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We consider quantum networks, where entangled photon pairs are distributed using fibre optic links from a centralized source to entangling nodes. The entanglement is then stored (via an entanglement swap) in entangling nodes' quantum memories until used in, e.g., distributed quantum computing, quantum key distribution, quantum sensing, and other applications. Due to the fibre loss, some photons are lost in transmission. Noise in the transmission link and the quantum memory also reduces fidelity. Thus, entangling nodes must keep updated records of photon-pair arrivals to each destination, and their use by the applications. This coordination requires classical information exchange between each entangled node pair. However, the same fibre link may not admit both classical and quantum transmissions, as the classical channels can generate enough noise (i.e., via spontaneous Raman scattering) to make the quantum link unusable. Here, we consider coordinating entanglement distribution using a standard Internet protocol (IP) network instead, and propose a control protocol to enable such. We analyse the increase in latency from transmission over an IP network, together with the effect of photon loss, quantum memory noise and buffer size, to determine the fidelity and rate of entangled pairs. We characterize the relationship between the latency of the non-ideal IP network and the decoherence time of the quantum memories, providing a comparison of promising quantum memory technologies.

Distributing entanglement over long distances remains a challenge due to its fragility when exposed to environmental effects. In this work, we compare various entanglement distribution protocols in a realistic noisy fiber network. We focus specifically on two schemes that only require the sending of a non-entangled carrier photon to remote nodes of the network. These protocols rely on optical CNOT gates and we vary the probability with which they can be successfully performed. Encoding our entangled states in photon polarization, we analyse the effect of depolarizing noise on the photonic states as the carrier passes through the fibers. Building a robust model of photon loss and calculating the distillable entanglement of the noisy states, we find the entanglement distribution rate. We discover that methods involving a separable carrier can reach a higher rate than the standard entanglement distribution protocol, provided that the success probability of the optical CNOT gates is sufficiently high., Comment: 12 pages, 10 figures. Comments welcome

We analyze the extraction of the rotational energy of a Kerr black hole (BH) endowed with a test charge and surrounded by an external test magnetic field and ionized low-density matter. For a magnetic field parallel to the BH spin, electrons move outward (inward) and protons inward (outward) in a region around the BH poles (equator). For zero charge, the polar region comprises spherical polar angles $-60^\circ\lesssim \theta \lesssim 60^\circ$ and the equatorial region $60^\circ\lesssim \theta \lesssim 120^\circ$. The polar region shrinks for positive charge, and the equatorial region enlarges. For an isotropic particle density, we argue the BH could experience a cyclic behavior: starting from a zero charge, it accretes more polar protons than equatorial electrons, gaining net positive charge, energy, and angular momentum. Then, the shrinking(enlarging) of the polar(equatorial) region makes it accrete more equatorial electrons than polar protons, gaining net negative charge, energy, and angular momentum. In this phase, the BH rotational energy is extracted. The extraction process continues until the new enlargement of the polar region reverses the situation, and the cycle repeats. We show that this electrodynamical process produces a relatively limited increase of the BH irreducible mass compared to gravitational mechanisms like the Penrose process, hence being a more efficient and promising mechanism for extracting the BH rotational energy., Comment: Accepted for publication in EPJC

The binary-driven hypernova (BdHN) model proposes long gamma-ray bursts (GRBs) originate in binaries composed of a carbon-oxygen (CO) star and a neutron star (NS) companion. The CO core collapse generates a newborn NS and a supernova that triggers the GRB by accreting onto the NSs, rapidly transferring mass and angular momentum to them. This article aims to determine the conditions under which a black hole (BH) forms from NS collapse induced by the accretion and the impact on the GRB observational properties and taxonomy. We perform three-dimensional, smoothed-particle-hydrodynamics simulations of BdHNe using up-to-date NS nuclear equations of state (EOS), with and without hyperons, and calculate the structure evolution in full general relativity. We assess the binary parameters leading either NS in the binary to the critical mass for gravitational collapse into a BH and its occurrence time, $t_{\rm col}$. We include a non-zero angular momentum of the NSs and find that $t_{\rm col}$ ranges from a few tens of seconds to hours for decreasing NS initial angular momentum values. BdHNe I are the most compact (about five minutes orbital period), promptly form a BH and release $\gtrsim 10^{52}$ erg. They form NS-BH binaries with tens of kyr merger timescale by gravitational-wave emission. BdHNe II and III do not form BHs, release $\sim 10^{50}$-$10^{52}$ erg and $\lesssim 10^{50}$ erg. They form NS-NS binaries with a range of merger timescales larger than for NS-BH binaries. In some compact BdHNe II, either NS can become supramassive, i.e., above the critical mass of a non-rotating NS. Magnetic braking by a $10^{13}$ G field can delay BH formation, leading to BH-BH or NS-BH of tens of kyr merger timescale., Comment: Version accepted for publication in The Astrophysical Journal

