Papers

The tokamak, a toroidal magnetic device confining a hot plasma, is one of the most advanced approaches to fusion energy. A central obstacle is turbulent transport driven by the ion-temperature-gradient (ITG) mode. Operation scenarios that rely on a weak or zero magnetic shear core, such as the ITER hybrid scenario, have achieved markedly improved confinement, yet the underlying mechanism has remained unclear. Here we show that the radial width of ITG poloidal harmonics is constrained not only by the familiar parallel Landau damping, but also by the isotropy of micro-turbulence in the plane perpendicular to the magnetic field. In the weak-shear limit, micro-isotropy dominates and constrains the radial width at one poloidal wavelength, yielding a critical magnetic shear $s_{\text{crit}} \approx 1/(2\pi)$. Above this threshold, the extended Type II ballooning modes prevail; below it, the localized Type I modes emerge, comprising only two or three harmonics. Global gyrokinetic simulations spanning DIII-D, JET~and ITER parameters confirm this geometric criterion. Nonlinear simulations with sustained heating show that weak-shear plasmas spontaneously form internal transport barriers with the turbulence suppressed in the radial region determined by $|s| < s_{\text{crit}}$. This geometric criterion defines the weak-magnetic-shear regime and offers a fresh perspective on turbulent transport in fusion plasmas.

Whether orthogonalising the moment basis changes a central-moment lattice Boltzmann scheme is decided by the geometry of the velocity set. The basis enters the collision only through the conjugate $\mathit{T}^{-1} \Lambda \mathit{T}$, so two bases related by a constant matrix $\mathit{A}$ define exactly the same scheme if and only if $[\Lambda,\mathit{A}]_{ij}=\mathit{A}_{ij}(\lambda_i-\lambda_j)$ vanishes, and on physical states only its columns for the non-conserved moments matter. We prove that on lattices with velocities in $\{0,\pm1\}^d$ and symmetric weights orthogonalisation reaches the shear moments only through the face and body diagonals: whatever the orthogonalisation, the shear rate is free on D2Q9 and D3Q15, whereas on D3Q19 and D3Q27 the scheme changes whenever the fourth-order moments do not relax at the shear rate. On rectangular lattices, where the symmetry is broken, an independent bulk rate yields an orthogonal counterpart that does not share the transport coefficients of the published scheme, which is itself orthogonal in the inner product of the rest equilibrium up to the one relaxation entry that consistency requires. Where the formulations differ but share their hydrodynamics, a basis orthogonal in the inner product of the rest equilibrium, which guarantees linear stability at rest, was never less robust in the least stable flow direction by more than a few per cent, often much more robust, and the more accurate against a Taylor-Green DNS. Computed through the non-orthogonal transforms with a conjugated relaxation matrix, it costs at most $2\%$ more on D3Q27.

We extend Marcuse analysis of pulse fluctuations of randomly phased multimode sources to arbitrary chromatic dispersion, chirp, finite mode linewidth, mode partition noise and finite receiver bandwidth. On long fibers the fluctuations depend only on the shape of the group delay curve, a monotonic delay separates the modes, whereas a symmetric delay leaves pairs of modes with identical intensity profiles and a persistent beat noise. Dispersion downconverts the beats of overlapping modes to baseband, where receivers cannot filter them. The detected power follows random phasor statistics, and Gaussian estimates of fade probability can be wrong by orders of magnitude. Mode partition noise grows with dispersion and dominates in band limited links.

Solar cycle variation of earth's atmosphere, particularly the ionosphere is of particular interest in the field of space science and space weather studies. In this article, we present the outcome of our detailed quantitative study on solar cycle variation of lower ionospheric properties using numerical investigation. First, we seek to model and compare the collective D-region ionization rates (q's) due to the individual contributions from the ionizing sources, namely, (a) solar extreme ultraviolet (EUV) radiation including the Lyman-alpha irradiation and (b) solar X-ray irradiation throughout the 24th solar cycle (C24). Then, we compute the electron density (Ne) profiles using the ionization rates. We report significant solar cycle variation in ionization rate and electron density profiles for the entire span of C24. We use the sunspot number (SPN) profile to substantiate the finer details of Ne profile during C24. For the segments of the D-region above two different geographic coordinates, we report that Ne profiles show a consistent "dual peak" nature. It is very similar to the SPN profile during C24. As a next-order validation, we compare our modeled Ne profiles with their IRI-2020 counterpart (Ne,iris). Their overall trends are found to be in agreement. Finally, we discuss the response of the D-region in terms of Ne due to C24. The work lays the foundation for our upcoming studies on D-region response to solar cycle variation with Very Low Frequency (VLF) observation.

