Papers

Goniopolar metals exhibit opposite thermoelectric polarities along different crystallographic directions, enabling zero-field transverse thermoelectricity but offering few means for external control. Here we show that a spatially structured Laguerre–Gaussian vector potential can programmably reconstruct the goniopolar phase space of NaSn$_2$As$_2$. First-principles-derived Wannier transport with bond-dependent Peierls coupling reveals two OAM-dependent spatial scaling laws: the radial response follows the Laguerre–Gaussian radius $r_{\max}\propto\sqrt{|\ell|}$, while calculations for $|\ell|=2$–5 yield a dominant angular harmonic $m_{\mathrm{dom}}=2|\ell|$, encoding the optical winding in a frequency-doubled thermoelectric response. Increasing $|\ell|$ simultaneously reconstructs pre-existing goniopolar windows, enhancing a representative window by approximately 17% at $|\ell|=5$. By contrast, reversing $\ell$ at fixed polarization produces only a small correction that approximately interchanges upon polarization reversal. Energy-resolved transport reveals that the structured field redistributes in-plane and cross-plane electronic velocities, shifting the directional Seebeck-zero boundaries that define the goniopolar state. These results establish vortex position and OAM magnitude as programmable control coordinates for goniopolar thermoelectricity.

The origin of chirality-induced spin selectivity (CISS) remains elusive, and ultrahigh spin polarization (SP) in topologically knotted molecules is unexplained. We develop a discrete geometric spin-orbit coupling (SOC) framework for molecular junctions, resolving site-specific curvature and current-partition effects beyond continuous models. For trefoil-knot molecules, it quantifies site-resolved geometric SOC, reaching $\sim$120 meV, nearly two orders of magnitude larger than intrinsic SOC of light atoms. The substrate-coupled benzene unit, carrying the largest current and remarkable geometric SOC, dominates the CISS effect. The framework quantitatively reproduces measured SP, temperature-dependent magnetoresistance (MR) and $\Delta$MR trends, establishing discrete geometric SOC as a predictive tool for CISS in topologically knotted molecules.

Bismuth telluride (Bi2Te3) is a prototypical V-VI semiconductor of interest for both thermoelectric and topological applications; however, phase-selective synthesis and thermal stability across the bismuth-telluride homologous series remain poorly understood. We report a facile and phosphine-free colloidal synthesis approach for a phase-selective synthesis of Bi2Te3, BiTe, and Bi4Te5 nanosheets with well-defined hexagonal morphology. By controlling precursor chemistry and reaction temperature, we achieved the selective formation of different phases within the (Bi2)m(Bi2Te3)n homologous series. Based on in situ heating studies, BiTe and Bi4Te5 nanosheets transform into Bi2Te3 at about 340 degree C, followed by preferential Te sublimation under vacuum or oxidation in air at higher temperatures. We discuss plausible mechanisms for these phase transformations. EDS analysis and FFT analysis of STEM images provide direct evidence for the temperature-dependent compositional and structural changes and highlight the close thermal relationship among these phases. These results not only advance fundamental understanding of phase stability and thermal behavior in bismuth-tellurides at the nanoscale but also establish a framework for understanding structural evolution in related homologous series, providing insights into their potential future applications in thermoelectric, spintronic, and topological systems.

We report the synthesis and comprehensive investigation of single-crystalline Tb$_2$IrAl$_4$Ge$_2$ and Er$_2$IrAl$_4$Ge$_2$, the first Ir-based members of the $Ln_2M$Al$_4$Ge$_2$ family. Both compounds crystallize in the tetragonal Tb$_2$NiAl$_4$Ge$_2$-type structure (space group $I4/mmm$) and exhibit easy-axis magnetic anisotropy with the crystallographic $c$ axis as the preferred magnetization direction. Tb$_2$IrAl$_4$Ge$_2$ undergoes antiferromagnetic ordering below $T_N = 25$ K and develops a sequence of field-induced metamagnetic transitions accompanied by pronounced magnetotransport anomalies, including a nonlinear Hall response. In contrast, Er$_2$IrAl$_4$Ge$_2$ exhibits three successive zero-field magnetic transitions and a substantially richer low-temperature magnetic phase diagram comprising multiple competing field-induced phases confined to relatively modest magnetic fields. The differences between the Tb- and Er-based compounds demonstrate the wide range of magnetic behavior that can be realized within the \ce{Tb2NiAl4Ge2}-type structure. More broadly, the successful realization of Ir-based $Ln_2M$Al$_4$Ge$_2$ compounds considerably expands the accessible chemical space of this family and opens a route toward the exploration of related $4d$- and $5d$-based aluminogermanides.

