Papers

We present a lattice model for morphogen-controlled branching morphogenesis which combines ideas and concepts from non-equilibrium physics and developmental biology. In this model, the stochastic occupation dynamics of cells is coupled with signaling molecules (morphogens) produced by the cells. We investigate growth patterns governed by morphogen concentration gradients, spanning regimes ranging from the diffusion-limited aggregation limit to the stochastic surface growth (Eden model) limit. Moreover, we introduce control over topology by a local operator and study growth, degrowth, and steady-state dynamics of branched patterns. The topology-preserving steady-state clusters exhibit a power-law scaling of radius of gyration with cluster size, yielding the exponents $0.68\pm0.01$ in square lattice and $0.67\pm 0.01$ in hexagonal lattice.

Temperature fluctuations of the matter produced in relativistic heavy-ion collisions are related to event-by-event fluctuations of the mean transverse momentum and, through the specific heat, to the QCD equation of state. We calculate the temperature-fluctuation cumulants $c_2$, $c_3$, and $c_4$ in the ideal hadron resonance gas (HRG), in an excluded-volume HRG consistent with lattice QCD constraints on baryon repulsion, and in a van der Waals HRG that reproduces the nuclear ground state. At zero baryon density all three models agree with lattice QCD thermodynamics up to the chiral crossover and separate above it. Along the chemical freeze-out curve the models remain close for $\sqrt{s_{NN}} \gtrsim 20$ GeV and separate strongly at lower energies, where baryonic interactions dominate the thermal response. In the van der Waals model the variance $c_2$ develops a minimum along the Widom line of the nuclear liquid-gas transition and $c_3$ changes sign across it. Temperature cumulants thus connect mean-transverse-momentum fluctuations to thermodynamic structures in two regions of the QCD phase diagram.

Extreme epidemic risk is controlled by the right tail of the outbreak-size distribution, but this distribution is generally unknown for non-Markovian spreading on networks. Here we determine this distribution by mapping non-Markovian SIR dynamics to an effective Markovian description. We show that arbitrary infection and recovery time statistics can be incorporated through a single edge transmissibility, yielding an effective Markovian process that reproduces the full outbreak-size statistics. For weakly heterogeneous networks, the reduction yields a universal well-mixed semiclassical theory governed by the bond-percolation reproductive number. Outbreak statistics across diverse waiting-time distributions and topologies collapse onto one predictive curve. For highly heterogeneous and empirical networks, the corresponding effective Markovian dynamics on the network captures the complete distribution. Our results provide a direct route from measured waiting-time distributions to quantitative predictions of network-level extreme-outbreak risk.

We present a refined astrometric and photometric analysis of the well-studied intermediate-age open clusters NGC 2266 and NGC 2324 using high-precision Gaia DR3 data, complemented by 2MASS and LAMOST DR7 catalogs. Probable cluster members are identified using unsupervised machine learning techniques. We apply both Gaussian Mixture Models (GMMs) and pyUPMASK. We find that the GMM-based membership sample yields a cleaner, more coherent cluster sequence in the Gaia CMDs than pyUPMASK. We identified 719 and 852 high-probability members ($P \geq 0.7$) for NGC 2266 and NGC 2324, respectively. Using the parallax method, we determine distances of 3.55 $\pm$ 0.23~kpc for NGC 2266 and 4.18 $\pm$ 0.24~kpc for NGC 2324. The radius estimates for both clusters are 7.23 $\pm$ 0.47 pc and 10.94 $\pm$ 0.63 pc. Isochrone fitting estimated ages of $1.1 \pm 0.1$~Gyr for NGC 2266 and $790 \pm 150$~Myr for NGC 2324. These age estimates were derived assuming metallicities of $Z = 0.0084$ and $Z = 0.0038$, respectively. The King profile fitting indicates that both clusters exhibit compact, well-defined radial structures. Their tidal radii are $8.84'$ (9.13 pc) for NGC 2266 and $10.97'$ (13.34 pc) for NGC 2324. The slopes of the present-day mass functions are $1.13\pm0.18$ for NGC 2266 and $1.24\pm0.19$ for NGC 2324, indicating a deficiency of low-mass stars. The derived mass-function slopes are consistent with dynamical evolution in both clusters. The clusters exhibit short relaxation times, while only NGC 2324 shows a mild indication of mass segregation. This study highlights the power of Gaia astrometry to resolve internal structures within open clusters and refine their dynamical parameters.

