Papers

Fully suspended thin films can decouple substrate effects and provide additional tuning degrees of freedom compared with their substrate-supported counterparts, making them unique platforms for next-generation thin film devices. Here we report one-step, transfer-free and substrate-free fabrication of centimeter-scale ultrathin fully suspended metal and metal oxide film structures via liquid metal capillary forming. We show that, analogous to soap film formation, the instantaneously developed few-nanometer-thick native surface oxide can laminate various liquid metals into micrometer-thick metallic films. Surprisingly, the surfactant-like metal oxide bilayer can survive dewetting-induced liquid metal drainage, forming suspended two-dimensional films featuring an enormous lateral size-to-thickness ratio on the order of 10^7. We further demonstrate rapid prototyping of metallic minimal-surface thin-walled structures and ultra-sensitive acoustic wave detection with these suspended thin film platforms.

Competing magnetic interactions and frustration-induced quantum fluctuations in spatially anisotropic low-dimensional magnets often give rise to exotic magnetic phenomena, including field-induced phases. Here, we present crystal structure, magnetic susceptibility, specific heat, and electron spin resonance (ESR) measurements on polycrystalline Y$2$CuGe$4$O${12}$, supported by density functional theory (DFT) calculations. In this compound, the Cu$^{2+}$ ions form a distorted triangular lattice with competing intraplanar ferromagnetic ($J_1 \approx 0.138$ K and $J_2 \approx 0.01$ K) and antiferromagnetic ($J_3 \approx -3.22$ K) exchange interactions, together with a weaker interplanar antiferromagnetic coupling ($J_4 \approx -1.56$ K). These interactions account for the small Curie–Weiss temperature, $\theta{\rm CW}=-1.8$ K. Despite the dominant antiferromagnetic interactions, no signature of long-range magnetic ordering is observed down to 0.4 K. Instead, broad maxima in both the magnetic susceptibility and magnetic specific heat reveal the development of short-range spin correlations, further supported by the critical ESR linewidth broadening characteristic of low-dimensional frustrated magnets. Application of an external magnetic field progressively suppresses the broad maximum in the magnetic specific heat, reflecting competition between the Zeeman and exchange energy scales, and drives the system into a field-polarized state above the saturation field, $\mu_0H_{\rm s}=2.6$ T. In this regime, the magnetic specific heat exhibits an exponential temperature dependence, consistent with gapped magnon excitations. These results establish Y$_2$CuGe$4$O${12}$ as a rare distorted triangular-lattice magnet in which further-neighbor exchange interactions dominate the magnetic behavior, providing a promising platform for exploring frustration-driven quantum phenomena.

Phonons hold promise for storing and transferring quantum information, including in mechanically-mediated quantum interconnects between superconducting qubits and light. Phononic crystal cavities confine gigahertz sound to micron-scale volumes well matched to near-infrared light. So far, these devices have typically been suspended to suppress phononic radiation loss into the substrate, but suspension limits thermal anchoring leading to excess noise. Release-free phononic crystals have emerged as a way to address this challenge – but had yet to be shown compatible with strong electromechanical interactions. Here, we demonstrate a release-free phononic crystal cavity strongly coupled to a high-impedance microwave resonator, with an electromechanical coupling rate $g_\mathrm{em}/(2\pi) \approx 30\,\text{MHz}$ that exceeds both the mechanical and microwave loss rates, leading to a cooperativity up to $\mathcal{C} \approx 180$ on resonance. In addition, our lithium niobate phononic crystals reach quality factors above $10^4$ at millikelvin temperature on both silicon and sapphire substrates. Our results establish release-free phononic crystals as compact, scalable interfaces between microwaves and gigahertz sound for emerging sensing, communication, and computing systems.

Quantum integrability is a cornerstone of the exact theory of interacting quantum spin chains. In its standard formulation, however, one starts from R-matrices satisfying the Yang–Baxter equation, rather than from the Hamiltonian itself. It has therefore remained unclear how Yang–Baxter solvability can be characterized directly at the Hamiltonian level, and how it is related to the existence of local conservation laws. Here we prove that, in a broad standard setting, the Reshetikhin condition is not only necessary but also sufficient for Yang–Baxter integrability, thereby reducing the hidden algebraic structure of integrability to a Hamiltonian-level conservation law. Since the Reshetikhin condition is equivalent to conservation of the total energy current, this Hamiltonian-level criterion is also experimentally accessible. This result establishes a quantum counterpart of the Liouville–Arnold theorem for isotropic spin chains, stating that Yang–Baxter solvability is equivalent to an infinite hierarchy of local conserved quantities. Our result also simplifies substantially the search for integrable spin chains by replacing the search for R-matrices with a direct criterion on local Hamiltonians.

