Papers

Stochastic binary networks are widely used to describe collective dynamics in complex systems and to perform neuromorphic computation, yet realistic networks often contain both asymmetric interactions and finite signal propagation times that fall outside conventional theories. Here we study stochastic binary networks with asymmetric and time-delayed interactions motivated by experimental observations in coupled superparamagnetic tunnel junctions. We find that time delay fundamentally reshapes the dynamics induced by anti-symmetric couplings, producing strong oscillatory temporal correlations consistent with experiment. At the same time, sufficiently long delays drive the steady-state probabilities toward equal state occupations even in strongly coupled systems. These apparently featureless probability distributions coexist with pronounced temporal correlations, distinguishing them from equilibrium high-temperature behavior. We further show analytically that delay-induced uniform distributions emerge in a broad class of stochastic networks, while symmetry-breaking bias fields restore interaction-dependent steady states with qualitatively modified behavior. Simulations of networks with five coupled spins demonstrate that these effects persist beyond minimal systems with only two spins. Our results establish a unified framework for stochastic binary networks in the intermediate regime between symmetric instantaneous interactions and asymmetric or time-delayed interactions, and suggest that asymmetry and delay can be exploited as functional resources in neuromorphic hardware and complex network dynamics.

The recent emergence of altermagnetism has opened new frontiers in condensed matter physics, yet material platforms capable of hosting both intrinsic altermagnetic order and superconductivity remain exceedingly rare. Here, based on symmetry analysis and first-principles calculations, we propose a realistic route to engineer robust altermagnetism in monolayer FeSe, a prototypical iron-based superconductor. By designing a stoichiometric Fe2Se2Cl structure through single-side Cl adsorption and introducing gate-tunable hole doping, we achieve a highly stable altermagnetic ground state. Our calculations reveal a synergistic mechanism: hole doping firmly stabilizes the checkerboard magnetic order, while the asymmetric ligand environment intrinsically breaks the outof-plane spatial inversion symmetry. Consequently, this interplay induces a giant altermagnetic spin splitting of up to 620 meV. Crucially, we demonstrate that this altermagnetic state and its giant spin splitting are highly resilient, persisting even in a 10-layer slab model that accurately simulates the bulk limit. By introducing altermagnetism into the well-established FeSe-based superconducting family, our findings identify Fe2Se2Cl as a promising platform for spintronic applications and motivate future studies of the possible interplay between altermagnetism and superconductivity.

Gyrotropy in twisted bilayer graphene can be used as a signature of interlayer electronic coupling. Gyrotropy can emerge in the absence of interlayer coupling in time-reversal symmetric bilayer systems. This gyrotropy originates from the extrinsic geometry associated with the physical geometry of the system and is independent of the structure of the electronic states. We first illustrate this effect for a purely classical bilayer array of one-dimensional wires. Next we study pristine twisted bilayer graphene and show that the gyrotropy is entirely due to interlayer coupling. Finally we consider twisted bilayer MoTe2, first as a pristine model where the gyrotropy exactly vanishes, and then with weak strain and displacement fields where we show that the geometric gyrotropy can dominate the gyrotropy due to interlayer coupling. Our results call attention to the necessity to separate the contribution of extrinsic physical geometry from the contribution of intrinsic electronic states to the properties of twisted materials.

We investigate the effects of excited normal modes on vortex dynamics in the Abelian Higgs model in the type I (static attraction) and type II (static repulsion) regimes. We demonstrate that shape normal modes compete with the static inter-vortex forces. This can result in excited type I (II) vortices repelling (attracting). In addition we observe the existence of spectral walls that prevent the formation (break up) of bound states in type I (II) systems. We study the long lived quasi-bound states and orbits induced by their competing forces and the effective centrifugal forces. Finally, we observe that the effect is strong enough to induce vortex-antivortex pairs to follow long-lived orbits.

