The ability to establish coherent communication channels is key for scaling up quantum devices. Here, we engineer interactions between distant polaritons, hybrid spin-photon excitations formed at different lumped-element superconducting resonators within a chip. The chip consists of several resonator pairs, slightly detuned in frequency to make them addressable, capacitively coupled within each pair and inductively coupled to a common readout line. They interact locally with samples of PTMr and Tripak$^{-}$ organic free radicals, deposited onto their inductors, which provide model $S = 1/2$, $g \simeq 2$ spin ensembles. Frequency-dependent microwave transmission experiments, performed at very low temperatures, measure polariton frequencies as a function of magnetic field in different scenarios. When only one resonator within a pair hosts a molecular sample, the results evidence that spins couple remotely to the empty LER as well as to the local cavity mode. If both resonators interact with a spin ensemble, the magnetic field tunes the polariton frequencies relative to each other, on account of the different spin-photon interactions at each LER. When polaritons are brought into mutual resonance, an avoided level crossing emerges that gives direct spectroscopic evidence for a coherent polariton-polariton interaction mediated by the circuit. Pump-probe experiments reveal that the excitation of a polariton within a connected pair is felt, thus it can be read out, by the other one. These observations, backed by model calculations, illustrate the control and detection of distant photon-photon and spin-spin correlations and entanglement in a scalable modular chip.

Several strong solar resonance lines show observable linear scattering polarization signals, holding a great potential for investigating the magnetism of the outer solar atmosphere. Accurately modeling these signals requires solving the radiative transfer (RT) problem for polarized radiation in comprehensive 3D models of the solar atmosphere, in non-local thermodynamic equilibrium, accounting for partial frequency redistribution (PRD) effects. This problem has so far been computationally inaccessible. We present the first scientific application of TRIP, a novel software for the massively parallel solution of the 3D non-LTE RT problem for polarized radiation, including scattering polarization and PRD. We aim to verify the code and explore the combined action of PRD and the 3D structure of the solar atmosphere on scattering polarization. We run TRIP to synthesize the Stokes profiles of the Ca I line at 4227 Å in a 3D model of the solar atmosphere extracted from a radiation magneto-hydrodynamic simulation. We efficiently solve the resulting large-scale problem, with up to $4 \times 10^{10}$ degrees of freedom, with a state-of-the-art preconditioned Krylov method, using up to 20 thousand parallel CPUs. After including verification tests, we find that the joint impact of PRD effects and the detailed 3D structure of the atmospheric model produce disk-center scattering polarization signals in the line wings. These signals are sensitive to the magnetic field, via magneto-optical effects, and to bulk velocity gradients. We also show that the CRD approximation underestimates the amplitude of disk-center line-core signals. This achievement represents a crucial step forward for diagnosing the magnetism of the solar chromosphere and transition region through the quantitative comparisons of synthetic and observational data.

We construct a contour function for the logarithmic negativity and the logarithm of the moments of the partial transpose of the reduced density matrix for multimode bosonic Gaussian states of a free lattice model. In one spatial dimension, numerical results are obtained for harmonic chains either in the ground state or at finite temperature, by considering, respectively, either a subsystem made by two adjacent or disjoint blocks on the line or a bipartition of the circle. The contour function of the logarithmic negativity diverges only at the entangling points, while the contour function for the logarithm of the moments of the partial transpose is divergent also at the boundary of the bipartite subsystem, as functions of the position. In a two-dimensional conformal field theory, analytic expressions that describe these divergencies are discussed. In one spatial dimension, we explore the partial derivative of the logarithmic negativity of two adjacent intervals with respect to the logarithm of the harmonic ratio of their lengths while their ratio and the other parameters are kept fixed. Considering the ground state of the harmonic chain on the line and in the massive regime, we report numerical results showing that this quantity displays a monotonically decreasing behaviour.

Defects in solid-state systems constitute a promising platform for the realization of deterministic quantum emitters. Among many candidate materials and emitters, point defects in hexagonal Boron Nitride (hBN) have recently emerged as particularly promising. In this work, we probe the coherence of an individual B center with a zero phonon line at 436 nm, under pulsed resonant excitation. We observe power-dependent Rabi oscillations up to 5π, demonstrating optical coherent control of the transition. We achieve an excellent single photon purity of 93% at π-pulse. Furthermore, we probe the coherence of the two-level system using Ramsey interferometry, revealing an inhomogeneous coherence time of T_2*=0.60 ns. These results establish B centers in hBN as viable candidates for triggered, coherent quantum emitters and represent an important step towards their integration into quantum photonic platforms.

