Papers

In this work, we investigate the resonant interaction between stochastic gravitational waves (GWs) and chiral Alfvén waves in a magnetized chiral plasma in the early Universe. Starting from covariant chiral magnetohydrodynamics coupled to linearized gravity, we derive a closed system of equations for the coupled chiral-Alfvén velocity and magnetic-field perturbations. Both analytics and numerics show a parametric resonance at the sum frequency of the two CVE-split branches, with an instability band that widens as the GW strain grows. This CVE-to-Alfvén ratio is not a free parameter. In the early Universe, it is fixed by the Standard Model's relativistic degrees of freedom. Including the plasma's backreaction on the GW makes the energy exchange nonlinear, breaking the usual single-frequency Manley-Rowe picture. For a self-consistent choice of parameters, where backreaction is only a small correction, the unsuppressed resonance still drives the system to a finite-time blow-up within a few Hubble times. We then work out the resonant frequencies and growth rates involved, mapping out what current and future gravitational-wave detectors could observe.

We study how colloidal inclusions modify the formation energy of dislocation pairs in lamellar block copolymer systems. Using a hybrid particle/Ginzburg–Landau model, we calculate defect formation energies by comparing defect-free and defect-containing states with and without embedded colloids. Finite-size scaling is used to obtain formation energies in the thermodynamic limit. The effect of colloid insertion depends strongly on particle sizes and surface patterning. Homogeneous particles increasingly stabilize dislocation pairs with increasing particle sizes. Particles larger than one lamellar domain preferentially occupy the dislocation cores, where they replace strained polymer rather than deforming defect-free lamellae. The magnitude of this stabilization depends on surface affinity. Balanced Janus particles instead increase the formation energy, because their competing surface preferences cannot be satisfied simultaneously near the curved core. Varying the patch ratio interpolates between these limits. Surface patterning has little effect for particles smaller than one lamellar domain but changes the formation energy by several tens of $k_BT$ for larger particles. These results provide quantitative guidelines for controlling topological defect stability in lamellar block copolymer systems.

For high-inclination projectiles undergoing Lidov–Kozai secular evolution, coupled variations in eccentricity and inclination complicate estimates of long-term collision frequencies with a target body. Previous collision-frequency studies for Kozai-driven projectiles have considered target-body orbits that are either circular or confined to the reference plane. The present study considers the general case in which the target body's orbit has both non-zero eccentricity and non-zero inclination. For each complete Lidov–Kozai cycle, the initial relative nodal longitude and the target body's initial argument of periapsis serve as two independent orientation variables. The single-cycle collision frequency is evaluated for each pair of initial values. Under the incommensurability condition considered here, the long-term mean is then obtained by explicitly averaging these values over both orientation variables. For the special cases in which the target body's orbit is circular or lies in the reference plane, the method is shown analytically to reduce to the corresponding formulations of previous studies. Numerical comparisons confirm these reductions. For the general eccentric and inclined case, the resulting collision frequency predicts a projectile survival curve that agrees well with the fraction of projectiles remaining in independent direct dynamical integrations. Finally, it is shown that, for a fixed dynamical setup and under the incommensurability condition, the long-term mean collision frequency associated with a given closed Hamiltonian level curve is independent of both the projectile's initial secular state along that level curve and its initial longitude of ascending node.

Large-scale, high-resolution spectroscopic surveys map detailed chemical abundance patterns for millions of stars. However, libraries of stellar evolution models and isochrones still rely on a simplified description of chemical abundances, generally assuming either solar-scaled compositions or a constant enrichment for all $\alpha$-elements. Moreover, the definition of $\alpha$-enrichment is survey-dependent and is not necessarily the most relevant quantity for stellar structure and evolution. In the era of precision stellar astrophysics, stellar models need to better account for the wealth of chemical information provided by spectroscopic surveys. We develop a perturbative method to compute stellar evolution tracks for stars with arbitrary patterns of $\alpha$-elements. We quantify the response of stellar evolutionary tracks to variations of individual $\alpha$-elements through polynomial expansions, which can be linearly combined to produce synthetic tracks for a given abundance pattern. We also introduce the evolutionary $\alpha$-enhancement, [$\alpha$/Fe]$_{\rm ev}$, a constant enhancement for all $\alpha$-elements that reproduces the impact of an observed abundance pattern on stellar models. We validate both methods using stars with detailed APOGEE abundances and quantify the differences between spectroscopic [$\alpha$/Fe] and [$\alpha$/Fe]$_{\rm ev}$ for different surveys. We identify a minimal set of chemical elements required for accurate stellar models and present ALCHEMY, a simple and fast tool to compute [$\alpha$/Fe]$_{\rm ev}$ for general $\alpha$-element abundance patterns.

