Papers

The liquid-vapor critical behavior of water is strongly influenced by both ionic solutes and confinement. Molecular dynamics simulations of aqueous NaCl solutions using the TIP4P/2005 water model and the Madrid-2019 ion parameters reveal a systematic increase in the liquid-vapor critical temperature and pressure with salt concentration, consistent with experimental trends. In contrast, confinement between parallel hydrophobic plates leads to a depression of the critical point. The critical temperature was determined from the Binder cumulant crossing in the NVT ensemble, using a recently developed method originally applied to an active Brownian particle system. The reliability of this approach was verified through complementary NPT simulations. We further demonstrate the pronounced sensitivity of the estimated critical point to the van der Waals cutoff distance, underscoring the importance of properly accounting for long-range interactions. Our framework, which employs and tests an adjusted subbox method, can be readily extended to other critical phenomena, including the liquid-liquid critical point of water.

We optimize theoretically and experimentally the performances of the recently demonstrated modulation transfer protocol [D.-A. Trinh, K. V. Adwaith, M. Branco, A. Rouxel, S. Welinski, P. Berger, F. Goldfarb, and F. Bretenaker, Applied Physics Letters 125, 154001 (2024)] aiming at extending the bandwidth of quantum RF receivers based on hot Rydberg atoms. This optimization relies on tuning the parameters of the phase modulation of the coupling beam, which is converted by the nonlinear response of the atoms into an amplitude modulation of the probe beam. We develop a theoretical model to optimize both the modulation frequency and the modulation amplitude of the coupling beam, thereby maximizing the atomic response. Once optimized, the sensitivity to detuned RF fields of this modulation transfer protocol is measured and compared with that of the conventional protocol. This comparison shows that the new protocol permits a strong increase in the detection bandwidth. Indeed, it outperforms the usual one as soon as the RF signal to be measured is detuned by more than a few MHz. We illustrate the capability of this modulation transfer protocol to enhance the detection bandwidth by showing experimentally how it permits to bridge the gap between two Rydberg transitions separated by 166 MHz. In all cases, the experimental results are in good agreement with the simulations.

This study presents a detailed quantum chemical investigation of the electronic and excited-state properties of syn- and anti-isomers of the borane cluster B18H22 and their sulfur-doped derivatives. Using the PB86/def2-SVP level of theory with dispersion corrections, the research examines how sulfur substitution and non-covalent interactions influence cluster stability, electronic structure, spectra, and optoelectronic potential. Comparative analysis of the syn- and anti-isomers reveals the impact of molecular conformation on frontier molecular orbitals and related energetic and photophysical properties. Sulfur doping is shown to enhance charge delocalization, stabilize excited states, and improve thermal stability, which form key factors for tunable laser applications. The inclusion of advanced dispersion correction methods proves essential for accurately capturing many-body interactions that govern electronic behavior. By elucidating the interplay between structural features, substitution patterns, and computational modeling, the work provides valuable insights into structure-property relationships critical for designing borane-based materials with tailored optoelectronic and thermal characteristics. In addition to doping and dispersion effects, functionals' effects were examined through comparison amidst various ones with different asymptotic exchange on excitation and gap energies. In summary, the computational methodology combined good DFT/Basis/dispersion set to accurately predict geometries, IR/UV spectra, NMR chemical shifts, dipole moments, polarizability and excited-state properties, thereby offering a comprehensive theoretical understanding of syn-, anti- isomers of B18H22 and its sulfur doped variants.

The article discusses an original spectroscopic method for the study of supersonic argon jets in atomic and cluster flow regimes. The method is based on absolute measurements of the VUV radiation flux from a supersonic argon jet induced by a 1 keV electron beam. The integral radiation flux and spectral distribution of the radiation flux density of a supersonic argon jet in the range of 50-150 nanometers were measured, which made it possible to determine the density of the non-condensed atomic component, the fraction of condensate, and the density of clusters in a supersonic argon jet at given parameters of its flow into vacuum. The obtained parameters also allowed us to estimate the emission cross sections for the argon resonance lines ArI ({\lambda}=104.8 nm, {\lambda}=106.7 nm) and the cluster continuum {\lambda}=127 nm.

