Papers

This work presents the demonstration of a superconducting niobium nitride (NbN) nanowire surface acoustic wave transducer, enabling a cryogenic acoustic delay line in scandium aluminum nitride (ScAlN) on silicon carbide (SiC). The superconducting nanowire slows the effective electromagnetic phase velocity along the acoustic wave propagation axis to match that of the surface acoustic wave, such that the co-propagating electrical signal continuously and coherently drives the acoustic wave along the length of the wire. The operating principle is validated through coupled full-wave electromagnetic and piezoelectric finite element method simulations and then experimentally confirmed through demonstration of a 500 {\mu}m delay line exhibiting a 125 ns time delay, with broadband transduction characterized across 0.5-20 GHz at 0.9 K, establishing superconducting nanowires as an emerging class of acoustic transducers with direct implications for cryogenic signal processing and integration with superconducting quantum circuits.

Bulk-Rashba spin splitting is forbidden in tetradymite topological insulators like Bi$_2$Se$_3$ or Bi$_2$Te$_3$, since their quintuple-layer stacking preserves inversion symmetry. We show that BiSbTeSe$_2$ escapes this restriction: in the Se-Bi-Se-Sb-Te sequence, the structure loses its inversion center, reducing the point group symmetry at $\Gamma$ from $D_{3d}$ to $C_{3v}$. First-principles density functional calculations with spin-orbit coupling show that this ordered structure retains bulk band inversion and a linearly dispersive surface state of a strong topological insulator. Additionally, its bulk bands acquire a pronounced linear-in-$k$ spin splitting away from $\Gamma$. Fitting the conduction- and valence-band doublets to symmetry-constrained two-band $k\cdot p$ Hamiltonians, we extract intrinsic linear Rashba coefficients of $\alpha_{\mathrm{CB}}\approx2.66~\mathrm{eV\,\text{\AA}}$ and $\alpha_{\mathrm{VB}}\approx0.35~\mathrm{eV\,\text{\AA}}$. The conduction-band value places ordered BiSbTeSe$_2$ among the strongest bulk-Rashba topological-insulator systems reported to date and approaches the coupling found in the benchmark polar Rashba semiconductor BiTeI. Sublattice ordering thus provides a route to giant bulk spin–momentum locking that coexists with protected topological surface states, offering a platform in which bulk-Rashba and topological surface contributions to spin and charge transport can be investigated within the same material.

In a rotated frame the biaxial spin Hamiltonian $k_1S_x^2+k_2S_y^2-\mathbf{h}\cdot\mathbf{S}$ is a finite tight-binding chain whose hopping amplitudes are tuned by the applied field. A chain with no vanishing hopping has a nondegenerate spectrum, so a degeneracy can occur only where the field severs the chain. We show that at every point of the exact diabolical-point lattice found by Kececioglu and Garg the chain is severed twice over, in two different rotated frames and at two bonds that are fixed independently. The two severings are carried by projectors that commute with the Hamiltonian but not with each other. In that form they realize the hidden symmetry anticipated by Garg. A single operator built from them pairs the degenerate levels; its rank gives the multiplicity of every lattice point, replacing an earlier continuity and topological argument. Because the two partners of a doublet occupy disjoint stretches of the chain, an exact and manifestly negative determinant fixes the orientation of every cone. At every degeneracy of the model the lower level therefore carries Chern charge -1 in the convention used here.

Reducing the electrical current required to excite magnetization dynamics is a central challenge, e.g. for energy-efficient magnonic devices or oscillator-based computing. Spin Hall oscillators typically rely on large current densities to compensate intrinsic magnetic damping, so these systems are usually studied on the nanoscale (Spin Hall Nano Oscillators, SHNOs) to work with moderate currents and a favorable heat dissipation geometry. Here, we demonstrate that engineering a near-zero effective magnetization ($M_\mathrm{eff}$) enables a drastic reduction of the magnetization oscillation threshold current density for Spin Hall oscillators. This makes it possible to excite even comparably large systems with micrometer lateral sizes, so-called "Spin Hall Micro-Oscillators" (SHMOs). Using micro-focused Brillouin light scattering spectroscopy, we quantify the threshold current density in SHMOs based on W/CoFeB/MgO/Ta with near-zero $M_\mathrm{eff}$. We observe threshold current densities as low as $J_{\mathrm{th}}$ = (0.292 $\pm$ 0.025) $\times 10^{10}$ A/m$^{2}$, representing a reduction of more than two orders of magnitude compared with most recent reported SHNOs. Using systematic micromagnetic simulations, we investigate the breaking down of the macrospin approximation and underline the high influence of $M_\mathrm{eff}$ on magnetization dynamics under applied spin currents. Our results establish $M_\mathrm{eff}$ engineering as a powerful strategy for realizing ultra-low-power spin Hall oscillators and energy-efficient magnetization control.