Transition metal dichalcogenides (TMDs) and their Weyl semimetal phases, such as MoTe$_2$, have attracted significant attention for spin-orbit torque applications due to their efficient charge-to-spin conversion. However, whether this conversion originates predominantly from the bulk or the interface remains unclear. Here, we investigate spin-charge interconversion in MoTe$_2$ using spin-pumping and spin-torque ferromagnetic resonance (SP-FMR and ST-FMR). Thickness-dependent measurements reveal large spin-to-charge conversion and spin-torque efficiencies that are essentially independent of MoTe$_2$ thickness, indicating that the conversion is predominantly governed by the Rashba-Edelstein effect at the Py/MoTe$_2$ interface rather than by bulk spin transport. This behavior contrasts with the characteristic thickness dependence observed in Pt heterostructures and is further supported by bidirectional SP-FMR and interface-separation measurements. Our results highlight the dominant role of the Py/MoTe$_2$ interface in enabling efficient spin-charge conversion and spin-orbit torques in TMD-based spintronic devices. These findings highlight the potential of sputtered MoTe$_2$/Py heterostructures for low-power spintronic applications, including magnetic memory and logic devices.

We investigate the Saha ionization equilibrium in the exterior Schwarzschild spacetime. Starting from the mass-shell condition for a massive particle, we derive the conserved energy associated with the timelike Killing symmetry and obtain its nonrelativistic limit in terms of the Schwarzschild lapse function. This energy is then incorporated into the Maxwell–Boltzmann distribution to construct the ionization balance as seen by an asymptotic observer. We show that the gravitational field modifies the Saha relation through the redshift of both the particle energies and the thermodynamic variables. By imposing the Tolman–Ehrenfest and Klein equilibrium conditions, the formulation expressed entirely in terms of locally measured quantities reduces to the standard flat-spacetime Saha equation. We further analyze the gravitational redshift of the ionization energy, the relative departure from the flat-spacetime ionization ratio, and the corresponding shift of the ionization fraction as a function of the asymptotic temperature. We also present the relativistic classical counterpart based on the Maxwell–Jüttner distribution and show explicitly that its leading correction is negligible in the temperature range where neutral hydrogen is appreciably abundant. These results provide a consistent description of ionization equilibrium in a static gravitational field and clarify the distinction between gravitational redshift effects and intrinsic modifications of local atomic physics.

Closed-loop human-AI systems generate high-dimensional behavioural trajectories whose collective dynamics remain obscure. Using 297,915 learners' adaptive-tutoring histories, we define semantic order variables before model fitting and test them in user-disjoint cohorts. The state exhibits reproducible basin-like flow and operationally defined, state-heterogeneous metastable-like kinetics. A construction-matched null distinguishes normalised-memory relaxation from a reproducible excess field. A four-term conditional mechanism recovers population drift (r = 0.946; learner-bootstrap 95% CI, 0.935-0.955). Predictive event-level self-supervised learning recovers the state and learned-plane flow; null-referenced corrections retain directional, partial-amplitude excess-field structure without full calibration. Shuffled-order training reverses learned-plane flow on ordered trajectories; support-alignment randomisation selectively reduces inward transport. Both axes remain linearly accessible without state supervision. Without cross-model fitting, the models share leading population drift (r = 0.866; learner-bootstrap 95% CI, 0.857-0.875) and persistence ordering; residual directions remain model-specific. These results identify an externally anchored leading-order effective field linking empirical dynamics, an interpretable mechanism and neural computation.