Helicity-dependent, or polarised, parton distribution functions describe the longitudinal polarisation of quarks, antiquarks, and gluons inside a polarised nucleon. They encode how the spin of a fast-moving proton or neutron is shared among its partonic constituents and are therefore central to the modern understanding of nucleon spin structure in Quantum Chromodynamics. Helicity PDFs are extracted from global QCD analyses of polarised hard-scattering data, including inclusive deep-inelastic scattering, semi-inclusive deep-inelastic scattering, and polarised proton-proton collisions. This article reviews the definition and physical interpretation of polarised PDFs, the perturbative QCD framework used to determine them, the experimental observables that constrain the different parton flavours, and the statistical methodology of global analyses. The state of the art in polarised PDF determination is presented, together with the impact expected from future measurements at the Electron-Ion Collider.

Cosmic microwave background (CMB) experiments use simulations of instrumental systematic effects to ensure high-fidelity measurements of cosmological parameters. Quantifying the expected magnitude of these effects enables experiments to improve designs, set performance requirements, and understand potential measurement biases from residual systematics. Here we present a new simulation framework, called Map Multi-Tool (MMT), which models beam-related systematics for CMB instruments using a map-based approach. The pipeline convolves simulated sky realizations with distorted intensity and polarization beams, including leakage effects, to produce sky maps and power spectra. These outputs can then be used as inputs for cosmological parameter estimators. this framework enables efficient evaluation of such systematic effects. We demonstrate the capabilities of MMT with examples of non-ideal beams induced by electrical readout crosstalk and detector time constant response. The electrical crosstalk example considers eight different schemes for a time-division multiplexed readout architecture, and shows how they lead to different levels of angular power spectrum leakage for row-switching and inductive crosstalk. The detector time constant example demonstrates how associated uncertainties can alter CMB spectra at high multipoles and bias cosmological parameters. These examples illustrate some of MMT's broad capabilities to inform critical design and calibration decisions to mitigate systematic effects in CMB instruments.

Tokamak disruptions may lead to the acceleration of some electrons to relativistic energies. These so-called runaway electrons (REs) can multiply exponentially via knock-on collisions with thermal electrons. As the resulting RE avalanche is exponentially sensitive to the pre-disruption plasma current, multi-MA RE beams may form in large future devices, risking severe localized wall damage. In this work, an energy and momentum conserving knock-on collision operator is implemented in the 3D nonlinear MHD code JOREK for the full-f relativistic hybrid fluid-kinetic model that describes the REs using the particle-in-cell (PiC) approach both for full-orbit and drift-kinetic markers, which will enable accurate modeling of the RE phase-space dynamics in realistic 3D electromagnetic fields. Such a self-consistent treatment of the RE avalanche and competing losses in the stochastic fields of MHD-active plasmas is required to further the understanding of RE transport and phase-space dynamics in self-consistent interaction with the 3D plasma evolution, which is needed for developing reliable predictions as well as reliable mitigation methods. To make such novel high-fidelity simulations computationally viable, a resampling technique was also implemented to restrict the number of markers. The avalanche model is verified using analytical expressions from literature and applied to a JET-like termination scenario, demonstrating its applicability to realistic 3D MHD active scenarios. Future work on porting to accelerated high-performance computing systems will be needed to cross the long time scales involved, e.g., in periodic termination and re-avalanching that could occur in large devices like ITER.

Altermagnetism, characterized by its ferromagnetism-like spin-splitting band structure and antiferromagnetism-like magnetic order, has garnered considerable attention recently. Although hole doping may promote magnetism in the debated altermagnet candidate RuO2, the evolution of its electronic and magnetic properties under hole doping remains poorly understood. Based on first-principles calculations, we employ quantum oscillations to study hole-doped RuO2. We find that hole doping can enhance spin splitting and reconstruct the Fermi surface in RuO2, which is revealed by the angle-dependent quantum oscillation frequency. By tracking a pair of closed Fermi-surface pockets, we identify a meaningful correlation between the magnetic moment of Ru and a quantum-oscillation-based signature of spin splitting. This correlation follows a quasi-linear trend over a broad doping range, which can be captured by a minimal two-dimensional d-wave altermagnetic model. In addition, the hole-doped RuO2 exhibits a transition from a nonmagnetic to an altermagnetic state via an intermediate state. The quasi-linear correlation through quantum oscillation and the distinct quantum oscillation frequency of the stable altermagnetic state can serve as useful signatures for identifying the altermagnetic state in RuO2. Our results provide a comprehensive framework for understanding hole-doped RuO2, offering new insights into altermagnetic transitions and their identification.

