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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
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DOE OSTI2021

Photon-Sparse, Poisson Light-Sheet Microscopy

Light-sheet microscopy has revolutionized bioimaging by enabling approximately an order of magnitude reduction in specimen irradiance compared to confocal imaging. Here, we introduce a light-sheet imaging system that enables an additional order of magnitude reduction in specimen irradiance by operating at the Poisson limit. To operate at this limit, we integrated classical illumination with single-photon detection and wavelet-based image reconstruction. This integration enabled brightness quantification and object recognition from fewer than one detected photon per image pixel, corresponding to more than 10-fold lower irradiance levels than modern systems. We demonstrate how such photon-sparse imaging can eradicate photobleaching and enable both dim and bright object imaging, thus, further enhancing the related gains of light-sheet microscopy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

The Potential of DAS in Teleseismic Studies: Insights From the Goldstone Experiment

Distributed acoustic sensing (DAS) is a recently developed technique that has demonstrated its utility in the oil and gas industry. Here we demonstrate the potential of DAS in teleseismic studies using the Goldstone OpticaL Fiber Seismic experiment in Goldstone, California. By analyzing teleseismic waveforms from the 10 January 2018 M7.5 Honduras earthquake recorded on ~5,000 DAS channels and the nearby broadband station GSC, we first compute receiver functions for DAS channels using the vertical-component GSC velocity as an approximation for the incident source wavelet. The Moho P -to- s conversions are clearly visible on DAS receiver functions. Here, we then derive meter-scale arrival time measurements along the entire 20-km-long array. We are also able to measure path-averaged Rayleigh wave group velocity and local Rayleigh wave phase velocity. The latter, however, has large uncertainties. Our study suggests that DAS will likely play an important role in many fields of passive seismology in the near future.

58 GEOSCIENCES↗
DOE OSTI2019

Disentangling the Effects of Temperature, Moisture, and Substrate Availability on Soil CO 2 Efflux

Soil respiration ($R_s$), the largest carbon emission flux in ecosystems, is usually modeled as an empirically parameterized function of temperature, and sometimes water availability. The likely contribution by other factors, such as carbohydrate substrate supply from photosynthesis, has been recognized, but modeling capacity to use this information is limited. Wavelet transformations of the residuals of a seasonal Q 10 temperature response model indicated structure at different temporal scales. In this work, we hypothesize that this indicates the lack of explicit representation of relevant processes in the models. Using cross-spectral analysis, we found that time series of photosynthetically active radiation explained most of the diurnal variation, temperature, explained variability at multiple time scales (diurnal-synoptic), whereas volumetric soil water content correlated with variability in Rs at scales 15-30 days. The results suggest that the time domains of influence for different driving variables of $R_s$ are discrete, and largely nonoverlapping, and represent functional relationships between soil biological activity and its constraints. Analysis of phase angles showed that $R_s$ lagged photosynthetically active radiation by 1.5-3.0 hr. As this time lag was the same in both young and mature trees, with more than fivefold difference in transport distances, we hypothesize that this finding adds to the body of literature that support the pressure-concentration-wave model of carbohydrate availability in plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Aperture‐Synthesis Radar Imaging With Compressive Sensing for Ionospheric Research

Abstract Inverse methods involving compressive sensing are tested in the application of two‐dimensional aperture‐synthesis imaging of radar backscatter from field‐aligned plasma density irregularities in the ionosphere. We consider basis pursuit denoising, implemented with the fast iterative shrinkage thresholding algorithm, and orthogonal matching pursuit (OMP) with a wavelet basis in the evaluation. These methods are compared with two more conventional optimization methods rooted in entropy maximization (MaxENT) and adaptive beamforming (linearly constrained minimum variance or often “Capon's Method.”) Synthetic data corresponding to an extended ionospheric radar target are considered. We find that MaxENT outperforms the other methods in terms of its ability to recover imagery of an extended target with broad dynamic range. Fast iterative shrinkage thresholding algorithm performs reasonably well but does not reproduce the full dynamic range of the target. It is also the most computationally expensive of the methods tested. OMP is very fast computationally but prone to a high degree of clutter in this application. We also point out that the formulation of MaxENT used here is very similar to OMP in some respects, the difference being that the former reconstructs the logarithm of the image rather than the image itself from basis vectors extracted from the observation matrix. MaxENT could in that regard be considered a form of compressive sensing.

