Papers

Deep learning models of nanocrystal synthesis enable the prediction of size and shape by encoding precursors and reaction conditions. However, their black-box nature hinders gaining deep insights into the underlying synthetic mechanisms. Here, we develop the Nanocrystal Equation Learner (NanoEQL), a fully white-box neural network to unravel the size determination mechanisms of nanocrystal synthesis. Building on the EQL architecture, eight operators are introduced to replace standard activation functions to fit the mathematical equations in nanocrystal synthesis. Among these operators, three smoothed operators address the gradient explosion of singular operators at zero. To evaluate the weights of different precursors, we develop a temperature-gated attention pooling strategy that encodes concentration-driven and reactivity-driven chemical synthesis mechanisms into the temperature gate. The NanoEQL model illustrates that the final nanocrystal size can be described by a linear equation composed of three scalars representing nanocrystallization capability (-Zp), growth capability (Zrea), and external input potential (-Zops). These interpretable scalars not only advance the rational design of nanocrystal synthesis but also establish a generalizable paradigm for deciphering chemical reaction mechanisms through white-box machine learning.

Physical entropy-driven true random number generators are essential for emerging probabilistic computing paradigms, but conventional implementations based on magnetic tunneling junctions have reached their performance plateaus limited by inherent tradeoffs and weak tunability. Here, autferroics, a sister branch of multiferroics, is proposed to construct true random number generators. Benefiting from its unique energy landscape due to strong seesaw-type magnetoelectricity, the performance of true random number generation can be significantly enhanced in autferroic tunneling junctions, verified by passing standard statistical tests. Furthermore, autferroics-based random number generators can exhibit multi-field tunability and intrinsic multi-state randomness, opening an avenue for efficient hardware realization of the complex-number arithmetic and simulation of probability distributions of quantum mixed states within stochastic circuits.

Transverse thermoelectric conversion using artificially tilted multilayers (ATMLs) offers a versatile device architecture that circumvents the structural limitations of conventional longitudinal thermoelectrics. However, achieving competitive room-temperature thermoelectric performance without an external magnetic field remains a critical challenge. Here, we report a record-high transverse thermoelectric figure of merit $z_{yx}T$ of 0.36 in Ni$_{50}$Fe$_{50}$/Bi$_{0.2}$Sb$_{1.8}$Te$_{3}$-based ATML at room temperature without an external magnetic field. Leveraging the longitudinal high power factor in a Ni$_{50}$Fe$_{50}$ alloy and the sharp contrast in electrical and thermal transport properties between $n$-type Ni$_{50}$Fe$_{50}$ and $p$-type Bi$_{0.2}$Sb$_{1.8}$Te$_{3}$, we engineer an anisotropic structure that simultaneously exploits high electrical conductivity, large transverse thermopower, and low thermal conductivity to maximize $z_{yx}T$ in ATML. Through the direct measurements of these thermoelectric transport parameters, we obtained $z_{yx}T$ of 0.36 in Ni$_{50}$Fe$_{50}$/Bi$_{0.2}$Sb$_{1.8}$Te$_{3}$-based ATML, which is in excellent agreement with the analytical prediction of 0.36 owing to the low interfacial electrical and thermal resistances at the Ni$_{50}$Fe$_{50}$/Bi$_{0.2}$Sb$_{1.8}$Te$_{3}$ junctions. These results pave the way for the practical implementation of transverse thermoelectric materials around room temperature.

We introduce a class of nonautonomous nonlinear oscillator equations of mixed Liénard type that arises from a parametric deformation of the commutative factorization procedure applied to second-order ordinary differential equations with periodic solutions. Their solutions, in particular the isochronous waveforms, are obtained in closed form through a Riccati reduction scheme for the power-law choice of the factorization function, $\phi(x)=kx^{q}$, $k\in \mathbb{R}$, and $q\in\mathbb{N}$, corresponding to the so-called modified Emden oscillators, and do not depend on the arbitrary deformation parameter $A_1$. The variational structure of the equation is characterised by a Lagrangian supplemented with a generalised Rayleigh dissipation function that contains a non-standard cubic term in $\dot{x}$. We also show that multiplying the equation of motion by the Jacobi multiplier $M(x)=x^{-2A_1}$ a position-dependent-mass (PDM) form is obtained with related friction and restoring force.

