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I discuss here the progress made in the last decade on few of the key open problems in GRB physics. These include: (1) the nature of GRB progenitors, and the outliers found to the collapsar/merger scenarios; (2) Jet structures, whose existence became evident following GRB/GW170817; (3) the great progress made in understanding the GRB jet launching mechanisms, enabled by general-relativistic magneto-hydrodynamic (GR-MHD) codes; (4) recent studies of magnetic reconnection as a valid energy dissipation mechanism; (5) the early afterglow, which may be highly affected by a wind bubble, as well as recent indication that in many GRBs, the Lorentz factor is only a few tens, rather than few hundreds. I highlight some recent observational progress, including major breakthrough in detecting TeV photons and the on-going debate about their origin, polarization measurements, as well as the pair annihilation line recently detected in GRB 221009A, and its implications on the prompt emission physics. I point into some open questions that I anticipate would be at the forefront of GRB research in the next decade., Comment: Short invited review, to be published in Galaxies

Collisionless shocks are complex nonlinear structures that are not yet fully understood. In particular, the interaction between these shocks and the particles they accelerate remains elusive. Based on an instability analysis that relates the shock width to the spectrum of the accelerated particle and the shock density ratio, we find that the acceleration process could come to an end when the fraction of accelerated upstream particles reaches about 30\%. Only unmagnetized shocks are considered., Comment: To appear in Laser and Particle Beams

The X-ray light curves of gamma-ray bursts (GRBs) display complex features, including plateaus and flares, that challenge theoretical models. Here, we study the properties of flares that are observed in the early afterglow phase (up to a few thousand of seconds). We split the sample into two groups: bursts with and without X-ray plateau. We find that the distributions of flare properties are similar in each group. Specifically, the peak time ($t_{\rm pk}$) of the flares and the ratio of the flare width to the flare peak time ($w/t_{\rm pk}$) which is found to be $\approx 1$, regardless of the presence of a plateau. We discuss these results in view of the different theoretical models aimed at explaining the origin of the plateau. These results are difficult to explain by viewing angle effects or late-time energy injection, but do not contradict the idea that GRBs with X-ray plateau have low Lorentz factor, of the order of tens. For these GRBs, the dissipation processes that produce the flares naturally occur at smaller radii compared to GRBs with higher Lorentz factors, while the flares maintain a similar behaviour. Our results therefore provide an independent support for the idea that many GRBs have a Lorentz factor of a few tens rather than a few hundreds., Comment: Submitted to ApJ

We studied magnetically arrested disks (MAD) around rotating black holes (BH), under the influence of radiative cooling. We introduce a critical value of the mass accretion rate $\dot M_{\rm crit}$ for which the cooling by the synchrotron process efficiently radiates the thermal energy of the disk. We find $\dot M_{\rm crit} \approx 10^{-5.5} \dot M_{\rm Edd}$, where $\dot M_{\rm Edd}$ is the Eddington mass accretion rate. The normalization constant depends on the saturated magnetic flux and on the ratio of electron to proton temperatures, but not on the BH mass. We verify our analytical estimate using a suite of general relativistic magnetohydrodynamic (GRMHD) simulations for a range of black hole spin parameters $a \in \{ -0.94, -0.5, 0, 0.5, 0.94 \}$ and mass accretion rates ranging from $10^{-7}\dot M_{\rm Edd}$ to $10^{-4}\dot M_{\rm Edd}$. We numerically observe that the MAD parameter and the jet efficiency vary by a factor of $\approx 2$ as the mass accretion rate increases above $\dot M_{\rm crit}$, which confirms our analytical result. We further detail how the forces satisfying the quasi-equilibrium of the disk change, with the magnetic contribution increasing as the thermal contribution decreases., Comment: Submitted to ApJL