Dipolar optical forces can confine Rayleigh-sized dielectric particles towards or away from intensity maxima, commonly known as bright and dark trapping. Structured light illumination opens up opportunities for customized trapping landscapes, unveiling the possibility of gray trapping, especially for larger Mie particles that can excite a higher-order multipolar response. While previous studies have primarily focused on calculations of the gradient force for some exemplary, focused scalar beams, we not only extend these analyses by combining vectorial focusing with generalized Lorenz-Mie theory, but also consider more complex trapping fields. Motivated by their unique tight focusing behavior, shaping strong transverse intensity gradients and three-dimensional electric field components, we explore higher-order cylindrical scalar and vector beams. We theoretically investigate multipolar trapping of Mie-regime silicon nanospheres in water, calculating the three-dimensional net radiation force and assess local trapping stability through the force Jacobian. Near an octupolar Mie resonance, we predict stable gray trapping with enhanced efficiency for vector beams. Further, we find field geometries enabling configurable, particle-size-dependent gray/dark trapping with subwavelength inter-particle spacing. These results establish polarization, illumination structure and particle parameters as complementary controls for radius-dependent multipolar trapping, providing a basis for potential applications in sub-wavelength particle sorting, trapping-assisted nanopatterning and optical binding investigations.

High-energy, dense, spin-polarized positron beams with attosecond duration are highly desirable for advanced accelerator physics, laboratory astrophysics, and ultrafast matter-antimatter studies, yet remain beyond the capability of conventional source and injection-based plasma-acceleration schemes. We propose an integrated in-situ method for production, trapping, and accelerating polarized attosecond positron bunches in a single plasma stage. An ultraintense hollow laser propagating in a plasma channel drives a radiative wakefield, where longitudinally injected electrons emit a dense MeV gamma-ray bath through nonlinear Compton scattering. Subsequent photon-photon collisions induce linear Breit-Wheeler pair production, while linear and nonlinear radiative processes mediate polarization transfer to the produced positrons. Spin-resolved QED particle-in-cell simulations indicate that the laser-modulated wakefield naturally captures positrons born in the frontier bubble wake, forming collimated bunch trains with hundred-attosecond duration, GeV-level energies, and densities up to 10^17 cm^-3. Parameter scans demonstrate robustness against variations of laser intensity and plasma-channel density. This single-shot, source-free approach simultaneously addresses positron production, polarization, temporal compression, and plasma injection, offering a compact route toward polarized attosecond antimatter beams.

Can a system with more stored energy cool faster than one with less? An overdamped resistor–inductor–capacitor (RLC) circuit offers a classical, experimentally accessible spectral Mpemba analogue: both states lose energy monotonically, yet the initially higher-energy state can cross below the lower-energy one. The reason is that initial energy alone does not determine the relaxation path; initial charge and current set how strongly the slow and fast decay modes are excited. We develop this mechanism from deterministic to stochastic and open-system descriptions. For the classical circuit, we derive the modal preparation conditions and crossing criterion, explain geometrically why equal-energy states can relax differently, and confirm the effect experimentally by reconstructing charge, current, and energy from oscilloscope traces. The inversion survives when the circuit is driven by externally injected white noise. An equilibrium Ornstein–Uhlenbeck treatment separates information carried by the ensemble mean from that stored in its covariance: centered Gibbs preparations preserve mean-energy ordering, while displaced or anisotropic Gaussian states can encode distinct slow and fast sectors. A Fokker–Planck generator then bridges to Markovian quantum dynamics. For a thermally damped quantum harmonic oscillator, the mean bare-energy excess decays with a single exponential factor, forbidding energy-order inversion for finite mean occupation. A below-threshold parametric oscillator restores slow and fast quadrature sectors, allowing crossings controlled by displacement and covariance. The Liouvillian formulation shows that observed relaxation depends jointly on the generator spectrum, the modes populated by preparation, and the modes visible to the observable.

Positron acceleration is possible in linear plasma wakes, but the nonlinear electron-driven blowout regime confines simultaneous acceleration and focusing to narrow regions of returning plasma electrons. Here we investigate how an axial magnetic field reorganizes this nonlinear return to open an operating regime for sustained positron acceleration in a uniform plasma. Using quasi-3D and full-3D particle-in-cell simulations, we connect the formation of finite-radius electron columns, or gyro images, to witness transport and its operating limits. The image spacing is governed by the quasi-static invariant, while canonical angular momentum limits the return radius. Modified by the orbit-sampled wake potential, this mechanism yields a positioning law that accurately predicts the density peaks across a wide range of magnetic field strengths. At a plasma density of $10^{16} cm^-3$ and a 35 T axial field, the reorganized structure expands the usable accelerating and focusing interval by more than a factor of four compared to the unmagnetized case. A positron witness bunch placed at the settled phase of this band achieves 92% capture over a 60 mm stage, with the normalized emittance saturating at 83 mm mrad. Independent codes confirm sustained transport, yielding energy gains between 99 and 150 MeV, though numerical convergence on the exact energy gain remains an open challenge. Together with beam loading, alignment, and driver-energy scaling tests, these results establish magnetic control of the nonlinear electron return as a route to single-stage positron acceleration. Beam quality preservation, formation-transient control, and solenoid integration define the necessary next development steps.