Machine learning (ML) is transforming materials discovery by enabling rapid prediction of properties that previously required computationally expensive first-principles calculations. Yet most current ML models remain fundamentally limited to zero-temperature descriptions, learning static lattice energies while neglecting the thermodynamic effects that govern materials behaviour at finite temperature. Because phase stability, functional response, and performance are governed by free-energy landscapes rather than static energies alone, this limitation represents a major barrier to predictive materials design under realistic operating conditions. In this Perspective, we argue that developing thermodynamics-informed ML constitutes one of the most important and least explored frontiers in materials discovery. We examine the fundamental shortcomings of energy-based models, highlighting the essential roles of entropy and anharmonicity in determining free energies and materials functionality. We review emerging strategies, including machine-learned interatomic potentials and hybrid ML-statistical mechanics frameworks, while identifying key challenges related to data availability, transferability, and thermodynamic consistency. Building on these advances, we outline a roadmap for thermodynamics-informed ML centred on direct free-energy learning, entropy-aware representations, and adaptive sampling across temperature. We highlight the transformative opportunities this paradigm offers for energy materials and argue that the next generation of ML models must move beyond static energy predictions towards a thermodynamic description of materials behaviour under realistic operating conditions.

As organisms navigate the environment to locate critical resources, their behavioral actions must be tightly coupled to their sensory inputs. Here, we introduce an information-theoretic framework that quantifies this coupling using transfer entropy, which measures information flow between sensory inputs and behavioral outputs. Information flow from sensory inputs to behavior defines a "reactive" component of a navigational strategy, whereas information flow from behavior to sensory inputs defines an "active" component, whereby actions shape subsequent sensory experiences. Analyzing these bidirectional information flows enables us to both predict navigational performance and dissect navigation strategies from trajectories. Using a minimal model that captures the active and reactive components, we connect macroscopic performance to microscopic information flows. We then apply the framework to experimentally measured trajectories of bacteria, worms, and flies, as well as to machine learning agents navigating sensory landscapes. Across systems, bidirectional information flow reliably predicts navigation efficiency, revealing a common behavioral-environment feedback loop. Decomposing active and reactive information flows further exposes distinct strategies underlying bacterial chemotaxis, the spatial dependency of the navigation strategy in fly olfactory navigation, and the learned policies of a reinforcement-trained agent. Together, these results establish bidirectional information flow as a unifying principle for understanding navigation in biological and artificial systems.

Dipolar magnetic skyrmions can assemble into chains with alternating helicity that act as one-dimensional polymers, yet their statistical mechanics violates the universal harmonic scaling observed in actin, DNA, and microtubules. From first principles, we compute the inter-skyrmion pair potential and find a bi-exponential form of competing interactions with two characteristic decay lengths that encode the distinct microscopic mechanisms of repulsion and attraction. Multiscale simulations reveal a power-law temperature dependence with exponent $1$ in the worm-chain limit of a single bond, and exponent $1/2$ in the three-bond limit. We find that the power-law behavior is remarkably independent of magnetic field strength, and the crossover is due to competing radial interactions responsible for the bonds, resulting in a quartic transverse confinement. We show that the precise form of the competing interactions (e.g., Morse or double-Yukawa) does not affect the temperature dependence.