Electronic decay processes provide a fascinating window into correlated electronic rearrangements occurring on ultrafast timescales. Following these dynamics in real time has become increasingly accessible experimentally, but extracting the underlying electronic dynamics from measured spectra requires understanding how nuclear motion shapes the observable signal. Here, we extend an analytical description of time-resolved electronic decay spectra to include dissociative nuclear dynamics and apply it to Interparticle Coulombic Decay (ICD) in the neon dimer. The resulting spectra reproduce the experimentally observed spectral shape and reveal an unexpectedly important role of interference between pathways involving different vibronic resonance states. We further establish a clear connection between the temporal build-up of the spectral structure and the nuclear wavepacket dynamics in the decaying electronic state. Most strikingly, our analytical expressions reveal that the time-dependent integrated ICD signal contains contributions proportional to both $\exp(-t/\tau)$ and $\exp[-t/(2\tau)]$. Nevertheless, a conventional mono-exponential fit can describe the temporal signal remarkably well while yielding a decay lifetime that differs substantially from the underlying value. Applying the theoretically derived fitting model to experimental data for the neon dimer yields an ICD lifetime $\tau$ of 73 fs, rather than the previously extracted 150(50) fs, placing the experimental value within the range of previous theoretical predictions. Since the underlying temporal structure is common to electronic decay processes, our findings have implications for extracting lifetimes from time-resolved decay spectra well beyond ICD.

The maximum current that can be extracted from a diode is a central question in electronic devices, especially for the generation of radiation from microwaves to x-rays. The challenge in its prediction increases significantly when the electron emission is restricted to a small area for which the classical one-dimensional Child-Langmuir law is no longer applicable. We address this unsolved problem using a model that simultaneously includes a small emission area and a small electron emission velocity. New scaling laws are presented for this difficult regime. These results are obtained from three vastly different approaches: a differential equation formulation which provides extremely high resolution, an integral equation formulation which leads to the scaling laws, and a particle-in-cell simulation which shows the temporal-spatial evolution. Comparisons of the predicted maximum current among these three approaches are performed over a large range of parameters, paying special attention to the resolution of the potential minimum in the immediate vicinity of the cathode surface. Corroborations of the scaling laws with experiments on thermionic cathodes and on photoinjectors are indicated. The model consists of a periodic array of electron sheets of finite width in a planar diode, all emitted from a cathode with the same energy. Electron motion is restricted to the direction normal to the cathode. This problem is of interest to the electron device, accelerator, pulsed power, aerospace, and applied mathematics communities.

The gluon Collins-Soper kernel, which encodes the rapidity evolution of transverse-momentum-dependent gluon distributions, is constrained for the first time in the nonperturbative regime, for transverse momentum scales $q_{T} \in [ 300\text{ MeV}, 1.3\text{ GeV}]$. The constraints are determined in lattice QCD at a close-to-physical pion mass $M_\pi = 172(3)\text{ MeV}$, a single lattice spacing $a=0.15\text{ fm}$, and next-to-next-to-leading logarithmic matching in Large-Momentum Effective Theory. These results represent the first step toward a controlled determination of the gluon Collins-Soper kernel in QCD, with eventual phenomenological import and relevance to present and future experiments sensitive to the gluon structure of hadronic matter.

The combination of the long baseline and characteristic energies of solar neutrinos offers an ideal framework to probe invisible neutrino decay. In this work we present the first constraint on invisible solar-neutrino decay using coherent elastic neutrino-nucleus scattering, recently observed in dark matter direct detection experiments. Through a combined analysis of nuclear-recoil data from XENONnT, PandaX-4T, and LUX-ZEPLIN, we constrain the lifetime of the neutrino mass state $\nu_{2}$, obtaining a bound already comparable in strength to that from the Sudbury Neutrino Observatory. We further evaluate the sensitivity that could be reached by a future xenon-based dark matter detector. For this projection, we extend the analysis to electronic-recoil data, estimating the impact of detecting lower-energy solar neutrinos from the $pp$-chain via elastic scattering off electrons. This channel would allow us to place strong constraints on the lifetimes of both the $\nu_{1}$ and $\nu_{2}$ mass eigenstates. Our results show that, with nominal future exposures, nuclear-recoil data would improve the current bound by about one order of magnitude, while electronic-recoil data would open a new detection channel for low-energy solar neutrinos, surpassing existing dedicated solar-neutrino bounds by 1 to 2 orders of magnitude.

