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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Apex Reference Manual 3.0 Beta

Apex is a toolkit for constructing software that behaves intelligently and responsively in demanding task environments. Reflecting its origin at NASA where Apex continues to be developed, current applications include: a) Providing autonomous mission management and tactical control capabilities for unmanned aerial vehicles including an autonomous surveillance helicopter and a simulation prototype of an unmanned fixed-wing aircraft to be used for wildfire mapping; b) Simulating human air traffic controllers, pilots and astronauts to help predict how people might respond to changes in equipment or procedures; and c) Predicting the precise duration and sequence of routine human behaviors based on a human-computer interaction engineering technique called CPM-GOMS. Among Apex s components are a set of implemented reasoning services, such as those for reactive planning and temporal pattern recognition; a software architecture that embeds and integrates these services and allows additional reasoning elements to be added as extensions; a formal language for specifying agent knowledge; a simulation environment to facilitate prototyping and analysis; and Sherpa, a set of tools for visualizing autonomy logic and runtime behavior. In combination, these are meant to provide a flexible and usable framework for creating, testing, and deploying intelligent agent software. Overall, our goal in developing Apex is to lower economic barriers to developing intelligent software agents. New ideas about how to extend or modify the system are evaluated in terms of their impact in reducing the time, expertise, and inventiveness required to build and maintain applications. For example, potential enhancements to the AI reasoning capabilities in the system are reviewed not only for usefulness and distinctiveness, but also for their impact on the readability and general usability of Apex s behavior representation language (PDL) and on the transparency of resulting behavior. A second central part of our approach is to iteratively refine Apex based on lessons learned from as diverse a set of applications as possible. Many applications have been developed by users outside the core development team including engineers, researchers, and students. Usability is thus a central concern for every aspect of Apex visible to a user, including PDL, Sherpa, the Apex installation process, APIs, and user documentation. Apex users vary in their areas of expertise and in their familiarity with autonomy technology. Focusing on usability, a development philosophy summarized by the project motto "Usable Autonomy," has been important part of enabling diverse users to employ Apex successfully and to provide feedback needed to guide iterative, user-centered refinement.

Freed, Michael A.↗
DOE OSTI2026

Automated Classification of Vehicle Movements at Signalized Intersections Using Vehicle Trajectories

Accurate vehicle movement classification through signalized intersections is of paramount importance to the analysis of intersection performance and the optimization of traffic control strategies. Conventional techniques for tracking vehicle turning movements depend on infrastructure-based strategies like human counts, loop detectors, and video analytics, all of which are costly, prone to errors, and spatially constrained. High-frequency trajectory data can be utilized to determine vehicle movement patterns in a scalable and infrastructure-independent method due to the adoption of connected vehicles (CVs). In recent years, several studies have utilized connected vehicle data to generate performance measures. Most of the trajectory-based performance measures approaches, however, require map matching-i.e., extracting geospatial references from maps to identify the movements that individual vehicles make at a signalized intersection. These approaches are often time-consuming and hinder scalability since geographic features need to be provided for an analysis to be conducted. Map matching methods are prone to errors as different map versions change these geographic features. This research presents a novel automatic classification pipeline that uses CV trajectory data to classify vehicle movements at signalized crossings, specifically pass-through left-turn and right-turn maneuvers. The process starts by filtering trips that cross a spatial bounding box that has been defined at the target intersection. Approach and departure headings for each trajectory crossing the boundary are computed and are clustered together to identify dominant movements. The proposed algorithm is used to classify the movement of vehicles at 10 intersections in the state of California, and the results indicate that the algorithm can classify movements at these intersections with varying traffic volumes and road network configurations, all in a map-less framework with no need for conflation of vehicle trajectories to a digital base map.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Three Decades of Precision Orbit Determination Progress, Achievements, Future Challenges and its Vital Contribution to Oceanography and Climate Research

