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At least 451 records · Page 25

Origin of the ring ellipticity in the black hole images of M87*

We investigate the origin of the elliptical ring structure observed in the images of the supermassive black hole M87*, aiming to disentangle contributions from gravitational, astrophysical, and imaging effects. Leveraging the enhanced capabilities of the Event Horizon Telescope (EHT)'s 2018 array, including improved (u,v)-coverage from the Greenland Telescope, we measured the ring's ellipticity using five independent imaging methods, obtaining a consistent average value of τ = 0.08−0.02+0.03 with a position angle of ξ = 50.1−7.6+6.2 degrees. To interpret this measurement, we compared it to general relativistic magnetohydrodynamic (GRMHD) simulations spanning a wide range of physical parameters including the thermal or nonthermal electron distribution function, spins, and ion-to-electron temperature ratios in both low- and high-density regions. We find no statistically significant correlation between spin and ellipticity in GRMHD images. Instead, we identify a correlation between ellipticity and the fraction of non-ring emission, particularly in nonthermal models and models with higher jet emission. These results indicate that the ellipticity measured from the M87* emission structure is consistent with that expected from simulations of turbulent accretion flows around black holes, where it is dominated by astrophysical effects rather than gravitational ones. Future high-resolution imaging, including space very long baseline interferometry and long-term monitoring, will be essential to isolate gravitational signatures from astrophysical effects.Key words: accretion, accretion disks / black hole physics / gravitation / galaxies: active** These authors have contributed equally to this work.*** NASA Hubble Fellowship Program, Einstein Fellow.† Deceased.

Dahale, Rohan [Granada U., Theor. Phys. Astrophys.↗

Deep Learning on Multimodal Chemical and Whole Slide Imaging Data for Predicting Prostate Cancer Directly from Tissue Images

Prostate cancer is one of the most common cancers globally and is the second most common cancer in the male population in the US. Here we develop a study based on correlating the hematoxylin and eosin (H&E)-stained biopsy data with MALDI mass-spectrometric imaging data of the corresponding tissue to determine the cancerous regions and their unique chemical signatures and variations of the predicted regions with original pathological annotations. We obtain features from high-resolution optical micrographs of whole slide H&E stained data through deep learning and spatially register them with mass spectrometry imaging (MSI) data to correlate the chemical signature with the tissue anatomy of the data. We then use the learned correlation to predict prostate cancer from observed H&E images using trained coregistered MSI data. This multimodal approach can predict cancerous regions with ~80% accuracy, which indicates a correlation between optical H&E features and chemical information found in MSI. Further, we show that such paired multimodal data can be used for training feature extraction networks on H&E data which bypasses the need to acquire expensive MSI data and eliminates the need for manual annotation saving valuable time. Two chemical biomarkers were also found to be predicting the ground truth cancerous regions. This study shows promise in generating improved patient treatment trajectories by predicting prostate cancer directly from readily available H&E-stained biopsy images aided by coregistered MSI data.

60 APPLIED LIFE SCIENCES↗

Probing cold nuclear matter with energy correlators

The future electron-ion collider (EIC) will produce the first-ever high energy collisions between electrons and a wide range of nuclei, opening a new era in the study of cold nuclear matter. Quarks and gluons produced in these collisions will propagate through the dense nuclear matter of nuclei, imprinting its structure into subtle correlations in the energy flux of final state hadrons. In this article, we apply recent developments from the field of jet substructure, namely the energy correlator observables, to decode these correlations and provide a new window into nuclear structure. The energy correlators provide a calibrated probe of the scale dependence of vacuum quantum chromodynamics (QCD), enabling medium modifications to be imaged and interpreted as a function of scale. Using the eHIJING parton shower to simulate electron-nucleus collisions, we demonstrate that the size of the nucleus is imprinted as an angular scale in the correlators, with a magnitude that is visible for realistic EIC kinematics. We can observe the size difference between the proposed EIC nuclear targets 3 He, 4 He, 12 C, 40 Ca, 64 Cu, 197 Au, and 238 U, showing that the energy correlators can image femtometer length scales using asymptotic energy flux. Our approach offers a unified view of jet substructure across collider experiments, and provides numerous new theoretical tools to unravel the complex dynamics of QCD in extreme environments, both hot and cold.