Topology governs finite-size violations of local electroneutrality in confined electrolytes. Within Poisson-Boltzmann theory, we show that this topological control gives rise to a universal hierarchy of deviations in spherical, cylindrical, and planar confinement. We quantify this effect through an electroneutrality deviation ratio that captures the global electrostatic constraints associated with compactness and boundary multiplicity in the three topological classes corresponding to slit, cylindrical, and spherical cavities. Although local electroneutrality is asymptotically restored in the limit of infinite cavity size, finite-size deviations follow a robust topological hierarchy, being strongest in spherical cavities, weaker in cylindrical confinement, and weakest in planar slits. These results prove that topology is the organizing principle underlying confinement-induced charge redistribution and that violations of local electroneutrality constitute a general electrostatic constraint governing overcharging, charge reversal, and long-range charge correlations. More fundamentally, they demonstrate that changing the topology modifies the global electrostatic constraints without altering the local Poisson-Boltzmann equations. As a counterintuitive manifestation of nonlinear confinement in a point-ion model, we report the existence of inside confinement charge reversal (ICCR) in charged hollow cylindrical and spherical nanoparticles. Since physically consistent, more general electrolyte theories must recover the Poisson-Boltzmann description in the appropriate limiting case, the present results establish a benchmark against which topological effects should be assessed beyond the Poisson-Boltzmann description.

Fracture and calving of glaciers are key contributors to ice-mass loss and sea-level rise, yet predictive modeling remains challenging. Fracture in grounded glaciers is driven by gravitational forces and is typically studied within the framework of quasi-static linear elastic fracture mechanics. In this work, we show that purely quasistatic brittle fracture simulations within the phase field fracture framework under fixed self-weight can become strongly overdriven after crevasse initiation, producing unphysical thickening of the diffusive crack band and diffuse damage patterns. This pathology arises because gravity drives a growing region ahead of the crack tip beyond the strength surface. To resolve this, we show that the post-nucleation propagation is fundamentally a dynamic instability rather than a quasistatic process and propose the use of dynamic formulations of fracture. We demonstrate that accounting for inertia results in sharp, localized cracks that propagate through the ice thickness. As a second objective, this paper introduces a new dynamic formulation of the phase-field fracture model of Kumar et al. (J. Mech. Phys. Solids 2018) in which elastic, inertial, and gravitational contributions are degraded consistently in fractured regions.

This work is devoted to the mechanisms of dielectric response and electric conductivity of suspensions consisting of the nematic liquid crystal 5CB with different concentrations (from 0 to 10 wt.%) of ferroelectric BaTiO_3 nanoparticles with an average size of 24 nm. We revealed that the incorporation of nanoparticles influences significantly the dielectric permittivity magnitude and anisotropy, as well as dielectric losses of the suspension. A pronounced temperature dependence of the anisotropic dielectric permittivity of the suspensions was found at lower temperatures corresponding to the mesophase state; but it is also present at higher temperatures corresponding to the isophase. The dependence of the mesophase-isophase transition temperature on the concentration of BaTiO_3 nanoparticles appeared nonmonotonic. With increasing temperature, both the capacitance and the electrical resistance of the pure liquid crystal increase, as well as it increases in the suspensions with small concentration of BaTiO_3 nanoparticles. Due to space charge accumulation in the shells of nanoparticles, larger concentrations of BaTiO_3 nanoparticles influence strongly the ionic transport by promoting the formation of ionic-electronic screening. This effect modifies the dielectric properties and conduction mechanisms of the suspension, leading to the nonmonotonic dependence of the mesophase - isophase transition temperature versus the nanoparticle concentration.

We introduce the multispecies version of the harmonic process on a one-dimensional chain in contact with boundary reservoirs. This process is a continuous-time Markov chain where each site can host an unbounded number of colored particles. The symmetric bulk dynamics is put in contact with reservoirs, which inject and remove particles driving the system out-of-equilibrium. The Markov generator of the process is identified with the integrable Hamiltonian of an open rational Heisenberg spin chain of higher rank. We derive the underlying R- and K-matrices in operator form and construct the double-row transfer matrix following Sklyanin. Similar to the monospecies case the R-matrix factorises into two R-operators, each factor corresponding to left and right moving particles. We further define three dual models: an absorbing particle model, a hidden parameter model and a heat conduction model.