We develop a backpropagation algorithm for evaluating parameter gradients in quantum circuits using Pauli propagation simulation. The method has computational complexity comparable to that of standard sparse Pauli simulation techniques, while producing gradients whose accuracy is of the same order as the corresponding observable expectation values. By exploiting the reversibility of quantum circuits, the algorithm reduces the memory cost by a factor of $\mathcal{O}(n_\text{param})$ compared with conventional reverse-mode automatic differentiation, where $n_\text{param}$ denotes the number of parameters in the circuit. Compared with finite difference methods, the algorithm is $\mathcal{O}(n_\text{param})$ more efficient in function evaluations. These features enable efficient and accurate classical optimization of quantum circuits for applications such as state preparation and time-evolution compression, while also allowing operator-complexity measures such as the operator stabilizer Rényi entropy to be monitored and regularized during optimization. We demonstrate the method by optimizing low-energy state-preparation circuits for transverse-field Ising models in one, two, and three dimensions and for the three-dimensional Heisenberg model, and by compressing two-dimensional time-evolution circuits.

Dissipative preparation of quantum order offers a route to superconductivity that does not rely on enhancing attractive interactions. Here we propose a driven-dissipative protocol to prepare superconductivity as a stationary state of a two-dimensional moiré heterostructure. The key ingredient is a bilayer moiré platform in which the layer degree of freedom acts as a pseudospin, allowing the pseudospin structure required for pairing to be implemented through optically induced spatial operations. This preparation scheme requires local dissipation, which we show to arises naturally from weakly dispersive bosonic modes in the heterostructure. In contrast, in the opposite regime of collective dissipation, the same platform exhibits an early-time superradiant burst. Our results establish driven-dissipative moiré heterostructures as a promising platform for preparing superconductivity, while also revealing a connection between steady-state pairing and transient superradiance.

The corner transfer matrix renormalization group (CTMRG) is one of the standard contraction methods for infinite projected entangled-pair states (iPEPS), but its computational cost is dominated by repeated truncated singular value decompositions (SVDs). We introduce subspace-iteration CTMRG (SI-CTMRG), a QR-based projector construction that replaces each large-matrix SVD with an SVD of a much smaller matrix. The resulting algorithm shifts the dominant cost from decompositions to tensor contractions, making it highly suited to GPU acceleration and yielding speedups of up to two orders of magnitude over standard CTMRG. We demonstrate the efficiency and accuracy of the method for the triangular-lattice Heisenberg antiferromagnet, reaching state-of-the-art iPEPS results on a single H100 GPU in approximately 10 hours of computation.

Quantum many-body scars provide an exception to generic thermalising dynamics, but their relation to integrability remains unclear. Here we apply the periodic-orbit framework to the integrable XYZ/XXZ spin-1/2 chain, developing an energy-resolved approach that enables us to locate and track periodic orbits across the spectrum. We identify families of scarred orbits and resolve their supporting eigenstates in terms of Bethe-ansatz quantum numbers, revealing a common string core dressed by zero-momentum magnon pairs. This allows us to reconstruct both the scarred eigenstates and the associated towers directly within the Bethe ansatz, and explain the equidistant tower spacing analytically from the decoupling of zero-momentum magnon pairs in the Bethe equations, providing a microscopic realisation of scar phenomenology in an integrable setting. We further show that this structure persists upon breaking integrability with a transverse field, with the periodic orbits continuing to govern the dynamics. Our results establish a direct connection between the periodic-orbit picture of quantum scarring and the algebraic structure of integrable models, showing that key features of scar dynamics can be understood analytically within the Bethe ansatz framework.

The concept of finite entanglement scaling forms one of the pillars on which the tensor network ecosystem is built. In this paper, we resolve the open problem of determining the actual perturbations induced by matrix product state approximations of critical systems, and we demonstrate that these can be quite different than the ones predicted by conformal field theory. To that aim, we develop a sparse linear solver to calculate the forward and backward derivatives of 2-dimensional tensor networks with respect to their defining parameters in an implicit way. This algorithm is of independent interest as it provides a primitive for the variational optimization of projected entangled pair states that circumvents the instabilities plaguing traditional automatic differentiation methods.

Hysterons provide a minimal description of memory in driven matter: bistable elements with distinct switching thresholds whose interactions generate hysteresis, avalanches, and return point memory or its violation. Experimental realizations have so far been dominated by solid state mechanical systems, where bistability is usually encoded structurally through buckling, snap through, or geometric incompatibility. Here we realize hysteron physics through a hydrodynamic route. A single elastic fiber anchored in a microfluidic channel becomes bistable through nonlinear elastohydrodynamic feedback: viscous loading deforms the fiber, deformation reshapes hydraulic resistance, and flow redistribution modifies the loading. This feedback produces a fluidic hysteron whose onset is organized by a cusp catastrophe in geometric control parameters. A parallel bypass channel acts as a geometric load line that reshapes, and can even eliminate, bistability while simultaneously mediating long ranged hydraulic interactions between fibers. In arrays, varying a single geometric parameter drives a transition from a non interacting Preisach regime with return point memory to an interacting regime with avalanche like switching and return point memory violation. These results establish a passive hydrodynamic route to hysteron networks, in which memory emerges from flow structure feedback and global hydraulic constraints rather than solid state multistability or external control.

