Papers

We investigate the origin of negative threshold voltage shifts in back-gated amorphous IGZO TFTs under positive bias and high temperature stress. Combined DC and 1/f noise measurements reveal that the stress does not generate new dielectric traps but instead broadens the IGZO conduction band tail states. A recovery experiment confirms that the associated threshold voltage, subthreshold swing, and noise degradation are reversible. Simulations using an in-house Poisson solver confirm the experimental observations that high-temperature stress increases hydrogen doping and the density of sub-gap states.

We report on the GPU port of the Abinit high-performance simulation code for plane-wave DFT calculations. Large-scale electronic structure calculations require computing the electronic wave function by solving the Kohn-Sham equations discretized over a large number of plane waves. Porting such calculations to GPU nodes relies not only on extensive usage of vendor libraries from a development perspective, but also on algorithmic revisions of the iterative diagonalization procedure in the resolution of the Kohn-Sham equations to identify GPU-efficient mathematical operations (linear algebra, FFTs) applied to the wave function distributed in memory. The present contribution discusses the Abinit implementation on multi-GPU architectures, providing detailed performance results for heterogeneous CPU-GPU nodes versus CPU nodes. Particular attention is given to comparing two diagonalization algorithms—Locally Optimal Block Preconditioned Conjugate Gradient and Chebyshev polynomial filtering—in terms of GPU efficiency.

We report the motion of individual magnetic Quincke rollers composed of silica particles doped with superparamagnetic iron oxide nanoparticles, whose activity arises from the coupling between Quincke rolling and an externally applied rotating magnetic field. We applied a clockwise (CW) rotating magnetic field of magnitude approximately 11 mT and rotational frequencies ranging from 0.2 to 2.75 Hz. At low frequencies, the dominant mode of motion is a CW helical trajectory. Circular trajectories emerge as a limiting case of this helical motion, in which lateral translation vanishes and the particle traces overlapping closed loops in the xy-plane. At higher frequencies, a second regular mode becomes prevalent, characterized by helical wavy trajectories in which the particle follows a CW helical path with a spatially varying curvature. Under specific conditions, however, we observe the unexpected emergence of anomalous counterclockwise (CCW) trajectories, in which individual particles roll in a direction opposite to that of the applied CW rotating magnetic field. A theoretical model incorporating electrostatic interactions, far-field hydrodynamic coupling, and a magnetic dipole approximation indicates that the anomalous behavior results from the interplay among the magnitude and orientation of the initial magnetic dipole moment, the frequency of the rotating magnetic field, and the magnitude of the initial translational velocity. Together, these factors determine the likelihood of a particle exhibiting regular or anomalous rotational motion.

The solid state reaction method is employed to synthesize Sn1-xInxTe samples. Power Factors of synthesized samples are estimated from resistivity and thermopower data. Modifications in structural parameters, resistivity and thermopower owing to In doping in SnTe thermoelectric material are reported. In-depth structural analysis, employing Rietveld refinement of X-ray diffraction data, confirms the substitution of Sn by In. A minute amount of embedded phases in synthesized samples is revealed from the refinement of X-ray diffraction data. Williamson-Hall and modified Williamson-Hall methods are employed to estimate dislocation density and strain. The highest power factor and maximum host phases are simultaneously achieved for the Sn0.96In0.04Te sample amid the synthesized Sn1-xInxTe samples.

Stacking order in bilayers of transition metal dichalcogenides (TMDs) controls structural symmetry and layer-to-layer interactions, offering a direct route to tune their electronic properties and enable optoelectronic applications. The work function is a key parameter that determines the electronic and optoelectronic device performance. However, a comprehensive understanding of the influence of stacking order on work function of TMDs remains limited. Herein, we employ Kelvin Probe Force Microscopy (KPFM) to probe spatial variations in surface potential and thereby determine the work function of AA'- and AB-stacked MoS2 bilayers grown using NaCl-assisted chemical vapor deposition (CVD) technique. The work function increases with layer number in both AA'- and AB-stacked MoS2, with a larger work function difference in AB-stacked layers, reflecting their stronger interlayer coupling. KPFM measurements clearly resolve local electronic heterogeneities arising from carrier trapping at residual surface particulates from CVD growth. Photoinduced surface potential variations imply n-type doping in MoS2 due to enhanced photogating from trapped holes and Na+ ions at the MoS2/SiO2 interface. Our study demonstrates the competing effects of interlayer coupling, substrate-induced photogating, and carrier trapping by surface particulates in determining the localized optoelectronic response of MoS2 bilayers. Correlative atomic force microscopy measurements in lateral force microscopy and force modulation microscopy modes probe the nanomechanical response to electronic variations. These findings provide new insights into the localized optoelectronic response of CVD-grown AA'- and AB-stacked MoS2, with significant implications for the design and reliability of optoelectronic devices.