Although satellite altimetry has been around for thirty years, the last fifteen beginning with the launch of TOPEX/Poseidon (TP) have yielded an abundance of significant results including: monitoring of ENS0 events, detection of internal tides, determination of accurate global tides, unambiguous delineation of Rossby waves and their propagation characteristics, accurate determination of geostrophic currents, and a multi-decadal time series of mean sea level trend and dynamic ocean topography variability. While the high level of accuracy being achieved is a result of both instrument maturity and the quality of models and correction algorithms applied to the data, improving the quality of the Climate Data Records produced from altimetry is highly dependent on concurrent progress being made in fields such as orbit determination. The precision orbits form the reference frame from which the radar altimeter observations are made. Therefore, the accuracy of the altimetric mapping is limited to a great extent by the accuracy to which a satellite orbit can be computed. The TP mission represents the first time that the radial component of an altimeter orbit was routinely computed with an accuracy of 2-cm. Recently it has been demonstrated that it is possible to compute the radial component of Jason orbits with an accuracy of better than 1-cm. Additionally, still further improvements in TP orbits are being achieved with new techniques and algorithms largely developed from combined Jason and TP data analysis. While these recent POD achievements are impressive, the new accuracies are now revealing subtle systematic orbit error that manifest as both intra and inter annual ocean topography errors. Additionally the construction of inter-decadal time series of climate data records requires the removal of systematic differences across multiple missions. Current and future efforts must focus on the understanding and reduction of these errors in order to generate a complete and consistent time series of improved orbits across multiple missions and decades required for the most stringent climate-related research. This presentation discusses the POD progress and achievements made over nearly three decades, and presents the future challenges, goals and their impact on altimetric derived ocean sciences.

Luthcke, Scott↗
NASA NTRS1977

Annual Symposium on Machine Processing of Remotely Sensed Data, 4th, Purdue University, West Lafayette, Ind., June 21-23, 1977, Proceedings

Papers are presented on a variety of techniques for the machine processing of remotely sensed data. Consideration is given to preprocessing methods such as the correction of Landsat data for the effects of haze, sun angle, and reflectance and to the maximum likelihood estimation of signature transformation algorithm. Several applications of machine processing to agriculture are identified. Various types of processing systems are discussed such as ground-data processing/support systems for sensor systems and the transfer of remotely sensed data to operational systems. The application of machine processing to hydrology, geology, and land-use mapping is outlined. Data analysis is considered with reference to several types of classification methods and systems.

Morrison, D. B.↗
NASA NTRS2007

Observations on Cost Modeling and Performance Measurement of Long Term Archives

This paper describes a prototype suite of Excel-based tools that could be used for estimating lifecycle costs for newly planned or modified long-term archival facilities. These tools may also prove valuable for monitoring the long-term performance of such facilities once operational. Cost estimation is by analogy, using statistical curve-fitting techniques across a database of comparable data activities. The database currently includes 29 operational data centers ranging from small (2 FTEs) to large (66 FTEs), and is readily expandable to include additional activities specifically involving data preservation and added value. Each comparable data center is described in terms of its staffing, throughput workload, archival and distribution requirements, levels of user service, overall complexity, degree of automation, and other data, comprising 94 distinct descriptors in all. The descriptors were developed by normalizing heterogeneous data from the various centers and mapping them into an Excel framework consistent with the OAIS reference model. A user-friendly tool is provided for generating input to and updating the comparables database. This tool can also be used to benchmark the performance (in terms of cost versus throughput) of an operational data center, and to update the staffing, cost and workload data on a periodic basis. The comparables database could thus provide a history of staffing and throughput over time, as a means of performance monitoring and providing feedback for continuous improvement. Ancillary tools are also provided for performing "what-if' cost exercises for planning purposes, and for graphical display of data and results. We provide a high-level description of the tools; present our experiences and observations on gathering the information and maintaining the database; and discuss how this tool set might be applied to long term archives.

Fontaine, Kathy↗
NASA NTRS2015

ExMC Work Prioritization Process

Last year, NASA's Human Research Program (HRP) introduced the concept of a "Path to Risk Reduction" (PRR), which will provide a roadmap that shows how the work being done within each HRP element can be mapped to reducing or closing exploration risks. Efforts are currently underway within the Exploration Medical Capability (ExMC) Element to develop a structured, repeatable process for prioritizing work utilizing decision analysis techniques and risk estimation tools. The goal of this effort is to ensure that the work done within the element maximizes risk reduction for future exploration missions in a quantifiable way and better aligns with the intent and content of the Path to Risk Reduction. The Integrated Medical Model (IMM) will be used to identify those conditions that are major contributors of medical risk for a given design reference mission. For each of these conditions, potential prevention, screening, diagnosis, and treatment methods will be identified. ExMC will then aim to prioritize its potential investments in these mitigation methods based upon their potential for risk reduction and other factors such as vehicle performance impacts, near term schedule needs, duplication with external efforts, and cost. This presentation will describe the process developed to perform this prioritization and inform investment discussions in future element planning efforts. It will also provide an overview of the required input information, types of process participants, figures of merit, and the expected outputs of the process.

