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At least 451 records · Page 25

Incomplete segregation of endorgan-specific vestibular ganglion cells in mice and rats

The endorgan-specific distribution of vestibular ganglion cells was studied in neonatal and postnatal rats and mice using indocarbocyanine dye (DiI) and dextran amines for retrograde and anterograde labeling. Retrograde DiI tracing from the anterior vertical canal labeled neurons scattered throughout the whole superior vestibular ganglion, with denser labeling at the dorsal and central regions. Horizontal canal neurons were scattered along the dorsoventral axis with more clustering toward the dorsal and ventral poles of this axis. Utricular ganglion cells occupied predominantly the central region of the superior vestibular ganglion. This utricular population overlapped with both the anterior vertical and horizontal canals' ganglion cells. Posterior vertical canal neurons were clustered in the posterior part of the inferior vestibular ganglion. The saccular neurons were distributed in the two parts of the vestibular ganglion, the superior and inferior ganglia. Within the inferior ganglion, the saccular neurons were clustered in the anterior part. In the superior ganglion, the saccular neurons were widely scattered throughout the whole ganglion with more numerous neurons at the posterior half. Small and large neurons were labeled from all endorgans. Examination of the fiber trajectory within the superior division of the vestibular nerve showed no clear lamination of the fibers innervating the different endorgans. These results demonstrate an overlapping pattern between the different populations within the superior ganglion, while in the inferior ganglion, the posterior canal and saccular neurons show tighter clustering but incomplete segregation. This distribution implies that the ganglion cells are assigned for their target during development in a stochastic rather than topographical fashion.

NASA Discipline Developmental Biology↗

SD-WAN Evaluation Criteria for a Defense Information Systems Network Expeditionary Customer Edge

The Defense Information Systems Agency (DISA) has identified a service provision gap midway between the capacity and capability of a Defense Information Systems Network (DISN) transport Edge Points of Presence (POP) and U.S. Department of Defense (DoD) Enterprise Classified Travel Kit (DECTK). Some deployed force 100-user Tactical Operations Centers are in field locations far removed from the DISN transport core, in challenging environmental conditions with limitations on space, weight, power, and cooling for network equipment. As part of a multi-phase project, Pacific Northwest National Laboratory (PNNL) will gather and analyze requirements, design, develop, prototype, and test a miniaturized and ruggedized DISN Customer Edge POP scaled to support approximately 100 users in a field Tactical Operations Center. An Expeditionary Customer Edge (ECE) will be more suitable for field deployment than a DISN transport Edge POP, using ruggedized hardware and network function virtualization (NFV) to operate in challenging field environmental conditions, plus reduce weight, power, and cooling requirements. A key enabling technology for ECE is Software Defined Wide Area Networking (SD-WAN). This document provides: • A brief overview of SD-WAN use cases and how they apply to ECE • How SD-WAN technology compares to existing networks like DISN that use Optical Transport Networking (OTN) and Multiprotocol Label Switching (MPLS) • SD-WAN functional requirements relevant to ECE • A description of an ECE Virtual Prototype, including simulated wide area network paths and a DISN-representative implementation of MPLS, in Cisco Modeling Labs • Detailed network flow walkthroughs • Evaluation criteria based on ECE-relevant SD-WAN functional requirements Finally, an appendix provides an informal evaluation of Speedify—a commercial retail Virtual Private Network service—against the ECE SD-WAN evaluation criteria.

42 ENGINEERING↗

Deep Domain Adaptation based Cloud Type Detection using Active and Passive Satellite Data

Domain adaptation techniques have been developed to handle data from multiple sources or domains. Most existing domain adaptation models assume that source and target domains are homogeneous, i.e., they have the same feature space. Nevertheless, many real world applications often deal with data from heterogeneous domains that come from completely different feature spaces. In our remote sensing application, data in source domain (from an active spaceborne Lidar sensor CALIOP onboard CALIPSO satellite) contain 25 attributes, while data in target domain (from a passive spectroradiometer sensor VIIRS onboard Suomi-NPP satellite) contain 20 different attributes. CALIOP has better representation capability and sensitivity to aerosol types and cloud phase, while VIIRS has wide swaths and better spatial coverage but has inherent weakness in differentiating atmospheric objects on different vertical levels. To address this mismatch of features across the domains/sensors, we propose a novel end-to-end deep domain adaptation with domain mapping and correlation alignment (DAMA) to align the heterogeneous source and target domains in active and passive satellite remote sensing data. It can learn domain invariant representation from source and target domains by transferring knowledge across these domains, and achieve additional performance improvement by incorporating weak label information into the model (DAMA-WL). Our experiments on a collocated CALIOP and VIIRS dataset show that DAMA and DAMA-WL can achieve higher classification accuracy in predicting cloud types.