The energy gap is one of the defining properties of a superconductor and appears because the quasiparticle excitations radically change once a metallic system enters the superconducting state. Unconventional superconductors typically exhibit a non-uniform gapping and therefore show physical effects that are subject to intense research. In this review, we provide an overview of concepts needed to understand how unconventional superconductors are different from conventional ones, where the gapping comes from and how it expresses itself in experimentally accessible quantities. This should give the basis to understand current open research questions and navigate the recent literature that tend to contain contradictory conclusions.

Fault-tolerant topological quantum computing relies on identifying Majorana zero modes (MZMs), but reliable detection in realistic devices remains challenging. Conventional topological indicators are inherently biased in finite, disordered systems, blurring the distinction between true MZMs and trivial states. Furthermore, attempts to map these indicators to real observables via machine learning require dense, expensive conductance measurements, creating a severe scaling bottleneck. To simultaneously address topological bias and measurement limitations, we present MEDA: a Measurement-Efficient, Disorder-Aware framework for MZM detection in realistic devices. MEDA maps sparse, practically obtainable observables directly to the robust periodic disorder invariant (PDI). Using a novel sparse parameter regime, MEDA reduces measurement volume by 10x while maintaining predictive quality, even in moderate to strong disorder regimes that limit conventional methods. Furthermore, MEDA naturally prioritizes input features consistent with the topological gap protocol, demonstrating strong physical interpretability.

We calculate massless Dirac scattering and the conductance response to a localized scalar ring gate in a graphene wormhole with two independent curvature scales and no axial magnetic flux. Matching Hankel and Gauss hypergeometric spinors gives the unperturbed scattering states. Interchanging the throat segments preserves the total Landauer conductance, while a gate at a fixed displaced position produces different conductance changes in the two mirror configurations. For $a=5$~nm and $r_L+r_R=13.68$~nm, a $1$~meV gate of width $1$~nm centered at $u_0=7$~nm gives relative conductance changes of $+0.0718\%$ and $-0.0918\%$ at $E=200$~meV for $\eta=0.5$ and $2$, respectively. Energy–position maps show how asymmetry redistributes the electrical response. Gates centered well inside both curved segments can give different response magnitudes; opposite signs occur near the mouths and farther out. We also find opposite response signs in the fixed-length comparison at the chosen operating point. For equally occupied opposite angular channels, the sublattice imbalances cancel and the conductance responses add. A spatially controlled gate thus probes throat orientation through conductance even when the unperturbed two-terminal measurement cannot distinguish the two configurations.

A recent Google Quantum AI experiment [\href{https://www.science.org/doi/10.1126/science.adr9680}{Gyawali et al., Science 393, 71 (2026)}] has exploited quantum parallelism to emulate disorder-averaged many-body dynamics, with conserved local degrees of freedom generating an effective disorder potential. We investigate how the local spectrum of these static variables controls localization in a flavor-extended ${\mathbb Z}_2$ lattice gauge theory, which maps onto a mixed-field Ising chain with $n$-level bond disorder. Combining finite-size spectral and entanglement diagnostics with infinite matrix-product state dynamics, we find a qualitative distinction between binary and multilevel disorder. For $n=2$, apparent localization ultimately gives way to thermalization; the long-lived transient arises from energy-scale separation, degenerate spectral towers, and approximate Hilbert-space fragmentation. By contrast, $n=4$ displays consistent localization signatures, including Poissonian level statistics, area-law eigenstate entanglement, nonthermal entanglement spectra, and persistent local memory over accessible times in the thermodynamic limit. Our results show that, despite its larger variance, binary disorder lacks the local amplitude diversity needed to suppress resonances. Thus, localization is governed not simply by disorder strength, but by the local disorder spectrum and the resulting resonant connectivity of the many-body Hilbert space.