In CrSBr, as in many crystalline materials, the type and density of defects are expected to strongly influence material behavior. Identifying the underlying atomic defect configurations and controlling their populations during growth are therefore important steps toward understanding and ultimately tailoring its rich magneto-electrical properties. However, systematic control of defects in CrSBr during chemical vapor transport (CVT) growth has not yet been established. Here, we correlate CVT growth conditions with defect concentrations measured using conductive atomic force microscopy (CAFM). We focus on a characteristic defect with a strong electronic fingerprint, labeled D*, and decrease its concentration by up to an order of magnitude through optimized growth conditions. We show that defect densities can be tuned by adjusting precursor stoichiometry, where sulfur- and bromine-rich conditions suppress defect formation, and by lowering the absolute growth temperatures while maintaining the same temperature gradient. Thermodynamic modeling and density functional theory calculations suggest that D* is most consistent with a sulfur-related vacancy complex rather than an isolated point defect. These results provide practical strategies for growing high-quality CrSBr with controlled defect densities.

We introduce a thermodynamic theory of voting and show that it provides a good description of distribution of party votes in EU elections. The theory traces parallels between system energies of coupled nonlinear oscillators and party vote fractions. Such a classical system evolution is characterized by the conservation of total energy and probability norm that leads to the Rayleigh-Jeans (RJ) thermalization and condensation at low energy states. A similar thermalization also describes the wealth inequality in society. This feature belongs to the phenomena of constraint driven condensation known in statistical mechanics. We show that the RJ theory well depicts the Lorenz and Pareto curves obtained from the EU vote results. The theory also recovers the dispersion of votes between candidates of first round presidential elections in France.

Magnetic materials support both time-reversal-even (T-even) and time-reversal-odd (T-odd) spin Hall currents, yet their underlying microscopic origins remain elusive. Here, we elucidate the spin Hall effect (SHE) in collinear ferromagnets by treating spin-orbit coupling (SOC) as a perturbation that breaks spin-group symmetry, thereby revealing how magnetic order activates distinct spin Hall response. To first order in SOC, we identify two dominant T-even SHE mechanisms: a magnetization-independent conventional contribution and a magnetization-dependent channel associated with anomalous Hall charge transport. At the same order, the leading T-odd magnetic spin Hall effect (MSHE) originates from the exchange interaction between the conventional spin current and the local magnetization. At second order in SOC, we further uncover a distinct T-odd planar spin Hall mechanism. Our spin-symmetry analysis is corroborated by first-principles calculations, which reveal a pronounced anisotropic magnetic spin Hall effect whose magnitude can be comparable to the T-even spin Hall conductivity (SHC) when the magnetic moment is tilted away from the principal crystallographic axes. These findings clarify the microscopic origins of the SHC in collinear ferromagnets and pave the way for ferromagnet-based spin current sources with versatile properties in spintronic applications.

Cr2AlC MAX phase is synthesized by high-pressure solid-state annealing and investigated as a candidate platform for optically responsive magnetism. Structural characterization confirms the formation of the Cr2AlC phase, while magnetic and optical-magnetic properties are examined by superconducting quantum interference device (SQUID) magnetometry, electron spin resonance (ESR), and first principles calculations. SQUID magnetometry identifies Cr 2AlC as a weak, field-linear metallic paramagnet dominated by Pauli-like susceptibility of itinerant Cr-derived states. Its non-monotonic temperature dependence is described by an additional contribution from antiferromagnetically coupled Cr-Cr dimers, whereas the low-temperature Curie-like upturn originates from only a trace population of localized Cr centers. Under red-light illumination, SQUID magnetometry does not reveal an intrinsic macroscopic optomagnetic response. In contrast, ESR at 4 K shows a reversible light-induced reduction of a local magnetic signal, but the optically modified spin population corresponds only to several tens of ppm of the Cr sublattice. Ab initio Bethe-Salpeter equation (ai-BSE) calculations combined with the maximally localized Wannier function analysis suggest that optical excitation can redistribute spin polarization between neighboring Cr sites with the opposite local moments. The combined experiment-theory approach therefore establishes the hierarchy of magnetic contributions in Cr 2AlC and identifies the microscopic origin of its local optical sensitivity. This provides a reference for designing MAX phases and related MXenes in which defects, surface terminations or reduced dimensionality may enhance optically active magnetic states.