Machine learning is increasingly used to learn structure property relationships from spectroscopic and diffraction data, yet its adoption in materials discovery is often limited by poor interpretability of model predictions. Although attention mechanisms are frequently treated as inherently explainable, unregularized attention can yield unstable, fragmented, or intensity driven attribution patterns that obscure the physical origin of these relationships. Here we introduce SPEAR (Structure Property Explainability with Attention Regularization), a framework that constrains attention distributions during training to improve their stability, selectivity, and physical interpretability. SPEAR augments attention based regression with a learnable temperature that controls attention concentration and a smoothness penalty that enforces coherence across neighboring spectral positions, treating attention as a learnable explanatory object rather than a post hoc visualization. Using synthetic spectral benchmarks with known generative structure, we show that attention regularization produces smooth, contiguous attribution profiles aligned with causal features while preserving predictive accuracy. Applied to experimental X ray diffraction data from a combinatorial rare earth zirconate thin film library, the regularized model selectively emphasizes physically relevant diffraction features and decouples feature importance from raw peak intensity. The reflection it identified prompted a reassessment of our earlier structural analysis, revealing a correlation between the 220 peak position, the tetragonal distortion that accommodates cation size disorder, and the local thermal conductivity. Attention regularization therefore provides a principled training constraint for explainable structure property regression, yielding mechanistically meaningful explanations without sacrificing predictive performance.

Self-organized spatial patterns are central to nonequilibrium physics and cell biology, yet locating instabilities in multi-component, reaction-diffusion networks remains challenging because standard eigenvalue analyses scale with the number of biochemical states and rely on reaction kinetics often poorly constrained by experiments. Exploiting the common mass-conserving structure of protein reaction kinetics and the fact that nonlinear feedback is typically confined to membrane reactions while lateral membrane diffusion is negligible, we develop a geometric classification that predicts stationary, and approximately also oscillatory, pattern-forming instabilities from reactive equilibria. The developed criteria reduce the stability analysis from the full component space to the space of conserved species. On this reduced space, slope matrices—describing the change of equilibrium cytosolic densities with respect to total species densities—govern onset. Based on densities in chemical equilibrium, this approach eliminates the requirement of comprehensive kinetic knowledge frequently lacking in experimental systems. Thus, a broad range of instabilities can be understood as mass-redistribution instabilities—self-amplifying mass redistribution caused by shifting local equilibria. We apply these criteria to models for the Escherichia coli Min system and the Caenorhabditis elegans polarity system and show that the reduction extends to the mixed-dimensional dynamics in systems coupling bulk cytosolic dynamics with membrane dynamics on the boundary. Together, these results provide an interpretable, broadly applicable, and experimentally accessible framework for diagnosing and designing pattern formation in multicomponent nonequilibrium systems on the basis of conservation laws.

This document describes the models used in the simulator for the dynamics of a nanoparticle levitated in a Paul trap combined with an optical tweezer. The focus is the coupled evolution between the center-of-mass motion, the internal temperature of the particle, and the effective temperature associated with the mechanical motion. The formulation includes electric and optical forces, gas damping, thermal noise, heat exchange with the gas, thermal radiation, active optical absorption, parasitic absorption, anti-Stokes cooling, and absorption/emission spectra obtained from generic presets, generated bands, or experimental tables loaded by the user

