The scale-dependent bias in halo and galaxy power spectra is a key signature of local primordial non-Gaussianity (local PNG), with PNG sensitivity scaling as $b_ϕ/b_1$ -- the ratio of their responses to long-wavelength primordial potential $b_ϕ$ and late-time density fluctuations $b_1$. For number density fluctuations, these responses are closely tied by the universality relation, limiting the achievable ratio. We show that size density fluctuations strongly violate this relation, thus evading the limit. For galaxy-mass halos, sizes have a vanishingly small density response but a sizable, negative local PNG response, implying an effective $b_ϕ/b_1$ that is large in magnitude and opposite in sign to that of number counts. This makes galaxy sizes complementary probes of local PNG from the same galaxy sample, without any sample split. For a DESI-like survey, a multi-tracer analysis combining galaxy numbers and sizes improves the local-PNG detection significance by a factor of $\sim\!3.6$. Due to the sign flip, the number-size cross power spectrum further provides a handle on systematics in the event of a detection.

A new measurement of the Hubble constant $H_0$ is presented using the statistical dark siren method applied to a sample of seven well-localized gravitational-wave (GW) events from the fourth LIGO-Virgo-KAGRA (LVK) observing run and ten additional events from the first three runs. Galaxy catalogs from the DESI Legacy Imaging Survey (LS) are combined with a deep learning model to compute photometric redshift probability density functions. We extend our previous analysis by including the events GW230731_215307 and GW230927_153832, using sky maps from the fourth Gravitational-Wave Transient Catalog (GWTC-4), and introducing key methodological improvements: $r$-band luminosity weighting of host galaxies; an extended GW likelihood that incorporates information from the binary black hole component masses; and a consistent treatment of selection effects that accounts for the incompleteness of the magnitude-limited LS galaxy catalog. Using a total of 17 well-localized dark sirens (seven from the first part of the fourth observing run, O4a), we obtain $H_0 = 78.8^{+14.6}_{-12.2}$ km/s/Mpc without luminosity weighting and $H_0 = 78.2^{+12.0}_{-11.0}$ km/s/Mpc when applying $r$-band luminosity weighting. Finally, we combine the luminosity-weighted dark siren sample with the bright siren GW170817, including constraints on the jet viewing angle and corrections for the host galaxy peculiar velocity, to obtain a final constraint of $H_0 = 69.9^{+4.1}_{-4.0}$ km/s/Mpc, representing an improvement of approximately 11% in the uncertainty relative to the GW170817-only result.

Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse datasets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000 times faster than DFT. While previous MLIP training datasets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) dataset provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pre-trained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation-solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion-correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations.

Construction of creation operators which can properly sample the underlying energy eigenstates remains a fundamental first step in lattice QCD spectroscopy calculations, particularly when the spectrum includes states with different composition such as mesons, glueballs, multi-particle states, etc. We tackle this issue in the study of the scalar glueball and charmonium mixing, where we use improved operators for both types of states to resolve the low-lying spectrum and identify the dominant composition of each state in a mass regime where the glueball is stable. We include derivative-based meson operators combined with distillation profiles, as well as glueball operators built from the chromo-magnetic field and its derivatives which retain angular momentum information from their continuum counterparts. We comment on the advantages of these operators, particularly on the construction and implementation of the glueball ones, thanks to which we identify the lightest iso-scalar state as glueball-dominated $0^{++}$.