Magnetic monopoles lie at the crossroads of gauge fields, topology, geometric phases, and charge quantization, yet they remain elusive as fundamental particles. Here we show that an emergent Dirac-monopole framework arises naturally from the dynamics of massive quantum vortices in a spherical superfluid shell. Their dynamics is formally equivalent to that of interacting charged particles constrained to a sphere in the field of a magnetic monopole. The monopole charge is fixed by the superfluid density and automatically satisfies Dirac's quantization condition. The emergent monopole description predicts cyclotron-like vortex motion, in quantitative agreement with Gross–Pitaevskii simulations. We further show that topological frustration induced by two like-charged polar vortices gives rise to the formation of an equatorial vortex necklace, a configuration reminiscent of the polygonal cyclone clusters observed around Jupiter's poles, before its subsequent breakup through a Kelvin–Helmholtz-like instability. Within this framework, the equatorial vortex necklace emerges as the quantized realization of the effective electrostatic line charge that restores global charge neutrality on the sphere. Our results establish spherical superfluids as a versatile platform for realizing and exploring fundamental aspects of Dirac-monopole physics.

We employ a mathematically equivalent form of the GKLS master equation to arrive at an exact theoretical description of a two-level system strongly coupled to the environment. The framework, while intuitive, shedding light on the physics of the problem, and agreeing with existing results, such as thermalisation to a non-canonical state, is based around three parameters that are unknown outside of the weak coupling regime – the analogue to the detailed balance relation, and two coupling strength constants. As a way forward, we propose a feasible experimental protocol based on a solid-state electronic quantum dot device, through which the fundamental parameters of the problem can be revealed, which would further the fundamental understanding of strong coupling.

The coupled dynamics of local fields exert a drastic influence on the light-activated self-propulsion of a Janus particle in a binary solvent under spatial confinement. In this work, we investigate this problem using numerical simulations that account for local phase separation and wetting phenomena, as well as hydrodynamic effects. We find that confining the binary solvent within a channel results in a reduction of the active particle's propulsion speed and an extension of the duration of its directed motion. Furthermore, the orientational dynamics of this self-propelled particle are not restricted to two dimensions, unlike the phenomenon known as "orientational quenching". Increasing the light intensity leads to strong fluctuations in the local fields and, consequently, in the particle's speed. In this context, the significance of key physical parameters governing the efficiency of particle motion control is elucidated.

Dissociative chemisorption (DC) of H$_2$ on the Cu(111) surface is a prototypical problem for understanding elements of heterogeneous catalysis [Science 326, 832 (2009)]. The challenge lies in modeling the reaction dynamics that in turn reflects a classical potential for atomic deformations, friction, and inelastic scattering. Here, I test the use of a set of range-separated hybrid (RSH) van der Waals density functionals (vdW-DFs) [JPCM 37, 211501 (2025)] on their ability to describe the classical barrier for dynamics in this H$_2$+Cu(111) DC problem. I furthermore document use of a variant for fast accurate predictions of the molecular quasi-particles (QPs), finding excellent performance across a set of small molecules that are often studied in catalysis. Finally, I suggest and implement a way to use that QP focus to identify what I consider a best-possible non-empirical (yet adsorbate specific) RSH vdW-DF version, denoted AHBR($\gamma^*$) for H$_2$ DC modeling, navigating what are partly conflicting requirements on the molecule and metal sides. I find that the AHBR($\gamma^*$) can determine the classical H$_2$+Cu(111) DC barrier height close to chemical accuracy. I suggest that DC modeling can test broader relevance of the physics underpinning these RSH vdW-DFs.

