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Gravitational waves (GWs) from binary neutron star (BNS) merger remnants complement constraints from the inspiral phase, mass-radius measurements, and microscopic theory by providing information about the neutron-star equation of state (EOS) at extreme densities. We perform general-relativistic simulations of BNS mergers using EOS models that span the uncertain high-density regime. We find a robust correlation between the ratio of energy and angular momentum lost during the late-time post-merger GW signal - the long ringdown - and the EOS at the highest densities in neutron star cores. Applying this correlation to post-merger GW signals reduces EOS uncertainty at several times saturation density, where no direct constraints currently exist.

The strong gravitational field of a black hole bends light, forming multi-level images, yet extracting precise spacetime information from them remains challenging. In this study, we investigate how gravitational lensing leaves unique and detectable signatures in black hole movies using autocorrelation analysis. By examining the two-dimensional autocorrelation of a movie depicting a hotspot orbiting a Kerr black hole, as viewed by a near-axis observer, we identify a persistent secondary peak structure induced by gravitational lensing. Notably, these secondary peaks converge toward an approximately fixed point in the time-angle lag domain, largely independent of the orbital radius of the hotspot. This key property suggests that combining future flare observations with precise autocorrelation analysis could effectively disentangle lensing effects from orbital dynamics, enabling direct measurement of black hole parameters.

Multimessenger signals from binary neutron star (BNS) mergers are promising tools to infer the largely unknown properties of nuclear matter at densities that are presently inaccessible to laboratory experiments. The gravitational waves (GWs) emitted by BNS merger remnants, in particular, have the potential of setting tight constraints on the neutron-star equation of state (EOS) that would complement those coming from the late inspiral, direct mass-radius measurements, or ab-initio dense-matter calculations. To explore this possibility, we perform a representative series of general-relativistic simulations of BNS systems with EOSs carefully constructed so as to cover comprehensively the high-density regime of the EOS space. From these simulations, we identify a novel and tight correlation between the ratio of the energy and angular-momentum losses in the late-time portion of the post-merger signal, i.e., the ``long ringdown'', and the properties of the EOS at the highest pressures and densities in neutron-star cores. When applying this correlation to post-merger GW signals, we find a significant reduction of the EOS uncertainty at densities several times the nuclear saturation density, where no direct constraints are currently available. Hence, the long ringdown has the potential of providing new and stringent constraints on the state of matter in neutron stars in general and, in particular, in their cores.

The continued development of computational approaches to many-body ground-state problems in physics and chemistry calls for a consistent way to assess its overall progress. In this work, we introduce a metric of variational accuracy, the V-score, obtained from the variational energy and its variance. We provide an extensive curated dataset of variational calculations of many-body quantum systems, identifying cases where state-of-the-art numerical approaches show limited accuracy, and future algorithms or computational platforms, such as quantum computing, could provide improved accuracy. The V-score can be used as a metric to assess the progress of quantum variational methods toward a quantum advantage for ground-state problems, especially in regimes where classical verifiability is impossible.

Black hole - neutron star (BHNS) mergers are a promising target of current gravitational-wave (GW) and electromagnetic (EM) searches, being the putative origin of ultra-relativistic jets, gamma-ray emission, and r-process nucleosynthesis. However, the possibility of any EM emission accompanying a GW detection crucially depends on the amount of baryonic mass left after the coalescence, i.e. whether the neutron star (NS) undergoes a `tidal disruption' or `plunges' into the black hole (BH) while remaining essentially intact. As the first of a series of two papers, we here report the most systematic investigation to date of quasi-equilibrium sequences of initial data across a range of stellar compactnesses $\mathcal{C}$, mass ratios $q$, BH spins $\chi_{_{\rm BH}}$, and equations of state satisfying all present observational constraints. Using an improved version of the elliptic initial-data solver FUKA, we have computed more than$1000$individual configurations and estimated the onset of mass-shedding or the crossing of the innermost stable circular orbit in terms of the corresponding characteristic orbital angular velocities$\Omega_{_{\rm MS}}$and$\Omega_{_{\rm ISCO}}$as a function of$\mathcal{C}, q$, and$\chi_{_{\rm BH}}$. To the best of our knowledge, this is the first time that the dependence of these frequencies on the BH spin is investigated. In turn, by setting$\Omega_{_{\rm MS}} = \Omega_{_{\rm ISCO}}$it is possible to determine the separatrix between the `tidal disruption' or `plunge' scenarios as a function of the fundamental parameters of these systems, namely,$q, \mathcal{C}$, and$\chi_{_{\rm BH}}$. Finally, we present a novel analysis of quantities related to the tidal forces in the initial data and discuss their dependence on spin and separation.