Self-assembly of constituents determines structure formation in the microscopic world. Attractive forces can assemble active particles into colloidal machines, but they do not fix the particles' orientations, which limits control over the machine's function. We demonstrate that non-reciprocal turn-towards torques not only assemble active particles into clusters, without requiring attractive forces, but also link particle orientations to the cluster configuration. Symmetry then dictates whether the cluster is static, rotates, or translates. In small systems, the particle number uniquely determines the stable configuration and function. In larger systems, there are multiple stable configurations with distinct functions, and tuning the torque strength allows us to bias towards the desired function, such as a run-and-tumble motion. Because the interactions driving assembly can be switched on and off, the clusters self-assemble when needed. For such a "just-in-time" self-assembly to be practical, fast assembly is necessary. We show that stochastic resetting, implemented by briefly turning off propulsion and torque, significantly speeds up self-assembly by avoiding slow pathways. Together, our findings demonstrate that non-reciprocal torques can rapidly assemble active particles into colloidal micromachines with controllable function.

Hydrodynamics governs diverse collective phenomena in nature, from the expansion of a quarkgluon plasma to viscous electron flow in quantum materials. In strongly interacting hydrodynamic fluids, the transport of spin remains poorly understood. Here, we investigate spin transport in the hydrodynamic regime of a spin-imbalanced unitary Fermi gas confined in a uniform optical box. By quenching a spatially periodic optical potential that modulates both the density and spin polarization, we observe the relaxation of the many-body system, which determines both the spin diffusivity and the spin Seebeck/Peltier coefficients in a homogeneous quantum gas. Our measurements provide parameter-free benchmarks for microscopic theories and establish an ultracold atom platform for studying spin caloritronics in strongly correlated matter.

Recent development in the field of altermagnetism, and increased demand for the search of applications of anomalous hall effect have ushered in a new era for novel quantum phases in materials. Quantum materials previously anticipated to be scientifically predictable have unfolded novel properties that brought them into the spotlight. These manifestations have led us to rethink our understanding of existing classification of magnetic materials and preexisting notions about anomalous hall effect in the light of topologically nontrivial phases of matter. One such recent de- velopment lies in the novel class of alter-magnetic materials with prospect for quantum computing. In this article, we delineate the spin and orbital resolved electronic spectrum, mode-decomposed phonon dispersion relations, geometrical berry curvature and topological surface states and their implications on anomalous Hall conductivity in the promising altermagnetic compound CrSb. We further utilize first principles calculations coupled with computationally efficient maximally localized wannier states of numerous magnetic configurations of the altermagnet to simulate the effect of external fields and elucidate the fact that the linear behaviour of anomalous hall conductivity with magnetization does not necessarily hold true for all magnetic classes, such as altermagnets.

Condensates formed by oppositely charged intrinsically disordered proteins provide model systems for understanding how transient electrostatic interactions govern structure and dynamics in biomolecular assemblies. Here we investigate a nearly charge-neutral condensate composed of 50 Prothymosin alpha (ProTalpha) and 40 Histone H1 molecules using a single-bead-per-residue coarse-grained model combining the HPS hydropathy model for disordered regions with a Go model for the globular domain of Histone H1 under NPT conditions at pressures from 2 to 12 bar. We find that chain dimensions, including the radius of gyration (Rg), end-to-end distance (Ree), and their ratio R, are insensitive to pressure, indicating that chain conformations remain largely unchanged over the pressure range studied. Histone H1 exhibits systematically larger values of R than ProTalpha because of its globular-core plus disordered-tail architecture. Translational diffusion coefficients decrease monotonically with pressure, from approximately 0.22 to 0.06 nm^2/ns, with substantial chain-to-chain heterogeneity comparable to the mean diffusion coefficient. Chain relaxation follows a stretched exponential with beta less than 1 that decreases with pressure. ProTalpha relaxation times of approximately 12 to 40 ns obey Rouse scaling, whereas Histone H1 deviates because of the internal constraint imposed by its globular domain. ProTalpha-Histone H1 contact lifetimes of approximately 0.43 to 0.56 ns are much shorter than the Rouse relaxation time, placing the system firmly in the fast-exchange regime where transient electrostatic contacts renormalize chain friction rather than acting as permanent cross-links, consistent with the moderate stretching exponent beta of approximately 0.55 to 0.70 observed across all pressures.