Symbiotic recurrent novae provide a unique laboratory for studying thermonuclear explosions, shock evolution, and nonthermal particle acceleration in dense circumstellar environments. In this work, we develop a time-dependent, multi-energy framework to describe neutrino emission from such systems, consistently incorporating both MeV neutrinos produced during thermonuclear runaway and GeV neutrinos generated through hadronic interactions in nova-driven shocks. Using RS Oph as a benchmark source, we model the evolution of the shock interacting with both the red giant wind and a dense accretion disk surrounding the white dwarf. We show that the resulting neutrino signal exhibits a characteristic two-component temporal structure: an early, rapidly rising MeV component tracing nuclear burning, followed by a delayed GeV component governed by shock propagation and particle acceleration. The presence of an accretion disk can significantly enhance the early-time GeV neutrino emission by providing a dense target for proton-proton interactions. This leads to a pronounced neutrino flux within the first few hours after eruption, a feature absent in wind-dominated scenarios. We further evaluate the detectability of these signals and find that while the MeV component remains below current detection thresholds, the GeV neutrino emission from nearby systems may become accessible to next-generation detectors. Our results highlight the critical role of the circumstellar structure in shaping nova neutrino emission and demonstrate that symbiotic recurrent novae are promising targets for future multi-messenger observations.

Transient thermal grating (TTG) experiments provide a powerful means of probing material properties and heat-transport dynamics at small spatiotemporal scales through the temporal response to a spatially periodic excitation. However, quantitative interpretation of the measured transient requires a forward model that consistently connects energy deposition, subsequent heat transport, and the detected TTG observable over the experimental timescale. A unified formulation linking these stages remains insufficiently developed in the TTG context. Here, we formulate a continuum, operator-based TTG forward model that describes the sequence from energy deposition through thermal transport to the temporal evolution of the selected spatial temperature mode within a unified transfer-function framework, while leaving the instrument-specific detection process outside the scope of the present formulation. Heat-transport dynamics are represented by a temporal memory kernel, allowing unresolved relaxation processes to be incorporated into the macroscopic response. The framework provides a basis for assessing the identifiability of thermal diffusivity, heat-propagation speed, and heat-flux relaxation time when flux-memory effects are resolved on the experimental timescale. These macroscopic parameters can, in turn, inform the microscopic interpretation of the measured dynamics. Analysis of the resulting model further demonstrates that the observability of heat-flux memory is not equivalent to the presence of oscillations in the measured response. Oscillations can provide a clear signature of finite flux-relaxation dynamics, but their absence does not establish the validity of Fourier heat conduction: finite flux relaxation dynamics need not produce experimentally observable oscillations under all conditions.

Monitoring long-term chromospheric activity and large-scale solar structures like filaments and plages is critical for understanding solar magnetic cycles and predicting space-weather events. While photospheric magnetic fields are routinely mapped, a consistent, global reference for chromospheric structures has been absent from H-$\alpha$ observations. This technical report provides a comprehensive description of the methodology used to construct the NSF Global Oscillations Network Group (GONG) H-$\alpha$ Integral Carrington Synoptic Maps from full-disk observations. We outline the processing pipeline developed to transform these observations into 720 x 360 pixel maps binned by Carrington longitude and sine(latitude) and describe characteristics of the final data product.

Electrons in two-dimensional electron gases in the presence of an out-of-plane magnetic field propagate along the edge with a high velocity of the order of the Fermi velocity. Under microwave and terahertz radiation, photon absorption by these electrons provides a pathway to realising sensitive radiation detection. Here, we develop a detailed quantum theory of the photocurrent generated in such a system by an incident electromagnetic wave and propose an experimental geometry for observing the predicted phenomenon. By using suitably arranged radiation confinement structures, a strong photocurrent generation efficiency can be obtained. We also demonstrate that the resulting photoresponse in III-V semiconductor structures can be orders of magnitude higher than that measured in graphene.

