Papers

Describing fermionic systems with attractive interactions, such as superconductors and atomic nuclei, beyond the mean-field level remains a central challenge. In this work, we investigate the performance of Bogoliubov fully self-consistent $GW$ (Bog.~sc$GW$) and second-order Green's function (Bog.~scGF2) methods, implemented within a unified imaginary-time and imaginary-frequency framework. Using the attractive Hubbard model as a benchmark against full configuration interaction (FCI), we find that Bog. scGF2 provides a more accurate description than Bog.~sc$GW$. In particular, Bog.~sc$GW$ systematically overestimates the correlation energy, with errors increasing rapidly as the attractive interaction strength grows. These results highlight the importance of exchange contributions in strongly correlated fermionic systems, even when exchange effects are included only at low order in perturbation theory.

Climate oscillations are intrinsically out-of-equilibrium phenomena, yet the connection between their predictability and nonequilibrium thermodynamic properties remains unexplored. We develop a coarse-grained stochastic thermodynamic framework for Ornstein-Uhlenbeck (OU) processes and apply this framework to climate data via linear inverse models (LIMs), linking predictability, entropy production, dynamical activity, and path action. Climate oscillations are often studied in a 2d phase space of climate indices, which are even under time-reversal, motivating our focus on 2d OU dynamics with even variables. We find that coordinate-invariant properties of 2d OU processes can be reduced to a minimal three-parameter description: two diffusivities and a phase-space rotation. We show that these quantities fundamentally characterize distinct aspects of the dynamics. We find that higher irreversibility and dynamical activity do not necessarily imply reduced predictability. Rather, it is the path action which is most closely connected to a commonly used measure of predictability, the anomaly correlation coefficient (ACC). As an illustrative example, we apply this framework to the Madden-Julian Oscillation (MJO) over the twentieth century. We find that the MJO has become simultaneously more predictable, as seen previously, while at the same time becoming more irreversible and more active. Predictability is driven predominantly by the reduced mean diffusion. Entropy production reflects the combined evolution of all three parameters. These results suggest that stochastic thermodynamics provides a powerful lens for studying nonequilibrium climate phenomena.

Griffiths phases provide a mechanism for sustaining critical dynamics over extended parameter regions without fine-tuning to an isolated transition point. This behavior has been mainly associated with structural heterogeneity in complex networks. Here we show that quenched heterogeneity in local parameters can generate a chaotic Griffiths phase in a network of map-based neurons. We study globally coupled Chialvo maps with quenched disorder in a local neuronal parameter, thereby isolating intrinsic parameter disorder from topological disorder. As the coupling strength is varied, a chaotic Griffiths phase emerges between desynchronized and coherent chaotic dynamics, characterized by intermittent formation and breakup of neuronal clusters and large fluctuations in the fraction of clustered neurons. Within this regime, cluster sizes exhibit power-law distributions with coupling-dependent exponents, providing evidence of critical behavior over a finite parameter interval. The chaotic Griffiths phase is absent in the homogeneous limit and broadens progressively as the degree of parameter heterogeneity increases. We further introduce topological disorder through small-world connectivity and find that its combined action with local parameter heterogeneity substantially extends the chaotic Griffiths phase. In both globally coupled and small-world networks, the number of positive Lyapunov exponents displays anomalous scaling with system size. These results demonstrate that intrinsic dynamical heterogeneity constitutes an independent mechanism for generating chaotic Griffiths phases and that its interplay with structural disorder enhances extended criticality in neuronal networks.

Yield point phenomena in metals, anticracks in soils and snows, or planewise collapses in lattice metamaterials, are different manifestations of plastic instabilities characterized by stress softening and strain localization. Several independent constitutive descriptions exist and suffer from similar challenges: experimental difficulties to link local events to global measurements, and computational lack of convergence, spurious localization and mesh sensitivity. This work proposes a minimal field-agnostic constitutive framework where plastic softening is represented by a damage-like internal variable which explicitly separates stable hardening behavior from unstable softening. The resulting formulation admits a variational structure and can leverage regularization tools originally developed by the ductile fracture community. The framework aims at emphasizing similarities within plastic instability phenomena and establishing a bridge with continuum damage mechanics, to open a path towards regularized variational formulations of localized plastic flows.