Simon, Matthew↗
NASA NTRS2012

Assimilation of GIRO Data into a Real-Time IRI

Increasingly accurate and detailed global 3-D specification of the Earth's space plasma environment is required to further understand its intricate organization and behavior. For a long time space physics and aeronomy research has been data starved due to the great variety of natural time scales involved in the plasma phenomenology. We have started developing a new approach to the global ionospheric specification called Real-Time Assimilative Mapping (RTAM). The IRI-RTAM will use data from the Global Ionospheric Radio Observatory (GIRO) to smoothly transform International Reference Ionosphere's (IRI's) background empirical maps of the ionospheric characteristics to match the observations. Such empirical assimilative modeling will provide a high-resolution, global picture of the ionospheric response to various short-term events observed during periods of storm activity or the impact of gravity waves coupling the ionosphere to the lower atmosphere, including timelines of the vertical restructuring of the plasma distribution. It will also contribute to the challenging task of providing a rapid insight into the temporal and spatial space weather development using the real-time GIRO data streams. The new assimilation technique "updates" the IRI electron density distribution while preserving the overall integrity of IRI s typical ionospheric feature representations. The technique adjusts the coefficients of the spherical/diurnal expansions used by the CCIR and URSI-88 model to obtain the global sub-peak electron density distribution. The set of global corrected coefficients can be generated as frequently as every 15 min and easily disseminated using a single real-time RTAM server operated by GIRO.

Galkin, I. A.↗
DOE OSTI2026

Spatially Mapping the CO 2 Alkaline Sorbent Diffuse Microenvironment Using Operando Raman Spectroscopy

When designing a chemical process, the local balance of transport and kinetics, collectively referred to as the diffuse microenvironment, plays a critical role in performance but is difficult to directly observe. This work demonstrates a method of two-dimensional spatial chemical mapping of the diffuse microenvironment in the context of alkali metal hydroxide direct air capture of carbon dioxide using a custom operando gas-absorption flow cell along with confocal Raman spectroscopy. Notably, we observe the concentration boundary layer near the gas–liquid interface and elucidate the interplay of carbonate and bicarbonate ions within it while inferring local hydroxide depletion through continuum modeling. These first of their kind observations provide a technique to compare the performance of direct air capture solvents based on diffuse microenvironment dynamics while also providing metrics important for air contactor design such as boundary layer thickness. Overall, this work showcases a new experimental platform to study interfacial diffuse microenvironments in and outside of the field of direct air capture of carbon dioxide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

Multiprocessor performance modeling with ADAS

A graph managing strategy referred to as the Algorithm to Architecture Mapping Model (ATAMM) appears useful for the time-optimized execution of application algorithm graphs in embedded multiprocessors and for the performance prediction of graph designs. This paper reports the modeling of ATAMM in the Architecture Design and Assessment System (ADAS) to make an independent verification of ATAMM's performance prediction capability and to provide a user framework for the evaluation of arbitrary algorithm graphs. Following an overview of ATAMM and its major functional rules are descriptions of the ADAS model of ATAMM, methods to enter an arbitrary graph into the model, and techniques to analyze the simulation results. The performance of a 7-node graph example is evaluated using the ADAS model and verifies the ATAMM concept by substantiating previously published performance results.

Hayes, Paul J.↗
NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗
NASA NTRSDate not supplied

3D Localization of Defects in Facility Inspection

Wind tunnels are crucial facilities that support the aerospace industry. However, these facilities are large, complex, and pose unique maintenance and inspection requirements. Manual inspections to identify defects such as cracks, missing fasteners, leaks, and foreign objects are important but labor and schedule intensive. Our goal is to utilize small Unmanned Aircraft Systems (sUAS) and computer vision-based analysis to automate the inspection of the interior and exterior of NASA’s critical wind tunnel facilities. We detect missing fasteners as our defect class, and detect existing fasteners to provide potential future missing fastener sites for preventative maintenance. These detections are done on both 2D raw images and in 3D space to provide a visual reference and real world location to facilitate repairs. A dataset was created consisting of images taken along a grid-like pattern of an interior tunnel section in the AEDC National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center. Our method uses object detection to create image level bounding boxes of the fasteners and missing fasteners, then uses photogrammetry to create a mapping from 2D image locations to 3D real world locations. The image level bounding boxes and the 2D to 3D mapping are then combined to determine the 3D location of the defects. We describe the data collection, photogrammetry, and computer vision techniques used for object detection as well as a quantitative analysis of the method.