Satellite galaxies in the Local Group tend to be distributed in thin, planar configurations, with many sharing coherent orbital motion. Galaxy formation simulations in $Λ$CDM have historically struggled to produce similar structures, leading to the so-called "planes of satellites problem". In this work, we investigate whether the emergence of such structures is connected to the mass of a major merger at $z\sim2$, analogous to the Gaia-Sausage-Enceladus (GSE) event in the Milky Way. We use the VINTERGATAN-GM suite of high-resolution zoom-in simulations, comprising five realizations of the same Milky Way-mass halo generated through targeted genetic modifications of a GSE progenitor. The GSE-like merger mass ratio is systematically varied from 1:10 to 1:2.1, while keeping the final dynamical mass and large-scale environment fixed. We find a clear and consistent trend: more massive GSE-like mergers lead to satellite populations that are both more planar and more kinematically coherent. In particular, simulations with merger mass ratios larger than 1:6 develop Kinematic Persistent Planes (KPPs), in which at least 40% of satellites co-orbit around a common axis over extended periods, comparable to those observed in the Milky Way. These structures arise when sufficiently massive mergers, accreted along the direction of maximum compression of the Lagrangian volume, produce flattened host halos with anisotropic velocity dispersions aligned with the merger direction. The merger aligns the host halo's minor axis with the direction of flattening of the surrounding cosmic web, and planes of satellites then emerge through two complementary processes: (i) satellites preferentially infall along the host's equatorial plane, and (ii) anisotropic dynamical friction in the non-spherical halo gradually reshapes their orbits toward this plane, generating coherent and long-lived planar configurations.

High-dimensional Schrödinger systems arising from tensor-product discretizations suffer from exponential state growth, making direct controller synthesis and real-time closed-loop simulation computationally challenging. Hierarchical Tucker (HT) tensor representations offer scalable low-rank surrogates, but the impact of fixed-rank truncation on closed-loop stability is not well understood. This paper develops a local robustness framework for sampled-data feedback control implemented with fixed-rank HT projections. By viewing each truncation as a bounded, rank-dependent perturbation of the nominal closed loop, and assuming a local phase-invariant contraction certificate together with trajectory-level hierarchical spectral decay, we show that the HT-projected dynamics are practically exponentially stable: trajectories converge to a dimension-independent tube whose radius decreases with the prescribed rank. We further obtain an explicit logarithmic rank-accuracy relation and establish conditions under which controllers designed on the HT-truncated surrogate model retain practical exponential tracking guarantees when deployed on the full system, together with an explicit bound quantifying the resulting surrogate-to-plant mismatch. A compact lattice example demonstrates the applicability of the framework.

Quantum extreme learning machines (QELMs) are unconventional computing architectures that bear remarkable promise in both classical and quantum machine-learning tasks, such as the estimate of quantum state properties. However, the probabilistic nature of quantum measurements demands extensive repetitions for training to precisely estimate expectation values, imposing stringent trade-offs among experimental resources, acquisition time, and signal-to-noise ratio, particularly for large datasets. Here we introduce a paradigm shift by harnessing the correspondence between stimulated and spontaneous emission. The QELM is trained exclusively with intense classical fields, yet it performs inference directly on previously unseen quantum input states to predict their quantum properties. This strategy dramatically reduces acquisition times while substantially enhancing the signal-to-noise ratio. Using frequency-bin-encoded biphoton states, implemented here for the first time in a quantum machine-learning architecture, we demonstrate entanglement witnessing of two-qubit states with (93 +- 4)% accuracy, multi-dimensional entanglement detection, and learning of the Hamiltonian governing photon-pair generation with a fidelity of (96 +- 4)%. By establishing classical training as a scalable route to quantum feature extraction, our results bridge macroscopic observables and nonclassical correlations, opening a new pathway toward faster and more robust quantum neural networks