The invention of X-ray interferometers has led to advanced phase-sensing devices that are invaluable in various applications. These include the precise measurement of universal constants, e.g. the Avogadro number, of lattice parameters of perfect crystals, and phase-contrast imaging, which resolves details that standard absorption imaging cannot capture. However, the sensitivity and robustness of conventional X-ray interferometers are constrained by factors, such as fabrication precision, beam quality, and, importantly, noise originating from external sources or the sample itself. In this work, we demonstrate a novel X-ray interferometric method of phase measurement with enhanced immunity to various types of noise, by extending, for the first time, the concept of the SU(1,1) interferometer into the X-ray regime. We use a monolithic silicon perfect crystal device with two thin lamellae to generate correlated photon pairs via spontaneous parametric down-conversion (SPDC). Arrival time coincidence and sum-energy filtration allow a high-precision separation of the correlated photon pairs, which carry the phase information from orders-of-magnitude larger uncorrelated photonic noise. The novel SPDC-based interferometric method presented here is anticipated to exhibit enhanced immunity to vibrations as well as to mechanical and photonic noise, compared to conventional X-ray interferometers. Therefore, this SU(1,1) X-ray interferometer should pave the way to unprecedented precision in phase measurements, with transformative implications for a wide range of applications.

Generative modeling typically concerns the transport of a single source distribution to a single target distribution by learning (i.e., regressing onto) simple probability flows. However, in modern data-driven fields such as computer graphics and single-cell genomics, samples (say, point-clouds) from datasets can themselves be viewed as distributions (as, say, discrete measures). In these settings, the standard generative modeling paradigm of flow matching would ignore the relevant geometry of the samples. To remedy this, we propose \emph{Wasserstein flow matching} (WFM), which appropriately lifts flow matching onto families of distributions by appealing to the Riemannian nature of the Wasserstein geometry. Our algorithm leverages theoretical and computational advances in (entropic) optimal transport, as well as the attention mechanism in our neural network architecture. We present two novel algorithmic contributions. First, we demonstrate how to perform generative modeling over Gaussian distributions, where we generate representations of granular cell states from single-cell genomics data. Secondly, we show that WFM can learn flows between high-dimensional and variable sized point-clouds and synthesize cellular microenvironments from spatial transcriptomics datasets. Code is available at [WassersteinFlowMatching](https://github.com/DoronHav/WassersteinFlowMatching)., Comment: 24 pages, 10 figures

Synchrotron maser emission is a leading candidate to explain the coherent emission from Fast Radio Bursts (FRBs). This mechanism requires a population inversion in order to operate. We show that nonresonant interactions between Alfv\'{e}n waves and a relativistic plasma result in the formation of population inversions across a wide range of magnetizations, $\sigma\gtrsim10^{-4}$, and temperatures, $10^{-2} \leq k_bT/mc^2 \leq 3$, spanning the parameters expected in FRB environments. We calculate the fraction of energy contained in the inversion across the whole of this parameter space for the first time and we show that energy fractions of $f_{inv}\sim 0.3$ are achieved for high magnetizations $\sigma >1$. The population inversion forms on time-scales compatible with the typical dynamical time-scales of magnetars for all magnetizations. Furthermore, we provide physical explanations for the behaviour of the interaction in different magnetization regimes, and identify the important characteristic values at which this behaviour changes. We also show that the mechanism is capable of producing an FRB signal at GHz frequencies in a relativistic magnetar wind close to the light cylinder and that this signal can escape the magnetar environment without significant damping., Comment: 19 pages, 21 figures, submitted to MNRAS

We explore a new mechanism for photon energy gain in a relativistic plasma with velocity shear. This process takes place in optically thick plasma and resembles conventional Fermi acceleration, where photons undergo multiple scatterings between regions with varying Lorentz factors, leading to an overall energy increase. The resulting high-energy spectra from the escaped photons exhibit a power-law form. The mechanism is an alternative to the classical radiation spectrum from power-law accelerated particles, which can produce power-law spectra in sources like Gamma-ray bursts (GRBs) and Active Galactic Nuclei (AGNs). By employing both numerical simulations and theoretical analysis, we calculate the expected spectra for GRBs, and show that they match the observed photon indices ($\beta$) at high energies., Comment: Proceeding in Marcel Grossman 17, Pescara, Italy