We consider a variational model of electrified liquid drops, involving competition between surface tension and charge repulsion. Since the natural model happens to be ill-posed, we show that by adding to the perimeter a Willmore-type energy, the problem turns back to be well-posed. We also prove that for small charge the droplets is spherical.

An increasing number of media streaming services have expanded their offerings to include entities of multiple content types. For instance, audio streaming services that started by offering music only, now also offer podcasts, merchandise items, and videos. Ranking items across different content types into a single slate poses a significant challenge for traditional learning-to-rank (LTR) algorithms due to differing user engagement patterns for different content types. We explore a simple method for cross-content-type ranking, called multinomial blending (MB), which can be used in conjunction with most existing LTR algorithms. We compare MB to existing baselines not only in terms of ranking quality but also from other industry-relevant perspectives such as interpretability, ease-of-use, and stability in dynamic environments with changing user behavior and ranking model retraining. Finally, we report the results of an A/B test from an Amazon Music ranking use-case., Comment: To appear in 18th ACM Conference on Recommender Systems (RecSys24), Bari, Italy. ACM, New York, NY, USA, 3 pages

Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances this capability by integrating diverse data types such as imaging, textual data, and genetic information, leading to more robust and accurate predictive models. In MDL, differently from early and late fusion methods, intermediate fusion stands out for its ability to effectively combine modality-specific features during the learning process. This systematic review aims to comprehensively analyze and formalize current intermediate fusion methods in biomedical applications. We investigate the techniques employed, the challenges faced, and potential future directions for advancing intermediate fusion methods. Additionally, we introduce a structured notation to enhance the understanding and application of these methods beyond the biomedical domain. Our findings are intended to support researchers, healthcare professionals, and the broader deep learning community in developing more sophisticated and insightful multimodal models. Through this review, we aim to provide a foundational framework for future research and practical applications in the dynamic field of MDL.

In the fight against the COVID-19 pandemic, leveraging artificial intelligence to predict disease outcomes from chest radiographic images represents a significant scientific aim. The challenge, however, lies in the scarcity of large, labeled datasets with compatible tasks for training deep learning models without leading to overfitting. Addressing this issue, we introduce a novel multi-dataset multi-task training framework that predicts COVID-19 prognostic outcomes from chest X-rays (CXR) by integrating correlated datasets from disparate sources, distant from conventional multi-task learning approaches, which rely on datasets with multiple and correlated labeling schemes. Our framework hypothesizes that assessing severity scores enhances the model's ability to classify prognostic severity groups, thereby improving its robustness and predictive power. The proposed architecture comprises a deep convolutional network that receives inputs from two publicly available CXR datasets, AIforCOVID for severity prognostic prediction and BRIXIA for severity score assessment, and branches into task-specific fully connected output networks. Moreover, we propose a multi-task loss function, incorporating an indicator function, to exploit multi-dataset integration. The effectiveness and robustness of the proposed approach are demonstrated through significant performance improvements in prognosis classification tasks across 18 different convolutional neural network backbones in different evaluation strategies. This improvement is evident over single-task baselines and standard transfer learning strategies, supported by extensive statistical analysis, showing great application potential.