Hysell, D. L.↗
DOE OSTI2024

Airborne Measurements of Scale‐Dependent Latent Heat Flux Impacted by Water Vapor and Vertical Velocity Over Heterogeneous Land Surfaces During the CHEESEHEAD19 Campaign

Abstract The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio ( r v ) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity ( w ) variance (), and r v variance () over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, , and at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in , and 200 m–8 km in . The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by and . The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from and . The monthly temporal variations mainly come from the first two major contributing classified scales in LE, , and . These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Boundary Layer Structures Over the Northwest Atlantic Derived From Airborne High Spectral Resolution Lidar and Dropsonde Measurements During the ACTIVATE Campaign

The Planetary Boundary Layer height (PBLH) is essential for studying PBL and ocean-atmosphere interactions. Marine PBL is usually defined to include a mixed layer (ML) and a capping inversion layer. The ML height (MLH) estimated from the measurements of aerosol backscatter by a lidar was usually compared with PBLH determined from radiosondes/dropsondes in the past, as the PBLH is usually similar to MLH in nature. However, PBLH can be much greater than MLH for decoupled PBL. Here, in this study, we evaluate the retrieved MLH from an airborne lidar (HSRL-2) by utilizing 506 co-located dropsondes during the ACTIVATE field campaign over the Northwest Atlantic from 2020 to 2022. First, we define and determine the MLH and PBLH from the temperature and humidity profiles of each dropsonde, and find that the MLH values from HSRL-2 and dropsondes agree well with each other, with a coefficient of determination of 0.66 and median difference of 18 m. In contrast, the HSRL-2 MLH data do not correspond to dropsonde-derived PBLH, with a median difference of -47 m. Therefore, we modify the current operational and automated HSRL-2 wavelet-based algorithm for PBLH retrieval, decreasing the median difference significantly to -8 m. Further data analysis indicates that these conclusions remain the same for cases with higher or lower cloud fractions, and for decoupled PBLs. These results demonstrate the potential of using HSRL-2 aerosol backscatter data to estimate both marine MLH and PBLH and suggest that lidar-derived MLH should be compared with radiosonde/dropsonde-determined MLH (not PBLH) in general.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Semi‐Mechanistic Model for Partitioning Evapotranspiration Reveals Transpiration Dominates the Water Flux in Drylands

Abstract Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well‐suited to dryland ecosystems, such as high sensitivity of plant water‐use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine‐scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi‐mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process‐based models, and loosely constrains time‐varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross‐wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub‐yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem‐scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

Environmental Sciences & Ecology↗
DOE OSTI2025

Enhanced Boundary Layer Height Detection Using Ceilometer, Surface Meteorology, and Radiation Products With a Random Forest Ensemble Method

This study develops and evaluates a Random Forest (RF) model for estimating planetary boundary layer height (PBLH) using 9 years of data from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) user facility, with potential application in the NOAA Surface Radiation (SURFRAD) Network. The model integrates ceilometer, surface meteorology, and radiation measurements, and is trained using thermodynamic PBLH estimates derived from radiosondes. This approach aims to bridge gaps between aerosol-based and thermodynamic-based PBLH estimates. The RF model outperformed traditional methods during daytime and better captured transition periods, demonstrating improved accuracy and robustness. At ARM SGP, it showed a substantial reduction in both bias and RMSE, with a bias near zero (−4.9 m) compared with traditional Haar Wavelet (HW) (70.9 m) and Vaisala BL-View software (124.1 m), and an RMSE of 303.2 m, lower than both BL-View (566.9 m) and HW (404.6 m). During daytime hours, RF consistently outperformed both alternatives, maintaining lower bias and RMSE across all periods. At a second evaluation site, RF achieved the lowest overall RMSE (323.7 m), similar to HW (326.4 m) and significantly better than BL-View (738.3 m). However, all models showed reduced accuracy under stable nighttime conditions, limiting the reliability of PBLH estimates. Key predictors for the model included the lifting condensation level height (LCLH), aerosol gradients, and month for seasonal variability. The study underscores the potential of integrating machine learning with multiple data sets such as surface energy and thermodynamic data to advance PBLH estimation.