domain adaptation↗

Mobile Sensor Technologies Being Developed

The NASA Glenn Research Center is developing small mobile platforms for sensor placement, as well as methods for communicating between roving platforms and a central command location. The first part of this project is to use commercially available equipment to miniaturize an existing sensor platform. We developed a five-circuit-board suite, with an average board size of 1.5 by 3 cm. Shown in the preceding photograph, this suite provides all motor control, direction finding, and communications capabilities for a 27- by 21- by 40-mm prototype mobile platform. The second part of the project is to provide communications between mobile platforms, and also between multiple platforms and a central command location. This is accomplished with a low-power network labeled "SPAN," Sensor Platform Area Network, a local area network made up of proximity elements. In practice, these proximity elements are composed of fixed- and mobile-sensor-laden science packages that communicate to each other via radiofrequency links. Data in the network will be shared by a central command location that will pass information into and out of the network through its access to a backbone element. The result will be a protocol portable to general purpose microcontrollers satisfying a host of sensor networking tasks. This network will enter the gap somewhere between television remotes and Bluetooth but, unlike 802.15.4, will not specify a physical layer, thus allowing for many data rates over optical, acoustical, radiofrequency, hardwire, or other media. Since the protocol will exist as portable C-code, developers may be able to embed it in a host of microcontrollers from commercial to space grade and, of course, to design it into ASICs. Unlike in 802.15.4, the nodes will relate to each other as peers. A demonstration of this protocol using the two test bed platforms was recently held. Two NASA modified, commercially available, mobile platforms communicated and shared data with each other and a central command location. Web-based control and interrogation of similar mobile sensor platforms have also been demonstrated. Expected applications of this technology include robotic planetary exploration, astronaut-to-equipment communication, and remote aerospace engine inspections.

FROM↗

Nonvolatile Memory Technology for Space Applications

This slide presentation reviews several forms of nonvolatile memory for use in space applications. The intent is to: (1) Determine inherent radiation tolerance and sensitivities, (2) Identify challenges for future radiation hardening efforts, (3) Investigate new failure modes and effects, and technology modeling programs. Testing includes total dose, single event (proton, laser, heavy ion), and proton damage (where appropriate). Test vehicles are expected to be a variety of non-volatile memory devices as available including Flash (NAND and NOR), Charge Trap, Nanocrystal Flash, Magnetic Memory (MRAM), Phase Change--Chalcogenide, (CRAM), Ferroelectric (FRAM), CNT, and Resistive RAM.

Oldham, Timothy R.↗

Dextroamphetamine: a pharmacologic countermeasure for space motion sickness and orthostatic dysfunction

Dextroamphetamine has potential as a pharmacologic agent for the alleviation of two common health effects associated with microgravity. As an adjuvant to Space Motion Sickness (SMS) medication, dextroamphetamine can enhance treatment efficacy by reducing undesirable Central Nervous System (CNS) side effects of SMS medications. Secondly, dextroamphetamine may be useful for the prevention of symptoms of post-mission orthostatic intolerance caused by cardiovascular deconditioning during spaceflight. There is interest in developing an intranasal delivery form of dextroamphetanmine for use as a countermeasure in microgravity conditions. Development of this dosage form will require an analytical detection method with sensitivity in the low ng range (1 to 100 ng/mL). During the 1995 Summer Faculty Fellowship Program, two analytical methods were developed and evaluated for their suitability as quantitative procedures for dextroamphetamine in studies of product stability, bioavailability assessment, and pharmacokinetic evaluation. In developing some of the analytical methods, beta-phenylethylamine, a primary amine structurally similar to dextroamphetamine, was used. The first analytical procedure to be evaluated involved hexane extraction and subsequent fluorescamine labeling of beta-phenylethylamine. The second analytical procedure to be evaluated involved quantitation of dextroamphetamine by an Enzyme-Linked ImmunoSorbent Assay (ELISA).