In this paper we introduce a simple variational model describing the ground state of a superconducting charge qubit. The model gives rise to a shape optimization problem that aims at maximizing the number of qubit states at a given gating voltage. We show that for small values of the charge optimal shapes exist and are $C^{2,\alpha}$-nearly spherical sets. In contrast, for large values of the charge the optimal shape does not exist, with the energy favoring disjoint collections of sets., Comment: 33 pages

The concept of the irreducible mass ($M_{\rm irr}$) has led to the mass-energy ($M$) formula of a Kerr black hole (BH), in turn leading to its surface area $S=16\pi M_{\rm irr}^2$. This also allowed the coeval identification of the reversible and irreversible transformations, soon followed by the concepts of "extracted" and "extractable" energy. This new conceptual framework avoids inconsistencies recently evidenced in a repetitive Penrose process. We consider repetitive decays in the ergosphere of an initially extreme Kerr BH and show the processes are highly irreversible. For each decay, the particle that the BH captures causes an increase of the irreducible mass (so the BH horizon), much larger than the extracted energy. The energy extraction process stops {when the BH reaches a positive spin lower limit set by the process boundary conditions}. Thus, the reaching of a final non-rotating Schwarzschild BH state through this accretion process is impossible. We have assessed such processes for selected decay radii and incoming particle with rest mass $1\%$ of the BH initial mass $M_0$. For $r= 1.2 M$ and $1.9 M$, the sequence stops after $8$ and $34$ decays, respectively, at a spin $0.991$ and $0.857$, the energy extracted has been only $1.16\%$, and $0.42\%$, the extractable energy is reduced by $17\%$ and $56\%$, and the irreducible mass increases by $5\%$ and $22\%$, all values in units of $M_0$. These results show the highly nonlinear change of the BH parameters, dictated by the BH mass-energy formula, and that the BH rotational energy is mainly converted into irreducible mass. Thus, evaluating the irreducible mass increase in any energy extraction processes in the Kerr BH ergosphere is mandatory., Comment: Submitted to PRL. Revised version following Referees' reports

The observation of a gamma-ray burst (GRB) associated with a supernova (SN) coincides remarkably with the energy output from a binary system comprising a very massive carbon-oxygen (CO) core and an associated binary neutron star (NS) by the Binary-Driven Hypernova (BdHN) model. The dragging effect in the late evolution of such systems leads to co-rotation, with binary periods on the order of minutes, resulting in a very fast rotating core and a binary NS companion at a distance of $\sim 10^5$ km. Such a fast-rotating CO core, stripped of its hydrogen and helium, undergoes gravitational collapse and, within a fraction of seconds, leads to a supernova (SN) and a newly born, fast-spinning neutron star ($\nu$NS), we name the emergence of the SN and the $\nu$NS as the SN-rise and $\nu$NS-rise. Typically, the SN energies range from $10^{51}$ to $10^{53}$ erg. We address this issue by examining 10 cases of Type-I BdHNe, the most energetic ones, in which SN accretion onto the companion NS leads to the formation of a black hole (BH). In all ten cases, the energetics of the SN events are estimated, ranging between $0.18$ and $12 \times 10^{52}$ erg. Additionally, in all 8 sources at redshift $z$ closer than $4.61$, a clear thermal blackbody component has been identified, with temperatures between $6.2$ and $39.99$ keV, as a possible signature of pair-driven SN. The triggering of the X-ray afterglow induced by the $\nu$NS-rise are identified in three cases at high redshift where early X-ray observations are achievable, benefits from the interplay of cosmological effects., Comment: The previous version was uploaded on arXiv before being submitted to any Journal, this new version matches the one actually submitted for publication

