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This summary of the second Terrestrial Very-Long-Baseline Atom Interferometry (TVLBAI) Workshop provides a comprehensive overview of our meeting held in London in April 2024, building on the initial discussions during the inaugural workshop held at CERN in March 2023. Like the summary of the first workshop, this document records a critical milestone for the international atom interferometry community. It documents our concerted efforts to evaluate progress, address emerging challenges, and refine strategic directions for future large-scale atom interferometry projects. Our commitment to collaboration is manifested by the integration of diverse expertise and the coordination of international resources, all aimed at advancing the frontiers of atom interferometry physics and technology, as set out in a Memorandum of Understanding signed by over 50 institutions., Comment: Summary of the second Terrestrial Very-Long-Baseline Atom Interferometry Workshop held at Imperial College London: https://indico.cern.ch/event/1369392/

We investigate ensembles of Matrix Product States (MPSs) generated by quantum circuit evolution followed by projection onto MPSs with a fixed bond dimension $\chi$. Specifically, we consider ensembles produced by: (i) random sequential unitary circuits, (ii) random brickwork unitary circuits, and (iii) circuits involving both unitaries and projective measurements. In all cases, we characterize the spectra of the MPS transfer matrix and show that, for the first two cases in the thermodynamic limit, they exhibit a finite universal value of the spectral gap in the limit of large $\chi$, albeit with different spectral densities. We show that a finite gap in this limit does not imply a finite correlation length, as the mutual information between two large subsystems increases with $\chi$ in a manner determined by the entire shape of the spectral density. The latter differs for different types of circuits, indicating that these ensembles of MPS retain relevant physical information about the underlying microscopic dynamics. In particular, in the presence of monitoring, we demonstrate the existence of a measurement-induced entanglement transition (MIPT) in MPS ensembles, with the averaged dimension of the transfer matrix's null space serving as the effective order parameter.

Bayesian analysis has begun to be more widely adopted in X-ray spectroscopy, but it has largely been constrained to relatively simple physical models due to limitations in X-ray modelling software and computation time. As a result, Bayesian analysis of numerical models with high physics complexity have remained out of reach. This is a challenge, for example when modelling the X-ray emission of accreting black hole X-ray binaries, where the slow model computations severely limit explorations of parameter space and may bias the inference of astrophysical parameters. Here, we present RTFAST-Spectra: a neural network emulator that acts as a drop in replacement for the spectral portion of the black hole X-ray reverberation model RTDIST. This is the first emulator for the reltrans model suite and the first emulator for a state-of-the-art x-ray reflection model incorporating relativistic effects with 17 physically meaningful model parameters. We use Principal Component Analysis to create a light-weight neural network that is able to preserve correlations between complex atomic lines and simple continuum, enabling consistent modelling of key parameters of scientific interest. We achieve a $\mathcal{O}(10^2)$ times speed up over the original model in the most conservative conditions with $\mathcal{O}(1\%)$ precision over all 17 free parameters in the original numerical model, taking full posterior fits from months to hours. We employ Markov Chain Monte Carlo sampling to show how we can better explore the posteriors of model parameters in simulated data and discuss the complexities in interpreting the model when fitting real data., Comment: 22 pages, 35 figures. Submitted to MNRAS

We introduce an efficient method to quantify nonstabilizerness in fermionic Gaussian states, overcoming the long-standing challenge posed by their extensive entanglement. Using a perfect sampling scheme based on an underlying determinantal point process, we compute the Stabilizer R\'enyi Entropies (SREs) for systems with hundreds of qubits. Benchmarking on random Gaussian states with and without particle conservation, we reveal an extensive leading behavior equal to that of Haar random states, with logarithmic subleading corrections. We support these findings with analytical calculations for a set of related quantities, the participation entropies in the computational (or Fock) basis, for which we derive an exact formula. Applying the sampling algorithm to a two-dimensional free-fermionic topological model, we uncover a sharp transition in magic at the topological phase boundary, highlighting the power of our approach in exploring different phases of quantum many-body systems, even in higher dimensions.

