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At least 91 records · Page 5

Enhancement of second-order optical nonlinearities and nanoscale periodic domain patterning in ferroelectric boron-substituted aluminum nitride thin films

The discovery and development of CMOS-compatible, nonlinear optical materials is essential to produce integrated photonic devices with advanced functionalities. AlN is a strong candidate for on-chip device demonstration due to its intrinsic second-order optical nonlinearities, large bandgap, and well-established fabrication techniques. However, AlN is not easily phase matched for the largest coefficient d 33 ; the coefficients that could potentially be dispersion phase-matched, d 31 and d 15 , have weak nonlinearities. This work investigates ferroelectric Al 1-x B x N (x = 0 to 0.11) for viability as a large bandgap nonlinear optical material with unique suitability towards ultraviolet light generation using second harmonic generation. The linear and nonlinear optical properties are characterized accounting for material anisotropy. With increasing B concentration, a large enhancement from near negligible values to d 31 = 0.9 ± 0.1 pm/V and d 15 = 1.2 ± 0.1 pm/V is observed. This compares favorably to other large bandgap materials like β-Ba(BO 2 ) 2 , where the largest nonlinear coefficient is d 22 ~ 2.3 pm/V at 800 nm. This is accompanied by a change in the bandgap from 6.1 eV to 5.8 eV as B substitution goes from 0 to 11%. A periodically poled, quasi-phase-matched ferroelectric domain pattern with 400 nm domain size and a wall roughness of <16 nm is demonstrated.

36 MATERIALS SCIENCE↗

Neural Network-Based Variational Methods for Solving Quadratic Porous Medium Equations in High Dimensions

Here, in this paper, we propose and study neural network-based methods for solutions of high-dimensional quadratic porous medium equation (QPME). Three variational formulations of this nonlinear PDE are presented: a strong formulation and two weak formulations. For the strong formulation, the solution is directly parameterized with a neural network and optimized by minimizing the PDE residual. It can be proved that the convergence of the optimization problem guarantees the convergence of the approximate solution in the $L^1$ sense. The weak formulations are derived following (Brenier in Examples of hidden convexity in nonlinear PDEs, 2020) which characterizes the very weak solutions of QPME. Specifically speaking, the solutions are represented with intermediate functions who are parameterized with neural networks and are trained to optimize the weak formulations. Extensive numerical tests are further carried out to investigate the pros and cons of each formulation in low and high dimensions. This is an initial exploration made along the line of solving high-dimensional nonlinear PDEs with neural network-based methods, which we hope can provide some useful experience for future investigations.

97 MATHEMATICS AND COMPUTING↗

Bayesian optimization of Fisher Information in nonlinear multiresonant quantum photonics gyroscopes

Abstract We propose an on-chip gyroscope based on nonlinear multiresonant optics in a thin film χ (2) resonator that combines high sensitivity, compact form factor, and low power consumption simultaneously. We theoretically analyze a novel holistic metric – Fisher Information capacity of a multiresonant nonlinear photonic cavity – to fully characterize the sensitivity of our gyroscope under fundamental quantum noise conditions. Leveraging Bayesian optimization techniques, we directly maximize the nonlinear multiresonant Fisher Information. Our holistic optimization approach orchestrates a harmonious convergence of multiple physical phenomena – including noise squeezing, nonlinear wave mixing, nonlinear critical coupling, and noninertial signals – all encapsulated within a single sensor-resonator, thereby significantly augmenting sensitivity. We show that ∼ 470 × $\sim 470{\times}$ improvement is possible over the shot-noise limited linear gyroscope with the same footprint, intrinsic quality factors, and power budget.