In-context learning (ICL) enables a pretrained model to infer a task from demonstrations without updating its parameters. While much of the existing theory focuses on linear target functions, in this paper we study nonlinear cases by comparing two one-layer attention architectures on the same family of single-index tasks. A kernel learner first maps inputs through a fixed nonlinear feature map and then applies linear attention, whereas a feature learner applies attention to the original input, followed by a learned nonlinear readout. We derive predictions for their memorization and generalization errors using the replica method, retaining the effects of pretraining size, task-pool diversity, and training and inference context lengths. The resulting predictions closely match numerical experiments across a broad range of regimes. Our analysis yields phase diagrams that characterize when each architecture is advantageous as the amount of pretraining data, task diversity, and context lengths vary. We further identify qualitatively different context-length scalings for the two learners. Together, these results clarify how architectural choices interact with the dataset and govern nonlinear in-context learning.

We study the interplay between local stroboscopic measurements and the unitary quantum circuit dynamics of the deterministic Floquet-quantum East model. We derive exact analytical results for the probability of first detecting a subset of qubits back in their initial state. This is achieved via a renewal equation linking the first-detection probability to the subsystem Loschmidt echo, which encodes the effective open dynamics of the monitored qubits. The resulting statistics exhibit two regimes set by the competition between the measurement probing time and the relaxation timescale of the unitary circuit dynamics: while infrequent monitoring leads to geometric first-detection statistics, frequent monitoring induces correlations that manifest as deviations from this geometric behavior. These results provide a rare exact characterization of how local measurement backaction reshapes detection statistics in an interacting quantum many-body system. In our local protocol, return probabilities are controlled by the size of the monitored subregion and can therefore be accessed on digital quantum simulators via local mid-circuit measurements.

The active Brownian particle (ABP) model is one of the most widely used particle-based models in studies of scalar active fluids. A collection of interacting ABPs is known to exhibit intriguing phenomena that are absent in equilibrium counterparts. A prominent example is spontaneous phase separation, known as motility-induced phase separation (MIPS), which occurs even in the absence of explicit attractive interactions. In parallel, the large-scale behavior of scalar active fluids is often modeled using continuum descriptions, namely, scalar field theories. Such scalar active field theories are usually formulated in a top-down manner, and establishing their connections to particle-based models remains challenging, with these connections not yet fully understood. To advance the microscopic derivation of scalar active field theories, we revisit the connection between ABPs interacting via a two-body potential in two dimensions and scalar field theories that include all possible terms up to fourth order in spatial gradients. Our approach is based on a pressure expansion and the renormalization group (RG) method in the context of singular perturbation theory. The RG method provides a systematic way to eliminate fast variables and identify the dynamics on the slow invariant manifold. Within this framework, scalar field theories can be obtained as RG flow equations. We also apply this method to a chiral variant of the ABP model, the chiral ABP (cABP) model, in which a constant torque biases particle rotation to the left or right. We show that the scalar field theory corresponding to the cABP model contains two “odd” terms in addition to those present in the scalar field theory for ABPs. The method developed here may also be useful for deriving hydrodynamic descriptions of other types of active matter systems.

Event-chain Monte Carlo (ECMC) has revolutionised computational sampling over recent years, providing a powerful alternative to the molecular-dynamics (MD) and Hamiltonian Monte Carlo (HMC) algorithms. Each method outperforms the ubiquitous random-walk Metropolis algorithm by advancing particles along deterministic trajectories, but ECMC achieves this without being constrained by Newtonian dynamics. Recent advances exploited this dynamical freedom to induce a collective particle dynamics that relax local density variations on fast timescales. In a foundational model of $N$ pairwise-interacting particles on the 1D torus, this led to an $O(N^{3/4})$ improvement on the industry-leading computational efficiency of MD and HMC - but with an impractically small prefactor at low/high mean particle density for general attractive/repulsive interactions. Here we present a universal framework that generalises this high-efficiency sampling strategy to all translationally symmetric pairwise models on the torus - creating the potential to surpass MD and HMC as the state of the art. We also numerically elucidate the collective particle dynamics and discuss broad impact across the physical sciences and computational statistics.