We examine the correlations between new scalar boson decays to photons and electric dipole moments (EDMs) in the CP-violating flavor-aligned two-Higgs-doublet model (2HDM). It is convenient to work in the Higgs basis $\{{H}_1, {H}_2\}$ where only the first Higgs doublet field ${H}_1$ acquires a vacuum expectation value. In light of the LHC Higgs data, which agree well with Standard Model (SM) predictions, it follows that the parameters of the 2HDM are consistent with the Higgs alignment limit. In this parameter regime, the observed SM-like Higgs boson resides almost entirely in ${H}_1$, and the other two physical neutral scalars, which reside almost entirely in ${H}_2$, are approximate eigenstates of CP (denoted by the CP-even $H$ and the CP-odd $A$). In the Higgs basis, the scalar potential term $\bar{Z}_7 {H}_1^\dagger {H}_2 {H}_2^\dagger {H}_2+{\rm h.c.}$ governs the charged-Higgs loop contributions to the decay of $H$ and $A$ to photons. If $ \text{Re } \bar{Z}_7 \, \text{Im } \bar{Z}_7 \neq 0$, then CP-violating effects are present and allow for an $H^+ H^- A$ coupling, which can yield a sizable branching ratio for $A\to\gamma\gamma$. These CP-violating effects also generate non-zero EDMs for the electron, the neutron and the proton. We examine these correlations for the cases of $m_{A}=95$ GeV and $m_{A}=152$ GeV where interesting excesses in the diphoton spectrum have been observed at the LHC. These excesses can be explained via the decay of $A$ while being consistent with the experimental bound for the electron EDM in regions of parameter space that can be tested with future neutron and proton EDM measurements. This allows for the interesting possibility where the 95 GeV diphoton excess can be identified with $A$, while $m_H\simeq 98$ GeV can account for the best fit to the LEP excess in $e^+e^-\to ZH$ with $H\to b\bar b$., Comment: 13 pages, 3 figures; V2: Updated references

In this article, we examine the Standard Model extended by a $Y=0$ real Higgs triplet, the $\Delta$SM. It contains a $CP$-even neutral Higgs ($\Delta^0$) and two charged Higgs bosons ($\Delta^\pm$), which are quasi-degenerate in mass. We first study the theoretical constraints from vacuum stability and perturbative unitarity and then calculate the Higgs decays, including the loop-induced modes such as di-photons ($\gamma\gamma$) and $Z\gamma$. In the limit of a small mixing between the SM Higgs and $\Delta^0$, the latter decays dominantly to $WW$ and can have a sizable branching ratio to di-photon. The model predicts a positive definite shift in the $W$ mass, which agrees with the current global electroweak fit. At the Large Hadron Collider, it leads to a $(i)$ stau-like signature from $pp\to \Delta^+\Delta^-\to \tau^+\tau^-\nu\bar\nu$, $(ii)$ multi-lepton final states from $pp\to \gamma^*\to \Delta^+\Delta^-\to W^+W^-ZZ$ and $pp\to W^{*} \to \Delta^\pm\Delta^0\to W^\pm Z W^+W^-$ as well as $(iii)$ associated di-photon production from $pp\to W^{*} \to \Delta^\pm(\Delta^0\to\gamma\gamma)$. Concerning $(i)$, the reinterpretation of the recent supersymmetric tau partner search by ATLAS and CMS excludes $m_{\Delta^\pm}<110$ GeV at 95% CL. From $(ii)$, some of the signal regions of multi-lepton searches lead to bounds close to the predicted cross-section, but electroweak scale masses are still allowed. For $(iii)$, the recast of the associated di-photon searches by ATLAS and a combined log-likelihood fit of signal and background to data find that out of the 25 signal regions, 10 provide relevant limits on Br$(\Delta^0\to\gamma\gamma)$ at the per cent level. Interestingly, 6 signal regions show excesses at around 152 GeV, leading to a preference for a non-zero di-photon branching ratio of about 0.7% with the corresponding significance amounting to about $4\sigma$., Comment: 62 pages, 21 figures

This work focuses on the analysis of the spectral $\zeta$-function associated with a Schr\"{o}dinger operator endowed with a P\"oschl--Teller potential. We construct the spectral $\zeta$-function using a contour integral representation and, for particular self-adjoint extensions, we perform its analytic continuation to a larger region of the complex plane. We show that the spectral $\zeta$-function in these cases can possess a very unusual and remarkable structure consisting of a series of logarithmic branch points located at every nonpositive integer value of $s$ along with infinitely many additional branch points (and finitely many simple poles) whose locations depend on the parameters of the problem. By comparing the P\"oschl--Teller potential to the classic Bessel potential, we further illustrate that perturbing a given potential by a smooth potential on a finite interval can greatly affect the meromorphic structure and branch points of the spectral $\zeta$-function in surprising ways., Comment: 33 pages, LaTex

We perform a comprehensive analysis of the quantum-enhanced Monte Carlo method [Nature, 619, 282-287 (2023)], aimed at identifying the optimal working point of the algorithm. We observe an optimal mixing Hamiltonian strength and analyze the scaling of the total evolution time with the size of the system. We also explore extensions of the circuit, including the use of time-dependent Hamiltonians and reverse digitized annealing. Additionally, we propose that classical, approximate quantum simulators can be used for the proposal step instead of the original real-hardware implementation. We observe that tensor-network simulators, even with unconverged settings, can maintain a scaling advantage over standard classical samplers. This may extend the utility of quantum enhanced Monte Carlo as a quantum-inspired algorithm, even before the deployment of large-scale quantum hardware., Comment: JC and PI contributed equally

Here we present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic for a superconducting transmon-based quantum computer based on simulated studies. Our approach is multi-stage. We first bootstrap a model based on simulation with access to the full statevector for measuring gate fidelity. We next present an algorithm, named adapted randomized benchmarking (ARB), for fine-tuning the gate on hardware based on measurements of the devices. We also present techniques for deploying the model on programmable devices with care to reduce the required resources. While the techniques here are applied to a transmon-based computer, many of them are portable to other architectures.