Maps of the sky in millimeter wavelengths contain rich information on cosmology through anisotropies of the cosmic microwave background (CMB). Creating multifrequency sky maps of anisotropies in the $I$, $Q$, and $U$ Stokes parameters is one of the first steps of CMB cosmology analyses. In this work, we describe the production and validation of a set of sky maps from the South Pole Telescope's third-generation camera, SPT-3G. The maps are from data taken in frequency bands centered at 95, 150, and 220 GHz and taken during the first two years, 2019 and 2020, of the SPT-3G Main survey, which covers $4\%$ of the sky. We applied high-pass filters to time series of individual detectors and binned the filtered time series samples into map pixels. After that, we calibrated and cleaned the maps to reduce known systematic errors. In addition, we searched for other systematic errors through null tests and mitigated a significant systematic error detected therein. The white noise levels of the full-depth maps of the $I$ Stokes parameter are $5.4$, $4.4$, and $16.2$ $\mathrm{μK}$-$\mathrm{arcmin}$ in the 95, 150, and 220 GHz bands, respectively, and $8.4$, $6.6$, and $25.8$ $\mathrm{μK}$-$\mathrm{arcmin}$ for $Q/U$. These maps are the deepest to date used for measurements of mid-to-high-$\ell$ primary temperature and $E$-mode polarization CMB anisotropies, and reconstructions of the CMB gravitational lensing potential. We make these maps and supporting data products publicly accessible.

We compute the full-sky angular power spectrum and bispectrum, along with their Fisher matrices, to forecast constraints on cosmological parameters for the BINGO and SKA1-MID Band 2 radio telescopes. This represents the first forecast analysis using the full-sky relativistic bispectrum in redshift space for these surveys. Our results show that the second-order velocity contribution, often neglected under the Limber approximation, accounts for approximately $24\%$ of the total signal at low redshifts, indicating that it must be included for accurate modeling. Using these forecasts, we find that while the bispectrum provides constraints comparable to the angular power spectrum for $Λ$CDM and ${\rm w}$CDM models, it becomes a powerful probe of dynamical dark energy. Restricting the analysis to linear scales, we show that the inclusion of the bispectrum yields a substantial improvement in the determination of the Chevallier-Polarski-Linder (CPL) parameters. In particular, the joint analysis of the bispectrum, power spectrum, and Planck CMB data improves constraints on ${\rm w}_0$ and ${\rm w}_a$ by over $70\%$, and the Hubble parameter $h$ by approximately $60\%$. These results underscore the importance of relativistic bispectrum for breaking parameter degeneracies and probing the nature of dark energy with upcoming large-scale structure surveys.

The problem of classifying all unitary R-matrices of arbitrary finite dimension that have precisely two distinct eigenvalues is described, working up to a natural equivalence relation given by the characters of their braid group representations. Up to one class that might or might not exist in even dimension larger than two, a full classification theorem is obtained.

The $B$-factory experiments operate at electron-positron colliders with beam energies precisely tuned for optimal $B^{0}\text{-}\bar{B}^{0}$ meson pair production. These $B^{0}\text{-}\bar{B}^{0}$ meson pairs are produced entangled and offer a unique opportunity to explore quantum correlations and examine the foundational aspects of quantum mechanics. In this work, we present a comprehensive analysis of entanglement metrics in the $B$-meson system within the framework of open quantum systems, which introduces decoherence due to interactions with the environment. We examine several distinct entanglement measures, each highlighting different facets of quantum entanglement and its sensitivity to decoherence effects. We further analyze the impact of decoherence by systematically varying the decoherence parameter across different scales.

We study sterile neutrino dark matter in a minimal Type-I Dirac seesaw framework where the states responsible for generating Dirac neutrino masses at tree level can be viable dark matter candidates. A $\mathcal{Z}_6$ symmetry, spontaneously broken to a residual $\mathcal{Z}_3$ by the vacuum expectation value of a singlet scalar, forbids Majorana mass operators and ensures neutrino Diracness. The lightest sterile neutrino is produced non-thermally via freeze-in from decays of Standard Model particles and an additional scalar state. We show that the presence of an additional right-handed mixing angle, $θ_R$, opens up viable regions of parameter space where the observed dark matter relic abundance can be reproduced while maintaining cosmological stability. This mainly stems from the absence of X-ray astrophysical constraints in our scenario. We further find that the freeze-in production of right-handed neutrinos yields a negligible contribution to $ΔN_{\rm eff}$, consistent with current cosmological bounds.

