Papers

The domain wall is a kind of topological defect that can appear when a discrete symmetry is broken. If the discrete symmetry appears as an intermediate symmetry during a $U(1)$ symmetry breaking, the domain walls are connected to cosmic strings, forming walls bounded by strings. Intuitively, the domain wall disappears if the breaking scale of the discrete symmetry is comparable to that of the $U(1)$ symmetry. In this paper, relying on a 3:1 $U(1)$ model, we show the detailed processes of the disappearance of the domain wall. Due to the existence of the non-negligible “bias angle” $\beta$, the relevance of the “$Z_3$ symmetry” and the domain wall is blurred, and thereby the evaluations of the string profiles in a hybrid wall-string network should be revised. We also made some preliminary calculations of the gravitational waves generated by the wall-string network created in the early universe.

The highly-redshifted 21 cm signal from the cosmic Dark Ages presents an exciting frontier for cosmology, with the potential to observe a large number of Fourier modes of the cosmic density field in the absence of complicating astrophysical phenomena. Because the Earth's ionosphere and human-generated interference affect these low radio frequencies, the lunar far side - the most radio-quiet region in the inner solar system - is considered the ideal site to conduct such an experiment. The bright synchrotron foregrounds at these frequencies are expected to be spectrally smooth and thus occupy a subset of spectral Fourier modes, leaving an observable "window" to the Dark Ages signal. However, in practice, spectral structure arises in foregrounds due to instrumental artifacts, leading to a spillover of foreground power into the observable window. In this paper, we quantify this spillover for a set of simulated visibility measurements given a number of antenna beams, sky models, and baseline configurations. Notably, we examine the effects on foreground spillover due to variations in the lunar regoliths using two numerically simulated beam models with 1 and 4 layers of substrate materials underneath. We find that the regolith material properties can induce unwanted spectral structure in the beams, which potentially prevents foreground power suppression at the levels required. The detailed spectral behavior depends on the lunar regolith model used, making it paramount to produce both accurate models of foregrounds and of the lunar regolith for Dark Ages cosmology.

We present a quantitative framework for predicting how kinetic barriers governing temperature dependent relaxation arise in finite square magnetic networks. By formulating a series of non homogeneous transfer matrices from the adjacency spectrum of the underlying graph, we show how local coordination shapes the energy landscape and identifies geometric regions that act as bottlenecks for flux transport. Our approach predicts bimodal kinetic behavior, in which long intervals of trapping within charge compensated manifolds are interrupted by sudden, avalanche like relaxation episodes. Representing finite systems with a Husimi tree, we find that low temperature data from forty generations collapse onto a single curve consistent with a power law scaling form, implying that boundary truncation alone can give rise to scale invariant flux arrest, analogous to athermal granular jamming. By employing transition probabilities constructed from local Boltzmann factors, this framework connects equilibrium energy landscape concepts to non equilibrium phenomena, including kinetic arrest and telegraph noise, thereby enabling the prediction and design of intermittent transport in finite, frustrated networks.

Atom interferometry is a sensitive tool for measuring relativistic effects, but there are no known non-trivial exact solutions for relativistic atom interferometer phase shifts. Here we derive relativistically exact expressions within the usual semiclassical approximation for a wide range of experimentally interesting atom interferometer pulse sequences in flat spacetime, including Mach-Zehnder, resonant, and large momentum transfer interferometer geometries. As an example, the leading order phase shift $\omega_a g T^2/c$ for a Mach-Zehnder clock atom interferometer is found to become $\omega_a \left(1 + \frac{\omega_a}{2m}\right)(e^{-gT/c}-1)^2 c/g$ when all relativistic kinematics are included. We calculate exact phase shifts for both clock (single-photon) interferometers and Raman or Bragg (two-photon) interferometers.

Machine learning (ML) has become integral to fundamental physics, accelerating statistical workflows from data acquisition through inference and hypothesis testing. As ML systems grow increasingly autonomous, ensuring their reliability for discovery claims becomes critical. This review synthesizes the VERaiPHY (Validation & Evaluation for Robust AI in PHYsics) initiative's frameworks for rigorous ML assessment across particle physics, astrophysics, and cosmology. We establish when verification is essential by contextualizing ML within the statistical discovery workflow. We emphasize fundamental limitations: inductive bias is unavoidable, sample complexity bounds learning, and experimental constraints limit discovery. We reflect on physicists' evolving role as both experimental designers and evaluators whose judgments encode scientific rigor into AI systems. Responsible integration requires understanding ML's transformative potential alongside its intrinsic boundaries.