Fast radio bursts (FRBs) are bright extragalactic transients with several mysteries surrounding their origins. Large FRB samples enable accurate measurements of the cosmic matter distribution, in particular on scales $\lesssim 10$ Mpc. These measurements will impact cosmological inference and our understanding of astrophysical feedback, from the circumgalactic medium to cluster scales. Here we forecast the expected yields, redshifts, and host galaxies of FRBs as observed by the Deep Synoptic Array (DSA), and describe the key science cases enabled by the large FRB sample. The DSA will be an interferometer consisting of 1650$\times$6.15 m antennas, operating between 0.7–2 GHz, to be located in Nevada, USA. The Chronoscope backend on the DSA, hereafter DSA/Chronoscope, is designed to search for FRBs across the field of view in real time, enabling the storage of full-polarization voltage data. Extrapolating from existing FRB surveys, we expect roughly $10^4$ FRB detections per year in each of three search sub-bands. Combining across sub-bands, the survey could produce $\sim$ 10$^5$ FRBs over the nominal 5-year DSA survey, assuming Euclidean source counts and a baseline compute backend that can search $6\times10^6$ beams at 1 ms sampling. The well-characterized DSA synthesized beam and deep simultaneous reference images will enable localization precisions of $\lesssim$ 250 milliarcseconds. Key science cases include the use of FRB propagation effects in probing cosmic baryons, and studies of the FRB phenomenon using FRB host galaxies and their local environment, as well as multiwavelength counterparts.

The trilayered (A-B-A type) anisotropic (single site) XY magnetic model is considered with the intra-plane ferromagnetic and the inter-plane antiferromagnetic interactions. The equilibrium properties of such trilayered anisotropic XY system has been studied by Monte Carlo simulation with Metropolis single spin (randomly chosen) update algorithm. In a given range of interaction parameters, the system has been found to exhibit the high temperature critical (vanishing sublattice magnetisations and total magnetisation) and low temperature compensation (vanishing total magnetisation even for non-vanishing sublattice magnetisations) behaviours. The compensation temperature and the critical temperature both are found to increase with the increase of single site anisotropy. The comprehensive phase diagram is drawn. The finite size study reveals the growth of correlations near the critical temperature.

Quantum signal processing (QSP) provides a simple and efficient framework for implementing polynomial transformations using quantum circuits. Its classical design stage leads to a constrained minimax approximation problem: find a polynomial of prescribed parity that approximates a target function uniformly on a fitting set while remaining bounded in magnitude by one on the domain $[0,1]$, which can be viewed as a semi-infinite constraint. Discretization converts the problem into a linear program, but feasibility at a set of finitely many sampled points does not ensure feasibility on the whole domain, especially when an optimal approximant reaches the boundary of the feasible set. We investigate two approaches to address this difficulty. A Remez exchange method combined with active-set constraint enforcement is efficient on many tested instances, but its stability depends on the target and problem geometry. We then introduce nonlinear Fourier retraction, which uses QSP completion and phase synthesis to turn a nearly feasible polynomial into phase factors for a feasible QSP polynomial without increasing the degree. Across representative problems, retraction largely preserves approximation accuracy and remains effective on instances where the Remez heuristic is unstable. The resulting workflow connects classical minimax approximation and semi-infinite optimization with nonlinear Fourier analysis, and is implemented in the qsppack software package.

The chiral symmetry is a property of the fundamental theory of the strong interaction that is relevant for the hadronic physics. It is expected that at sufficiently high temperature and matter density, this symmetry becomes manifest. Within the Chiral Dual Partner Model the chiral transformation is implemented in such a way that a fermion mass term is allowed if the parity partner of each baryon is included in the framework. This model is used here to study possible manifestations of the chiral symmetry in dense nuclear matter, assuming constant isospin fraction. It is found that the onset of the odd parity baryons is associated with two branches of thermodynamical instabilities, one of them leads to a first order phase transition for temperatures below $T_c\simeq 11$ MeV. An analysis of these instabilities in the phase space is given, and neutron star matter is considered as a special case.