Electron-ion collisions↗

Imaging a light-induced molecular elimination reaction with an X-ray free-electron laser

Tracking the motion of individual atoms during chemical reactions represents a severe experimental challenge, especially if several competing reaction pathways exist or if the reaction is governed by the correlated motion of more than two molecular constituents. Here we demonstrate how ultrashort X-ray pulses combined with coincident ion imaging can be used to trace molecular iodine elimination from laser-irradiated diiodomethane (CH 2 I 2 ), a reaction channel of fundamental importance but small relative yield that involves the breaking of two molecular bonds and the formation of a new one. We map bending vibrations of the bound molecule, disentangle different dissociation pathways, image the correlated motion of the iodine atoms and the methylene group leading to molecular iodine ejection, and trace the vibrational motion of the formed product. Our results provide a quantitative mechanistic picture behind previously suggested reaction mechanisms and prove that a variety of geometries are involved in the molecular bond formation.

Atomic and molecular interactions with photons↗

High-speed quantitative X-ray multi-contrast imaging with deep learning based modulated pattern analysis

The advent of X-ray multi-contrast imaging methods, providing absorption, phase, and dark-field images, holds tremendous promise for complementary and non-destructive visualization of inner structures within materials and bio-samples. However, the low efficiency in measuring and analyzing X-ray modulated patterns has hindered their application in high-resolution in situ imaging. In this work, the Enhanced Scanning Pattern-based Imaging Neural Network (ESPINNet) is introduced as a powerful tool for achieving high-speed, high-resolution quantitative imaging. ESPINNet is faster than correlation-based speckle tracking methods such as XSVT and UMPA, and provides a balanced performance in terms of resolution and speed for data collection by using fewer scanning images. In comparison with our previously developed neural network, ESPINNet introduces the capability to generate dark-field images, further enhancing its versatility. By leveraging scanning patterns, ESPINNet significantly improves resolution and measurement precision. Furthermore, its adaptability to various modulation patterns, including those produced by sandpaper, coded masks, or gratings, ensures broad applicability. These features enable real-time 2D and 3D multi-contrast imaging, positioning ESPINNet as a transformative solution for applications in materials science and biomedical research, particularly for high-speed and in situ measurements.

X-ray at-wavelength metrology↗

Dark Energy Survey Year 3 results: Measurement of the baryon acoustic oscillations with three-dimensional clustering

The three-dimensional correlation function offers an effective way to summarize the correlation of the large-scale structure even for imaging galaxy surveys. We have applied the projected three-dimensional correlation function, ξ p to measure the baryonic acoustic oscillations (BAO) scale on the first-three years Dark Energy Survey data. The sample consists of about 7 million galaxies in the redshift range 0.6< z p < 1.1 over a footprint of 4108 deg 2 . Our theory modeling includes the impact of realistic true redshift distributions beyond Gaussian photo-z approximation. ξ p is obtained by projecting the three-dimensional correlation to the transverse direction. To increase the signal-to-noise of the measurements, we have considered a Gaussian stacking window function in place of the commonly used top-hat. ξ p is sensitive to D M (z eff )/r s , the ratio between the comoving angular diameter distance and the sound horizon. Using the full sample, D M (z eff )/r s is constrained to be19.00 ± 0.67 (top-hat) and 19.15 ± 0.58 (Gaussian) at z eff = 0.835. The constraint is weaker than the angular correlation w constraint 18.84 ± 0.50), and we trace this to the fact that the BAO signals are heterogeneous across redshift. While ξ p responds to the heterogeneous signals by enlarging the error bar, w can still give a tight bound on D M s in this case. When a homogeneous BAO-signal subsample in the range 0.7 < z p <1.0 (z eff = 0.845) is considered, ξp yields 19.80 ± 0.67 (top-hat) and 19.84 ± 0.53 (Gaussian). The latter is mildly stronger than the w constraint (19.86 ± 0.55). We find that the ξ p results are more sensitive to photo-z because ξ p keeps the three-dimensional clustering information causing it to be more prone to photo-z noise. The Gaussian window gives more robust results than the top-hat as the former is designed to suppress the low signal modes. ξ p and the angular statistics such as w have their own pros and cons, and they serve an important crosscheck with each other.