Community detection, also known as graph partitioning, is a well-known NP-hard combinatorial optimization problem with applications in diverse fields such as complex network theory, transportation, and smart power grids. The problem's solution space grows drastically with the number of vertices and subgroups, making efficient algorithms crucial. In recent years, quantum computing has emerged as a promising approach to tackling NP-hard problems. This study explores the use of a quantum-inspired algorithm, Simulated Bifurcation (SB), for community detection. Modularity is employed as both the objective function and a metric to evaluate the solutions. The community detection problem is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling seamless integration with the SB algorithm. Experimental results demonstrate that SB effectively identifies community structures in benchmark networks such as Zachary's Karate Club and the IEEE 33-bus system. Remarkably, SB achieved the highest modularity, matching the performance of Fujitsu's Digital Annealer, while surpassing results obtained from two quantum machines, D-Wave and IBM. These findings highlight the potential of Simulated Bifurcation as a powerful tool for solving community detection problems.

Future black hole (BH) imaging observations are expected to resolve finer features corresponding to higher-order images of hotspots and of the horizon-scale accretion flow. In spherical spacetimes, the image order is determined by the number of half-loops executed by the photons that form it. Consecutive-order images arrive approximately after a delay time of $\approx\pi$ times the BH shadow radius. The fractional diameters, widths, and flux-densities of consecutive-order images are exponentially demagnified by the lensing Lyapunov exponent, a characteristic of the spacetime. The appearance of a simple point-sized hotspot when located at fixed spatial locations or in motion on circular orbits is investigated. The exact time delay between the appearance of its zeroth and first-order images agrees with our analytic estimate, which accounts for the observer inclination, with $\lesssim 20\%$ error for hotspots located about $\lesssim 5M$ from a Schwarzschild BH of mass $M$. Since M87$^\star$ and Sgr A$^\star$ host geometrically-thick accretion flows, we also explore the variation in the diameters and widths of their first-order images with disk scale-height. Using a simple conical torus model, for realistic morphologies, we estimate the first-order image diameter to deviate from that of the shadow by $\lesssim 30\%$ and its width to be $\lesssim 1.3M$. Finally, the error in recovering the Schwarzschild lensing exponent ($\pi$), when using the diameters or the widths of the first and second-order images is estimated to be $\lesssim 20\%$. It will soon become possible to robustly learn more about the spacetime geometry of astrophysical BHs from such measurements.

Reflection of X-rays at the inner accretion disk around black holes imprints relativistically broadened features in the observed spectrum. Besides the black hole properties and the ionization and density of the accretion disk the features also depend on the location and geometry of the primary source of X-rays, often called the corona. We present a fast general relativistic model for spectral fitting of a radially extended, ring-like corona above the accretion disk. A commonly used model to explain observed X-ray reflection spectra is the lamp post, which assumes a point-like source on the rotational axis of the black hole. While often being able to explain the observations, this geometric model does not allow for a constraint on the radial size of the corona. We therefore extend the publicly available relativistic reflection model RELXILL by implementing a radially extended, ring-like primary source. With the new RELXILL model allowing us to vary the position of the primary source in two dimensions, we present simulated line profiles and spectra and discuss implications of data fitting compared to the lamp post model. We then apply this extended RELXILL model to XMM-Newton and NuSTAR data of the radio-quiet Seyfert-2 AGN ESO 033-G002. The new model describes the data well, and we are able to constrain the distance of the source to the black hole to be less than three gravitational radii, while the angular position of the source is poorly constrained. We show that a compact, radially extended corona close to the ISCO can explain the observed relativistic reflection equally well as the point-like lamp post corona. The model is made freely available to the community.

Electromagnetic fields surrounding pulsars may source coherent ultralight axion signals at the known rotational frequencies of the neutron stars, which can be detected by laboratory experiments (e.g., pulsarscopes). As a promising case study, we model axion emission from the well-studied Crab pulsar, which would yield a prominent signal at $f \approx 29.6$ Hz regardless of whether the axion contributes to the dark matter abundance. We estimate the relevant sensitivity of future axion dark matter detection experiments such as DMRadio-GUT, Dark SRF, and CASPEr, assuming different magnetosphere models to bracket the uncertainty in astrophysical modeling. For example, depending on final experimental parameters, the Dark SRF experiment could probe axions with any mass $m_a \ll 10^{-13}$ eV down to $g_{a\gamma\gamma} \sim 3 \times 10^{-13}$ GeV$^{-1}$ with one year of data and assuming the vacuum magnetosphere model. These projected sensitivities may be degraded depending on the extent to which the magnetosphere is screened by charge-filled plasma. The promise of pulsar-sourced axions as a clean target for direct detection experiments motivates dedicated simulations of axion production in pulsar magnetospheres.