Positive spectral lags are commonly observed in gamma-ray burst (GRB) prompt phase where soft photons lag behind hard ones in their spectral studies. Opposite to this pattern, a fraction of GRBs show a negative spectral lag where hard photons arrive later compared to soft photons. Similarly, recent Fermi-LAT observations show a late onset of high-energy photons in most GRB observations. A fraction of GRBs show a transition from positive to negative lags. Such negative lags and the spectral lag transition have no convincing explanation. We show that a structured GRB jet with velocity shear naturally produces both positive and negative spectral lags. s gain energy from repeated scattering with shearing layers and subsequently escape from higher altitudes. Hence, these photons are delayed compared to soft photons producing a negative spectral lag. The inner jet has no shear and a positive lag appears providing a unified picture of spectral lags in GRBs. The theory predicts a flip in spectral lag from positive to negative within the evolution of the prompt phase. Comparison of the observed lags with the prediction of the theory limits the possible range of GRB jet Lorentz factors to be a few tens., Comment: Submitted to ApJL

Decision trees (DTs) and their random forest (RF) extensions are workhorses of classification and regression in Euclidean spaces. However, algorithms for learning in non-Euclidean spaces are still limited. We extend DT and RF algorithms to product manifolds: Cartesian products of several hyperbolic, hyperspherical, or Euclidean components. Such manifolds handle heterogeneous curvature while still factorizing neatly into simpler components, making them compelling embedding spaces for complex datasets. Our novel angular reformulation of DTs respects the geometry of the product manifold, yielding splits that are geodesically convex, maximum-margin, and composable. In the special cases of single-component manifolds, our method simplifies to its Euclidean or hyperbolic counterparts, or introduces hyperspherical DT algorithms, depending on the curvature. We benchmark our method on various classification, regression, and link prediction tasks on synthetic data, graph embeddings, mixed-curvature variational autoencoder latent spaces, and empirical data. Compared to six other classifiers, product DTs and RFs ranked first on 21 of 22 single-manifold benchmarks and 18 of 35 product manifold benchmarks, and placed in the top 2 on 53 of 57 benchmarks overall. This highlights the value of product DTs and RFs as straightforward yet powerful new tools for data analysis in product manifolds. Code for our paper is available at https://github.com/pchlenski/embedders., Comment: 25 pages, 9 figures. Submitted to ICLR 2025

The prompt phase X- and $\gamma$-ray light curves of gamma-ray bursts (GRBs) exhibit erratic and complex behaviour, often with multiple pulses. The temporal shape of individual pulses is often modelled as 'fast rise exponential decay' (FRED). Here, we introduce a novel fitting function to quantify pulse asymmetry. We conduct a light curve and a time-resolved spectral analysis on 61 pulses from 22 GRBs detected by the Fermi Gamma-ray Burst Monitor. Contrary to previous claims, we find that only $\sim 50\%$ of pulse lightcurves in our sample show a FRED shape, while about $25\%$ have a symmetric lightcurve, and the other $25\%$ have a mixed shape. Furthermore, our analysis reveals a clear trend: in multi-pulse bursts, the initial pulse tends to exhibit the most symmetric light curve, while subsequent pulses become increasingly asymmetric, adopting a more FRED-like shape. Additionally, we correlate the temporal and spectral shapes of the pulses. By fitting the spectra with the classical "Band" function, we find a moderate positive Spearman correlation index of 0.23 between pulse asymmetry and the low-energy spectral index $\alpha_{\max}$ (the maximum value across all time bins covering an individual pulse). Thus, during GRB light curves, the pulses tend to get more asymmetric and spectrally softer with time. We interpret this as a transition in the dominant emission mechanism from photospheric (symmetric-like and hard) to non-thermal emission above the photosphere and show that this interpretation aligns with a GRB jet Lorentz factor of the order of a few 10s in many cases., Comment: Submitted to ApJ

The brightest of all time (BOAT) GRB221009A show evidence for a narrow, evolving MeV emission line. Here, we show that this line can be explained as due to pair annihilation in the prompt emission region, and that its temporal evolution is naturally explained as the high-latitude emission (emission from higher angles from the line of sight) after prompt emission is over. We consider both the high and low optical depth for pair production regimes, and find acceptable solutions, with the GRB Lorentz factor $\Gamma \approx 600$ and the emission radius $r \gtrsim 10^{16.5}$~cm. We discuss the conditions for the appearance of such a line, and show that a unique combination of high luminosity and Lorentz factor that is in a fairly narrow range are required for the line detection. This explains why such an annihilation line is rarely observed in GRBs., Comment: typo corrected; extended discussion on pair contribution. Published in Ap.J. Lett