Quantum mechanics constrains conjugate observables from being simultaneously measurable with arbitrary precision. In a Josephson junction, these are the transferred electric charge and the quantum-mechanical phase difference between the superconducting domains. Which of them fluctuates determines the supercurrent: a dissipative trickle of single Cooper pairs in one limit, a coherent dissipationless flow in the other. Bridging both regimes in one device remained elusive because the Josephson and charging energies are fixed at fabrication. Here, we use the tunable tunnel junction of a scanning tunneling microscope at millikelvin temperature to vary their ratio continuously over many orders of magnitude. In this way, we monitor the smooth transition between incoherent and coherent Cooper pair flow in a single junction, revealing the quantum-to-classical transition in a controlled way.

Advancing the understanding of electron-electron interactions in one-dimensional systems remains one of the central challenges in low-dimensional physics, especially for Coulomb-coupled Tomonaga-Luttinger liquids. Notably, the difficulty of reliably extracting one-dimensional system parameters, combined with the presence of disorder, has hindered the interpretation of 1D Coulomb drag experiments. Here, we present a self-consistent experimental determination of the relative Luttinger liquid interaction parameters through 1D Coulomb drag measurements, and achieve quantitative agreement with theoretical predictions. Utilizing vertically coupled GaAs-AlGaAs quantum wires, we fully characterize the one-dimensional parameters through magnetic depopulation. Coulomb drag exhibits a systematic evolution with magnetic field, reflecting the successive depopulation of 1D subbands and the suppression of disorder effects. Two distinct temperature regimes are identified, marking the boundary between momentum-resolved and disordered-averaged Coulomb drag. The observed scaling, peak broadening, and nonlinear current-voltage characteristics establish a unified and quantitative framework for probing electron-electron interactions in 1D systems.

We study pairing of attractively interacting fermions confined to a box-shaped trap. In contrast to the infinite translationally-invariant case, where the local pairing order is spatially uniform and undergoes the Bose-Einstein Condensate to Bardeen-Cooper-Schrieffer (BEC-BCS) crossover as interactions are varied, in this case the local pairing is expected to vary rapidly near the edge of the box. We address this problem in the limit of a semi-infinite superfluid, finding that the nature of the edge pairing depends sensitively on the coupling. The local pairing exhibits Friedel-like oscillations in the weak coupling BCS regime that are suppressed with increasing coupling strength towards the BEC regime.

The proposal is to probe Majorana modes in the system when its parameters are tuned to bring it into a disentangled ground state, which occur on the parametric curves known as disorder lines (DL). In such state certain correlation functions do not depend on separation. The exact results are presented for the XY spin chain in transverse field, also called the Kitaev chain in the Majorana representation. The single Majorana modes are shown to be localized near the ends of the chain, as in the states off the DL, while the disentangled $n$-particle Majorana modes ($n \geq 2$) penetrate into the bulk without attenuation. The predicted bulk-edge effects can be detected in the specially engineered optical chains and lattices.

We propose a method to realize stable, tunable two-component quantum mixtures of ultracold polar molecules. First, we show that a pair of polar molecules in two distinct rovibrational states exhibits a repulsive interaction, thereby leading to collisional shielding without requiring any external field. We refer to this as "vibrational shielding". This intercomponent interaction is tunable by an external static electric or a microwave field, with the latter stabilizing both inter- and intracomponent interactions in a two-component bulk mixture. Additionally, we show that two microwave fields can independently tune the interactions of the individual components. Our findings thus open the door to the experimental realization of tunable quantum mixtures using polar molecules, analogous to tunable magnetic Feshbach resonances in two-component atomic quantum gases.

A recently derived nonlinear velocity theory of extreme type-II superconductors is shown to possess an exactly solvable one-dimensional sector. Its solutions include nonlinear Meissner states exhibiting universal tails, vortex sheets, and periodic laminar structures. The thermodynamic critical field emerges from a marginal Meissner profile equivalent to the normal-superconducting boundary and may be viewed as a half-soliton. The vortex sheet is a soliton characterized by a discontinuity of the velocity field, a continuous and localized magnetic field and vanishing superconducting density at its center, and may be interpreted as the coarse-grained limit of a dense row of Abrikosov vortices. Periodic solutions describe laminar states that may be interpreted as coarse-grained rectangular vortex lattices.