42 ENGINEERING↗

Instantaneous difference frequency locking observed during toroidicity-induced Alfvén eigenmode coupling in the DIII-D tokamak

In magnetic confinement fusion, toroidicity-induced Alfvén eigenmodes (TAEs) are well-studied, weakly stable solutions of the linearized ideal magnetohydrodynamic equations. Driven unstable by suprathermal populations of energetic particles, TAE pose a key vulnerability to the confinement of high-energy alpha particles generated by fusion reactions. Hence, it is paramount to understand TAE dynamics if a working reactor is to be realized. In this work, we detect and characterize signatures of nonstationary nonlinear coupling between TAE using a novel, time-resolved bispectral analysis; results are supported by analytic signal of band-passed data. Crucially, a stationary phase relationship between two TAE and a nascent low frequency fluctuation is observed precisely when the triple product of magnetic fluctuation amplitudes is enhanced. Local mode number and frequency spectrum, gleaned from beam-emission spectroscopy, corroborates simultaneous satisfaction of nonlinear matching conditions, and provides a tool to identify theorized pathways of energy transfer, e.g. TAE parametric instability.

bispectral analysis↗

Quantum Versus Classical Switching Dynamics of Driven Dissipative Kerr Resonators

Here, we report a first-principles study of the driven dissipative dynamics for Kerr oscillators in the mesoscopic regime. This regime is characterized by large Kerr nonlinearity, realized here using the nonlinear kinetic inductance of a large array of Josephson junctions. The experimentally measured nonlinear resonance lineshapes of the junction array modes show significant deviations from steady-state numerical predictions, and necessitate time-dependent numerical simulations indicative of strong measurement-induced dephasing in the system arising from the large cross-Kerr effect between array modes. Analytical and numerical calculations of switching rate corroborate this by showing the emergence of a slow time scale, which is much longer than the linear decay rate and is set by fluctuation-induced switching times in the bistable regime. Furthermore, our analysis shows that the usual quantum-activated escape treatment is inadequate for prediction of the switching rates at large frequency shifts caused by strong nonlinearities, necessitating a quantum treatment that utilizes the full system Liouvillian. Based on our analysis, we identify a universal crossover parameter that delineates the regimes of validity of semiclassical and quantum descriptions, respectively. Our work shows how dynamical switching effects in strongly nonlinear systems provide a platform to study quantum-to-classical transitions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Encoding the complete electric field of an ultraviolet ultrashort laser pulse in a near-infrared nonlinear-optical signal

We introduce a variation on the cross-correlation frequency-resolved optical gating (XFROG) technique that uses a near-infrared (NIR) nonlinear-optical signal to characterize pulses in the ultraviolet (UV). Using a transient-grating XFROG beam geometry, we create a grating using two copies of the unknown UV pulse and diffract a NIR reference pulse from it. We show that, by varying the delay between the UV pulses creating the grating, the UV pulse intensity-and-phase information can be encoded into a NIR signal. We also implemented a modified generalized-projections phase-retrieval algorithm for retrieving the UV pulses from these spectrograms. We performed proof-of-principle measurements of chirped pulses and double pulses, all at 400 nm. This approach should be extendable deeper into the UV and potentially even into the extreme UV or x-ray range.

47 OTHER INSTRUMENTATION↗

Simulations of Laser Experiments to Study the Origin of Cosmic Magnetic Fields

Magnetic fields are ubiquitous in the universe; however, their origin is not fully understood. Cosmologists and astrophysicists have proposed a variety of ways in which small seed magnetic fields could be created. It is widely thought that the much larger values of the cosmic magnetic fields that we observe are a result of the amplification of these seed fields by the nonlinear turbulent dynamo mechanism. Such a mechanism had not yet been demonstrated in a controlled laboratory environment. We conceived experiments designed to demonstrate and study the nonlinear turbulent dynamo mechanism in the laboratory. These experiments characterize the distribution of turbulent energy among the velocity, magnetic field, and density fluctuations, providing a comprehensive picture of the energy cascade in a magnetized, turbulent plasma. The experiments build on the pathfinder experiments we have conducted on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and the OMEGA laser at Laboratory for Laser Energetics at Rochester. They utilize the high-intensity lasers at the Omega Laser Facility, the National Ignition Facility (NIF) at LLNL and the Laser Megajoule (LMJ) Facility in France – the largest laser facilities in the world. The goal of this project was to design and model the highly demanding experiments through simulation campaigns using FLASH, a highly capable radiation-MHD code we have developed, and large-scale 3D simulations on the Mira supercomputer at ANL. The simulations were vital to ensuring the experiments achieve the strong turbulence and large magnetic Reynolds numbers required for the nonlinear turbulent dynamo mechanism to operate. The simulations were also critical to determining when to fire the diagnostics, since the experiments last tens of nanoseconds but the signals of the strongly amplified magnetic fields last only a few nanoseconds. Finally, high-fidelity, validated FLASH simulations were crucial to interpreting the results of the experiments. By combining theory, experiments, and simulations, we were able to succeed in demonstrating and characterizing the nonlinear turbulent dynamo mechanism. The effort leveraged (1) the emergence of the Flash Center for Computational Science as a leader in numerical modeling of academic High Energy Density Physics (HEDP) experiments; (2) the FLASH code, which has been developed by the Flash Center and is a leadership-class, multi- physics, publicly available community code that has been applied successfully in many laser-driven experiments; (3) the expertise acquired through pathfinder experiments we performed on the Vulcan laser at the Rutherford-Appleton Laboratory in the UK and on the Omega laser facility; (4) the experience we have gained in designing and interpreting these experiments using validated simulations done with FLASH; and (5) the close collaborations we have established with outstanding experimental groups in the US and abroad. The broader impacts of the project are two-fold: (1) the work furthered the transformation of the academic community’s ability to design and analyze HEDP experiments at large laser facilities that is happening through the availability of FLASH and its widespread adoption by the academic community – a community that previously had had limited access to open and validated hydro/MHD simulation tools for HEDP experiments; and (2) the work trained young scientists to design and interpret HEDP experiments using validated simulations – a critical national need.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data-driven chaos indicator for nonlinear dynamics and applications on storage ring lattice design

