Iax SNe 2018cni and 2020kyg. SN 2018cni is a bright type Iax SN (M$_{V,peak}$ = $-$17.81$\pm$0.21 mag) whereas SN 2020kyg (M$_{V,peak}$ = $-$14.52$\pm$0.21 mag) is a faint one. We derive $^{56}$Ni mass of 0.07 and 0.002 M${_\odot}$, ejecta mass of 0.48 and 0.14 M${_\odot}$ for SNe 2018cni and 2020kyg, respectively. A combined study of the bright and faint type Iax SNe in $R/r$- band reveals that the brighter objects tend to have a longer rise time. However, the correlation between the peak luminosity and decline rate shows that bright and faint type Iax SNe exhibit distinct behaviour. Comparison with standard deflagration models suggests that SN 2018cni is consistent with the deflagration of a CO white dwarf whereas the properties of SN 2020kyg can be better explained by the deflagration of a hybrid CONe white dwarf. The spectral features of both the SNe point to the presence of similar chemical species but with different mass fractions. Our spectral modelling indicates stratification at the outer layers and mixed inner ejecta for both the SNe., Comment: 18 pages, 18 figures, Accepted for Publication in The Astrophysical Journal

In the description of transport phenomena an important aspect represents the diffusion. In certain cases the diffusion may appear together with convection. In this paper we study the diffusion equation with the self similar Ansatz. With an appropriate change of variables we found original solutions of diffusion equation for infinite horizon. Here we present the even solutions of diffusion equation for the boundary conditions presented. For completeness the odd solutions are also mentioned as well, as part of the previous works. Finally, the diffusion equation with constant source term is discussed, which also has even and odd solutions, too, Comment: 17 pages, 9 figures

We present a general mathematical procedure to handle interactions described by a Morse potential in the presence of a strong harmonic excitation. We account for permanent and field-induced terms and their gradients in the dipole moment function, and we derive analytic formulae for the bond-length change and for the shifted energy eigenvalues of the vibrations, by using the Kramers-Henneberger frame. We apply these results to the important cases of $\mathrm{H}_{2}$ and $\mathrm{LiH}$, driven by a near- or mid-infrared laser in the $10^{13}$ $\mathrm{ W/cm^2}$ intensity range.

We present a dark fluid model described as a non-viscous, non-relativistic, rotating, and self-gravitating fluid. We assumed that the system has spherical symmetry and the matter can be described with the polytropic equation of state. The induced coupled non-linear partial differential equation system was solved by using a self-similar time-dependent ansatz introduced by L. Sedov and G. I. Taylor. These kinds of solutions were successfully used to describe blast waves induced by an explosion since the Guderley-Landau-Stanyukovich problem. We showed that these kinds of solutions can provide new solutions that are consistent with the Newtonian cosmological framework. We have found that such solutions can be applied to describe normal-to-dark energy on the cosmological scale., Comment: 16 page, 8 figures

Given two strings of length $n$ over alphabet $\Sigma$, and an upper bound $k$ on their edit distance, the algorithm of Myers (Algorithmica'86) and Landau and Vishkin (JCSS'88) computes the unweighted string edit distance in $\mathcal{O}(n+k^2)$ time. Till date, it remains the fastest algorithm for exact edit distance computation, and it is optimal under the Strong Exponential Hypothesis (STOC'15). Over the years, this result has inspired many developments, including fast approximation algorithms for string edit distance as well as similar $\tilde{\mathcal{O}}(n+$poly$(k))$-time algorithms for generalizations to tree and Dyck edit distances. Surprisingly, all these results hold only for unweighted instances. While unweighted edit distance is theoretically fundamental, almost all real-world applications require weighted edit distance, where different weights are assigned to different edit operations and may vary with the characters being edited. Given a weight function $w: \Sigma \cup \{\varepsilon \}\times \Sigma \cup \{\varepsilon \} \rightarrow \mathbb{R}_{\ge 0}$ (such that $w(a,a)=0$ and $w(a,b)\ge 1$ for all $a,b\in \Sigma \cup \{\varepsilon\}$ with $a\ne b$), the goal is to find an alignment that minimizes the total weight of edits. Except for the vanilla $\mathcal{O}(n^2)$-time dynamic-programming algorithm and its almost trivial $\mathcal{O}(nk)$-time implementation, none of the aforementioned developments on the unweighted edit distance apply to the weighted variant. In this paper, we propose the first $\mathcal{O}(n+$poly$(k))$-time algorithm that computes weighted string edit distance exactly, thus bridging a fundamental gap between our understanding of unweighted and weighted edit distance. We then generalize this result to weighted tree and Dyck edit distances, which lead to a deterministic algorithm that improves upon the previous work for unweighted tree edit distance.