Progenitor stars of long gamma-ray bursts (GRBs) could be surrounded by a significant and complex nebula structure lying at a parsec scale distance. After the initial release of energy from the GRB jet, the jet will interact with this nebula environment. We show here that for a large, plausible parameter space region, the interaction between the jet blastwave and the wind termination (reverse) shock is expected to be weak, and may be associated with a precursor emission. As the jet blast wave encounters the contact discontinuity separating the shocked wind and the shocked interstellar medium, we find that a bright flash of synchrotron emission from the newly-formed reverse shock is produced. This flash is expected to be observed at around ~100 s after the initial explosion and precursor. Such a delayed emission thus constitutes a circumburst medium (CBM) phase in a GRB, having a physically distinct origin from the preceding prompt phase and the succeeding afterglow phase. The CBM phase emission may thus provide a natural explanation to bursts observed to have a precursor followed by an intense, synchrotron-dominated main episode that is found in a substantial minority, ~10% of GRBs. A correct identification of the emission phase is thus required to infer the properties of the flow and of the immediate environment around GRB progenitors., Comment: 14 pages, 3 figures. Submitted for publication in the Astrophys. J

Reconstructing jets, which provide vital insights into the properties and histories of subatomic particles produced in high-energy collisions, is a main problem in data analyses in collider physics. This intricate task deals with estimating the latent structure of a jet (binary tree) and involves parameters such as particle energy, momentum, and types. While Bayesian methods offer a natural approach for handling uncertainty and leveraging prior knowledge, they face significant challenges due to the super-exponential growth of potential jet topologies as the number of observed particles increases. To address this, we introduce a Combinatorial Sequential Monte Carlo approach for inferring jet latent structures. As a second contribution, we leverage the resulting estimator to develop a variational inference algorithm for parameter learning. Building on this, we introduce a variational family using a pseudo-marginal framework for a fully Bayesian treatment of all variables, unifying the generative model with the inference process. We illustrate our method's effectiveness through experiments using data generated with a collider physics generative model, highlighting superior speed and accuracy across a range of tasks., Comment: 21 pages, 9 figures

Cross-validation is a common method for estimating the predictive performance of machine learning models. In a data-scarce regime, where one typically wishes to maximize the number of instances used for training the model, an approach called "leave-one-out cross-validation" is often used. In this design, a separate model is built for predicting each data instance after training on all other instances. Since this results in a single test data point available per model trained, predictions are aggregated across the entire dataset to calculate common rank-based performance metrics such as the area under the receiver operating characteristic or precision-recall curves. In this work, we demonstrate that this approach creates a negative correlation between the average label of each training fold and the label of its corresponding test instance, a phenomenon that we term distributional bias. As machine learning models tend to regress to the mean of their training data, this distributional bias tends to negatively impact performance evaluation and hyperparameter optimization. We show that this effect generalizes to leave-P-out cross-validation and persists across a wide range of modeling and evaluation approaches, and that it can lead to a bias against stronger regularization. To address this, we propose a generalizable rebalanced cross-validation approach that corrects for distributional bias. We demonstrate that our approach improves cross-validation performance evaluation in synthetic simulations and in several published leave-one-out analyses., Comment: 20 pages, 5 figures, supplementary information

Despite being studied for many years, the structure of collisionless shocks is still not fully determined. Such shocks are known to be accelerators of cosmic rays, which, in turn, modify the shock structure. The shock width $\lambda$ is known to be connected to the cosmic rays (CRs) spectral index, $a$. Here, we use an instability analysis to derive the shock width in the presence of CRs. We obtain an analytical expression connecting the shock width to the CRs index and to the fraction of upstream particles that are accelerated. We find that when this fraction becomes larger than $\sim$~30\%, a new instability becomes dominant. The shock undergoes a transition where its width increases by a factor $\sim 8- 10$, and the CRs acceleration effectively ends. Our analysis is valid for strong, non-relativistic and unmagnetized shocks. We discuss the implication of these results to the expected range of CRs spectra and flux observed, and on the structure of non-relativistic collisionless shocks., Comment: 14 pages, 6 figures, to appear in ApJ