Peripheral nerves buried beneath intact tissue are difficult to visualize during surgery and remain inaccessible to white light wide-field imaging and other surface optical imaging methods. Existing OCT nerve studies have largely relied on exposed nerves or polarization contrast with limited depth penetration, restricting their value for subsurface intraoperative guidance. Here, we introduce, to our knowledge, the first label-free framework for detecting peripheral nerves beneath unopened tissue and resolving their depth using intensity-based OCT structural signatures alone. The framework combines a handheld multimodal probe, integrating swept-source OCT with co-registered white light and autofluorescence imaging, with a “confirm-then-capture” workflow designed for practical surgical use. To enable efficient analysis of sparsely sampled OCT volumes, we develop NerveDetNet, a lightweight 2.5D segmentation network that recovers weak and spatially displaced nerve signals by incorporating spatial context, frame-order information, and shift-tolerant correlations across frames through a dedicated nerve feature correlation module. In ex vivo tissue experiments, NerveDetNet consistently outperformed six representative 2D baselines across all frame spacings, achieving a Dice score of 0.725 under the sparsest sampling condition while using approximately half the model parameters. End-to-end validation demonstrated localization of nerves invisible at the surface and depth-resolved detection up to 1.3–1.4~mm below the tissue surface, with OCT derived depth maps overlaid directly onto the surgical view. Together, these results establish a practical label-free approach for subsurface nerve visualization that supports intraoperative compatibility, enables efficient sparse-volume analysis, and provides depth-resolved guidance without tissue opening, contrast agents, or nerve exposure.

We study the Néel quench dynamics of a 1D Fermi-Hubbard model which has recently been simulated on quantum hardware. We demonstrate that the set of 7260 observable trajectories measured in the quantum experiment can be obtained more quickly and accurately through classical tensor network simulation using modest computation. Our result relies on transverse tensor network contraction, where a bond dimension of 32 is already sufficient to reproduce the quantum experiment. We further extend the converged observable trajectories to longer times than in the hardware simulation and in other recent classical simulations.

We report a systematic study of the correlations among electrochemical processing conditions and the morphological, chemical, and optical properties of porous silicon (pSi). Twenty pSi samples were fabricated from boron-doped (100) crystalline silicon by varying current density, etching time, and hydrofluoric-acid concentration. Scanning electron microscopy, Fourier-transform infrared spectroscopy, and photoluminescence were used to characterize the resulting structures. The two-dimensional porosity varied only moderately, whereas porous-layer thickness increased with etching time and current density. The silicon oxide to silicon hydride ratio showed comparatively small variations. Corrected photoluminescence spectra were fitted with a four-component quantum-wire/quantum-dot model including localized surface-state transitions. The extracted quantum-wire and quantum-dot dimensions decreased systematically with increasing current density, while the photoluminescence maximum under 375 nm excitation showed no clear monotonic dependence on processing conditions. The results demonstrate that no single descriptor adequately captures the multiscale behavior of porous silicon.

We provide an unfolded formulation of linearised 6D exotic supergravity with manifest superconformal symmetry including conformal duality transformations. The construction is based on a superoscillator realisation of the metaplectic supergroup $MOSp(16|16)$ containing the Howe dual pair $MOSp(8^\ast|8)\times SU(2)$. Exotic graviton potentials arise in conformally dual pairs of two-forms in direct products of $SU(2)$-triplets and supertraceless graded-symmetric rank-two supertensors of $OSp(8^\ast|8)$ generated from a hypercharge by the supercharges, providing an analogue of the adjoint representation of $\mathfrak{psu}(2,2|4)$. The potentials are sourced via relative Chevalley-Eilenberg cocycles by a conformally dual pair of chiral and anti-chiral Weyl zero-forms valued in $SO(1,1)\times Spin(1,5)\times USp(8)$-covariant monomorphic restrictions of an extended supersingleton, i.e., an infinite-dimensional $SU(2)$-invariant Hermitian left-module of $MOSp(8^\ast|8)$ containing various irreps associated with different boundary conditions, including the unitarizable exotic supergravity multiplet. Two natural quadratic observables are i) an on-shell closed zero-form built from the chiral Weyl zero-form and its dual, akin to the on-shell value of the second Chern class on the internal twistor $Z$-space of 4D Vasiliev systems; and ii) an off-shell topological six-form built from the conformally dual pair of two-form potentials, reducing on-shell to a generating function for chiral two-point functions in super-Poincaré backgrounds.