We present a strategy for the quantum simulation of many-body lattice models with constrained Hilbert spaces. We focus on lattice gauge theories (LGTs), which underlie a wide range of phenomena in particle physics, condensed matter, and quantum information. In present-day quantum computing platforms, perfect restrictions of the Hilbert space to the desired gauge sectors are beyond reach: for LGTs, violations of the local constraint are unavoidable, posing a formidable challenge for the emulation of the underlying physics. Here, we develop a Floquet-engineering framework that restructures departures from a target sector such that a series of emergent local symmetries occurs hierarchically in time and in a controllable way. This leads to a set of approximate dynamical selection rules that strongly restrict inter-sector couplings, resulting in a pronounced, symmetry-controlled hierarchy of lifetimes for the state population to spread among sectors. Concretely, this protects $U(1)$ LGTs against violations of the {defining} local symmetry. While some sectors remain very long-lived, others are destabilized on shorter timescales. We numerically verify our theory for the one-dimensional $U(1)$ quantum link model. In addition, we reveal that `defects', whose movement accounts for violations of the gauge constraint, are kinetically constrained, becoming mobile only through the assistance of intra-sector dynamics, which we describe using an effective quantum marble model. Our results can thus be used to extend the lifetime, in the spirit of passive error correction, of quantum simulations of complex many-body problems when emergent or desired local symmetries are only implemented approximately.

Resonant inelastic X-ray scattering measurements reveal robust magnetic excitations in the perovskite iridates SrIr$_{1-x}$Sn$_x$O$_3$. We analyzed the dispersions of the magnetic excitation with spin-dilution ratio $x$ = 0, 0.03, 0.06, 0.1, and 0.2, crossing from semi-metal to spin-diluted while antiferromagnetically ordered insulators. The extracted effective magnetic exchange interactions decrease continuously upon increasing spin dilution, and their evolution follows a simple spin-dilution scaling law. These results not only verify the strong electron-correlation nature of the metallic parent SrIrO$_3$, but also reveal the entanglement of the charge and spin dynamics in this system.

The Calogero-Sutherland model is a paradigmatic integrable system describing one-dimensional non-relativistic particles with inverse-square-type interactions. At interaction strength $\lambda=2$, the CSM exhibits a deep connection to anyon physics, featuring the Laughlin-Jastrow polynomial as its exact ground state. Motivated by this structure, we develop a general reverse-engineering construction of positive semidefinite continuum parent Hamiltonians for trial states admitting a rational conformal field theory description with central charge $c<1$. By leveraging the null-vector structure of the underlying primary fields and the associated Belavin-Polyakov-Zamolodchikov equations, we derive corresponding many-body annihilation operators. We then apply this construction explicitly to the Moore-Read and $k=3$ Read-Rezayi states-relating to Ising and Fibonacci anyons, respectively-obtaining continuum Hamiltonians for which these Jack-polynomial states, viewed as one-dimensional chiral spin liquid wave functions, are exact zero modes. We emphasize, however, that our construction does not by itself establish ground-state uniqueness or determine the nature of the excitation spectrum.

The emergence of spin-polarized currents in nonrelativistic platforms continues to attract significant interest in spintronics. Here we demonstrate that a noncollinear kagome antiferromagnet can generate an alternating out-of-plane spin polarization originating from the spin chirality of the magnetic unit cell, in the absence of relativistic spin–orbit coupling. Under spatial confinement, the system develops distinct real-space spin separation patterns whose structure is governed by the symmetry of the lattice termination. In particular, breaking the transverse mirror symmetry of the ribbon produces an altermagnetic-like spin splitting in the band structure. Furthermore, we uncover a spin–edge locking mechanism in which propagating edge states acquire an unconventional spin polarization. These results highlight how magnetic symmetry and confinement can generate spin-polarized transport in coplanar antiferromagnets without relying on relativistic interactions.