In this study, we conducted a theoretical analysis of specific C36 and O@C36 Fullerene isomers, namely those with (D3h, C1, Cs, C2, D2) symmetries, in the gaseous phase using the DFT method at B3LYP/6-31G* level. We studied geometry optimizations, relative stability, atomization energies, Fermi energy, energy gap, electronic properties, electric dipole moment, polarizabilities, and thermodynamic analysis, along with IR and NMR spectra. Consistently, our findings revealed distinct properties and characteristics among different C36 fullerene isomers. The energetic order of C36 fullerene isomers was established as C36-D3h < C36-C1 < C36-Cs < C36-C2 < C36-D2, a trend unaffected by the encapsulation of oxygen. Notably, the D2 isomer displayed the smallest energy gap, indicating higher electrical conductivity compared to other isomers, while it exhibited the largest gap after encapsulation. Furthermore, we observed that the C1 (D2) isomer exhibited the largest (smallest) Electric dipole moment among the studied C36 isomers, whereas the C2 (D2) isomer demonstrated the largest Electric dipole moment among the O@C36 isomers studied. The encapsulation of oxygen in C36 isomers influenced their properties, including alterations in electronic properties, IR, and NMR chemical shifts. A detailed analysis of BSSE corrections showed the tininess of their impact on the analyzed observables, such that uncorrected and BSSE-corrected calculations led to nearly identical results, confirming the robustness and reliability of the B3LYP/6-31G* approach used in this work and, eventually, in other large and rigid fullerenes systems.

The representation and future evolution of summer Greenland atmospheric blocking in climate models is here investigated from a Lagrangian perspective using a novel Python package blocktrack. By applying the blocktrack algorithm to ERA5 reanalysis and a CMIP6 model ensemble, we identify and track blocking events over Greenland, and obtain their trajectories, intensities, duration and wave-breaking patterns. Greenland blocking (GB) events in ERA5 are then classified into two types based on their wave-breaking characteristics. These correspond to the previously identified upstream (anticyclonic wave breaking) and retrograding (cyclonic wave breaking) GBs. Upstream blocks, which originate in Northern Canada, exhibit stronger moisture transport before and during blocking onset and higher temperature anomalies than retrograding blocks, which follow an east-to-west trajectory and originate in the North Atlantic. Our analyses show how the recent observed increase in GB frequency, particularly in 2012, is primarily driven by upstream blocks. CMIP6 models generally fail to capture the observed increase and underestimate GB variability, especially for the upstream component. Projections under the SSP3-7.0 scenario show a decline in retrograding blocks but a possible increase in upstream blocks, depending on the detection index used. We discuss possible drivers of these changes, which include jet stream shifts, increased frequency of high-moisture transport events from low to high latitudes, surface temperature increases due to Atlantic Multidecadal Variability and Arctic Amplification. By analyzing block trajectories, this study demonstrates how Lagrangian diagnostics can provide novel insights into the dynamics of blocking events over Greenland.

A quantitative phase analysis of substrate-free single-component and binary clusters of the Ar-Kr system obtained by adiabatic expansion of gas into vacuum through a supersonic nozzle was performed. The studies were carried out in-situ using transmission electron diffraction technique (THEED) on clusters with an average size ranging from 2000 to 100000 atoms/cluster and across the entire range of component concentrations. The independence of the threshold size of clusters, corresponding to the beginning of the formation of the hcp phase, from the component composition was revealed. It was established that clusters larger than this threshold size have a two-phase fcc-hcp structure with an identical concentration of components in each phase. The fraction of the hexagonal phase increases with the size of the aggregations and depends on the component content, reaching maximum in clusters with an equimolar composition. Arguments are presented in favor of the formation of two-phase clusters in the supersonic jet, rather than separate single-phase fcc and hcp ones. These findings are in good agreement with the previously proposed thermally activated diffusion mechanism for the nucleation and growth of the hcp phase in rare gas clusters.

Molecules are emerging as new benchmark for metrology and fundamental physics research, driving the demand for spectroscopic techniques combining high sensitivity and resolution. Photoacoustic spectroscopy has proven to combine high sensitivity with appealing features like compactness, wavelength-independent and background-free detection. To date, photoacoustic sensing has mostly been focused on high-pressure applied trace-gas analysis, while accessing the low-pressure regime has been considered not compatible with efficient acoustic wave propagation. However, sensing gas samples at low pressure is the key to get access to high-resolution spectroscopy. Here, we demonstrate that sub-Doppler saturation spectroscopy can be performed on low-pressure trace gases in a cavity-enhanced photoacoustic sensor with mW-level mid-infrared radiation. Moreover, we show that the same setup can be operated at higher pressure, enabling trace-gas detection with 5 parts-per-billion sensitivity with a laser power as low as 35 microwatts. This allows to extend the unique advantages of the photoacoustic technique to metrology and fundamental physics and provides the mid-infrared with a cost-effective, flexible tool combining high sensitivity and resolution.