Identifying the causes of Earth's extremes is challenging because counterfactual experiments are not possible in the observed world. Data-driven causal discovery complements computationally expensive and potentially biased numerical experiments, but existing methods can struggle with undersampled, high-dimensional data and fail to recover multi-timestep, multivariate pathways leading to specific events. We introduce Tracer of Causal Evolutions in Space and Time (TraCE-ST), a probabilistic Lagrangian approach that produces event-conditioned causal trajectories in multivariate gridded data. TraCE-ST recovers known causal drivers and estimates their relative contributions in synthetic experiments and real-world extremes, including the 1991 Mount Pinatubo eruption. TraCE-ST also highlights less-studied drivers, such as orography-driven vorticity for Tropical Storm Debby (2006) and anomalous ocean-surface fluxes for the 2021 Pacific Northwest heatwave. Here, we propose causal tracking as an efficient data-driven framework for synthesizing causal evidence and generating testable hypotheses, complementing association analyses and numerical modeling while accelerating the study of high-impact events.

This paper presents a maximally flat-top half-band FIR optical filter on a silicon nitride (SiN) platform at 193 THz. Using a cascaded Mach-Zehnder Interferometer (MZI) topology simulated in Lumerical INTERCONNECT, MODE, and FDTD, the filter achieves insertion losses of 0.1349 dB and 0.1761 dB with extinction ratios of 18.317 dB and 23.002 dB for Channel-A and Channel-B, respectively, under realistic S-parameter conditions.

Two-dimensional magnetic materials offer unique opportunities for exploring low-dimensional spin phenomena and next-generation spintronic devices. Chromium trihalides CrX3 (X = Cl, Br, I) belong to an important family of these materials, where alloying opens pathways for tailoring their electronic, magnetic, optical properties, and thermodynamic stability. In this work, we present a density functional theory study of CrX3 compounds and their ternary alloys. Our results show that for the pure compounds, the ground state is ferromagnetic (FM), with the antiferromagnetic-zigzag (AFM-Z) and paramagnetic (PM) phases being close in energy. For these pure systems, the band gap variation among different magnetic phases does not exceed 0.16 eV, and the average magnetic moments on Cr atoms increase from Cl to Br to I. For the alloys, the FM state remains the lowest-energy configuration, but the energy difference towards the AFM-Z phase decreases for compounds with lower iodine concentration. The calculated band gaps reveal a pronounced bowing along the compositional edge connecting CrCl3 and CrI3. The Curie temperatures show a smooth variation across compositions, consistent with the nearly linear behavior of the magnetic exchange parameters. Based on the calculated mixing enthalpy and configurational entropy, the approximate Gibbs free energy indicates that alloy formation becomes thermodynamically favorable at finite temperatures, which is important to overcome the intrinsic experimental instability of these compounds.

Estimating the level of non-thermal support in cores is both challenging and crucial for constraining the earliest stages of star formation. We quantify the kinetic and magnetic support operating within the cores of the high-mass protocluster W43-MM1, and test the assumptions behind the virial theorem used to interpret observations. We used ALMA 12m molecular line observations of DCN (3-2), 13CS (5-4), and CH3CN (5_3-4_3) to estimate kinetic support. The plane-of-sky magnetic field strength (B_POS) was derived from dust-polarization observations using the Davis-Chandrasekhar-Fermi method, obtained at the three-beam scale (~12500 au) and extrapolated to core scales (~2500 au) using the density-field strength relation. We derive kinetic support estimates for 45 cores (21 prestellar and 24 protostellar), of which 21 also have magnetic field estimates. Velocity dispersions range from 0.34 to 4.48 km/s, and B_POS values span 1.1-49.3 mG at core scales. Using the virial theorem, ~70% of cores appear stable against collapse when considering turbulence alone, and ~85% when combining both kinetic and magnetic support (alpha_vir,B > 1). These are unexpectedly high values, particularly for protostellar cores expected to be undergoing collapse. We conclude that contamination of linewidths by organized motions (1-3 km/s, consistent with previous observational studies), together with the omission of surface terms in the observational virial theorem, prevents accurate measurement of non-thermal support in cores. This highlights that simplified virial analyses can introduce significant biases when assessing physical support mechanisms within cores.