The Potential Field Source Surface (PFSS) model is the most used approach for extrapolating the global coronal magnetic field, offering efficiency and strong performance at large scales. However, PFSS assumes a potential coronal field, so it cannot account for distortions from electric currents. More advanced methods, such as nonlinear force-free field (NLFFF) models, can represent these effects but are much more computationally intensive. Recent observational techniques also allow 3D reconstruction of coronal loops, which trace solar magnetic field geometry. This work develops a new approach that constrains the PFSS model using 3D coronal loop information, improving agreement with observations while keeping efficiency. The model is based on PFSS field constraints from photospheric data but allows magnetic field deviations from the potential state within loop-influenced regions, maintaining control over divergence and force-freeness. We adapted NLFFF optimization to the PFSS framework, enabling multiple physical constraints. Our functional includes up to three terms: divergence-free, loop geometry, and force-free. The resulting Python algorithm was tested with synthetic loops, using Carrington rotation 2284 as the lower boundary. This method yields magnetic field solutions that better match the geometry of included loops and controls divergence and force-freeness. Our results show that 3D coronal loop information can be incorporated into PFSS, largely preserving computational efficiency even with many loops. This approach lets PFSS better reflect observed coronal structures without significant computational cost.

Strain engineering provides a powerful route for tuning the electronic properties of two-dimensional (2D) materials, but exploring the full multidimensional strain space with density functional theory (DFT) is computationally prohibitive due to the nonlinear coupling between normal and shear components. In this work, we introduce a Transformer-based, multi-target surrogate model framework that achieves DFT-level bandgap prediction accuracy, reaching a mean absolute error of 0.0103 eV while retaining full interpretability through attention-weight analysis. The learned self-attention map consistently identifies shear strain as the interaction center that influences both bandgap and phonon stability, an insight not readily captured by classical feature-importance metrics. This work establishes attention-based architectures as physically interpretable surrogate models for multi-property prediction, offering a generalizable strategy for accelerating deep elastic strain engineering in materials informatics.

We present a fully Gaussian and experimentally feasible scheme for the simultaneous estimation of the four real parameters that characterize an arbitrary two-channel unitary transformation. The scheme utilizes a two-mode squeezed probe and balanced homodyne detection at both output ports, for which we derive the complete classical Fisher-information matrix analytically. Our scheme achieves the Heisenberg-scaling sensitivity for all four parameters simultaneously, enabling full multiparameter characterization of the generic two-channel interferometric device. We further show, by maximum-likelihood estimation, that the corresponding multiparameter Cramér-Rao bounds are saturated with a modest number of experimental repetitions and for low photon numbers. The scheme establishes a practical route to Heisenberg-scaling multiparameter Gaussian metrology for arbitrary two-channel networks, with direct relevance to calibration and sensing in integrated photonics and distributed quantum-enhanced measurement architectures.

In this letter, we numerically investigate a long-haul coherent data transmission system with a cascade of semiconductor optical amplifiers (SOAs). We exploit low-complexity neural networks that can be implemented in real time to compensate for the accumulated distortions induced by a cascade of SOAs. This equalization provides an order-of-magnitude reduction in bit error rate at low dispersion (in the O-band), whereas higher dispersion degrades performance.

The phase behavior of a single type of colloid C suspended in near-critical solvents is known to be very rich. Motivated in part by recent experiments we consider a mixture of two colloidal types C1 and C2 in a binary solvent close to its demixing critical point. We extend a mean-field description of a lattice model, previously used to investigate systems with a single type of colloid in two dimensions, to the binary colloid case in three dimensions. The model treats the system as a full four-component mixture. For simplicity we choose C1 and C2 to be hard spheres with the same radius but with different affinities for one species, B, of the AB binary solvent. We show that intricate interplay between couplings of C1 and solvent, C2 and solvent as well as solvent-solvent interactions and hard sphere packing drive significant changes in the topology of the colloidal phase diagram when the relative volume fractions of the two different colloid types change. The behavior of the two lines of triple points is particularly interesting. Our results can provide some insight into the control of the self-assembly process for colloidal 'alloys' mediated by a near-critical solvent and therefore controlled by temperature in a reversible manner

