We investigate precision scaling at the interface between unitary and non-unitary encoding under generalized noise including single-particle and collective dephasing and decay. Using linear response theory and the error propagation formula, we derive analytic precision expressions for both the unitary parameter $Ω$ and the dissipation strength $γ$. For unitary encoding, when the observable commutes with a Hermitian noise operator, the optimal encoding time is independent of $N$, yielding the Heisenberg limit $ΔΩ\propto 1 / N$; otherwise the precision degrades to the standard quantum limit or ceases to improve with $N$. For non-unitary encoding, when $[\hat{A}, \hat{O}] = 0$, the precision is insensitive to intrinsic dynamics and encoding time, scaling as $Δγ\propto \sqrt{γ/ \expval*{\hat{L}^\dagger \hat{L}}}$. Notably, for collective decay, the Dicke state reaches the Heisenberg limit $Δγ\propto 1 / N$, demonstrating that entanglement can enhance non-unitary estimation. Our results provide a unified framework and practical guidance for designing quantum metrology protocols in noisy environments.

Non-Hermitian skin effects (NHSEs) enable dramatic boundary accumulation of waves, yet their experimental realization typically demands engineered nonreciprocity or spatially patterned loss. Here we demonstrate theoretically and experimentally that uniform loss provides a simple and previously overlooked mechanism for enforcing unidirectional-like edge transport in photonic crystals (PhCs) that breaks time-reversal symmetry in the presence of nonchiral edge states. Using a core cladding geometry where domains share identical Chern numbers but possess distinct bulk polarizations, we show that uniform loss activates NHSEs that reshape the spectral topology of edge bands, giving rise to point gap windings that dictate a one way propagation. Near field measurements confirm that loss converts intrinsically bidirectional interface states into a unidirectional-like circulation around the entire domain wall, showing excellent agreement with theory. Our results establish uniform loss as a universal and structurally simple route for achieving unidirectional-like wave transport.

We performed a 2D finite-element electrothermal computational study of thermoelectric effects and filamentary electronic transport in Ge$_2$Sb$_2$Te$_5$ mushroom phase change memory cells during Reset and Set operations, accounting for spatial activation energy variations in amorphous Ge$_2$Sb$_2$Te$_5$ and phase-change dynamics. Reset operations with current going from the top electrode to the narrow 4 nm bottom electrode require $\sim$3x less energy and power, and $\sim$2x lower current to achieve the same Reset resistance, compared to the opposite polarity, due to thermoelectric effects. Filamentary conduction, electrical breakdown, thermal runaway, and local crystallization of amorphous Ge$_2$Sb$_2$Te$_5$ depend on current polarity and thermal boundary conditions, and determine the location, shape, and volume of the programming region, which may be significantly smaller than the semi-cylindrical mushroom region. The programming volume does not scale with contact dimensions larger than 10 nm. Larger contact areas introduce increased device-to-device and cycle-to-cycle variability due to filamentary conduction but are expected to lead to higher reliability and endurance.

Multifractality is an effective formalism for quantifying the nonlinear, scale-free properties of complex data. In this study, we propose a novel and efficient methodology, termed Multifractal Space-filling Curve Analysis (MFSCA), for quantifying the correlation structure of multidimensional data. Within this framework, the original multidimensional data - while preserving both local and long-range organisational properties - are projected onto a one-dimensional representation using a fractal space-filling curve. The resulting one-dimensional signal is then analysed using multifractal algorithms. We demonstrate the utility of the method using both artificially generated multifractal structures and real data. In particular, we apply MFSCA to analyse magnetic resonance imaging (MRI) data from Alzheimer patients at different stages of dementia. Based on the results, we estimate the multifractal profiles of the brain for healthy subjects of different ages as well as for dementia patients. The analysis reveals that the spatial organization of brain structures, as measured by the degree of multifractality, progressively weakens with age and the development of dementia. A transition from multifractality to monofractality is observed both in control groups, when comparing the Young Control and Elderly Control groups, and among dementia subjects of similar age but at different stages of the disease, namely early dementia and mild cognitive impairment. Thus, from the perspective of multiscaling properties, the heterogeneous characteristics of spatial brain organization deteriorate under worsening conditions, leading to a homogeneous and weakly correlated structure. These findings not only effectively capture key aspects of brain organisation, but also demonstrate that the multifractality of MRI data can serve as a marker of structural brain changes.