Starting from a probabilistic numerics approach to the Fermion sign problem in path integral Monte Carlo, we recast the arithmetic calculation of a Fermionic observable as a statistical inference problem. We develop approaches that learn the behaviour of Fermion exchange cycles binned by the conjugacy class of the permutation group (which we term `permutation family'). This extends the work of DuBois, Brown and Alder\cite{dubois2017overcoming} to inhomogeneous and more complex systems. Monte Carlo samples are used to train models for both the probability of a permutation family and the energy of this set of exchange permutations. The overall Fermionic energy is then directly inferred from these models, without using a direct ratio estimator on the Monte Carlo samples. By imposing physical understanding as inductive priors, we produce accurate and useful fits that remain robust even in regimes with severe sign problems. We generalise the linear (ideal-gas style) models of DuBois et al. with Bayesian priors that enforce the intuitive models of Feynman\cite{Feynman1953A} at their asymptotic limits. These linear models serve as the baseline for a Long Short-Term Memory (LSTM) neural network, which is tasked with learning only the residual many-body correlations on top of the physical model. We develop active important sampling methods driven by these models, which direct the Monte Carlo chains toward undersampled permutation regions, to efficiently reduce the variance in the observable. We apply this framework to small experiments on benchmark systems: the spin-polarised uniform electron gas, and electrons in a 2D harmonic confining potential. In both cases we demonstrate that this inference-based framework can extract stable energies in regimes where direct Monte Carlo sampling fails due to the sign problem.

Characterizing the mechanical response of materials traditionally requires solving optimization problems in which model parameters are calibrated or trained to minimize the discrepancy between model predictions and experimental data. This process can be computationally expensive and time-consuming. To overcome this limitation, we propose two neural operator architectures that directly map experimentally measured data to the constitutive functions governing the mechanical response of the material: Physics-Augmented Neural Operators (PANO) and Constitutive Artificial Neural Operators (CANO). The proposed neural operators approximate the mapping between the infinite-dimensional input space of full-field displacement measurements and net reaction forces, and the infinite-dimensional output space of hyperelastic strain-energy density functions. The displacement fields are encoded through Laplacian eigenfunctions to obtain discretization-independent and noise-robust predictions. Our framework constrains the output space to physically admissible material models that satisfy fundamental physical requirements by design. The neural operators are trained on simulated data tuples of displacement fields and reaction forces for a range of material models. Once trained, the neural operators enable near-instantaneous material characterization and require only a single forward pass to infer the strain-energy density function from a given experimental dataset. We test the predictive power of the neural operators for unseen data, noisy data, data with missing information, data from different spatial discretizations, and data from geometries of different sizes.

Based on the Kramers-Krong relations, we derive and apply a quite general expression that that relates the low frequency quasi-dc Hall conductivity to the asymptotic high frequency optical Hall response (and its manifestations in Kerr and Faraday effects) for time-reversal symmetry breaking (TRSB) states of matter like ferromagnets and time-reversal symmetry breaking superconductors as well as metals in magnetic field. Parametric plots shows this relation is obeyed exactly for the trivial single-mode case of sharp cyclotron resonance, and approximately for theoretical models for ferromagnets and TRSB superconductors. We also apply it to the experimental data from a variety of ferromagnetic systems and show reasonable agreement there as well. We use the relation to predict, from the size of the spontaneous Kerr effect at the pseudogap temperature of the cuprate superconductors that cuprates should exhibit an anomalous Hall effect of approximately 0.1 Ohm$^{-1}\cdot$cm$^{-1}$. This is a small value, but one within experimental reach and we encourage the search for it. Although not explicitly quantum geometric, our treatment has some similarities to efforts to set bounds on physical quantities based on quantum geometric relations and limited physical information.

Liquid transport growth (LTG) is a horizontal flux growth technique that is closely analogous to chemical vapor transport, with the key distinction that a molten flux rather than a vapor serves as the transport agent. Unlike conventional flux growth, LTG spatially separates charge dissolution and crystal precipitation and couples them through continuous solute transport under a deliberately imposed temperature gradient. This enables crystal growth to begin before the charge is completely dissolved, removes the equilibrium solubility constraint on the starting charge/flux ratio, and allows large yields of single crystals to be obtained from a single growth. Recent studies have further shown that by spatially separating dissolution and crystallization and maintaining crystallization at a nearly constant temperature, LTG is particularly effective for two classes of materials: compounds that crystallize only within a narrow temperature and/or composition window, and compounds whose stoichiometry, defect concentration, and thus physical properties are sensitive to the crystallization temperature. In this review, we discuss representative examples including Fe$_3$Sn$_2$, CrTe$_3$, YFe$_2$Ge$_2$, UTe$_2$, CeRh$_2$As$_2$, MoTe$_2$, WTe$_2$, and LuNb$_6$Sn$_6$ to illustrate the unique capabilities of LTG for producing high quality single crystals of diverse quantum materials. We also summarize practical considerations for LTG experimental design, including furnace selection, growth time, melt stability, and ampoule geometry, and discuss future opportunities for transforming LTG from an empirical growth method into a more predictive crystal growth technique.