We study quantum phase transitions of Mott insulators between spin-glass and featureless paramagnetic phases. Specifically, we consider a triangular-lattice bilayer Heisenberg model with bond disorder. The clean system has two phases, a dimer quantum paramagnet and a non-collinear antiferromagnet, separated by a quantum critical point. Bond disorder destroys the antiferromagnetic phase via the interference of dipolar textures and results in spin-glass order, such that the system features a quantum phase transition between spin-glass and dimer phases. We study the vicinity of this transition using a variant of bond-operator theory and calculate thermodynamic observables as well as excitation spectra. Bond disorder leads to strong inhomogeneities near the transition which suppresses non-collinearities and leads to anomalously weak glassiness in the near-critical quantum spin glass. We characterize the low-energy excitations which have a strong tendency towards spatial localization, and we track the behavior of the amplitude (i.e. Higgs) mode across the glass phase whose spectral weight we find to be strongly suppressed due to interference effects.

Crystalline symmetries stabilize topological states with distinct electronic properties, while altermagnets exhibit momentum-dependent spin splitting without net magnetization. Here, we combine first-principles calculations with a minimal tight-binding model to realize $C$-paired spin-valley-locked nodal-line fermions in the $d$-wave altermagnet $\mathrm{AV_2X_2O}$ (A = Rb, Cs, or K; X = Te, Se, or S). The low-energy electronic structure hosts coexisting spin-degenerate and spin-polarized nodal lines around $C_{4z}$-paired valleys near the Fermi level. The spin-polarized nodal lines are protected by the out-of-plane mirror symmetry $\mathcal{M}_z$ and remain robust against spin-orbit coupling. The minimal model reveals their microscopic origin and establishes a general design principle for their isolation. Layer engineering and electronic correlations serve as material-specific knobs for realizing these isolated spin-valley-locked nodal lines near the Fermi level. Our results establish the $\mathrm{AV_2X_2O}$ family as a versatile platform for exploring topological spin-valley locking in $d$-wave altermagnets.

Nonholonomic mechanics describes systems subject to non-integrable velocity constraints, such as rolling bodies and skating motion. These systems generally lack a canonical Hamiltonian formulation, obstructing standard quantization methods. Here we quantize nonholonomic systems as Markovian open quantum systems, with the nonholonomic constraint appearing in a large-dissipation limit. We find explicit Lindblad superoperators that reproduce the classical dynamics of the Chaplygin sleigh and the Suslov problem in the semiclassical limit. The master equation is numerically simulated, and the covariance is shown to satisfy a relation predicted by the theory of metastability in open quantum systems.

Simulating the real-time dynamics of particle collisions is a promising application of quantum simulators, because classical methods such as tensor networks struggle to capture the highly entangled states generated in high-energy scattering. Realizing such simulations requires both the preparation of incoming wave packets and the detection of the outgoing scattering products. In this work, we propose protocols that address both challenges on programmable analog and digital quantum simulation platforms. Our state-preparation scheme uses a weakly coupled auxiliary qubit - or, more generally, a customized local quench - to inject a single quasiparticle with well-defined momentum. Because it relies only on conservation of energy, this scheme requires no fine-tuning or prior knowledge about particle eigenstates, making it robust against errors in calibration and implementation. The momenta of scattering products are then extracted, using only local measurements, from the interference pattern that arises when particles are reflected at the system's boundary. We validate our protocols through numerical simulations, first in a simple single-particle model and subsequently in two interacting many-body systems: a Rydberg atom chain and an Ising chain in a mixed field. We demonstrate how high-energy regimes, necessary to access inelastic scattering processes, can be reached through an adiabatic ramp, and how the wave packet shape can be optimized by spatially modulating the Hamiltonian. Finally, we show how the protocol can be generalized to systems with more than one spatial dimension. Our proposal provides a versatile approach to the quantum simulation of scattering phenomena, and is compatible with several quantum simulation platforms that are already experimentally available.