The probability distribution of a two-particle correlation function computed over background auxiliary field configurations, used to generate the interactions, has been shown to inform about the spectra of universal $n$-body clusters [1]. Here, we utilize two approaches, a numerical lattice computation and an analytic expansion in the limit of large numbers of identical species, in an attempt to refine the initial predictions. Exploratory calculations in these directions are presented, and future investigations laid out.

Active rotator models provide a minimal phase description of excitable and oscillatory systems, and have long been used to study mutual entrainment, synchronization, and collective transitions. Here, we investigate fully connected active rotator networks with Kuramoto coupling, where a common intrinsic drive competes with local feedback amplitudes drawn from a zero-mean Gaussian distribution. This produces a competition between local pinning and collective phase alignment. Using mean absolute late-time drift and the fractions of positive and negative drifting oscillators, we construct numerical regime maps in the feedback-disorder-coupling plane. At weak coupling, increasing the feedback disorder strength suppresses drift, while stronger coupling can restore positive late-time drift when feedback disorder is not too strong. We interpret these regimes using analytical limits for the uncoupled and coherent strong-coupling cases. We also examine finite-size effects and zero-mean distributed intrinsic frequencies. Together, these results show that mixed-sign local feedback alone can reshape the balance between pinning and drifting in coupled active rotator networks, even when the intrinsic drive is homogeneous.

Quantum circuits suffer from severe trainability issues: even shallow circuits are swamped with poor local minima. Yet matrix product states (MPS), which can be prepared by sequential circuits, are remarkably trainable in practice -- as demonstrated by decades of successful density matrix renormalization group calculations. In this work, we resolve this apparent paradox by proving that the energy landscapes of MPS are free from poor local minima, under the same setting where brickwork circuits are not. The key insight is that the gauge freedom of MPS creates an effective local overparametrization that causes local minima to concentrate near the global minimum, analogous to overparametrized classical neural networks. We rigorously prove that the local minimum distribution of the MPS energy landscape is invariant under moves of the orthogonality center. Numerical experiments further confirm that the optimization of sequential circuits converges to near-optimal solutions even for random Hamiltonians, in stark contrast to brickwork circuits. Our findings highlight the pivotal role of effective local overparametrization in determining trainability, providing a valuable guide for overcoming the trainability bottleneck of variational quantum algorithms.

The deconfined quantum critical point (DQCP) provides a prominent example of the unconventional phase transitions beyond the Landau-Ginzburg-Wilson paradigm and its nature has been controversial for decades. The DQCP has been extensively studied and the results lead to two opposite scenarios with pseudo-criticality or multicriticality. The pseudo-criticality is a prevailing scenario of DQCP which interprets the approximately scale invariant numerical results with the walking behavior near complex fixed points. In contrast, the multicriticality scenario conjectures the DQCP is a unitary fixed point with a relevant $SO(5)$ singlet scalar. In this work we provide substantial evidence for the multicriticality scenario using conformal bootstrap. We start with the observation that the large scale Quantum Monte Carlo (QMC) results nearly saturate the bootstrap bounds. After imposing suitable sparseness condition the bootstrap bound forms a sharp cone in the three-dimensional parameter space. The bootstrap cone is close to the QMC data. We use the navigator algorithm to locate the apex of the cone and extract the extremal solutions. We find striking consistencies between the bootstrap solutions and the fuzzy sphere data of DQCP, including the coefficients in the operator product expansions (OPEs) and the higher spectrum! The bootstrap cone unifies the QMC and the fuzzy sphere data into a unitary conformal field theory with a relevant $SO(5)$ singlet scalar, thus strongly supporting the multicriticality scenario of DQCP. The agreement between the conformal bootstrap, QMC and fuzzy sphere results is a surprise towards solving DQCP and decoding the profound phase diagram of the two-dimensional quantum magnets.