Chiral fluids, for which the mobility tensor has antisymmetric, off-diagonal components, exhibit transport phenomena absent in conventional systems, including interaction-enhanced diffusion and negative mobility. While these effects have been predicted theoretically and observed in simulations, their microscopic origin has remained unclear. Here, we address this question using a mobility-based nonequilibrium approach, analysing the steady-state drift of a tracer driven through an interacting chiral fluid. We show that, under strong chirality, the tracer generates a reversed density wake, in which regions of particle accumulation and depletion are inverted compared to the achiral case. This structural inversion of the wake provides a unified physical mechanism underlying both enhanced diffusion and negative mobility. Furthermore, we demonstrate that these phenomena are robust to changes in the interaction potential, highlighting their generality as a consequence of odd mobility.

We introduce a new programming language and its categorical semantics in order to design and implement neural networks within the framework of algebraic effects and handlers for arrows. Our language enables us to construct neural networks symbolically, in the same manner as algebraic effects, and to assign implementations -- such as backpropagation computations -- to them via handlers. The advantage of this language design is that network descriptions become abstract and high-level, while implementations can be flexibly assigned to networks. We establish a rigorous foundation for our language by developing a type system, an operational semantics, a categorical semantics, and soundness and adequacy theorems. The technical core is the introduction of \emph{reverse handlers}, a novel handler mechanism for arrows for implementing backpropagation, together with new algebras of strong promonads on reverse differential restriction categories (RDRCs), whose string diagrams provide a formal graphical syntax and semantics for neural networks.

The diffusion of complex opinions is severely hindered in multilayer social networks by echo chambers and cognitive consistency mechanisms. We investigate Influence Maximization strategies within the 3-state multilayer q-voter model. Utilizing the mABCD benchmark, we simulate social environments ranging from integrated Open Worlds to segregated Fortress Worlds. Our results reveal a topological paradox that we term the "Fortress Trap". In highly modular networks, strategies maximizing local density such as Clique Influence Maximization (CIM) and k-Shell fail to trigger global cascades, creating isolated bunkers of consensus due to the Overkill Effect. Furthermore, we identify a Redundancy Trap in perfectly aligned Clan topologies, where the structural overlap of layers creates a "Perfect Prison," rendering it the most resistant environment to diffusion. We demonstrate that VoteRank, a strategy that prioritizes diversity of reach over local intensity, consistently outperforms structure-based methods. These findings suggest that, for complex contagion, maximizing topological entropy is more effective than reinforcing local clusters.

This paper presents methods for meta-analysis of $2 \times 2$ tables, both with and without allowing heterogeneity in the treatment effects. Meta-analysis is common in medical research, but most existing methods are unsuited for $2 \times 2$ tables with rare events. Usually the tables are modelled as pairs of binomial variables, but we will model them as Poisson pairs. The methods presented here are based on confidence distributions, and offer optimal inference for the treatment effect parameter. We also propose an optimal method for inference on the ratio between treatment effects, and illustrate our methods on a real dataset.

Leveraging channel state information from multiple Wi-Fi bands can improve delay resolution for ranging and sensing when a wide contiguous spectrum is unavailable. However, frequency gaps shape the delay response, introducing sidelobes and secondary peaks that can obscure closely spaced multipath components. This paper examines multipath delay estimation for Wi-Fi-compliant multiband configurations using channel state information (CSI). For a two-path model with unknown complex gains and delays, the Cramér-Rao lower bound (CRLB) for delay separation is derived and analyzed, confirming the benefit of larger frequency aperture, while revealing pronounced, separation-dependent oscillations driven by gap geometry and inter-path coupling. Given the local nature of Cramér-Rao lower bound, the delay response is analyzed next. In the single-path case, the combined subband responses determine how delay-domain sidelobe levels are distributed. The dominant peak spacing is set primarily by the separation between subband center frequencies. In the two-path case, increased aperture sharpens the mainlobe but also intensifies sidelobes and leakage, yielding competing peaks and, in some regimes, a dominant peak shifted from the true delay. Finally, a normalized leakage metric is introduced to predict problematic separations and to identify regimes where local Cramér-Rao lower bound analysis does not capture practical peak-leakage behavior in delay estimation.