The Traveling Salesman Problem is a classical NP-hard problem with significant implications in logistics, circuit design, and operations research. This paper presents a comparative study of four approaches to solving the Traveling Salesman Problem: brute-force enumeration, a 2-approximation algorithm using minimum spanning trees, simulated annealing, and the Quantum Approximate Optimization Algorithm. We implement each technique and evaluate them on graphs of varying sizes to analyze performance, solution quality, and scalability. In doing so, we have also developed an open-source framework that allows researchers and practitioners to explore, test and extend these methods.

The Arches cluster, located in the Galactic Centre (GC) is one of the best astrophysical laboratories to study the properties of massive stars and young massive clusters (YMCs). However, several fundamental parameters of the Arches cluster remain uncertain. Our goal is to constrain key cluster parameters (cluster age, mass, and initial mass function, IMF) by comparing the observed stellar radio flux density distribution of the Arches cluster to those derived from a set of synthetic clusters. We use the deep X-band (10 GHz) Very Large Array data from our previous radio continuum study of the Arches cluster. We model each simulated cluster with three parameters: age, mass, and IMF slope. We use three different stellar evolutionary models: GENEC, PARSEC, and MIST at two different metallicities, solar ($Z=0.014$) and super-solar ($Z=0.020$). We run Markov-chain Monte-Carlo simulations for each model/metallicity combination in order to explore parameter space. All models and metallicities return preferred ages in the $2\lesssim t_{\rm age}/{\rm Myr}\lesssim 3$ range. We obtain an IMF slope of $\alpha_{\rm IMF}=-1.85^{+0.28}_{-0.20}$, averaged over all models, where uncertainties are dominated by the degeneracy between cluster mass and IMF slope. If we use the IMF slope from previous infrared studies as prior, the cluster mass distributions peak at $\sim2.7\times10^4\, M_\odot$ and we can establish a lower limit at $\gtrsim2\times10^4 M_\odot$ for the Arches cluster mass. Radio continuum observations of their most massive stars can be used to constrain YMC parameters. In the case of the Arches cluster, age can be determined regardless of prior spectroscopic information, which can be useful to characterise newly discovered YMCs in the GC. Our results support the idea that a top-heavy IMF may be preferred in the GC or in YMCs in general.

Hydrodynamics provides a universal description of many-body systems at long wavelengths. Its long-lived collective excitations, known as hydrodynamic modes, admit long-wavelength expansions whose convergence is encoded in the analytic structure of retarded correlators of conserved quantities in thermal equilibrium. We show that a boost can change which nonhydrodynamic singularity limits such an expansion. In the large-boost limit, the relevant singularity originates in the large-momentum, near-light-cone region of the rest-frame spectrum. After factoring out the Lorentz-factor growth, the rescaled convergence scale is controlled by the microscopic spectral structure of the theory. We explicitly demonstrate this in two examples: relaxation-time kinetic theory and holography.

In this work, we present a novel perspective on the coupling force employed to compensate the interface artifacts prevalent in adaptive resolution simulations (AdResS) of open many-particle systems. We show that a substantial part of this "thermodynamic force" can be framed in terms of the theoretical model of the Liouville-type hierarchy for open systems. The correspondence is made explicit for the case of a simple atomistic fluid, for which a one-dimensional integral expression is derived. This enables the analysis for dependencies of the thermodynamic force on important simulation parameters, which is taken to inspire both simplifications for the numerical calculation of the thermodynamic force and new criteria for its validation that are adequate to the interfacial nature of the problem. The theoretical claims are then verified in a simulation study of the atomistic supercritical Lennard-Jones fluid at different thermodynamic states.