In the fermionic liquids, the Fermi surface is topologically stable,\cite{Volovik2003} which is at the origin of the applicability of the Landau theory of Fermi liquid (LFL). The LFL exists under special condition, when the Green's function has a pole with nonzero residue $Z$. Otherwise one has non-Landau Fermi liquid (NLFL), such as Luttinger liquid, which is described by the same topological invariant. It appears that in general this topological invariant is the property of the fermionic particle, i.e. the particle charge (or the electric charge of electron) is equivalent to the topological charge of the fermion. The conservation of the fermionic charge is equivalent to the conservation of the topological charge. We consider the application of this topological charge to the Landau theory of Fermi liquids. We also consider the application to non-Fermi liquids and crystalline insulators in relation to the Luttinger theorem.

We report on the microscopic superconducting properties of the Dirac semimetal PdTe2. In this study, we have focused on mosaic crystals of PdTe2, and used detailed zero field and transverse field muon spin relaxation/rotation ($\mu$SR), ac-magnetic susceptibility, and resistivity measurements to investigate their superconducting properties. The magnetic susceptibility measurements reveal two superconducting transition temperatures at 1.8 and 1.6~K, respectively, in agreement with earlier reports. In contrary to these reports, we find that these mosaic PdTe2 crystals, are not type-I, but rather type-II superconductors. In fact, we observe the clear manifestation of a flux line lattice through a clear diamagnetic shift and Gaussian broadening of the Fourier spectra in the superconducting state. This behavior is likely caused by the disorder in the mosaic crystals of PdTe2 studied here. Our analysis of the superconducting order parameter by the means of temperature dependent magnetic penetration depth $\lambda(T)$ reveals a fully gapped superconducting state that can be well-fitted using an s-wave symmetric gap. We find that PdTe2 is a promising model system for the investigation and interplay of non-trivial topology, surface superconductivity, and type-II bulk superconductivity in a van-der-Waals material. Moreover, our results indicate that the superconductivity in this material can be easily modified from type-I to type-II by disorder in the system.

We propose algebraic closure as a stabilizing mechanism for quantum many-body scar subspaces, showing that scar states need not rely on an embedded equally spaced spectrum or analytical solvability. We formulate Lie-algebraically closed invariant subspaces and construct local quantum many-body Hamiltonians that preserve an $\mathfrak{su}(N)$-invariant scar subspace but need not act diagonally within it. Such non-diagonal action mixes the conventional tower states while preserving the multidirectional lattice-like spectral structure, allowing nonthermal dynamics and persistent multifrequency oscillations to survive even when individual scar eigenstates become analytically intractable.

Recent experiments on K3C60 revealed a giant enhancement of the light-induced superconducting-like optical response for pump frequencies near 10 THz, with an efficiency roughly two orders of magnitude larger than for off resonant excitation. Here we show that a resonant enhancement of pair correlations arises naturally in a driven purely electronic model of K$_3$C$_{60}$ with ab initio parameters. The underlying mechanism is a symmetry constrained two-photon pathway: the first photon drives the system from the even-parity ground state to an intermediate odd-parity manifold, while the second photon induces a transition to an even-parity excited state with enhanced pair correlations. Larger-cluster calculations show that the corresponding resonance energy is strongly renormalized downward with system size and connectivity, reflecting the kinetic-energy gain of delocalized photo-excited doublon-holon configurations. A simplified single-orbital model reproduces this scaling trend and reaches a 14-site fcc cluster, where the resonant peak is pushed to 30 THz, with a trend compatible with a further reduction toward the experimental 10 THz scale in larger systems. Varying the Hubbard coupling strength, we find that the resonance is lowest and the pairing enhancement strongest near intermediate couplings, where doublon-holon excitations are both well defined and mobile. Our results establish a purely electronic mechanism for resonant light-enhanced pair correlations in K$_3$C$_{60}$ and support the interpretation of the experimental 10 THz resonance as optical access to a paired many-body excited state rather than improved metallicity. More broadly, they suggest that related resonant pathways may arise in other intermediate-coupling Hubbard materials.