In the past two decades, the observed large-scale magnetic field of the active M dwarf star AD Leo has evolved from strongly to mildly negative, raising a suspicion that it might switch polarity. Although magnetic field reversals are observed every 11 years for the Sun, such reversals are poorly understood for M dwarfs. Further, no reversals have been observed for fast-rotating M dwarfs. We examine the properties of AD Leo's large-scale magnetic field and investigate how its evolution affects the space weather environment. We analysed spectropolarimetric data collected by ESPaDOnS and SPIRou in late-2022 and early-2023. With the optical and near-infrared data we computed the longitudinal magnetic field, and with the near-infrared data reconstructed the large-scale magnetic field using Zeeman-Doppler imaging. Using five magnetograms, from 2019 to 2023, we simulated three-dimensional Alfven wave-driven stellar winds using the space weather code SWMF. Although we see an evolution of the large-scale magnetic field of AD Leo, we find no polarity reversal. Rather, we see a restoration of the field to a simpler configuration with consistently negative values for the longitudinal magnetic field strength. Our new large-scale field reconstruction for AD Leo is characterised by a highly axisymmetric, poloidal-dipolar field with an increased mean large-scale field strength. SWMF simulations find the stellar mass loss rates to be, on average, an order of magnitude greater than that of the Sun. Additionally, we find that the habitable zone resides beyond the Alfven surface. Hypothetical magnetised habitable zone planets (with planetary field strengths greater than 0.34 G) would likely be shielded from the incident wind and atmospheric erosion would be negligible. Further, we find variable conditions across each epoch due to the evolving axisymmetry of the stellar large-scale magnetic field.

In recent years, stealthy Android malware has increasingly adopted sophisticated techniques to bypass automatic detection mechanisms and harden manual analysis. Adversaries typically rely on obfuscation, anti-repacking, steganography, poisoning, and evasion techniques to AI-based tools, and in-memory execution to conceal malicious functionality. In this paper, we investigate WebAssembly (Wasm) as a novel technique for hiding malicious payloads and evading traditional static analysis and signature-matching mechanisms. While Wasm is typically employed to render specific gaming activities and interact with the native components in web browsers, we provide an in-depth analysis on the mechanisms Android may employ to include Wasm modules in its execution pipeline. Additionally, we provide Proofs-of-Concept to demonstrate a threat model in which an attacker embeds and executes malicious routines, effectively bypassing IoC detection by industrial state-of-the-art tools, like VirusTotal and MobSF.

These notes are devoted to fluctuations of one-dimensional random walks. We discuss various approaches to first-passage times and to the corresponding conditional distributions. After discussion of some classical methods, such as reflection principle for simple random walks and Wiener-Hopf factorisation, we proceed to the universality approach, which has been developed in recent past. Considering one-dimensional case allows us to avoid some technical obstacles and to present the core of this method in a more transparent way. It turns out that the universality method is much more robust than the Wiener-Hopf factorisation and allows one to consider walks with non-identically distributed or even dependent increments.

This document serves as supplementary material for our journal submission, providing detailed mathematical proofs and derivations that support the results presented in the main manuscript. Specifically, under a modeling framework that jointly considers transceiver hardware impairments and imperfect successive interference cancellation (SIC), we systematically derive and prove from an optimality perspective that: when the residual interference coefficient approaches 1 (i.e., SIC becomes severely ineffective), there exists an optimal solution such that the common stream beamformer satisfies $\bm w_c^\star=\bm 0$, and hence the optimal rate-splitting multiple access (RSMA) transmission structure degenerates into space division multiple access (SDMA). This conclusion provides a verifiable theoretical justification for the convergence phenomenon observed in simulations, namely that "the RSMA performance gradually approaches that of SDMA as SIC degrades", and can also serve as a reference for multiple-access selection and system design in SIC-limited scenarios.