We offer a quantum chemical analysis of mono-halogenated borane molecules using DFT and TD-DFT theories, applying the PBE0/def2-SVPD and B3LYP/6-311+G(d) methods as implemented in ORCA, and explore how solvent effects influence electronic transition properties. The comparable benchmarks are the archetype anti-\ce{B18H22} denoted as (1) against hypothetical halogenated derivatives: 7-F-anti-\ce{B18H21} (2), 4-F-anti-\ce{B18H21} (3), and the recently synthesized 4-Br-anti-\ce{B18H21} (4). The analysis includes an optimization of the ground and first singlet excited states, vibrational frequency analysis, and a comprehensive spectroscopic profile covering IR, Raman, UV-Vis absorption, and emission spectra. The IR spectra of the fluorinated compounds feature a characteristic B-F stretching peak, while the Raman spectra closely resemble the parent molecule. UV-Vis spectral analysis shows a redshift and oscillator strength enhancement for F at position B7, indicating altered electronic properties due to substitution with lighter halogen. Furthermore, solvent effects enhance the probability of electronic transitions. Halogene presence led to a decrease of the energy gap EG(LUMO-HOMO) due to the stabilization of LUMO, which implied a redshift in the emission/absorption wavelength spectra, with the largest EG change at around 14% occurring for the (4)$^{th}$ benchmark compound.. Notably, all compounds emit light within the visible spectrum, underscoring their potential for optoelectronic applications.

Pathological hubs in the brain networks of epilepsy patients are hypothesized to drive seizure generation and propagation. In epilepsy-surgery patients, these hubs have traditionally been associated with the resection area (RA): the region removed during the surgery with the goal of stopping the seizures, and which is typically used as a proxy for the epileptogenic zone. However, recent studies hypothesize that pathological hubs may extend to the vicinity of the RA, potentially complicating post-surgical seizure control. Here we propose a neighbourhood-based analysis of brain organization to investigate this hypothesis. We exploit a large dataset of pre-surgical magnetoencephalography-derived whole-brain networks from 91 epilepsy-surgery patients. Our neighbourhood focus is 2-fold. Firstly, we propose a partition of the brain regions into three sets, namely resected nodes, their neighbours and the remaining network nodes. Secondly, we introduce generalized centrality metrics that describe the neighbourhood of each node, providing a regional measure of hubness. Our analyses reveal that both the RA and its neighbourhood present large hub status, but with significant variability across patients. For some, hubs appear in the RA; for others, in its neighbourhood. Moreover, this variability does not correlate with surgical outcome. These results highlight the potential of neighbourhood-based analyses to uncover novel insights into brain connectivity in brain pathologies, and the need for individualized studies, with large enough cohorts, that account for patient-specific variability.

Recent observations by the IceCube Neutrino Observatory have revealed a significant excess of high-energy neutrinos from nearby Seyfert galaxies, such as NGC~1068, without a corresponding flux of high-energy gamma-rays. This suggests that neutrinos are produced via hadronic interactions in a region opaque to gamma-rays, likely a hot corona surrounding the central supermassive black hole. However, the mechanism responsible for accelerating the parent protons to the required energies ($\sim 100$ TeV) remains an open question. In this study, we investigate diffusive shock acceleration (DSA) in active galactic nucleus (AGN) coronae using a suite of one-dimensional Particle-in-cell (PIC) simulations spanning a broad range of plasma parameters. We find that DSA is a robust and efficient mechanism for proton acceleration, consistently channeling approximately 10% of the shock's kinetic energy into non-thermal ions, even for shocks with sonic Mach number as low as $ M_s \approx 2$. In contrast, the efficiency of electron acceleration is highly variable and less efficient ($<1\%$) in our parameter survey. These findings provide strong, first-principles support for the hadronic models of neutrino production in AGN and offer quantitative constraints that can explain the observed gamma-ray deficit.