Interatomic potentials which accurately describe long-range electrostatics require atom-centred charges. One such method to determine these atom-centred charges from density functional theory (DFT) calculations is the density-derived atomic point (DDAP) charge method. DDAP fits atom-centred Gaussians to the ground-state DFT charge density and preserves the multipole moments that govern long-range electrostatics. While these charges accurately predict long-range behaviour, in practice, they are limited by their reliance on fixed, heuristic parameters and a constrained solver that becomes numerically unstable for complex or covalent systems. In this work, we present opt-DDAP, which solves this limitation by reformulating the algorithm as a differentiable computational graph. This reformulation allows for the optimisation of Gaussian basis parameters and the reciprocal-space cutoff using automatic differentiation. To ensure numerical robustness through this automatic differentiation process, we replace the conventional Lagrange-multiplier approach with a pseudo-inverse solution followed by charge renormalisation, maintaining stability even in the presence of ill-conditioned matrices. We validate the framework on NaCl vacancy supercells and on MoS$_2$, demonstrating faithful reconstruction of both absolute and difference charge densities. The optimised charges are intended to serve as inputs to effective electrostatic models in machine-learning and empirical interatomic potentials that incorporate long-range interactions.

Diffusion models generate high-dimensional data such as images by learning a process that gradually removes noise from corrupted data. Recent studies have shown that the backward dynamics of diffusion models exhibit two characteristic transitions: the speciation transition, at which generated samples begin to capture the global structure of the training data, and the collapse transition, at which the generation dynamics starts committing to individual training samples. While these transitions have been theoretically analyzed for continuous data, the same theoretical criteria have not been applied for discrete diffusion models, which are diffusion models for discrete data. In this work, we propose a simple effective model for discrete diffusion models trained on two-class Ising variable data with a general mixture ratio and analyze its backward dynamics using methods from statistical mechanics. We show that, as in the previous study on continuous data, the speciation transition can be determined through a second-order phase transition analysis using high-temperature expansion, while the collapse transition corresponds to a condensation transition described by the Random Energy Model. An analytical expression for the speciation time is obtained, and we show that its scaling becomes consistent with that of the continuous case when the noise increases with time as in practical diffusion models. These theoretical predictions are confirmed by numerical simulations and experiments with trained discrete diffusion models on real datasets. These results suggest that the original theoretical framework for continuous data remain valid for discrete data, and may provide a useful starting point for the statistical-mechanics analysis of discrete generative diffusion in more realistic settings.

The study of magnetism in transition metals is a cornerstone in understanding complex electronic and magnetic interactions in condensed matter systems. Among transition metal elements, body-centered cubic (bcc) chromium stands out because of its spin-density wave (SDW) ground state, posing a long-standing challenge for density functional theory (DFT). Conventional functionals, such as the generalized-gradient approximation (GGA) and the local-density approximation (LDA), fail to predict this experimentally observed incommensurate SDW as the ground state. In this study, we present a comprehensive DFT analysis of bcc Cr employing GGA and a variety of meta-GGA functionals. We evaluated total energies, structural parameters, and magnetic properties across a wide range of SDW wave vectors. Our results show that all meta-GGA functionals overestimate the local magnetic moments and enhance the nodal magnetic frustration, destabilizing the SDW state relative to the commensurate antiferromagnetic (AF) configuration. Tao-Perdew-Staroverov-Scuseria (TPSS) yields results closest to those of the GGA, thus providing the most adequate description of bcc Cr among the meta-GGA functionals. These results emphasize the need for the further development of non-local or hybrid functionals tailored for complex magnetic systems.

Free-fall atom interferometers offer a powerful platform for accurate, absolute gravitational sensing. Szigeti et al. [Phys. Rev. Lett. 125, 100402 (2020)] recently proposed a quantum-enhanced scheme that uses a spin-squeezed Bose-Einstein condensate as an input state to improve the phase sensitivity of the interferometer. The spin squeezing, generated via one-axis twisting interactions, was limited by condensate expansion. Here we present an improved state preparation in which a sudden trapping potential – a delta kick – is initially applied to focus the condensate. The resulting increase in density enhances the one-axis-twisting interactions and produces greater spin squeezing. Using multimode truncated-Wigner simulations, we quantify the performance of the interferometer and find that, for an optimal kick strength, the phase sensitivity surpasses the standard quantum limit by a factor of $\sim 20$. This represents a fourfold improvement over the original scheme without the delta kick and is well captured by a two-mode approximation.