The strong $\mathcal{CP}$ problem and quark mass hierarchies can probe the same ultraviolet structure. We show this by extending modular strong-$\mathcal{CP}$ solutions to non-Abelian finite modular symmetries. This reveals a previously overlooked modular-anomaly condition from the finite representations. Regularity removes the dependence of the QCD angle on the $\mathcal{CP}$-breaking modulus, yielding $\bar\theta=0$. For positive modular weight, it also forces the quark Yukawa determinant to vanish at the cusp. This leads to pronounced mass hierarchies among the quarks. We further stress that modular symmetries act as R-symmetries. Under moderate additional assumptions, this renders the QCD angle independent of the dilaton. An explicit model illustrates the mechanism.

Inelastic neutron scattering on a single crystal resolves how the intensity of a magnetic transition of a molecular spin cluster varies with the momentum-transfer vector $\mathbf{Q}$. The point group fixes that dependence completely when a single symmetry species mediates the transition and the local spin operators contain only one occurrence of that species. Functions for such universal $\mathbf{Q}$ dependences have been tabulated. As we show here, even when these conditions are not fulfilled, the point group still fixes, at a given geometry, momentum transfers at which the intensity vanishes for every Hamiltonian that has the symmetry of the cluster. We call such momentum transfers extinctions and derive an equation whose every zero is an extinction, built from the symmetry species of the two levels and from the positions and scattering amplitudes of the magnetic sites. The extinctions follow in closed form in two cases: when each orbit of symmetry-equivalent sites contributes a single occurrence of the mediating species, and when the site phases recur under a subgroup up to one common factor.

We demonstrate intracavity terahertz (THz) generation via optical rectification in a 50-m-thick lithium niobate crystal placed inside a compact diode-pumped Kerr-lens mode-locked (KLM) Yb:CALGO bulk oscillator. The oscillator operates at a repetition rate of 85 MHz and delivers 83-fs pulses with up to 71 W of average intracavity power, obtained with only 21.4 W of low-cost multimode diode pump power. We generate single-cycle THz pulses with a spectrum extending up to 3 THz, detected by electro-optic sampling with 60 dB dynamic range within 156 s of measurement time (313 averaged traces) and up to 120 W of THz average power. This work combines the high damage threshold, power-handling capability, and cost-effectiveness of thin LN plates with simplicity, compactness, and low-cost multimode diode-pumped solid-state bulk lasers, offering an attractive alternative for high-repetition-rate THz time-domain spectroscopy systems.

A large-eddy simulation (LES) of a laminar separation bubble (LSB) induced by an adverse pressure gradient over a flat plate is performed at an inflow displacement-thickness-based Reynolds number of 410 and a free-stream Mach number of 0.25. With a mean peak reverse flow of 21.4%, the bubble sustains self-excited vortex shedding through a local region of absolute instability, in the absence of any external forcing. Spectral proper orthogonal decomposition (SPOD) applied to the LES data identifies three dominant coherent structures within the LSB: two-dimensional and oblique Kelvin–Helmholtz (KH) waves in the separated shear layer at the vortex-shedding frequency, and stationary spanwise-periodic streaks near reattachment at near-zero frequency. Classical resolvent analysis of the mean flow identifies strong convective amplification of the KH waves over a range of spanwise wavenumbers, but predicts only weak amplification in the low-frequency, streak-forming region, where the leading gain is orders of magnitude smaller and no dominant rank-one mechanism is present. This discrepancy with the SPOD energy indicates that the streaks are not sustained by same-frequency linear amplification, but are instead energized by the intrinsic forcing, which the classical framework treats as an unexplained input. Harmonic resolvent analysis of the time-periodic base flow reveals the underlying mechanism: the base-flow unsteadiness couples the oblique KH wave at the shedding frequency to the stationary streak through cross-frequency amplification, yielding a gain far larger than that of the direct same-frequency amplification. This cross-frequency route provides a likely explanation for how the stationary streaks observed near reattachment are energized.