Extracting the rotational energy from a Kerr black hole (BH) is one of the crucial topics in relativistic astrophysics. Here, we give special attention to the Penrose ballistic process based on the fission of a massive particle $\mu_0$ into two particles $\mu_1$ and $\mu_2$, occurring in the ergosphere of a Kerr BH. Bardeen et al. indicated that for the process to occur, some additional "hydrodynamical forces or superstrong radiation reactions" were needed. Wald and Chandrasekhar further expanded this idea. This animosity convinced T. Piran and collaborators to move from a simple three-body system characterizing the original Penrose process to a many-body system. This many-body approach was further largely expanded by others, some questionable in their validity. Here, we return to the simplest original Penrose process and show that the solution of the equations of motion, imposing the turning point condition on their trajectories, leads to the rotational energy extraction from the BH expected by Penrose. The efficiency of energy extraction by a single process is quantified for three different single decay processes occurring respectively at $r=1.2 M$, $r=1.5 M$, and $r=1.9 M$. An interesting repetitive model has been proposed by Misner, Thorne \& Wheeler (hereafter MTW73). Indeed, it would appear that a repetitive sequence of $246$ decays of the above injection process at $r=1.2 M$ and the corresponding ones at $r=1.5 M$ and $r=1.9 M$ could extract $100\%$ of the rotational energy of the BH, so violating energy conservation. The accompanying paper, accounting for the existence of the BH irreducible mass, introduces a non-linear approach that avoids violating energy conservation and leads to a new energy extraction process., Comment: Final version accepted by Physical Review Letters

Multiple visions of 6G networks elicit Artificial Intelligence (AI) as a central, native element. When 6G systems are deployed at a large scale, end-to-end AI-based solutions will necessarily have to encompass both the radio and the fiber-optical domain. This paper introduces the Decentralized Multi-Party, Multi-Network AI (DMMAI) framework for integrating AI into 6G networks deployed at scale. DMMAI harmonizes AI-driven controls across diverse network platforms and thus facilitates networks that autonomously configure, monitor, and repair themselves. This is particularly crucial at the network edge, where advanced applications meet heightened functionality and security demands. The radio/optical integration is vital due to the current compartmentalization of AI research within these domains, which lacks a comprehensive understanding of their interaction. Our approach explores multi-network orchestration and AI control integration, filling a critical gap in standardized frameworks for AI-driven coordination in 6G networks. The DMMAI framework is a step towards a global standard for AI in 6G, aiming to establish reference use cases, data and model management methods, and benchmarking platforms for future AI/ML solutions.

O-RAN introduces intelligent and flexible network control in all parts of the network. The use of controllers with open interfaces allow us to gather real time network measurements and make intelligent/informed decision. The work in this paper focuses on developing a use-case for open and reconfigurable networks to investigate the possibility to predict handover events and understand the value of such predictions for all stakeholders that rely on the communication network to conduct their business. We propose a Long-Short Term Memory Machine Learning approach that takes standard Radio Access Network measurements to predict handover events. The models were trained on real network data collected from a commercial O-RAN setup deployed in our OpenIreland testbed. Our results show that the proposed approach can be optimized for either recall or precision, depending on the defined application level objective. We also link the performance of the Machine Learning (ML) algorithm to the network operation cost. Our results show that ML-based matching between the required and available resources can reduce operational cost by more than 80%, compared to long term resource purchases.

We investigate resource allocation for quantum entanglement distribution over an optical network. We characterize and model a network architecture that employs a single quasi-deterministic time-frequency heralded Einstein-Podolsky-Rosen (EPR) pair source, and develop a routing scheme for distributing entangled photon pairs over such a network. We focus on max-min fairness in entanglement distribution and compare the performance of various spectrum allocation schemes by examining the max-min and median number of EPR-pairs assigned by them, and the Jain index associated with this assignment. Since this presents an NP-hard problem, we identify two approximation algorithms that outperform others in minimum and mean EPR-pair rate distribution and are comparable to others in the Jain index. We also analyze how the network size and connectivity affect these metrics using Watts-Strogatz random graphs. We find that a spectrum allocation approach that achieves high minimum EPR-pair rate can perform significantly worse when the median EPR-pair rate, Jain index, and runtimes are considered., Comment: originally appeared as arXiv:2311.14613v2 in error. arXiv admin note: text overlap with arXiv:2311.14613

We present a multi-tenant multi-wavelength upstream transmission scheme for virtualised PONs, enabling compliance with latency-oriented Service Level Agreements (SLAs). Our analysis highlights an important trade-off between single-channel vs. multi-channel PONs, depending on ONUs tuning time.