We propose multi-spin molecules as a viable architecture for fault-tolerant quantum computing. To this aim, we introduce a correction protocol handling both diagonal and off-diagonal errors, typically associated with dephasing and relaxation. The scheme is based on a hybrid encoding which combines dephasing-tolerant units suppressing the leading pure dephasing error into a multi-spin molecule implementing a multi-qubit code for residual off-diagonal errors. Our proposal leverages peculiar properties of molecular spins, i.e. the strong hierarchy between different errors and the possibility to engineer multi-spin molecules at the synthetic level. Moreover, it addresses the important issue of the loss of coherences in anharmonic systems subject to off-diagonal errors, which hampers their correction at the single spin level. Thanks to the huge suppression of dephasing by the first-level code, we numerically demonstrate the potential performance of this strategy even with a limited number of spins per logical unit.

During zirconium carbide oxidation, liberated carbon can remain beneath the oxide or escape as gas, complicating the interpretation of mass measurements. We adapt the small-cell ensemble method using sixteen 140 ps ab initio molecular dynamics trajectories at 873-1273 K under a sustained high oxygen flux with gas removal. The average rates of net mass gain and total carbon transfer into gas or retained chains follow Arrhenius trends. Above 973 K, gas evolution levels off while total carbon transfer increases. The fraction of transferred carbon retained in chains rises from 40 % at 973 K to 66 % at 1273 K. Fits after 40 ps suggest declining carbon transfer rates over time, although not in every trajectory. These results show that carbon partitioning during early oxidation depends on temperature, with increasing temperature above 973 K favouring chain formation over gasification.

We explore the microscopic origin of THz-driven lattice dynamics in methylammonium lead bromide CH$_3$NH$_3$PbBr$_3$ using two-dimensional THz Kerr-effect spectroscopy. The analysis of the experiment enables discrimination between competing nonlinear excitation mechanisms and reveals that the dominant pathway is phonon-mediated rather than purely photonic. In particular, we argue that the commonly observed 1.15~THz Raman-active $A_g$ mode is not excited directly by the THz electric field. Instead, it emerges through cubic anharmonic coupling to an infrared-active phonon at 0.68~THz. Furthermore, a satellite feature at 1.36~THz is identified as a two-phonon Raman response of the same infrared-active mode. The observation of strong quadratic coupling involving the infrared-active phonon suggests an unconventional form of electron-phonon dressing present in lead-halide perovskites.

The symmetry of a physical system given by the 122 magnetic point groups (MPGs) leads to only 21 sets of restrictions on any physical tensors. Those, so called, tenor forms were labeled by letters from A to U by R. R. Birss (Symmetry and Magnetism, North Holland, Amsterdam, 1964). A new concept of property-related point groups (PRPGs) is proposed. It is shown that the 21 PRPGs isomorphic to the 21 non-centrosymmetric crystallographic point groups (CPGs) corresponds to the 21 tensor forms. Therefore instead of a symbols from A to U one can use PRPGs as mathematical objects corresponding to the tenor forms. From the Neumann's principle given multipole component is only allowed in a system when a group describing symmetry of the system is a subgroup of the multipole component symmetry. Each tensor can be expressed in the terms of the multipole degrees of freedom, i.e. it corresponds to a subset of all multipole components allowed by given PRPG. Those relations leads to the algebra of tensor forms, where space of allowed tensor components and space of PRPG operators are somehow dual to each other.