Model-based active flow control requires predictive models that are accurate, stable, and fast enough for real-time optimisation. In controlled wake flows, this is often achieved through Reduced-Order Models (ROMs) that first compress high-dimensional velocity snapshots into a latent space and then learn a time- stepping predictor for the dynamics in the latent space. Here, we study how the choice of the spatial encoder affects the predictability of the resulting latent coordinates for wake flows under control inputs. Using two actuated 2D wake configurations, a simplified truck wake and the fluidic pinball, we compare Proper Orthogonal Decomposition (POD) against nonlinear Convolutional Autoencoders (CAEs) and two types of variational autoencoders for compression, and evaluate several temporal predictors based on Long Short-Term Memory networks. CAEs achieve higher compression efficiency and sharper short-term reconstructions, but they produce latent dynamics that are more irregular and with broadband spectral content. As a consequence, long-horizon forecasts degrade faster and show a higher probability of catastrophic divergence than POD-based models. POD yields smoother latent trajectories that are easier to learn and extrapolate, leading to more reliable predictions beyond the short- term regime. These results reveal a clear trade-off between compactness and forecast accuracy, and suggest that the stability of the latent dynamics prediction can outweigh maximal compression. This is particularly relevant for control strategies rooted in forecasts of the dynamics, such as model predictive control and reinforcement learning. The findings provide practical guidance for designing actuation-aware, hardware-feasible predictive ROMs for real-time flow control.

Solid tumours and other hypoxic regions are difficult to treat with conventional systemic drug delivery, which distributes therapeutics non-specifically and increases toxicity in off-target sites. Biohybrid microrobots driven by living cells offer a self-powered, bio-compatible solution to autonomous targeted delivery, however, existing platforms often require external stimuli to move and locate towards target zones. We present a computational model of an H-shaped biohybrid microrobot, actuated by neonatal rat cardiomyocytes coupled to the body through an anisotropic friction-ratchet generating a net forward locomotion. The model is simulated under normoxic straight-line conditions and hypoxic gradient-steering conditions for two distinct phenotypes, atrial and ventricular. Ventricular cells produce a $4.35\times$ increase in locomotion speed over atrial cells at an equivalent cost of transport and a $2.91\times$ greater heading response under an applied gradient, confirming that phenotype is an underexploited design variable. The computational model in this study shows autonomous, gradient-based steering in a cardiomyocyte-based platform and the effectiveness of treating cardiomyocyte phenotype as an explicit design parameter. These findings support the long-term feasibility of cardiomyocyte-driven microrobots for autonomous, self-targeted therapeutic delivery in hypoxic regions and as such offer a route to reducing systemic drug exposure relative to conventional treatment.

Suspension microarrays based on optically encoded microbeads have become one of the most versatile platforms for multiplexed bioanalysis because they combine solution-phase reaction kinetics, flexible assay design, and high-throughput detection. However, despite more than two decades of intense research, no consensus has emerged regarding the optimal strategies for particle encoding, surface functionalization, and signal decoding. Progress has mainly been driven by incremental improvements in individual materials rather than by systematic comparison of competing technological concepts. This review critically evaluates the main approaches to the fabrication of optically encoded microbeads, including post-synthetic (swelling and layer-by-layer assembly) and in situ encoding strategies, and proposes a mechanistic classification of in situ methods of particle formation into polymerization-driven and confinement-controlled ones. Instead of comparing the fabrication methods solely in terms of encoding capacity, we assess their relative merits in terms of structural control, code stability, scalability, compatibility with biofunctionalization, and suitability for clinical implementation. We further examine the strengths and limitations of organic fluorophores, aggregation-induced emission luminogens, semiconductor quantum dots, and upconversion nanoparticles and show that no encoding material is universally optimal and that performance is determined by trade-offs between optical properties, manufacturing complexity, and stability in biological media. We argue that future progress will depend not as much on increasing the theoretical number of optical codes as on improving the code reproducibility, minimizing spectral crosstalk and nonspecific interactions, and employing microfluidic fabrication, antifouling surface chemistry, automated spectral decoding, and artificial intelligence-assisted data analysis. These developments are expected to transform suspension microarrays from multiplexed analytical tools into standardized lab-on-a-microbead platforms suitable for next-generation clinical diagnostics.