We present smoothed-particle-hydrodynamics (SPH) simulations of the binary-driven hypernova (BdHN) scenario of long gamma-ray bursts (GRBs), focusing on the binary stability during the supernova (SN) explosion. The BdHN progenitor is a binary comprised of a carbon-oxygen (CO) star and a neutron star (NS) companion. The core collapse of the CO leads to an SN explosion and a newborn NS ($\nu$NS) at its center. Ejected material accretes onto the NS and the $\nu$NS. BdHNe of type I have compact orbits of a few minutes, the NS reaches the critical mass, forming a black hole (BH), and the energy release is $\gtrsim 10^{52}$ erg. BdHNe II have longer periods of tens of minutes to hours; the NS becomes more massive, remains stable, and the system releases $\sim 10^{50}$-$10^{52}$ erg. BdHN III have longer periods, even days, where the accretion is negligible, and the energy released is $\lesssim 10^{50}$ erg. We assess whether the system remains gravitationally bound after the SN explosion, leading to an NS-BH in BdHN I, an NS-NS in BdHN II and III, or if the SN explosion disrupts the system. The existence of bound systems predicts an evolutionary connection between the long and short GRB populations. We determine the binary parameters for which the binary remains bound after the BdHN event. For these binaries, we derive fitting formulas of the numerical results for the main parameters, e.g., the mass loss, the SN explosion energy, orbital period, eccentricity, center-of-mass velocity, and the relation between the initial and final binary parameters, which are useful for outlined astrophysical applications., Comment: Submitted

We demonstrate a real-time, converged 5G-PON through the Cooperative Transport Interface, synchronising 5G and PON-DBA upstream schedulers. This innovative approach, implemented using 5G and PON open network implementations, significantly enhances network resource allocation, reducing latency.

Non-linear structure formation for fermionic dark matter particles leads to dark matter density profiles with a degenerate compact core surrounded by a diluted halo. For a given fermion mass, the core has a critical mass that collapses into a supermassive black hole (SMBH). Galactic dynamics constraints suggest a $\sim 100$ keV/$c^2$ fermion, which leads to $\sim 10^7 M_\odot$ critical core mass. Here, we show that baryonic (ordinary) matter accretion drives an initially stable dark matter core to SMBH formation and determine the accreted mass threshold that induces it. Baryonic gas density $\rho_b$ and velocity $v_b$ inferred from cosmological hydro-simulations and observations produce sub-Eddington accretion rates triggering the baryon-induced collapse in less than a Gyr. This process produces active galactic nuclei in galaxy mergers and the high-redshift Universe. For TXS 2116-077, merging with a nearby galaxy, the observed $3\times 10^7 M_\odot$ SMBH, for $Q_b = \rho_b/v_b^3 = 0.125 M_\odot/(100 \text{km/s pc})^3$, forms in $\approx 0.6$ Gyr, consistent with the $0.5$-$2$ Gyr merger timescale and younger jet. For the farthest central SMBH detected by the \textit{Chandra} X-ray satellite in the $z=10.3$ UHZ1 galaxy observed by the James Webb Space Telescope (\textit{JWST}), the mechanism leads to a $4\times 10^7 M_\odot$ SMBH in $87$-$187$ Myr, starting the accretion at $z=12$-$15$. The baryon-induced collapse can also explain the $\approx 10^7$-$10^8 M_\odot$ SMBHs revealed by the JWST at $z\approx 4$-$6$. After its formation, the SMBH can grow to a few $10^9 M_\odot$ in timescales shorter than a Gyr via sub-Eddington baryonic mass accretion., Comment: Accepted for publication in The Astrophysical Journal Letters

We investigate resource allocation for quantum entanglement distribution over an optical network. We characterize and model a network architecture that employs a single quasideterministic time-frequency heralded EPR-pair source, and develop a routing scheme for distributing entangled photon pairs over such a network. We focus on fairness in entanglement distribution, and compare both the performance of various spectrum allocation schemes as well as their Jain index.