From linear response theory, we derive the equation of motion for Landau-damped magnon quasi-particles in absence of spin-orbit coupling. The derivation is based on a minimal set of assumptions, namely that the transverse magnetic susceptibility is diagonalized by one collective eigenmode per magnetic atom in the unit cell, and that the spectrum of each collective eigenmode is dominated by a single magnon resonance. The resulting equation of motion leads to a natural definition of the exchange interaction as the restoring force acting on the collective mode magnetization near equilibrium. In addition to magnetic exchange, the magnon equation of motion also contains a damping term and a dispersive quasi-particle mass, both originating from the electron-magnon coupling. The effect of these terms is illustrated for a prototypical itinerant ferromagnet, where they redshift the magnon dispersion and reduce the magnon lifetime as the magnon enters the Stoner continuum. By further assuming wave vector independence of the collective magnon subspace, the magnon equation of motion becomes atomistic with well defined magnetic sites. For real materials, one can approximate the magnon coupling constants using an arbitrary level of band theory for the dynamic transverse magnetic susceptibility.

Understanding the spin alignment of vector mesons in relativistic heavy-ion collisions requires a nonperturbative description of their spin-dependent in-medium properties. We investigate this problem within a unified four-flavor soft-wall holographic framework that combines an anisotropic Einstein–Maxwell–dilaton background at finite temperature, baryon chemical potential, and angular velocity. Spin alignment is determined from the medium-induced splitting of the spin-resolved vector-current spectral functions through an instantaneous freeze-out prescription. We systematically study the strange and charm vector mesons $K^{*}$, $\phi$, $D^{*}$, $D_s^{*}$, and $J/\psi$ and the dependence of their spin alignment on transverse momentum, rapidity, temperature, baryon chemical potential, and angular velocity. We find that the heavy charm vector mesons $D^{*}$, $D_s^{*}$, and $J/\psi$ mesons exhibit $\rho_{00}>1/3$ at low transverse momentum, whereas the light strange vector mesons $K^{*}$ and $\phi$ exhibit the opposite low-momentum behavior and angular distributions with $\rho_{00}<1/3$. We trace this flavor-dependent separation to the different locations of the vacuum mass shell relative to the thermally shifted longitudinal and transverse spectral peaks. The results qualitatively reproduce several trends observed at low and intermediate transverse momentum. Spin alignment is insensitive to baryon chemical potential and only weakly affected by angular velocity. These results establish an equilibrium holographic baseline for vector-meson spin alignment across flavor sectors and help delineate the regimes in which additional mechanisms, such as nonequilibrium evolution, fluctuations, and hard production, become important.

Numerical simulations of elastic turbulence in parallel shear flows of polymer solutions indicate that the phenomena is associated with the formation and instability of exact coherent states dominated by thin sheets of polymer stress. However, these “arrowhead” structures are yet to be seen directly in experiments, where simultaneous velocity and polymer conformation measurements are challenging to obtain. Motivated by these challenges, we introduce a method for the prediction of the polymer conformation field given a time series of vorticity measurements. Our approach consists of two components: the first is a convolutional neural network architecture which takes vorticity fields and outputs a positive definite conformation tensor. The second is the adaptation of an assimilation-based training algorithm (Zhu & Page, 2026) which does not require a pre-generated `offline' library of reference conformation fields, but is trained only using the vorticity measurements. This is particularly important in viscoelastic problems, where the appropriate model and parameters to compare to the experiments may need to be determined as part of the solution. In training, measurements made on a time-marched network prediction are required to match the saved time series, while the output of the solver and network predictions at later times are required to be self-consistent. We apply these ideas to two-dimensional Kolmogorov flow in a range of regimes, from simple traveling waves to a fully chaotic state. In all cases, our method produces robust predictions of the polymer stretch, while standard, unregularised variational assimilation is ineffective. In the chaotic case we show that our networks generalise to much larger domains – without further optimisation – than the `minimal' units in which they were trained.

Disclinations are elementary topological defects in two-dimensional (2D) crystalline membranes, yet their elastic properties remain largely unexplored. Using atomistic simulations, we address the energetics, morphology, and interactions of disclinations in free-standing graphene, a prototypical 2D crystal. We find that while disclinations with positive topological charges follow an expected behavior, negative disclinations exhibit sublinear energy scaling with charge as well as equilibrium shape that deviates sharply from the conventional saddle ansatz. This breakdown of charge-conjugation symmetry leads to qualitatively distinct interactions: positive disclinations repel, whereas negative disclinations display a robust long-range attraction. These trends are shown to be further amplified by self-adhesion in folded membranes. Our results uncover a fundamentally different energetic landscape for negative curvature defects and provide a basis for understanding the stability, self-folding behavior, and defect-driven morphology of graphene and other 2D membranes.