Non-Abelian gauge theories with dynamical matter govern the strong interaction and a broad class of strongly correlated quantum systems, yet their ground-state properties remain difficult to obtain from first principles. Using a continuous-group variational Monte Carlo approach that retains the full SU$(2)$ gauge field without truncation, we determine the ground-state behavior of the SU$(2)$ lattice gauge theory with staggered fermions on an $L\times L$ square lattice. Treating the magnetic and electric couplings $\lambda$ and $g^2$ independently, we find a magnetic-flux transition at $\lambda^\ast=-0.040\pm 0.005$, with no resolvable drift of the transition point as the electric coupling is varied. Along the physical coupling line $\lambda=4/g^2$, for $L=4,6,8$, we uncover a gauge-matter delocalization crossover from a flux-disordered regime at strong electric coupling to an ordered unity-flux regime at weak coupling. The chiral condensate, a gauge-invariant Wilson-line meson correlator, and the local color density consistently reveal the emergence of coherent gauge-assisted matter dynamics. Together, these results provide a unified physical picture of how magnetic-flux ordering and fermionic coherence develop in an untruncated non-Abelian lattice gauge theory.

Determining the ground state of non-Abelian lattice gauge theories coupled to dynamical fermions is key to understanding confinement and the phase structure of gauge–matter systems. We present a variational Monte Carlo framework for the ground state of the untruncated fully-continuous SU$(2)$ lattice gauge theory coupled to dynamical staggered fermions on an $L\times L$ square lattice. We work in the magnetic basis with a neural-network representation of the gauge wavefunction. The fermions are described by a gauge-covariant Gaussian fermionic correction built on a fixed Néel reference state where, for each sampled gauge configuration $\mathbf{U}$, the correction is generated by a Hermitian operator. This operator is constructed from short Wilson lines and the eigenvectors of the mass–hopping Hamiltonian, with number of variational parameters polynomial in the system size. This Gaussian structure also gives analytical expressions for all fermionic contributions to the energy and related observables in terms of the fermion occupation matrix. The results are validated against strong-coupling perturbation theory, where they recover the expected effective antiferromagnetic spin Hamiltonian. Using this framework, we map a coarse ground state phase diagram in the plane of independent electric and magnetic couplings $(g^2, \lambda)$ and show that a hysteresis analysis can identify the existence of phase transitions. Restoring the physical relation $\lambda=4/g^2$, we characterize how increasing the system size and changing the electric coupling $g^2$ move the state away from the reference Néel state, for lattice sizes $L=4,6,8$. More broadly, the method offers a sign-problem-free variational framework for continuous non-Abelian gauge groups with dynamical matter that should extend to other matter content and higher-dimensional lattices.

A recent construction showed that iteratively gauging symmetries of a quantum field theory can generate an emergent extra spatial dimension. Here we identify the precise mechanism underlying this phenomenon: it is dimensional deconstruction, the procedure by which an extra dimension is encoded in the structure of a quiver gauge theory. We demonstrate this by showing that the standard deconstruction action, upon dualizing the Goldstone fields on the Higgs branch, is exactly equivalent to the action produced by iterative gauging. The dictionary is transparent: quiver nodes correspond to gauge fields, and quiver links correspond to the gauge fields introduced to couple to magnetic symmetries. We further show that starting by gauging the electric rather than the magnetic symmetry produces the deconstructed theory written in the dual variables, with all coupling constants inverted.

The interplay between ionic and electronic subsystems dictates the behavior of structural phase transitions in polar dielectrics, a coupling mediated by soft optical phonon modes. In incipient ferroelectrics such as SrTiO$_3$ (STO), strong local-field effects can drive the lattice into a non-perturbative regime near the phase boundary. However, disentangling the distinct contributions of local fields from those of spontaneous macroscopic polarization remains an experimental challenge. Here, we isolate these mechanisms by probing paraelectric STO deep within its symmetric phase, where macroscopic spontaneous polarization is suppressed. Linear terahertz (THz) spectroscopy reveals that the soft mode exhibits a hybrid character, predominantly driven by electronic polarizability. Utilizing two-dimensional THz spectroscopy, we map the underlying nonlinear signals, demonstrating that the system persists in a perturbative regime characterized by robust local-field coherence. By implementing a microscopic model of coupled electronic and lattice degrees of freedom mediated by local fields, we qualitatively reproduce these multidimensional coherent signatures. Our findings highlight that while local fields are necessary to initiate non-perturbative lattice dynamics, they are insufficient on their own. This reveals that spontaneous polarization plays a deterministic role in dictating soft-mode nonlinearities in strongly correlated polar dielectrics.