"Clipping" (a.k.a. importance weight truncation) is a widely used variance-reduction technique for counterfactual off-policy estimators. Like other variance-reduction techniques, clipping reduces variance at the cost of increased bias. However, unlike other techniques, the bias introduced by clipping is always a downward bias (assuming non-negative rewards), yielding a lower bound on the true expected reward. In this work we propose a simple extension, called $\textit{double clipping}$, which aims to compensate this downward bias and thus reduce the overall bias, while maintaining the variance reduction properties of the original estimator., Comment: Presented at CONSEQUENCES '23 workshop at RecSys 2023 conference in Singapore

Efficient use of spectral resources will be an important aspect of converged access network deployment. This work analyzes the performance of variable bandwidth Analog Radio-over-Fiber signals transmitted in the unfilled spectral spaces of telecom-grade ROADM channels dedicated for coherent signals transmission over the OpenIreland testbed.

Internet of Things (IoT) systems require highly scalable infrastructure to adaptively provide services to meet various performance requirements. Combining Software-Defined Networking (SDN) with Mobile Edge Cloud (MEC) technology brings more flexibility for IoT systems. We present a four-tier task processing architecture for MEC and vehicular networks, which includes processing tasks locally within a vehicle, on neighboring vehicles, on an edge cloud, and on a remote cloud. The flexible network connection is controlled by SDN. We propose a CPU resource allocation algorithm, called Partial Idle Resource Strategy (PIRS) with Vehicle to Vehicle (V2V) communications, based on Asymmetric Nash Bargaining Solution (ANBS) in Game Theory. PIRS encourages vehicles in the same location to cooperate by sharing part of their spare CPU resources. In our simulations, we adopt four applications running on the vehicles to generate workload. We compare the proposed algorithm with Non-Cooperation Strategy (NCS) and All Idle Resource Strategy (AIRS). In NCS, the vehicles execute tasks generated by the applications in their own On-Board Units (OBU), while in AIRS vehicles provide all their CPU resources to help other vehicles offloading requests. Our simulation results show that our PIRS strategy can execute more tasks on the V2V layer and lead to fewer number of task (and their length) to be offloaded to the cloud, reaching up to 28% improvement compared to NCS and up to 10% improvement compared to AIRS., Comment: 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

We present a novel ML framework for modeling the wavelength-dependent gain of multiple EDFAs, based on semi-supervised, self-normalizing neural networks, enabling one-shot transfer learning. Our experiments on 22 EDFAs in Open Ireland and COSMOS testbeds show high-accuracy transfer-learning even when operated across different amplifier types., Comment: This paper is a preprint of a paper submitted to ECOC 2023 and is subject to Institution of Engineering and Technology Copyright. If accepted, the copy of record will be available at IET Digital Library

The binary-driven hypernova (BdHN) model explains long gamma-ray bursts (GRBs) associated with supernovae (SNe) Ic through physical episodes that occur in a binary composed of a carbon-oxygen (CO) star and a neutron star (NS) companion in close orbit. The CO core collapse triggers the cataclysmic event, originating the SN and a newborn NS (hereafter $\nu$NS) at its center. The $\nu$NS and the NS accrete SN matter. BdHNe are classified based on the NS companion fate and the GRB energetics, mainly determined by the orbital period. In BdHNe I, the orbital period is of a few minutes, so the accretion causes the NS to collapse into a Kerr black hole (BH), explaining GRBs of energies $>10^{52}$ erg. BdHN II, with longer periods of tens of minutes, yields a more massive but stable NS, accounting for GRBs of $10^{50}$--$10^{52}$ erg. BdHNe III have still longer orbital periods (e.g., hours), so the NS companion has a negligible role, which explains GRBs with a lower energy release of $<10^{50}$ erg. BdHN I and II might remain bound after the SN, so they could form NS-BH and binary NS (BNS), respectively. In BdHN III, the SN likely disrupts the system. We perform numerical simulations of BdHN II to compute the characteristic parameters of the BNS left by them, their mergers, and the associated short GRBs. We obtain the mass of the central remnant, whether it is likely to be a massive NS or a BH, the conditions for disk formation and its mass, and the event's energy release. The role of the NS nuclear equation of state is outlined., Comment: Published in Universe in the Special Issue Remo Ruffini Festschrift