Quantum dot (QD) supraparticle lasers are promising platforms for microscale light sources and photonic labeling, yet their optical properties are set during assembly. Here we introduce QD colloidosomes, liquid-core/solid-shell supraparticles that combine whispering-gallery-mode optical feedback with stimulus-triggered structural collapse. Intact QD colloidosomes show cavity-defined lasing with fluence thresholds of ~2.8 mJ/cm2 and linewidths of 2.2-3.7 nm, demonstrating efficient light trapping without a solid core. We identify shell continuity as a critical determinant for whispering-gallery feedback and lasing by exploring a morphological continuum of suprastructures comprising solid supraparticles, colloidosomes, and microporous hollow shells. Intact colloidosomes support narrow cavity modes, whereas porous shells remain broadband even at high pump fluence. We show that colloidosomes can be driven to rupture and release payload through well-defined pathways, including meniscus-driven capillary failure, uniform heating, and localized near-infrared activation, thereby reconfiguring their optical response from cavity-defined lasing to broadband emission. These results establish QD colloidosomes as reconfigurable microlasers that couple optical-state switching and triggered release within a single self-assembled platform.

We study kinetics of phase transitions within a single component Lennard-Jones model. For low enough particle densities disconnected clusters form that can move ballistically in an inviscid vapor background. The clusters undergo sticky collisions, thereby forming larger aggregates, which can be of fractal nature at ultra cold temperatures. As the temperature is varied, the exponent of the algebraic growth of average cluster mass changes, exhibiting pronounced nonmonotonic character. We capture this anomalous behavior, in two and three space dimensions, within a ballistic aggregation theory. We show that the scope of the theory is much broader than the typically considered case where cluster motions are uncorrelated. An analysis of the theory shows that ballistic aggregation can even occur exponentially fast. This is in sharp contrast with the conventional algebraic picture, regarding passive matter phase transitions. We discuss scenario where such explosive growth can be realized. In addition, our results are widely relevant in understanding structure and growth in aerosols, cosmic dust and other aggregation processes.

The so-called “cosmic dipole tension” challenges the Cosmological Principle by positing a discrepancy between the Solar System's peculiar velocity inferred from the Cosmic Microwave Background (CMB) dipole and that derived from large-scale structure number-count dipoles. Here we provide a high-precision determination of the kinematic dipole using the redshift-dipole method applied to the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). By exploiting the Doppler-induced modulation of observed redshifts, this estimator is intrinsically less sensitive to imaging systematics and selection-function uncertainties that can bias traditional number-count measurements. We conduct a tomographic analysis of four tracer populations, Bright Galaxy Sample, Luminous Red Galaxies, Emission Line Galaxies, and quasars, spanning $0.1<z<2.1$. Survey geometry and statistical uncertainties are quantified using 1,000 EZmock realizations. We find that the high-redshift QSO sample implies a peculiar velocity of $v = 357.95_{-48.47}^{+55.05}\,\mathrm{km\,s^{-1}}$, in excellent agreement with the CMB-inferred value of $369.82 \pm 0.11\,\mathrm{km\,s^{-1}}$. By contrast, a complementary number-count analysis yields a significantly enhanced dipole amplitude, which we attribute to leakage of large-scale power and to incompleteness within the DESI DR1 footprint. These results indicate that the redshift dipole provides a cleaner and more reliable probe of the kinematic rest frame, offering strong support for the standard kinematic interpretation at high redshift and helping to resolve the apparent dipole anomaly.