Type Iax supernovae (SN Iax) are the largest known class of peculiar white dwarf supernovae, distinct from normal Type Ia supernovae (SN Ia). The unique properties of SN Iax, especially their strong photospheric lines out to extremely late times, allow us to model their optical spectra and derive physical parameters for the long-lasting photosphere. We present an extensive spectral timeseries, including 21 new spectra, of SN Iax 2014dt from +11 to +562 days after maximum light. We are able to reproduce the entire timeseries with a self-consistent, nearly unaltered deflagration explosion model from Fink et al. (2014) using TARDIS, an open-source radiative transfer code (Kerzendorf & Sim 2014; Kerzendorf et al. 2023). We find that the photospheric velocity of SN 2014dt slows its evolution between +64 and +148 days, which closely overlaps the phase when we see SN 2014dt diverge from the normal spectral evolution of SN Ia (+90 to +150 days). The photospheric velocity at these epochs, ~400$-$1000 km s$^{-1}$, may demarcate a boundary within the ejecta below which the physics of SN Iax and normal SN Ia differ. Our results suggest that SN 2014dt is consistent with a weak deflagration explosion model that leaves behind a bound remnant and drives an optically thick, quasi-steady-state wind creating the photospheric lines at late times. The data also suggest that this wind may weaken at epochs past +450 days, perhaps indicating a radioactive power source that has decayed away., Comment: Accepted to ApJ, 22 pages, 8 figures, 3 tables

The edit distance between strings classically assigns unit cost to every character insertion, deletion, and substitution, whereas the Hamming distance only allows substitutions. In many real-life scenarios, insertions and deletions (abbreviated indels) appear frequently but significantly less so than substitutions. To model this, we consider substitutions being cheaper than indels, with cost $1/a$ for a parameter $a\ge 1$. This basic variant, denoted $ED_a$, bridges classical edit distance ($a=1$) with Hamming distance ($a\to\infty$), leading to interesting algorithmic challenges: Does the time complexity of computing $ED_a$ interpolate between that of Hamming distance (linear time) and edit distance (quadratic time)? What about approximating $ED_a$? We first present a simple deterministic exact algorithm for $ED_a$ and further prove that it is near-optimal assuming the Orthogonal Vectors Conjecture. Our main result is a randomized algorithm computing a $(1+\epsilon)$-approximation of $ED_a(X,Y)$, given strings $X,Y$ of total length $n$ and a bound $k\ge ED_a(X,Y)$. For simplicity, let us focus on $k\ge 1$ and a constant $\epsilon > 0$; then, our algorithm takes $\tilde{O}(n/a + ak^3)$ time. Unless $a=\tilde{O}(1)$ and for small enough $k$, this running time is sublinear in $n$. We also consider a very natural version that asks to find a $(k_I, k_S)$-alignment -- an alignment with at most $k_I$ indels and $k_S$ substitutions. In this setting, we give an exact algorithm and, more importantly, an $\tilde{O}(nk_I/k_S + k_S\cdot k_I^3)$-time $(1,1+\epsilon)$-bicriteria approximation algorithm. The latter solution is based on the techniques we develop for $ED_a$ for $a=\Theta(k_S / k_I)$. These bounds are in stark contrast to unit-cost edit distance, where state-of-the-art algorithms are far from achieving $(1+\epsilon)$-approximation in sublinear time, even for a favorable choice of $k$., Comment: The full version of a paper accepted to ITCS 2023; abstract shortened to meet arXiv requirements