Semiconducting Barrier Discharges (SeBDs) generate uniform ionization waves in air at atmospheric pressure. In this work, we investigate how externally applied irradiation synchronized with the discharge can mimic photoconductive-type coupling between the plasma and the semiconductor surface. By illuminating the Si-SiO$_2$ interface with nanosecond pulsed irradiation at wavelengths from 532 nm to 1064 nm, and using fast imaging, optical emission spectroscopy, and current-voltage measurements, we demonstrate that the photoexcitation of charge carriers in silicon enhances the plasma emission and increases the reduced electric field, with no detectable change in the electrical energy. The magnitude and thresholds of these responses depend on wavelength. By comparing the SeBD to a MOS photodetector, this behaviour can be explained by the absorption length. This length determines whether carriers are photogenerated inside the depletion region at the SiO$_2$-Si interface, where they are efficiently separated and undergo impact-ionization amplification, or deeper in the silicon bulk where carrier separation is weaker and free-carrier absorption diminishes the quantum efficiency. These results focus on the microscopic processes governing the plasma-semiconductor coupling and demonstrate how the optoelectronic properties of silicon can influence surface ionization waves.

Wide channel Couette (WCC) turbulence is striking in being dominated by a large-scale spanwise periodic structure composed of streamwise streaks and associated roll superstructures. This apparent equilibrium is shown in this work to correspond to a fixed point solution of the Navier-Stokes equations expressed in the statistical state dynamics (SSD) framework. Moreover, this fixed point solution is found to be rank-three, consisting of one analytically identified roll-streak structure (RSS) constituting the first cumulant of the SSD, and two analytically determined eigenmodes supporting the second cumulant. This minimal representation captures both the structure and the dynamics of WCC turbulence, while the remaining spectral components contribute negligibly to the equilibrium dynamics. Turbulent Couette flows other than WCC can be understood to be limit cycle and chaotic extensions supported by the same underlying mechanism as the fixed point WCC turbulence except for the two eigenmodes supporting WCC turbulence being replaced by two Floquet modes and two Lyapunov vectors, respectively. These results provide an analytic solution for turbulence in Couette flow.

The register tube marks the invention of the clarinet in the early eighteenth century, tripling the range of its ancestor, the chalumeau, and giving it the widest range among wind instruments. Opening this narrow tube causes the fundamental frequency of the played note to increase by a factor of three, from the first to the second register of the resonator. The geometry and location of the register hole condition not only this mode selection mechanism, but also the global tuning of the second register. However, existing self-sustained nonlinear models of reed instruments fail to predict whether a register transition can occur, limiting optimization of the register hole geometry. Here, we introduce a sparse self-oscillating clarinet model that includes localized nonlinear acoustic losses in the register hole. This nonlinear mechanism is shown to be necessary to reproduce register transitions observed experimentally. Using systematic exploration of the control and design parameter spaces, we identify combinations of register hole diameter, position, and chimney length that ensure reliable register transitions. We show that the competing demands of playability and tuning are only satisfied by a long and narrow tube. Our findings provide a predictive tool for instrument making, assisting manufacturers in refining clarinets as well as other reed instruments, including oboes, bassoons, and saxophones.

Overload-induced cascading failures can cause extreme disruptions in a wide range of networked systems, such as power grids, transportation networks, or financial systems. Empirical studies across domains report that the size of such disruptions often follows a Pareto- or heavy-tailed distribution. While many models reproduce this scaling behavior, they are either tailored to specific domains or based on simplified mechanisms that overlook key aspects of overload cascading behavior. Hence, a general understanding of the mechanisms driving scale-free behavior in these settings remains incomplete. In this paper, we develop a universal and analytically tractable model of overload cascading failures on flow networks, offering a new perspective on how Pareto-tailed disruptions emerge across networks. Our framework shows, under mild assumptions, that heavy-tailed disruptions can arise naturally from Pareto-tailed external inputs, and it establishes a transformation law linking the input and output tail exponents. We further identify broad conditions under which the resulting cascade cost exhibits a heavy-tailed distribution and show that the mechanism is robust across several domains, including power transmission, traffic networks, and processing systems. Our results provide a unified explanation for the emergence of scale-free failures in overload-driven systems and connect previously disparate, application-specific models under a unified framework.