Parallel-in-time (PinT) techniques have been proposed to solve systems of time-dependent differential equations by parallelizing the temporal domain. Among them, Parareal computes the solution sequentially using an inaccurate (fast) solver, and then "corrects" it using an accurate (slow) integrator that runs in parallel across temporal subintervals. This work introduces RandNet-Parareal, a novel method to learn the discrepancy between the coarse and fine solutions using random neural networks (RandNets). RandNet-Parareal achieves speed gains up to x125 and x22 compared to the fine solver run serially and Parareal, respectively. Beyond theoretical guarantees of RandNets as universal approximators, these models are quick to train, allowing the PinT solution of partial differential equations on a spatial mesh of up to $10^5$ points with minimal overhead, dramatically increasing the scalability of existing PinT approaches. RandNet-Parareal's numerical performance is illustrated on systems of real-world significance, such as the viscous Burgers' equation, the Diffusion-Reaction equation, the two- and three-dimensional Brusselator, and the shallow water equation., Comment: Accepted at the 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

We address the critical need for accurate Rosseland mean gas opacities in high-pressure environments, spanning temperatures from 100 K to 32000 K. Current opacity tables from Wichita State University and AESOPUS 2.0 are limited to $\log(R) \le 1$, where $R=\rho\, T_6^{-3}$ in units of $\mathrm{g}\,\mathrm{cm}^{-3}(10^6\mathrm{K})^{-3}$. This is insufficient for modeling very low-mass stars, brown dwarfs, and planets with atmospheres exhibiting higher densities and pressures ($\log(R) > 1$). Leveraging extensive databases such as ExoMol, ExoMolOP, MoLLIST, and HITEMP, we focus on expanding the AESOPUS opacity calculations to cover a broad range of pressure and density conditions ($-8 \leq \log(R) \leq +6$). We incorporate the thermal Doppler mechanism and micro-turbulence velocity. Pressure broadening effects on molecular transitions, leading to Lorentzian or Voigt profiles, are explored in the context of atmospheric profiles for exoplanets, brown dwarfs, and low-mass stars. We also delve into the impact of electron degeneracy and non-ideal effects such as ionization potential depression under high-density conditions, emphasizing its notable influence on Rosseland mean opacities at temperatures exceeding $10,000$ K. As a result, this study expands AESOPUS public web interface for customized gas chemical mixtures, promoting flexibility in opacity calculations based on specific research needs. Additionally, pre-computed opacity tables, inclusive of condensates, are provided. We present a preliminary application to evolutionary models for very low-mass stars., Comment: 25 pages, 17 figures, accepted for publication in APJ

We extend the shifted boundary method (SBM) to the simulation of incompressible fluid flow using immersed octree meshes. Previous work on SBM for fluid flow primarily utilized two- or three-dimensional unstructured tetrahedral grids. Recently, octree grids have become an essential component of immersed CFD solvers, and this work addresses this gap and the associated computational challenges. We leverage an optimal (approximate) surrogate boundary constructed efficiently on incomplete and adaptive octree meshes. The resulting framework enables the simulation of the incompressible Navier-Stokes equations in complex geometries without requiring boundary-fitted grids. Simulations of benchmark tests in two and three dimensions demonstrate that the Octree-SBM framework is a robust, accurate, and efficient approach to simulating fluid dynamics problems with complex geometries.