Hydrodynamic coarsening of bicontinuous domains is a central process in liquid-liquid phase separation, yet how soluble surfactants regulate this process remains poorly understood. Using a validated two-order-parameter phase-field model coupled to the incompressible Navier-Stokes equations, we show that hydrodynamic coarsening is suppressed primarily by surfactant-induced Marangoni stresses rather than by the reduction of mean interfacial tension alone. These stresses hinder interfacial coalescence, reorganize the local vortical flow, and thereby redirect the morphological evolution of bicontinuous domains. A central result is that this suppression depends non-monotonically on the surfactant Péclet number, with the strongest inhibition occurring at an intermediate value, $Pe_\psi=10$, rather than at $Pe_\psi=1$ or 100. Analyses of force evolution, interfacial surfactant statistics, and decomposed surfactant flux budgets show that this non-monotonicity arises from a competition between surfactant replenishment and gradient retention. At low $Pe_\psi$, diffusion efficiently replenishes the interface but smooths interfacial concentration gradients; at high $Pe_\psi$, advection preserves interfacial heterogeneity but leaves the interface insufficiently supplied with surfactant. The strongest suppression therefore occurs when sufficient interfacial surfactant loading coexists with persistent concentration gradients. These results establish a transport-controlled mechanism by which soluble surfactants regulate bicontinuous hydrodynamic coarsening.

Forecasting extreme precipitation is essential yet challenging due to its rarity and complexity. We develop a large deviation framework to estimate the return times of extreme precipitation events. We first find that the Landau distribution, originally introduced in plasma physics, accurately captures extreme precipitation at approximately 93% of global locations, outperforming conventional extreme value distributions with 76% matched locations under the same accuracy criterion. Enriching rare event samples by the fitted Landau distribution, we obtain more accurate estimates of large deviation rate functions and return times, enabling forecasts beyond historically observed precipitation intensities. Mapping historical return times to future projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we show that return time curves under different emission scenarios collapse onto a unified relation, revealing a sharply increased lifetime exposure to extreme precipitation for 21st-century birth cohorts under most future emission scenarios.

We introduce a lightweight universal machine-learning interatomic potential (uMLIP), SevenNet-Nano, based on the graph neural network architecture SevenNet and enabled by a knowledge-distillation framework. The model inherits the broad generalization capability of a large multi-task foundation model, SevenNet-Omni, trained on diverse materials datasets across chemical, configurational, and computational spaces. By learning chemical representations from high-quality inference data generated by the teacher model within a unified computational framework, SevenNet-Nano achieves high accuracy and strong transferability despite its compact architecture. The model also accurately captures a wide range of interatomic interactions, enabling reliable simulations under both equilibrium and extreme conditions, including plasma etching of SiO$_2$. Comprehensive benchmarks on static and dynamical properties–such as Li-ion diffusion and liquid densities–demonstrate its broad applicability with minimal fine-tuning. Importantly, SevenNet-Nano significantly reduces computational cost, achieving over an order-of-magnitude speedup and enabling large-scale atomistic simulations involving thousands of atoms.

Halide perovskites are promising optoelectronic materials, but their time-dependent permanent deformation under illumination (i.e., photo-creep) is poorly understood, limiting their mechanical stability. Here we report wavelength-dependent photo-creep phenomena in CsPbBr3 and FAPbBr3 single crystals, studied by constant-load nanoindentation under controlled light with various wavelengths. Compared with creep in dark, continuous green light (near-bandgap) suppresses creep by 19% in CsPbBr3 and 10% in FAPbBr3, whereas violet (far above-bandgap) light enhances creep by 16% in CsPbBr3 and 8% in FAPbBr3. In contrast, when light is onset during creep, blue light enhances creep most prominently, whereas green light exhibits minimal influence. Such photo-creep behavior in halide perovskites are distinct with photo-plasticity phenomenon in conventional semiconductors. By combining the photoluminescence and photocurrent measurements, we unveil that ion migration promotes dislocation climb and creep, while carrier trapping suppresses dislocation glide and related creep in halide perovskites. Such competition between carrier trapping and ion migration tuned by wavelength governs the photo-creep response. Our findings uncover a photomechanical effect in halide perovskites and highlight how coupled carrier and ion dynamics under illumination affect their device reliability.