The binary-driven hypernova (BdHN) model address long gamma-ray bursts (GRBs) associated with type Ic supernovae (SNe) through a series of physical episodes that occur in a binary composed of a carbon-oxygen (CO) star (of mass about 10 solar mass) and a neutron star (NS) companion (of mass about 2 solar mass) in a compact orbit. The SN explosion of the CO star triggers sequence of seven events. The BdHN model has followed the traditional picture of the SN from the CO iron's core collapse. However, the lack of a solution to the problem of producing successful SNe leaves room for alternative scenarios. We here show that tidal synchronization of the CO-NS binary can lead the CO star to critical conditions for fission, hence splitting into two stellar remnants, e.g., about 8.5 solar mass + 1.5 solar mass. We give specific examples of the properties of the products for various orbital periods relevant to BdHNe. The astrophysical consequences of this scenario are outlined.

The repointing time of the XRT instrument on the Neil Gehrels Swift Observatory satellite has posed challenges in observing and studying the early X-ray emissions within $\approx40$ s after a gamma-ray burst (GRB) trigger. To address this issue, we adopt a novel approach that capitalizes on the cosmological time dilation in GRBs with redshifts ranging from $3$ to $9$. Applying this strategy to Swift/XRT data, we investigate the earliest X-ray emissions of $368$ GRBs from the Swift catalog, including short and long GRBs. We compare the time delay between the GRB trigger and the initial Swift/XRT observation, measured in the GRB observer frame (OTD) and the cosmological rest-frame (RTD). This technique is here used in the analysis of GRB 090423 at $z=8.233$ (RTD $\sim8.2$ s), GRB 090429B at $z\approx9.4$ (RTD $\sim10.1$ s), and GRB 220101A at $z=4.61$ (RTD $\sim14.4$ s). The cosmological time dilation enables us to observe the very early X-ray afterglow emission in these three GRBs. We thus validate the observation of the collapse of the carbon-oxygen (CO) core and the coeval newborn neutron star ($\nu$NS) formation triggering the GRB event in the binary-driven hypernova (BdHN) scenario. We also evidence the $\nu$NS spin-up due to supernova ejecta fallback and its subsequent slowing down due to the X-optical-radio synchrotron afterglow emission. A brief gravitational wave signal may separate the two stages due to a fast-spinning $\nu$NS triaxial-to-axisymmetric transition. We also analyze the long GRB redshift distribution for the different BdHN types and infer that BdHNe II and III may originate the NS binary progenitors of short GRBs., Comment: Accepted by ApJ

Observations support the idea that supermassive black holes (SMBHs) power the emission at the center of active galaxies. However, contrary to stellar-mass BHs, there is a poor understanding of their origin and physical formation channel. In this article, we propose a new process of SMBH formation in the early Universe that is not associated with baryonic matter (massive stars) or primordial cosmology. In this novel approach, SMBH seeds originate from the gravitational collapse of fermionic dense dark matter (DM) cores that arise at the center of DM halos as they form. We show that such a DM formation channel can occur before star formation, leading to heavier BH seeds than standard baryonic channels. The SMBH seeds subsequently grow by accretion. We compute the evolution of the mass and angular momentum of the BH using a geodesic general relativistic disk accretion model. We show that these SMBH seeds grow to $\sim 10^9$-$10^{10} M_\odot$ in the first Gyr of the lifetime of the Universe without invoking unrealistic (or fine-tuned) accretion rates., Comment: 11 pages, 9 figures, 2 appendices. Accepted for publication in MNRAS

We consider a branched transport type problem which describes the magnetic flux through type-I superconductors in a regime of very weak applied fields. At the boundary of the sample, deviation of the magnetization from being uniform is penalized through a negative Sobolev norm. It was conjectured by S. Conti, F. Otto and S. Serfaty that as a result, the trace of the magnetization on the boundary should be a measure of Hausdorff dimension $8/5$. We prove that this conjecture is equivalent to the proof of local energy bounds with an optimal exponent. We then obtain local bounds which are however not optimal. These yield improved lower bounds on the dimension of the irrigated measure but unfortunately does not improve on the trivial upper bound. In order to illustrate the dependence of this dimension on the choice of penalization, we consider in the last part of the paper a toy model where the boundary energy is given by a Wasserstein distance to Lebesgue. In this case minimizers are finite graphs and thus the trace is atomic., Comment: 36 pages, 3 figures