Sgr A East is the supernova remnant closest to the centre of the Milky Way. Its age has been estimated to be either very young, around 1-2 kyr, or about 10 kyr, and its exact origin remains unclear. We aspire to create a simple model of a supernova explosion that reproduces the shape, size, and location of Sgr A East. Using a simplified hydrodynamical code, we simulated the evolution of a supernova remnant in the medium around the Galactic centre. The latter consists of a nearby massive molecular cloud with which Sgr A East is known to be interacting and a wind from the nuclear star cluster. Our preferred models of the Sgr A East remnant are compatible with an age of around 10 kyr. We also find suitable solutions for older ages, but not for ages younger than 5 kyr. Our simulations predict that the supernova exploded at a distance of about 3.5 pc from the Galactic centre, below the Galactic plane, slightly eastwards from the centre and 3 pc behind it., Comment: 13 pages, 15 figures, accepted by A&A

We present JWST near- and mid-infrared spectroscopic observations of the nearby normal Type Ia supernova SN 2021aefx in the nebular phase at $+255$ days past maximum light. Our Near Infrared Spectrograph (NIRSpec) and Mid Infrared Instrument (MIRI) observations, combined with ground-based optical data from the South African Large Telescope (SALT), constitute the first complete optical $+$ NIR $+$ MIR nebular SN Ia spectrum covering 0.3$-$14 $\mu$m. This spectrum unveils the previously unobserved 2.5$-$5 $\mu$m region, revealing strong nebular iron and stable nickel emission, indicative of high-density burning that can constrain the progenitor mass. The data show a significant improvement in sensitivity and resolution compared to previous Spitzer MIR data. We identify numerous NIR and MIR nebular emission lines from iron-group elements and as well as lines from the intermediate-mass element argon. The argon lines extend to higher velocities than the iron-group elements, suggesting stratified ejecta that are a hallmark of delayed-detonation or double-detonation SN Ia models. We present fits to simple geometric line profiles to features beyond 1.2 $\mu$m and find that most lines are consistent with Gaussian or spherical emission distributions, while the [Ar III] 8.99 $\mu$m line has a distinctively flat-topped profile indicating a thick spherical shell of emission. Using our line profile fits, we investigate the emissivity structure of SN 2021aefx and measure kinematic properties. Continued observations of SN 2021aefx and other SNe Ia with JWST will be transformative to the study of SN Ia composition, ionization structure, density, and temperature, and will provide important constraints on SN Ia progenitor and explosion models., Comment: published in ApJ Letters, 17 pages, 12 figures

Computing the edit distance of two strings is one of the most basic problems in computer science and combinatorial optimization. Tree edit distance is a natural generalization of edit distance in which the task is to compute a measure of dissimilarity between two (unweighted) rooted trees with node labels. Perhaps the most notable recent application of tree edit distance is in NoSQL big databases, such as MongoDB, where each row of the database is a JSON document represented as a labeled rooted tree, and finding dissimilarity between two rows is a basic operation. Until recently, the fastest algorithm for tree edit distance ran in cubic time (Demaine, Mozes, Rossman, Weimann; TALG'10); however, Mao (FOCS'21) broke the cubic barrier for the tree edit distance problem using fast matrix multiplication. Given a parameter $k$ as an upper bound on the distance, an $O(n+k^2)$-time algorithm for edit distance has been known since the 1980s due to the works of Myers (Algorithmica'86) and Landau and Vishkin (JCSS'88). The existence of an $\tilde{O}(n+\mathrm{poly}(k))$-time algorithm for tree edit distance has been posed as an open question, e.g., by Akmal and Jin (ICALP'21), who gave a state-of-the-art $\tilde{O}(nk^2)$-time algorithm. In this paper, we answer this question positively., Comment: Full version of a paper accepted to FOCS 2022

A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 ($\sim 2800$--8700$A$ central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 $\mu$m with the open-source model-training software SALTShaker, which can easily accommodate future observations. Using simulated data we show that the training process constrains the NIR model to $\sim 2$--3% across the phase range ($-20$ to $50$ days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to $\sim 30$% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to $\sim20%$. For SN Ia observations expected from the \textit{Roman Space Telescope}, SALT3-NIR increases the amount of usable data in the SALT framework by $\sim 20$% at redshift $z\lesssim0.4$ and by $\sim 50$% at $z\lesssim0.15$. The SALT3-NIR model is part of the open-source {\tt SNCosmo} and {\tt SNANA} SN Ia cosmology packages.