We provide a new version of the Poincar\'e-Birkhoff theorem for possibly multivalued successor maps associated with planar non-autonomous Hamiltonian systems. As an application, we prove the existence of periodic and subharmonic solutions of the scalar second order equation $\ddot x + \lambda g(t,x) = 0$, for $\lambda>0$ sufficiently small, with $g(t,x)$ having a superlinear growth at infinity, without requiring the existence of an equilibrium point., Comment: 21 pages, 4 figures

The Local Ultraviolet to Infrared Treasury (LUVIT) is a Hubble Space Telescope program that combines newly acquired data in the near ultraviolet (NUV), optical, and near infrared (NIR) with archival optical and NIR imaging to produce multiband panchromatic resolved stellar catalogs for 23 pointings in 22 low-mass, star-forming galaxies ranging in distance from the outskirts of the Local Group to ~3.8 Mpc. We describe the survey design, detail the LUVIT broadband filter observations and the archival datasets included in the LUVIT reductions, and summarize the simultaneous multiband data reduction steps. The spatial distributions and color-magnitude diagrams (CMDs) from the resulting stellar catalogs are presented for each target, from the NUV to the NIR. We demonstrate in which regions of the CMDs stars with NUV and optical, optical and NIR, and NUV through NIR detections reside. For each target, we use the results from artificial star tests to measure representative completeness, bias, and total photometric uncertainty as a function of magnitude in each broadband filter. We also assess which LUVIT targets have significant spatial variation in the fraction of stars recovered at a given magnitude. The panchromatic LUVIT stellar catalogs will provide a rich legacy dataset for a host of resolved stellar population studies., Comment: 48 pages, 14 figures, 8 tables, accepted for publication in ApJS

Binaries with a Wolf-Rayet star and a compact object (WR-COs), either a black hole (BH) or a neutron star (NS), have been proposed as possible progenitors for the binary compact object mergers (BCOs) observed with the gravitational wave (GW) detectors. In this work, we use the open-source population synthesis code SEVN to investigate the role of WR-COs as BCO progenitors. We consider an initial population of $5 \times 10^6$ binaries and we evolve it across 96 combinations of metallicities, common envelope efficiencies, core-collapse supernova models and natal kick distributions. We find that WR-COs are the progenitors of most BCOs, especially at high and intermediate metallicity. At $Z=0.02,\,{}0.014,$ and $0.0014$, more than $\gtrsim 99 \%$ of all the BCOs in our simulations evolved as WR-COs. At $Z = 0.00014$, inefficient binary-stripping lowers the fraction of BCOs with WR-CO progenitors to $\approx 83-95 \%$. Despite their key role in BCO production, only $\approx 5-30 \%$ of WR-COs end their life as BCOs. We find that Cyg X-3, the only WR-CO candidate observed in the Milky Way, is a promising BCO progenitor, especially if it hosts a BH. In our simulations, about $\approx 70-100 \%$ of the Cyg X-3 - like systems in the WR-BH configuration (BH mass $ \leq 10 \rm ~ M_\odot$) are BCO progenitors, in agreement with the literature. Future observations of WR-COs similar to Cyg X-3 may be the Rosetta stone to interpret the formation of BCOs., Comment: 16 pages, 13 figures, 1 table. Submitted to A&A, comments welcome

In high-stakes domains like legal question-answering, the accuracy and trustworthiness of generative AI systems are of paramount importance. This work presents a comprehensive benchmark of various methods to assess the groundedness of AI-generated responses, aiming to significantly enhance their reliability. Our experiments include similarity-based metrics and natural language inference models to evaluate whether responses are well-founded in the given contexts. We also explore different prompting strategies for large language models to improve the detection of ungrounded responses. We validated the effectiveness of these methods using a newly created grounding classification corpus, designed specifically for legal queries and corresponding responses from retrieval-augmented prompting, focusing on their alignment with source material. Our results indicate potential in groundedness classification of generated responses, with the best method achieving a macro-F1 score of 0.8. Additionally, we evaluated the methods in terms of their latency to determine their suitability for real-world applications, as this step typically follows the generation process. This capability is essential for processes that may trigger additional manual verification or automated response regeneration. In summary, this study demonstrates the potential of various detection methods to improve the trustworthiness of generative AI in legal settings., Comment: to appear NLLP @ EMNLP 2024

Detectors at future high energy colliders will face enormous technical challenges. Disentangling the unprecedented numbers of particles expected in each event will require highly granular silicon pixel detectors with billions of readout channels. With event rates as high as 40 MHz, these detectors will generate petabytes of data per second. To enable discovery within strict bandwidth and latency constraints, future trackers must be capable of fast, power efficient, and radiation hard data-reduction at the source. We are developing a radiation hard readout integrated circuit (ROIC) in 28nm CMOS with on-chip machine learning (ML) for future intelligent pixel detectors. We will show track parameter predictions using a neural network within a single layer of silicon and hardware tests on the first tape-outs produced with TSMC. Preliminary results indicate that reading out featurized clusters from particles above a modest momentum threshold could enable using pixel information at 40 MHz., Comment: Contribution to the 42nd International Conference on High Energy Physics (ICHEP)