We calculate the real-time symmetric correlation function of the stress-energy tensor for a non-integrable Ising field theory consisting of three stable scalar particles via lattice Hamiltonian simulation. Using classical exact diagonalization and the matrix product state tensor network methods, we find that in the scaling region of the lattice theory, Umklapp processes are suppressed and the sound modes of relativistic hydrodynamics emerge at long wavelength and late time. The extracted ratio of bulk viscosity to entropy density is $ζ/s=14.19\pm 0.90$ and the speed of sound is $c_s/c=0.76 \pm 0.02$ at the temperature $T\approx 7.14$ in units of the lowest stable particle's mass. Our study demonstrates the utility of real-time lattice Hamiltonian simulation for describing hydrodynamization and calculating transport coefficients nonperturbatively.

Mesoscopic colliders provide an effective platform for probing the mutual statistics of quantum particles. Recent experiments have successfully extracted the mutual statistics of fermions, and more exotic anyons using quantum point contacts (QPCs). Coupling a point-like collider, such as a quantum point contact, to a two-level impurity or qubit can induce statistical transmutation of fermions, causing them to display boson-like bunching tendencies. Here, we extend the analysis to an extended collider. We investigate the scattering of two incoming fermionic and bosonic wave packets in the presence of post-selection on the impurity state, and systematically analyze the possible benchmarks used to characterize bunching and infer the underlying mutual statistics. We show that only a specific benchmark faithfully captures the mutual statistics of the colliding particles, while alternative choices can produce spurious statistical signatures. Hence, the correct benchmark for probing the quantum statistics depends on the intricate details of the mesoscopic collider.

Surface altermagnetism extends spin splitting beyond bulk altermagnets through symmetry reduction at surfaces and interfaces. An existing classification applies to the local symmetry of atomically flat surface terraces. The present paper addresses the symmetry of macroscopic spin-momentum correlations that survive averaging over compensated rough surfaces. These correlations are governed by the surface antisymmetry Laue point group. Rough-surface altermagnetism is forbidden at any surface of a magnet whose antisymmetry space group contains antitranslations, and the classification therefore reduces to $PT$-symmetric antiferromagnets. By restoring all symmetries leaving the surface normal invariant, roughness can generate compensated surface altermagnets from uncompensated flat terminations, increase the surface symmetry, or suppress spin splitting. By combining bulk switchability with altermagnetic surface transport properties, roughness-robust surface altermagnetism in $PT$-symmetric antiferromagnets provides a route toward spintronic functionality.

Electrochemical H2O2 synthesis was investigated using a 3 percent WO3 C gas diffusion electrode GDE. The catalyst outperformed bare Vulcan carbon, generating H2O2 concentrations of 423, 586, and 916 mg L at 50, 75, and 100 mA cm2, respectively, maintaining around 70 percent current efficiency. This performance and lower energy consumption are attributed to the WO3 carbon synergistic effect. In electro Fenton EF applications, the WO3 C GDE achieved rapid initial ciprofloxacin CIP degradation of around 70 percent in 30 min, though limited later by slow Fe2 regeneration. Incorporating UV light photoelectro Fenton overcame this constraint, yielding complete CIP removal within 90 min, while a boron doped diamond BDD anode enhanced total organic carbon TOC mineralization to 66 percent. The proposed degradation mechanism proceeds via hydroxyl radical attack on the piperazine ring with or without defluorination and quinolone ring oxidation, with theoretical analysis confirming reduced environmental toxicity of the transformation products. Overall, WO3 C GDEs represent a highly efficient strategy for H2O2 generation and wastewater remediation.

Quantum impurity models, which describe the coupling between interacting orbitals and a non-interacting bath, play a central role in the physics of strongly correlated electron systems. Solving a quantum impurity model in general requires the use of non-perturbative numerical methods. Hamiltonian-based approaches, which rely on an explicit bath discretization, are typically limited to a small number of bath sites or small entanglement, and diagrammatic methods suffer from sign problems, slow convergence, or diagram truncation approximations. Here we show that these two classes of methods can be combined: augmenting diagrammatic methods with a small auxiliary bath can reduce the residual problem to a regime where low-order perturbation theory is highly accurate and rapidly converging. In a simple benchmark, the precision of the hybrid approach surpasses bold-line calculations by several orders of magnitude; for a strongly interacting two-orbital model with a severe sign problem, convergence is achieved at three orders of magnitude lower computational cost than competing methods; and convergence to the unknown exact result is rapidly accelerated in a difficult realistic problem. Our results establish a practical route to high-precision quantum impurity solutions in correlated quantum systems.