The cell cortex and cell adhesion contribute to the mechanics of epithelial cells and hence tissues. Vertex models of epithelia represent the cell cortex and cell adhesion, but these models mostly ignore the other subcellular structures that compose the cytoplasm surrounded by the cortex. Here, we reveal the mechanical consequences of these structures in a minimal vertex model of an epithelial monolayer, in which the single-cell energy includes a cytoplasmic contribution that represents, e.g., the cost of confinement of cytosolic polymers. Strikingly, our simulations show that the buckling transition of the monolayer under compression becomes discontinuous in an intermediate range of values of the associated cytoplasmic modulus. By asymptotic solution of this buckling problem in the continuum limit of the model, we explain this reentrant behaviour in terms of the tricritical points of a sixth-order Landau theory. Our results thus underline how cell-scale mechanics beyond the cortex and cell adhesion can change emergent, tissue-scale behaviour even qualitatively.

We investigate collective charge excitations in three-dimensional semimetals with dipole-like Berry-curvature (BC) profiles, focusing on vortex nodal-ring semimetals (VNRs) and Hopf semimetals (HSMs). The VNR hosts a continuous ring of dipole-like BC sources generated by its winding pseudospin texture, whereas the HSM hosts an ideal BC dipole. This allows us to examine how distinct realisations of dipole-like BC structure affect collective charge dynamics. While plasmon modes in $\mathcal{PT}$-symmetric nodal-ring semimetals (PTNRs) and their gapped cousins were studied in a companion work, arXiv:2609.35373, here we analyse the density response, Drude weights, dielectric function, and plasmon modes of VNRs and HSMs at low doping within the random-phase approximation. For VNRs, we consider untilted, in-plane tilted, and axially tilted systems. Although VNR and PTNR have identical energy dispersions, their distinct eigenstates introduce a toroidal-angle dependence in the band-overlap factor, yielding additional interband contributions for in-plane wavevectors and weak corrections to the screened plasmon frequencies. The toroidal Fermi surface also produces intrinsically anisotropic bare plasmons. In contrast, HSMs have isotropic bare plasmons, with anisotropy arising only through their interband response. Our results show that collective charge dynamics can distinguish different realisations of dipole-like BC structure and reveal pseudospin information beyond the single-particle dispersion.

We present a numerical study of a blockade Hamiltonian with a local $\mathbb{Z}_2$ symmetry. For such models, the existence of a topologically ordered ground state has been proven rigorously for weak Rabi driving [T. F. Maier et al., PRX Quantum 6, 030340 (2025)]. However, the phase diagram beyond weak driving is still an open question. We perform large-scale infinite-size density matrix renormalization group (iDMRG) simulations on a cylinder and map out the full phase diagram of the model. We find a single continuous phase transition between the topologically ordered phase and a trivial paramagnetic phase, and confirm numerically the stability of the topologically ordered phase up to Rabi drives comparable to the characteristic energy scale of the system. Furthermore, we compute the excitation gaps and show that the charge gap remains open across the phase transition and charges become confined in the trivial phase. On the other hand, the gap in the symmetric sector closes at the transition, consistent with the condensation of flux excitations.

We study the full counting statistics of the integrated current in a one-dimensional hard-rod gas in equilibrium, employing two recently proposed fluctuating hydrodynamic frameworks: (i) Ballistic Macroscopic Fluctuation Theory (BMFT) and (ii) diffusive fluctuating hydrodynamic theory based on correlated Brownian motion approximation of hard-rod quasiparticles (CBFHD). We investigate how the predictions of these two approaches compare with each other and with the underlying microscopic dynamics. We show within BMFT that the current distribution admits a large-deviation form under ballistic scaling, and we derive an explicit expression for the large-deviation function, valid for an arbitrary inhomogeneous initial state factorized in point-particle coordinates. The corresponding current cumulants are also obtained. We subsequently analyze the current statistics within the CBFHD framework, which explicitly incorporates stochastic noise and dissipative terms, and demonstrate that the current distribution likewise obeys a large-deviation principle in this approach. We find that, while BMFT predictions for the first few cumulants and the rate function are in excellent agreement with direct numerical simulations of the microscopic hard-rod dynamics, CBFHD prediction is not. We further verify the predictions of the CBFHD independently using a collection of correlated Brownian motions, which provides an approximate description of the dynamics of hard-rod quasiparticles. Our findings indicate that CBFHD does not accurately capture large-scale current fluctuations in the hard-rod gas, whereas BMFT yields predictions in quantitative agreement with the microscopic dynamics, at least in the context of full counting statistics.