MAXI J1803-298 is a transient black hole candidate discovered in May of 2021 during an outburst that lasted several months. Multiple X-ray observations reveal recurring "dipping" intervals in several of its light curves, particularly during the hard/intermediate states, with a typical recurrence period of $\sim7\,\mathrm{hours}$. We report analysis of four NuSTAR observations of the source, supplemented with NICER data where available, over the duration of the outburst evolution covering the hard, intermediate and the soft states. Reflection spectroscopy reveals the black hole to be rapidly spinning ($a_*=0.990\pm{0.001}$) with a near edge-on viewing angle ($i=70\pm{1}\deg$). Additionally, we show that the light-curve dips are caused by photo-electric absorption from a moderately ionized absorber whose origin is not fully understood, although it is likely linked to material from the companion star impacting the outer edges of the accretion disk. We further detect absorption lines in some of the spectra, potentially associated with Fe XXV and Fe XXVI, indicative of disk winds with moderate to extreme velocities. During the intermediate state and just before transitioning into the soft state, the source showed a sudden flux increase which we found to be dominated by soft disk photons and consistent with the filling of the inner accretion disk, at the onset of state transition. In the soft state, we show that models of disk self-irradiation provide a better fit and a preferred explanation to the broadband reflection spectrum, consistent with previous studies of other accreting sources., Comment: 21 pages, 9 figures, accepted for publication in ApJ

The Linear Mixing Approximation (LMA) is often used in planetary models for calculating the equations of state (EoSs) of mixtures. A commonly assumed planetary composition is a mixture of rock and water. Here we assess the accuracy of the LMA for pressure-temperature conditions relevant to the interiors of Uranus and Neptune. We perform MD simulations using ab-initio simulations and consider pure-water, pure-silica, and 1:1 and 1:4 silica-water molecular fractions at temperature of 3000 K and pressures between 30 and 600 GPa. We find that the LMA is valid within a few percent (<~5%) between ~150-600 Gpa, where the sign of the difference in inferred density depends on the specific composition of the mixture. We also show that the presence of rocks delays the transition to superionic water by ~70 GPa for the 1:4 silica-water mixture. Finally, we note that the choice of electronic theory (functionals) affect the EoS and introduces an uncertainty in of the order of 10% in density. Our study demonstrates the complexity of phase diagrams in planetary conditions and the need for a better understanding of rock-water mixtures and their effect on the inferred planetary composition., Comment: Accepted for publication in ApJ

We present our analysis of MAXI J1813-095 during its hard state ``stalled'' outburst in 2018. This self-consistent analysis has been carried out using \NICER, \Swift, \Chandra, and {\NuSTAR} throughout seven observations of MAXI J1813-095. We find a relativistic iron line at $\sim$6.5 keV from the inner region of the accretion disk. Our results are consistent with a slightly truncated disk or non-truncated disk for an inner radius of $\sim$2$R_\mathrm{g}$ and minimum spin of $>$0.7 with a best value of $\sim0.9$, assuming $R_\mathrm{in}$ reaches the innermost stable circular orbit at $\it{L_\mathrm{x}}$ $\sim$ 1\% $\it{L_\mathrm{Edd}}$. We analyzed MAXI J1813-095 over its outburst employing a spectral model which self-consistently couples the seed disk photons to the Comptonization and reflection components, also inclusive of reflection Comptonization. The unique aspect of this work is a reflection fraction of order unity, which is significantly higher than previous studies of this source, and is a consequence of applying the self-consistent disk-Comptonization-reflection spectral model. Other key parameters such as inclination and inner radius are found to be consistent with other works. works.

We investigate quantum random tensor network states where the bond dimensions scale polynomially with the system size, $N$. Specifically, we examine the delocalization properties of random Matrix Product States (RMPS) in the computational basis by deriving an exact analytical expression for the Inverse Participation Ratio (IPR) of any degree, applicable to both open and closed boundary conditions. For bond dimensions $\chi \sim \gamma N$, we determine the leading order of the associated overlaps probability distribution and demonstrate its convergence to the Porter-Thomas distribution, characteristic of Haar-random states, as $\gamma$ increases. Additionally, we provide numerical evidence for the frame potential, measuring the $2$-distance from the Haar ensemble, which confirms the convergence of random MPS to Haar-like behavior for $\chi \gg \sqrt{N}$. We extend this analysis to two-dimensional systems using random Projected Entangled Pair States (PEPS), where we similarly observe the convergence of IPRs to their Haar values for $\chi \gg \sqrt{N}$. These findings demonstrate that random tensor networks with bond dimensions scaling polynomially in the system size are fully Haar-anticoncentrated and approximate unitary designs, regardless of the spatial dimension.