The fission matrix (FM) method recasts neutron transport in matrix form, enabling fast, interpolation-based reactor calculations from a pre-computed database of Monte Carlo-derived coefficients. Propagation of the underlying Monte Carlo statistical uncertainty to the FM eigenvalue and eigenvector is rarely rigorous: prior approaches assume independent coefficients without testing this against their actual covariance. This work derives a full-covariance Delta-method framework for propagating uncertainty to keff and the fission source, and evaluates it with two cheaper alternatives, a diagonal-covariance approximation and direct resampling of the FM coefficients, using an OpenMC model of the JSI TRIGA Mark-II reactor. For the all-rods-out case, these three estimators and an empirical benchmark of 100 independent Monte Carlo runs agree within 5.7% for keff and 1% for the fission source. The sign of the diagonal approximation's bias flips between the two statistics levels, so it must be checked case by case. With a global fixed-source FM generation strategy, the diagonal, resampling, and independent-run estimators agree within about 2% and lie roughly 10% below the full-covariance estimate, a gap attributed to covariance sampling noise. The large off-diagonal covariance is nearly symmetric and mostly cancels when propagated, rather than being small or negative as previously assumed. For the FM control-rod interpolation and combination strategy (FM-CRd), keff matches an exact perturbed reference within 60 pcm (about two standard deviations) and the fission source within 0.7%, while the diagonal and resampling estimators agree closely and are conservative by about a factor of two. Given this and the prohibitive memory cost of the full covariance, the diagonal Delta method is recommended as the practical default, with the full covariance reserved for one-time characterization of a system.

The Baroclinic Annular Mode (BAM) strongly influences extratropical circulation, yet its role in the global hydrological cycle remains unclear. Using ERA5 reanalysis and a global atmospheric river (AR) database, we show that BAM systematically reorganizes AR occurrence and extreme precipitation in both hemispheres. During high-BAM states, AR frequency increases along the flanks of major storm tracks and decreases near their climatological cores, redistributing preferred AR corridors. Relative AR-frequency changes locally exceed 50%, with the most zonally coherent patterns over the Southern Ocean. Extreme precipitation varies correspondingly, with 99th-percentile precipitation occurrence increasing by more than 50% across broad poleward storm-track regions. A large fraction of these extremes coincide with ARs, and AR-associated extreme precipitation shows similar BAM-related modulations. Low-BAM states show broadly opposite anomalies. These results identify BAM as a key mode linking large-scale circulation to global moisture transport and hydrological extremes.

The exploration of topological states has emerged as a vibrant frontier across diverse physical systems. Among these, the Möbius strip stands out as a canonical structure that has recently inspired intriguing optical physics.In this work, we extend this concept into the high-dimensional realm by using an optical analogue-the optical Möbius snail. Specifically, employing a skyrmionic beam as the input field, tight focusing yields a continuous family of Möbius strips that exists in three-dimensional space, giving rise to a snail-like polarization topological texture. Furthermore, we demonstrate full-field polarization tomography and achieve switchable control of this optical snail texture by tuning the Skyrme number of the incident skyrmionic beam. Our findings establish a direct bridge between low- and high-dimensional Möbius geometries, opening a new platform for exploring complex spatial topology and tailored light-matter interactions.

The hyperfine structure splitting for the triplet $2^{3}S(L = 0)-$state in the two-muonic helium ${}^{3}$He $\mu_{2}$ atom is determined to high accuracy. Such a structure arises as a result of hyperfine (or spin-spin) interaction between the triplet two-muonic shell and non-zero spin of the central helicon nucleus. Our result for the hyperfine structure splitting is $\Delta \approx 5.1623403103010 \cdot 10^{7}$ $MHz$, where the standard uncertainty has been evaluated as $\pm 10$ $Hz$.