The stellar compactness, that is, the dimensionless ratio between the mass and radius of a compact star, $\mathcal{C} := M/R$, plays a fundamental role in characterising the gravitational and nuclear-physics aspects of neutron stars. Yet, because the compactness depends sensitively on the unknown equation of state (EOS) of nuclear matter, the simple question: ``how compact can a neutron star be?'' remains unanswered. To address this question, we adopt a statistical approach and consider a large number of parameterised EOSs that satisfy all known constraints from nuclear theory, perturbative Quantum Chromodynamics (QCD), and astrophysical observations. Next, we conjecture that, for any given EOS, the maximum compactness is attained by the star with the maximum mass of the sequence of nonrotating configurations. While we can prove this conjecture for a rather large class of solutions, its general proof is still lacking. However, the evidence from all of the EOSs considered strongly indicates that it is true in general. Exploiting the conjecture, we can concentrate on the compactness of the maximum-mass stars and show that an upper limit appears for the maximum compactness and is given by $\mathcal{C}_{\rm max} = 1/3$. Importantly, this upper limit is essentially independent of the stellar mass and a direct consequence of perturbative-QCD constraints.

We present a comprehensive investigation into the phenomenological consequences of axion-like particle (ALP) mediated dark matter (DM) on neutron star (NS) structure. Using a relativistic mean-field framework with non-linear mesonic self-interactions constrained by nuclear data and astrophysical observations, we explore the DM parameter space spanning $m_\chi \in [0, 1000]~\mathrm{GeV}$ and $q_f \in [0, 0.06]~\mathrm{GeV}$, generating over 30,000 equations of state (EoSs). Two representative hadronic EoSs are employed, a stiff (EoS1) and a soft (EoS18), with explicit inclusion of the crustal EoS. A multi-tiered statistical filtering scheme, combining voting, likelihood, and kernel density estimation scores, is applied using constraints from radio and X-ray pulsars, GW170817, and the low-mass compact object HESS J1731-347. We find that models satisfying the PSR J0614$-$3329 radius bound automatically comply with HESS, positioning ALP-mediated DM as a viable explanation for low-mass compact objects while still supporting $2\,M_\odot$ NSs. For the stiff EoS, we obtain $m_\chi \gtrsim 43~\mathrm{GeV}$, with score-weighted posteriors favoring $q_f = 0.034^{+0.020}_{-0.012}$ and a broad allowed DM mass range $m_\chi \in [101, 949]~\mathrm{GeV}$ (median $\sim 466$ GeV). The soft EoS yields no strict lower bound, though large $m_\chi$--$q_f$ combinations are disfavored. A high-precision supervised regression model built with AutoGluon achieves $R^2 > 0.998$ for inferring DM parameters from NS observables. Feature analysis reveals $m_\chi$ is constrained by structural ratios such as $R_{1.6}/R_{1.4}$, whereas $q_f$ is set mainly by the tidal deformability $\Lambda_{1.4}$.

We present a newly developed hybrid hadronic transport + hydrodynamics framework geared towards heavy ion collisions at low to intermediate beam energies, and report on the resulting excitation function of dileptons. In this range of energies, it is unclear how to properly initialize the hydrodynamic evolution. Due to the cumulative electromagnetic radiation throughout the collision, dilepton observables are sensitive to the initial condition. In this work, we study how the dilepton ``thermometer'' is affected by employing dynamical initial conditions, in contrast to the traditional fixed-time approach.

Black hole (BH) - neutron star (NS) binary mergers are not only strong sources of gravitational waves (GWs), but they are also candidates for joint detections in the GW and electromagnetic (EM) spectra. However, the possible emergence of an EM signal from these binaries is determined by a complex combination of the equation of state (EOS), the BH spin, and the mass ratio. In this second paper in a series, we present a systematic exploration of the possible space of binary parameters in terms of the mass ratio and BH spin so as to construct a complete description of the dynamical processes accompanying a BHNS binary merger. This second work relies not only on the initial data presented in the companion paper I, but also on the predictions via quasi-equilibrium (QE) sequences on the outcome of the binary. In this way, and for the first time, we are able to relate the predictions of QE analyses with the results of accurate general-relativistic magnetohydrodynamic simulations. In addition to a careful investigation of the evolution of the BH mass and spin as a result of the merger, the total remnant rest-mass of the resulting accretion disk and its properties, and of the corresponding post-merger GW emission, special attention is paid to the conditions that lead to tidal disruption. Leveraging QE calculations, we are able to verify the reliability of stringent predictions about the occurrence or not of a plunge and to measure the `strength' of the tidal disruption when it takes place. Finally, using a novel contraction of the Riemann tensor in a tetrad comoving with the fluid introduced in paper I, we are able to point out the onset of the instability to tidal disruption. This new diagnostic can be employed not only to determine the occurrence of the disruption, but also to characterize it in terms of the binary parameters.