boundary layer height↗
DOE OSTI2026

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed. In this study, we developed a short-term hourly weather forecast framework with a wavelet transform function for data preprocessing and a spatiotemporal DL model, PredRNN, for predicting five surface atmospheric variables, including wind speed and direction, mean sea level pressure (MSLP), temperature, and precipitation. The framework demonstrated promising results. It produces global forecasts at 0.25° (∼25 km) with a 1-day lead time RMSE of 1.8 m/s for wind components, 180 Pa for MSLP, and 1.8 K for temperature. Although our model does not surpass state-of-the-art AI weather forecast models across all metrics, it outperforms these models in precipitation forecasting and wind prediction at short lead times and achieves comparable accuracy for MSLP. Its native hourly forecasting capability, together with training on widely accessible GPU hardware, contributes meaningfully to the advancement of accessible DL weather forecasting methods. Our work highlights the importance of integrating temporal components and data transformation techniques to improve the predictability and accuracy of weather forecasts.

Tran, Hoang [Pacific Northwest National Laboratory↗
DOE OSTI2025

A unified ensemble soil moisture dataset across the continental United States

Abstract A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies in temporal scales across datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions and making recommendations for drought response planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Theory of Single-Impact Atomic Force Spectroscopy in liquids with material contrast

Scanning probe microscopy has enabled nanoscale mapping of mechanical properties in important technological materials, such as tissues, biomaterials, polymers, nanointerfaces of composite materials, to name only a few. To improve and widen the measurement of nanoscale mechanical properties, a number of methods have been proposed to overcome the widely used force-displacement mode, that is inherently slow and limited to a quasi-static regime, mainly using multiple sinusoidal excitations of the sample base or of the cantilever. Here, a different approach is put forward. It exploits the unique capabilities of the wavelet transform analysis to harness the information encoded in a short duration spectroscopy experiment. It is based on an impulsive excitation of the cantilever and a single impact of the tip with the sample. It performs well in highly damped environments, which are often seen as problematic in other standard dynamic methods. Our results are very promising in terms of viscoelastic property discrimination. Their potential is oriented (but not limited) to samples that demand imaging in liquid native environments and also to highly vulnerable samples whose compositional mapping cannot be obtained through standard tapping imaging techniques.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Few-cycle Regime Atomic Force Microscopy

Abstract Traditionally, dynamic atomic force microscopy (AFM) techniques are based on the analysis of the quasi-steady state response of the cantilever deflection in terms of Fourier analysis. Here we describe a technique that instead exploits the often disregarded transient response of the cantilever through a relatively modern mathematical tool, which has caused important developments in several scientific fields but that is still quite unknown in the AFM context: the wavelet analysis. This tool allows us to localize the time-varying spectral composition of the initial oscillations of the cantilever deflection when an impulsive excitation is given (as in the band excitation method), a mode that we call the few-cycle regime . We show that this regime encodes very meaningful information about the tip-sample interaction in a unique and extremely sensitive manner. We exploit this high sensitivity to gain detailed insight into multiple physical parameters that perturb the dynamics of the AFM probe, such as the tip radius, Hamaker constant, sample’s elastic modulus and height of an adsorbed water layer. We validate these findings with experimental evidence and computational simulations and show a feasible path towards the simultaneous retrieval of multiple physical parameters.