We report on hyperfine structure measurements of the $1s2s\,{}^{3\!}S_1 \rightarrow 1s2p\,{}^{3\!}P_{0,2}$ fine-structure transitions in the spectrum of $^{11}$B$^{3+}$ ions. The helium-like ions were created in an electron beam ion trap (EBIT) and ejected after a short production period of 15 ms. A challenge of the experiment was the treatment of the complex energy-time-profile of the created ion bunches and the sensitivity of the collinear laser spectroscopy to the starting potential inside the EBIT. Despite these complications and the low statistics of the experiment, we were able to confirm and improve the results of a previous measurement of these transitions. While we find moderate tension in the results for the hyperfine parameters of the $^{3\!}P_{0,2}$ levels, their fine-structure level energies are in reasonable agreement between experiments and with theory.

We report a pre-registered test of five hypotheses about the synapse-flow random walk on the connectome of the male Drosophila central nervous system (166,700 neurons, 124 million synapses), in which a walker moves to a postsynaptic partner in proportion to synapse number. The hypotheses concern the spectral gap and its dependence on the neck connective, the localisation of the leading modes of an input-normalised signed map, the certified mixing depth measured by the Dobrushin coefficient, its robustness to per-synapse detection confidence, and the dependence of the signed spectrum on the neurotransmitter sign convention. After public registration and a code freeze, each was tested once. Two held: the two-neuron photoreceptor modes that lead the signed spectrum are an artefact of normalising by very small inputs, removed by an input floor at the median, and they do not depend on the sign convention. Three failed: at a threshold of five synapses per connection the spectral gap is an order of magnitude smaller than predicted ($|\lambda_2| = 0.9965$) and the chain is certifiably far from mixed after 128 steps, and at no confidence level tested was the mixing depth certifiably robust. Exploratory analyses trace the slow mode to eleven neurons of the cord, seven of them mesothoracic efferent neurons, that become nearly closed once weak connections are dropped, find a similar boundary set in the lamina of the FlyWire female brain, show that null models preserving cell-type wiring reproduce the slow modes, and show that exact chains built from the confidence data change the depth profile after 32 steps by at most 0.017 at the pre-registered confidence level, far less than the worst-case certificate allows. Random-walk summaries of connectomes are dominated by nearly closed sets at the edges of the reconstruction unless these are treated explicitly.

Non-collinear antiferromagnets offer unconventional routes for controlling magnetic, electrical, and thermoelectric responses through their complex spin configurations and interfacial symmetry. Here, we detect exceptional interfacial properties arising from a non-collinear antiferromagnet by demonstrating a robust and quantitatively consistent exchange-bias response in an IrMn$_3$/Py heterostructure. The system consists of a 10 nm IrMn$_3$ layer coupled to a 5 nm permalloy (Py) film. Longitudinal magneto-optical Kerr effect (MOKE), anisotropic magnetoresistance (AMR), and anomalous Nernst effect (ANE) measurements independently reveal the same unidirectional field shift of approximately 50 Oe, together with a consistent cosine angular dependence. The simultaneous observation of these signatures establishes a direct correspondence between the interfacial magnetic symmetry imposed by the non-collinear antiferromagnet and the responses of the adjacent ferromagnet. This symmetry is manifested consistently in magnetization reversal, charge transport, and thermally driven voltage generation, demonstrating that the exchange-bias imprint is not restricted to a single experimental observable. Our results reveal a coherent multifunctional response of IrMn$_3$/Py and extend the conventional understanding of exchange bias beyond collinear antiferromagnetic systems. More broadly, they demonstrate the potential of non-collinear antiferromagnets as platforms for coupling magnetic, electrical, and thermoelectric functionalities in spintronic and spin-caloritronic devices.

Plume-laden convection plays a fundamental role in thermal transport in geophysical and industrial flows. While the dynamics of isolated laminar plumes have been extensively studied, their collective interactions and evolution in a multi-plume system remains poorly quantified due to the lack of four-dimensional (4D, in space and time) flow measurements for viscous convection, common in the turbulence community. Here we present a time-resolved experimental study of clustered plume dynamics in a high-Prandtl-number Rayleigh-Bénard system with temperature-dependent viscosity from 4D velocity measurements. Building on our companion methodology (Bao and Lithgow-Bertelloni, 2025), we characterize the spatiotemporal distribution, morphological evolution, and interaction modes of tens of coexisting plumes. We identify a wide spectrum of dynamical behaviors–merging, splitting, branching, pulsing, and head detachment–that arise from coupled interactions among plumes, multiscale flow, and the evolving thermal boundary layers. We synthesize prior behaviors into a unified, time-resolved framework of plume evolutionary pathways. Characteristic length and timescales, including spacing and initiation times, are compared with previous theoretical and experimental studies. We find thinner plumes with greater minimum spacing. The fraction of isolated plumes (e.g., Hawaii-like) varies dramatically (0–60%) as the flow evolves. Our results provide new insight into plume self-organization and spatiotemporal variability under Earth-like conditions, crucial for understanding geochemical evolution and mapping geochemical anomalies from hotspot lavas to deep sources. These results quantitatively complement previous experimental work and numerical studies on interacting plumes, serving as a benchmark for comparison with geodynamical simulations of mantle convection.