Dense melts of nonconcatenated ring polymers exhibit anomalous dynamics and nonlinear rheology, in some cases linked to long-lived inter-ring threading entanglement. Detecting these geometric constraints remains computationally demanding, with different methods being based on different geometric features tuned to specific models. Here, we introduce a machine-learning framework that detects threading directly from the writhe of ring conformations and we demonstrate its broad generalisability. Trained on simulations of isolated, distance-constrained pairs of short rings, a one-dimensional convolutional neural network (CNN1D) operating on the writhe profile classifies threading states with over 98% accuracy on held-out ring pairs. Remarkably, this model generalises without retraining to equilibrium dense melts spanning a wide range of densities and chain lengths (N = 100 to 1600), maintaining true-positive rates above 91% with false-positive rates near zero. Misclassified conformations are limited to physically ambiguous, shallow threading events which are arguably not impacting the dynamics of the rings. Effectively, writhe captures the interaction between the two rings, allowing writhe-based classifiers to improve the topological analysis of large ring-polymer systems with a 3-fold speed-up over the state-of-the-art minimal-surface detection. These results establish the writhe-trained neural networks as an accurate, scalable tool for characterising entanglement in ring polymer melts.

In polar semiconductors the Fröhlich interaction is the dominant electron–phonon coupling, yet excitonic resonances in materials such as halide perovskites remain anomalously sharp. We show that standard frozen-center-of-mass treatments of the exciton–phonon problem miss the decisive kinematic degree of freedom: restoring the exact center-of-mass (COM) recoil reveals a universally open, parameter-free $1s\to1s$ absorption channel at recoil momentum $q_*=\sqrt{2M_{\rm ex}\hbar\omega_{\rm LO}}/\hbar$, whose rate scales as $N_{\rm LO}(T)$. We prove that this recoil channel is controlled by destructive electron–hole interference: the recoil linewidth vanishes with the mass asymmetry as $\gamma_{\rm LO}^{\rm recoil}\propto\mathcal{F}_{1s,1s}(q_*)^2$, and the elastic dressing obeys the exact suppression law $S_X/S_{\rm ind}=\eta^2(6-\eta^2)/5$ within the hydrogenic Fröhlich model. The theory establishes a hierarchy of scattering regimes. In mass-asymmetric materials (GaAs, $\eta=-0.74$) the recoil channel is active ($\gamma_{\rm LO}^{\rm recoil}=2.2$~meV); in mass-symmetric materials (FAPbI$_3$, $\eta=0$; MAPbI$_3$, $\eta=-0.11$) it is killed by interference (0.00 and 0.12 meV), showing that the observed 27–40 meV perovskite linewidths cannot be accounted for by COM recoil and therefore require internal-state-changing and other inelastic channels, of which the constructive, $\eta$-robust $1s\to np$ resonance is the leading candidate within the present model. The Fröhlich constant $\alpha$ alone is therefore insufficient as a figure of merit: after projection onto the correlated exciton, the controlling parameters are $\eta$, $q_*a_X$, and the Rydberg detuning.

In a polar material, a neutral exciton couples to phonons through the sum of the electron and hole deformation potentials. Because the total source vanishes by charge neutrality, the elastic exciton-phonon vertex is regularized by electron-hole interference. Here we determine the non-perturbative fate of this interference by exact diagonalization of a Holstein-exciton model. By parameterizing the mass asymmetry to decouple it from the small-polaron atomic limit, we map a regime map comprising an internal dressing crossover and a dissociation boundary. We prove analytically and verify numerically that for equal masses, the symmetric exciton ground state is protected from phonon dressing by an exact exchange selection rule, provided the phonon source is odd under electron-hole exchange (the neutral case). As mass asymmetry increases, this selection rule is broken and the exciton acquires a strong local polaronic cloud. We show that the dissociation boundary, conversely, is set by a global energy balance between Coulomb binding and polaronic stabilization, and is nearly independent of the internal dressing. Paradoxically, the very symmetry that protects the exciton from dressing denies it polaronic stabilization, driving it toward dissociation at strong coupling. We discuss these results in the context of lattice exciton-polaron models and their implications for sharp versus broad excitonic lines in mass-symmetric versus mass-asymmetric polar semiconductors.