How can a growing biological filament remain straight despite stochastic fluctuations in growth? Motivated by filamentary structures that develop reproducibly across biological systems, we study the stability of a noisy, growing elastic filament regulated by feedback. We formulate a minimal model in which growth responds to the filament's strain, curvature, and orientation through local or nonlocal spatiotemporal feedback laws. Linear stability analysis identifies the conditions under which these feedback mechanisms stabilize a straight configuration. In the presence of noise, we show that purely local feedback requires orientation sensing to suppress long-wavelength instabilities, whereas nonlocal feedback allows stabilization through proprioceptive (curvature) sensing alone. Coupling to an elastic substrate further suppresses large-scale fluctuations. Our results establish minimal control strategies that ensure robust straight growth and suggest experimental signatures for identifying the feedback mechanisms underlying morphogenesis.

Crystalline materials with ultralow thermal conductivity ($κ$) are potential thermal barrier coatings or thermoelectrics, yet the discovery of ultralow-$κ$ materials remains inefficient due to the limitations of trial-and-error approaches. Herein, we propose a state-of-the-art high-throughput workflow that integrates universal machine learning interatomic potentials with high-fidelity phonon transport theories to accelerate the exploration of thermal insulators. Applying this approach, we identify dozens of crystalline materials with intrinsic room-temperature $κ$ values below 0.2 $\rm W m^{-1} K^{-1}$. Among them, we report and experimentally validate CsTlI$_4$, a record-breaking material with an ultralow $κ$ of 0.14 $\rm W m^{-1} K^{-1}$ at 300 K. Structural and bond analyses reveal that a hierarchical bonding framework, consisting of multi-coordinated Cs-I and antibonding Tl-I interactions, leads to weak chemical bonding and a soft lattice. These features reduce phonon group velocities, enhance phonon scattering, and induce strong vibrational mismatch between sublattices, collectively suppressing both particle-like phonon propagation and wave-like tunneling. Beyond this specific system, we establish physically interpretable descriptors based on interatomic force constants that correlate strongly with ultralow $κ$ and capture the role of bonding hierarchy and coordination environments in governing thermal transport. This work demonstrates a robust data-driven strategy for accelerating the discovery of thermal insulators and provides microscopic insight into how hierarchical bonding and strong anharmonicity cooperate to impede heat-carrying vibrations.

We investigate a minimal molecular model consisting of square planar plaquettes hosting multiple electrons, whose dynamics is governed by a tight-binding Hamiltonian supplemented by on-site Hubbard repulsion. By coupling this system to a spatially nonuniform cavity mode, we analyze the emergence of a magnetostatic instability, namely photon condensation, originating from the paramagnetic Van Vleck mechanism. The global behavior of the system is analyzed for different electronic filling factors, and we find that, except for the special cases of half-filling and single electron, where the transition, if it occurs, is necessarily a second order phase transition, the global system may also undergo a first order transition because of the action of the electron-electron interaction. The polaritonic excitation energies are analyzed, providing clear spectroscopic signatures of the magnetostatic instability and of its order.

We generalize the condition under which a quantum material exhibiting a pseudogap phase is a precursor to a superconducting (SC) dome. The result reveals the non-analytic T* as a function of doping. A well-known example is the high-Tc cuprates. Essentially, the SC dome is generated under two conditions: (1) that the pseudogap T* is a decreasing function of doping, due to the decrease in size of extended pairing of doped holes with doping, and most importantly, (2) that the rate of configurational-ordering parameter is an increasing function of doping as a result of the decrease in extended length of the disordered pairs. These two conditions are provided by the new entanglement and confinement pairing mechanism of high-Tc cuprates. This is a theory that has recently been discussed in the literature by Buot et al. It hinges on a novel strong entanglement and confinement hole pairing (ECHP) mechanism that unravels the microscopic features of the entire phase diagram of both electron and hole-doped high-Tc cuprates.

The physics of polymer chains is often probed using molecular stretching experiments and various idealized single-chain models. The majority of these models consist of a discrete sequence of links, which may be treated as rigid or extensible. Although such models are well established and many specific extensible variants have been proposed, no generally applicable theory has been presented. Moreover, most existing treatments are heuristic rather than systematically and rigorously derived. This critical gap is closed here through the development of a generally applicable asymptotic theory for including link extensibility in a broad class of discrete models for single-chain thermodynamics. The theory is verified analytically using the freely jointed chain and validated numerically using the freely rotating chain. The resulting approximation is first-order accurate in inverse link stiffness, with quadratically decreasing error, and recovers extensible behavior across all link stiffnesses from a single rigid-link reference calculation.

