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At least 109 records · Page 6

Deep learning-assisted modeling for χ (2) nonlinear optics

Modeling second-order (χ(2)) nonlinear optical processes remains computationally expensive due to the need to resolve fast field oscillations and simulate wave propagation using methods such as the split-step Fourier method (SSFM). This can become a bottleneck in real-time applications, such as high-repetition-rate laser systems requiring rapid feedback and control. We present a long short-term memory-based surrogate model trained on SSFM simulations generated from a start-to-end model of the photocathode drive laser at SLAC National Accelerator Laboratory’s Linac Coherent Light Source II. The model achieves over 250× speedup while maintaining high fidelity, enabling future real-time optimization and laying the foundation for data-integrated modeling frameworks and digital twins of laser systems.

Accelerator Physics (physics.acc-ph)↗

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗

Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics

In recent years deep neural networks have been proposed as a lightweight data-driven model to capture high-dimensional, nonlinear physical processes to predict building thermal responses. However, the need of a large amount of data for the training process of deep neural networks clashes with the potential limited data availability in most existing or new buildings. Transfer learning aims to enhance the performance of a target learner exploiting knowledge from related and similar environments. This study conducted a suite of experiments that leveraged 250 data-driven models based on a synthetic dataset of a building archetype to study the influence of data availability, energy efficiency level, occupancy and climate for the transfer process of thermal dynamics. The performance of the transfer learning process was compared against a classical machine learning approach. Here, the results suggest that building thermal dynamics can be effectively transferred under the same climatic conditions, increasing performance when dealing with different occupancy schedules, efficiency levels and low data availability. Furthermore, the paper compares the performance of both transfer learning and machine learning approaches in an online fashion, to support the implementation in real-world deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Suhl instabilities in nanoscopic spheroids

We simulate the magnetization dynamics of a permalloy spheroid of nanoscopic size in zero external field, such that both dipolar and exchange interactions are important. Low excitation power is used to obtain the frequencies and mode patterns of many normal modes. At higher power, non-linear three and four mode couplings between magnons carrying orbital angular momentum are observed to give rise to Suhl instabilities. Suhl’s analysis of the selection rules governing the allowed processes is extended to initial states other than uniform precession. These rules are studied and confirmed by the simulations. Both down- and up-conversion are seen as well as three and four-mode processes. As a result, general trends are inferred for preferred instabilities among those that are allowed, although the thresholds for some instabilities appear to be very high.

3D nanomagnetism↗

Single-Atom Doping at the Molecule–Metal Interface: How Rh Affects Surface Explosion Kinetics

Controlling chemical reactions at interfaces is central to many fields, including atmospheric, environmental, and biological chemistry as well as catalysis and corrosion. We performed a fundamental study of how catalytically active Rh atoms placed at and above a molecule-metal interface influence the surface reaction kinetics of tartaric acid (TA) decomposition. Specifically, TA decomposition on Cu(100) exhibits autocatalytic decomposition kinetics involving a slow initiation step followed by fast decomposition of the molecular layer. These so-called “surface explosions” are extremely sensitive to initial conditions, making it fundamentally interesting to study how the placement of reactive atoms affects the reaction rate. Temperature-programmed reaction (TPR) experiments reveal that Rh atoms embedded in the Cu(100) surface beneath TA (TA/Rh/Cu) or atop the TA layer (Rh/TA/Cu) reduce the decomposition temperature and modify the reaction rate constants. Isothermal TPR analysis reveals that Rh enhances both the initiation rate constant, k i , and the explosion rate constant, k e , facilitating explosive decomposition at lower temperatures. This result provides evidence that both the initiation and explosion steps occur at the metal-molecule interface and are accelerated by the presence of Rh at this interface. This study illustrates how small amounts of reactive elements may be used to control nonlinear kinetic processes at interfaces.

desorption↗

Circularly Polarized Attosecond Pulses Enabled by an Azimuthal Phase and Polarization Grating