Why can masked prediction learn useful representations that unmasked reconstruction misses? We study this question in a high-dimensional model of a masked autoencoder (MAE) trained on data with shared latent structure and heterogeneous noise. We prove that masked linear reconstruction can recover the latent feature at linear sample complexity in regimes where unmasked linear reconstruction, equivalent to PCA, fails. The analysis also quantifies the statistical advantage of mask resampling, an established ingredient of masked pretraining. By introducing a fixed collection of $K$ masks per sample, we characterize its effect on feature recovery and downstream performance, identifying regimes where greater mask diversity lowers sample complexity. Guided by this prediction, we find that random cropping and flipping in standard image-training pipelines can obscure the advantage of mask resampling by renewing the prediction task even when the patch mask is fixed. Removing these transformations reveals a downstream advantage for dynamic over static masking in CNN autoencoders and vision transformers. A complementary BERT pilot finds benefits from greater mask diversity on downstream language tasks. Our results separate the benefit of the masked prediction objective from that of mask diversity, and show how a tractable theory can guide experiments that uncover advantages hidden by standard training practices.

Phyllosilicate clays are widely used in polymer nanocomposites owing to their high anisotropy and tunable surface polarity. Their distribution and interface localization in polymer blends can be used to tune the properties of polymer-clay nanocomposites (PCNCs). A coarse-grained (CG) force field for clays can aid molecular simulations in PCNC development. Here, we developed MARTINI-3 parameters, a CG force field with high chemical specificity, for phyllosilicate clays with diverse surface polarities. Initial interactions for the clay functional groups were determined from hydration free energies, obtained by applying the Lifshitz theory to experimental surface tension data. These were fine-tuned using the structural, thermodynamic, and dynamic properties of thermoplastic starch (TPS)-clay composites from all-atom (AA) molecular dynamics (MD) simulations. The radial distribution function and two-body excess entropy of TPS components, not used in CG parameterization, were accurately estimated, establishing the robustness of the parameters. We investigated the effect of clay surface polarity on polymer segmental dynamics and structure-property relationships. The CG parameters were then used to study the effect of dodecyltrimethylammonium (C12TAB)-modified montmorillonite (MMT), an organically-modified MMT, on TPS-polyethylene (PE) blend morphology using large time- and length-scale MD simulations. We observed compatibilization of the TPS-PE interphase by the amphiphilic clay particle, reducing the TPS-PE interfacial tension from 45 mN/m to 13.06 mN/m. We found good agreement between MARTINI-3 estimates for properties of model MMT-based PCNCs and those from AA simulations and experimental data, establishing grounds for the transferability of the parameters to other systems.

Magnetic skyrmions are promising nanoscale information carriers because their position can be manipulated by electrical currents. The additional ability of deterministic control of the spin structure would allow the use of magnetic skyrmions as multi-state bits, expanding the capabilities of skyrmion devices further. Such control could be realized by coupling all-optical helicity independent switching of magnetization (AO-HIS) to magnetic skyrmions. This is realized in a Pt/Ir/CoB/Gd/Pt multilayer that is engineered to stabilize magnetic skyrmions and, at the same time, enable AO-HIS by single ultrafast laser pulse. Laser excitation is used to write skyrmionic textures, whose polarity is selected by a small applied out-of-plane field. A single 30 fs laser pulse is then used to toggle the magnetization of an illuminated region containing skyrmionic textures, reversing their polarities without requiring any magnetic field or current pulses. This establishes deterministic optical switching of the skyrmion spin structure as a new manipulation channel, distinct from previously reported optical nucleation and annihilation. The material is then patterned into a wire, to combine the optical manipulation with current-induced skyrmion motion. These results establish a route toward opto-spintronic skyrmion devices in which light programs the internal state of a skyrmion and electrical currents control its position.

The interplay between electronic and structural degrees of freedom underpins many emergent phenomena in quantum materials, yet magnetoelastic coupling in metallic systems is typically weak and confined to low temperatures or microscopic length scales. Here, we report giant magnetoelastic coupling slightly above room temperature in the uranium-based intermetallic compound UIr$_4$Al$_{15}$. Using temperature-dependent single-crystal X-ray diffraction together with anisotropic magnetic susceptibility measurements, we directly resolve subtle but reproducible structural distortions coupled to magnetic alignment. Despite the absence of crystallographic symmetry breaking, pronounced anomalies emerge in lattice parameters and selected chemical bond distances near the magnetic transition region, revealing an unusual sensitivity of the crystal structure to magnetic orientation. The coupling enables direct probing of how atomic distances and local chemical bonding govern the electronic and magnetic states in a bulk intermetallic material. Our results establish UIr$_4$Al$_{15}$ as a rare platform in which magnetism and lattice distortions are strongly intertwined near room temperature, opening new opportunities for magnetically responsive quantum materials and functional magnetic sensing applications.