Optimal transport (OT) and the related Wasserstein metric (W) are powerful and ubiquitous tools for comparing distributions. However, computing pairwise Wasserstein distances rapidly becomes intractable as cohort size grows. An attractive alternative would be to find an embedding space in which pairwise Euclidean distances map to OT distances, akin to standard multidimensional scaling (MDS). We present Wasserstein Wormhole, a transformer-based autoencoder that embeds empirical distributions into a latent space wherein Euclidean distances approximate OT distances. Extending MDS theory, we show that our objective function implies a bound on the error incurred when embedding non-Euclidean distances. Empirically, distances between Wormhole embeddings closely match Wasserstein distances, enabling linear time computation of OT distances. Along with an encoder that maps distributions to embeddings, Wasserstein Wormhole includes a decoder that maps embeddings back to distributions, allowing for operations in the embedding space to generalize to OT spaces, such as Wasserstein barycenter estimation and OT interpolation. By lending scalability and interpretability to OT approaches, Wasserstein Wormhole unlocks new avenues for data analysis in the fields of computational geometry and single-cell biology., Comment: Published at the Forty-first International Conference on Machine Learning (ICML2024)

Monochromatic gamma-ray signals constitute a potential smoking gun signature for annihilating or decaying dark matter particles that could relatively easily be distinguished from astrophysical or instrumental backgrounds. We provide an updated assessment of the sensitivity of the Cherenkov Telescope Array (CTA) to such signals, based on observations of the Galactic centre region as well as of selected dwarf spheroidal galaxies. We find that current limits and detection prospects for dark matter masses above 300 GeV will be significantly improved, by up to an order of magnitude in the multi-TeV range. This demonstrates that CTA will set a new standard for gamma-ray astronomy also in this respect, as the world's largest and most sensitive high-energy gamma-ray observatory, in particular due to its exquisite energy resolution at TeV energies and the adopted observational strategy focussing on regions with large dark matter densities. Throughout our analysis, we use up-to-date instrument response functions, and we thoroughly model the effect of instrumental systematic uncertainties in our statistical treatment. We further present results for other potential signatures with sharp spectral features, e.g.~box-shaped spectra, that would likewise very clearly point to a particle dark matter origin., Comment: 44 pages JCAP style (excluding author list and references), 19 figures; minor changes to match published version

In the context of modeling spectral energy distributions (SEDs) for blazars, we extend the method that uses a convolutional neural network (CNN) to include external inverse Compton processes. The model assumes that relativistic electrons within the emitting region can interact and up-scatter external photon originating from the accretion disk, the broad-line region, and the torus, to produce the observed high-energy emission. We trained the CNN on a numerical model that accounts for the injection of electrons, their self-consistent cooling, and pair creation-annihilation processes, considering both internal and all external photon fields. Despite the larger number of parameters compared to the synchrotron self-Compton model and the greater diversity in spectral shapes, the CNN enables an accurate computation of the SED for a specified set of parameters. The performance of the CNN is demonstrated by fitting the SED of two flat-spectrum radio quasars, namely 3C 454.3 and CTA 102, and obtaining their parameter posterior distributions. For the first source, the available data in the low-energy band allowed us to constrain the minimum Lorentz factor of the electrons, $\gamma_{\rm min}$, while for the second source, due to the lack of these data, $\gamma_{\rm min} = 10^2$ was set. We used the obtained parameters to investigate the energetics of the system. The model developed here, along with one from B\'egu\'e et al. (2023), enables self-consistent, in-depth modeling of blazar broadband emissions within leptonic scenario., Comment: submitted to ApJ. The model will be publicly available soon at https://mmdc.am/