Turbulent bluff-body wakes exemplify the coexistence of large-scale coherent structures and fine-scale turbulence – two ends of a wide dynamical range of scales connected through the turbulent cascade. In this work, we study the multiscale dynamics in the high-Reynolds-number wake behind a circular disk. One-point and two-point statistics are first examined, including the budget and spectra of the turbulent kinetic energy (TKE). Streamwise advection is found to contribute the most to the TKE balance, while the dissipation rate does not follow the classical equilibrium scaling ($\varepsilon \nsim \mathcal{U}^3/\mathcal{L}$). The largest scales are represented by the three-dimensional coherent modes extracted using spectral proper orthogonal decomposition, whereas the TKE and Reynolds shear stress spectra exhibit inertial-range scalings. A filtering-based triple decomposition further separates the fluctuations into large- and small-scale components and partitions the kinetic energy, with respective spatial transports at each scale and an inter-scale transfer in between. The inter-scale fluxes indicate a statistical forward cascade and follow the classical $\mathcal{U}^3/\mathcal{L}$ scaling, while their radial profiles become self-similar. The disequilibrium between inter-scale flux and dissipation is shown to arise from non-negligible streamwise advection at the sub-filter scale. Finally, the observed anti-correlation between the dissipation coefficient and the local Taylor Reynolds number, $C_\varepsilon = \varepsilon \mathcal{L}/\mathcal{U}^3 \sim Re_\lambda^{-1}$, is shown to originate from a similar correlation in the coarse-grained, locally averaged statistics. The results suggest that the instantaneous cascade-dissipation disequilibrium is intrinsic to turbulence and becomes apparent when large-scale unsteadiness and length-scale growth prevent statistical equilibrium.

Photonic-crystal microresonators (PhCRs) are a powerful platform for generating Kerr frequency combs. Because Kerr-soliton dynamics in PhCRs are largely decoupled from the operating wavelength, the comb output can be engineered through customization of the device layer. Here, we demonstrate a tantalum pentoxide (tantala) PhCR platform that supports 1310 nm and 1550 nm band operation, and we explore high-efficiency O-band soliton microcombs with all-semiconductor laser pumps. We engineer the PhCRs with silicon dioxide cladding and normal dispersion with intrinsic quality factors exceeding $7\times10^{6}$. By pumping bandgap modes, we obtain robust and efficient soliton comb formation at a 200 GHz mode spacing. Our PhCRs enable systematic tuning from narrowband to broadband comb states within a single device geometry. The combs exhibit low relative intensity noise approaching the shot-noise limit, indicating stable phase-matching in the PhCR. Using a second resonator coupler, we amplify the comb output off-chip, demonstrating a pathway to high-power O-band sources. These results establish PhCR engineering in the tantala platform as a scalable approach to wavelength-agile, low-noise microcombs for applications in communications, sensing, and signaling.

We investigate the magnetic-field response of interstitial anionic electrons (IAEs) in two-dimensional electrides, using monolayer Ca$_2$N as a prototypical system. By computing the Landau-level (LL) spectrum of the electride bands forming the Fermi surface, we find a linear LL evolution with magnetic field that closely resembles the behavior of a nearly-free 2D electron gas (2DEG). The extracted cyclotron effective mass and Landé g-factor deviate moderately from their free-electron values, indicating that the IAEs retain a remarkably free-electron-like character. Furthermore, the energy dispersion of the electride bands remains insensitive to the choice of exchange-correlation functional (LDA vs.~PBEsol), indicating that local exchange and correlation effects have minimal influence on the IAEs. Overall, our findings provide fundamental insight into the quantum nature of electrides and open new avenues for exploring magnetic confinement, correlation effects, and emergent quantum phenomena in low-dimensional interstitial electronic systems.