This paper investigates the impact of particles on isothermal flow inside a lab-scale swirl combustor for a fixed inlet swirl number of 0.67 using steady-state CFD simulations. The combustor geometry and baseline conditions, with no particles, are taken from Taamallah et al. [1], but with a simplification. In the present work, we provide rotation to the flow using velocity boundary condition, whereas in [1], a swirler is built into the geometry to achieve the same effect. Shear stress transport (SST) k-omega model, an eddy-viscosity based Reynolds averaged Navier-Stokes equation approach, is used for modelling turbulence. The comprehensive model is validated against the experimental axial-velocity data in [1]. Two simulations, one with 75 and another with 100 micron particles using Discrete particle model (DPM) were conducted to isolate the effect of particle motion on swirl-combustor flow without combustion. Their analysis shows significant downstream shift of central recirculation zone (CRZ). An effect that can significantly impact the stabilization of coal flame in pulverized particle reactors.

We consider the nature of the wave function using the example of a harmonic oscillator. We show that the eigenfunctions $\psi_n{=}z^n$ of the quantum Hamiltonian in the complex Bargmann-Fock-Segal representation with $z\in\mathbb C$ are the coordinates of a classical oscillator with energy $E_n=\hbar\omega n$, $n=0,1,2,...\,$. They are defined on conical spaces ${\mathbb C}/{\mathbb Z}_n$ with cone angles $2\pi/n$, which are embedded as subspaces in the phase space $\mathbb C$ of the classical oscillator. Here ${\mathbb Z}_n$ is the finite cyclic group of rotations of the space $\mathbb C$ by an angle $2\pi/n$. The superposition $\psi =\sum_n c_n\psi_n$ of the eigenfunctions $\psi_n$ arises only with incomplete knowledge of the initial data for solving the Schrödinger equation, when the conditions of invariance with respect to the discrete groups ${\mathbb Z}_n$ are not imposed and the general solution takes into account all possible initial data parametrized by the numbers $n\in\mathbb N$.

The article describes fundamental analytical properties of an unforced mechanical oscillator with a Duhem-type viscoelastoplastic hysteretic element. These properties include global existence of solutions, uniqueness of solutions, and convergence of each solution to an equilibrium point.

We demonstrate photonic control of radiative heat transport in nanoscale networks through phase-controlled interference between elastic and inelastic Floquet scattering channels induced by temporal permittivity modulation. Relative modulation phases select constructive or destructive interference, enabling directional thermal-photon currents and heat splitting even at thermal equilibrium. Modulation amplitude and frequency further tune the enhancement, suppression and redistribution of energy flow. This interference-based mechanism enables thermal routing and logic operations and provides a general platform for reconfigurable photonic heat management at the nanoscale.

Chiral particles are experimentally investigated while settling inwater with various turbulence intensity levels. The locations and orientations of the particles are tracked over time, allowing the close investigation of the particles' settling dynamics. The generated turbulent flow is measured using laser Doppler anemometry (LDA), and the turbulence strength varies between experiments in the range $0 \leq Re_\lambda \leq 250$. Starting with quiescent particle settling, the chiral particle's orientation dynamics are studied, revealing a preferred alignment and a strong translation-rotation coupling. The particle chirality determines the preferred rotation direction, though the alignment and translation-rotation coupling gradually vanish with increasing turbulence. We identify multiple settling modes for the chiral particles, which are characterised by the evolution of the rotation angles. Finally, a theoretical model assuming a simplified chiral particle in Stokes flow clarifies the emergence of each settling mode.

This work investigates the weakly nonlinear dynamics of internal shear layers and the mean zonal flow induced by the longitudinal libration of an inner core within a spherical shell. Building on the work of He et al. (J. Fluid Mech., vol. 939, 2022, A3), which focused on linear dynamics, we adopt a similar setup to explore the nonlinear regime using both asymptotic theory and numerical computations, with Ekman numbers as low as $E=10^{-10}$. A specific forcing frequency of $\widehat{\omega}=\sqrt{2}\widehat{\Omega}$, where $\widehat{\Omega}$ denotes the rotation rate, is introduced to generate a closed rectangular path of characteristics for the inertial wave beam generated at the critical latitude. Our approach extends previous results by Le Dizès (J. Fluid Mech., vol. 899, 2020, A21) and reveals that nonlinear interactions are predominantly localized around regions where the wave beam reflects on the boundary. We derive specific scaling laws governing the nonlinear interactions: the width of the interaction region scales as $E^{1/3}$, and the amplitude of the resulting mean zonal flow scales as $E^{1/6}$ in general. However, near the rotation axis, where the singularity of the self-similar solution becomes more pronounced, the amplitude exhibits a scaling of $E^{-1/2}$. In addition, our study also examines the nonlinear interactions of beams which are governed by different scaling laws. Through comparison with numerical results, we validate the theoretical predictions of the asymptotic framework, observing good agreement as the Ekman number decreases.