Coercivity-aware machine learning is developed to screen rare-earth-free soft magnetic alloys using Curie temperature and coercivity as coupled design targets. A compiled experimental magnetic-material dataset is evaluated using composition-grouped partitioning to avoid overlap of identical compositions between training and testing, and elemental fractions and composition-weighted elemental descriptors are examined for prediction of the two magnetic properties. Residual-based prediction intervals and distance-to-training filters are then incorporated to screen Fe-Co-Ni-Mn-Al-Si compositions. Composition-grouped evaluation shows lower predictive accuracy than conventional random partitioning, demonstrating the importance of evaluating transfer to previously unseen compositions. Combining weighted elemental descriptors with elemental fractions improves Curie-temperature prediction, whereas the additional descriptors do not improve coercivity prediction, consistent with the strong dependence of coercivity on processing and microstructure. Uncertainty-aware screening substantially narrows the candidate space and identifies Fe-Co-rich compositions for further evaluation. First-principles calculations independently show strong magnetic polarization and magnetovolume effects in representative Fe-Co structures, while finite-temperature atomistic spin simulations place the Fe-Co benchmark systems on high magnetic-ordering-temperature scales. The combined approach provides a computational framework for prioritizing rare-earth-free soft-magnetic chemistries while distinguishing composition-level screening from candidate-specific physical validation.

Topological Deep Learning (TDL) is designed to learn features associated with higher-dimensional simplices including not only nodes but also edges, triangles and so on. However, most TDL approaches, being based on boundary operators and Hodge Laplacians, have the limitation that features and signals cannot be lifted or lowered across more than one dimension per layer. To overcome this limitation, in this work, we propose the adoption of the cup and cap products. Specifically, we formulate the Cup and Cap Topological Neural Network (CCNN), a topological deep learning architecture designed to learn node-based variables (or 0-cochains) by taking into account their many-body interactions (e.g. triangles) present in the data. We validate CCNN by assessing its performance on the TopoBench datasets, revealing its competitiveness with respect to other simplicial complex neural networks.

Here, we report the fabrication and characterization of single crystal diamond films on a two-inch wafer-scale containing three-dimensional layered structures of negatively charged nitrogen-vacancy color centers (NV$^{-}$). The (100)-oriented layered diamond films were grown by chemical vapor deposition (CVD) to create spatially separated regions of enhanced emission associated with NV$^{-}$ centers. Such localized emission enhancement as well as 2D and 3D arrays of spins could enable close-packed architectures for emerging quantum devices, such as data processors, memory cells, and magnetic sensors. A cyclic sequence of CVD growth and oxygen-plasma etching is employed, resulting in the in-situ formation of layered inverted pyramidal structures with flat $\{$111$\}$ sidewalls. These pits are subsequently overgrown by nitrogen-doped diamond to achieve NV$^{-}$-rich facets with a uniform N-V bond arrangement and improved nitrogen incorporation efficiency.