79 ASTRONOMY AND ASTROPHYSICS↗

Field-Tunable Interactions and Frustration in Underlayer-Mediated Artificial Spin Ice

We report that artificial spin ice systems have opened experimental windows into a range of model magnetic systems through the control of interactions among nanomagnet moments. This control has previously been enabled by altering the nanomagnet size and the geometry of their placement. Here we demonstrate that the interactions in artificial spin ice can be further controlled by including a soft ferromagnetic underlayer below the moments. Such a substrate also breaks the symmetry in the array when magnetized, introducing a directional component to the correlations. Using spatially resolved magneto-optical Kerr effect microscopy to image the demagnetized ground states, we show that the correlation of the demagnetized states depends on the direction of the underlayer magnetization. Further, the relative interaction strength of nearest and next-nearest neighbors varies significantly with the array geometry. We exploit this feature to induce frustration in an inherently unfrustrated square lattice geometry, demonstrating new possibilities for effective geometries in two-dimensional nanomagnetic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimizing cloud motion estimation on the edge with phase correlation and optical flow

Abstract. Phase correlation (PC) is a well-known method for estimating cloud motion vectors (CMVs) from infrared and visible spectrum images. Commonly, phase shift is computed in the small blocks of the images using the fast Fourier transform. In this study, we investigate the performance and the stability of the blockwise PC method by changing the block size, the frame interval, and combinations of red, green, and blue (RGB) channels from the total sky imager (TSI) at the United States Atmospheric Radiation Measurement user facility's Southern Great Plains site. We find that shorter frame intervals, followed by larger block sizes, are responsible for stable estimates of the CMV, as suggested by the higher autocorrelations. The choice of RGB channels has a limited effect on the quality of CMVs, and the red and the grayscale images are marginally more reliable than the other combinations during rapidly evolving low-level clouds. The stability of CMVs was tested at different image resolutions with an implementation of the optimized algorithm on the Sage cyberinfrastructure test bed. We find that doubling the frame rate outperforms quadrupling the image resolution in achieving CMV stability. The correlations of CMVs with the wind data are significant in the range of 0.38–0.59 with a 95 % confidence interval, despite the uncertainties and limitations of both datasets. A comparison of the PC method with constructed data and the optical flow method suggests that the post-processing of the vector field has a significant effect on the quality of the CMV. The raindrop-contaminated images can be identified by the rotation of the TSI mirror in the motion field. The results of this study are critical to optimizing algorithms for edge-computing sensor systems.

54 ENVIRONMENTAL SCIENCES↗

Multiparticle cumulant mapping for Coulomb explosion imaging: Calculations and algorithm

We present a versatile cumulant mapping algorithm for analyzing correlated particle emission, offering insights into complex electronic and nuclear dynamics. Recently, we have demonstrated the use of cumulant mapping to extract information-rich correlations between the momenta of multiple fragments produced in Coulomb explosion imaging experiments [C. Cheng et al., Phys. Rev. Lett. 130, 093001 (2023)]. We define cumulant mapping in terms of histograms, enabling fast computation of linear (additive) observables. However, applying the same algorithm to nonlinear (nonadditive) observables poses challenges, as the computation time of conventional estimators scales nonlinearly with data size. To overcome this, we develop estimators and an accompanying algorithm to enable computationally efficient estimation of the cumulant of interest. Comparisons of computation times and signal-to-noise ratios reveal the superior performance of our approach. This method is demonstrated on the (D+, D+, C+, O+) dissociation channel of CD 2 ⁢O 4+ produced in a strong-field ionization experiment. Additionally, Poisson statistics are used to simulate the two methods and provide insights into the efficiency of our algorithm. The proposed methodology unlocks efficient computation of cumulant mapping for a broader range of complex systems and observables, such as the laser pulse dependence of ionization dynamics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Analysis of structure-property gradients in orthogonally machined chips and workpiece subsurface

Production of machined surfaces with optimized mechanical properties requires fundamental process-structure-property knowledge. In this paper, we focus on structure-property gradients in orthogonally cut OFHC Copper chips and the workpiece subsurface. We utilize orientation imaging microscopy and statistical spatial correlation metrics to quantify the microstructure. Constitutive elastic-plastic properties of the workpiece subsurface and chips are measured using spherical nanoindentation. Analysis of the data reveals significant structure and property gradients in both regions. Differences and similarities in structure and property gradients near the workpiece surface and tool-chip interface, and in the chip middle are discussed and explained.