This paper proposes a monostatic wideband system for integrated sensing and communication (ISAC) at millimeter-wave frequencies, based on multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM). The system operates in a hybrid near-/far-field regime. The transmitter (Tx) operates in the far field (FF) and uses low-complexity beam steering. The receiver (Rx), on the other hand, operates in a pervasive near field (NF), enabled by a very large effective array aperture. To enable a fully digital implementation, we introduce an extremely large antenna spacing (ELAS) design. This design attains the required aperture with only a few widely spaced antenna elements while avoiding grating lobes in the composite Tx-Rx response. We analytically characterize the NF range-angle response of this architecture and study the interplay between NF effects and waveform bandwidth. This leads to the definition of a super-resolution region, where NF propagation at the Rx dominates the achievable range resolution and surpasses the classical, bandwidth-limited resolution. As a case study, we consider an extended target modeled as a collection of scatterers and assess localization performance via maximum-likelihood estimation. Numerical results evaluated in terms of root mean square error (RMSE) and generalized optimal sub-pattern assignment (GOSPA) show that operating in NF conditions with the ELAS-based design yields significant gains compared to a conventional FF baseline at both the Tx and Rx.

After a concise overview of Einstein spacetimes of type II (or more special) in four and five dimensions, we summarize recent results in the six-dimensional case. We assume the optical matrix to be non-degenerate and ``generic'', and the Weyl tensor to fall off sufficiently rapidly at infinity. As it turns out, the most general metric is characterized by one discrete (normalized) and three continuous parameters, is of type D and belongs to the Kerr-Schild class. Its relation to the previously known Kerr-(A)dS and Kerr-NUT-(A)dS metrics is clarified.

We provide a geometric approach to two combinatorically symmmetric overconstrained spatial linkages. Both contain eight bodies and twelve revolute joints and collapse in aligned poses. The first one is spherical and the union of six spherical isograms. It is the spherical image of a Bricard octahedron of type~3 and was already analysed 1912 by Bennett. The second linkage is the dualized version and composed from six Bennett isograms. Our approach via line reflections discloses some symmetries at spatial poses.

We model sunspot brightness temperature in the wavelength range 0.3-10mm using the Atacama Large Millimeter/submillimeter Array (ALMA) single-dish measurements together with other instruments. Our modeling idea starts from an existing model, the 1D semi-empirical Avrett-Tian-Landi-Curdt-Wülser (ATLCW) model for sunspots. The original model is then modified in density and temperature with a constant factor over all heights. A least-square fit in both density and temperature to the observed values yields an improved model for sunspot brightness temperature. Observations show that sunspots are darker than QS at wavelengths below 2 mm and brighter beyond, while fitting of the ATLCW sunspot model imply that sunspots should be darker than QS over the entireALMArange. The best-fitted sunspot brightness temperature profiles resulted in 3.6-4.0 times lower sunspot density compared to the original sunspot ATLCW model, or 1.4-1.8 times higher density compared to QS. The temperature came out around 1.2 times higher than the original ATLCW predictions for sunspots, or 1.2 times lower than QS temperature. Even with improved density and temperature parameters, the remaining discrepancy between the bestfitted models and observations indicated that additional improvements are needed in the ATLCW model and modeling assumptions.

Galaxy mergers play a crucial role in shaping the morphology, the star formation, and the mass growth of galaxies across cosmic time. While mergers have been extensively investigated in the local Universe, the evolution of their frequency and physical properties in the early Universe has yet to be fully understood. We investigate the role of mergers in a large spectroscopic sample of 1233 galaxies in the range 5<z<14 with good detection (S/N-pixel > 3) in JWST imaging, covering six different extragalactic fields. We identify mergers from rest-frame optical disturbances in F444W, using a combination of Gini, M-20, and Asymmetry parameters. We find a morphological merger fraction f_m that does not strongly evolve with redshift from z=0 to z ~ 8. The average f_m of our primary major merger condition (Gini+0.14xM-20 > 0.33, A>0.35) is ~ 5 %, which increases to ~13 % for major+minor merger tracers. Accounting for the evolving observability timescale of each tracer, we find that the merger rate is strongly increasing from z=1 to 7 by more than 1 dex, averaging ~ 2 merger/galaxy/Gyr at 5<z<10 for major mergers (in agreement with photometric pair studies), and a factor of 3 higher for minor+major mergers. We also perform SED modeling using available HST+JWST photometry to infer stellar masses and SFRs, using a non parametric star-formation history. We find that mergers at z > 5 have a significant impact, although significantly lower than at z<1, on the SFR of galaxies. When averaged over 10 Myr (comparable to the observability timescale of morphological disturbances), their SFRs are a factor of 1.7 higher than a mass and redshift matched sample of non-mergers, suggesting that mergers trigger new star-formation through short-lived powerful bursty episodes. Despite this, mergers contribute only by 5% - 10% to the mass build-up of galaxies in the redshift range explored.