The effects of the polarization characteristics of beam trains in optical long-baseline interferometers are well known and have led to difficulties in measuring the spatial coherence of astronomical sources in the past. This has been overcome by designing symmetrical optical trains. With the advent of interferometers using large telescopes, observations of faint sources with high degrees of polarization have become even more possible. As in the radio domain, where radiation processes usually lead to high polarization rates, a description of coherence for polarized or unpolarized sources observed with non-polarization neutral interferometers is necessary. A theory of optical long-baseline interferometry fully taking into account the polarization characteristics of beam trains and those of the sources is presented in this paper, building on concepts developed for radio aperture synthesis. The concept of generalized Mueller matrix is introduced for the case of multi-aperture interferometers leading to a simple matrix relationship between the observed Stokes visibilities, as they are disturbed by the instrument polarization characteristics, and the object Stokes visibilities. This relationship is applied to the case of single-mode interferometers. The formalism also shows that classical complex visibilities (squared moduli, phases and closure phases) need to be debiased from polarization crosstalk, even when the source is not polarized as in this case ghost polarized visibilities are created.

Quantum error correction (QEC) enables reliable computation on noisy hardware by encoding logical information across many physical qubits and periodically measuring parities to detect errors. A decoder is the classical algorithm that uses these measurements to infer which error most likely occurred, so that the system can correct it. The decoder's accuracy-how rarely it makes the wrong guess-directly determines the scale of quantum computation that can be reliably executed. With a wealth of competing decoding algorithms, a QEC system designer needs reliable methods to evaluate them. Today, the dominant approach is to evaluate decoders using Monte Carlo simulation. However, simulation has several drawbacks such as requiring many samples to produce low variance estimates. In this work, we develop a new systematic analysis for evaluating decoders. We introduce a novel formal semantics of a core language for QEC programs that captures the de facto standard Stim circuit format, providing a principled theoretical foundation for the emerging space of fault-tolerant quantum systems design. Given a QEC program and a decoder, our verifier can quantify both the decoder accuracy and the decoder robustness to drift in physical error rate. Our approach has two key components: (i) a structured search over the space of possible errors; and (ii) a constrained polynomial optimization kernel. A thorough empirical evaluation of our approach suggests that it can outperform simulation, especially in low error rate regimes, and that it can be deployed to quantify decoder robustness over an interval of physical error rates.

We present an integrated iontronic memristor circuit that reproduces biologically inspired Spike Rate-Dependent Plasticity (SRDP) and functions as a physical nonlinear frequency kernel, which we demonstrate can be used to classify natural auditory data. The fluidic circuit integrates two parallel memristive membranes containing short and long conical memristive channels with opposite orientations, giving rise to heterogeneous internal timescales and different potentiation responses. As a result, the circuit exhibits a nonlinear frequency response in which low-frequency inputs decrease the overall conductance, whereas higher-frequency inputs increase it, thereby emulating biological SRDP. Our experimental measurements are inspired by and consistent with predictions of a theoretical model. We demonstrate the functionality of the device by separating encoded sound signals from different insects that cannot be linearly separated. By unifying theoretical predictions with experimental realisation of coupled iontronic memristors, this work moves beyond isolated components and demonstrates how heterogeneous iontronic dynamics can unlock nonlinear time-series processing capabilities, essential for future iontronic neuromorphic computing.

Quasi-axisymmetric stellarators are the stellarator analogue of the axisymmetric tokamak, retaining many of its favorable confinement properties, its compacity and its relative coil simplicity, while avoiding its principal limitation, the need for an inductively driven plasma current. Despite these attractive physics properties, the development of quasi-axisymmetric configurations has been severely constrained by the absence of an experimentally validated divertor concept compatible with their large bootstrap current. In this Letter, approximately quasi-axisymmetric fields, complemented with piecewise omnigenous perturbations, are proposed as the basis for a new strategy towards a stellarator reactor that simultaneously achieves simple coil geometries, tokamak-like confinement properties and, through tailoring of the bootstrap current, compatibility with an island divertor. Implications for attaining a high bootstrap current fraction in tokamak devices are also discussed.