A core inverse problem in the experimental sciences is the inference of a hidden dynamical state from sparse or indirect measurements. There is a natural opportunity for deep learning methods here, but machine-learnt reconstruction methods typically require full state data for training. We present Trajectory-Consistent Network Training (TraCTra), a label-free framework that trains reconstruction networks using only partial observation sequences and a differentiable forward model. TraCTra requires the network reconstruction and dynamical evolution to be mutually consistent: network-predicted states are marched forward in time to match subsequent observations and to agree in the full state space with independent reconstructions at later times. Across four fluid systems, the same objective reconstructs three-dimensional turbulence from coarse-grained fields, velocity from observations of density fluctuations, and three-dimensional density and velocity from sequences of projected two-dimensional shadowgraphs, while also recovering global vorticity from observations confined to a small spatial window. TraCTra outperforms assimilation-only and physics-informed neural approaches, preserves dynamically important multiscale structure, and remains accurate beyond the optimisation window. It transfers to held-out times in the three-dimensional shadowgraph problem and, when trained across trajectories, generalises to unseen flows in the two-dimensional problem. The results establish trajectory consistency as a general supervision principle for reconstructing hidden dynamical states without full state training targets.

The downwash wake of a hovering quadrotor governs both the vehicle's own performance and the safe spacing of multi-rotor formations. Prior measurements have largely characterized the mean flow, using single-point anemometry, volumetric tracking, or planar cuts through part of the rotor system. Higher-order turbulent statistics of the merged wake, and how they relate to canonical jet scaling, have remained unresolved, particularly for small quadrotors at the low-Reynolds-number end of the size range. Here, we present a detailed particle image velocimetry (PIV) study of the downwash of a hovering Crazyflie 2.1 quadrotor (arm length, $l = 46$ mm), sampled along a diagonal cut, passing through rotors along the symmetry axis of the quadrotor, and a front-rotor cut, passing through adjacent rotors. The four rotor jets merge into a single column by $z/l \approx 5$, beyond which the mean velocity profiles progressively approach the canonical round-jet self-similar form, collapsing by $z/l \approx 13$ when scaled by the local centerline velocity and half-width. Centerline decay and half-width growth follow canonical scaling laws with an effective source diameter $D_\text{eff} = 2.29\,l$, effective Reynolds number $Re_{D_\text{eff}} = 3 \times 10^4$, at the low end of the range over which canonical jet scaling has been established, and spreading and decay constants nonetheless within the canonical round-jet range. Resolving both cuts shows that the turbulent normal stresses retain a bimodal, cut-dependent signature of the four-rotor source throughout the measurement domain.

Metaphotonic platforms based on quasi-bound states in the continuum (qBICs), harnessing strong near-field enhancement and deeply subwavelength field confinement, provide a versatile framework for surface-enhanced infrared absorption (SEIRA) spectroscopy. However, real-time molecular sensing in water using qBIC metasurfaces remains challenging. First, strong water absorption in the mid-infrared region damps qBICs and obscures weak analyte signals. Second, conventional metasurfaces rely on discrete arrays targeting individual wavelengths and coupling conditions, increasing the device footprint and fabrication effort required to match the qBIC to the molecular vibrational resonance. Here, we present a dual-gradient plasmonic qBIC metasurface with diamond-shaped resonators for in situ molecular vibrational sensing in water, where spatially encoded gradients in the scaling factor and asymmetry parameter independently control the qBIC spectral positions and radiative rates, respectively, across a 1000 um x 700 um footprint. Building on this capability, we experimentally monitor lipid vesicle dynamics in real time and resolve the carbonyl vibrational signature despite the unavoidable water absorption. We then directly identify the optimal sensing condition and track its evolution across the spatially encoded parameter space. The results establish a compact single-chip strategy that combines adsorption-kinetics monitoring, vibrational fingerprint detection, and on-chip optimization, opening opportunities for investigating biological dynamics under aqueous conditions.

We study the production of the $\phi(1020)$ and $\Omega(1672)$ in heavy ion collisions at $\sqrt{s_{NN}} = 5.02$ TeV by employing two complementary approaches. In the first approach, the production of the $\phi$ and $\Omega$ is discussed in the coalescence model. In the second approach, we developed a hybrid framework that combines the recombination of shower and thermal partons with remnant string fragmentation. Thermal partons in the quark-gluon plasma are modeled using a blast-wave parameterization, while the phase space information of medium-modified parton showers is generated from Q-PYTHIA, using unquenched jet partons obtained from HIJING initial inputs. We show that both approaches agree well with the experimental measurements, and demonstrate that this hybrid framework provides deeper insight into the underlying strangeness components in the production of $\phi$ and $\Omega$ in relativistic heavy-ion collisions.