Small Unmanned Aircraft Systems (sUAS)↗
NASA NTRS1996

Imaging Radar Applications in the Death Valley Region

Death Valley has had a long history as a testbed for remote sensing techniques (Gillespie, this conference). Along with visible-near infrared and thermal IR sensors, imaging radars have flown and orbited over the valley since the 1970's, yielding new insights into the geologic applications of that technology. More recently, radar interferometry has been used to derive digital topographic maps of the area, supplementing the USGS 7.5' digital quadrangles currently available for nearly the entire area. As for their shorter-wavelength brethren, imaging radars were tested early in their civilian history in Death Valley because it has a variety of surface types in a small area without the confounding effects of vegetation. In one of the classic references of these early radar studies, in a semi-quantitative way the response of an imaging radar to surface roughness near the radar wavelength, which typically ranges from about 1 cm to 1 m was explained. This laid the groundwork for applications of airborne and spaceborne radars to geologic problems in and regions. Radar's main advantages over other sensors stems from its active nature- supplying its own illumination makes it independent of solar illumination and it can also control the imaging geometry more accurately. Finally, its long wavelength allows it to peer through clouds, eliminating some of the problems of optical sensors, especially in perennially cloudy and polar areas.

Farr, Tom G.↗
DOE OSTI2025

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

The NASA/MSFC Global Reference Atmospheric Model-1995 version (GRAM-95)

The latest version of the Global Reference Atmospheric Model (GRAM-95) is presented and discussed. GRAM-95 uses the new Global Upper Air Climatic Atlas (GUACA) CD-ROM data set, for 0- to 27-km altitudes. As with earlier versions, GRAM-95 provides complete geographical and altitude coverage for each month of the year. Individual years 1985 to 1991 and a period-of-record (1980 to 1991) can be simulated for the GUACA height range. GRAM-95 uses a specially developed data set, based on Middle Atmosphere Program (MAP) data, for the 20- to 120-km height range, and the NASA Marshall Engineering Thermosphere (MET) model for heights above 90 km. Fairing techniques assure a smooth transition in the overlap height ranges (20 to 27 km and 90 to 120 km). In addition to the traditional GRAM variables of pressure, density, temperature and wind components, GRAM-95 now includes water vapor and 11 other atmospheric constituents (O3, N2O, CO, CH4, CO2, N2, O2, O, A, He, and H). A new, variable-scale perturbation model provides both large-scale and small-scale deviations from mean values for the thermodynamic variables and horizontal and vertical wind components. The perturbation model includes new features that simulate intermittency (patchiness) in turbulence and small-scale perturbation fields. The density perturbations and density gradients (density shears) computed by the new model compare favorably in their statistical characteristics with observed density perturbations and density shears from 32 space shuttle reentry profiles. GRAM-95 provides considerable improvement in wind estimates from the new GUACA data set, compared to winds calculated from the geostrophic wind relations previously used in the 0- to 25-km height range. The GRAM-95 code has been put into a more modular form, easier to incorporate as subroutines in other programs (e.g., trajectory codes). A complete user's guide for running the program, plus sample input and output, is provided.

Justus, C. G.↗
DOE OSTI2022

Kilauea Magnetotelluric Dataset

In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the USGS Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kilauea and the East and Southwest Rift zones, which has implications for understanding Kilaueas plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. In total, data were acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone (ERZ), where electrical contact resistances are on the order of 100 kOhm. This data supports the continuing efforts to increase geothermal power on the island of Hawaii. Each of the 70 EDI files are the MT impedance tensors for 1 site. There is also a description of the processing of the data and a site map showing the locations of each site.