High-harmonic generation (HHG) is an extreme nonlinear optical process that can map the properties of an infrared driving laser beam onto short wavelength attosecond pulse trains. However, current techniques for generating circularly polarized high harmonics for probing magnetic materials and chiral systems have limitations: two-color collinear counter-rotating driving lasers result in a low cutoff photon energy, while single-color non-collinear counter-rotating schemes suffer from low conversion efficiency. In this work, we generate circularly polarized attosecond pulse trains by using a structured laser driver which has a rotating polarization and phase grating along the azimuthal coordinate. Furthermore, our experimental and numerical results demonstrate the production of left and right circularly polarized harmonics, which naturally separate upon propagation. Our approach uses a single laser color in a collinear geometry, that can be scaled for high efficiency. Simulations show this scheme can extend into the soft x-ray region when driven by mid-infrared driving lasers, while preserving the same high phase-matching cutoff photon energy as for linearly-polarized high harmonics.

attosecond science↗

Protonic nickelate device networks for spatiotemporal neuromorphic computing

Computation in biological neural circuits arises from the interplay of nonlinear temporal responses and spatially distributed dynamic network interactions. Replicating this richness in hardware has remained challenging, as most neuromorphic devices emulate only isolated neuron- or synapse-like functions. Here we introduce an integrated neuromorphic computing platform in which both nonlinear spatiotemporal processing and programmable memory are realized within a single perovskite nickelate material system. By engineering symmetric and asymmetric hydrogenated NdNiO 3 junction devices on the same wafer, we combine ultrafast, proton-mediated transient dynamics with stable multilevel resistance states. Networks of symmetric NdNiO 3 junctions exhibit emergent spatial interactions mediated by proton redistribution, while each node simultaneously provides short-term temporal memory, enabling nanosecond-scale operation with an energy cost of ~0.2 nJ per input. When interfaced with asymmetric output units serving as reconfigurable long-term weights, these networks allow both feature transformation and linear classification in the same material system. Leveraging these emergent interactions, the platform enables real-time pattern recognition and achieves high accuracy in spoken digit classification and early seizure detection, outperforming temporal-only or uncoupled architectures. These results position protonic nickelates as a compact, energy-efficient, CMOS-compatible platform that integrates processing and memory for scalable intelligent hardware.

Electrical and electronic engineering↗

Visualization of bulk and edge photocurrent flow in anisotropic Weyl semimetals

Materials that rectify light into current in their bulk are desired for optoelectronic applications. In Weyl semimetals that break inversion symmetry, bulk photocurrents may arise due to nonlinear optical processes that are enhanced near the Weyl nodes. However, the photoresponse of these materials is commonly studied by scanning photocurrent microscopy, which convolves the effects of photocurrent generation and collection. Here we directly image the photocurrent flow inside the type-II Weyl semimetals WTe 2 and TaIrTe 4 using high-sensitivity quantum magnetometry with nitrogen-vacancy centre spins. We elucidate a mechanism for bulk photocurrent generation, which we call the anisotropic photothermoelectric effect, where unequal thermopowers along different crystal axes drive intricate circulations of photocurrent around the photoexcitation. Using overlapping scanning photocurrent microscopy and magnetic imaging at the interior and edges of the sample, we visualize how the anisotropic photothermoelectric effect stimulates the long-range photocurrent collected in our WTe 2 and TaIrTe 4 devices through the Shockley–Ramo mechanism. Furthermore, our results highlight a widely relevant source of current flow and will inspire photodetectors that utilize bulk materials with thermoelectric anisotropy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spatially co-registered wide-field nonlinear optical imaging of living and complex biosystems in a total internal reflection geometry

Nonlinear optical microscopy that leverages an objective based total internal reflection (TIR) excitation scheme is an attractive means for rapid, wide-field imaging with enhanced surface sensitivity. Through select combinations of distinct modalities, one can, in principle, access complementary chemical and structural information for various chemical species near interfaces. Here, we report a successful implementation of such a wide-field nonlinear optical microscope system, which combines coherent anti-Stokes Raman scattering (CARS), two-photon fluorescence (TPF), second harmonic generation (SHG), and sum frequency generation (SFG) modalities on the same platform. The intense optical fields needed to drive these high order nonlinear optical processes are achieved through the use of femtosecond pulsed light in combination with the intrinsic field confinement induced by TIR over a large field of view. The performance of our multimodal microscope was first assessed through the experimental determination of its chemical fidelity, intensity and polarization dependences, and spatial resolution using a set of well-defined model systems. Subsequently, its unique capabilities were validated through imaging complex biological systems, including Hydrangea quercifolia pollen grains and Pantoea sp. YR343 bacterial cells. Specifically, the spatial distribution of different molecular groups in the former was visualized via vibrational contrast mechanisms of CARS, whereas co-registered TPF imaging allowed the identification of spatially localized intrinsic fluorophores. We further demonstrate the feasibility of our microscope for wide-field CARS imaging on live cells through independent characterization of cell viability using spatially co-registered TPF imaging. Overall, this approach to TIR enabled wide-field imaging is expected to provide new insights into bacterial strains and their interactions with other species in the rhizosphere in a time-resolved and chemically selective manner.