Purpose: Fully optical receive coils can potentially allow dense receiver arrays with a large channel count, reduced channel crosstalk, and less cable clutter. The power requirements of conventional low-noise amplifiers (LNAs) are prohibitive for simultaneously driving many coils through optical means, as opto-electric power conversion efficiencies can only reach about 50%. The goal is to develop low-power LNAs (LPLNA) with substantially lower power consumption without compromising noise figure (NF) and gain. Methods: A LPLNA was designed as a two-stage cascaded amplifier using an MR-compatible E-pHEMT (Enhancement-mode Pseudomorphic High Electron Mobility Transistor) transistor. The design was implemented on a single-sided printed circuit board (PCB), and its performance was compared with a commercial LNA. A four-channel shielded loop resonator array was constructed, and the signal-to-noise ratio (SNR), noise covariance, and preamplifier decoupling performance were evaluated. Results: The LPLNA had a five-fold lower electrical power consumption (40 mW) than the commercial LNA and provided comparable SNR in phantom measurements. In vivo experiments further confirmed that the LPLNA operates reliably under realistic MRI conditions. Additionally, four-channel receiver array measurements demonstrated comparable SNR within 2% of the commercial LNA and lower inter-channel noise correlation with 0.26 vs 0.3 on average. Conclusion: This study demonstrates the feasibility of LPLNAs for optically-powered RF receiver coil arrays. The LPLNA could also be applied in power-constrained or remote MRI environments.

We compute the fermion-photon vertex in QED in the presence of a constant and uniform magnetic background up to one-loop order. We show that even at tree-level, the vertex is modified due to the loss of Lorentz invariance induced by the magnetic field, thus breaking into longitudinal and transverse pieces. Moreover, the radiative corrections induce the emergence of a rich tensor structure that includes the anomalous magnetic moments in the transverse, parallel, and mixed transverse/parallel directions. We concentrate on studying one of these anomalous magnetic moment components, the one in the purely transverse direction. We find the selection rules for transitions between a few low-lying Landau levels and show that the amplitudes for transitions from an initial to a final Landau level differ by a sign from the reverse process due to the loss of time reversal invariance induced by the presence of the field. Contrary to the vacuum case, the amplitudes are, in general, complex, and the phase factor can be interpreted in terms of a finite life-time of the decaying state. For the anomalous magnetic moment in the purely transverse direction, transitions between states occupying both the lowest Landau levels are forbidden. Moreover, for the computation of the allowed transitions, we find that it is not necessary to include a photon mass since the magnetic field acts as an infrared regulator.

The interplay between nonlinear optical transitions and topological band structure offers a route to control photocurrents. We reveal a fourth-order optoelectronic response that emerges due to an interlink between the circular photogalvanic effect (CPGE) and the Berry curvature dipole (BCD) in noncentrosymmetric 2D materials. Using monolayer $\Td$-WTe$_2$ as a prototype, we predict that circularly polarized mid-infrared light produces a steady dc injection current that induces an internal electric field, which in turn drives a transverse nonlinear Hall response through BCD. The resulting cascaded photovoltage scales as the fourth power of the optical field $E_0^4$. By mapping the full injection current tensor, we show that this cascaded voltage is strongly tunable by the optical geometry: normal incidence drives an in-plane resonance $\mathrm{Im}(\eta_{yxy})$, whereas oblique illumination ($\theta = 45^{\circ}$) recruits a dominant out-of-plane component $\mathrm{Im}(\eta_{yyz})$ and amplifies the signal by more than two orders of magnitude (${\sim}10^2~\mu$V). While the massive linear Drude background typically screens nonlinear responses in semimetals, we argue that the amplitude modulation of the optical pump allows lock-in detection to cleanly isolate the frequency-doubled cascaded response. The proposed mechanism converts mid-infrared light into a gate-tunable transverse signal, providing a route for probing quantum geometry and realizing topological photodetectors and frequency doublers.

Non-fullerene acceptors such as Y6 have enabled high-efficiency organic photovoltaic devices and motivated the development of single-component architectures; however, the microscopic mechanisms governing exciton transport and charge dissociation remain under active investigation. In particular, the interplay between Frenkel-charge-transfer excitations and their coupling to environmental fluctuations complicates the description of light absorption and subsequent exciton dynamics. Here, ultrafast transient absorption spectroscopy is used to probe exciton quenching dynamics in Y6 films interfaced with hole-transport layers. To interpret these measurements, we develop an analytical model based on hybrid Frenkel-charge-transfer states that enables direct extraction of intermolecular electronic couplings, charge-transfer character, and system-bath interaction strengths from experimental data. The analysis reveals a substantial charge-transfer admixture of 20-40% in the exciton states and identifies a transport regime characterized by delocalization-mediated exciton motion rather than purely diffusive hopping. Consistent with this interpretation, the corresponding quenching dynamics occur on a ~1 ps timescale within ~4 nm of the interface, suggesting a short-range injection mechanism facilitated by exciton delocalization. In addition to providing physical parameters for Y6, these results establish a quantitative framework that connects spectroscopic observables to microscopic transport mechanisms and can be generalized to other non-fullerene acceptors.