Modeling the multiwavelength spectral energy distributions (SEDs) of blazars provides key insights into the underlying physical processes responsible for the emission. While SED modeling with self-consistent models is computationally demanding, it is essential for a comprehensive understanding of these astrophysical objects. We introduce a novel, efficient method for modeling the SEDs of blazars by the mean of a convolutional neural network (CNN). In this paper, we trained the CNN on a leptonic model that incorporates synchrotron and inverse Compton emissions, as well as self-consistent electron cooling and pair creation-annihilation processes. The CNN is capable of reproducing the radiative signatures of blazars with high accuracy. This approach significantly reduces computational time, thereby enabling real-time fitting to multi-wavelength datasets. As a demonstration, we used the trained CNN with MultiNest to fit the broadband SEDs of Mrk 421 and 1ES 1959+650, successfully obtaining their parameter posterior distributions. This novel framework for fitting the SEDs of blazars will be further extended to incorporate more sophisticated models based on external Compton and hadronic scenarios, allowing for multi-messenger constraints in the analysis. The models will be made publicly available via a web interface, the Markarian Multiwavelength Datacenter, to facilitate self-consistent modeling of multi-messenger data from blazar observations., Comment: 16 pages, submitted to ApJ. The model will be publicly available from the 20th of November on https://mmdc.am/

Protocols for processing of quantum information are the foundation of quantum technology, enabling to share secrets at a distance, teleport quantum states, and to implement quantum computation. While many protocols were realized, and even commercialized, the throughput and processing speed of current protocols is limited by the narrow electronic bandwidth of standard measurement devices (typically in the MHz-to-GHz range), which is orders-of-magnitude lower than the optical bandwidth of available quantum optical sources (10-100 THz), indicating that the bandwidth resource is dramatically underutilized in current quantum optical technology. We present a general concept of frequency multiplexed quantum channels and a set of methods to process quantum information efficiently across the available optical bandwidth. Using a broadband source of squeezed light, spectral manipulation methods and parametric homodyne detection, we are able to generate, process and measure all the channels in parallel, thereby harnessing the optical bandwidth for quantum information in an efficient manner. We exemplify the concept through two basic protocols: Multiplexed Continuous-Variable Quantum Key Distribution (CV-QKD) and multiplexed continuous-variable quantum teleportation. The multiplexed QKD protocol is demonstrated in a proof-of-principle experiment, where we successfully carry out QKD over 23 uncorrelated spectral channels, with capability to detect eavesdropping in any channel. These multiplexed methods (and similar) will enable to carry out quantum processing in parallel over hundreds of channels, potentially increasing the throughput of quantum protocols by orders of magnitude.

Hyperbolic geometry is gaining traction in machine learning for its effectiveness at capturing hierarchical structures in real-world data. Hyperbolic spaces, where neighborhoods grow exponentially, offer substantial advantages and consistently deliver state-of-the-art results across diverse applications. However, hyperbolic classifiers often grapple with computational challenges. Methods reliant on Riemannian optimization frequently exhibit sluggishness, stemming from the increased computational demands of operations on Riemannian manifolds. In response to these challenges, we present hyperDT, a novel extension of decision tree algorithms into hyperbolic space. Crucially, hyperDT eliminates the need for computationally intensive Riemannian optimization, numerically unstable exponential and logarithmic maps, or pairwise comparisons between points by leveraging inner products to adapt Euclidean decision tree algorithms to hyperbolic space. Our approach is conceptually straightforward and maintains constant-time decision complexity while mitigating the scalability issues inherent in high-dimensional Euclidean spaces. Building upon hyperDT we introduce hyperRF, a hyperbolic random forest model. Extensive benchmarking across diverse datasets underscores the superior performance of these models, providing a swift, precise, accurate, and user-friendly toolkit for hyperbolic data analysis.

The detection of gravitational waves from a binary neutron star merger by Advanced LIGO and Advanced Virgo (GW170817), along with the discovery of the electromagnetic counterparts of this gravitational wave event, ushered in a new era of multimessenger astronomy, providing the first direct evidence that BNS mergers are progenitors of short gamma-ray bursts (GRBs). Such events may also produce very-high-energy (VHE, > 100GeV) photons which have yet to be detected in coincidence with a gravitational wave signal. The Cherenkov Telescope Array (CTA) is a next-generation VHE observatory which aims to be indispensable in this search, with an unparalleled sensitivity and ability to slew anywhere on the sky within a few tens of seconds. New observing modes and follow-up strategies are being developed for CTA to rapidly cover localization areas of gravitational wave events that are typically larger than the CTA field of view. This work will evaluate and provide estimations on the expected number of of gravitational wave events that will be observable with CTA, considering both on- and off-axis emission. In addition, we will present and discuss the prospects of potential follow-up strategies with CTA., Comment: Presented at the 38th International Cosmic Ray Conference (ICRC 2023), 2023 (arXiv:2309.08219)