Snow, L. Dale↗

From Formal Errors Towards Realistic Uncertainties

Evaluation of uncertainties of geodetic parameter estimates is the problem that is not yet solved in a satisfactory way. A direct evaluation of the uncertainties derived from a least square solution is labeled "formal" and is usually biased, sometimes up to an order of magnitude. Customary, the use of formal errors for scientific analysis is discouraged. We claim that the root of the problem is neglecting off-diagonal elements in the variance-covariance matrix of the noise in the data. A careful reconstruction of the full variance-covariance matrix, including the off-diagonal terms greatly improves realism of uncertainty estimates derived from least squares. We processed the dataset of VLBI group delays and built a prior variance-covariance of the atmosphere-driven noise based on analysis of the output of NASA high-resolution numerical weather models. We found that the uncertainties of parameter estimates derived from this least square solution that uses such variance-covariance matrices become much closer to realistic errors. We consider approaches for implementation of this method in routine data analysis of space geodesy data.

Leonid Petrov↗

Characterization of auxin-binding proteins from zucchini plasma membrane

We have previously identified two auxin-binding polypeptides in plasma membrane (PM) preparations from zucchini (Cucurbita pepo L.) (Hicks et al. 1989, Proc. Natl. Acad. Sci. USA 86, 4948-4952). These polypeptides have molecular weights of 40 kDa and 42 kDa and label specifically with the photoaffinity auxin analog 5-N3-7-3H-IAA (azido-IAA). Azido-IAA permits both the covalent and radioactive tagging of auxin-binding proteins and has allowed us to characterize further the 40-kDa and 42-kDa polypeptides, including the nature of their attachment to the PM, their relationship to each other, and their potential function. The azido-IAA-labeled polypeptides remain in the pelleted membrane fraction following high-salt and detergent washes, which indicates a tight and possibly integral association with the PM. Two-dimensional electrophoresis of partially purified azido-IAA-labeled protein demonstrates that, in addition to the major isoforms of the 40-kDa and 42-kDa polypeptides, which possess isoelectric points (pIs) of 8.2 and 7.2, respectively, several less abundant isoforms that display unique pIs are apparent at both molecular masses. Tryptic and chymotryptic digestion of the auxin-binding proteins indicates that the 40-kDa and 42-kDa polypeptides are closely related or are modifications of the same polypeptide. Phase extraction with the nonionic detergent Triton X-114 results in partitioning of the azido-IAA-labeled polypeptides into the aqueous (hydrophilic) phase. This apparently paradoxical behavior is also exhibited by certain integral membrane proteins that aggregate to form channels. The results of gel filtration indicate that the auxin-binding proteins do indeed aggregate strongly and that the polypeptides associate to form a dimer or multimeric complex in vivo. These characteristics are consistent with the hypothesis that the 40-kDa and 42-kDa polypeptides are subunits of a multimeric integral membrane protein which has an auxin-binding site, and which may possess transporter or channel function.

NASA Program Space Biology↗

A Simple and Sensitive LC-MS/MS Method for the Determination of Free 8-Hydroxy-2'-Deoxyguanosine in Human Urine

Urinary free 8-hydroxy-2'-deoxyguanosine (8OHdG), an oxidized product of DNA, and is frequently chosen as a biomarker of oxidative stress in humans, including studies of oxidative DNA damage during space flight. It is challenging to accurately and efficiently quantify urinary free 8OHdG in large scale human studies. LC-MS/MS is emerging as a preferable analytical technique owing its high sensitivity, selectivity and efficiency, compared to some traditional methods such as ELISA and HPLC. A simple and sensitive LC-MS/MS method has been developed for the determination of free 8OHdG in human urine. Sample preparation was done by solid phase extraction with a Waters Oasis HLB 96 well plate. A Waters Alliance 2795 HT Separation Module combined with a Quattro Micro tandem mass spectrometer was used as the LC-MS/MS system. The runtime of one injection can be less than 5 minutes using a reversed phase C18 column and an isocratic flow of methanol/water. ESI positive ions were quantified in the multiple reaction modes (MRM) using m/z 284 yields 168 for 8OHdG and m/z 289 yields173 for stable isotope labeled internal standard [(15)N5] 8OHdG. With this method for 8OHdG, a lower limit of quantitation of 1.0 nM (0.28 ng/mL) has been achieved using 100 microliter urine sample. The analytical range is between 1.0 and 100 nM with a correlation coefficient greater than or equal to 0.99. Good reproducibility can be obtained with intra-assay and inter-assay CVs less than or equal to 10% for 8OHdG spiked urine QC samples. This method can be used in high-throughput routine analysis of free 8OHdG in human urine.