Ground and excited electronic states in highly symmetric systems typically possess high degrees of spatial degeneracy as a consequence of point-group symmetry. However, many current quantum-chemical methods struggle to accurately describe the strong correlation effects inherently present in these states, thereby precluding the ability to obtain meaningful insights into the electronic structure of the underlying systems. Consequently, many of their important chemical and spectroscopic properties cannot be reliably computed and predicted. In this article, a new theoretical framework is described that unifies the symbolic treatment of non-Abelian symmetry in QSym$^2$ and the recently developed state-specific multi-reference coupled cluster theory termed Generalised Normal Ordered Coupled Cluster (GNOCC) to describe such difficult ground and excited states in a balanced and targeted manner. This is ensured by the ability of QSym$^2$ to exploit symmetry orbits to restore any broken spatial symmetries and generate symmetry-adapted multi-determinantal wavefunctions, as well as the ability of GNOCC to dynamically correlate arbitrary spin eigenfunctions in a size-extensive and spin-free manner. To illustrate the capabilities of this framework, several ground and excited states in three model systems are examined in detail: (i) octahedral $(\textrm{H}_6)^{2+}$, (ii) octahedral $\textrm{H}_6$, and (iii) tetrahedral $\textrm{Li}_4$. The results demonstrate that the proposed method can target both degenerate and non-degenerate states, while delivering improved numerical performance relative to conventional single-reference coupled-cluster approaches.

Bern-Carrasco-Johansson relations are helicity-independent constraints among the partial amplitudes of tree-level processes containing gluons and possibly also matter fields. They are a consequence of color-kinematic duality, but alternatively can be derived using the color-factor symmetry of tree-level amplitudes. We use recursive perturbiner methods to present a general, streamlined proof of the color-factor symmetry of all tree-level amplitudes containing an arbitrary number of fundamental spin-zero or spin-one-half matter fields and at least one gluon.

We present a fully differentiable far-field transform in cylindrical coordinates for full-area point spread function (PSF) evaluation and optimization of large axisymmetric metalenses. The method computes wave-optical responses of apertures spanning thousands to tens of thousands of wavelengths in diameter (millimeter scales in the visible, centimeter scales in the infrared) in seconds, achieving three to four orders of magnitude speedup over Green's function integration while avoiding the prohibitive memory of two-dimensional FFTs. The approach decomposes vectorial near fields into parallel angular-momentum channels, applies FFTLog-accelerated Hankel transforms, and uses Graf's addition theorem to recenter focal fields under oblique illumination. Analytic adjoint gradients enable optimization with only ~65% overhead relative to a forward simulation. For a 4 mm-diameter aperture (~8000 wavelengths, ~12,600 azimuthal modes) at 30-degree incidence, a forward-adjoint iteration requires only ~12 s on a 350-thread CPU, making oblique optimization practical without ray-tracing approximations. Applied to polychromatic RGB (446/530/650 nm) metalens design at normal incidence, full-area PSF evaluation exposes efficiency limits hidden by conventional cropped-focal-spot analysis: a mono-pillar metalens that appears diffraction-limited achieves only ~6% average absolute focusing efficiency, while direct far-field optimization raises this to 37% (locally periodic approximation) and 51% (zoned discrete axisymmetry). A cascaded double-metasurface design reaches 63%, while a four-metasurface architecture attains 96% average relative efficiency. We also demonstrate millimeter-scale, oblique-incidence optimization of single-surface and doublet architectures; cascaded doublets enable partial coma correction inaccessible to a single rotationally symmetric surface.