In this work we analyze the spectral $\zeta$-function associated with the self-adjoint extensions, $T_{A,B}$, of quasi-regular Sturm--Liouville operators that are bounded from below. By utilizing the Green's function formalism, we find the characteristic function which implicitly provides the eigenvalues associated with a given self-adjoint extension $T_{A,B}$. The characteristic function is then employed to construct a contour integral representation for the spectral $\zeta$-function of $T_{A,B}$. By assuming a general form for the asymptotic expansion of the characteristic function, we describe the analytic continuation of the $\zeta$-function to a larger region of the complex plane. We also present a method for computing the value of the spectral $\zeta$-function of $T_{A,B}$ at all positive integers. We provide two examples to illustrate the methods developed in the paper: the generalized Bessel and Legendre operators. We show that in the case of the generalized Bessel operator, the spectral $\zeta$-function develops a branch point at the origin, while in the case of the Legendre operator it presents, more remarkably, branch points at every nonpositive integer value of $s$., Comment: 39 pages

Electronic correlations arise from the competition between the electrons' kinetic and Coulomb interaction energy and give rise to a rich phase diagram and many emergent quasiparticles. The binding of doubly-occupied and empty sites into a doublon-holon exciton is an example of this in the Hubbard model. Unlike traditional excitons in semiconductors, in the Hubbard model it is the kinetic energy which provides the binding energy. Upon doping, we find the emergence of exciton complexes, such as a holon-doublon-holon trion. The appearance of these low-lying collective excitations make screening more effective in the doped system. As a result, Hubbard-based modelling of correlated materials should use different values of $U$ for the doped system and the insulating parent compound, which we illustrate using the cuprates as an example., Comment: 8 pages, 9 figures

Pair-instability supernovae (PISNe) have crucial implications for many astrophysical topics, including the search for very massive stars, the black hole mass spectrum, and galaxy chemical enrichment. To this end, we need to understand where PISNe are across cosmic time, and what are their favourable galactic environments. We present a new determination of the PISN rate as a function of redshift, obtained by combining up-to-date stellar evolution tracks from the PARSEC and FRANEC codes, with an up-to-date semi-empirical determination of the star formation rate and metallicity evolution of star-forming galaxies throughout cosmic history. We find the PISN rate to exhibit a huge dependence on the model assumptions, including the criterion to identify stars unstable to pair production, and the upper limit of the stellar initial mass function. Remarkably, the interplay between the maximum metallicity at which stars explode as PISNe, and the dispersion of the galaxy metallicity distribution, dominates the uncertainties, causing a $\sim$ seven-orders-of-magnitude PISN rate range. Furthermore, we show a comparison with the core-collapse supernova rate, and study the properties of the favourable PISN host galaxies. According to our results, the main contribution to the PISN rate comes from metallicities between $\sim 10^{-3}$ and $10^{-2}$, against the common assumption that views very-low-metallicity, Population III stars as exclusive or dominant PISN progenitors. The strong dependencies we find offer the opportunity to constrain stellar and galaxy evolution models based on possible future (or the lack of) PISN observations., Comment: Accepted for publication on MNRAS, 23 pages, 25 figures, 4 tables

There is mounting evidence that a second quantum revolution based on the technological capabilities to detect and manipulate single quantum particles (e.g., electrons, photons, ions, etc), a feat not achieved during the first quantum revolution, is progressing fast. It is expected that in less than 10 years, this second quantum revolution shall have a significant impact over numerous industries, including finance, medicine, energy, transportation, etc. Quantum computers threaten the status quo of cybersecurity, due to known quantum algorithms that can break asymmetric encryption, which is what gives us the ability to communicate securely using a public channel. Considering the world's dependence on digital communication through data exchange and processing, retaining the ability to communicate securely even once quantum computers come into play, cannot be stressed enough. Two solutions are available: Quantum Key Distribution (QKD) and Post-Quantum Cryptography (PQC); which, we emphasise, are not mutually exclusive. The EuroQCI initiative, of which EQUO is a part of, focuses on QKD and aims to build a network whereby EU countries can communicate securely through QKD. To this aim, the DEP (Digital Europe Programme) project aims to bring technological matureness to QKD by deploying a QKD test network and, through this exercise, understand what is lacking from an operator's point of view when the time to integrate QKD in their network comes., Comment: IEEE 2024 International Conference on Quantum Communications, Networking, and Computing (QCNC)

The LLMJudge challenge is organized as part of the LLM4Eval workshop at SIGIR 2024. Test collections are essential for evaluating information retrieval (IR) systems. The evaluation and tuning of a search system is largely based on relevance labels, which indicate whether a document is useful for a specific search and user. However, collecting relevance judgments on a large scale is costly and resource-intensive. Consequently, typical experiments rely on third-party labelers who may not always produce accurate annotations. The LLMJudge challenge aims to explore an alternative approach by using LLMs to generate relevance judgments. Recent studies have shown that LLMs can generate reliable relevance judgments for search systems. However, it remains unclear which LLMs can match the accuracy of human labelers, which prompts are most effective, how fine-tuned open-source LLMs compare to closed-source LLMs like GPT-4, whether there are biases in synthetically generated data, and if data leakage affects the quality of generated labels. This challenge will investigate these questions, and the collected data will be released as a package to support automatic relevance judgment research in information retrieval and search., Comment: LLMJudge Challenge Overview, 3 pages