Traffic movement on highways and data packet transmission across the Internet serve as prototypical examples of collective dynamical behavior in complex systems. Although enhancing traffic flow in complex networks has been extensively investigated, most existing studies focus on single-queue models. In this paper, we introduce a simple yet effective two-queue scheme with gate control that regulates vehicle entry and integrates it with the routing protocol. When vehicles arrive at a on-ramp gate, they first join a waiting queue and are permitted to enter the main flowing queue once it has emptied. This two-queue strategy is especially advantageous when highway inflow varies periodically with large fluctuations, as is commonly observed in real traffic. Moreover, it modifies the system's failure characteristics, replacing sudden, discontinuous jamming transitions with gradual, continuous ones. The approach is based on a simple rule using only local queue information, making it easy to implement and widely applicable. Beyond the specific setup studied here, it can be applied to other transportation networks under different conditions or extended to other queuing systems, such as Internet data packet routing.

We examine whether the perturbative renormalization group (RG) regime of stochastic turbulence can be continued from small $\varepsilon$ to the physical value $\varepsilon_{\mathrm{phys}}=2$, corresponding to large-scale forcing. Exploiting the simplifications of the large-$d$ limit, we calculate the correction exponent $\omega$ to five-loop order and find a simple structure suggesting a closed analytic form. This form implies that the fixed point stable near $\varepsilon=0$ ceases to be simultaneously real and infrared stable before reaching $\varepsilon_{\mathrm{phys}}=2$, pointing to a possible change of infrared regime rather than a controlled perturbative RG extrapolation.

Most proposals for $Z_3$ parafermions in fractional quantum Hall-superconductor structures used the spin-unpolarized $\nu = 2/3$ Halperin $(1,1,2)$ state. The fractional quantum anomalous Hall (FQAH) states of twisted MoTe$_2$ and rhombohedral graphene are believed to be spin- and valley-polarized Jain states, with the same topological order but a different spin structure. We analyze a trench between two polarized $\nu = 2/3$ edges. Among the pairing and tunneling bilinears of the edge-mode electrons, exactly two of each have zero conformal spin. Pairing is compatible only with the neutral-mode superconductivity channel and tunneling only with neutral-mode backscattering, whereas in the unpolarized state singlet pairing and tunneling select the same channel. Since the two channels condense the same neutral anyon up to a local operator, the domain walls carry $Z_3$ parafermions, with 3 protected states per pair, whether or not the neutral channel changes between regions; fixing the fermion parity does not enlarge this count. Before the neutral gap forms, pairing is at best marginal for repulsive inter-edge coupling unless an attractive neutral coupling favors its channel; once the gap has formed, both charge terms are relevant for an inter-edge Coulomb coupling below 7/25 of the intra-edge one. The superconductor must supply even-frequency, equal-spin, intravalley pairing, which an s-wave singlet superconductor with only Ising spin-orbit coupling does not provide at leading order, whereas chiral $p+ip$ and $f+if$ states do. The $Z_3$ label is carried by a quasiparticle of the FQAH state, so no process confined to a junction whose tunneling segments are not FQAH can change it, and we expect a $6\pi$-periodic Josephson current with or without fixed fermion parity.

Simulating microstructure evolution requires quantum-mechanical accuracy and mesoscopic reach in length and time scales, a combination that no current method achieves. Classical phase-field models provide this reach, but their accuracy is limited by phenomenological free energies and mobilities. Here we develop a framework for learning ab initio phase-field models, where the mesoscopic equation is not postulated but derived from a Mori-Zwanzig projection of molecular dynamics onto species-density fields under explicit assumptions. The nonlocal free energy and mobility left unspecified by this equation are parametrized by neural networks and learned from short molecular dynamics trajectories generated with machine-learning interatomic potentials of ab initio accuracy. We demonstrate the framework on an iron-boron melt and on hydrogen-helium mixtures under planetary conditions. For iron-boron, the model shows that the melt at the FeB$_4$ composition is spinodally unstable at ambient pressure but stabilized at 10 GPa, offering a thermodynamic rationale for why FeB$_4$ has been synthesized only under high pressure. For hydrogen-helium, the model predicts the immiscibility boundary and captures droplet nucleation and growth in helium-rain simulations of a column corresponding to 2.2 million atoms, far beyond the scale of atomistic modeling at comparable accuracy. Trained across compositions and conditions, such models could provide a mesoscopic counterpart to ab initio molecular dynamics.