Coarse-graining (CG) lowers the computational cost of atomistic simulations by representing groups of atoms as effective interaction sites, reducing the degrees of freedom of the system but often compromising structural fidelity or requiring system-specific parameterization. Here, we introduce a novel anisotropic machine learning CG potential that extends the point particle representation of atomic nuclei to massive ellipsoidal beads with orientation-dependent features, enabling the learning of energies, forces, and torques directly from atomistic data. The anisotropic representation is physically motivated for polar and asymmetric molecules, where directional interactions and shape anisotropy play important roles in determining structure and dynamics. Using an equivariant message-passing neural network, the model accurately reproduces radial and angular distribution functions as well as relative orientation correlations in liquid water, demonstrating that both translational and rotational dynamics are well captured. Comparison with an isotropic baseline reveals that the lack of orientation information leads to systematic errors in short and long range order and degradation of angular correlations, proving orientation features are essential for accurate coarse-graining. The anisotropic model also exposes rotational structural observables fundamentally inaccessible to isotropic representations, with minimal computational overhead. Even for coarse-graining just three degrees of freedom, CG simulations achieve 7-27$\times$ speedups while preserving structural fidelity, highlighting the efficiency gains of this systemic reduction. This framework establishes the feasibility and necessity of learned equivariant representations for anisotropic CG modeling and provides a path towards accurate and efficient mesoscopic simulations of complex molecular liquids, polymers, and biomolecular systems.

We study scalar and vector bosons in the Bonnor–Melvin–$\Lambda$ spacetime within the Duffin–Kemmer–Petiau (DKP) formalism. By employing Umezawa's projection operators, we separate the physical spin-0 and spin-1 sectors and derive the corresponding exact second-order equations in the full curved spacetime, without relying on the conical approximation. For the scalar sector, the radial equation reduces to a Schrödinger-like equation with a trigonometric Pöschl–Teller effective potential. In the vector sector, the longitudinal mode is governed by the same effective potential, whereas the transverse polarizations are described by generalized trigonometric Pöschl–Teller potentials. Because the me\-tric function vanishes at a discrete set of radial points, the radial dynamics is naturally formulated as a singular Sturm–Liouville problem on a fundamental interval, with the physical radial domain fixed by the Friedrichs self-adjoint extension of the corresponding singular radial operators. As a result, all physical sectors exhibit purely discrete radial spectra, and their eigenfunctions are obtained in closed form. These results provide a unified exact treatment of scalar and vector bosons in the Bonnor–Melvin–$\Lambda$ spacetime, complement previous analyses based on the conical approximation, and clarify the role of the global geometric structure of the background in shaping confinement and spectral properties.

We study the sedimentation of stationary random suspensions of rigid particles in Stokes flow. Batchelor's formula predicts the first dilute correction to the infinite-volume mean settling speed due to hydrodynamic interactions between suspended particles. A rigorous derivation has long been obstructed by the long-range nature of the Stokes flow, which gives rise to infrared divergences in the large-volume limit. In dimension $d>2$, for stationary suspensions satisfying quantitative decorrelation assumptions, we construct the infinite-volume mean settling speed and show that it governs the relative settling speed of particles in large containers, independently of the container shape. We then establish a renormalized cluster expansion of this mean settling speed in the dilute regime and compute it up to the two-particle term, thereby justifying Batchelor's formula. The proof is based on the infrared renormalization of hydrodynamic interactions. Infinite-volume observables are decomposed into an explicit singular part, carrying the non-integrable large-scale contribution, and a regular remainder controlled by elliptic estimates. The singular part is renormalized through counterterms that encode the diverging mean backflow generated by the suspension. At the level of the dilute cluster expansion, the renormalization is implemented cluster by cluster and the singular-regular decomposition is achieved through a finitary diagrammatic expansion of hydrodynamic interactions, inspired by the method of reflections, which isolates the leading divergent substructures and exposes the key cancellations.

Growing complex shapes requires control over both where growth begins and how it evolves in time. Here, we introduce a geometric framework for growing prescribed 2D shapes using a disk packing algorithm. In this approach, a target geometry is filled by disks whose centers define where growth is initiated and whose radii define how long each region is allowed to grow. The allowed disk sizes are constrained by the physics of the process, including the growth velocity, the time required to initiate each growth event, and the number of initiations that can occur in parallel. To generate physically realizable packings, we introduce the Largest Gap Algorithm (LGA), which sequentially fills the largest remaining gaps in a target shape with the largest disk that satisfies both geometric and kinetic constraints. We show that this method produces high coverage packings for a variety of geometries and that the resulting packings can be directly converted into spatiotemporal packing instructions. We then demonstrate that these instructions can be realized experimentally using multi-point initiation of frontal polymerization in viscosified dicyclopentadiene (DCPD) resin using CO$_2$ laser. Our results show that complex shapes can be grown by programming a small number of local initiation events, providing a simple connection between geometry and dynamics of growth.