The study of Magnetically Arrested Disks (MAD) attract strong interest in recent years, as these disk configurations were found to generate strong jets as observed in many accreting systems. Here, we present the results of 14 general relativistic magnetohydrodynamic(GRMHD) simulations of advection dominated accretion flow in the MAD state across black hole spins, carried with cuHARM. Our main findings are as follows. (i) The jets transport a significant amount of angular momentum to infinity in the form of Maxwell stresses. For positive, high spin, the rate of angular momentum transport is about 5 times larger than for negative spin. This contribution is nearly absent for a non-rotating black hole. (ii) The mass accretion rate and the MAD parameter, both calculated at the horizon, are not correlated. However, their time derivatives are anti-correlated for every spin. (iii) For zero spin, the contribution of the toroidal component of the magnetic field to the magnetic pressure is negligible, while for fast spinning black hole, it is in the same order as the contribution of the radial magnetic component. For high positive spin, the toroidal component even dominates. (iv) For negative spins, the jets are narrower than their positive spin counterparts, while their fluctuations are larger. The weak jet from the non-rotating black hole is the widest with the smallest fluctuations. Our results highlight the complex, non-linear connection between the black hole spin and the resulting disk and jet properties in the MAD regime., Comment: 29 pages, submitted to ApJ

We present a mode-locked semiconductor laser oscillator that emits few picosecond pulses (5-8ps at 379MHz repetition) with record peak power (112W) and pulse energy (0.5nJ) directly out of the oscillator (with no amplifier). To achieve this high power performance we employ a high-current broad-area, spatially multi-mode diode amplifier (0.3x5mm), placed in an external cavity that enforces oscillation in a single spatial mode. Consequently, the brightness of the beam is near-ideal ($M^2 = 1.3$). Mode locking is achieved by dividing the large diode chip (edge emitter) into two sections with independent electrical control: one large section for gain and another small section for a saturable absorber. Precise tuning of the reverse voltage on the absorber section allows to tune the saturation level and recovery time of the absorber, which provides a convenient control knob to optimize the mode-locking performance for various cavity conditions.

Observations of long duration gamma-ray bursts (GRBs) with TeV emission during their afterglow have been on the rise. Recently, GRB 221009A, the most energetic GRB ever observed, was detected by the {LHAASO} experiment in the energy band 0.2 - 7 TeV. Here, we interpret its afterglow in the context of a hybrid model in which the TeV spectral component is explained by the proton-synchrotron process while the low energy emission from optical to X-ray is due to synchrotron radiation from electrons. We constrained the model parameters using the observed optical, X-ray and TeV data. By comparing the parameters of this burst and of GRB 190114C, we deduce that the VHE emission at energies $\geq$ 1 TeV in the GRB afterglow requires large explosion kinetic energy, $E \gtrsim 10^{54}$~erg and a reasonable circumburst density, $n\gtrsim 10$~cm$^{-3}$. This results in a small injection fractions of particles accelerated to a power-law, $\sim 10^{-2}$. {A significant fraction of shock energy must be allocated to a near equipartition magnetic field, $\epsilon_B \sim 10^{-1}$, while electrons should only carry a small fraction of this energy, $\epsilon_e \sim 10^{-3}$. Under these conditions required for a proton synchrotron model, namely $\epsilon_B \gg \epsilon_e$, the SSC component is substantially sub-dominant over proton-synchrotron as a source of TeV photons.} These results lead us to suggest that proton-synchrotron process is a strong contender for the radiative mechanisms explaining GRB afterglows in the TeV band., Comment: 15 pages and 4 figures (Accepted to be published in ApJ)