Entanglement distillation and entanglement swapping have been extensively studied assuming perfect quantum memories. However, near-term quantum networks will be fundamentally limited by quantum memories with a finite coherence time, resulting in complex choices for the timing and ordering of these operations. In this work, we study entanglement distillation and entanglement swapping at the level of the elementary building blocks of noisy quantum repeater networks, with the goal of elucidating the fundamental tradeoffs induced by memory decoherence. First, we focus on a minimal one-hop setting, where we analytically compare “distill-as-soon-as-possible” and “distill-as-late-as-possible” strategies against a baseline strategy that simply discards the older entangled state. We find that in the low memory coherence time regime, discarding the older entangled state achieves higher expected output fidelity, while in the high coherence time regime, delaying distillation until the end achieves the highest expected output fidelity and, over most of the deadline range, the highest weighted coherent information, at the expense of a lower success probability. We then extend our analysis to two-hop repeater chains using Monte Carlo simulation. In this setting, we find that the highest weighted coherent information is achieved by strategies that defer distillation to the end of the time window, with Distill-ALAP-then-Swap-ALAP and Swap-ASAP-then-Distill-ALAP leading at different operating points, while Discard-Oldest-then-Swap never reaches positive weighted coherent information in any regime tested. Together, these results clarify how decoherence reshapes the optimal operation timing in quantum networks and provide instructive insights into the link-level principles that govern larger-scale architectures.

The nature of the scalar charmed meson $D_0^*(2300)$ remains one of the most intriguing questions in hadron spectroscopy. A prominent interpretation is a two-pole structure generated by the coupled channels $D\pi$, $D\eta$, $D_s\bar K$, and $D\eta'$, in which the lower pole couples mainly to $D\pi$ and the higher pole to $D_s\bar K$. Following this picture, we calculate the decay constants of these two poles using the effective Lagrangian approach. The resulting values, $f_{D_0^*}^{(\mathrm{lower})}=68.46^{+0.93}_{-1.25}\,\mathrm{MeV}$ and $f_{D_0^*}^{(\mathrm{higher})}=90.51^{+5.91}_{-11.64}\,\mathrm{MeV}$, are substantially smaller than those predicted by conventional $c\bar q$ excited-state scenarios. This difference suggests that decay constants can serve as a sensitive probe to discriminate between different internal structures of the $D_0^*(2300)$. As a phenomenological application, we further predict the branching fractions for the Cabibbo-favored decays $B_s \to D_s D_0^*$, $\Lambda_b \to \Lambda_c D_0^*$, and $\Xi_b \to \Xi_c D_0^*$ within the factorization approach. These predictions provide crucial tests to validate the two-pole interpretation of the $D_0^*(2300)$.

We study the real-frequency structure of the self-energy in the bilayer Hubbard model, using the dynamical cluster approximation. At half filling, the Mott insulator-band insulator (MI-BI) crossover involves a rearrangement of self-energy poles between the bonding and antibonding bands; these poles cross as the interlayer hopping $t_{\perp}$ is varied. Upon doping, this pole structure produces a band-selective pseudogap and enhances $s^{\pm}$-wave superconductivity. The order parameter is maximized near the MI-BI boundary, where low-energy anomalous self-energy poles develop simultaneously in both bands and cooperatively enhance the pairing. We further show that these self-energy poles can be interpreted as emergent fermionic excitations, offering an enhanced-pairing mechanism in common with the single-layer Hubbard model. The controllability of these poles through $t_{\perp}$ makes the bilayer system an unconventional platform for optimizing strongly correlated superconductivity.

High throughput optical communication links require the use of adaptive optics (AO) to compensate for atmospheric turbulence even in strong perturbation conditions and at low elevation. Considering the intensity fluctuations brought by scintillation, we present a new slope measurement algorithm for the Shack–Hartmann wavefront sensor (SHWFS), based on a joint maximum likelihood approach. We show that this estimator is robust to sensor saturation and widens by more than two orders of magnitude the intensity range exploitable for reliable slope measurements compared to classical algorithms. Consequently, by increasing the intensity assigned to the wavefront sensor, we also increase the number of valid measurements despite sensor saturation.

The Wide-field Spectroscopic Telescope (WST) is a planned 12-meter-class dedicated spectroscopic facility designed to address key scientific challenges through large spectroscopic surveys. This paper presents design and performance trade-offs for the Low-Resolution Multi-Object Spectrograph (MOS-LR) instrument. With a multiplex of 30,000 covering a field of view of 3.1 square degrees, this instrument will provide unprecedented survey efficiency, an order of magnitude beyond those of current facilities. Covering the 370 to 930 nm range at a resolving power of 3,000 with a sky-projected fiber diameter of 1 arcsec, this instrument faces extreme challenges in design, manufacturing, and maintenance. We present a systematic approach to trading off optical and mechanical design options, taking into account constraints such as volume and mass, but also projected availability of detectors and gratings etc.