The orbital and eccentricity evolution for compact object binaries through gravitational wave emission first derived by Peters and Mathews are used extensively throughout the gravitational wave community for calculating the orbital evolution and merger time of compact binaries. While improved calculations of the binary merger time have been the focus of several investigations since, the orbital evolution has not received the same attention. As the equations lack a closed form solution, a numerical integrator is required, but standard methods typically break when the point of merger is overstepped. We present a rewrite of Peters' equations in $\ln$-space, which allows common numerical solvers to converge. This leads to a more numerically robust and computationally efficient method for evolving compact binaries due to gravitational wave emission, reducing the number of function evaluations by 60\% to 70\% in our tests.

DNA self-assembly is a well-understood nanotechnology to obtain extremely ordered structures from the nanometer to up to the hundred of microns scale. By contrast, DNA hydrogels rely on the disordered assembly of DNA building blocks to reach macroscopic volumes. However, in order to hold the promise of DNA bulk materials, the sequence designer needs a systematic understanding of how macroscopic properties emerge from disorder. Here, we show a method to study systematically the mechanical response of a simple DNA nanostar hydrogel. This method mobilises bulk rheology, dynamic light scattering microrheology, mechanical modeling, as well as thermodynamic calculation and DNA sequence alteration. At low temperatures, we demonstrate a systematic deviation from Maxwell behaviour that is symptomatic of disordered materials. At temperatures much higher than the percolation of the DNA network, we characterise a surprising solid behaviour that we attribute to a glass transition. Our results show the importance of disorder in DNA materials. Furthermore, the method we showcase in this article can be widely applied to more complex DNA materials.

A combination of measurements of the CP properties of Higgs boson interactions with electroweak gauge bosons is presented, using 140 fb$^{-1}$ of proton-proton collisions at $\sqrt{s} = 13$ TeV recorded by the ATLAS detector. Results from $H\toττ$, $H\to WW^{*}$, $H\toγγ$, $H\to ZZ^{*}$, and $WH,H\to b\bar{b}$ channels are combined. No evidence of CP violation is observed, and constrains on the CP-violating operators in the SMEFT framework are set in the Warsaw basis. The results from the combination improve by over 40% on previous individual limits on $c_{H\tilde{W}}$ and, for the first time, simultaneous constraints on three coefficients $c_{H\tilde{W}}$, $c_{H\tilde{B}}$, and $c_{H\tilde{W}B}$ are set. This limits are the most stringent constraints to date on the relevant Wilson coefficients in the SMEFT framework with minimum model dependence.

The complex cislunar dynamical environment poses challenges for spacecraft navigation and Space Domain Awareness (SDA) operations, where the knowledge of current and future spacecraft states is essential. Conventional Gaussian-based approaches for SDA degrade under the nonlinearities that manifest in this regime. To accurately model the underlying dynamics and characterize uncertainty, this work explores the Modified Generalized Equinoctial Orbital Elements under high-fidelity propagation for cislunar applications. The Henze-Zirkler test for multivariate normality is leveraged to evaluate uncertainty evolution across a range of orbits, demonstrating improved preservation of Gaussian behavior in cislunar space.