While radio measurements of extensive air showers have shown to achieve a high precision of $X_\mathrm{max}$ sensitivity, it has been shown that parameters beyond $X_\mathrm{max}$ can also be reconstructed. These shape parameters contain additional sensitivity to the hadronic physics in the shower as well as its mass composition. In this work, we showcase a reconstruction framework to recover the full longitudinal profile from realistic radio measurements. The framework is based on Information Field Theory that infers the full profile with a forward-based model, which uses a Gaisser-Hillas profile with weakly informative shower priors, SMIET with a template library to synthesise pulses at any event geometry, and a realistic antenna response and noise level emulating that of SKA-Low. We verify the self-consistency of our framework with $\sim 900$ events generated with SMIET with antennas placed on the $\vec{v} \times (\vec{v} \times \vec{B})$ axis. The framework recovers the full profile within uncertainty and capture correlations between shower parameters. We yield an $X_\mathrm{max}$ resolution of $< 9$ g cm$^{-2}$ as well as resolutions of the width and asymmetry with minimal bias. The profile is also recovered with a bias of $< 4$% at all atmospheric depths $< 1200$ g cm$^{-2}$. We aim to apply this framework with pulses simulated from CoREAS with measured noise, ultimately extending the framework to realistic antenna layouts such as from LOFAR or SKA-Low.

We theoretically investigate the inter-sideband phase coherence within the resonance fluorescence spectrum of an acoustically modulated quantum dot using a filtered-field formalism for a Mach-Zehnder configuration. We demonstrate that geometric slant of the interferograms provides an indicator of phase coherence that is resilient to environmental white noise. Specifically, noise-induced spectral diffusion reduces the global fringe intensity, while leaving the characteristic inclination strictly invariant. Our findings establish a framework for verifying single-photon coherence between spectral sidebands, essential for frequency-bin encoding and scalable quantum networking in realistic, noisy solid-state architectures.

Slow twist-angle and heterostrain textures in twisted bilayer graphene provide a natural route to phase-space Berry geometry. We show that a purely geometric tetrad/shift sector does not generate mixed Berry curvature once the spin connection is treated consistently. By contrast, a projected textured mini-Dirac cone in twisted bilayer graphene acquires genuine mixed phase-space curvature. We analyze a controlled local Hall-bar limit with a one-dimensional texture and mirror $M_x$. In that limit the pseudogauge gradient renormalizes only the longitudinal conductivity along the textured direction, while a dc nonlinear Hall response appears only when an additional valley-odd tilt generates a Berry-curvature dipole. Both geometric responses peak at the same local filling, $\mu_{\rm loc}=\sqrt{2}\,m$, providing a gate-tunable fingerprint of their common origin. All local-cone parameters and their texture susceptibilities are extracted from a heterostrained Bistritzer-MacDonald model at $\theta=1.3^\circ$. The tilt invoked in the transport estimates corresponds to heterostrain of only $0.03\%-0.2\%$, below values routinely imaged in devices. The resulting theory provides a local analytic framework for textured moiré Dirac materials and cleanly separates geometric, texture-induced, and transport-level ingredients relevant to realistic TBG.

Extreme and rare changes in space mission solar irradiance records are scientifically relevant but difficult to quantify because these records are finite, instrument dependent, and affected by observational gaps and time varying measurement quality. We evaluated extreme daily logarithmic changes in the band integrated 0.1-7.0 nm irradiance measured by photodiode 7 of the Solar Radiation and Climate Experiment/X-Ray Photometer System (SORCE/XPS) from 2005 to 2019. After constructing a regular daily series by linear interpolation, we analyzed daily logarithmic changes in irradiance and fitted stationary Generalized Extreme Value models to 60 day block maxima and transformed 15 day block minima. Block lengths were selected using Ljung-Box diagnostics and sample autocorrelation functions. Maximum likelihood estimation was used as the primary inferential method, with probability weighted moments as a sensitivity check. The maximum likelihood GEV shape estimates were 0.1661 for maxima and 0.2928 for transformed minima, with closely aligned estimates under the two fitting methods. These positive point estimates are compatible with Fréchet type tails under the selected block constructions. Annualized return levels provide interpretable summaries of extreme relative increases and reductions, but estimates for long return periods remain strongly dependent on extrapolation beyond the 15 year record. Reported measurement precision and absolute uncertainty were used to qualify the interpretation of the fitted tails and were not propagated through the likelihood. By combining EVT based tail modeling with explicit consideration of measurement precision, absolute uncertainty, interpolation, and mission data gaps, the analysis provides an uncertainty aware astrostatistical baseline for extreme value inference from processed solar mission records.