Nuclear magnetic resonance (NMR) is a powerful probe of atomic structure, but accurate quantum-mechanical predictions of tensorial NMR parameters are computationally demanding. This creates a bottleneck both for direct quantum-mechanical studies and for collecting high-quality training data for machine-learning (ML) models. Here, we introduce a synthetic pre-training and fine-tuning protocol for graph-based ML models of solid-state NMR parameters. We first pre-train models on synthetic tensorial data, as obtained using an existing ML model, and subsequently fine-tune those models on new ground-truth data. We observe a pronounced improvement in data efficiency when pre-training and fine-tuning span the same compositional and configurational space, and we carry out initial experiments regarding chemical transferability. Our work outlines a route toward future data-efficient training workflows for tensorial ML models for solid-state NMR, combining inexpensive synthetic supervision with targeted first-principles refinement.

The sustainable electrogeneration of hydrogen peroxide (H2O2) via the two-electron oxygen reduction reaction (2e$^-$ ORR) represents a promising alternative to conventional production methods. In this study, CeO2 and CeO2MnOx nanoparticles were synthesized and supported on Vulcan XC-72 carbon at varying loadings (1, 3, and 5%), aiming to assess the lowest metal loading and high H2O2 electrosynthesis. Physicochemical characterizations confirmed the successful formation of CeO2 nanowires and the effectiveness of the MnOx surface modification. XRD, TEM, XPS, EPR, and contact angle analyses revealed that CeO2 loading increased surface hydrophilicity through the presence of oxygenated functional groups, thereby favoring electrochemical activity. On the other hand, all CeO2MnOx loadings were statistically equivalent to Vulcan XC-72 in terms of contact angle. Electrochemical evaluations using a rotating ring-disk electrode (RRDE) demonstrated enhanced ORR activity and high H2O2 selectivity for the 1% CeO2MnOx/C and 3% CeO2/C catalysts, achieving up to 90% selectivity and elevated ring currents. The results suggest that low metal loading and surface modification via MnOx improve the balance between active site exposure, oxygen adsorption, and intermediate stabilization, thus favoring the selective 2e$^-$ pathway. These findings support the development of cost-effective, non-noble-metal catalysts for green H2O2 production via electrosynthesis.

Motivated by the experimental realization of the two-dimensional (2D) carbon biphenylene network (BPN), the theoretical extension of the BPN topology to various groups of elements was successfully implemented. In this work, we conducted first principles and quantum transport calculations to reveal the electronic, thermal, thermoelectric performance and current-voltage (\textit{I-V}) behavior of the pristine MoS$_2$-BPN by using density functional theory (DFT) combined with Non-Equilibrium Green's Function (NEGF) formalism. At room temperature, the phonon thermal conductance is remarkably low along both the armchair and zigzag orientations, with values of 0.28 nW/K and 0.23 nW/K, respectively. The directional dependence of the electronic and thermal transport properties is clearly reflected in the thermoelectric figure of merit ($zT$) values, which reach first peaks at 0.27 and 0.19 along the armchair and zigzag directions, respectively. The current-voltage ($I-V$) characteristics demonstrate an exceptionally strong transport anisotropy, characterized by a substantial current ratio of $I_{\text{armchair}}/I_{\text{zigzag}} \approx 7 \times 10^4$. Furthermore, while the current along the armchair direction increases steadily with the applied bias, transport along the zigzag direction is characterized by a pronounced intrinsic negative differential conductance (NDC). This contrast highlights fundamentally distinct charge transport mechanisms along the two orthogonal axes. Consequently, different directions of this BPN phase of MoS$_2$ can be tailored for distinct nanoelectronic applications, where the armchair and zigzag axes serve as a reliable current switch and an active NDC device, respectively.