Singlet fission, the conversion of one singlet exciton into two triplet excitons, has the potential to revolutionize solar energy production by boosting the efficiency of solar cells beyond the Shockley-Queisser limit. However, the practical realization of singlet fission remains an outstanding challenge, and its underlying mechanisms have long been debated. Here we show that singlet fission arises from a distinctive type of collective excitonic entanglement in which the excitons condense into a single particle-hole mode, the same principle that leads to the Bose-Einstein condensation of excitons. Quantitatively, this condensation appears as a large eigenvalue of the particle-hole reduced density matrix (RDM), representing multiple excitons occupying a collective mode. We utilize the particle-hole RDM to capture the intrinsic particle-hole correlations in singlet fission materials including acene crystals and covalently linked pentacene dimers, revealing how structural changes control singlet fission mechanisms and modulate the contributions of charge transfer states. The same characteristic enhancement of excitonic population in a single mode is common to the onset of exciton condensation and the mechanism of photosynthetic energy transfer. Together, our results establish a unifying framework for understanding the origins of singlet fission in terms of collective excitonic entanglement.

Shao et al. recently showed that the 1+1D staggered fermion Hamiltonian admits a whole algebra of lattice operators that flow to the same axial charge in the thermodynamic limit (TL). On the lattice the principal axial charge does not commute with the vector charge, although their commutator is expected to vanish in the TL, providing a lattice realization of the chiral anomaly. We investigate the effect of this anomaly on the ground state(s) using the entanglement asymmetry. Unexpectedly, the asymmetry remains nonzero in the TL, despite the vanishing of the commutator, and exhibits a novel scaling behavior.

We present a pulse-shaper-based dispersion-scan (d-scan) framework for the combined generation and characterization of polarization-tailored femtosecond laser fields. By integrating a programmable $4f$ pulse shaper with polarization-resolved d-scan measurements, the framework enables the programmable synthesis and reconstruction of complex time-dependent polarization states. We demonstrate its capabilities for several classes of vector fields, including counter-rotating circularly polarized pulse pairs, oppositely chirped counter-rotating circularly polarized pulses, polarization-gate pulses, and multi-pulse sequences utilizing polynomial, periodic and discrete spectral phase functions. The reconstructed temporal electric fields and time-dependent ellipticities show excellent agreement with the simulated target fields and accurately reproduce the defining features of each pulse class. By combining the versatility of programmable pulse shaping with the robustness of the d-scan technique, this approach provides a flexible platform for the generation and validation of polarization-tailored ultrashort laser fields in ultrafast photonics and light-matter interaction studies.

The study of large-$N$ cases of the $O(N)$-symmetric model at criticality has attracted significant attention in recent years. In particular, a recent high-precision Monte Carlo study ( Physical Review B 105, 054428 (2022)) reported the most accurate estimates to date for the critical exponents $\nu$, $\eta$, and $\omega$ for $N \ge4$. Within the framework of the renormalization group (RG)—the cornerstone of the modern theory of critical phenomena—powerful computational approaches such as the $\varepsilon$-expansion and non-perturbative RG are available. Since the effective expansion parameter in the $\varepsilon$-expansion, $\sigma = \frac{3}{N+8}$, decreases with increasing N, one expects resummation techniques to become progressively more accurate in the large-N regime. To test this expectation, we apply the entire-hypergeometric resummation algorithm developed by Shalaby et al. to the recently obtained seven-loop divergent $\varepsilon$-series for $N \ge 4$, yielding high-precision estimates for $\nu$, $\eta$, and $\omega$ . Our analysis confirms the anticipated improvement in accuracy with increasing N. To assess the significance of these results, we note that at the same seven-loop order the $O(2)$ case exhibits errors that are an order of magnitude larger than those obtained from experiment, Monte Carlo simulations, and conformal-field-theory analysis. In contrast, for sufficiently large N, the errors in the present work are of the same order of magnitude as those from Monte Carlo and non-perturbative RG methods, demonstrating the strong predictive power of our resummation approach in the large-N regime.