Structured light can generate electronic dc currents with azimuthal winding, yet the rules governing their winding order $m$ remain unclear. Here we identify sector-resolved winding selection rules using graphene as a clean two-dimensional platform. By decomposing the current response into local and gradient sectors at the current-operator level, we show that the winding order is determined not by the optical orbital angular momentum $\ell$ alone, but by the angular structure of the corresponding current operators together with projection onto the azimuthal direction. For scalar Laguerre-Gaussian beams, linear polarization yields $m=|\ell\pm1|$ in the local sector and $m=|\ell|,|\ell\pm2|$ in the gradient sector, whereas circular polarization with helicity $\sigma=\pm1$ selects $m=|\ell-\sigma|$ in the local sector and $m=|\ell+2\sigma|$ in the gradient sector. Numerical time-evolution calculations verify these rules and further show that helicity can select an $m=0$ branch, producing an azimuthally uniform circulating current whose radial profile determines the axial magnetic field $B_z(z)$. Our results provide a sector-resolved organizing principle for classifying and controlling structured-light-driven dc currents with tailored winding structures.

We study the thermalization in the random free fermion model by a detailed random-matrix analysis. By computing the ensemble average and fluctuations of $\operatorname{Tr}(A\rho(t))$ for a single-particle observable $A$, we derive the thermalization function $g^2(t/\tau_\lambda)$ with $\tau_\lambda = \hbar/(2\eta\sqrt{N})$, prove its $|t|^{-3}$ asymptotic decay, and show that the variance of the fluctuations vanishes as $O(1/N)$ in the thermodynamic limit.Particle number conservation is also incorporated into the model, by which we further study the energy-shell eigenstate statistics and prove a factorization theorem of the eigenstate statistics. We further show that under a controlled eigenvector-eigenvalue correlation deformation, the diagonal energy-resolved slope and the off-diagonal eigenstate thermalization hypothesis spectral function acquire an energy dependence.Finally, we compute the fluctuations of correlation functions and compare the fluctuation scales with those of a fully chaotic system, revealing quantitative differences rooted in the Gaussian nature of the eigenstates.Our work establishes the random free fermion model as an analytically solvable realization of weak eigenstate thermalization hypothesis type self-averaging, and as a controllable setting in which eigenbasis chaos can be separated from spectral chaos.

Co-propagating chiral Majorana edge modes are predicted to exist in proximity-coupled quantum anomalous Hall systems. They combine the exciting prospects of edge vortices as flying non-Abelian Ising anyons, with their fully electrical detection through anyon fusion processes. In this setup, electrical transport arises from the interference of a pair of Majorana edge states. By bosonizing the model with an additional replica sector, we generalize previous treatments to fully asymmetric configurations. We analyze a Mach-Zehnder interferometer and show that while the DC conductance does not exhibit signatures of edge-vortex interference, at low frequencies, this interference manifests as an effective capacitance. This quantity is sensitive to the non-Abelian anyon statistics of edge vortices and, in particular, carries signatures of their topological spin and nontrivial conformal dimension. We demonstrate that the thermal length $l_T = \hbar v/(\pi k_B T)$ is the relevant scale at low temperatures $T$, analogous to quasiparticle transport in conventional quantum Hall edge states with velocity $v$. As long as the interferometer arm lengths match within this length scale, transport signatures of the non-Abelian statistics of edge vortices remain visible.

Peptide sequence governs both the structures formed through supramolecular assembly and the dynamics by which they emerge, but predicting either requires resolving slow collective processes among many interacting molecules. Molecular dynamics (MD) provides microscopic insight into these processes, yet the long timescales of assembly and the vast peptide sequence space make systematic exploration computationally demanding. We introduce SupraTITO, a transferable generative molecular dynamics (GenMD) framework for supramolecular systems, demonstrated through peptide self-assembly. SupraTITO learns transferable implicit transfer operators (TITO) conditioned on peptide sequence, molecular topology, and periodic geometry, allowing configurations to be propagated over physical intervals much longer than an MD integration step. On a comprehensive dipeptide benchmark, SupraTITO generalizes to held-out sequences and reproduces sequence-dependent structures and dynamics while maintaining molecular integrity over long rollouts. Compared with direct ensemble prediction trained on the same trajectory data, SupraTITO more accurately reproduces assembly structures while also resolving their temporal evolution. The learned dynamics generalize across peptide concentrations, including dilute conditions not represented during training. These results extend transferable GenMD to collective dynamics in periodic supramolecular systems and provide a foundation for modeling related processes beyond peptide assembly.