We investigate localization properties of the Apollonian network (AN) in the presence of diagonal and off-diagonal disorder. By employing a site-resolved localization measure, we show that the localization degree is strongly dependent on the energy and tied to the hierarchical topology of the network. At the spectral edges, eigenstates are strongly localized on highly connected sites originating from previous generations, a behavior that persists under both disorder mechanisms. In contrast, around zero energy localization is associated with the lowest-degree sites. As disorder breaks the underlying C3 symmetry of the AN, it promotes spatial reconfiguration of these states while preserving their support on low-degree nodes. For diagonal disorder, localization is enhanced over a broad range of negative energies, whereas off-diagonal disorder induces weakening of localization in this region. Finally, we show that the hub dominates the spectral edges but has negligible contribution near the band center, indicating that its associated localized states are robust against disorder. These results highlight how topology and disorder jointly shape localization in complex networks.

The computational demands of deep learning motivate the investigation of alternative approaches to computation. One alternative is physical neural networks~(PNNs), in which learning and inference are performed directly via physical processes. Stochastic PNNs arise when the underlying neurons are realized by the dynamics of a stochastic activation switch. Here we propose novel electronic and photonic stochastic neurons. The electronic realization is implemented by single-electron tunneling through a quantum dot. The photonic realization is implemented via a single-photon source driving one of two modes coupled via a controllable beam-splitter-like interaction. In the electronic case, the charge state of the quantum dot forms the basis for the stochastic neuron, whereas in the photonic case the occupation of the undriven mode serves as the basis for the stochastic neuron. Training of stochastic PNNs is performed with models of stochastic neurons, as well as with coherently-driven, single-photon detector stochastic neurons previously introduced. Several training strategies for MNIST handwritten digit classification have been investigated using single-hidden-layer stochastic PNNs, including varying the number of trials in each layer to control forward pass stochasticity and employing either true probability or empirical outputs in the backward pass to evaluate their influence on gradient estimation. We show that when empirical outputs are used in the backward pass, the network achieves more than 97% test accuracy with few trials per layer. Despite the simplicity of the model architecture, high test accuracy is maintained in the presence of a high degree of noise and model uncertainty. The results demonstrate the potential of embracing stochastic PNNs for deep learning.

We study a relativistic scalar field model for self-bound Bose-Einstein condensates (BECs) by analyzing a nonlinear Klein-Gordon equation with cubic and logarithmic interactions. This framework captures essential features of quantum droplets, such as self-trapping and finite energy configurations, which emerge from the interplay between attractive and repulsive terms. By performing the non-relativistic limit, we derive a generalized Gross-Pitaevskii equation with a logarithmic correction, consistent with recent models used to describe ultra-cold atomic gasses beyond mean-field theory. We construct the corresponding Lagrangian density, identify conserved quantities via Noether's theorem, and compute the energy-momentum tensor. Numerical solutions of the BEC parameters are shown, establishing the foundations for a field theoretical description of relativistic condensates with a logarithmic interaction. This model provides a unified approach to investigate relativistic effects in quantum droplets and enriches the theoretical landscape of Bose-Einstein condensates with non-standard interactions. The resulting dynamics exhibit stable oscillatory regimes consistent with self-bound condensate configurations.

We discuss a no-go theorem for Bose-Einstein condensation (BEC) of quasiparticles (phonons) from the viewpoint of operator algebras, using the van Hove model. The $\beta$-KMS states of the van Hove model satisfy the self-consistency condition of arXiv:1207.4621. However, the self-consistency condition is a constraint concerning the definition of the field, and is insufficient to establish the no-go theorem for BEC. In this paper, we prove the no-go theorem for BEC via two routes. First, imposing time cluster properties on the $\beta$-KMS states precludes BEC. Second, under nonlinear dispersion with $s > 2$, the treatment of infrared divergences automatically reduces the algebra of physical observables, and BEC is mathematically excluded on the reduced algebra. In particular, the latter property admits an interpretation in terms of the ideal theory of the resolvent algebra.

We investigate the nonequilibrium dynamics of the weak-coupling Hubbard-Holstein model after a sudden switch-on of the electron-phonon interaction within nonequilibrium dynamical mean-field theory (DMFT). Using the self-consistent Migdal approximation for the electron-phonon coupling together with second-order perturbation theory for the electron-electron interaction, we show that the relaxation dynamics exhibits a crossover between electron-dominated and phonon-dominated regimes, extending to finite Hubbard interaction the scenario previously identified in the Holstein model. To investigate the microscopic buildup of the thermal state, we analyze the dynamics within the Step-by-Step DMFT framework. In the plane of real time and DMFT iteration number, thermalization is marked by a sharp propagating front. This front appears in electronic observables already for weak quenches within the simulated time window, whereas the phononic sector exhibits a visible front only at sufficiently strong coupling. Thus, at weak coupling the local dispersionless phonons show a delayed onset of front formation, while near and beyond the crossover the front develops on comparable timescales in both the electronic and phononic sectors. Whenever both fronts are resolved, they propagate with the same velocity, showing that thermalization spreads coherently through the coupled electron-phonon system.