We reformulate the relaxation problem in statistical mechanics by making explicit what are the operational objects subject to relaxation: the local time statistics of the recorded signal $Z(t)$. These local time statistics are simply the estimated histograms of observations $\{Z(t_i)\}_{i=1}^M$ performed at uniformly random times $\{t_i\}_{i=1}^M$ by a clockless observer. The subject of prediction is a belief about a future fresh out-of-sample reading of a measurement outcome whose distribution is inferred from the mathematical model believed to be true. For finite bounded systems of $N\ge 1$ degrees of freedom global irreversible relaxation of predictions can occur but special initial conditions exist. The form of the predictions depends on certain loss functions whose choice is up to the particular observer. Finally, entropy is given a learning interpretation as mutual information between the observer and the unknown past of the system under consideration and, in complete generality, its stationary value depends on the information available.

Ultrafast electron diffraction (UED) provides direct information on changes in molecular structure following photoexcitation, but identifying the individual vibrational motions contributing to these dynamics remains challenging. Here, we introduce frequency-resolved UED, where Fourier transformation of the time-dependent difference pair distribution function ($\Delta$PDF) gives a two-dimensional frequency-distance representation of the structural dynamics. We apply this approach to allene and 1,2-butadiene following photoexcitation to the $S_1(\pi\pi^*)$ state at 200 nm, using electron scattering signals simulated from previously-published ab initio multiple spawning trajectories (S. P. Neville et al., J. Chem. Phys., 2016, 144, 014305). We identify C=C stretching and CCC bending motions and the internuclear distances over which they contribute, and separate overlapping CH$_2$ vibrational motions. By changing the pump-probe delay range used for the Fourier transform, we identify when specific frequency components contribute during the excited-state dynamics. Methyl substitution reduces the C=C stretching and CCC bending frequencies and introduces an additional frequency component in 1,2-butadiene during the first 90 fs. We further show the importance of sub-20-fs, and ultimately few-femtosecond, temporal resolution for retrieving these frequency components. Frequency-resolved UED therefore provides the vibrational frequencies, internuclear distances, and reaction times associated with photoinduced structural dynamics.

Diffusion processes involving membranes are of fundamental importance in both science and technology, since membranes serve as selective interfaces that regulate the transport of mass, charge, and information across multiple length and time scales. In this study, we employ molecular dynamics (MD) simulations to calculate the self-diffusion coefficient, tetrahedral order parameter and hydrogen-bond (HB) lifetime of SPC/E water over a wide high-temperature range in the presence of thermally activated membranes (TAMs). These membranes exhibit thermally controlled stochastic behavior that locally influences particle dynamics by probabilistically inducing elastic scattering events as particles traverse the membrane. The stochastic behavior of the membranes is governed by a sigmoidal profile, which depend on the reduced temperature of the system. The effective activation energy for diffusion is estimated for several membrane configurations. It is found that the diffusion coefficients generally decrease with an increase in the number of membranes and are in reasonable agreement with the Arrhenius approximation at high temperatures. Additionally, both the tetrahedral order parameter and the HB lifetime are only locally sensitive to the action of the membranes.

Slow slip events within subduction zones offer a unique window into earthquake prediction. The subducting plate drives dehydration reactions in the fault, causing cyclical slip and observable surface displacements. Earthquake footprints can then be identified in these displacement series through coupling the multi-physics governing the subduction process with regional seismic activity. However, data noise and traditional filtering methods obscure the underlying mechanisms. Here, we alleviate this constraint with our physics-based attractor. By accounting for the physics of subduction paired with AI-assisted manifold detection, we are able to predict an earthquake in New Zealand's Hikurangi trench one week early. Additionally, predictability limits extend to 5-6 weeks with decadal repeatability, pointing to the fundamental determinism of the suggested mechanism through which physics-based seismic forecasting is possible.