In this work, we investigate a continuum model of two-dimensional electrons interacting via long-range Coulomb forces and subject to a triangular periodic potential at filling factor $\nu=2$. Using neural quantum states based on message-passing neural networks optimized with variational Monte Carlo, we determine the ground-state phase diagram as a function of periodic potential strength and Zeeman field. Although the noninteracting system is expected to form a conventional band insulator, we show that strong correlations can qualitatively reshape the insulating state and, in part of the phase diagram, suppress the band insulator in favor of a correlated metallic phase, with a first-order transition separating the two regimes. Moreover, the metal–insulator transition exhibits a strong dependence on spin polarization: the unpolarized system becomes insulating at substantially weaker periodic potentials through the formation of an $s$-wave molecular insulator, where opposite-spin electrons bind near each potential minimum, whereas the fully polarized system requires a significantly deeper potential and instead forms a symmetry-broken orbital nematic molecular crystal. This spin-dependent molecular transition gives rise to discontinuous magnetization curves, metamagnetic transitions, and several multicritical points in the phase diagram, together with clear signatures in the density profiles, real-space correlation functions, and structure factors. To further elucidate the role of the long-range character of the Coulomb interaction, we also study short-range repulsive interactions, which can be realized with ultracold-atom platforms. We find that the qualitative structure of the many-body phase diagram remains unchanged, demonstrating the robustness of our results across different interaction models.

We study a finite-width Majorana shutter as a local, time-dependent scattering defect and determine which features of its infrared memory are insensitive to the microscopic spatial profile. For a smooth shutter, the zero-frequency scattering matrix is fixed by the integrated coupling, while finite-width corrections vanish in the long-wavelength limit. A time-dependent switch then produces an infrared Bogoliubov kernel whose singular part is controlled by the change in this scattering matrix. We examine the many-body response through three observables. The overlap of the pre- and post-shutter Gaussian vacua exhibits Anderson orthogonality, with an exponent set by the scattering angle. A lattice calculation of the post-quench quasiparticle number resolves its logarithmic infrared growth, reaching the predicted coefficient in the slow-switch test and reproducing the expected dependence on the scattering-angle change. When the entanglement cut passes through the shutter, the entropy follows the effective-central-charge description of a conformal defect, with parameter-free agreement at the percent level, improving for the wider shutter. When the shutter lies inside the interval, its contribution remains a subleading finite-size correction. A local bilinear correlator approaches the expected Majorana power law and shows no stable logarithmic amplitude. These results show that the same low-frequency scattering data control distinct global and spatial observables, while their infrared coefficients are not interchangeable. The remaining limits are also made explicit: the finite-memory correction to the continuum kernel and the controlled continuum limit of large-interval spatial entropy.

We identify an entropy-mediated mechanism underlying the spatiotemporal organization of the chromosome in the bacterial cell Caulobacter crescentus. Effective entropic interactions between replicating DNA segments emerge from their topological modifications of daughter DNA polymers caused by transient ParA-ParB binding. Enthalpic contributions arising from the ParABS system further influence their dynamics. In C. crescentus, chromosome replication and segregation occur concurrently before cell division. The origin of replication oriC of the mother chromosome of C. crescentus is tethered to the old cell pole. Replication generates two daughter oriCs, one of which remains anchored at the old pole. The other oriC is actively transported toward the new pole by the ParABS system of proteins even as replication of the rest of the chain is in progress. How ParABS generates a directed force to transport a daughter oriC to the opposite pole during chromosome replication remains unclear. Furthermore, the two daughter chromosomes get neatly segregated into two halves of the cell. In a bead-spring polymer model of the replicating C. crescentus chromosome, we model transient ParA-ParB contacts that generate DNA loops and an effective entropic repulsion. This repulsion drives chromosome segregation and produces oriC trajectories consistent with experiments, aided by the ParA concentration gradient near the new pole. This minimal framework, incorporating the physics of topologically modified (ToMo) polymers, allows us to quantitatively reproduce the time-dependent spatial organization of different tagged loci and replisomes observed in multiple experiments. Incorporating a minimal model of extrusion also allows us to recover the linear arrangement of the chromosome arms, as is inferred from the characteristic diagonals of Hi-C maps.