Superselective multivalent binding enables sharp receptor-density discrimination in targeting and sensing, but what its logarithmic response measures microscopically remains unclear. Here, we derive an exact response decomposition of the selectivity into receptor-state reweighting and a direct occupation response. In the dilute quenched Poisson limit, the direct term vanishes and selectivity is exactly the mean receptor excess beneath bound particles, which can be measured at a single density from a sufficiently large co-registered receptor-particle image. Beyond Poisson statistics, the excess is normalized by the Fano factor for a linear count response, while changes in distribution shape require the full count-resolved response. Lattice simulations verify these relations across distinct receptor statistics, while off-lattice simulations show that particle crowding enters through the direct term. These results establish a fluctuation-response framework linking multivalent selectivity to the local receptor fluctuations preferentially sampled by adsorption.

Restricted path integral Monte Carlo (RPIMC) sidesteps the fluctuating Fermion sign problem by confining paths within nodal regions of a trial density matrix, thereby recovering polynomial scaling. However, this nodal surface must be provided from elsewhere; unless it is exact, it introduces a fixed-node energy error. Here we introduce Spindrift, a Variational Density Matrix approach that learns the many-body Fermionic density matrix from a regularised Bloch residual, evaluated on samples drawn by a restricted Worm algorithm. Motivated by the `purity' of quantum statistical mechanics at high temperature (where kinetic energy dominates), we train the density matrix along an imaginary-time (descending temperature) curriculum from an exact infinite-temperature heat-kernel starting point, learning the condensation of quantum correlations as temperature drops, through successive corrections to the previous reference. We parametrise our model with a permutation-equivariant continuous normalising flow to generate quasi-particle backflow trajectories, modulated by a symmetric Jastrow factor. This architecture guarantees exact Fermionic antisymmetry and spatial symmetry throughout training. Simulating $N=3$ interacting Fermions in a two-dimensional harmonic trap, we demonstrate stable curriculum training. The learnt velocity field smoothly deforms the nodal structure away from the free-particle reference. Open-Worm G-sector trapping provides a natural diagnostic for nodal accuracy. Spindrift systematically lowers the restricted energy relative to the free-particle reference across all temperatures and successfully reproduces the benchmark energy at $\beta=1$, establishing a stable, physics-informed framework for finite-temperature quantum Monte Carlo where the nodal structure is learnt self-consistently.

We use first-principles calculations and multipole analyses to demonstrate the relationship between ferroaxiality and chirality in the prototypical ferroaxial material K2Zr(PO4)2. Using the atomic-site electric toroidal monopole as a measure of electronic chirality in real space, we show that, while the paraxial phase of K2Zr(PO4)2 is non-chiral, the ferroaxial phase is antiferro-chiral. By applying an electric field, we induce a ferri-chiral state with net electronic chirality which is opposite for opposite underlying ferroaxial domains and can be tuned by the direction and strength of the electric field. Associated with the real-space induced chirality, we find a distinct response in momentum space, with induced non-zero components in the Berry curvature dipole tensor that switch sign between opposite ferri-chiral domains. Our findings therefore reveal hidden chirality in ferroaxial materials in both real and momentum space.

Exponential Hopfield networks store a number of patterns that grows exponentially with the number of neurons, and in their classical formulation they are auto-associative: they complete a corrupted copy of a memory into the memory itself. Many of the tasks one wants such a network to perform are instead hetero-associative, mapping a cue to a different target. We introduce and analyse an exponential neural network of $L$ layers of $N$ binary neurons, each layer carrying its own dataset, whose energy is an exponential of the product of the per-layer Mattis overlaps, so that it is minimised precisely when every layer retrieves the pattern of the same index; the stored association must be a surjective function of the cue, and we show why nothing else can be stored at all. A cavity/signal-to-noise analysis, made exact at leading order by a large-deviation evaluation of the noise, shows that the aligned hetero-associative state is a fixed point of the zero-temperature dynamics up to a number of stored patterns $P_c\sim e^{N\rho_L}$, exponential in the layer size, with an explicit rate $\rho_L$ that grows like $L\log 2$; enlarging the basins of attraction lowers the rate but never destroys its exponential character. Comparing the theory with structured data we find that the exponential capacity and the predicted basins survive correlated, many-to-one patterns: the network is a near-perfect content-addressable memory. The same closed forms describe, without refitting, a synthetic manifold, real T-cell-receptor/epitope triples and natural-language intent data, so the mechanism is domain-universal. Generalisation to unseen cues, though significantly above chance, stays below memorisation, and it is the geometry of the encoding, rather than the data domain, that sets how far above chance it reaches. In this family, exponential storage and strong generalisation are distinct capabilities.