We present results for the chromo-electric field generated by a static quark-antiquark pair at finite temperature, in lattice QCD with 2+1 dynamical staggered fermions at physical quark masses. We investigate the evolution of the field as the temperature increases through and beyond the chiral transition. For all the temperatures considered we find clear evidence of a chromo-magnetic current and of a longitudinal nonperturbative chromo-electric field that stays almost uniform along the flux tube. In the high-temperature region the magnitude of the flux-tube field is determined by an effective string tension that decreases exponentially as the temperature increases, while the flux-tube width decreases according to an inverse-temperature law. Our results suggest that beyond the chiral pseudocritical temperature the quark-antiquark system can be characterized by a screened string tension.

Stochastic thermodynamics is the field of study relating fluctuations in stochastic systems to thermodynamic quantities. The total entropy production (EP), is central to the thermodynamic classification of systems. Non-equilibrium systems manifestly all have non-zero EP and therefore impose an "arrow of time". Thermodynamic inequalities are lower bounds on the total EP and are especially useful when only parts of systems are operationally accessible. We use a stochastic calculus approach to directly derive and generalise three classes of inequalities for Markov jump processes using correlations of path observables, e.g., currents and densities. Our theoretical predictions are compared with simulations, where a good agreement is observed. The thermodynamic bounds we investigate include the thermodynamic uncertainty relation (TUR), thermodynamic transport bound (TB), and thermodynamic correlation bound (CB). We provide insight into the saturation conditions for these bounds and to what degree saturation can be achieved. Additionally, for the TUR and TB, we show how the bounds are related, which includes identifying a diffusion coefficient for jump dynamics. %An example using a toy model shows how the CB may yield a negative lower bound on the total entropy production, contrary to the non-negative bound that the TUR and TB yield. Comparisons are drawn between the TUR and TB for relaxation and stationary processes in biologically relevant settings. Specifically, calmodulin folding dynamics and secondary active transport, where differences in long-time relaxation and convergence are observed. For a systematic way to construct models, we formulate two methods to drive systems out of equilibrium without changing the stationary probability distribution.

At the earliest times after a heavy-ion collision, the magnetic field created by the spectator nucleons will generate an extremely strong, albeit rapidly decreasing in time, magnetic field. The impact of this magnetic field may have detectable consequences, and is believed to drive anomalous transport effects like the Chiral Magnetic Effect (CME). We detail an exploratory study on the effects of a dynamical magnetic field on the hydrodynamic medium created in the collisions of two ultrarelativistic heavy-ions, using the framework of numerical ideal MagnetoHydroDynamics (MHD) with the ECHO-QGP code. In this study, we consider a magnetic field captured in a conducting medium, where the conductivity can receive contributions from the electromagnetic conductivity $\sigma$ and the chiral magnetic conductivity $\sigma_{\chi}$. We first study the elliptic flow of pions, which we show is relatively unchanged by the introduction of a magnetic field. However, by increasing the magnitude of the magnetic field, we find evidence for an enhancement of the elliptic flow in peripheral collisions. Next, we explore the impact of the chiral magnetic conductivity on electric charges produced at the edges of the fireball. This initial $\sigma_\chi$ can be understood as a long-wavelength effective description of chiral fermion production. We then demonstrate that this chiral charge, when transported by the MHD medium, produces a charge dipole perpendicular to the reaction plane which extends a few units in rapidity. Assuming charge conservation at the freeze-out surface, we show that the produced charge imbalance can have measurable effects on some experimental observables, like $v_1$ or $\langle \sin \phi \rangle$. This demonstrates the ability of a MHD fluid to transport the signature of the initial chiral magnetic fields to late times.

We introduce Net2Brain, a graphical and command-line user interface toolbox for comparing the representational spaces of artificial deep neural networks (DNNs) and human brain recordings. While different toolboxes facilitate only single functionalities or only focus on a small subset of supervised image classification models, Net2Brain allows the extraction of activations of more than 600 DNNs trained to perform a diverse range of vision-related tasks (e.g semantic segmentation, depth estimation, action recognition, etc.), over both image and video datasets. The toolbox computes the representational dissimilarity matrices (RDMs) over those activations and compares them to brain recordings using representational similarity analysis (RSA), weighted RSA, both in specific ROIs and with searchlight search. In addition, it is possible to add a new data set of stimuli and brain recordings to the toolbox for evaluation. We demonstrate the functionality and advantages of Net2Brain with an example showcasing how it can be used to test hypotheses of cognitive computational neuroscience.