Phase-space approaches such as the truncated Wigner approximation (TWA) provide an efficient semiclassical framework for performing approximate simulations of the dynamics of open quantum many-body systems outside the reach of exact numerical methods but beyond the mean-field level. For bosonic systems, TWA is known to be equivalent to a Keldysh path-integral formulation truncated at second order in the so-called quantum fluctuations. This semiclassical approach provides an alternative transparent route towards approximate stochastic equations of motion, which can be efficiently solved. Here we establish the corresponding path-integral formulation for interacting open spin-$1/2$ systems using the continuous $\mathrm{SU}(2)$ phase space. We show, in particular, that a consistent treatment of dissipation requires correctly mapping operator products onto the curved spin phase space, leading to stochastic equations that coincide with those obtained from the continuous TWA formulation and thus reproduce the exact dynamics of a single dissipative spin. Our results provide a unified field-theoretic foundation for the TWA to dissipative spin dynamics and offer a systematic starting point for extensions beyond the semiclassical approximation.

Rare-earth iron garnets offer an ideal platform for exploring the interplay of low-energy excitations and the complex temperature-dependent magnetization dynamics. In these systems, exchange coupling between rare-earth and iron sublattices generates high-frequency collective spin excitations. In addition, the robust spin-orbit coupling of localized 4$f$ electrons triggers the crystal-electric-field (CEF) transitions at THz frequencies. Despite extensive research into the garnet spin dynamics, the interplay between CEF excitations and exchange modes has remained largely unmapped. Using temperature-dependent THz time-domain spectroscopy, we demonstrate a hybridization between the Yb-ion CEF excitation and the Yb-Fe exchange mode in Gd$_{3/2}$Yb$_{1/2}$BiFe$_{5}$O$_{12}$. This coupling is characterized by a significant redistribution of spectral and temporal weights as the material approaches its magnetization compensation temperature. Notably, the Yb-Fe exchange mode exhibits an anomalous redshift upon cooling – a reversal of the conventional blue shift typically driven by increased exchange coupling. We trace this phenomenon to a modification of Yb-Fe exchange anisotropy, driven by the interplay of the Fe exchange field and Yb CEF excitations. These findings highlight the critical role of CEF-mediated exchange coupling in shaping low-energy spin dynamics, positioning rare-earth garnets as a cornerstone for future THz spintronic technologies.

The dynamics of a nuclear spin bath generates magnetic noise that is a key contributor to the decoherence of electron spin qubits in electrostatically-defined quantum dots. In this paper, we extend the cluster correlation expansion (CCE) technique, which has proven useful for predicting solid-state qubit coherence times across various settings but is limited to shorter time scales, to incorporate stochastic treatments of cluster dynamics in order to efficiently predict slow drifting Overhauser fields over longer time scales. This approach combines quantum evolution with classical rate matrices to enable simulation across a wide range of temporal regimes required to simulate, for example, the long-time convergence of the ergodic $T_2^*$ from Ramsey experiments. Our methodology is validated against experimental data from various silicon spin qubit systems, demonstrating a strong agreement between simulation and measurement of Ramsey experiments presented in the form of $T_2^*$ versus averaging time, autocorrelation functions, as well as power spectral densities. Furthermore, we demonstrate significant back-action effects through modeling and experiment; specifically, the dynamics of the nuclear spin bath depends upon the electron spin occupation schedule. Finally, our modeling quantitatively predicts the benefits from compensating for the slow drift of Overhauser fields in qubit operations. Our findings indicate that compensating for an Overhauser rotation measured $\Delta t$ in the past results in an effective $T_2^*$, which we denote $\tilde{T}_2^*(\Delta t)$ for clarity, under certain scenarios of interest, can be one or two orders of magnitude larger than the ergodic $T_2^*$ if the Overhauser rotation is re-characterized every 100 milliseconds; that is, $\tilde{T}_2^*(\Delta t = 100~{\rm ms})$ can be $10$ to $100$ times larger than $T_2^*$.