The Moon Mineralogy Mapper (M3) observed a widespread 3-micron absorption feature on the lunar surface, commonly attributed to surficial OH and/or H2O. The feature varies with latitude, local time, and lunar phase, suggesting that at least part of the optically active reservoir is dynamic. We compare phase- and local-time-resolved M3 abundance estimates with a global solar wind proton implantation, hydrogen diffusion, and H2 exosphere model. The model tracks implanted H in the upper grain rim, thermally activated retention and loss, recombinative H2 release, and phase-driven source variations associated with the solar wind, magnetosheath, and magnetotail. We compute the surface abundance using a weighted activation-energy-bin representation, in which the activation-energy distribution is discretized into fixed probability-weighted bins rather than sampled stochastically by Monte Carlo particles. This implementation reduces particle sampling noise in low-flux regions. A refined grid of Gaussian effective activation-energy distributions shows that the low- and mid-latitude M3 trends are best matched by distributions centered near Ec = 0.520 eV with width Ew = 0.090 eV. The preferred case gives a combined low- and mid-latitude RMSE of approximately 27 ppm and a small mean bias of only a few ppm. These fitted parameters should be interpreted as an effective response of the M3-sensitive retained H/OH reservoir, not as a unique mineralogical activation energy. The model reproduces the dominant local-time and phase-dependent abundance structure, including the reduced retained abundance near local noon, while model-data differences near plasma-transition intervals and high-latitude behavior may reflect additional sampling, saturation, or surface-plasma processes.

We performed high-precision mass measurements of the proton-rich nuclei $^{52}$Ni and $^{51}$Co with the LEBIT Penning trap at the Facility for Rare Isotope Beams (FRIB). For $^{52}$Ni, a mass excess of $-22474.8(2.2)$~keV was determined, which is consistent with a recent storage-ring measurement at the Cooler-Storage Ring (CSRe) but has a factor 37 improved precision. For $^{51}$Co, we obtained a mass excess of $-27375.1(5.7)$~keV, agreeing with a recent CSRe result, while reducing the uncertainty by a factor~2. Combining our mass value for $^{52}$Ni with the known two-proton decay energy of $^{54}$Zn, we determined the mass excess of $^{54}$Zn to be $-6463(42)$~keV. These new mass values reveal a substantial breakdown of the isobaric mass multiplet equation for $A=52$ and $A=54$, and provide stringent benchmarks for isospin-symmetry-breaking effects in the proton-rich $fp$-shell, favoring theoretical descriptions that omit the Coulomb-exchange term.

The population of close double white dwarfs (DWDs) in the Milky Way will make up the largest population of sources resolved by LISA, with a subset of the population having three-dimensional position and chirp mass measurements obtained from LISA observations. Because white dwarfs are the bulk of the Milky Way's stellar remnant population, the positions and masses of close DWDs resolved by LISA are defined by the stellar population properties that host them. Recent Gaia data has unveiled a triaxial accreted component of the Galactic stellar halo: the Gaia-Sausage-Enceladus, which contains stars that are more metal-rich than the extremely metal-poor population of stars residing in the stellar halo beyond 30 kpc. In this work, we assess the size and characteristics of the population of close DWDs using an empirically motivated Galactic model which incorporates the GSE and compare to the classical Galactic model that contains only a single very metal-poor halo population. To do this, we simulate a realistic present-day Galactic DWD population and determine its gravitational wave signal in LISA using LEGWORK. We find that incorporating the metal-rich population from the GSE imprints significant differences in the chirp mass and distance distributions of resolved DWDs, but that the strength and height of the gravitational wave foreground remains unchanged.