The study of mathematical connections between operator-theoretic formulations of classical dynamics and quantum mechanics began at least as early as the 1930s in work of Koopman and von Neumann and was developed in later decades by many authors, often independently, into a framework now broadly known as Koopman-von Neumann representation of classical dynamics. This article surveys aspects of this framework for measure-preserving ergodic dynamical systems and connects it with recent approximation techniques for Koopman and transfer operators that are amenable to data-driven numerical implementation. In broad terms, these methods are based on representations of (i) classical observables as elements of an algebra of operators acting on a Hilbert space; and (ii) classical probability measures as elements of the state space of that algebra, with lifted versions of the Koopman and transfer operators inducing dynamical evolution of observables and states, respectively. A common theme underlying the techniques surveyed here is the use of reproducing kernel Hilbert spaces with coalgebra structure (so-called "reproducing kernel Hilbert algebras'') that aids the quantum representation of classical objects, as well as the use of Fock spaces to build approximation schemes with high expressivity and structure preservation properties (notably, preservation of positivity and multiplicativity of composition operators). Applications to quantum algorithms for approximating the Koopman evolution of observables in systems with pure point spectra are also discussed.

When the number of massless fermions exceeds a critical value $N_f^*$, QCD enters the conformal window and becomes chirally symmetric already in the vacuum. Determining $N_f^*$ from lattice simulations is challenging, since calculations are performed at finite lattice spacing, quark mass, and temporal lattice size, where both a thermal transition and an unphysical bulk transition obscure the conformal behaviour. In this work, we present results on the chiral phase boundaries in the bare lattice parameter space $(N_τ,\;β,\;am,\;N_f)$ of unimproved staggered fermions. Our analysis indicates that the chiral transition in continuum QCD is of second order for all $N_f$ up to the onset of the conformal window. By systematically studying the thermal chiral transition and its interplay with the bulk transition, we obtain a coherent picture of the lattice phase structure and suggest how the onset of the conformal window can be identified from simulations performed away from the chiral and continuum limits.

RS Canum Venaticorum (RS CVn) close binaries, characterized by tidal locking, rapid rotations, and strong magnetic fields, are ideal laboratories for high-resolution radio observations to probe emission processes, magnetic field configurations, and interaction activity. Despite their importance, only a few RS CVn sources have been explored by polarimetric observations of very long baseline interferometry (VLBI). To expand the effort, we have analyzed the existing Very Long Baseline Array (VLBA) astrometric data for the RS CVn binary FF Ursae Majoris (FF UMa). In the 5GHz VLBA experiments conducted between 2021 and 2024, both total intensity and circularly polarized emission were clearly detected at six of seven epochs. The consistently high brightness temperatures (10^7 K) and the moderate fractional circular polarization (10%-30%) over about three years indicate that the radio emission is mainly produced by gyrosynchrotron radiation from mildly relativistic electrons in the highly-ordered magnetic field. The radio luminosities are also comparable to those of previously studied powerful RS CVn binaries and show a significant anti-correlation with fractional circular polarization. A mean centroid offset of 13.4 +/- 3.1 solar radii between the Stokes I and V emission was found across multiple epochs, indicating a possible additional contribution from the secondary star via a magnetically active corona, a giant magnetic loop, or significant interaction activity with the primary star in the quiescent state.

We derive the effective action governing the dynamics of a compact binary system when gravitational radiation is emitted by any mass or current multipole, scattered by the quasi-static field associated with the binary's angular momentum, and then reabsorbed. Among such angular momentum failed-tail processes, the ones involving multipole moments up to mass and current octupoles, which mix also with quadrupoles of opposite parity, contribute to the system dynamics at sixth post-Newtonian order; we display these terms explicitly as a particular case of our general derivation. Additionally, we derive the radiative multipole moments associated to arbitrary angular momentum failed-tails in emission processes.

We prove a no-go theorem for symmetry-based dissipative engineering of collective-spin steady states: in spin-only Lindblad dynamics with jump operators linear in the collective-spin operators, any unique steady state exhibiting at least $\mathbb{Z}_2 \times \mathbb{Z}_2$ symmetry is necessarily the maximally mixed state. We then show that bath memory lifts this obstruction, enabling unique entangled steady states with a prescribed symmetry and a metrological gain, and providing a steady-state witness of non-Markovianity. Notably, this framework is largely insensitive to the microscopic details of the bath.