47 OTHER INSTRUMENTATION↗

Advances in the photon avalanche luminescence of inorganic lanthanide-doped nanomaterials

Photon avalanche (PA)—where the absorption of a single photon initiates a ‘chain reaction’ of additional absorption and energy transfer events within a material—is a highly nonlinear optical process that results in upconverted light emission with an exceptionally steep dependence on the illumination intensity. Over 40 years following the first demonstration of photon avalanche emission in lanthanide-doped bulk crystals, PA emission has been achieved in nanometer-scale colloidal particles. The scaling of PA to nanomaterials has resulted in significant and rapid advances, such as luminescence imaging beyond the diffraction limit of light, optical thermometry and force sensing with (sub)micron spatial resolution, and all-optical data storage and processing. In this review, we discuss the fundamental principles underpinning PA and survey the studies leading to the development of nanoscale PA. Finally, we offer a perspective on how this knowledge can be used for the development of next-generation PA nanomaterials optimized for a broad range of applications, including mid-IR imaging, luminescence thermometry, (bio)sensing, optical data processing and nanophotonics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatiotemporal dispersion compensation for a 200-THz noncollinear optical parametric amplifier

A noncollinear optical parametric amplifier (NOPA) can produce few-cycle femtosecond laser pulses that are ideally suited for time-resolved optical spectroscopy measurements. However, the nonlinear-optical process giving rise to ultrabroadband pulses is susceptible to spatiotemporal dispersion problems. Here, we detail refinements, including chirped-pulse amplification (CPA) and pulse-front matching (PFM), that minimize spatiotemporal dispersion and thereby improve the properties of ultrabroadband pulses produced by a NOPA. Here, the description includes a rationale behind the choices of optical and optomechanical components, as well as assessment protocols. We demonstrate these techniques using a 1 kHz, second-harmonic Ti:sapphire pump configuration, which produces ~5-fs duration pulses that span from about 500 to 800 nm with a bandwidth of about 200 THz. To demonstrate the utility of the CPA-PFM-NOPA, we measure vibrational quantum beats in the transient–absorption spectrum of methylene blue, a dye molecule that serves as a reference standard.

47 OTHER INSTRUMENTATION↗

Suppression of ion temperature gradient modes by Alfvén activity above a drive threshold in DIII-D

A recent study demonstrates that the suppression of ion temperature gradient (ITG) modes can occur during the nonlinear evolution of toroidicity-induced Alfvén eigenmodes (TAEs) in the DIII-D tokamak [Du et al., Phys. Rev. Lett. 135, 265101 (2025)]. In that work, ITG was suppressed by the formation of a narrow, TAE-induced shear flow layer, whose shearing rate exceeded the ITG decorrelation rate. Here, the shear flow arises from an imbalance between Reynolds and Maxwell stress forces, as the TAE departs from the conventional shear Alfvén wave polarization. This follow-up paper systematically identifies the plasma conditions required for robust ITG suppression through a series of comparative experiments. The results show that TAEs routinely suppress ITG turbulence in plasmas with higher local safety factor (q), elevated fast-ion beta, and larger populations of fast ions on passing orbits, i.e., conditions consistent with the substantial TAE drive. Database analysis further reveals the existence of a threshold in TAE drive for ITG suppression. That is, once the drive exceeds a critical value within a favorable q window, the system undergoes the nonlinear bifurcation process, characterized by a sharp increase in TAE saturated amplitudes at a nearly fixed fast ion drive, suppression of ITG turbulence, and the formation of an internal thermal transport barrier at the localized radii.