Here, we present a platform built on our inverted Graph Transformer Network, IMPRESSION-G2, which can accurately and rapidly reconstruct molecular bonding directly from experimental nuclear magnetic resonance (NMR) spectroscopic information. It comprises three interconnected stages: a one-shot model that predicts bond connectivity between atoms; a structure-correction stage that corrects the predicted structures by removing uncertain bonds and iteratively reassigning them; noise-augmented multi-shot prediction, generating an ensemble of candidate structures, which are ranked to identify the best-fit structure. By integrating a range of $^{1}$H and $^{13}$C NMR data, including two-dimensional (2D) experiments such as COSY, HSQC, and HMBC, the inverse-IMPRESSION platform correctly identifies the structures of 77.8% of molecules with up to 30 heavy atoms (H, C, N, O and F) using simulated NMR data, and 10 of 19 (53%) molecules using experimental NMR data. The experimental structures solved have molecular weights of up to 480 Da and are representative of the complex structures in synthetic and natural products that routinely challenge chemists. The inverse-IMPRESSION framework thus provides the first effective approach for automated molecular structure elucidation using graph-based machine learning on experimental data.

Ni nanoparticles are frequently used as catalysts for hydrogenation reactions as well as in hydrogen storage applications. Recently, we have shown that small Ni nanoparticles can absorb hydrogen at < 10 bar pressure to form Ni hydride. During this process, the hydride growth is anisotropic, and a coherent Ni/NiH interface is formed. In order to explain the anisotropy and to comprehensively account for the coupling chemical, mechanical and thermal effects, we develop in this study a simplified chemo-thermo-mechanical enthalpy model for Ni/NiH interfaces in thin films. This model captures the combined influence of extent of hydride formation x, temperature T, pressure P, size effect ($l$), and the ${\alpha}$/${\beta}$ interface energy ${\lambda}$. Two different ${\alpha}$/${\beta}$ interface orientations, namely (100) and (111), are investigated. The model is shown to correctly predict the enthalpy and volume changes over a wide range of length scales, from atomically thin layers (~1 nm) to micron scale and larger. This work provides the basis for the development of similar enthalpy models for other solid-state hydrogen storage nanostructured materials where anisotropic growth of hydride phases is also observed.

Hybrid programs combine a quantum circuit with a classical host program that consumes measurement outcomes. In such programs, an outcome may be syntactically read by the host but semantically non-contributory: changing the outcome cannot change the returned value. Such outcomes obscure gates that are dead only relative to the host semantics, and are therefore invisible to circuit-local optimizers. We present a semantics-aware host-side static analysis that identifies non-contributory measurement outcomes by abstract interpretation, and prove its soundness. We implement the analysis and evaluate it on $24$ application-faithful hybrid workloads across quantum chemistry, optimization, quantum machine learning, and quantum finance. Compared with a syntactic liveness baseline, our analysis identifies more than $4\times$ as many non-contributory measurements, and it standalone enables the removal of $37.98\%$ of total gates on average. Even after the state-of-the-art optimizers like Qiskit, t|ket$\rangle$, and PyZX have already optimized the circuits, our analysis still enables removal of more than $30\%$ of the post-optimized gates, showing that the host-semantic opportunities exposed by our analysis are not subsumed by circuit-local optimization. To scale our analysis, we further lower host programs to an SSA-style levelized intermediate representation that exposes level-wise parallelism for GPU execution, and implement a CUDA backend. We prove that this lowering preserves the analysis result, and the evaluation shows speedups of up to $6.53\times$ over a sequential baseline as structural parallelism increases.

The paper studies the problem of circular total positivity of the symmetric matrices with zero row sums. These matrices are exactly response matrices of the electrical networks. Alman, Lian and Tran described tests for circular total positivity in two related frameworks: the cluster algebra $\mathcal{CM}_n$ and the Laurent Phenomenon algebra $\mathcal{LM}_n$. Our first result is the construction of a seed in Scott's cluster algebra structure on the coordinate ring of the Grassmannian $\mathrm{Gr}(n-1,2n)$ that consists entirely of circular minors. We compare the cluster structure induced by this seed with $\mathcal{CM}_n$. In particular, for odd $n$ the cluster algebra structure $\mathcal{CM}_n$ is isomorphic to the cluster algebra structure on $\mathrm{Gr}(n-1,2n)$ subject to natural freezing and trivialization of certain cluster variables in their initial seeds. We use this isomorphism to relate circular total positivity to positivity in the Grassmannian. Our second result is that the Laurent Phenomenon algebra $\mathcal{LM}_n$ is isomorphic to the coordinate ring of the noncompactified space of electrical network, or equivalently, to a certain localization of the grove algebra.