The Poisson-bracket (PB) formalism is widely used to derive dynamics of coarse-grained (CG) fields to capture large-scale physics, extending the role of PBs in classical particle mechanics to macroscopic fields. It has been applied to fluctuations in critical phenomena, hydrodynamics of liquid crystals, liquid crystal elastomers, tissues, and the emergence of odd viscosity from spinning particles. The PB formalism can be formulated in either the Lagrangian framework, using reference space, or the Eulerian framework, using real space. Conventionally, the Lagrangian formulation is used for elastic solids, and the Eulerian one for fluids. However, growing interest in Eulerian descriptions of solids has emerged for phenomena naturally defined in real space, such as viscoelastic responses, moving interfaces, and field-induced structural changes in particles. Here we develop a systematic formulation for applying the Eulerian PB formalism to elastic systems with potentials typically written in Lagrangian space, and clarify its consistency with the Lagrangian counterpart. We show that the Eulerian formulation generates additional nonlinearities absent in the Lagrangian framework. Such nonlinearities originate from CG volume changes under coordinate transformation and from particle flow across neighboring CG volumes. They must be retained when nonlinear effects are important. To illustrate, we study chiral active solids of finite-sized particles, where active torques drive internal particle rotations and generate geometric nonlinearities. These nonlinearities give rise to the odd elastic modulus, which non-reciprocally couples two different shear modes in stress-strain response. By recovering this modulus directly from the Eulerian PB formalism, we demonstrate its ability to capture emergent nonlinear elastic behavior in driven active solids, whose stresses are naturally measured in real space.

High-entropy perovskite oxides (HEPOs) represent a chemically complex class of materials with promising functional properties, yet their vast compositional space and, chemical/structural disorder pose significant challenge for accurate property prediction. Graph neural networks (GNNs) enable rapid exploration of materials space but are often limited by the availability of representative training data. Here, we investigate ordered-to-disordered transfer learning using GNNs for formation-energy and HOMO-LUMO gap prediction in HEPOs by transferring knowledge learned from chemically ordered perovskites. Four representative GNN models, including CGCNN, GATGNN, ALIGNN and M3GNet are evaluated to understand the role of structural representations, spanning pairwise two-body and angular three-body interactions in transfer performance. We find strong property-dependent transfer behavior: formation-energy prediction transfers effectively to disordered HEPOs, whereas HOMO-LUMO gap prediction shows limited transferability due to its sensitivity to local chemical environments. Incorporating a small HEPO-specific training dataset substantially improves HOMO-LUMO gap prediction. Representation-level analysis using UMAP further highlights the importance of encoding three-body geometric information such as in ALIGNN for capturing complex structure-property relationships and improving transferability.

We present a vectorial phase-only framework for the gradient-based optimization of computer-generated holograms. Our approach addresses a critical limitation in high numerical aperture (NA) optical systems, where standard scalar approximations often experience significant fidelity degradation. We highlight the limitations of scalar diffraction models (Fraunhofer and Debye) at high NA for representative classes of target intensities, namely tweezer arrays and extended flat-top profiles. Using a differentiable Richards-Wolf forward model, we numerically demonstrate stable algorithmic convergence and the generation of highly uniform intensity profiles in the deep non-paraxial regime. At NA=0.9, Richards-Wolf (RW) optimization reaches flat-top and tweezer uniformities of 99.97 % and 99.98 %, respectively, with a mean tweezer ellipticity of $\varepsilon=$1.007, while scalar forward models show target-dependent degradation in plateau fidelity or focal geometry. Furthermore, because the RW model returns the full vectorial field, the same framework can optimize objectives that depend on local polarization. We demonstrate this for a polarization-sensitive optical-dipole-potential target, where direct RW-potential optimization reduces the mean normalized residual by more than an order of magnitude when including vector and tensor light-shift terms.