We report rovibronic spectra of the A $^3\Sigma^+$($v'=0-2$) - X $^3\Pi_\Omega(v=0)$ rovibronic transitions ($|\Omega|=0, 1$ and 2) of the CO$^{2+}$ doubly-charged molecular ion. Spectra were recorded at high resolution ($\sim 5$~cm$^{-1}$) in a fast beam of CO$^{2+}$ molecules by detecting the Coulomb explosion of the molecules upon excitation to the A state. Measurements were guided by ab initio calculations which then assisted the assignment of the observed spectral features. Our results resolve the spin-orbit splittings of the ground vibronic state X $^3\Pi_\Omega(v=0)$, but not the rotational structure of the bands due to spectral congestion, and provide spectroscopic information on CO$^{2+}$ with unprecedented resolution. In doing so they expand our knowledge of this benchmark doubly charged molecular ion and expand the short list of doubly charged molecules studied at high resolution.

We report a self-supervised deep learning framework for Rydberg sensors that enables single-shot noise suppression matching the accuracy of multi-measurement averaging. The framework eliminates the need for clean reference signals (hardly required in quantum sensing) by training on two sets of noisy signals with identical statistical distributions. When evaluated on Rydberg sensing datasets, the framework outperforms wavelet transform and Kalman filtering, achieving a denoising effect equivalent to 10,000-set averaging while reducing computation time by three orders of magnitude. We further validate performance across diverse noise profiles and quantify the complexity-performance trade-off of U-Net and Transformer architectures, providing actionable guidance for optimizing deep learning-based denoising in Rydberg sensor systems.

This paper investigates the temporal evolution of high-speed compressible fluids in irregular flow fields using the Fourier Neural Operator (FNO). We reconstruct the irregular flow field point set into sequential format compatible with FNO input requirements, and then embed temporal bundling technique within a recurrent neural network (RNN) for multi-step prediction. We further employ a composite loss function to balance errors across different physical quantities. Experiments are conducted on three different types of irregular flow fields, including orthogonal and non-orthogonal grid configurations. Then we comprehensively analyze the physical component loss curves, flow field visualizations, and physical profiles. Results demonstrate that our approach significantly surpasses traditional numerical methods in computational efficiency while achieving high accuracy, with maximum relative $L_2$ errors of (0.78, 0.57, 0.35)% for ($p$, $T$, $\mathbf{u}$) respectively. This verifies that the method can efficiently and accurately simulate the temporal evolution of high-speed compressible flows in irregular domains.

Exceptional points (EPs), ubiquitous non-Hermitian degeneracies, are central features in band structures where non-Hermitian Fermi arcs connect EPs and eigenvalue knots encircle them. Under open boundary conditions (OBCs), non-Hermitian skin effects enforce complex momenta and yield non-Bloch band structures, introducing EPs unique to OBCs whose origins depend on boundary-driven mechanisms. Here, we reveal both theoretically and experimentally that geometry itself can induce such non-Bloch EPs in a reciprocal non-Hermitian Lieb lattice supporting geometry-dependent skin effects. By analyzing non-Bloch band structures, we find that geometry-induced EPs correspond to saddle points rather than branch points. Branch points, even while carrying OBC eigenenergies, do not yield EPs but manifest as Whitney cusps, a characteristic type of geometric singularity, and Fermi arcs connecting them remain crucial in determining eigenvalue knots. Our measurements of these knots confirm that geometry-induced EPs are detached from the branch points of Fermi arcs, contrasting with their unified counterparts in Bloch systems. Our results establish geometry as an additional degree of freedom for engineering EP-based devices and reveal its fundamental role in shaping non-Bloch band structures.

The mean free path of photocarriers is a crucial parameter for material design, device optimization, and new optoelectronics applications. Currently, this parameter remains unknown for many materials, and experimental means available for its measurement are considerably lacking. Meanwhile, it remains an unclear issue whether the mean free path of the photogenerated high-energy hot carriers is significantly different from that of the localequilibrium-state carriers near the Fermi surface or around the band edge. Based on the concept of transient grating Fourier transform and utilizing a virtual lock-in amplification technique, we proposed and demonstrated an efficient experimental technique for measuring the mean free path of photocarriers. This method has facilitated direct observation of the photocarrier transport behavior across the transition between diffusive and ballistic motion, from which we surprisingly find that the mean free path of photogenerated hot carriers in Silicon membrane and GaAs quantum well can reach micron scale, more than an order of magnitude larger compared to the electrically-measured one. This work provides new ideas for characterization of photoelectronic devices under operating status and is expected to greatly enhance the understanding of the photocarrier transport process in opto-electronic or photonic materials.