Du, X. D. [General Atomics, San Diego, CA (United ↗

Femtosecond laser fabrication of nanograting-based distributed fiber sensors for extreme environmental applications

Abstract The femtosecond laser has emerged as a powerful tool for micro- and nanoscale device fabrication. Through nonlinear ionization processes, nanometer-sized material modifications can be inscribed in transparent materials for device fabrication. This paper describes femtosecond precision inscription of nanograting in silica fiber cores to form both distributed and point fiber sensors for sensing applications in extreme environmental conditions. Through the use of scanning electron microscope imaging and laser processing optimization, high-temperature stable, Type II femtosecond laser modifications were continuously inscribed, point by point, with only an insertion loss at 1 dB m −1 or 0.001 dB per point sensor device. High-temperature performance of fiber sensors was tested at 1000 °C, which showed a temperature fluctuation of ±5.5 °C over 5 days. The low laser-induced insertion loss in optical fibers enabled the fabrication of a 1.4 m, radiation-resilient distributed fiber sensor. The in-pile testing of the distributed fiber sensor further showed that fiber sensors can execute stable and distributed temperature measurements in extreme radiation environments. Overall, this paper demonstrates that femtosecond-laser-fabricated fiber sensors are suitable measurement devices for applications in extreme environments.

Wang, Mohan (ORCID:0000000166784993)↗

Intrinsic nonlocality of spin- and polarization-resolved probabilities in strong-field quantum electrodynamics

Spin and polarization are central to precision tests of fundamental physics and for interpreting radiation from astrophysical sources and ultraintense laser-matter experiments. Here, focusing on the fundamental process of nonlinear Compton scattering, we demonstrate that a key assumption underlying current strong-field quantum electrodynamics models, i.e., that emission can be treated as an instantaneous random event sampled from a local differential rate, is inconsistent once emission angles, electron spin, and/or photon polarization are resolved. Namely, even in strictly constant and uniform fields , the resulting fully differential distribution is sign indefinite, yielding negative inferred probabilities. The physical reason is that the photon emission probability builds up over a finite length of the electron trajectory, the formation region, during which the electron direction changes by roughly the same small angle that defines the radiation cone. Therefore, we put forward a new method where we integrate over this formation region analytically to obtain a physically consistent electron spin and photon polarization model. We show that the implementation of our model is compatible with existing Monte Carlo and particle-in-cell workflows. Simulations of a GeV-class electron-laser collision accessible at current petawatt facilities and of emission in a pulsarlike magnetic field are shown to reveal spin and polarization patterns that differ even qualitatively from state-of-the-art local models. In particular, our new model predicts substantial angle-dependent circular photon polarization where the well-known collinear-emission approach yields none, and a pronounced helicity bias in the recoiling electrons absent from current predictions. These findings have direct implications for upcoming strong-field QED experiments and for interpreting polarized radiation from extreme astrophysical environments.

astrophysical electromagnetic fields↗

Transport and relaxation of current-generated nonequilibrium phonons from nonlocal electronic measurements

We study phonons generated by current in a Pt nanowire by measuring the resistance of another nanowire separated from the first one by an insulating spacer. For thin spacers, the resistance varies almost linearly with current at cryogenic temperatures, while an additional quadratic contribution emerges for thicker spacers. These observations suggest a nonthermal distribution of current-generated phonons that relax via strongly nonlinear dynamical processes rather than few-phonon scattering. Our results provide insight into the nonequilibrium phonon dynamics at nanoscale, which may facilitate efficient heat management in electronic nanodevices.

36 MATERIALS SCIENCE↗

Necklace-structured high-harmonic generation for low-divergence, soft x-ray harmonic combs with tunable line spacing

The extreme nonlinear optical process of high-harmonic generation (HHG) makes it possible to map the properties of a laser beam onto a radiating electron wave function and, in turn, onto the emitted x-ray light. Bright HHG beams typically emerge from a longitudinal phased distribution of atomic-scale quantum antennae. Here, we form a transverse necklace-shaped phased array of linearly polarized HHG emitters, where orbital angular momentum conservation allows us to tune the line spacing and divergence properties of extreme ultraviolet and soft x-ray high-harmonic combs. The on-axis HHG emission has extremely low divergence, well below that obtained when using Gaussian driving beams, which further decreases with harmonic order. This work provides a new degree of freedom for the design of harmonic combs—particularly in the soft x-ray regime, where very limited options are available. Such harmonic beams can enable more sensitive probes of the fastest correlated charge and spin dynamics in molecules, nanoparticles, and materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