We demonstrate, by femtosecond time- and angle-resolved photoemission spectroscopy, that photoinduced interlayer charge transfer in a heterostructure consisting of Bernal-stacked bilayer graphene and a single atomic layer of silver on 6H-SiC(0001) transiently modulates the intrinsic potential landscape across the silver-graphene interface. This acts as an ultrafast optoelectronic gate that drives momentum-dependent band renormalizations, resulting in a transient band-gap opening on femtosecond timescales. Simultaneously, the photogenerated hot-carrier population enhances electronic screening, leading to subsequent closing of the band-gap beyond the thermal equilibrium value. These findings reveal two different mechanisms for photoinduced, reversible control of the electronic band structure in bilayer graphene -- interlayer charge transfer and hot-carrier-enhanced screening -- providing a general framework for the ultrafast control of electronic properties in graphene-based heterostructures. This opens up novel pathways for the realization of ultrafast optoelectronic devices and the exploration of correlated quantum phases in bilayer graphene under non-equilibrium conditions.

Over the past four decades, distributed security has undergone a remarkable transformation -- from crash-fault tolerant protocols designed for controlled environments to sophisticated Byzantine-resilient architectures operating in open, adversarial settings. This vision paper examines this evolution and argues for a fundamental shift in how we approach distributed security: from studying individual security properties in isolation to understanding their synergistic combinations. We begin by conclude four foundational properties, \textit{agreement, consistency, privacy, verifiability, accountability}. We trace their theoretical origins and practical maturation. We then demonstrate how the frontier of research now lies at the intersection of these properties, where their fusion creates capabilities that neither property could achieve alone. Looking forward, we identify critical research challenges: discovering new security properties driven by emerging applications, developing systematic frameworks for property convergence, managing the computational overhead of cryptographic primitives in high-performance consensus layers, and addressing post-quantum and human-factor challenges. The future of distributed security lies not in improving individual properties, but in understanding and harnessing their synergies to build a singular fabric of trust.

Recent advances in continuous-time optimal stopping have been driven by entropy-regularized formulations of randomized stopping problems, with most existing approaches relying on partial differential equation methods. In this paper, we propose a fully probabilistic framework based on the Doob-Meyer-Mertens decomposition of the Snell envelope and its representation through reflected backward stochastic differential equations. We introduce an entropy-regularized penalization scheme yielding a monotone approximation of the value function and establish explicit convergence rates under suitable regularity assumptions. In addition, we develop a policy improvement algorithm based on linear backward stochastic differential equations and illustrate its performance through a simple numerical experiment for an American-style max call option

Power system operators are increasingly deploying Variable Impedance Devices (VIDs), e.g., Smart Wires, and Network Topology Optimization (NTO) schemes for mitigating operational challenges such as line and transformer congestion, and voltage violations. This work aims to optimize and coordinate the operation of distributed VIDs considering fixed and optimized topologies. This problem is inherently non-linear due to power flow equations as well as bilinear terms introduced due to variable line impedance of VIDs. Furthermore, the topology optimization scheme makes it a mixed integer nonlinear problem. To tackle this, we introduce using McCormick relaxation scheme, which converts the bilinear constraints into a linear set of constraints along with the DC power flow equations. We propose an iterative correction of the McCormick relaxation to enhance its accuracy. The proposed framework is validated on standard IEEE benchmark test systems, and we present a performance comparison of the iterative McCormick method against the non-linear, SOS2 piecewise linear approximation, and original McCormick relaxation.