42 ENGINEERING↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The hidden influence of terrestrial groundwater on salt marsh function and resilience

Salt marshes are hotspots of nutrient processing and carbon sequestration. So far, studies addressing spatiotemporal variability in and drivers of salt marsh biogeochemical function, carbon storage and resilience have focused on ocean-driven surface hydrologic influences, neglecting effects of terrestrial hydrology through subsurface connections. Here we evaluate drivers of salt marsh redox potential, a proxy for biogeochemical state, through wavelet analyses and information theory using data from seven marshes. The results point to terrestrial groundwater level as a dominant control on redox variability across all sites. Because redox is a key driver of biogeochemical processes, and specifically oxidation of organic matter that sequesters carbon and maintains marsh elevation, these terrestrial influences are critical to understanding marsh function and evolution. Further, the newly identified links between onshore groundwater levels and marsh redox conditions shift the traditional paradigm and suggest that terrestrial hydrology is a primary control on salt marsh carbon sequestration potential and resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Planck 2013 results. XXIV. Constraints on primordial non-Gaussianity

The Planck nominal mission cosmic microwave background (CMB) maps yield unprecedented constraints on primordial non-Gaussianity (NG). Using three optimal bispectrum estimators, separable template-fitting (KSW), binned, and modal, we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result f NL local = 2.7 ± 5.8, f NL equil = -42 ± 75, and f NL orth = -25 ± 39 (68% CL statistical). Non-Gaussianity is detected in the data; using skew-C &ell; statistics we find a nonzero bispectrum from residual point sources, and the integrated-Sachs-Wolfe-lensing bispectrum at a level expected in the ΛCDM scenario. The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are confirmed by skew-C &ell; , wavelet bispectrum and Minkowski functional estimators. Beyond estimates of individual shape amplitudes, we present model-independent, three-dimensional reconstructions of the Planck CMB bispectrum and thus derive constraints on early-Universe scenarios that generate primordial NG, including general single-field models of inflation, excited initial states (non-Bunch-Davies vacua), and directionally-dependent vector models. We provide an initial survey of scale-dependent feature and resonance models. These results bound both general single-field and multi-field model parameter ranges, such as the speed of sound, c s ≥ 0.02 (95% CL), in an effective field theory parametrization, and the curvaton decay fraction r D ≥ 0.15 (95% CL). The Planck data significantly limit the viable parameter space of the ekpyrotic/cyclic scenarios. The amplitude of the four-point function in the local model τ NL < 2800 (95% CL). Taken together, these constraints represent the highest precision tests to date of physical mechanisms for the origin of cosmic structure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Planck intermediate results: LIV. The Planck multi-frequency catalogue of non-thermal sources$^\star$

This paper presents the Planck Multi-frequency Catalogue of Non-thermal (i.e. synchrotron-dominated) Sources (PCNT) observed between 30 and 857 GHz by the ESA Planck mission. This catalogue was constructed by selecting objects detected in the full mission all-sky temperature maps at 30 and 143 GHz, with a signal-to-noise ratio (S/N)> 3 in at least one of the two channels after filtering with a particular Mexican hat wavelet. As a result, 29 400 source candidates were selected. Then, a multi-frequency analysis was performed using the Matrix Filters methodology at the position of these objects, and flux densities and errors were calculated for all of them in the nine Planck channels. This catalogue was built using a different methodology than the one adopted for the Planck Catalogue of Compact Sources (PCCS) and the Second Planck Catalogue of Compact Sources (PCCS2), although the initial detection was done with the same pipeline that was used to produce them. The present catalogue is the first unbiased, full-sky catalogue of synchrotron-dominated sources published at millimetre and submillimetre wavelengths and constitutes a powerful database for statistical studies of non-thermal extragalactic sources, whose emission is dominated by the central active galactic nucleus. Together with the full multi-frequency catalogue, we also define the Bright Planck Multi-frequency Catalogue of Non-thermal Sources (PCNTb), where only those objects with a S/N > 4 at both 30 and 143 GHz were selected. In this catalogue 1146 compact sources are detected outside the adopted Planck GAL070 mask; thus, these sources constitute a highly reliable sample of extragalactic radio sources. We also flag the high-significance subsample (PCNThs), a subset of 151 sources that are detected with S/N > 4 in all nine Planck channels, 75 of which are found outside the Planck mask adopted here. The remaining 76 sources inside the Galactic mask are very likely Galactic objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CODEX clusters