Vacancy ordered double perovskites (VODPs) have been known for more than 100 years, but their exact crystal structures and magnetic ground state remained controversial till date. Anhydrous VODP iridates ($A_2$Ir$X_6$; $A$ = K$^+$, (NH$_4$)$^+$, Cs$^+$, Rb$^+$, and $X$ = F$^-$, Cl$^-$, Br$^-$), having $face-centered~cubic$ (fcc) antiferromagnetic ground state, offer a chemically well-defined platform to investigate the influence of on-site Coulomb repulsion, crystal field, spin-orbit coupling, and competing Heisenberg and Kitaev interactions. Interestingly, among these, the Na-based VODP iridates seem to possess an unusual hydration dependent structural and magnetic uncertainty. As a result, a cubic Na$_2$IrCl$_6$ system having fcc antiferromagnetism could not be stabilized ever. Here, for the first time, we report the synthesis and comprehensive characterization of anhydrous Na$_2$IrCl$_6$ single crystals having fcc structure with antiferromagnetic transition temperature of 1.91 K. Thermogravimetric analysis establishes the absence of lattice water and also demonstrates thermal stability of the crystals up to 453 K. The cubic phase reported here contrasts with previously described 'anhydrous' monoclinic Na$_2$IrCl$_6$ and highlights the strong structural and physical property relationship in Na-based VODP iridates. This new material offers an exciting playing ground for exploring another potential perfect $J_{eff}$ = $\frac{1}{2}$ octahedra and the consequent strong Kitaev interaction within the nearest-neighbor (nn) pairs of Ir ions.

Average atom (A-atom) potentials provide a mean-field description of a chemically disordered alloy and are used to predict the properties of solid solutions without short-range order. Such potentials are usually averaged from an existing interatomic potential and are therefore only as accurate as the parent model. Accurate interatomic potentials are themselves difficult to parameterize and can require large training datasets. Here we benchmark a recently developed formalism that computes an exact A-atom potential directly from a linear atomic cluster expansion (ACE). We first fit a linear ACE to Fe-W data generated with an embedded atom method (EAM) potential. The resulting A-atom potential reproduces the properties of the disordered phase computed from an explicit random supercell and from a conventional A-atom potential averaged from the same EAM potential. We then fit a linear ACE to energies and forces computed from electronic structure calculations for about 1500 small Mo-Nb structures with an average of 7 atoms per structure. The A-atom potential derived from this ACE reproduces the DFT elastic constants, lattice parameter, mixing enthalpy, and Bain path of special quasirandom structures. Of the three chemical site bases, only the occupation basis also reproduces the DFT surface energies of the alloy. For Mo-Nb, the A-atom potential also predicts that the ideal solution entropy outweighs the destabilizing vibrational contribution to the finite-temperature free energy of the disordered phase. These benchmarks show that the properties of disordered alloys can be recovered from small training datasets when the chemical site basis is chosen carefully.

Ultrashort light pulses can drive transient photocurrents in solids, the basis of modern terahertz (THz) emitters. Ferroelectrics have recently emerged in this context as sources that require neither the bias voltage of photoconductive antennas nor the magnetic field of spintronic emitters, yet the ultrafast photocurrent generating the emission has remained debated. Here, we resolve this question in epitaxial BiFeO$_3$ thin films with engineered ferroelectric domain configurations, from single-domain to periodic stripe patterns. The stripe-domain film emits a THz field four times stronger than the single-domain configurations, reaching about half the output of a metallic spintronic reference emitter while remaining unsaturated at our highest excitation fluences. Resolving the emitted THz field in amplitude and phase as a function of the pump light polarization and the crystal orientation, we separate the coexisting photocurrents by their symmetry. This identifies the ultrafast screening of the ferroelectric polarization by photocarriers as the dominant emission mechanism in the in-plane-polarized films, enhanced in multidomain films by the strong built-in fields at the domain walls, while an out-of-plane polarization favors the bulk photovoltaic current. Our results establish the ferroelectric domain configuration as a design parameter setting both the strength and the microscopic origin of light-driven THz emission.