The macroscopic dynamics of topological defects in magnetic materials are traditionally modeled using pairwise interactions. However, higher-order quantum exchange mechanisms - such as biquadratic and 4-spin ring exchange-play a critical role in strongly correlated systems. In this work, we introduce the "Simplicial Bridge," an exact analytical framework that maps these high-dimensional, non-linear Landau-Lifshitz partial differential equations onto generalized Kuramoto phase-oscillator networks operating on abstract simplicial complexes. We rigorously demonstrate that spatial overlap in the continuous limit natively generates higher-order topological forces without requiring a supportive discrete atomic lattice. Specifically, the overlap of 1D helimagnetic kinks generates 2-simplices (triadic forces), while the spatial compression of 2D skyrmion tails - governed by modified Bessel function asymptotics - generates true 3-simplices (tetradic forces). Furthermore, we establish that the higher-order spatial derivatives inherent to these multi-spin interactions provide an intrinsic energetic barrier that bypasses Derrick's Theorem, stabilizing 2D topological solitons without the strict need for Dzyaloshinskii-Moriya Interaction (DMI).

Vacancy-induced structural reconstruction provides a general microscopic route to $d$-wave altermagnetism in two-dimensional systems. As a concrete realization, reconstructed $\mathrm{V_2X_2}$ ($\mathrm{X}=\mathrm{S}, \mathrm{Se}$) monolayers form an inverse Lieb magnetic network in which two inequivalent edge vanadium sites, related by $C_4$ lattice rotational symmetry and carrying opposite exchange fields, yield zero net magnetization despite broken time-reversal ($\mathcal{T}$) and combined inversion–time-reversal ($\mathcal{PT}$) symmetries. Structural stability is confirmed by formation energies, phonon spectra, and $ab$ $ initio$ molecular dynamics simulations at room temperature. A minimal tight-binding model, incorporating anisotropic second-order hopping between the inequivalent magnetic sites mediated by a nonmagnetic corner site, produces spin splitting with a $(\cos k_x - \cos k_y)$ form factor in quantitative agreement with first-principles calculations. The resulting spin splitting is strongly anisotropic, maximized near the $X$ and $Y$ high-symmetry points and exhibiting a symmetry-enforced nodal degeneracy at $M$, consistent with a $d_{x^2-y^2}$ altermagnetic form factor confirmed by the fourfold Fermi surface pattern. These findings establish vacancy-driven reconstruction of an inverse Lieb magnetic network as a general design principle for two-dimensional $d$-wave altermagnets.

We derive a bound on the efficiency of thermal engines that can be sharper than Carnot's limit. It is a function of statistical correlations between the engine internal state and Hamiltonian, can be saturated even in finite-time cycles, and applies to both classical and quantum engines. Specifically, the bound establishes the exact maximal efficiency of engines operating with multiple baths, tightening the upper limit set by Carnot's theorem. Then, we show that an engine made of a quantum dot coupled with fermionic baths can achieve the bound, even when operating beyond the quasistatic regime. The result provides a design principle for realistic energy harvesting machines.

Tunable interactions make ultracold quantum gases a unique platform for exploring hydrodynamic properties in the strongly correlated regime. Of particular interest are turbulent flows possible in the regime of high Reynolds numbers. Since the system size and flow velocity are limited in experimentally realistic systems, we propose an alternative approach to enhance the Reynolds numbers in an ultracold Fermi gas by minimizing the shear viscosity in the vicinity of the Feshbach resonance. By employing the Keldysh formulation of the linear response theory, we theoretically demonstrate that the shear viscosity can vary by several orders of magnitude in the vicinity of the BCS-BEC crossover. It is also shown that while Drude-like contributions generally dominate at large Feshbach detunings, higher-order vertex corrections, including the Maki-Thompson contribution, become significant and suppress singular behavior in the near-resonant regime. Our results provide a roadmap for achieving tunable Reynolds numbers in ultracold quantum fluids, which can serve as table-top turbulence simulators.