Laboratory investigation of convective flow in viscous fluids is crucial for various engineering and geophysical applications, including vigorous convection in planetary mantles, which involves multiple rising plumes. Many experimental techniques have been developed to visualize the flow and plumes, but most previous measurements remain largely qualitative. Here we present a method to measure and analyze four-dimensional (4D) plume-bearing viscous fluid flow, extending volumetric velocimetry approaches to the high Prandtl-number laminar regime relevant to mantle convection. First, a customized three dimensional (3D) Scanning Stereoscopic Particle Image Velocimetry (SSPIV) system is applied to a Rayleigh-Bénard experiment suitable to study the dynamics of Earth's interior. We report the first quantitative 4D velocity measurements of multiple interacting laminar plumes at high Prandtl numbers. The raw velocity data are postprocessed with a Lagrangian Coherent Structure (LCS) and cluster analysis pipeline, tailored for clusters of viscous plumes, which allows quantitative, transport-based material boundary tracking of the plumes in space and time. We show example results to demonstrate the power of our method while fully exploring the dynamics in a companion paper Bao and Lithgow-Bertelloni (2025). Our analysis quantifies the rich dynamical behavior of multiple interacting plumes. We suggest our method of measurement and analysis can help better quantify the morphology, interaction, and evolutionary pathways of plumes feeding Earth's volcanic hotspots and other planetary interiors.

Atmospheric rivers (ARs) produce many of the world's most extreme precipitation events and hydrometeorological hazards. Although artificial intelligence weather prediction (AIWP) models have demonstrated skill comparable to or exceeding numerical weather prediction (NWP) systems for large-scale atmospheric variables, their ability to forecast AR-related precipitation remains insufficiently characterized globally. Here, we evaluate 24-hour precipitation forecasts from the Global Forecast System (GFS), Global Ensemble Forecast System (GEFS), GraphCast, and Artificial Intelligence Forecasting System (AIFS) from Day 1 through Day 10 globally and across North America, Europe, and Australia and New Zealand. Using the Extreme Weather Bench framework, forecasts are evaluated against Integrated Multi-satellitE Retrievals for GPM (IMERG) observations using measures of precipitation magnitude, spatial structure, and localization. GraphCast and AIFS exhibit greater spatial skill than GFS and GEFS, particularly for heavy precipitation and at longer lead times, and better preserve the spatial organization of AR-related precipitation through Day 10. However, this improved spatial skill does not translate into accurate precipitation magnitudes. AIWP models tend to overpredict moderate-to-heavy accumulations while underpredicting the heaviest precipitation at longer lead times, whereas NWP systems develop pronounced dry biases. These results reveal distinct strengths and limitations of AIWP for high-impact precipitation forecasting and provide a reproducible benchmark.

Accurate high-resolution wind field simulations are critical for resolving fine-scale atmospheric dynamics, yet the simulation of wind fields in Earth System Models (ESMs) remains limited by coarse spatial resolution and systematic biases. To address this, data-driven down scaling techniques have been widely used to enhance coarse-resolution ESM outputs. However, existing methods are typically tied to fixed discretizations, limiting generalization across models with different native resolutions. Here we formulate global near-surface wind downscaling as an operator-learning problem on continuous atmospheric state fields and develop a downscaling neural operator that maps coarse-scale fields to fine-scale counterparts across heterogeneous discretizations. The operator learning-based neural downscaling framework outperforms dominant baselines, recovers fine-scale physical structures, and generalizes to previously unseen ESMs and future climate scenarios without retraining, while preserving long-term wind projection trends. These findings establish a generalizable paradigm for high-resolution climate downscaling across diverse simulation outputs and future scenarios.