The first edition of the workshop on Large Language Model for Evaluation in Information Retrieval (LLM4Eval 2024) took place in July 2024, co-located with the ACM SIGIR Conference 2024 in the USA (SIGIR 2024). The aim was to bring information retrieval researchers together around the topic of LLMs for evaluation in information retrieval that gathered attention with the advancement of large language models and generative AI. Given the novelty of the topic, the workshop was focused around multi-sided discussions, namely panels and poster sessions of the accepted proceedings papers., Comment: LLM4Eval Workshop Report

The black hole X-ray binary H1743-322 lies in a region of the Galaxy with high extinction, and therefore it has not been possible to make a dynamical mass measurement. In this paper we make use of a recent model which uses the X-ray reflection spectrum to constrain the ratio of the black hole mass to the source distance. By folding in a reported distance measurement, we are able to estimate the mass of the black hole to be $12\pm2~\text{M}_\odot$ ($1\sigma$ credible interval). We are then able to revise a previous disc continuum fitting estimate of black hole spin $a_*$ (previously relying on a population mass distribution) using our new mass constraint, finding $a_*=0.47\pm0.10$. This work is a proof of principle demonstration of the method, showing it can be used to find the mass of black holes in X-ray binaries., Comment: 13 pages, 7 figures. Accepted for publication in MNRAS

Introduction. Here we reported the virological, entomological and epidemiological characteristics of the large autochthonous outbreak of dengue (DENV) occurred in a small village of the Lombardy region (Northern Italy) during summer 2023. Methods. After the diagnosis of the first autochthonous case on 18 August 2023, public health measures, including epidemiological investigation and vector control measures, were carried out. A serological screening for DENV antibodies detection was offered to the population. In the case of positive DENV IgM, a second sample was collected to detect DENV RNA and verify seroconversion. Entomological and epidemiological investigations were also performed. A modeling analysis was conducted to estimate the dengue generation time, transmission potential, distance of transmission, and assess diagnostic delays. Results. Overall, 416 subjects participated to the screening program and 20 were identified as DENV-1 cases (15 confirmed and 5 probable). In addition, DENV-1 infection was diagnosed in 24 symptomatic subjects referred to the local Emergency Room Department for suggestive symptoms and 1 case was identified through blood donation screening. The average generation time was estimated to be 18.3 days (95% CI: 13.1-23.5 days). R0 was estimated at 1.31 (95% CI: 0.76-1.98); 90% of transmission occurred within 500m. Entomological investigations performed in 46 pools of mosquitoes revealed the presence of only one positive pool for DENV-1. Discussion. This report highlights the importance of synergic surveillance, including virological, entomological and public health measures to control the spread of arboviral infections.

Several studies have investigated human interaction using modern tracking techniques for face-to-face encounters across various settings and age groups. However, little attention has been given to understanding how individual characteristics relate to social behavior. This is particularly important in younger age groups due to its potential effects on early childhood development. In this study, conducted during the Complexity 72h Workshop, we analyze human social interactions in a French preschool, where children's face-to-face interactions were monitored using proximity sensors over an academic year. We use metadata from parent surveys and preschool linguistic tests, covering demographic information and home habits, to examine the interplay between individual characteristics and contact patterns. Using a mixture of approaches, from random forest classifiers to network-based metrics at both dyadic and higher-order (group) levels, we identify sex, age, language scores, and number of siblings as the variables displaying the most significant associations with interaction patterns. We explore these variables' relationships to interactions within and outside classrooms and across mixed and single-grade classes. At the group level, we investigate how group affinity affects group persistence. We also find that higher-order network centrality (hypercoreness) is higher among children with siblings, indicating different group embedding despite similar total contact duration. This study aligns with existing literature on early social development and highlights the importance of integrating individual traits into the study of human interactions. Focusing on 2-5-year-olds offers insights into emerging social preferences during critical phases of cognitive development. Future research could use these findings to enhance mechanistic models of complex social systems by incorporating individual traits., Comment: This work is the output of the Complexity72h workshop, held at the Universidad Carlos III de Madrid in Legan\'es, Spain, 24-28 June 2024