42 ENGINEERING↗

Revealing the three-dimensional structure of microbunched plasma-wakefield-accelerated electron beams

Abstract Plasma wakefield accelerators use tabletop equipment to produce relativistic femtosecond electron bunches. Optical and X-ray diagnostics have established that their charge concentrates within a micrometre-sized volume, but its sub-micrometre internal distribution, which critically influences gain in free-electron lasers or particle yield in colliders, has proven elusive to characterize. Here, by simultaneously imaging different wavelengths of coherent optical transition radiation that a laser-wakefield-accelerated electron bunch generates when exiting a metal foil, we reveal the structure of the coherently radiating component of bunch charge. The key features of the images are shown to uniquely correlate with how plasma electrons injected into the wake: by a plasma-density discontinuity, by ionizing high- Z gas-target dopants or by uncontrolled laser–plasma dynamics. With additional input from the electron spectra, spatially averaged coherent optical transition radiation spectra and particle-in-cell simulations, we reconstruct coherent three-dimensional charge structures. The results demonstrate an essential metrology for next-generation compact X-ray free-electron lasers driven by plasma-based accelerators.

43 PARTICLE ACCELERATORS↗

Electric field stimulates production of highly conductive microbial OmcZ nanowires

Multifunctional living materials are attractive due to their powerful ability to self-repair and replicate. However, most natural materials lack electronic functionality. Here we show that an electric field, applied to electricity-producing Geobacter sulfurreducens biofilms, stimulates production of cytochrome OmcZ nanowires with 1,000-fold higher conductivity (30 S cm -1 ) and threefold higher stiffness (1.5 GPa) than the cytochrome OmcS nanowires that are important in natural environments. Using chemical imaging-based multimodal nanospectroscopy, we correlate protein structure with function and observe pH-induced conformational switching to β-sheets in individual nanowires, which increases their stiffness and conductivity by 100-fold due to enhanced π-stacking of heme groups; this was further confirmed by computational modeling and bulk spectroscopic studies. These nanowires can transduce mechanical and chemical stimuli into electrical signals to perform sensing, synthesis and energy production. Overall, these findings of biologically produced, highly conductive protein nanowires may help to guide the development of seamless, bidirectional interfaces between biological and electronic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Collagen Turnover in Relation to Risk Factors and Hemodynamics in Human Intracranial Aneurysms

Determinants for molecular and structural instability, that is, impending growth or rupture, of intracranial aneurysms (IAs) remain uncertain. To elucidate this, we endeavored to estimate the actual turnover rates of the main molecular constituent in human IA (collagen) on the basis of radiocarbon ( 14 C) birth dating in relation to IA hemodynamics. Collagen turnover rates in excised human IA samples were calculated using mathematical modeling of 14 C birth dating data of collagen in relation to risk factors and histological markers for collagen maturity/turnover in selected IA. Hemodynamics were simulated using image-based computational fluid dynamics. Correlation, logistic regression, and receiver operating characteristic analyses were performed. Collagen turnover rates were estimated in 46 IA (43 patients); computational fluid dynamics could be performed in 20 IA (20 patients). The mean collagen turnover rate (γ) constituted 126% (±1% error) per year. For patients with arterial hypertension, γ was greater than 2600% annually, whereas γ was distinctly lower with 32% (±1% error) per year for patients without risk factors, such as smoking and hypertension. There was a distinct association between histological presence of rather immature collagen in human IA and the presence of modifiable risk factors. Spatial-temporal averaged wall shear stress predicted rapid collagen turnover (odds ratio, 1.6 [95% CI, 1.0–2.7]). Receiver operating characteristic analysis demonstrated a good test accuracy (area under the curve, 0.798 [95% CI, 0.598–0.998]) for average wall shear stress with a threshold ≥4.9 Pa for rapid collagen turnover. Our data indicate that turnover rates and stability of collagen in human IA are strongly associated with the presence of modifiable risk factors and aneurysmal hemodynamics. Finally, these findings underline the importance of strict risk factor modification in patients with unruptured IA. Future should include more detailed risk factor data to establish a more causal understanding of hemodynamics and the rupture risk of individual IA.