15 GEOTHERMAL ENERGY↗
NASA NTRS2002

Interferometer for Testing in Vibration Environments

Temporal phase shifting interferometers require a stable environment during the data acquisition, so that well controlled phase steps can be introduced between successively acquired interferograms. In contrast, single-frame interferometers need to acquire only one interferogram to provide a phase map with very good precision at high spatial resolution. Thus these interferometers are well suited for the interferometric testing of large optics with long radius of curvature for which vibration isolation is difficult, eg. testing astronomical telescope mirrors in a test tower, or testing space optics inside a cryogenic vacuum chamber. This paper describes the Instantaneous Phase Interferometer (IPI) by ADE Phase Shift, together with measurement results at NASA. The IPI consists of a polarization Twyman-Green interferometer operating at 632.8 nm, with single-frame data acquisition based on a spatial carrier technique. The spatial carrier fringes are generated by introducing large amount of tilt between the test beam and the reference beam. The phase information of the optical surface under test is encoded in the straightness of the interference fringes, which can be detected in a single frame with spatial sampling of 1000 x 1000 pixels. Measurements taken at the NASA Marshall Space Flight Cater in support of the characterization of developmental optics for the Next Generation Space Telescope are presented. Such tests consist of a mirror placed inside a cryogenic vacuum chamber, with the IPI placed outside the test chamber without any additional vibration isolation.

Eng, Ron↗
DOE OSTI2020

LiDAR-Aided Interior Orientation Parameters Refinement Strategy for Consumer-Grade Cameras Onboard UAV Remote Sensing Systems

Unmanned aerial vehicles (UAVs) are quickly emerging as a popular platform for 3D reconstruction/modeling in various applications such as precision agriculture, coastal monitoring, and emergency management. For such applications, LiDAR and frame cameras are the two most commonly used sensors for 3D mapping of the object space. For example, point clouds for the area of interest can be directly derived from LiDAR sensors onboard UAVs equipped with integrated global navigation satellite systems and inertial navigation systems (GNSS/INS). Imagery-based mapping, on the other hand, is considered to be a cost-effective and practical option and is often conducted by generating point clouds and orthophotos using structure from motion (SfM) techniques. Mapping with photogrammetric approaches requires accurate camera interior orientation parameters (IOPs), especially when direct georeferencing is utilized. Most state-of-the-art approaches for determining/refining camera IOPs depend on ground control points (GCPs). However, establishing GCPs is expensive and labor-intensive, and more importantly, the distribution and number of GCPs are usually less than optimal to provide adequate control for determining and/or refining camera IOPs. Moreover, consumer-grade cameras with unstable IOPs have been widely used for mapping applications. Therefore, in such scenarios, where frequent camera calibration or IOP refinement is required, GCP-based approaches are impractical. To eliminate the need for GCPs, this study uses LiDAR data as a reference surface to perform in situ refinement of camera IOPs. The proposed refinement strategy is conducted in three main steps. An image-based sparse point cloud is first generated via a GNSS/INS-assisted SfM strategy. Then, LiDAR points corresponding to the resultant image-based sparse point cloud are identified through an iterative plane fitting approach and are referred to as LiDAR control points (LCPs). Finally, IOPs of the utilized camera are refined through a GNSS/INS-assisted bundle adjustment procedure using LCPs. Seven datasets over two study sites with a variety of geomorphic features are used to evaluate the performance of the developed strategy. The results illustrate the ability of the proposed approach to achieve an object space absolute accuracy of 3–5 cm (i.e., 5–10 times the ground sampling distance) at a 41 m flying height.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Phase-resolving spin-wave microscopy using infrared strobe light

The need for sensitively and reliably probing magnetization dynamics has been increasing in various contexts such as studying novel hybrid magnonic systems, in which the spin dynamics strongly and coherently couple to other excitations, including microwave photons, light photons, or phonons. Recent advances in quantum magnonics also highlight the need for employing the magnon phase as quantum state variable, which is to be detected and mapped out with high precision in on-chip micro- and nanoscale magnonic devices. Here, in this study, we demonstrate a facile optical technique that can directly perform concurrent spectroscopic and imaging functionalities with spatial and phase resolutions, using infrared strobe light operating at 1550-nm wavelength. To showcase the methodology, we spectroscopically studied the phaseresolved spin dynamics in a bilayer of Permalloy and yttrium iron garnet Y 3 Fe 5 O 12 (YIG), and spatially imaged the backward-volume spin-wave modes of YIG in the dipolar spin-wave regime. Using the strobe light probe, the detected precessional phase contrast can be directly used to construct the map of the spin wave's wave front, in the continuous-wave regime of spin-wave propagation and in the stationary state, without needing any optical reference path. By selecting the applied field, frequency, and detection phase, the spin-wave images can be made sensitive to the precession amplitude and phase. Our results demonstrate that infrared optical strobe light can serve as a versatile platform for magneto-optical probing of magnetization dynamics, with potential implications in investigating hybrid magnonic systems.

Xiong, Yuzan [University of North Carolina, Chapel↗