The magnetic material MnBi2Te4 (MBT) has garnered significant attention due to its unique combination of long-range antiferromagnetism and nontrivial topological electronic properties. However, experimental measurements report inconsistent magnetizations, which could be attributed to a variety of intrinsic defects. To date, a comprehensive investigation of defect-engineered MBT systems has not yet been established. Employing state-of-the-art $ab~initio$ techniques, this work systematically investigates the influence of various experimentally reported defects on the magnetic properties of bulk and monolayer MBT at different concentrations. Mn-vacancy and Mn-rich defects are found to enhance the ferromagnetism of bulk MBT. The investigation of Mn-rich and intermixing defects in the monolayer reveals that subtle structural and electronic modifications can alter the magnetic coupling. Projection onto a Heisenberg Hamiltonian demonstrates that defects modify exchange interactions, thereby giving rise to distinct magnetic ground states. This work sheds light on magnetic coupling mechanisms and provides guidelines for the experimental control of magnetism in MnBi2Te4.

Single-file transport means no overtaking: particles move in a narrow channel while preserving their longitudinal order. This simple constraint has profound dynamical consequences, most notably tracer subdiffusion, and has made single-file transport a paradigmatic form of confined many-body motion, observed from molecular transport in zeolites to single-file diffusion of colloids in narrow channels. The standard view is that, once overtaking is suppressed, collective transport reduces to that of a strictly one-dimensional file. Here we show that this reduction fails in experimentally relevant finite-width channels: even when exchange is forbidden, the transverse equilibrium structure controls the transport laws and can qualitatively reshape them. Starting from the Brownian dynamics in the full confined geometry, we derive an exact large-scale one-dimensional fluctuating hydrodynamics for the longitudinal density, whose coefficients are fixed by the confined equilibrium equation of state. In the minimal hard-core setting, this yields a collective diffusivity that can become non-monotonic in density. This geometric anomaly propagates to exact large-scale predictions for integrated-current fluctuations, tracer displacement fluctuations and the associated density profiles. The effect is robust to the interaction potential, channel geometry, initial preparation and microscopic dynamics. Quasi-one-dimensional single-file transport therefore defines a distinct regime in which forbidding overtaking does not erase geometry from collective transport.

A previously unreported triangular lattice (TL) antiferromagnet, TmZnGaO4, was synthesized as single crystals, and its crystal structure, magnetic susceptibilities, and specific heat were reported. Its crystal structure is isomorphic to that of the transverse-field Ising antiferromagnet TmMgGaO4, with Tm3+ ions located in the TLs, separated by a nonmagnetic bilayer composed mainly of Ga3+ and Zn2+ ions. The magnetic susceptibilities indicate the dominating antiferromagnetic interactions. The magnetization curves (M-H) exhibit strong easy-c-axis anisotropy, with a clear one-third magnetic plateau emerging, consistent with a field-induced up-up-down spin configuration. Instead of forming a conventional long-range magnetic order, the system exhibits two broad anomalies at 0.11 K and 2.81 K in zero-field specific heat measurements, highlighting the persistence of strong spin fluctuations and the potential for exotic quantum spin states. The above results reveal its future interest in exploring exotic quantum spin states in TmZnGaO4.

The interaction-driven crossover from a Slater insulator to a Mott insulator in the Néel-ordered ground state of the Hubbard model is a fundamental paradigm of strongly correlated electrons, yet its quantitative characterization has remained elusive. Here we establish a clear and experimentally accessible thermal criterion for this crossover via the sign change of the temperature derivative of double occupancy, $(\partial D/\partial T)_U$, near zero temperature. In the Slater regime, $(\partial D/\partial T)_U>0$ reflects the major role of charge fluctuations; in the Mott regime, the anomalous $(\partial D/\partial T)_U<0$, a manifestation of the Pomeranchuk effect, signals the dominance of low-energy spin superexchange physics. Using exact diagonalization and {\it numerically exact} quantum Monte Carlo simulations, we demonstrate that this criterion determines the crossover boundary at $U_{\rm cross}/t=4.0(2)$ for the half-filled two-dimensional Hubbard model. Furthermore, we obtain a consistent boundary independently from the maximum in the antiferromagnetic correlation length, which also arises from the superexchange physics. These two thermal signatures are theoretically unified through the local minimum of thermal entropy versus interaction $U$ at low temperatures. Our results offer a direct, measurable, and physically intuitive framework to identify the Slater-Mott crossover in optical lattice experiments.