60 APPLIED LIFE SCIENCES↗

Humming Trains in Seismology: An Opportune Source for Probing the Shallow Crust

Abstract Seismologists are eagerly seeking new and preferably low-cost ways to map and track changes in the complex structure of the top few kilometers of the crust. By understanding it better, they can build on what is known regarding important, practical issues. These include telling us whether imminent earthquakes and volcanic eruptions are generating telltale underground signs of hazard, about mitigation of induced seismicity such as from deep injection of wastewater, how the Earth and its atmosphere couple, and where accessible natural resources are. Passive seismic imaging usually relies on blind correlations within extended recordings of Earth’s ceaseless “hum” or coda of well-mixed, small vibrations. In this article, we propose a complementary approach. It is seismic interferometry using opportune sources—specifically ones not stationary in time and moving in a well-understood configuration. Its interpretation relies on an accurate understanding of how these sources radiate seismic waves, precise timing, careful placement of pairs of listening stations, and seismic phase differentiation (surface and body waves). Massive freight trains were only recently recognized as such a persistent, powerful cultural (human activity-caused) seismic source. One train passage may generate a tremor with an energy output of a magnitude 1 earthquake and be detectable for up to 100 km from the track. We discuss the source mechanisms of train tremors and review the basic theory on sources. Finally, we present case studies of body- and surface-wave retrieval as an aid to mineral exploration in Canada and to monitoring of a southern California fault zone. We believe noise recovery from this new signal source, together with dense data acquisition technologies such as nodes or distributed acoustic sensing, will deeply transform our ability to monitor activity in the shallow crust at sharpened resolution in time and space.

Geochemistry & Geophysics↗

Trace Chemical Detection Using Intercalated MXenes as a Signal Enhancing Substrate in Optical Probes

MXenes are 2D materials composed of layered transition metal nitrides or carbides. These materials are synthesized by HF exfoliation from MAX phases (Ti{sub 3}AlC{sub 2}). The 2D nanomaterial was synthesized by the removal of the 'A' element, resulting in a Mxene product (Ti{sub 3}C{sub 2}). MXenes have the general formula M{sub n+1}X{sub n}T{sub x}, where M is an early transition metal, X is Carbon and/or Nitrogen, and T accounts for surface terminated functional groups such as Fluoride, hydroxyl, and oxygen. These materials have very unique properties, similar to graphene, that allows them to be applied in a variety of trace detection techniques including surface-enhanced Raman spectroscopy (SERS). MXenes have also been demonstrated to selectively uptake uranyl ion, UO{sub 2}{sup 2+}. If this property can be combined with SERS or fluorescence detection, it may be possible to use MXenes as the basis for an alternative method to kinetic phosphorescence analysis (KPA) for trace uranyl measurements. Objectives: To confirm that MXene Nano materials are suitable substrates for SERS and sensor development by enhancing Raman signaling. To determine if certain MXene preparation methods yield materials that are more suitable for trace sensing methods. To determine uranyl uptake properties of these MXene materials and test them for analytical signals. Sample Preparation: Preparation of Ti{sub 3}C{sub 2}MXene (at FSU). MXenes were prepared by etching Al from Ti{sub 3}AlC{sub 2} (MAX phase)material. Two etching techniques yield different MXene products: LiF/HCl: Milder reaction, larger MXene flakes. HF: Harsher reaction, smaller flakes, larger layer separation. Products washed to remove etchant, vacuum filtered, and dried. Dried MXene flakes are air-stable. Film preparation for sensor testing (at SRNL): Suspend powder in diH{sub 2}O, purge with Ar, sonicate for 30 min. Centrifuge and collect supernate with suspended particles. Observed LiF-etched Mxene yielded a higher density of particles and darker collected solution. Drop-cast (4 ml) supernate onto slides and dried with Ar. For Rhodamine B (RhB) testing, drop-cast 4 ml drops onto Mxene spots and dried with Ar. Scanning Electron Microscopy conditions: 10 kV Beam energy, high vacuum; Working distance of 8 mm; beam penetration depth appx. 4 microns, beam spot size appx. 2 nanometers. Results: Detection of aluminum correlates with bright spots on image. Presence of aluminum shows that LiF/HCl etching was less thorough than HF etching. Trace Cl detection in LiF images suggests incomplete rinsing. HF has smaller feature size, more layer structure, and increased homogeneity, consistent with expectations. Macroscopic Raman spectroscopy measurements: 532 nm excitation, ∼50 mW with a ∼100 micron spot size (InPhotonics RPB probe). Kaiser Optical Holospec f/1.8 spectrometer with cooled (-60 deg.C) Andor iDus OE420 CCD. LiF 1x supernate showed good signal for trace measurements of Rhodamine B. HF and 1/4x LiF supernates showed little Mxene or Rhodamine B signal. Low deposition densities led to excess background signal from glass slides. For LiF film, response is linear with Rhodamine B concentration over range tested. Will retest with Raman microscope (∼1 micron spot size) to characterize SERS of more dilute LiF and HF etched Mxenes. Conclusions: The LiF etched material was more suitable for macroscopic SERS measurements because it was more concentrated, resulting in a thicker film than the HF etched Mxene and diluted LiF sample. However, the other materials may give greater SERS enhancements, which we hope to determine from measurements with the Raman microscope. From characterization with SEM we concluded that the HF etched Mxene is more uniform/homogenous and has smaller particle size than the LiF etched Mxene. There is still aluminum present in both samples indicating that etching wasn't complete, but the removal of the aluminum was more efficient in the HF method. Path Forward: Observe SERS with Raman microscopy, to obtain better signals for the more diluted samples and be able to compare enhancement effects for the different MXenes. Characterize uranyl sorption into MXene films and test Raman and fluorescence signals. Revisit the etching conditions to improve removal of aluminum. FSU and SRNL will continue to collaborate to create and characterize different Mxene materials and test their usefulness for sensor applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Background-Oriented Schlieren Velocimetry of Helium Coolant Flow in Additively Manufactured Channels