Bow shocks (BSs) around massive stars are commonly identified in mid-infrared (MIR) surveys. In contrast, systematic optical investigations of these structures remain scarce with only a few possible detections reported so far. We performed a targeted Halpha imaging survey of 78 IR BS candidates compiled from literature catalogues. Observations were obtained with multiple ground-based facilities and complemented with archival MIR images from Spitzer and WISE. For the detected bow structures, geometrical parameters were measured, and the bows were classified based on the parameters of their central stars, the measured stand-off distances and adopted plausible ISM conditions Clear arc-shaped Halpha nebulae are detected in 15 objects, with one additional BS discovered serendipitously. A further 35 objects exhibit diffuse Halpha emission associated with complex background structures, while 28 show no detectable Halpha emission. The Halpha and IR morphologies generally trace the same large-scale structures, although most of the IR arcs lie slightly closer to the star and appear broader than their optical counterparts. We find that several systems are consistent with radiation-supported BSs, bow waves or dust waves, while others remain compatible with classical wind-supported BSs. This survey demonstrates that a fraction of IR BS candidates around OB stars also exhibit detectable ionised gas structures in Halpha, and both stellar wind momentum and radiation pressure can contribute to shaping these structures. No correlation is found between the detection of an Halpha BS and the stellar parameters, and the overlap in objects observed in Halpha and in the radio regime was too small for firm conclusions. Future spectroscopic observations will be required to determine the physical conditions and kinematics of the ionised gas and to further constrain the nature of these BS systems.

Quasi-two-dimensional (2D) van der Waals (vdW) ferromagnets such as the series Fe$_{3-x}$GeTe$_2$, with a relatively high Curie temperature and robust metallicity, offer an ideal platform for investigating itinerant magnetism in reduced dimensions. Here, we present a comprehensive electron spin resonance (ESR) investigation of single-crystalline almost-stoichiometric Fe$_{3.03 \pm 0.03}$GeTe$_{2}$ across wide ranges of frequencies, temperatures, and magnetic fields to gain quantitative insights into its magnetic anisotropy and spin dynamics. Frequency-dependent ESR measurements establish Fe$_{3}$GeTe$_{2}$ as an easy-axis ferromagnet. Temperature-dependent high-field ESR reveals a large internal field that gradually decreases at higher temperatures. Remarkably, this internal field persists even above $T_\mathrm{C}$, evidencing short-range spin correlations in Fe$_{3}$GeTe$_{2}$. Analysis of spin-wave modes yields a strong uniaxial magnetocrystalline anisotropy $K_{\text{int}} \approx - 5 \times 10^6$ erg cm$^{-3}$ at 3 K and a large magnon gap $\Delta(3 \mathrm{K})$ $\approx$ 87.8 $\pm$ 13.7 GHz ($\approx$ 0.363 $\pm$ 0.057 meV). Our study highlights that small variations in Fe content in Fe$_{3}$GeTe$_{2}$ lead to substantial changes in the magnon gap at low temperatures, indicating the extreme sensitivity of spin dynamics to the chemical composition. These results establish Fe$_{3}$GeTe$_{2}$ as a model vdW ferromagnet for exploring tunable anisotropies and magnon excitations in metallic 2D magnets.

Bayesian calibration of material constitutive parameters from multimodal mechanical test data is often limited by the need to specify a joint likelihood across measurement modalities that differ in dimensionality, noise structure, and physical units. The resulting posteriors are often broad or strongly correlated, causing standard Markov Chain Monte Carlo (MCMC) samplers to mix poorly. Here, we present an amortized, likelihood-free framework that combines Gaussian process (GP) surrogates with Conditional Flow Matching (CFM) to learn conditional posteriors over constitutive parameters directly from synthetic multimodal parameter–observation pairs, avoiding hand-crafted likelihoods and repeated MCMC sampling. Once trained, the GP–CFM model generates posterior samples for each new specimen at negligible cost. The utility of this novel approach is demonstrated in this paper by estimating the values of Young's modulus and yield strength from the early portion of the force–displacement ($F$–$D$) curve and a Digital Image Correlation (DIC)-based displacement field measured in a Small Punch Test (SPT). It is observed that the $F$–$D$ data alone produce broad posteriors, consistent with limited parameter discrimination in the global response. Adding the DIC-measured displacement field was seen to contract the posteriors and shift them towards the independently measured tensile reference values. This work establishes a robust likelihood-free framework for the inference of material constitutive parameters from multimodal data, demonstrated through SPT–DIC integration.