Strong light-matter coupling gives rise to polaritons through coherent and periodic energy exchange between electromagnetic cavity fields and material excitations. While this interaction is typically inferred from spectral mode splitting, its dynamics remain largely unexplored. Here, using phase-resolved terahertz time-domain spectroscopy, we observe Rabi oscillations of Landau polaritons formed by coupling the cyclotron resonance in a GaAs/Al$_{0.36}$Ga$_{0.64}$As two-dimensional electron gas with Fabry-Perot cavity modes. By employing cross-polarized spectroscopy and magnetic-field differential, we resolve the temporal beating of the cyclotron resonance oscillations. Remarkably, we find that the Rabi oscillations do not start immediately after excitation of the cyclotron resonance, but after a delay corresponding to one cavity round-trip time. This demonstrates that the strong-coupling regime sets up only after the formation of the cavity mode field. Our results provide direct insight into the dynamics of hybrid light-matter states in the THz regime.

We present a theoretical study of orbital-induced topological phase transitions in a two-dimensional lattice model with staggered potential $(\Delta)$ and orbital coupling $(\lambda)$ competing with the hopping strength. By tuning these parameters, two gap-closing mechanisms emerge: valley closure at $\mathbf{K}$ and $\mathbf{K'}$ for $\lambda=\pm\Delta$, and a $\mathbf{\Gamma}$-point closure at $\lambda=\pm\sqrt{\Delta^2+9t_0^{2}}$. Their interplay defines a topological window in which the Berry curvature localizes near a single valley, yielding a quantized anomalous Hall conductivity ($\sigma_{xy}=e^{2}/h$) and Chern number ($C=1$). These results demonstrate orbital-driven Chern insulating behavior without spin-orbit coupling. The resulting phase diagram captures the transition from trivial to topological phases and suggests practical routes for orbital engineering in tunable lattice systems.

Soft microgels are widely used as deformable building blocks for two-dimensional assemblies, yet solid substrates are often treated as passive supports after interfacial deposition. Here, we show that substrate wettability mechanically preconditions soft microgels before drying. Using in-liquid force-volume atomic force microscopy, we find that the same microgels adopt markedly different hydrated shapes and stiffness profiles depending on substrate contact angle: hydrophobic substrates induce spreading, flattening, and internal stiffening, whereas hydrophilic substrates preserve taller, softer microgels with smaller contact areas. These single-microgel states can explain how Langmuir-Blodgett-deposited monolayers respond during drying. On hydrophilic substrates, the observed assemblies are consistent with soft and weakly immobilized microgels rearranging under immersion-capillary forces, producing distinct corona-corona and core-core contact states and an apparent isostructural transition. On hydrophobic substrates, the flattened and stiffened microgels are more strongly immobilized, likely suppressing capillary-driven rearrangements and largely preserving the transferred interfacial assembly structure. These findings establish substrate-controlled microgel mechanics as the missing link between interfacial self-assembly and the final structures observed after transfer and drying.

Vortex clustering is commonly associated with conservative two-dimensional quantum-fluid dynamics. Therefore, particle loss is mainly expected to limit clustering by shortening the time available for vortex correlations to develop. Here we show instead that particle loss can enhance transient vortex clustering beyond the conservative evolution. We numerically study freely decaying, confined two-dimensional condensates initialized with random distributions of vortices and antivortices, and find a pronounced nonmonotonic dependence of the maximum clustering on particle lifetime. The enhancement is strongest at intermediate particle-loss rates, where loss-induced background rarefaction and incompressible kinetic energy relaxation occur on comparable timescales. Our results identify a finite dynamical window, selected by linear particle loss, in which a confined compressible quantum fluid develops stronger same-sign vortex correlations than in the conservative limit.

The rare earth nitrides are the only series of intrinsic ferromagnetic semiconductors where the interplay of spin and unquenched orbital angular momentum provides access to a range of magnetic behaviour. Furthermore, the magnetic properties can be finely tuned through the combination of multiple lanthanide ions in the nitride. Here we present a combined computational and experimental study on the electronic and magnetic properties of Gd$_x$Sm$_{1-x}$N and discuss the effect of cation substitution on the internal exchange field and band structure. We find that as the coercive field of Gd$_x$Sm$_{1-x}$N changes over orders of magnitude via cation substitution the internal exchange field changes by $\sim$20%. Control of these material properties is vital in the field of superconducting spintronics. Finally, motivated by an enhanced concentration of nitrogen vacancies in films with higher Sm content, we investigate computationally the formation of nitrogen vacancy defects in Gd$_x$Sm$_{1-x}$N finding that the formation energy is significantly reduced for vacancy sites adjacent to Sm ions rather than Gd ions.