Topological spin textures in antiferromagnets inherit the compensated magnetic order of the host material, resulting for skyrmions in the suppression of the skyrmion Hall effect and enabling ultrafast dynamics that make them attractive for low-power spintronic devices. In intrinsic antiferromagnets, the two sublattices are identical, but synthetic antiferromagnets offer additional control mechanisms by enabling independent tuning of the properties of two ferromagnetic layers. Analogous to a ferrimagnet, the total magnetic moment can be adjusted by compensating the two-layer moments. Here, we demonstrate that tuning the effective magnetic anisotropy difference between the two layers drives a spin-flop transition where one layer reorients and thus stabilizes an orthogonal configuration with one layer oriented along the out-of-plane direction and the other in-plane. In this transition, an antiferromagnetic skyrmion undergoes a homotopic reconfiguration into a complex spin texture comprising a skyrmion coupled to an in-plane bimeron. Element-specific X-ray microscopy resolves this texture layer by layer: one hosts an out-of-plane skyrmion coupled to an in-plane bimeron in the other. We refer to this previously unexplored three-dimensional spin texture as a skymeron. By using time-resolved pump-probe X-ray microscopy, we discover unique polarity ,dependent dynamics during current pulses: a short post-pulse inertia-like continuation of the motion, and a slower return towards the pinned initial state. Micromagnetic simulations reveal that the inertia-like propagation originates from the finite-time relaxation of reorientation of the skymeron. Our results establish layer-selective anisotropy engineering as a route to uncharted composite spin textures with internal dynamical degrees of freedom, not possible in conventional antiferromagnets with identical sublattices.

The Verwey transition in magnetite is a benchmark electronically driven phase transition that is highly sensitive to lattice imperfections and external perturbations. Doping, deviations from oxygen stoichiometry, and irradiation-induced point defects are known to lower the Verwey transition temperature, $T_{\rm V}$. By contrast, the role of remanent strain fields and extended defect structures generated by uniaxial stress has remained largely unexplored. Here we combine dark-field x-ray microscopy (DFXM) and ac magnetic susceptibility to determine how strain-induced defects affect the Verwey transition in stoichiometric single-crystalline magnetite after uniaxial compression and unloading. The DFXM measurements were performed on two samples compressed along the same $[011]$ direction: loading to $200~\mathrm{MPa}$ generated stable line-like defects and remanent strain fields, whereas loading beyond the fracture threshold produced denser defect networks and mechanical fracture. To test the effect of a different loading geometry, we also measured the ac susceptibility of a sample fractured by compression along $[001]$. Real-space DFXM imaging, lattice-orientation mapping, and residual strain mapping show substantial remanent structural disorder after compression. Nevertheless, neither the transition temperature $T_{\rm V}$ nor the sharpness of the transition changes measurably in any of the compressed or fractured samples. This behavior contrasts with the strong suppression of $T_{\rm V}$ by point-like disorder. Our results show that extended line-like defects and remanent strain fields produced by plastic deformation do not measurably perturb the macroscopic electronic ordering responsible for the Verwey transition, thereby distinguishing the effects of point defects from those of extended slip-related defects in magnetite.

Charging uniformity across distinct trials is an essential requirement for reliable quantum batteries. Nevertheless, intrinsic quantum stochasticity poses a fundamental challenge to this goal. This work investigates a two-qubit quantum battery within the framework of cascaded collision models. We propose an adaptive measurement on the charger after each collision, yielding two conditional battery states of equal expected stored energy. For chargers prepared in the excited state, we analytically prove that complete suppression of trajectory-dependent stored-energy fluctuations is attainable; for chargers prepared in general superposition states, our theory reveals that full suppression is fundamentally prohibited owing to battery-phase-dependent recursive dynamics. Numerical simulations are in excellent quantitative agreement with theoretical predictions. These findings provide a feasible pathway toward high-uniformity quantum-battery charging.

Generative models have made rapid progress in ordered crystal structure prediction, yet many functional materials are intrinsically disordered, with substitutional mixing, vacancies, or interstitial species controlling their properties. Existing crystal generators either assume deterministic site occupations or require site-level disorder annotations, which are often unavailable when the chemical formula is the primary input. We formulate disordered crystal structure prediction through an Occupancy Distribution Matrix (ODM), a continuous site-by-species representation that unifies ordered crystals, solid solutions, vacancy disorder, and interstitial occupancy. A valid ODM must satisfy coupled site-wise occupancy, mass-conservation, and non-negativity constraints, placing each sample on a formula-dependent transportation polytope. We propose Entropic Polytope Flow (EP-Flow), a marginal-constrained flow matching framework that canonicalizes heterogeneous polytopes into a shared double-centered space, learns a marginal-preserving flow, and recovers feasible occupancies through a Sinkhorn inverse map. By jointly generating occupancies, fractional coordinates, and lattice parameters, EP-Flow achieves state-of-the-art performance on formula-conditioned disordered CSP benchmarks derived from COD and MPDS, substantially outperforming adapted ordered-crystal generators. Analyses further show that EP-Flow recovers sparse and chemically meaningful local disorder patterns rather than merely matching global composition statistics.