Papapetrou showed that the covariant derivative of a Killing vector field satisfies Maxwell's equations in vacuum. We extend Papapetrou's result to show that the covariant derivative of a Killing vector field satisfies Maxwell's equations in non-vacuum backgrounds as well, if we allow electromagnetic currents of purely geometric origin. We postulate that every Killing vector field gives rise to a physical electromagnetic field and, in a non-vacuum background, a physical electromagnetic current—hereafter called Killing electromagnetic field and Killing electromagnetic current, respectively. We show that the Killing electromagnetic field of the flat FLRW universe comprises a Killing magnetic field and a rotational Killing electric field; we derive an upper bound on the Killing magnetic field and find that the upper bound is consistent with the current upper bound on the cosmic magnetic field. We show that the time-like Killing vector of the Schwarzschild spacetime gives rise to a radial Killing electric field. We also show that in the weak field regime—and far from the matter distribution—the back reaction of the radial Killing electric field changes the Schwarzschild metric to Reissner-Nordstr$\ddot{\mbox{o}}$m metric; our calculation yields the converse of Wald's result. Next, drawing upon Rainich's work on Rainich-Riemann manifolds, we discuss the etiological question of how a physical electromagnetic field can arise out of geometry; we also argue that detection of the Killing electric field of flat FLRW spacetime may be within current experimental reach. Finally, we discuss the relevance of Killing electromagnetic currents and the aforementioned transmutation of Schwarzschild spacetime to Reissner-Nordstrom spacetime, to Misner and Wheeler's program of realizing “charge without charge”.

On unstructured grids, the tangent of hyperbola for interface capturing (THINC) method with quadratic surface representation and Gaussian quadrature (THINC/QQ) requires topology-dependent numerical quadrature for cell and face integrals and Newton iteration for the surface constant. This study introduces a quadratic moment-matched sigmoid (QMMS) approximation that evaluates these quantities from the mean and variance of the quadratic field while retaining the hyperbolic-tangent reconstruction profile and the boundary variation diminishing (BVD) formulation. A slope-matched Gaussian cumulative distribution function and a moment-matched Gaussian model provide closed form approximations for the surface constant and face averages, eliminating Newton iteration and topology-dependent runtime quadrature from these evaluations. Single-cell tests and nine two- and three-dimensional benchmarks assess reconstruction accuracy, flow-field differences, and computational cost. Across the tested cases, the principal transported and shock structures remain closely aligned with those obtained using THINC/QQ, with local differences concentrated mainly near discontinuities, contact regions, and developed shear layers. Reconstruction-stage profiling gives mean THINC/QQ-to-QMMS time ratios of 2.12 in two dimensions and 1.85 in three dimensions. QMMS therefore reduces reconstruction-stage cost while replacing topology-dependent runtime integral evaluation with a common moment-based formulation

Although photomultiplier tubes (PMTs) are sufficiently sensitive for applications based on counting single photons, the thermionic emission of electrons from the photocathode is one of the dominant background sources. In this study, we modeled the dark count rate of a given PMT as a function of the temperature and external electric field based on the Richardson-Dushman equation and incorporated the Schottky effect. To validate the model, measurements were performed using an eight-centimeter Hamamatsu R14374 PMT equipped with a bialkali photocathode. The dark count rate was measured over a range of temperatures from 10 to 40 degree Celsius. An external electric field was applied to the outside surface of the optical window with the photocathode by varying the potential difference between the photocathode and the surrounding medium from 0 to 1100 V. The result confirmed that the influence of the external potential difference remained relatively small within a difference of 200 V, with the increase in the dark count rate remaining below 50 % across all measured temperatures. This behavior was incorporated into the proposed model by including an error function to predict the dark count rate under operating conditions with varying temperatures and external electric fields.

Electrostatic (ES) field enhancement at sharp conducting structures plays a central role in lightning protection, corona discharge, electrical breakdown in vacuum (for example in particle accelerators), and more generally in technological applications of field electron emitters. A canonical geometry for studying this ES effect is the hemisphere-on-cylindrical-post (HCP) model, in the regime where the structure stands on a planar conductor of large lateral extent, and a large gap exists between the structure and the counter-electrode. A parameter of major interest is the apex field enhancement factor (AFEF) (apex-ES-field/background-ES-field). For this (and other) structures, a formula for the AFEF can be written in the form AFEF = ASC x ASR, where the apex sharpness ratio (ASR) is given by the ratio (post-height/apex-radius-of-curvature), and the apex sharpness coefficient (ASC) depends on the post shape. For the HCP model, no exact analytical formulas for the ASC or the AFEF are currently known. (Quite possibly none exist.) This paper develops a compact analytical approximation for the ASC and hence for the AFEF. This compact formula has a logarithmic-style structure, rather than the power-style structure used in previous approximations. When compared with precise finite-element analyses of the HCP model, over the computationally accessible range 1 to 1000 for the ASR, this logarithmic-style formula has a maximum error-magnitude of 0.15 percent, which is significantly better than older approximations.