A data-driven chaos indicator concept is introduced to characterize the degree of chaos for nonlinear dynamical systems. The indicator is represented by the prediction accuracy of surrogate models established purely from data. It provides a metric for the predictability of nonlinear motions in a given system. When using the indicator to implement a tune-scan for a quadratic Hénon map, the main resonances and their asymmetric stop-band widths can be identified. When applied to particle transportation in a storage ring, as particle motion becomes more chaotic, its surrogate model prediction accuracy decreases correspondingly. So, the prediction accuracy, acting as a chaos indicator, can be used directly as the objective for nonlinear beam dynamics optimization. This method provides a different perspective on nonlinear beam dynamics and an efficient method for nonlinear lattice optimization. Applications in dynamic aperture optimization are demonstrated as real world examples.

36 MATERIALS SCIENCE↗

Data-driven Chaos Indicator for Nonlinear Dynamics and Applications on Storage Ring Lattice Design

A data-driven chaos indicator concept is introduced to characterize the degree of chaos for nonlinear dynamical systems. The indicator is represented by the prediction accuracy of surrogate models established purely from data. It provides a metric for the predictability of nonlinear motions in a given system. When using the indicator to implement a tune-scan for a quadratic Hénon map, the main resonances and their asymmetric stop-band widths can be identified. When applied to particle transportation in a storage ring, as particle motion becomes more chaotic, its surrogate model prediction accuracy decreases correspondingly. Therefore, the prediction accuracy, acting as a chaos indicator, can be used directly as the objective for nonlinear beam dynamics optimization. This method provides a different perspective on nonlinear beam dynamics and an efficient method for nonlinear lattice optimization. Applications in dynamic aperture optimization are demonstrated as real world examples.

43 PARTICLE ACCELERATORS↗

Near-zero-index ultra-fast pulse characterization

Transparent conducting oxides exhibit giant optical nonlinearities in the near-infrared window where their linear index approaches zero. Despite the magnitude and speed of these nonlinearities, a “killer” optical application for these compounds has yet to be found. Because of the absorptive nature of the typically used intraband transitions, out-of-plane configurations with short optical paths should be considered. In this direction, we propose an alternative frequency-resolved optical gating scheme for the characterization of ultra-fast optical pulses that exploits near-zero-index aluminium zinc oxide thin films. Besides the technological advantages in terms of manufacturability and cost, our system outperforms commercial modules in key metrics, such as operational bandwidth, sensitivity, and robustness. The performance enhancement comes with the additional benefit of simultaneous self-phase-matched second and third harmonic generation. Because of the fundamental importance of novel methodologies to characterise ultra-fast events, our solution could be of fundamental use for numerous research labs and industries.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Measurement and control of optical nonlinearities in dispersive dielectric multilayers