The current leading approach to the variational optimization of projected entangled-pair states (PEPS) is based on automatic differentiation, which allows for a convenient evaluation of the energy gradient with respect to the local variational degrees of freedom. However, evaluating the energy gradient not only remains a major computational bottleneck of the optimization procedure, but also suffers from frequent numerical instabilities. In this work, we adopt recent advances in implicit differentiation techniques to address these challenges in PEPS optimization. By reformulating the core step of the gradient computation in terms of a single characteristic equation for the contraction environment, we reduce the cost of the gradient computation and improve its scaling with the problem size. By choosing a suitable parametrization of this characteristic equation based on the intrinsic symmetries of the contraction environment, we can directly remove instabilities from the global gradient computation that would otherwise arise from the derivatives of subroutines of the contraction algorithm. Finally, we demonstrate how this approach drastically simplifies the practical implementation of stable gradient-based PEPS optimization.

Rhombohedral graphene systems provide a unique platform where strong electronic interactions and nontrivial band topology coexist at low carrier densities and high displacement fields, giving rise to a rich landscape of emergent electronic phases. Here, we report that the highly insulating state on the low-density side of chiral superconductivity in rhombohedral pentalayer graphene (R5G) corresponds to a Wigner crystal (WC) phase. In addition, a hole-doped metallic Wigner crystal (h-mWC) phase emerges near the WC boundary. Under an out-of-plane magnetic field, the system hosts competing magnetic-field-stabilized superconductivity (fSC) and unconventional reentrant quantum Hall (RIQH) states. These emergent phases are closely connected to the underlying WC and mWC states and evolve continuously across phase boundaries. Our results establish that WC phase plays an important role in the phase diagram of rhombohedral multilayer graphene and highlight its connection to a rich landscape of emergent phases.

Extending valleytronics from discrete points to continuous lines in momentum space transforms dispersionless bands into a controllable degree of freedom. Here we introduce ridge–spin–layer coupling (RSLC) in two-dimensional (2D) altermagnets, where a one-dimensional continuous line of dispersionless electronic states (a ridge) in momentum space locks to both spin polarization and atomic sublayer. This ridge-induced quenching of kinetic energy mimics flat-band physics, yet crucially, RSLC grants external control, allowing for layer-selective switching of ridge orientation in reciprocal space, spin-filtered transport in real space, and a distinct electric Hall response. Guided by collinear spin layer group symmetry, we identify three 2D candidate materials, namely Mg$_2$Mo$_2$(PO$_5$)$_2$, Ca(FeP)$_2$, and Mg$_2$V$_2$(SO$_5$)$_2$, each featuring a crossed-ridge structure with two ridges, one per spin channel and sublayer. Our work establishes ridgetronics as a controllable platform for direction-discriminating currents, bridging dispersionless bands with multifunctional device operation.

We present non-equilibrium molecular dynamics simulations of lubricated sliding between rough, deformable surfaces under conditions representative of mixed lubrication. One aim is to reduce the gap between highly idealized simulations of smooth interfaces and real, rough, load-bearing contacts. Another aim is to determine whether favorable tribological properties of two-fluid lubrication reported for solvated hydrophilic-hydrophobic polymer-brush interfaces can also be realized in rough contacts without brushes. To this end, we compare aqueous (water), hydrocarbon (n-dodecane), and immiscible two-fluid lubrication under identical geometric conditions representing randomly rough surfaces. For the single-component lubricants, the simulations reproduce established trends: water shows stronger speed dependence but reduced load-bearing capacity than n-dodecane, despite their similar ambient viscosities. Beyond this expected behavior, the simulations reveal that the combination of strong confinement and large height gradients can cause plug flow and thereby cavitation after asperity collisions. For a high-surface-tension liquid like water, cavitation leads to an abrupt shear-stress release on scales much exceeding the size of the cavity. Since plug motion only weakens with single-component lubricants at low speeds, the two-fluid lubricant can only leverage its potential advantages at low sliding velocities. It is also the only system in which folding lips form, occasionally developing into transient, detached clusters at high speeds.