Wang, Zuwei↗

Experiment K-6-18. Study of muscarinic and gaba (benzodiazepine) receptors in the sensory-motor cortex, hippcampus and spinal code

Frontal lobe samples of rat brains flown aboard Cosmos 1887 were processed for the study of muscarinic (cholinergic) and GABA (benzodiazepine) receptors and for immunocytochemical localization of the neurotransmitter gamma-aminobutyric acid (GABA) and glial fibrillary acidic protein (GFAP). Although radioactive labeling of both muscarinic cholinergic and GABA (benzodiazepine) receptors proved to be successful with the techniques employed, distinct receptor localization of individual laminae of the frontal neocortex was not possible since the sampling of the area was different in the various groups of animals. In spite of efforts made for proper orientation and regional identification of laminae, it was found that a densitometric (quantitation of autoradiograms) analysis of the tissue did not contribute to the final interpretation of the effects of weightlessness on these receptors. As to the immunocytochemical studies the use of both markers, GFAP and GABA antiserum, confirmed the suitability of the techniques for use in frozen material. However, similar problems to those encountered in the receptor studies prevented an adequate interpretation of the effects of micro-G exposure on the localization and distribution of GABA and GFAP. This study did, however, confirm the feasibility of investigating neurotransmitters and their receptors in future space flight experiments.

Daunton, N.↗

Energy metabolism of Macaca mulatta during spaceflight

The mean daily energy expenditure rates of two rhesus monkeys (Macaca mulatta) were determined during spaceflight on the joint U.S./Russian Bion 11 mission by the doubly labeled water (DLW, 2H218O) method. Control values were obtained from two studies performed under flight-like conditions (n = 4). The mean inflight energy expenditure for the two Bion 11 monkeys was 81.3 kcal/kg/day, which was higher than that seen previously. The average energy expenditure (77.6 +/- 4.4 kcal/kg/day) for the four ground control monkeys was slightly lower than had been measured previously.

short duration↗

Predicting the Seawater Chemistry of an Ocean World Using Machine Learning on Isotopic Measurements of Volatile CO2

Introduction: Given the long time intervals required for data transmission to and from ocean worlds targets, low bandwidth for data transmission, time required for data processing and analysis, and potentially extreme radiation environments (e.g., Europa), it is clear that ocean worlds missions will need more autonomous flight instruments and software in order to achieve established science goals. Protracted time intervals for data analysis (e.g., Europa Lander) strongly motivates the development of rapid, consistent and streamlined methods for interpreting data from flight mass spectrometers to e.g., determine how mass spectra from a plume or surface liquid/ice relates to the surface/subsurface. Since mass spectrometry also has the potential to correctly identify biosignatures[1], it is imperative that such methods for interpreting data are consistent and accurate. We used 848 isotope ratio mass spectra from laboratory analyses of CO2 that interacted with ocean worlds-relevant seawaters as a ‘training’ dataset for ‘unsupervised’ machine learning. In unsupervised learning, characteristics of the data are not labeled or linked, and any similarities found only result from the neural network. CO2 isotopologues analyzed for this dataset mimic the remote measurements of CO2 by a flight mass spectrometer, and are detailed in Theiling [2]. From this dataset, we used measured features of the spectra, such as retention time, intensity, and (isotopologue) mass ratios as inputs for our autoencoder neural network. Our neural network was trained to find similarities in these and other spectral features for seawaters of a particular composition and amount of initial CO2. Successful training then created an output of these similarities for various seawaters, which included MgSO4, Na2SO4, NaCl, MgCl2, KCl, and NaHCO3, and combinations of these salts. We then applied dimensionality reduction techniques such as Principal Component Analysis (PCA), T-Distributed Stochastic Neighbor Embedding (TSNE), and Uniform Manifold Approximation and Projection (UMAP) to demonstrate latent data features as a two-dimensional projection in a unitless, high-dimensional space. In this projection, a data point represents the combined effect of spectral features such as intensity, retention time, and isotope ratio. Our initial UMAP demonstrates data clustering (organization of the data by the neural network) based on the amount of CO2 that had initially interacted with each seawater. Further training using more ‘supervised’ learning techniques demonstrate strong clustering of preliminary data based on initial CO2 concentration, seawater chemical composition, and ionic strength (salinity). Our preliminary work therefore suggests that machine learning has the potential to identify compositional variants of an ocean world seawater based on mass spectra from volatile CO2 measurements. Acknowledgments: This work was funded through a Strategic Task Group at NASA Goddard Space Flight Center. The training dataset was collected through funding from the Oklahoma Space Grant Consortium. References: [1] Pappalardo, R. et al. (2013) Astrobiology, 13, 740–773. [2] Theiling (2020) Icarus, 114216.