Many real-world scale-free networks, such as neural networks and online communication networks, consist of a fixed number of nodes but exhibit dynamic edge fluctuations. However, traditional models frequently overlook scenarios where the node count remains constant, instead prioritizing node growth. In this work, we depart from the assumptions of node number variation and preferential attachment to present an innovative model that conceptualizes node degree fluctuations as a state-dependent random walk process with stasis and variable diffusion coefficient. We show that this model yields stochastic dynamic networks with stable scale-free properties. Through comprehensive theoretical and numerical analyses, we demonstrate that the degree distribution converges to a power-law distribution, provided that the lowest degree state within the network is not an absorbing state. Furthermore, we investigate the resilience of the fraction of the largest component and the average shortest path length following deliberate attacks on the network. By using three real-world networks, we confirm that the proposed model accurately replicates actual data. The proposed model thus elucidates mechanisms by which networks, devoid of growth and preferential attachment features, can still exhibit power-law distributions and be used to simulate and study the resilience of attacked fixed-size scale-free networks.

Dynamic control of laser emission direction is crucial for developing compact and reconfigurable nanophotonic devices. In this work, we numerically present a plasmonic nanolaser (PNL) integrated with a voltage-controlled liquid crystal (LC) layer to achieve active beam steering. We modeled the orientation of LC molecules under an applied bias and incorporated this into electromagnetic simulations to assess the optical response. We observed lasing at an emission wavelength of 870 nm for the single-mode PNL, with discrete voltage-dependent deflections of the far-field emission of up to $\pm67$\textdegree, while maintaining a beam divergence of less than 1\textdegree. The steering characteristics were significantly influenced by the electro-optic properties of the LC layer, with an optimized thickness of 3 $\mu$m. The structural periodicity governed the achievable angular separation and emission stability. Furthermore, we extended the concept to a dual-mode nanolaser based on a merged nanohole array (NHA), which supports two lasing wavelengths at 873 nm and 880 nm. Both lasing modes exhibited simultaneous voltage-dependent angular tuning without altering the cavity geometry. These results highlight the potential of LC-integrated PNLs as voltage-controlled, reconfigurable light sources for applications in optical interconnects, beam routing, adaptive imaging, and multiplexed communication.

We present a new approach to forecasting North Pacific Sea Surface Temperatures (SST) by recognizing that interannual variability primarily reflects amplitude changes in four dominant seasonal cycles. Our multivariate linear model simultaneously captures these amplitude-modulated seasonal cycles along with the Pacific Decadal Oscillation (PDO), which naturally emerges as an intrinsic feature of the system rather than a separate phenomenon. Using sixteen-dimensional regression based on four spatially distributed time series per variable, the model delivers unprecedented forecast accuracy for both interannual amplitude modulations and PDO evolution, maintaining skill beyond 36 months – a substantial improvement over current operational and research forecasts, including machine learning methods. Predictions initialized in 2024 project that the PDO will remain in its negative phase through late 2026, implying reduced likelihood of severe marine heatwaves in the eastern North Pacific during this period. These findings have direct implications for regional climate impacts, including storm tracks, precipitation patterns, and marine ecosystem health. By treating seasonal and interannual variability as coupled rather than independent processes, this framework advances our understanding of North Pacific climate dynamics and provides a powerful tool for stakeholders managing climate-sensitive resources and planning adaptation strategies in regions strongly influenced by North Pacific conditions.

Allostery is a fundamental mechanism of protein regulation and is commonly interpreted as modulating enzymatic activity or product abundance. Here we show that this view is incomplete. Using a stochastic model of allosteric regulation combined with an information-theoretic analysis, we quantify the mutual information between an enzyme's regulatory state and the states of downstream signaling components. Beyond controlling steady-state production levels, allostery also regulates the timing and duration over which information is transmitted. By tuning the temporal operating regime of signaling pathways, allosteric regulation enables distinct dynamical outcomes from identical molecular components, providing a physical mechanism for temporal information flow, signaling specificity, and coordination without changes in metabolic pathways.