Context: Large area catalogs of galaxy clusters constructed from ROSAT All-Sky Survey provide the basis for our knowledge of the population of clusters thanks to long-term multiwavelength efforts to follow up observations of these clusters. Aims: The advent of large area photometric surveys superseding previous, in-depth all-sky data allows us to revisit the construction of X-ray cluster catalogs, extending the study to lower cluster masses and higher redshifts and providing modeling of the selection function. Methods: We performed a wavelet detection of X-ray sources and made extensive simulations of the detection of clusters in the RASS data. We assigned an optical richness to each of the 24 788 detected X-ray sources in the 10 382 square degrees of the Baryon Oscillation Spectroscopic Survey area using red sequence cluster finder redMaPPer version 5.2 run on Sloan Digital Sky Survey photometry. We named this survey COnstrain Dark Energy with X-ray (CODEX) clusters. Results: We show that there is no obvious separation of sources on galaxy clusters and active galactic nuclei (AGN) based on the distribution of systems on their richness. This is a combination of an increasing number of galaxy groups and their selection via the identification of X-ray sources either by chance or by groups hosting an AGN. To clean the sample, we use a cut on the optical richness at the level corresponding to the 10% completeness of the survey and include it in the modeling of the cluster selection function. We present the X-ray catalog extending to a redshift of 0.6. Conclusions: The CODEX suvey is the first large area X-ray selected catalog of northern clusters reaching fluxes of 10 –13 ergs s –1 cm –2 . We provide modeling of the sample selection and discuss the redshift evolution of the high end of the X-ray luminosity function (XLF). Our results on z < 0.3 XLF agree with previous studies, while we provide new constraints on the 0.3 < z < 0.6 XLF. We find a lack of strong redshift evolution of the XLF, provide exact modeling of the effect of low number statistics and AGN contamination, and present the resulting constraints on the flat ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The Sagittarius stream in Gaia Early Data Release 3 and the origin of the bifurcations

The Sagittarius dwarf spheroidal (Sgr) is a dissolving galaxy being tidally disrupted by the Milky Way (MW). Its stellar stream still poses serious modelling challenges, which hinders our ability to use it effectively as a prospective probe of the MW gravitational potential at large radii. Our goal is to construct the largest and most stringent sample of stars in the stream with which we can advance our understanding of the Sgr-MW interaction, focusing on the characterization of the bifurcations. We improved on previous methods based on the use of the wavelet transform to systematically search for the kinematic signature of the Sgr stream throughout the whole sky in the Gaia data. We then refined our selection via the use of a clustering algorithm on the statistical properties of the colour-magnitude diagrams. Our final sample contains more than 700 000 candidate stars and is three times larger than previous Gaia samples. With it, we have been able to detect the bifurcation of the stream in both the northern and southern hemispheres, which requires four branches (two bright and two faint) to fully describe the system. We present the detailed proper motion distribution of the trailing arm as a function of the angular coordinate along the stream, showing, for the first time, the presence of a sharp edge (on the side of the small proper motions) beyond which there are no Sgr stars. We also characterize the correlation between kinematics and distance. Finally, the chemical analysis of our sample shows that the faint branch of the bifurcation is more metal poor than the bright. We provide analytical descriptions for the proper motion trends as well as for the sky distribution of the four branches of the stream. Based on our analysis, we interpret the bifurcations as a misaligned overlap of the material stripped at the antepenultimate pericentre (faint branches) with the stars ejected at the penultimate pericentre (bright branch), given that Sgr just went through its perigalacticon. The source of this misalignment is still unknown, but we argue that models with some internal rotation in the progenitor – at least during the time of stripping of the stars that are now in the faint branches – are worth exploring.

79 ASTRONOMY AND ASTROPHYSICS↗