We analyze the time evolution of the nearest-neighbour tight-binding chain in the presence of a single onsite defect. Such a defect was shown to generate non-trivial transport behavior recently in the article Acharya et al J. Stat. Mech. (2026) 043102. The authors have used a defect technique inspired by classical random walk methods to obtain exact analytical expressions for the occupation probability and subsequently the mean and mean-squared displacement (MSD). Here we derive the same results using a spectral decomposition approach. Starting from the secular equation, we obtain the self-consistency condition for the eigenvalues and construct the corresponding normalized eigenvectors. This approach naturally separates the Hilbert space into dark subspace, whose states have zero amplitude at the defect site and remain unaffected, and bright subspaces, whose states get modified because of the defect. Using this eigenvalue decomposition, we provide a spectral origin of non-monotonicity in the MSD. Numerical calculations for finite chains show that the analytically estimated critical defect strength is in excellent agreement with the defect strength that minimizes the MSD.

The in-plane anomalous Hall effect (IPAHE), driven by an in-plane net magnetization or an applied magnetic field, challenges the conventional anomalous Hall paradigm. Despite growing interest, a unified symmetry principle governing these phenomena has remained elusive. Here, we establish a comprehensive symmetry framework that bridges the spin space group, which dictates the magnetic geometry, with the magnetic space group, which governs the anomalous Hall response. We show that spontaneous IPAHE can emerge in ferromagnets when spin-orbit-coupling-induced spin-group symmetry breaking permits additional net magnetization directions. For field-induced IPAHE, we analyze how an applied magnetic field reduces the symmetries of all 122 magnetic point groups and identify 54 groups that support IPAHE. Our framework naturally predicts IPAHE in a broad class of unconventional magnets, including altermagnets and odd-parity magnets. In particular, symmetry analysis reveals characteristic one-, two-, or three-fold angular harmonics of the Hall conductance under an in-plane rotating field, providing a symmetry-resolved fingerprint for unconventional magnetism. Using this framework, we screen the MAGNDATA database and identify candidate materials supporting spontaneous or field-induced IPAHE, encompassing ferromagnets, antiferromagnets, and unconventional magnets. Finally, we validate the symmetry predictions through first-principles calculations for two representative materials.

The navigation time and optimal search strategies deriving from random dynamical processes on binary graphs have been extensively explored and analyzed, being of prominent interest in the network science field. In this work, we study an extension of these topological measures for simplicial complexes: a specific type of geometric and algebraic structures that encapsulates higher-order interactions. Here, the explorability analysis of simplicial complexes has been conducted in terms of the mean first passage times between nodes, i.e. the 0th-order simplices, with the inclusion of a long-range stochastic teleportation term modulated with respect to the local random walk hopping across the various dimensions. We also provide a perturbative approximation scheme recovering the modulation parameter between pure random walk and teleportation mode (for higher-order setting) acting as the expansion parameter.

Physical systems can process information through their natural dynamics, offering alternatives to conventional digital computing. Reservoir computing offers a basic framework by using a nonlinear substrate to map inputs into rich dynamical states read out by a simple linear layer. Active matter substrates are striking examples; they continuously consume energy and produce entropy. Theoretically, entropy production (EP) can describe the irreversibility and distance from equilibrium. But it remains unclear whether it can track computational capabilities. We address this conceptual gap by analyzing a driven swarm reservoir model. The system EP is computed from phase-space contraction and the bath EP from heat flow, separately, and put in direct association to prediction performance on a Lorenz-63 task. Via force parameter scans, we show that dynamical regimes with the strongest response to a driver as well as dissipation coincide with peak performance. Therein, the dynamical discrepancy between innate (minimal dissipation) and driven transferred heat (maximal dissipation) is sharpest. Generally, driver work and relative differences of driven and undriven EP closely mirror the performance landscape. The system EP, derived from a generalized Liouville-equation estimator, and heat flow provide complementary diagnostics and metrics, which are most robust in the best-performing regime. These results extend prior expectations that dissipation matters for computation by identifying when and how it becomes predictive. They also relate inference power to innate dynamics, pointing to generic principles for physical computing and where EP offers a screening metric for reservoirs and other base substrates.