In order to appropriately capture large-scale material features and emergent phenomena via atomistic simulations, such as Molecular Dynamics (MD), the system scale can range up to hundreds of millions of atoms. However, the force-field models that drive those simulations are generally trained with Density Functional Theory (DFT) reference data, limited to relatively small configurations on the order of 100s or 1000s of atoms. To compute DFT forces on atoms in regions of interest, for example for active-learning or on-the-fly training of interatomic potentials, one needs to extract a small set of atoms from the larger simulation box, and typically work with periodic boundary conditions for DFT. However, methods to select the shape and size of this extracted set of atoms, as well as to generate a potentially necessary passivating envelope, have not been systematically analyzed. In this work, we benchmark several techniques, including a generative diffusion-based artificial intelligence (AI) approach, for extracting atomic environments from large, bulk configurations and embedding them into smaller configurations suitable for DFT calculations with periodic boundary conditions. We test with a diverse set of material systems, which includes amorphous $\mathrm{SiO_2}$, Ta with screw dislocations, and molten C. We demonstrated a notably simple procedure, a method we refer to as deletions, yields superior performance over an array of alternative extraction methods.

We introduce Krylov-space memory cores as stationary, depth-resolved structures that reveal how anomalous initial-state memory is organized inside the Krylov space of otherwise thermalizing nonintegrable systems. The stationary occupation profile identifies where late-time probability is concentrated along the Krylov chain, while complementary diagnostics of residual equilibration fluctuations, deviation from the Gibbs reference, and long-time Krylov-current fluctuations determine the physical character of that region. Across weak thermalization, confinement-induced anomalous dynamics, and many-body scarring, anomalous initial states develop compact low-depth memory cores that carry appreciable residual fluctuations, Gibbs mismatch, and persistent current-fluctuation activity. These cores are often embedded within substantially broader stationary occupation halos. The reference states considered, by contrast, do not exhibit a comparable combination of signal strength and spatial compactness. An auxiliary integrable comparison further shows that compact Krylov memory is state selective rather than a generic consequence of integrability. Krylov-space memory cores therefore provide a stationary framework for identifying where structured quantum memory resides and how it remains dynamically encoded.

Many observables are symmetric second-rank tensors, reported through magnitude-ordered principal values and axes. This chart folds tensor space: the parameters develop cusps and exchange labels where the tensor is smooth. It also hides a global effect: an arrow carried along a principal axis around a loop encircling a degeneracy can return reversed, defining a binary return parity, invariant under smooth deformations of the loop avoiding degeneracy. For tensor fields, this structure is long established, but the parameters are coordinates of the domain on which the field is defined, and the degeneracies are a feature of that particular field. Here we show that the electric field gradient (EFG) carries the same structure in a control space: a traceless observable at a single probe site, steered through its five-dimensional tensor space by symmetry-adapted strain, with the encircling loop applied rather than found. First-principles calculations reveal an isolated degeneracy with nontrivial parity in rutile TiO$_2$, point- or line-like degeneracies in SnO$_2$ depending on the control slice, and access to all five EFG components in cubic MgO. Thus, return parity becomes accessible for a local observable, and strain-tuned, orientation-resolved hyperfine spectroscopy offers a route to reconstruct it.

Van der Waals (vdW) based antiferromagnets (AFMs) are an ideal platform for probing and understanding thickness- and twist-angle-dependent emergent spin phenomena. However, element-specific nanoscale characterization of the spin structure in atomically thin vdW-based AFMs systems and layer-parity effects remain elusive, making them crucial for both fundamental insight into low-dimensional magnetism and the rational design of spintronic devices based on these materials. Here, we utilize X-ray magnetic circular and linear dichroisms paired with photoemission electron microscopy to resolve the magnetic order in atomically thin CrSBr. Our comprehensive measurements reveal CrSBr magnetic structure at the nanoscale and its dependence on the layer number, surface encapsulation, temperature, and applied field. Moreover, in the orthogonally twisted bilayer configuration, obtained by twisting two CrSBr ferromagnetic monolayers by 90$^\circ$, the magnetic easy axis fundamentally differs from the individual monolayers, unlocking a new pathway for moiré magnetism.