In orbital mechanics, Gauss's method for orbit determination (OD) is a popular, minimal assumption solution for obtaining the initial state estimate of a passing resident space object (RSO). Since much of the cislunar domain relies on three-body dynamics, a key assumption of Gauss's method is rendered incompatible, creating a need for a new, minimal assumption method for initial orbit determination (IOD). In this work, we present a framework for short and long term probabilistic target tracking in cislunar space which produces an initial state estimate with as few assumptions as possible. Specifically, we propose an IOD method involving the kinematic fitting of several series of noisy, consecutive ground-based observations. Once a probabilistic initial state estimate in the form of a particle cloud is formed, we apply the powerful Particle Gaussian Mixture (PGM) Filter to reduce the uncertainty of our state estimate over time. This combined IOD/OD framework is demonstrated for several classes of trajectories in cislunar space and compared to better-known filtering frameworks.

In heterogeneous disordered traffic, where various vehicle types operate without strict lane discipline, self-organized vehicle groups often emerge. While the formation of such groups has been recognized, their influence on macroscopic traffic dynamics remains unclear. This study investigates how the prevalence and composition of vehicle groups affect flow-density relationships in heterogeneous disordered traffic. Using trajectory data from real-world video observations, we apply three distinct Passenger Car Unit (PCU) estimation methods to construct flow-density diagrams that account for traffic heterogeneity. The analysis reveals that group proportions, i.e., the proportion of vehicles that are classified as belonging to groups, have a nonlinear and traffic-situation-dependent impact on flow characteristics. Specifically, moderate group proportions (30-60%) are associated with higher flow rates in medium- and high-density conditions, whereas proportions exceeding 50% correspond to skewed traffic distributions toward low- or high-density extremes. Comparisons between vehicle-count-based and PCU-based group proportions indicate that normalization methods significantly affect the interpretation of group dynamics, particularly when groups consist mainly of small-PCU vehicles such as motorcycles. Additionally, lower group proportions enhance flow under free-flow conditions, while the entropy-based analysis indicates that the association between entropy alone and speed is not consistently observed across traffic situations. By contrasting representative trends and extreme high-flow cases, the results further suggest that traffic under similar density and group-proportion conditions can exhibit low-efficiency and high-efficiency modes.

Machine learning has revolutionized materials property prediction, yet fails catastrophically when extrapolating beyond training distributions-precisely the capability required for discovering unprecedented materials. Graph neural networks (GNNs) exhibit this collapse because end-to-end training fundamentally couples learned representations to target property distributions, preventing genuine extrapolation. We demonstrate that decoupled transfer learning-separating pretrained GNN feature extractors from simple regressors-overcomes this barrier. Pretrained features provide transferable structural knowledge, while simple regressors enable smooth extrapolation by maintaining learned trends beyond training boundaries. Benchmarked on layered intercalation compounds through four rigorous extrapolation scenarios and a temporal Materials Project split, our framework achieves 68% error reduction (RMSE: 0.881 vs. 2.778 eV/atom) versus end-to-end GNNs for extrapolation. Failure analysis reveals extrapolation succeeds for continuous chemical space but fails for discontinuous space, establishing clear design principles. Validated on Fermi energy prediction, this framework is immediately deployable using existing pretrained models, requiring no architectural innovations-transforming ML-driven materials discovery.

We provide a systematic discussion of the phenomenology of Dark Photon iDM (A$^{\prime}$iDM) where the Standard Model (SM) is extended by a dark sector containing an additional $U(1)_D$ gauge symmetry under which all SM particles are neutral, and that couples to the SM hypercharge gauge boson through a kinetic mixing parameter $ε$. The model contains two Majorana states $χ_1$ and $χ_2$ with $δ=M_{χ_2}-M_{χ_1}>0$ and $χ_1$ the dark matter candidate, and a dark photon $A^{\prime}$ with mass $M_{A^{\prime}}$. Our analysis represents an integration of existing ones, where only specific benchmarks of the A$^{\prime}$iDM scenario have been discussed. In particular, we fix the $U(1)_D$ coupling $α_D$ equal to the electromagnetic one $α_{EM}$ and $ε$ to its experimental upper bound, and perform a complete scan of the remaining parameters $(M_{χ_1},δ, M_{A^{\prime}})$, discussing the $χ_1$ relic abundance, its direct and indirect searches, as well as potential signals from astrophysics and accelerators. Our systematic scan shows that $α_D$ = $α_{EM}$ is not disfavored, as some previous analyses, limited to specific benchmarks, may suggest. We also find that when the $χ_1$ relic density matches observation direct and indirect searches are not kinematically accessible. On the other hand we find that the projected luminosity of FASER, a detector searching for Long Lived Particles (LLP) decay at the LHC, can probe or rule out the parameters space of the model for $M_{χ_1}\lesssim$ 7 GeV, 100 MeV $\lesssim δ\lesssim$ 300 MeV and $M_{A^{\prime}}\lesssim$ 25 GeV. This range of parameter could be significantly extended by the FASER 2 upgrade proposed for the High-Luminosity phase at the LHC. The parameter space probed by LLP seaches partially overlaps with that probed by $χ_1$ capture in neutron stars.