To capture the inherent geometric features of many community detection problems, we propose to use a new random graph model of communities that we call a Geometric Block Model. The geometric block model builds on the random geometric graphs (Gilbert, 1961), one of the basic models of random graphs for spatial networks, in the same way that the well-studied stochastic block model builds on the Erd\H{o}s-R\'{en}yi random graphs. It is also a natural extension of random community models inspired by the recent theoretical and practical advancements in community detection. To analyze the geometric block model, we first provide new connectivity results for random annulus graphs which are generalizations of random geometric graphs. The connectivity properties of geometric graphs have been studied since their introduction, and analyzing them has been more difficult than their Erd\H{o}s-R\'{en}yi counterparts due to correlated edge formation. We then use the connectivity results of random annulus graphs to provide necessary and sufficient conditions for efficient recovery of communities for the geometric block model. We show that a simple triangle-counting algorithm to detect communities in the geometric block model is near-optimal. For this we consider the following two regimes of graph density. In the regime where the average degree of the graph grows logarithmically with the number of vertices, we show that our algorithm performs extremely well, both theoretically and practically. In contrast, the triangle-counting algorithm is far from being optimum for the stochastic block model in the logarithmic degree regime. We simulate our results on both real and synthetic datasets to show superior performance of both the new model as well as our algorithm., Comment: 53 pages, 18 figures. Accepted at the Journal of Machine Learning Research (JMLR). Shorter versions accepted in AAAI 2018 (see arXiv:1709.05510) and RANDOM 2019 (see arXiv:1804.05013). arXiv admin note: text overlap with arXiv:1804.05013

The multi-messenger detection of the gravitational-wave signal GW170817, the corresponding kilonova AT2017gfo and the short gamma-ray burst GRB170817A, as well as the observed afterglow has delivered a scientific breakthrough. For an accurate interpretation of all these different messengers, one requires robust theoretical models that describe the emitted gravitational-wave, the electromagnetic emission, and dense matter reliably. In addition, one needs efficient and accurate computational tools to ensure a correct cross-correlation between the models and the observational data. For this purpose, we have developed the Nuclear-physics and Multi-Messenger Astrophysics framework NMMA. The code allows incorporation of nuclear-physics constraints at low densities as well as X-ray and radio observations of isolated neutron stars. In previous works, the NMMA code has allowed us to constrain the equation of state of supranuclear dense matter, to measure the Hubble constant, and to compare dense-matter physics probed in neutron-star mergers and in heavy-ion collisions, and to classify electromagnetic observations and perform model selection. Here, we show an extension of the NMMA code as a first attempt of analyzing the gravitational-wave signal, the kilonova, and the gamma-ray burst afterglow simultaneously. Incorporating all available information, we estimate the radius of a $1.4M_\odot$ neutron star to be $R=11.98^{+0.35}_{-0.40}$km., Comment: code available at https://github.com/nuclear-multimessenger-astronomy

We investigate the usage of a Schlieren imaging setup to measure the geometrical dimensions of a plasma channel in atomic vapor. Near resonant probe light is used to image the plasma channel in a tenuous vapor and machine learning techniques are tested for extracting quantitative information from the images. By building a database of simulated signals with a range of plasma parameters for training Deep Neural Networks, we demonstrate that they can extract from the Schlieren images reliably and with high accuracy the location, the radius and the maximum ionization fraction of the plasma channel as well as the width of the transition region between the core of the plasma channel and the unionized vapor. We test several different neural network architectures with supervised learning and show that the parameter estimations supplied by the networks are resilient with respect to slight changes of the experimental parameters that may occur in the course of a measurement., Comment: 26 pages, 13 figures, 1 table