The nature of dark matter (DM) is one of the most relevant questions in modern astrophysics. We present a brief overview of recent results that inquire into a possible fermionic quantum nature of the DM particles, focusing mainly on the interconnection between the microphysics of the neutral fermions and the macrophysical structure of galactic halos, including their formation both in the linear and non-linear cosmological regimes. We discuss the general relativistic Ruffini-Arg\"uelles-Rueda (RAR) model of fermionic DM in galaxies, its applications to the Milky Way, the possibility that the Galactic center harbors a DM core instead of a supermassive black hole (SMBH), the S-cluster stellar orbits with an in-depth analysis of the S2's orbit including precession, the application of the RAR model to other galaxy types (dwarf, elliptic, big elliptic and galaxy clusters), and universal galaxy relations. All the above focusing on the model parameters constraints, most relevant to the fermion mass. We also connect the RAR model fermions with particle physics DM candidates, self-interactions, and galactic observables constraints. The formation and stability of core-halo galactic structures predicted by the RAR model and their relation to warm DM cosmologies are also treated. Finally, we briefly discuss how gravitational lensing, dynamical friction, and the formation of SMBHs can also probe the DM nature., Comment: Review paper published in Universe, Special Issue "Galactic Center with Gravity"

The observations of supernovae (SNe) Ic occurring after the prompt emission of long gamma-ray bursts (GRBs) are addressed within the binary-driven hypernova (BdHN) model where GRBs originate from a binary composed of a $\sim10M_\odot$ carbon-oxygen (CO) star and a neutron star (NS). The CO core collapse gives the trigger, leading to a hypernova with a fast-spinning newborn NS ($\nu$NS) at its center. The evolution depends strongly on the binary period, $P_{\rm bin}$. For $P_{\rm bin}\sim5$min, BdHNe I occur with energies $10^{52}$--$10^{54}$erg. The accretion of SN ejecta onto the NS leads to its collapse, forming a black hole (BH) originating the MeV/GeV radiation. For $P_{\rm bin}\sim 10$min, BdHNe II occur with energies $10^{50}$--$10^{52}$erg and for $P_{\rm bin}\sim$hours, BdHN III occurs with energies below $10^{50}$erg. {In BdHNe II and III,} no BH is formed. The $1$--$1000$ms $\nu$NS originates, in all BdHNe, the X-ray-optical-radio afterglows by synchrotron emission. The hypernova follows an independent evolution, becoming an SN Ic, powered by nickel decay, observable after the GRB prompt emission. We report $24$ SNe Ic associated with BdHNe. Their optical peak luminosity and time of occurrence are similar and independent of the associated GRBs. {From previously identified $380$ BdHN I comprising redshifts up to $z=8.2$, we analyze} four examples with their associated hypernovae. By multiwavelength extragalactic observations, we identify seven new Episodes, theoretically explained, fortunately not yet detected in galactic sources, opening new research areas. Refinement of population synthesis simulations is needed to map the progenitors of such short-lived binary systems inside our galaxy., Comment: Accepted for publication in The Astrophysical Journal

It has been thought for decades that rotating black holes (BHs) power the energetic gamma-ray bursts (GRBs) and active galactic nuclei (AGNs), but the mechanism that extracts the BH energy has remained elusive. We here show that the solution to this problem arises when the BH is immersed in an external magnetic field and ionized low-density matter. For a magnetic field parallel to the BH spin, the induced electric field accelerates electrons outward and protons inward in a conical region, centered on the BH rotation axis, and of semi-aperture angle $\theta \approx 60^\circ$ from the BH rotation axis. For an antiparallel magnetic field, protons and electrons exchange their roles. The particles that are accelerated outward radiate off energy and angular momentum to infinity. The BH powers the process by reducing its energy and angular momentum by capturing polar protons and equatorial electrons with net negative energy and angular momentum. The electric potential allows for negative energy states outside the BH ergosphere, so the latter does not play any role in this electrodynamical BH energy extraction process., Comment: To be published in EPJC