The spectral fluctuations in complex quantum systems are modeled in terms of spectra from random matrices. Quantitative agreement with random matrices holds only when the quantum spectrum is a pure sequence, and not a composite spectrum that mixes levels from different symmetry sectors. It was shown earlier that discrete symmetries in composite spectra can be detected using higher-order spacing ratio statistics provided the symmetry sectors are of equal dimensions. The general case is when the symmetry sectors have unequal dimensions, and the symmetries of the Hamiltonian system are unknown or only partially known. In this work, we address how the number of symmetry sectors can be determined from a composite spectrum arising in Hermitian and non-Hermitian settings. A Best Subset Technique is proposed for determining the number of the symmetry sectors by comparing the spectral fluctuations to that of an appropriate random matrix ensemble without requiring de-symmetrization. It is demonstrated using spectra from Gaussian, Wishart and Ginibre ensembles, and also for spectra drawn from many-body quantum systems.

We develop a finite-state geometric framework based on third-order Bargmann invariants for evaluating Chern numbers and characterizing local quantum-state geometry. Using gauge-invariant state overlaps, the framework evaluates the Chern number directly on discretized parameter spaces while retaining local geometric information through the phase-derived density and the complementary amplitude density, as well as signatures associated with changes in topological character. We apply the construction to the Qi–Wu–Zhang, $1/3$- and $1/4$-flux Hofstadter, SSH, and Rice–Mele models, including a rank-$2$ extension for isolated composite subspaces and applications to closed-loop and parameter-space topology. The resulting framework organizes Chern topology and local geometric information directly from finite-state data, providing a compact state-based description without relying on dynamical evolution.

We couple a metal to an uncondensed bose gas with repulsive bose-fermi interactions in two dimensions. Within the random phase approximation, we show that the density fluctuations of the bosons, which mediate the effective fermion-fermion attraction, become long ranged on appropriate tuning of interactions. This leads to parametrically enhanced superconducting temperatures $T_c \propto g$ as opposed to $T_c \propto \exp(-1/g)$ for the BCS case. The dilute bose gas density acts as the primary bottleneck to the enhancement. We discuss the conceptual difficulties of implementing this idea in electron-exciton mixtures.

We consider the $\phi^4$ theory with $\phi(x)\in\mathbb{R}$ in three Euclidean dimensions. For a variety of self-couplings $\hat{\lambda}$, the critical (bare) parameter $\hat{\mu}_{0\mathrm{c}}^2(\hat{\lambda})$ is determined where the lattice-regulated system changes from the symmetric phase to the broken phase. Next, we send the box volume to infinity and switch to a universal scheme; this yields $\hat{\mu}_\mathrm{c}^2(\hat{\lambda})$ for each simulated $\hat{\lambda}$. Finally, a continuum extrapolation gives $f_\mathrm{c}=\lim_{\hat{\lambda}\to0} \hat{\lambda}^2/\hat{\mu}_\mathrm{c}^2(\hat{\lambda})$, and we find $f_\mathrm{c} = 18.808(64)_{\mathrm{stat}}(45)_{\mathrm{sys}} = 18.808(78)_{\mathrm{tot}}$. In addition, $\Delta\langle\phi^2\rangle_\mathrm{c}/\lambda = -0.00303(12)_{\mathrm{stat}}(12)_{\mathrm{sys}} = -0.00303(17)_{\mathrm{tot}}$ is determined in the combined continuum and infinite-volume limit.

In a world fraught with uncertainty, it behooves us to consider the most disastrous possible outcomes, in order that we can best mitigate against them. Often these are extreme risk events – of high consequence, but low probability. Yet, the rarity of such events limits our ability to study them; there is a paucity of past occurrences to draw upon, and sampling such rare events from models is typically costly in time. Here, we introduce an approach for rare-event sampling based on quantum stochastic models. This integrates the memory advantages of quantum stochastic modelling – and its associated efficient means of preparing quantum sample states – with the `speed-ups' of quantum amplitude amplification, to yield simultaneous reductions in spatial and temporal computational complexity compared to classical Monte Carlo-based approaches.