We address the question of whether holographic entropy inequalities obeyed in static states (by the RT formula) are always obeyed in time-dependent states (by the HRT formula), focusing on the case where the bulk spacetime is 2+1 dimensional. An affirmative answer to this question was previously claimed by Czech-Dong. We point out an error in their proof when the bulk is multiply connected. We nonetheless find strong support, of two kinds, for an affirmative answer in that case. We extend the Czech-Dong proof for simply-connected spacetimes to spacetimes with $\pi_1=\mathbb{Z}$ (i.e. 2-boundary, genus-0 wormholes). Specializing to vacuum solutions, we also numerically test thousands of distinct inequalities (including all known RT inequalities for up to 6 regions) on millions of randomly chosen configurations of regions and bulk spacetimes, including three different multiply-connected topologies; we find no counterexamples. In an appendix, we prove some (dimension-independent) facts about degenerate HRT surfaces and symmetry breaking., Comment: 30 pages. Watch a 4-minute video abstract: https://www.youtube.com/watch?v=ols92YU8rus

We investigate the late-time tail behavior in gravitational waves from merging eccentric binary black holes (BBH) using black hole perturbation theory. For simplicity, we focus only on the dominant quadrupolar mode of the radiation. We demonstrate that such tails become more prominent as eccentricity increases. Exploring the phenomenology of the tails in both spinning and non-spinning eccentric binaries, with the spin magnitude varying from $\chi=-0.6$ to $\chi=+0.6$ and eccentricity as high as $e=0.98$, we find that these tails can be well approximated by a slowly decaying power law. We study the power law for varying systems and find that the power law exponent lies close to the theoretically expected value $-4$. Finally, using both plunge geodesic and radiation-reaction-driven orbits, we perform a series of numerical experiments to understand the origin of the tails in BBH simulations. Our results suggest that the late-time tails are strongly excited in eccentric BBH systems when the smaller black hole is in the neighborhood of the apocenter, as opposed to any structure in the strong field of the larger black hole. Our analysis framework is publicly available through the \texttt{gwtails} Python package., Comment: 16 pages, 18 figures

A pipeline to evaluate the evolution of viral dynamics based on a new model-driven approach has been developed in the present study. The proposed methods exploit real data and the multiscale structure of the infection dynamics to provide robust predictions of the epidemic dynamics. We focus on viral load kinetics whose dynamical features are typically available in the symptomatic stage of the infection. Hence, the epidemiological evolution is obtained by relying on a compartmental approach characterized by a varying infection rate to estimate early-stage viral load dynamics, of which few data are available. We test the proposed approach with real data of SARS-CoV-2 viral load kinetics collected from patients living in an Italian province. The considered database refers to early-phase infections, whose viral load kinetics are not affected by mass vaccination policies in Italy. Our contribution is devoted to provide an effective computational pipeline to evaluate in real time the evolution of infectivity. Comprehending the factors influencing the in-host viral dynamics represents a fundamental tool to provide robust public health strategies. This pilot study could be implemented in further investigations involving other respiratory viruses, to better clarify the process of viral dynamics as a preparatory action for future pandemics.

We propose an enhanced Time-Dependent Variational Principle (TDVP) algorithm for Matrix Product States (MPS) that integrates Clifford disentangling techniques to efficiently manage entanglement growth. By leveraging the Clifford group, which maps Pauli strings to other Pauli strings while maintaining low computational complexity, we introduce a Clifford dressed single-site 1-TDVP scheme. During the TDVP integration, we apply a global Clifford transformation as needed to reduce entanglement by iteratively sweeping over two-qubit Clifford unitaries that connect neighboring sites in a checkerboard pattern. We validate the new algorithm numerically using various quantum many-body models, including both integrable and non-integrable systems. Our results demonstrate that the Clifford dressed TDVP significantly improves entanglement management and computational efficiency, achieving higher accuracy, extended simulation times, and enhanced precision in computed observables compared to standard TDVP approaches. Additionally, we propose incorporating Clifford gates directly within the two-site 2-TDVP scheme., Comment: 7 pages, 3 figures

This paper presents a case study of a cryptocurrency scam that utilized coordinated and inauthentic behavior on Twitter. In 2020, 143 accounts sold by an underground merchant were used to orchestrate a fake giveaway. Tweets pointing to a fake blog post lured victims into sending Uniswap tokens (UNI) to designated addresses on the Ethereum blockchain, with the false promise of receiving more tokens in return. Using one of the scammer's addresses and leveraging the transparency and immutability of the Ethereum blockchain, we traced the flow of stolen funds through various addresses, revealing the tactics adopted to obfuscate traceability. The final destination of the funds involved two deposit addresses. The first, managed by a well-known cryptocurrency exchange, was likely associated with the scammer's own account on that platform and saw deposits exceeding $3.5 million. The second address was linked to a popular cryptocurrency swap service. These findings highlight the critical need for more stringent measures to verify the source of funds and prevent illicit activities.