We investigate the growth of a circular domain in a phase-separating lipid membrane and its relation to the budding instability. We describe the in-plane dynamics with a conserved, time-dependent Ginzburg-Landau model under radial symmetry. Numerical solutions show a crossover of the domain size $D$ as a function of time $t$ from $D\sim t^{1/3}$ at early times to $D\sim t^{1/2}$ at later times, followed by saturation due to finite system size. The time-dependent line tension $\sigma(t)$, evaluated from the evolving concentration profile, rises rapidly before approaching the planar-interface value. This behavior distinguishes an early line-tension-dominated regime from a later domain-size-dominated regime. To estimate the budding instability, we combine $D(t)$ and $\sigma(t)$ with a quasistatic criterion for the loss of stability of a partially budded domain. The budding-instability time decreases with increasing membrane spontaneous curvature and increases near the critical point. Thus, the evolution of both domain size and line tension is essential for determining the time required for the budding instability.

We experimentally explore the collective behavior of the nematode T. Aceti inside flexible boundaries showing the emergence of previously unreported states. These nematodes have been previously shown to be able to synchronize their body oscillations in a favorable condition of confined space. In this collective state, they are able to exert a strong pushing force which we exploit to study how their collective motion could deform a pliable boundary. Using a novel experimental technique, we were able to simulate a non-rigid border at a liquid-liquid-gas triple point. We discovered a state with periodic boundary deformations which are due to the synchronized oscillations of the nematodes. More interestingly, we found a novel state where the nematodes are able to form multiple protrusions in the border which oscillate, rotate, merge, and split. We propose a numerical model that is able to reproduce some of the observed parameters of this state as well as offer an analytical insight into protrusions dynamics. Our research opens a pathway for exploring the interaction between active matter and flexible interfaces with a new kinds of active matter agents forming dynamic non-chaotic border deformations.

The effect of a porous coating on the water-exit dynamics of a circular cylinder is investigated experimentally. Cylinders comprising a $30~\mathrm{mm}$ solid core surrounded by a $10~\mathrm{mm}$-thick porous foam layer with pore densities of 10, 20, and 60 pores per inch (PPI) are compared with a smooth cylinder of the same outer diameter. Experiments are performed over $1.50\times10^{4}\leq Re\leq5.00\times10^{4}$ and $0.37\leq Fr\leq4.08$. Time-resolved particle image velocimetry characterizes the wake and reconstructed pressure field, while proper orthogonal decomposition (POD) examines its energetic organization. All porous cylinders reduce free-surface elevation relative to the smooth cylinder, with the largest reduction generally obtained for 60 PPI. The submerged wake, however, is not simply weakened. Porous cases generally develop larger circulation and vortex area, with a non-monotonic dependence on pore density and operating condition. The 10 PPI cylinder frequently produces the largest vortex region, whereas 60 PPI generates stronger negative pressure within the vortex and the largest integrated vortex-associated pressure deficit for $Fr=1.02$, $2.00$, and $4.08$. During the submerged approach to contact, this pressure deficit co-evolves strongly with circulation, with Pearson correlation coefficients typically between $0.90$ and $0.98$. POD shows that 9–18 modes recover 95% of the modal energy, with 20 PPI requiring only 9–10 modes. Overall, porous coating reorganizes wake strength, extent, pressure signature, and energetic structure while reducing the free-surface response.

Vision-language models (VLMs) are increasingly being used in scientific workflows, but their ability as agents to directly control laboratory experiments from visual feedback remains underexplored. This capability is important because many laboratory tasks do not naturally provide dense, pre-defined numerical objectives: informative signals can be sparse, intermittent, or visually ambiguous. A more general laboratory agent should instead be able to interpret visual observations, take actions to acquire useful feedback, and adapt its behavior based on the consequences of those actions. We study whether general-purpose VLMs can perform this kind of closed-loop scientific control using experimental optics as a testbed. We evaluate agents on three experimental systems that isolate distinct capabilities: a Michelson interferometer, a two-mirror cavity, and a four-mirror optical relay. The agents observe camera images, directly issue actuator and measurement commands, and retain their interaction history without receiving an engineered scalar objective during control. Across these experiments and matched simulations, we find that, given task-specific natural-language guidance, VLMs can estimate actuator-response relationships, resolve ambiguous observations through intervention, and actively create informative visual feedback when signals are sparse. These results suggest that pretrained multimodal models can serve as important decision-making agents within the experimental loop. Our work also establishes optics as a physically grounded testbed for visual reasoning and active perception in scientific agents.