Prediction of material durability is both very important and very difficult. In many cases, material durability is measured by subjecting a sample to repeating oscillatory cycles (in shear or tension-compression) until it fails in either ductile or brittle fashion. Typically, the stress amplitude is denoted S, and the number of cycles N, so the resulting dependence is known as the SN-curve. For many materials, SN curve has been shown to obey the empirical Basquin's law, N = AS^(-m), where the prefactor A was a function of the temperature, load frequency, and sample history, and the power law m was a real number, usually between 3 and 12. Here, we derive the Basquin's law using a linearized version of the Long's plasticity model and demonstrate that within this framework, m = 3. We also derive the expression for the prefactor A. Finally, we show that our theory successfully describes experimental data for three amorphous polymers, PS, PMMA, and PVC.

Single-crystal diamond is a leading material platform for high-power electronics and solid-state quantum technologies, yet many device architectures require micrometer-scale membranes with deeply etched features, patterned from commercially available substrates. In this work, we demonstrate a complete through-etch of a 16 {\mu}m -thick NV-doped single-crystal diamond membrane using a single-layer SiO2 hard mask combined with a multi-step oxygen-based ICPRIE process. With a diamond-to-SiO2 selectivity of 15:1, this non-metallic mask strategy can achieve etch depths of few tens of {\mu}m with well-defined sidewalls, conserved surface roughness and negligible micromasking. Furthermore, we use the oxide layer that remains after etching to serve as the bonding surface in a subsequent integration step. The etched microstructures are transferred onto SiO2 substrates and bonded at room temperature using O2 plasma surface activation and a sodium silicate interlayer. The resulting siloxane film is optically transparent across the visible spectrum and introduces no detectable parasitic photoluminescence, preserving the optical readout of the embedded NV centers. Together, this deep-etch and room-temperature bonding process provides a scalable and contaminationfree route from bulk diamond membranes to diamond-on-silica heterostructures for integrated quantum photonics and sensing applications.

Analog quantum simulation offers a powerful way to study strongly correlated quantum systems that are beyond the reach of classical computation. In this context, ultracold atomic gases have been demonstrated to be an exceptionally versatile and well-controlled platform for implementing various quantum Hamiltonians. In this work, we extend this level of control to a multiplexed configuration in which distinct quantum-simulation units are independently controlled and engineered starting from a single atomic cloud. We demonstrate multiplexed operation in two representative settings. First, by shaping box-trap potentials and separately controlling the evaporative cooling trajectories, we prepare subsystems at various temperatures across the superfluid transition of the unitary Fermi gas. Second, we demonstrate parallel quantum simulation of the Josephson Hamiltonian across distinct Josephson-junction quantum simulation units with individually tunable parameters, including local phase control to initialize the dynamics. Our scheme provides a versatile route toward systematic studies of dynamics and transport Hamiltonians in strongly correlated ultracold matter. Moreover, it is readily extendable to a wide range of atomic species, geometries, and dimensionalities.

Using a combination of static and dynamic density functional theory simulations, we systematically investigated how phosphorus doping and oxygen vacancies on the CeO$_2$(111) surface influence the oxidation mechanisms of formaldehyde (HCHO). Our results reveal that P cations (P$^{5+}$) substitutionally replace Ce$^{4+}$ in the lattice, forming Ce$-$O$-$P bonds that reduce the band gap (from 2.26 eV to 2.09 eV) and generate localized Ce$^{3+}$ states through charge redistribution. This synergistic effect of P doping combined with oxygen vacancy strengthens HCHO adsorption by decreasing the adsorption energy from -0.62 eV on pristine CeO$_2$(111) to -2.65 eV on the defective P-doped surface. Importantly, P doping lowers the C$-$H bond cleavage barrier by 0.84 eV relative to pristine CeO$_2$(111), accelerating formaldehyde oxidation on the defective surface. In addition, the rapid desorption of CO$_2$ and H$_2$O ($\tau \sim 0.59 s$ at 300 K) indicates weak product-surface interactions, which favor efficient catalyst regeneration during continuous operation. These findings highlight P-doped CeO$_2$(111) as a promising system for low-temperature HCHO oxidation and provide insights into the design of ceria-based catalytic materials.