In this study, we compute the radiative corrections to the $Λ_b \to p$ transition form factors at next-to-leading logarithmic accuracy, employing the framework of QCD light-cone sum rules with the light-cone distribution amplitudes of the $Λ_b$ baryon. The factorization formulae of the vacuum-to-$Λ_b$ correlation function, constructed from the interpolating current for the proton, are derived at leading power in $m_p / m_{Λ_b}$, using the method of regions. With our specific choice of interpolating current, only the twist-4 distribution amplitude of the $Λ_b$ baryon contributes to the form factors. Numerically, we find that the next-to-leading order QCD perturbative corrections reduce the tree-level form factors to approximately 65$\%$ of their original value, with the next-to-leading-order jet function providing the dominant contribution. In the large-energy limit ($E_p \to \infty$), the form factors exhibit a clear $1/E_p^3$ scaling, consistent with the expected power-counting behavior. By applying the $z$-series parameterization to perform a combined fit of the form factors from our results and available lattice QCD simulations, we further investigate the decay rate of $Λ_b \to p \ell^- \barν_{\ell}$ and extract the CKM matrix element $|V_{ub}| = (3.33\pm 0.43 ) \times 10^{-3}$.

We establish an optimal upper bound (negative result) of $\sim 0.526$ on the competitive ratio of the fractional version of online bipartite matching with two-sided vertex arrivals, matching the lower bound (positive result) achieved by Wang and Wong (ICALP 2015), and Tang and Zhang (EC 2024).

We introduce a geometric method for online transfer identification of a deterministic linear time-invariant system. At the beginning of the identification process, we assume access to abundant data from a system that is similar, though not identical, to the true system. In the early stages of data collection from the true system, the dataset generated is still not sufficiently informative to enable precise identification. Consequently, multiple candidate models remain consistent with the observations available at that point. Our method picks, at each instant, the model closest to the similar system that is consistent with the current data. As more data are collected, the proposed model gradually moves away from the initial similar system and eventually converges to the true system when the data set grows to be informative. Numerical examples demonstrate the effectiveness of the incremental transfer identification paradigm, where identified models with minimal data are used to solve the pole placement problem.

To date, there has been significant interest in globular cluster (GC)-rich ultra-diffuse galaxies (UDGs) and the evidence that they have formed via an unexpected, ``failed galaxy'' formation pathway. The majority of the evidence for ``failed galaxy'' UDGs originates from spectroscopic observations targeting passive GC-rich UDGs, with a focus on those residing in galaxy clusters. In this work, we study the gas-rich, GC-rich group UDG MATLAS-42 and derive its stellar population properties using the Keck Cosmic Web Imager. We measure a redshift for the galaxy ($V_{\rm R, \star}=2433\pm8$~km s$^{-1}$), confirming the previous assumptions that it is both part of the NGC~502 group and has an associated HI-reservoir ($V_{\rm R,HI}=2423\pm 15$~km s$^{-1}$). We measure integrated stellar populations and find the galaxy to be both young (mass-weighted age $=3.2^{+2.6}_{-1.5}$Gyr) and of average-to-low metallicity ($[M/H]=-1.19^{+0.42}_{-0.30}$ dex). When considering these properties in the context of the galaxy's formation, we note it likely does not follow the ``failed galaxy'' formation pathway commonly attributed to GC-rich, cluster UDGs, as it has experienced recent star formation. At most it started failed, however, it has recently rejuvenated its star formation. Finally, we build a toy model of the passive evolution of this galaxy, finding that its relative GC-richness (i.e., $M_{\rm GC}/M_\star$) will likely decrease with time as GCs slowly evaporate/disrupt to contribute to the stellar mass of the galaxy. Due to this, we hypothesise that it is likely not a low redshift analogue of the progenitor to a ``failed galaxy'' UDGs.