Europa↗

Comparison between ACE and CALIPSO observations of Antarctic polar stratospheric clouds

The depletion of stratospheric ozone is catalyzed by polar stratospheric clouds (PSCs) that form in the cold polar winter. The space-based lidar onboard CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) has been the reference instrument for measuring PSCs. Recently, the infrared transmission spectra recorded by the Fourier transform instrument on the ACE (Atmospheric Chemistry Experiment) satellite has provided measurements of PSC composition. We report on coincident observations made by the CALIPSO and the ACE satellites for three late winter periods (2016, 2018 and 2019) and evaluate CALIPSO's determination of PSC composition relative to ACE’s findings. We found that CALIPSO and ACE generally agree well for the detection of nitric acid trihydrate (NAT) clouds. However, CALIPSO detects some NAT clouds where ACE detects supercooled ternary solutions of nitric and sulfuric acid (STS). Similarly, CALIPSO only partially detects ice in ACE's ice clouds. Overall, these results seem to show that CALIPSO’s NAT classification might be too inclusive. We also found that supercooled nitric acid (SNA) clouds, a new classification, are labelled as STS by CALIPSO

Léo Lavy↗

Regime Characterization of Offshore Wind Resource Using Unsupervised Learning

Predictability of wind resource conditions is critical for offshore wind design and operations. While many studies of extreme wind conditions focus on specific events such as low-level jets or ramps, these rely on threshold definitions that limit generality. Here we present a data-driven framework that combines principal component analysis (PCA), self-organizing maps (SOM), and k-means clustering to classify wind resource conditions as typical and anomalous from climatological data. Anomalies are defined not by fixed thresholds but by flagging samples located far from SOM node centers inside the baseline SOM structure. This reframes extremes as rare ebents and hence, likely difficult to anticipate by numerical weather prediction models. We applied this approach to 23 years (2000–2022) of hourly profiles from the NOW-23 hindcast model at the Humboldt Wind Energy Area. Classification is conducted on a feature space consisting of 10 m wind speed and direction, bulk shear and veer across 30–270 m, and a low-level jet index. Dimensionality reduction is achieved through PC. A 2 × 3 OM lattice trained on the PCA vectors identified six baseline regimes spanning weak to strong flow states. High quantization-error profiles are identified and re-clustered into four anomalous regimes. The baseline regimes exhibited clear seasonal and diurnal cycles. Meanwhile, the anomalous regimes represented <10 % of all hours but showed distinct combinations of speed, shear, and veer, when compared to the baseline regimes. Anomalous regimes are typically short-lived (~few hours), yet their transitions can lead to hub-height wind changes of −18 to +9 m s -1 . For a representative 15 MW turbine, these shifts imply rapid swings in capacity factor from near-full output to negligible generation. Validation with lidar buoy data showed 51% agreement in SOM labels across ~6,000 overlapping hours, with most mismatches confined to adjacent speed classes. HRRR comparisons further revealed that anomalous regimes were disproportionately associated with forecast biases exceeding 5 m s -1 . Together, these results reframe extremes in offshore wind from absolute maxima or minima to weather states that are difficult to anticipate from models.