The jet cores in blazars are resolved and found to harbour an edge brightened structure where the jet base appears extended at sides compared to its propagation axis. This peculiar phenomenon invites various explanations. We show that the photosphere of an optically thick jet base in Active Galactic Nuclei (AGNs) is observed edge brightened if the jet Lorentz factor harbours an angular dependence. The jet assumes a higher Lorentz factor along the jet axis and decreases following a power law along its polar angle. For an observer near the jet axis, the jet has a lower optical depth along its propagation axis compared to off axis regions. Higher optical depths at the outer region makes the jet photosphere appear to extend to larger radii compared to a deeper photosphere along its propagation axis. We tackle the problem both analytically and numerically, confirming the edge brightening through Monte Carlo simulations. Other than the edge brightening, the outcomes are significant as they provide a unique tool to determine the jet structure and associated parameters by their resolved observed cores. The study paves way to explore the spectral properties of optically thick cores with structured Lorentz factors in the future., Comment: Submitted to APJL, 9 pages. Suggestions, comments or feedback will be appreciated

We show that an extragalactic jet with a velocity shear gives rise to Fermi like acceleration process for photons scattering withing the shear layers of the jet. Such photons then gain energy to produce a high energy power law. These power law spectra at high energies are frequently observed in several extragalactic objects such as Gamma Ray Bursts (GRBs). We implement the model on GRBs to show that the obtained range of the photon indices are well within their observed values. The analytic results are confirmed with numerical simulations following Monte Carlo approach., Comment: 4 pages, 2 figures

We solve the full quasilinear kinetic equation governing nonresonant interactions of Alfv\'en waves with relativistic plasmas. This work was motivated by the need to determine the energy available for the synchrotron maser in the context of Fast Radio Bursts (FRBs). This interaction can result in plasma heating and the formation of population inversions necessary for the maser. We find that population inversions containing $\sim 1-10\%$ of the distribution's energy form in the relativistic regime, providing an explanation for the formation of the inversion in the environment expected near FRBs., Comment: 7 pages, 2 figures, Accepted for publication in PRD

Autonomous driving and advanced driver-assistance systems rely on a set of sensors and algorithms to perform the appropriate actions and provide alerts as a function of the driving scene. Typically, the sensors include color cameras, radar, lidar and ultrasonic sensors. Strikingly however, although light polarization is a fundamental property of light, it is seldom harnessed for perception tasks. In this work we analyze the potential for improvement in perception tasks when using an RGB-polarimetric camera, as compared to an RGB camera. We examine monocular depth estimation and free space detection during the middle of the day, when polarization is independent of subject heading, and show that a quantifiable improvement can be achieved for both of them using state-of-the-art deep neural networks, with a minimum of architectural changes. We also present a new dataset composed of RGB-polarimetric images, lidar scans, GNSS / IMU readings and free space segmentations that further supports developing perception algorithms that take advantage of light polarization.

The Ultraviolet Transient Astronomy Satellite (ULTRASAT) is scheduled to be launched to geostationary orbit in 2026. It will carry a telescope with an unprecedentedly large field of view (204 deg$^2$) and NUV (230-290nm) sensitivity (22.5 mag, 5$\sigma$, at 900s). ULTRASAT will conduct the first wide-field survey of transient and variable NUV sources and will revolutionize our ability to study the hot transient universe: It will explore a new parameter space in energy and time-scale (months long light-curves with minutes cadence), with an extra-Galactic volume accessible for the discovery of transient sources that is $>$300 times larger than that of GALEX and comparable to that of LSST. ULTRASAT data will be transmitted to the ground in real-time, and transient alerts will be distributed to the community in $<$15 min, enabling a vigorous ground-based follow-up of ULTRASAT sources. ULTRASAT will also provide an all-sky NUV image to $>$23.5 AB mag, over 10 times deeper than the GALEX map. Two key science goals of ULTRASAT are the study of mergers of binaries involving neutron stars, and supernovae: With a large fraction ($>$50%) of the sky instantaneously accessible, fast (minutes) slewing capability and a field-of-view that covers the error ellipses expected from GW detectors beyond 2025, ULTRASAT will rapidly detect the electromagnetic emission following BNS/NS-BH mergers identified by GW detectors, and will provide continuous NUV light-curves of the events; ULTRASAT will provide early (hour) detection and continuous high (minutes) cadence NUV light curves for hundreds of core-collapse supernovae, including for rarer supernova progenitor types., Comment: 40 pages, 16 figures, 3 tables. Submitted to the AAS journals