Miniature probes extend optical coherence tomography (OCT) into lumens and other confined spaces, but conventional implementations often rely on multiple distal components, fiber processing, and probe-specific interferometer matching. Here, a fully fiber-integrated OCT (F2I-OCT) architecture is demonstrated in which two-photon microfabrication defines not only the terminal imaging optic, but the complete distal optical and interferometric architecture within a single fiber-mounted element. Beam expansion, side-view redirection, common-path reference generation, and terminal imaging are physically integrated while remaining independently designable. This architecture transfers complexity from component fabrication and interferometer matching into three-dimensional optical design, reducing assembly to a print-and-bond process and enabling plug-and-play exchange on the same OCT platform. Terminal optics can be adapted to different working distances, surrounding media, and wavefront transformations without redesigning the upstream architecture. Twenty assembled probes exhibit returned-reference and side-viewing-output power standard deviations of 0.149 dB and 0.071 dB, respectively. The system achieves 93.1 dB sensitivity and enables ex vivo imaging of airway and dental structures. The combination of a common plug-and-play architecture with broad optical design freedom provides a versatile platform for endoscopic and confined-space imaging across diverse biomedical and technical environments.

The presence of sidewalls in turbulent duct flows leads to the emergence of secondary flow structures in the form of counter-rotating streamwise vortices near the corners (Prandtl's secondary flow of the second kind). This work develops reduced-order Galerkin projection models that can predict the emergence and structure of these turbulent mean secondary flows in a square duct geometry, without requiring any prior knowledge of the turbulent statistics. The models are obtained by projecting the Navier–Stokes equations onto eigenmodes of the linearised system, with the resulting systems of ordinary differential equations simulated with the addition of zero-mean forcing. We show that most models obtained using leading streamwise-constant eigenmodes predict the correct shape and direction of the secondary mean, with the minimal such model requiring only two modes. In these models, the secondary mean contribution arises due to the nonzero average coefficient of an eigenmode that possesses all of the symmetry properties expected of a secondary mean. The models are sufficiently simple such that the relationship between this mean coefficient and the joint second moment of other mode coefficients can be computed analytically. We confirm that running streamwise-constant direct numerical simulations (DNS) with the same forcing structure as used in the reduced-order models produces similar secondary-flow structures. We additionally demonstrate that our models produce qualitatively similar Reynolds stress distributions to fully resolved direct numerical simulations, with improved agreement as model dimension increases.

Kirigami, the art of cutting sheets, offers unique characteristics such as shape morphing, stretchability, and adaptability, with applications in deployable and reconfigurable structures. While Finite Element (FE) approaches are widely used to analyze kirigami structures, they are computationally intensive and prone to convergence issues. On the other hand, existing simplified and theoretical models for evaluating kirigami are typically restricted to specific designs and analytical scenarios. This paper proposes a generalized, computationally efficient reduced-order model based on the bar and hinge approach for analyzing any kirigami system. The model represents the entire kirigami structure using truss bars, bending hinges, and torsional springs, capturing both the deformation and internal forces of the system. We derive stiffness expressions for kirigami structures that experience stretching and out-of-plane bending deformations, as well as for structures that experience only in-plane stretching and rotations. The accuracy and robustness of the model are validated through comparisons with FE analysis and experimental data on both single-cut kirigami designs and more complex designs with multiple cuts. Our results demonstrate less than 5% difference in deformation predictions and achieve at least a tenfold computational speedup compared to FE simulations. Additionally, we demonstrate the model's capabilities through simulating complex scenarios, including kirigami-skinned crawlers, high-throughput property-space exploration, and in-plane kirigami-inspired metamaterials. These examples demonstrate computational capabilities that enable large-deformation structural simulations and high-throughput design exploration beyond the practical limits of conventional FE methods.