Dispersive dielectric multilayer mirrors, high-dispersion chirped mirrors in particular, are widely used in modern ultrafast optics to manipulate spectral chirps of ultrashort laser pulses. Dispersive mirrors are routinely designed for dispersion compensation in ultrafast lasers and are assumed to be linear optical components. In this work, we report the experimental characterization of an unexpectedly strong nonlinear response in these chirped mirrors. At modest peak intensities <2 TW/cm 2 —well below the known laser-induced damage threshold of these dielectric structures—we observed a strong reflectivity decrease, local heating, transient spectral modifications, and time-dependent absorption of the incident pulse. Through computational analysis, we found that the incident laser field can be enhanced by an order of magnitude in the dielectric layers of the structure. The field enhancement leads to a wavelength-dependent nonlinear absorption, that shows no signs of cumulative damage before catastrophic failure. The nonlinear absorption is not a simply two-photon process but instead is likely mediated by defects that facilitate two-photon absorption. To mitigate this issue, we designed and fabricated a dispersive multilayer design that strategically suppresses the field enhancement in the high-index layers, shifting the high-field regions to the larger-bandgap, low-index layers. This strategy significantly increases the maximum peak intensity that the mirror can sustain. However, our finding of an onset of nonlinear absorption even at ‘modest’ fluence and peak intensity has significant implications for numerous past published experimental works employing dispersive mirrors. Additionally, our results will guide future ultrafast experimental work and ultrafast laser design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Virtual element approximations of the time-fractional nonlinear convection-diffusion equation on polygonal meshes

We extend the Virtual Element Method to a two-dimensional unsteady nonlinear convection-diffusion equation characterized by a fractional-order derivative with respect to the time variable. Our methodology is based on three fundamental technical components: a fractional version of the Grunwald-Letnikov approximation, discrete maximal regularity, and the regularity theory associated with non-linearity. We prove the method's well-posedness, i.e., the approximate solution's existence and uniqueness to the time-fractional convection-diffusion equation with a Lipschitz nonlinear source term. The fully discrete scheme inherently maintains stability and consistency by leveraging the discrete maximal regularity and the energy projection operator. The convergence in the L 2 -norm and H 1 -norm to various mesh configurations is validated by numerical results, underlining the practical effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗

Residue Specific Characterization of Electrostatics, Conformational Heterogeneity, and Dynamics of Electron Transfer Proteins with Linear and Nonlinear Infrared Spectroscopy. Final Report

The goal of this research project was to further our understanding of biological electron transfer through the development and application of new methods for studying proteins and their complexes with high spatial and temporal detail. The approach was based on incorporation of reporter bonds with distinct vibrational frequencies at specific locations in proteins and their characterization through the interaction of the bonds with pulses of infrared light. The project focused on the proteins plastocyanin (Pc) and cytochrome (cyt) f, two electron transfer partners in photosynthesis. The first thrust of the project was the incorporation of carbon deuterium bonds as non-perturbative probes at a ligand to the copper ion of Pc and their use to detect changes in the bonding due to the number of electrons at the metal and how the bonding changes upon association with cyt f. Toward developing more advanced approaches to characterize proteins, we incorporated a stronger reporter, the cyano group of cyanophenylalanine, at several locations in Pc and measured the frequency dynamics in the absence and presence of cyt f. The acquired data improved the current model for the protein complex. Notably, the data indicated that the majority of the population is involved in a loosely bound complex, providing insight into the nature of the ensembles formed by electron transfer protein complexes that is not available via other approaches. In addition to learning about the protein complex, we made strides toward developing and improving the new experimental approach to study highly dynamic behaviors of proteins.

59 BASIC BIOLOGICAL SCIENCES↗

Impedance‐matching model‐in‐the‐loop simulation

Abstract Impedance matching is a novel approach to executing model‐in‐the‐loop (MIL) simulations. The concept, key features, and sample applications of this approach have been described in a series of publications. This paper advances theory and implementation for impedance‐matching MIL by: (1) developing a feedback linearization technique for implementing MIL for nonlinear virtual systems, (2) systematically characterizing MIL performance‐stability tradeoffs using three design‐oriented criteria—performance: defined as closeness of the controlled‐actuator impedance to the virtual‐boundary impedance;control effort: low controller response at high frequencies to reduce sensitivity to measurement noise and uncertainties in the actuator model; andstability: pursued using passivity of the controlled actuator system, and (3) assessing, through experimentation, the robustness of two ways to estimate feedback reaction force from the test article. These fundamental advancements to MIL are described using a one‐dimensional configuration consisting of a fluid‐filled cylindrical vessel as the physical test article and a uniaxial hydraulic shake table controlled to imitate different seismic isolation systems at the base of the vessel.