High-pressure helium gas cooling is an attractive solution for thermal management of the fusion blanket first wall, as this coolant is chemically and neutronically inert and separable from hydrogenic species. However, due to the low thermal mass of helium, geometric optimization of these channels is required to provide sufficient cooling at manageable flow rates and pumping burdens. Increasingly, analysis and optimization of these coolant channels rely on computational fluid dynamics (CFD) simulations, and these require relevant experimental data for turbulence model validation. Toward this end, a high-pressure helium gas flow visualization system has been employed to image the flow of helium in flow channels with one-sided heating, mimicking the blanket first wall environment. Flow of helium at 4 MPa pressure and flow rates up to 68 g/s (Reynolds number 57 000) is supplied to rectangular channel test sections, with uniform heating applied to the bottom wall of the channel at heat fluxes varied between roughly 50 and 130 kW/m2. A high-speed camera is used to image index of refraction (IOR) gradients in the fluid via background-oriented schlieren (BOS), and temperature and pressure instrumentation are used to characterize thermal-hydraulic performance of each channel. Cross correlation of time-resolved BOS images is then used to calculate time-averaged 2-D helium velocity fields. Flow in additively manufactured (AM) channels is examined in this manner, including both featureless channels and those containing baffling as a heat transfer enhancement. The flow distribution seen in the featureless case differs significantly from that seen in prior simulations, whereas the flow in the baffled case shows the predicted behavior of flow forced along the heated wall. This augmented flow distribution is seen to increase the heat transfer coefficient in the baffled test section. Here, strategies are discussed for ongoing and future validation of these simulations, with the aim of model deployment for blanket cooling design and optimization.

Additive manufacturing↗

DESI luminous red galaxy samples for cross-correlations

We present two galaxy samples, selected from DESI Legacy Imaging Surveys (LS) DR9, with approximately 20,000 square degrees of coverage and spectroscopic redshift distributions designed for cross-correlations such as with CMB lensing, galaxy lensing, and the Sunyaev-Zel'dovich effect. The first sample is identical to the DESI Luminous Red Galaxy (LRG) sample, and the second sample is an extended LRG sample with 2–3 times the DESI LRG density. We present the improved photometric redshifts, tomographic binning and their spectroscopic redshift distributions and imaging systematics weights, and magnification bias coefficients. The catalogs and related data products will be made publicly available. The cosmological constraints using this sample and Planck lensing maps are presented in a companion paper. Here, we also make public the new set of general-purpose photometric redshifts trained using DESI spectroscopic redshifts, which are used in this work, for all galaxies in LS DR9.

79 ASTRONOMY AND ASTROPHYSICS↗