Topological superconductivity has attracted broad interest because of its connection to Majorana fermions and quantum computation. Kagome materials provide a natural setting in which interesting electronic structures, topological surface states, and superconductivity may occur in nearby energy windows. Here we carry out a systematic first-principles search for binary kagome superconducting candidates with topological electronic states across several structural families $A_mB_n$ ($m$:$n$=3:1; 3:2; 1:1). The screening combines formation-energy and phonon-stability filtering, magnetic-ground-state searches, electron-phonon-coupling calculations, and topological electronic-structure analysis. We identify 286 nonmagnetic dynamically stable candidates for electron-phonon-coupling analysis, among which 84 have estimated transition temperatures above 3 K and seven exceed the $\sim 9$ K reference scale of existing ambient-pressure kagome superconductors. In addition, several systems are predicted to host abundant topological surface states near the Fermi level. NbBi is identified as a $\mathbb{Z}_2$ topological metal with clear Dirac-cone topological surface states and a kagome-derived flat band near $E_F$. Ti$_3$Si, with the largest estimated $T_\text{c}=15.2$ K in this dataset, shows nodal-line-derived drumhead surface states and selected nodes that survive spin-orbit coupling near $E_F$. Combining superconductivity with nontrivial topological electronic structures, the binary kagome compounds predicted here represent compact and chemically tunable candidate platforms for topological superconductivity and for exploring kagome-related quantum phenomena.

The search for novel materials capable of robust spin-current generation remains an active area of research. Here, we investigate the intrinsic spin Hall and spin Nernst effects in Co- and Rh-based skutterudites and explore their enhancement through heavy-metal substitution and site-selective doping. Using first-principles calculations and Wannier-based tight-binding models, we analyze the spin Berry curvature and spin-transport responses of pristine MX$_3$, where M = Co, Rh and X = As, Sb, as well as chemically modified systems. Despite sizable momentum-resolved spin Berry curvature, the pristine compounds exhibit relatively small net spin Hall responses due to substantial cancellation across the Brillouin zone. Isoelectronic Ir and Bi substitution at 8$c$ Wycoff M site produces little enhancement near the E$_F$, whereas non-isoelectronic Pt substitution yields a relatively better response. Most interestingly, the incorporation of Pt at the interstitial $2a$ Wycoff site of RhAs$_3$ nearly doubles the spin Hall conductivity to $\sim400~(\hbar/e)(\Omega,\mathrm{cm})^{-1}$ near the E$_F$ when compared to Pt substitution at 8$c$ position. At 300 K, the same interstitially filled system exhibits a spin Nernst conductivity of $\sim1.46~(\hbar/e),\mathrm{A,m^{-1}K^{-1}}$ at the E$_F$, nearly an order of magnitude larger than that of $M$-site Pt substitution. The enhanced responses arise from Pt $5d$ states, strong spin-orbit coupling, and avoided crossings that generate pronounced spin-Berry-curvature hot spots. These results demonstrate that site-selective chemical engineering can effectively overcome momentum-space cancellation resulting in enhanced spin Hall and spin Nernst responses in skutterudites. Our results provide a possible route towards robust spin-current generation in this class of materials.

Collective modes of the superconducting condensate encode fundamental information on the pairing interaction, yet their direct detection remains experimentally challenging. In multiband superconductors, the Leggett mode, i.e., a coherent oscillation of the relative phase between two condensates, is Raman-active and couples to light only nonlinearly in ordinary situations. Here we show theoretically that terahertz two-dimensional coherent spectroscopy (2DCS) provides a direct fingerprint of the Leggett mode (with frequency $\omega_L$) through sideband emission at the detection frequency $\omega_t = \omega_L\pm\Omega$ ($\Omega$ is the central frequency of the incident pulses) in the nonlinear 2D spectrum. The key insight is that the finite duration of the THz pulses is the physical mechanism that makes the mode accessible: the broad spectral content of a finite pulse provides the nonlinear frequency combinations needed to resonantly excite the mode at {\omega}L without any prior knowledge of its value or tuning of external parameters. We demonstrate robustness of this signature against temperature and quasiparticle relaxation, and show that sweeping $\Omega$ allows unambiguous identification of the Leggett mode.