Engineering↗

Causal machine learning uncovers conditions for convective intensification driven by organic and sulfate aerosols

Aerosols are often hypothesized to invigorate deep convective clouds (DCCs), but observational evidence remains limited and inconclusive. Clarifying this hypothesis is critical for regions vulnerable to thunderstorms and flooding, particularly highly polluted coastal cities. Leveraging a novel causal discovery–inference pipeline and high-resolution observations near Houston, TX, we identify multiple causal pathways among aerosols (mostly organic and sulfate), DCCs, and meteorological factors. However, a direct causal link from aerosols to DCCs is found to be uncommon, occurring in less than 35% of analyzed scenarios, and is characterized by strong conditionality and nonlinearity. When aerosol impacts on DCCs do occur, they can be substantial, enhancing DCC core heights by approximately 1.7 km, with 92% of this effect concentrated in warmer-phase cloud regions. Notably, the presence of sea breezes and the inclusion of all measured aerosol particles each enhance DCCs in over 95% of aerosol-sensitive cases.

54 ENVIRONMENTAL SCIENCES↗

Practical Challenges in Real-Time Demand Response

We report on a real-time demand response experiment with 100 controllable devices. The experiment reveals several key challenges in the deployment of a real-time demand response program, including time delays, uncertainties, characterization errors, multiple timescales, and nonlinearity, which have been largely ignored in previous studies. To resolve these practical issues, we develop and implement a two-level multi-loop control structure integrating feed-forward proportional-integral controllers and optimization solvers in closed loops, which eliminates steady-state errors and improves the dynamical performance of the overall building response. Furthermore, the proposed methods are validated by Hardware-in-the-Loop (HiL) tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗

hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty

Bayesian inference provides a systematic framework for integration of data with mathematical models to quantify the uncertainty in the solution of the inverse problem. However, the solution of Bayesian inverse problems governed by complex forward models described by partial differential equations (PDEs) remains prohibitive with black-box Markov chain Monte Carlo (MCMC) methods. We present hIPPYlib-MUQ, an extensible and scalable software framework that contains implementations of state-of-the art algorithms aimed to overcome the challenges of high-dimensional, PDE-constrained Bayesian inverse problems. These algorithms accelerate MCMC sampling by exploiting the geometry and intrinsic low-dimensionality of parameter space via derivative information and low rank approximation. The software integrates two complementary open-source software packages, hIPPYlib and MUQ. hIPPYlib solves PDE-constrained inverse problems using automatically-generated adjoint-based derivatives, but it lacks full Bayesian capabilities. MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients and Hessians to permit large-scale solution. By combining these two complementary libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each and allows us to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering disciplines. To illustrate the capabilities of hIPPYlib-MUQ, we present a comparison of a number of MCMC methods available in the integrated software on several high-dimensional Bayesian inverse problems. These include problems characterized by both linear and nonlinear PDEs, various noise models, and different parameter dimensions. The results demonstrate that large (~ 50×) speedups over conventional black box and gradient-based MCMC algorithms can be obtained by exploiting Hessian information (from the log-posterior), underscoring the power of the integrated hIPPYlib-MUQ framework.

97 MATHEMATICS AND COMPUTING↗

Nonlinear refraction and absorption properties of optical materials for high-peak-power long-wave-infrared lasers

Optical materials transparent in the CO 2 laser wavelength range have been evaluated regarding their suitability for components in ultrashort-pulse (≤ a few ps), high-peak-power (≥ a few TW) long-wave infrared (LWIR) lasers. We provide values for the nonlinear refractive index ( n 2 ) for seventeen materials, and onsets for nonlinear absorption for eleven materials. Characterizations were performed using a 2 ps laser pulse at λ =9.2 μ m. This paper methodically presents the newly acquired data in conjunction with existing literature on linear optical properties, establishing it as a comprehensive reference for designing high-peak-power LWIR laser systems.

43 PARTICLE ACCELERATORS↗