17 WIND ENERGY↗

Creating Interactive Graphical Overlays in the Advanced Weather Interactive Processing System Using Shapefiles and DGM Files

Graphical overlays can be created in real-time in the Advanced Weather Interactive Processing System (AWIPS) using shapefiles or Denver AWIPS Risk Reduction and Requirements Evaluation (DARE) Graphics Metafile (DGM) files. This presentation describes how to create graphical overlays on-the-fly for AWIPS, by using two examples of AWIPS applications that were created by the Applied Meteorology Unit (AMU) located at Cape Canaveral Air Force Station (CCAFS), Florida. The first example is the Anvil Threat Corridor Forecast Tool, which produces a shapefile that depicts a graphical threat corridor of the forecast movement of thunderstorm anvil clouds, based on the observed or forecast upper-level winds. This tool is used by the Spaceflight Meteorology Group (SMG) at Johnson Space Center, Texas and 45th Weather Squadron (45 WS) at CCAFS to analyze the threat of natural or space vehicle-triggered lightning over a location. The second example is a launch and landing trajectory tool that produces a DGM file that plots the ground track of space vehicles during launch or landing. The trajectory tool can be used by SMG and the 45 WS forecasters to analyze weather radar imagery along a launch or landing trajectory. The presentation will list the advantages and disadvantages of both file types for creating interactive graphical overlays in future AWIPS applications. Shapefiles are a popular format used extensively in Geographical Information Systems. They are usually used in AWIPS to depict static map backgrounds. A shapefile stores the geometry and attribute information of spatial features in a dataset (ESRI 1998). Shapefiles can contain point, line, and polygon features. Each shapefile contains a main file, index file, and a dBASE table. The main file contains a record for each spatial feature, which describes the feature with a list of its vertices. The index file contains the offset of each record from the beginning of the main file. The dBASE table contains records for each attribute. Attributes are commonly used to label spatial features. Shapefiles can be viewed, but not created in AWIPS. As a result, either third-party software can be installed on an AWIPS workstation, or new software must be written to create shapefiles in the correct format.

Barrett, Joe H., III↗

A Statistical Model to Predict the Extratropical Transition of Tropical Cyclones

This paper introduces a logistic regression model for the extratropical transition(ET) of tropical cyclones in the North Atlantic and the Western North Pacific, using elastic net regularization to select predictors and estimate coefficients.Predictors are chosen from the 1979-2017 best track and reanalysis datasets, and verification is done against the tropical/extratropical labels in the best track data. In an independent test set, the model skillfully predicts ET at lead times up to two days, with latitude and sea surface temperature as its most important predictors. At a lead time of 24 h, it predicts ET with a Matthews correlation coefficient of 0.4 in the North Atlantic, and 0.6 in the Western North Pacific. It identifies 80% of storms undergoing ET in the North Atlantic, and 92% of those in the Western North Pacific. 90% of transition time errors are less than 24 h. Select examples of the model's performance on individual storms illustrate its strengths and weaknesses.Two versions of the model are presented: an "operational model" that may provide baseline guidance for operational forecasts, and a "hazard model"that can be integrated into statistical TC risk models. As instantaneous diagnostics for tropical/extratropical status, both models' zero lead time predictions perform about as well as the widely used Cyclone Phase Space (CPS) in the Western North Pacific and better than the CPS in the North Atlantic, and predict the timings of the transitions better than CPS in both basins.

Melanie Bieli↗

Guidelines for Design and Test of a Built-In Self Test (BIST) Circuit For Space Radiation Studies of High-Speed IC Technologies

Serial Bit Error Rate Testing under radiation to characterize single particle induced errors in high-speed IC technologies generally involves specialized test equipment common to the telecommunications industry. As bit rates increase, testing is complicated by the rapidly increasing cost of equipment able to test at-speed. Furthermore as rates extend into the tens of billions of bits per second test equipment ceases to be broadband, a distinct disadvantage for exploring SEE mechanisms in the target technologies. In this presentation the authors detail the testing accomplished in the CREST project and apply the knowledge gained to establish a set of guidelines suitable for designing arbitrarily high speed radiation effects tests.

Carts, M. A.↗

Celestial geometry

Celestial holography expresses S-matrix elements as correlators in a CFT living on the night sky. Poincaré invariance imposes additional selection rules on the allowed positions of operators. As a consequence, n-point correlators are only supported on certain patches of the celestial sphere, depending on the labeling of each operator as incoming/outgoing. Here we initiate a study of the celestial geometry, examining the kinematic support of celestial amplitudes for different crossing channels. We give simple geometric rules for determining this support. For n ≥ 5, we can view these channels as tiling together to form a covering of the celestial sphere. Our analysis serves as a stepping off point to better understand the analyticity of celestial correlators and illuminate the connection between the 4D kinematic and 2D CFT notions of crossing symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