We study the local density of states (LDoS) distribution of a general class of weighted Erdős-Rényi graphs. Using the cavity method, we obtain a good approximation to the full LDoS distribution and compact expressions for its power-law tails, which we show to have exponent $3$ in the extended phase. We deduce that the eigenvectors in the continuous part of the spectrum are extended but (weakly) multifractal, and we extract expressions for the associated fractal dimensions and the singularity spectrum. We also demonstrate that the inverse participation ratio in this multifractal phase exhibits an unusual logarithmic scaling with system size, which is neither fully-extended nor localised by the usual definitions. Finally, we verify that some symmetry properties (derived from the non-linear sigma model), which have been shown to hold for many systems exhibiting multifractality, also hold in our case, both for the LDoS distribution and the singularity spectrum.

We investigate optically excited spin dynamics in a uniaxial ferrimagnet near the magnetization compensation point under a magnetic field applied along the magnetic anisotropy axis. Experiment and numerical modeling reveal an unusual regime where the frequencies of two spin eigenmodes approach each other and become highly field sensitive. The modes, corresponding to opposite rotations of the Neel vector, simultaneously reverse their handedness at a critical field where their frequencies become degenerate. At this point, the two-frequency precessional dynamics collapses into a linear oscillations directed along the inverse-Faraday-effect excitation induced by a single pump pulse. We further show that a double-pulse excitation scheme enables control of the spin trajectory. These results uncover an unconventional dynamical regime in ferrimagnets and establish new opportunities for manipulating spin motion in magnonic systems and devices.

We present a new framework for extending Chapman-Enskog theory beyond the hard-sphere fluid model. Rather than relying on effective hard sphere diameters, the approach makes use of on an exchange function which can be related to the thermodynamic properties of the system. We show that two existing extensions, including modified Enskog theory (MET), fit into this new framework. Based on our approach, we propose an alternative to MET that takes into account the potential interaction energy associated with the inter-particle interactions in the fluid. The proposed expression is applied to predicting the shear viscosity of several different simulated fluid models across a wide set of densities $0.05 \leq ρ^* \leq 0.8$ and temperatures $1.5 \leq T^* \leq 4.0$ in Lennard-Jones units. The fluid models considered include both the Weeks-Chandler-Anderson (WCA) fluid and the Lennard-Jones (LJ) fluid. At low and intermediate density, here taken to be $ρ^* \leq 0.3$, we report mean relative prediction errors between $2\%$ and $4\%$ for both these. Across all densities considered, the largest mean relative errors reported are $4.4\%$ and $8.1\%$ for the WCA fluid and LJ fluid respectively. We also investigate other interaction models, including a diatomic molecular model, in order to better understand the limitations of our approach.

We theoretically show that circularly polarized phonons induce electronic magnetization and drive a topological phase transition via phonon Floquet engineering. Considering the electronic states modulated by circularly polarized phonons on a honeycomb lattice, we show that such lattice dynamics generates an effective next-nearest-neighbor electron hopping, leading to a Haldane-type mass term. Circularly polarized phonon breaks time-reversal symmetry (TRS) and opens a gap at valley points, undergoing phase transition from a trivial insulator to a Chern insulator. Moreover, the orbital and spin magnetizations emerge due to the breaking of TRS. Our results show that circularly polarized phonons serve as an effective magnetic field to engineer magnetism and topology, offering new opportunities for phonon Floquet approaches.

We explore the merits of building the Bethe-Salpeter absorption spectrum in a specific energy range using analytic continuation techniques. Specifically, we calculate iteratively a few $\bar{\bar α}(z_k)$ polarizability tensors for a coarse set of $(z_k)$ frequencies in the complex-plane. These data allow constructing a continued-fraction representation for $\bar{\barα}(z)$ that is used to calculate the absorption spectrum close to the real energy axis in the desired energy range. The number and location of these sampling complex frequencies are discussed. The importance of building a continued-fraction representation of the full polarizability tensor with matrix-valued coefficients is emphasized. We show how to extract the poles of the continued fraction as a tool for analyzing the resulting spectra. We study as examples the valence excitations of a paradigmatic dipeptide, the C$_{60}$ fullerene and its PCBM derivative, together with the description of the surface plasmon resonance of the Ag$_{20}$ silver cluster. Further, the high-energy C$_{60}$ X-ray absorption spectrum is explored.