We present the sensitivity of the Theia experiment to low-energy geo- and reactor antineutrinos. For this study, we consider one of the possible proposed designs, a 17.8-ktonne fiducial volume Theia-25 detector filled with water-based liquid scintillator placed at Sanford Underground Research Facility (SURF). We demonstrate Theia's sensitivity to measure the geo- and reactor antineutrinos via Inverse-Beta Decay interactions after one year of data taking with $11.9\times10^{32}$ free target protons. The expected number of detected geo- and reactor antineutrinos is $218\,^{+28}_{-20}$ and $170\,^{+24}_{-20}$, respectively. The precision of the fitting procedure has been evaluated to be 6.72% and 8.55% for geo- and reactor antineutrinos, respectively. We also demonstrate the sensitivity towards fitting individual Th and U contributions, with best fit values of $N_\text{Th}=39\,^{+18}_{-15}$ and $N_\text{U}=180\,^{+26}_{-22}$. We obtain $(\text{Th}/\text{U})=4.3\pm2.6$ after one year of data taking, and within ten years, the relative precision of the (Th/U) mass ratio will be reduced to 15%. Finally, from the fit results of individual Th and U contributions, we evaluate the mantle signal to be $S_\text{mantle} = 9.0\,\pm [4.2,4.5]$NIU. This was obtained assuming a full-range positive correlation ($\rho_c\in[0, 1]$) between Th and U, and the projected uncertainties on the crust contributions of 8.3% (Th) and 7.0% (U). When considering systematic uncertainties on the signal and background shape and fluxes, the mantle signal becomes $S_\text{mantle} = 9.3\,\pm [5.2,5.4]$NIU., Comment: 15 pages, 10 figures, submitted to European Physical Journal C

We study the diffusion equation with an appropriate change of variables. This equation is in general a partial differential equation (PDE). With the self-similar and related Ansat\"atze we transform the PDE of diffusion to an ordinary differential equation. The solutions of the PDE belong to a family of functions which are presented for the case of infinite horizon. In the presentation we accentuate the physically reasonable solutions. We also study time dependent diffusion phenomena, where the spreading may vary in time. To describe the process we consider time dependent diffusion coefficients. The obtained analytic solutions all can be expressed with Kummer's or Whittaker-type of functions., Comment: 28 pages, 5 figures

The High Energy Physics community can benefit from a natural synergy in research activities into next-generation large-scale water and scintillator neutrino detectors, now being studied for remote reactor monitoring, discovery and exclusion applications in cooperative nonproliferation contexts. Since approximately 2010, US nonproliferation researchers, supported by the National Nuclear Security Administration (NNSA), have been studying a range of possible applications of relatively large (100 ton) to very large (hundreds of kiloton) water and scintillator neutrino detectors. In parallel, the fundamental physics community has been developing detectors at similar scales and with similar design features for a range of high-priority physics topics, primarily in fundamental neutrino physics. These topics include neutrino oscillation studies at beams and reactors, solar, and geological neutrino measurements, supernova studies, and others. Examples of ongoing synergistic work at U.S. national laboratories and universities include prototype gadolinium-doped water and water-based and opaque scintillator test-beds and demonstrators, extensive testing and industry partnerships related to large area fast position-sensitive photomultiplier tubes, and the development of concepts for a possible underground kiloton-scale water-based detector for reactor monitoring and technology demonstrations. Some opportunities for engagement between the two communities include bi-annual Applied Antineutrino Physics conferences, collaboration with U.S. National Laboratories engaging in this research, and occasional NNSA funding opportunities supporting a blend of nonproliferation and basic science R&D, directed at the U.S. academic community., Comment: contribution to Snowmass 2021

We investigate a hydrodynamic equation system which - with some approximation - is capable to describe the tsunami propagation in the open ocean with the time-dependent self-similar Ansatz. We found analytic solutions how the wave height and velocity behave in time and space for constant and linear seabed functions. First we study waves on open water, where the seabed can be considered relatively constant, sufficiently far from the shore. In the second part of the study we also consider a seabed which is oblique. Finally, we apply the most common traveling wave Ansatz and present almost trivial solutions as well., Comment: 23 pages, 8 figures