Peculiar long gamma-ray bursts (GRBs), exemplified by GRBs 211211A and 230307A, exhibit a long-duration multi-component prompt emission, an X-ray plateau in their afterglow, and a kilonova signature. Their origin remains highly debated. In this work, we present a unified picture for these events based on neutron star–white dwarf (NS–WD) mergers involving a pre-merger magnetar and a massive WD. In this picture, tidal disruption of the WD forms a constant-entropy accretion disk. Hyperaccretion from this disk onto the NS during the early accretion phase amplifies its toroidal magnetic field to strengths sufficient to trigger repeated magnetar giant flares (GFs). The main burst (MB) of the prompt emission consists of a “forest” of initial spikes from these GFs, while the subsequent magnetic propeller phase generates the extended emission (EE) and naturally explains the observed MB–EE trough. Crucially, the $e^{\pm}$-$\gamma$ fireball associated with each GF initial spike shocks the NS crust, leading to crustal ejection that synthesizes r-process heavy elements via the $\alpha$-rich freeze-out mechanism, thereby resolving the r-process deficit in conventional NS–WD hydrodynamic simulations. The ensemble of such fireballs over the MB duration collectively yields $M_{\rm ej}\gtrsim 10^{-5}-10^{-3}\,M_\odot$ of ejecta, sufficient to power the observed kilonova signature when further boosted by the spin-down of the post-merger magnetar. Meanwhile, the spin-down radiation also powers the X-ray plateau. This tidally disrupted NS–WD merger picture provides a self-consistent framework that unifies the prompt emission, afterglow, kilonova, and r-process nucleosynthesis observed in peculiar long GRBs.

Upon fixing the adiabatic index, the spherically symmetric liquid Lane-Emden stars governed by the Euler-Poisson system with a "stiffened gas" equation of state $p=\rho^\gamma-1$ form a one-parameter family, naturally parametrised by the central density $\kappa=\bar\rho_\kappa(0)\in(1,\infty)$. In contrast to the gaseous case, the liquid free boundary breaks the self-similarity of the family and bends the mass-radius curve, creating extrema of the mass when $\gamma<2(d-1)/d$. We formulate a turning point principle in the spirit of Zel'dovich, Wheeler and Thorne, and of its rigorous relativistic counterpart from the works of Hadžić, Lin and Rein: the number of radial growing modes equals the negative Morse index of the linearised operator, is locally constant along the family, and can change only at the turning points of the mass-radius curve, the bending orientation there dictating whether a growing mode is gained or lost. We describe the large central density limit in which the gaseous tail (read off from a planar dynamical system) determines whether the mass-radius curve spirals, and hence whether the number of growing modes remains bounded or tends to infinity. As corollaries we recover and sharpen the known radial (in)stability results for liquid Lane-Emden stars and, in combination with existing non-radial analysis, obtain a turning point criterion for non-radial stability.

Technological progress is a double-edged sword in the world of radio astronomy: improvements in antennas, receivers, and digital backends increase sensitivity, but rapid growth in terrestrial and orbital communications has caused a steep rise in radio-frequency interference (RFI). Modern datasets have become increasingly contaminated by RFI that is difficult to remove and can mimic or obscure astrophysical signals, complicating the search for objects such fast radio bursts (FRBs), pulsars, and technosignatures. The lunar farside has such been proposed as a site for radio-quiet observations, motivating missions such as the Lunar Farside Transients and Technology Telescope (LFT3) and others. However, planned lunar missions may introduce intended and unintended radio emissions into this protected environment. We use a LFT3-like instrument to model the evolution of the apparent lunar farside RFI environment over the coming years. Using a planned lunar mission catalogue and models for intended and unintended emissions, we estimate the received RFI over the 0.1-2700 MHz frequency range. We find that while intended emissions are concentrated near communications bands, particularly 2.4-2.6 GHz, unintended emissions contaminate broad regions of the LFT3 band. We further find that, under the assumptions of our model, uniform UEMR shielding of at least 30 dB is required to place the maximum interference below the sensitivity of a LFT3-like instrument; more sensitive telescopes would require higher UEMR shielding. We predict that the lunar farside will remain usable for LFT3-like observations, but will become increasingly contaminated as the lunar satellite population grows. This highlights the decreasing window of opportunity for measurements of the lunar farside's radio quiet environment and should inform future mission design and policy choices for the protection of Moon-based radio science.