Establishing chemical design rules that simultaneously control the electronic structure and thermal transport is a long-sought goal for heat-management and energy materials. Here, we demonstrate that a single B-to-C substitution changes the electron count and simultaneously reconstructs the bonding network and crystal structure, driving a metal-to-semiconductor transition while concurrently enhancing the lattice thermal conductivity. Using density-functional theory (DFT) and machine-learned interatomic potentials (MLIPs), we investigate the electronic structure, lattice dynamics, and phonon thermal transport in cubic BaB3C3 and its B-to-C-substituted tetragonal BaB2C4 structure. The substitution donates one electron per formula unit to the B-C framework, thereby triggering the formation of strong C-C bonds and opening a bandgap of 0.33 eV. The Message Passing Atomic Cluster Expansion (MACE) model reproduces DFT energies and forces, yielding phonon dispersion and lattice thermal conductivity in excellent agreement with DFT benchmarks. Thermodynamically stable cubic BaB3C3 possesses an isotropic lattice thermal conductivity of 7.6 W/mK at 300 K. Substituting B with C hardens the phonon dispersion (evidenced by a frequency upshift from ~800 to ~900 cm^-1) and simultaneously boosts both phonon group velocities and lifetimes. Consequently, the lattice thermal conductivity surges to 18.7 W/mK, representing a remarkable ~2.5-fold enhancement of the in-plane component and a transformation from isotropic to anisotropic behavior, characterized by kappa_x = kappa_y > kappa_z. Our results demonstrate that minimal B-to-C substitution provides a viable strategy to modulate the electronic structure, thereby transforming the crystal from a metal to a semiconductor and concomitantly enhancing phonon thermal transport.

Turbulent flows span a wide range of scales, making direct numerical simulation (DNS) prohibitively expensive at high Reynolds numbers. Large eddy simulation (LES) offers a pragmatic alternative by only resolving the large-scale motions, but its accuracy hinges on the subgrid-scale (SGS) model. We introduce the Tau-orthogonal (TO) framework to the lattice Boltzmann method (LBM) using a macroscopic-velocity forcing. The TO method shifts the modeling target from a high-dimensional SGS field to the time dynamics of a small set of spatially integrated quantities of interest (QoIs). Training data are generated by a predictor-corrector tracking procedure that nudges coarse simulations toward reference QoI trajectories. Lightweight linear regression models with stochastic, multivariate Gaussian residuals (LRS) then drive the LES autonomously. Compact convolution-based kernels replace the sharp Fourier filters of the original formulation, lifting its restriction to rectangular periodic domains. We first evaluate the closure on two-dimensional Kolmogorov flow, where TO-LRS yields stable, statistically accurate online LES. However, bounded high-frequency oscillations are observed in the solution fields. The decisive test is three-dimensional turbulent channel flow, simulated on a grid five times coarser in every direction than the high-fidelity reference. Here the plain BGK solver is unstable, and even calibrated Smagorinsky and WALE models over-dissipate the near-wall flow. TO-LRS, applied on top of an eddy-viscosity substrate and with the QoI set augmented by mean-profile QoIs, reproduces the reference distributions and holds the DNS mean velocity profile, at $40\times$ lower online cost per simulated time unit than the high-fidelity simulation. These results establish reduced, QoI-based closures as an interpretable and inexpensive alternative to high-dimensional neural SGS models for LBM.

An improved algorithm to implement our previously proposed static quantum embedding method MPCC (J. Chem. Phys. 161, 164107 (2024)) is presented. It uses the density-fitting (DF) approximation for the electron-repulsion integrals (ERIs) across all layers of the embedding method: the low-level method, the screened interaction, and the high-level method. Additionally, an approximate factorized solution of the Sylvester equation is employed based on the Laplace transformation for the low-level method. To build the screened interaction, we have explored an approximate construction of it based on the distinguishable cluster approximation (DCA) by Kats and Manby (J. Chem. Phys. 141, 061101 (2014)), which amounts to neglecting certain higher-order exchange and ladder diagrams. Combining all these techniques, we have obtained an $\mathcal{O}(N^4)$ algorithm for the low-level method; a non-iterative $N_{\rm frag} \mathcal{O}(N^4)$ algorithm for the screened interaction; and an iterative $\mathcal{O}(N_{\rm frag}^6)$ algorithm for the fragment solver, where $N_{\rm frag}$ is the number of fragment orbitals and $N$ is the total number of orbitals. The resulting low-scaling implementation of the MPCC method is applied to trans polyacetylenes, that is, C$_{2n}$H$_{2n+2}$ molecules for chain lengths $n=1-8$, and the timing and accuracy of the method are compared to the original unfactorized implementation. Moreover, the approximations are further validated by applying the method to the potential energy surface of the \ce{O3} molecule. Finally, we apply the method to the selected molecules in the S22 dataset for which the performance of the MP2 method is known to be poor. The results demonstrate that the DF-based implementation of the MPCC method provides a significant reduction in computational cost while maintaining accuracy comparable to that of the original implementation.