Magnetic hyperthermia, based on the conversion of the magnetic energy of magnetic nanoparticles (MNP) under an alternating external field into heat, presents a great interest, especially because of important applications such as promising advances in cancer treatment. The underlying frequency-dependent response of the MNP assembly under the excitation field depends on the first hand on the individual properties of the MNP such as their size, shape and magnetocrystalline anisotropy and on the other hand on collective properties generated by interactions between MNP. Due to the long-range dipolar component of the latter, the first consequence is the so-called demagnetizing effects, making the response dependent on the external sample shape. This is the reason for studying the properties of MNP in assemblies of anisotropic external shapes such as films, chains, or elongated aggregates. In the present work, using a recently developed Time Quantified Monte Carlo (TQMC) framework for dynamic simulations, we focus more precisely on the importance of the local structure in such anisotropic aggregates to the dipolar interactions contribution of the response to the external field. Here the local structure is understood as both the location of the nanoparticles and the distribution of their easy axes. We show that the latter must be determined in a self-consistent way starting with the equilibrium structure of a ferrofluid modeled as the dipolar hard sphere fluid.

Classical reactive molecular dynamics of boron- and lithium-conditioned tungsten surfaces show that the order in which boron and oxygen are introduced - not the boron inventory - controls surface chemistry. On a thin engineered tungsten oxide, boron captures 81% of oxygen and consumes the oxide; on an engineered ~2 nm mixed WO3/WO2 film, boron captures only 20% and leaves 52% of reaction-zone tungsten in WO3-like coordination; and in a co-deposited W-B substrate later exposed to oxygen, boron captures only 28% despite a tenfold larger inventory. Adding lithium leaves the oxide-first cases unchanged but transforms the co-deposited case, where lithium becomes the dominant oxygen captor (58%) and a lithium-borate-glass-like network form. We outline the expected, divergent responses of the boron-only and boron-plus-lithium materials to deuterium irradiation.

The landscape of topological insulators has expanded beyond its traditional domain of periodic lattices with short-range hopping. Related studies have explored topological phenomena under non-Euclidean geometries, disordered structures, and long-range hopping, progressively narrowing the gap between topological phases of matter and complex networks. Here we demonstrate that genuine complex networks, far beyond periodic lattices and their conventional variants, can themselves host topological insulating phases. By developing a nonconflicting design framework for multiple topological objectives, we realize topological insulators in high-degree Hofstadter lattices and across regular, small-world, and random networks. This generalization uncovers distinct network-specific features, including an expanded range of attainable topological characteristics, a degree-dependent transition from Hofstadter-type to Haldane-type Chern insulators, and, most notably, the superior robustness and reconfigurability of small-world topological insulators. Our graph-theoretic framework establishes network complexity as a resource for realizing high-capacity and reconfigurable topological insulators.

Universal rheological properties of unentangled polymer melts are investigated through the stretch-orientation decomposition of polymer dynamics. By externalizing stretch from the explicit state of each Rouse mode, we construct a constitutive model with orientational kinetics that preserves the Rouse relaxation spectrum. The resulting model yields the observed steady-shear scalings of the shear viscosity and first normal-stress coefficient, predicts a finite second normal-stress coefficient, and approximately reproduces the Cox-Merz and Gleissle-Osaki rules. The derived steady-oscillatory shear correspondence further identifies an elastic contribution, associated with the first normal stress difference, that is absent from the conventional Cox-Merz rule.