A feedback loop that returns a message into the process it describes defines a quantum channel on the message. We ask when such a loop preserves entanglement with a reference, that is, when its channel is not entanglement breaking. For any qubit loop, the negativity of the Choi state is at most half the fidelity between the states that the two values of the message leave in the discarded registers, in any basis. This channel analogue of the duality between fringe visibility and which-way information is attained by pure dephasing, and a perfect record of the message in the discarded registers makes the loop entanglement breaking. We then solve a three-qubit loop in which the message steers a future event, a probe reads the event, and a partial swap feeds the probe back. Every partial feedback is a strict contraction, and the loop is entanglement breaking exactly when an explicit trigonometric polynomial in its coupling angles is not positive. A partial record of the message in the future event can restore entanglement that the feedback alone destroys. Stability, a coherent fixed point, information about the future event and entanglement preservation coexist on about three quarters of the parameter space.

Drying particle suspensions is widely used to assemble particles and to fabricate porous functional layers for various applications, in which microstructural properties critically influence the overall device performance. Understanding the mechanisms governing drying-induced microstructure formation is therefore essential for predictive control of the resulting structures. In this work, we numerically investigate the evolution of microstructures during the drying of particle suspension films, with a particular focus on the role of particle-particle interactions. For weakly interacting particles, the particles assemble into hexagonal structures at the interface, and upon drying, trigger subsequent layer-by-layer assembly. We present a simple theoretical model to predict the time evolution of the layer thickness, validated against our simulation results. With strong particle interactions, the particles aggregate and form a network-like structure during drying, leading to a porous deposit. The porosity of the structure follows a power-law relationship with a dimensionless adhesion parameter that characterizes the particle-particle interaction force relative to the capillary force. By systematically varying the adhesion parameter, three packing regimes of the final structure are identified: hexagonal close packing, random close packing, and adhesive packing. Overall, our results demonstrate that particle-particle interactions play a decisive role in determining the final porous structure, providing practical guidance for tailoring functional layers through controlled manipulation of particle interactions.

Modern transmission electron microscopes are versatile instruments which have become indispensable tools for understanding structure and chemical composition at the nano- and atomic scale. In the physical sciences these instruments are still largely manually controlled, requiring significant operator expertise, limiting throughput, and precluding statistical analysis of large datasets. Recent technical advances in both hardware and in control software now allow for the interaction with almost every functionality of the microscope through a programming interface. This enables better experimental design and data collection automation while also reducing operator collection bias and required expertise. In this study, we present an automated data collection routine with machine-driven decision-making to enable the collection of hundreds of 4D-STEM nanobeam diffraction and ptychography data from a large distribution of size-selectively deposited Pt nanoparticles. We present a semi-automated data analysis workflow to extract pertinent information from the large volumes of collected data. For the nanobeam diffraction data, reducing each dataset to its azimuthal variance profile and combining automated crystal orientation mapping with per-particle morphology descriptors reveals the orientation, shape and phase distributions across the ensemble, including a weak {110} texture. For the ptychographic data, an automated screening pipeline identifies on-zone-axis particles and enables atomic-resolution phase imaging and lattice-strain mapping of individual grains. Together these demonstrate how automation turns instrument throughput into statistically meaningful, atomic-scale microstructural information.

Channel–state duality identifies completely positive maps with bipartite states. Its generalisation to von Neumann algebras is known to produce states not on $\mathcal{M}\bar{\otimes}\mathcal{N}$ but on the tensor product of $\mathcal{M}$ with the opposite algebra of $\mathcal{N}$, or equivalently with a commutant; returning to $\mathcal{N}$ itself requires a transposition, and it has been observed that this step typically fails. We determine exactly when it does not fail. Our main result is that a Choi–Jamiołkowski type isomorphism which is natural in the first algebra exists if and only if the second algebra is $*$-anti-isomorphic to itself. Naturality cannot be dropped: whenever $\mathcal{M}$ is anti-isomorphic to itself such an isomorphism exists for trivial reasons, since the order structure of a predual is a Jordan invariant and cannot distinguish an algebra from its opposite. Consequently no such correspondence exists for the type III factors constructed by Connes. We show in addition that the domain admits no description in terms of properties of individual maps: the space of all normal maps with the operator norm is too large, and neither complete boundedness nor complete positivity cuts it down to the right size.