Astrophysics
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The day in astrophysics: stars, galaxies, and the sky that keeps surprising us.
Astrophysics reads the day across arXiv's astro-ph archive: what was observed, with which instrument, and what the observation constrains. The physicists in the studio argue about the error bars and about which model the data actually excludes, and the show keeps the difference visible between a detection, a hint, and a press release.
Episode: The day in conversation for 2026-11-01
November 01, 2026
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The discussion: Vera: The attenuation factors derived for optical power propagation in those CMB experiments seem overly optimistic regarding the thermal load implications; are we assuming perfect coupling between the detector and the primary mode, or is that a simplification? Jocelyn: I'm more concerned with how those specific rejection levels translate into hardware constraints, because if you increase the out-of-band attenuation requirement by a factor of two, does that necessitate a change in the cryogenic system's heat dissipation budget for an array the size of Planck? Subrahmanyan: That brings up my point about modeling; while I understand the propagation physics, I haven't seen how those derived factors interact with actual detector noise floors yet. Specifically, what is the dependency of that attenuation factor on the angular scale we are trying to resolve in the B-mode polarization signal? Vera: Well, based on the simulations presented in 2606.31778, they suggest a nearly frequency-independent behavior above 100 GHz for this specific atmospheric path, but I wonder if that holds up when considering potential foreground contamination from synchrotron emission at those higher frequencies. Jocelyn: If there is significant synchrotron contamination, does the model inherently account for the spectral index variation across the sky, or are we assuming a single characteristic
Episode: Unified matched-filter and excess-power pipeline for gravitational-wave detector characterization
November 01, 2026
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Introduction to the show: ident: Astrophysics. The day in astrophysics: observations, models and what the data forces.
Vera: I'm Vera.
Jocelyn: And I'm Jocelyn, here with Subrahmanyan.
Vera: We're looking at the paper: "Unified matched-filter and excess-power pipeline for gravitational-wave detector characterization".
Jocelyn: Here's the gist of the paper. sgnax presents sgnax, an open-source pipeline for gravitational-wave detector characterization that delivers both matched-filter and excess-power transient triggers from a single streaming dataflow graph The paper introduces sgnax as a unified Python package that subsumes both the multi-rate sine-Gaussian matched filter search of snax and the multi-resolution Q-transform excess-power search of omicron into one framework This unification allows for a single configuration object, output schema, and dependency tree to manage both analyses.
Vera: Pipeline Architecture sgnax is built on the Stream Graph Navigator (sgn) dataflow framework, which is described as a directed graph of elements connected through named pads The pipeline draws elements from four sgn ecosystem packages, including sgn-ts for time-series elements and sgn-ligo and sgn-arrakis for data sources.
Jocelyn: A single invocation processes an arbitrary list of channels from a single interferometer through one pipeline, with each channel's final trigger stream routed to its own pad on a single shared HDF5FeatureSink.
Vera: The two pipelines share a configuration object, DataSourceInfo, which specifies the data acquisition stage and allows both analyses to consume any of three data-source backends: offline frame caches, the low-latency shared-memory buffer, and the arrakis distribution service.
Paper summary: Vera: So, to recap, this paper introduces sgnax as an open-source pipeline that delivers both matched filter and excess power transient triggers from a single streaming dataflow graph. The core thesis is unification.
Jocelyn: They combine the multi-rate sine-Gaussian matched filter search of snax and the multi-resolution Q-transform excess-power search of omicron into one framework. This allows for a single configuration object, output schema, and dependency tree to manage both analyses together.
Subrahmanyan: The motivation for this rewrite is fourfold. First, the operational cost of maintaining snax as a thin Python layer over the gstreamer-one point zero dataflow has grown with each upstream release <ref:2608.09804#pg1>.
Vera: Second, the sgn framework offers a typed, native-python alternative whose elements can be composed without a C-level pipeline backbone. That’s a big deal for maintainability and flexibility.
Jocelyn: Third, omicron requires a heavy set of external libraries and two separate pipelines to run it. This unified approach solves that dependency problem by putting both analyses in one place.
Subrahmanyan: And the motivation is also about closing a long-standing latency gap by allowing Q-transform triggers to reach commissioners within tens of seconds of acquisition.
Vera: The pipeline itself is built on the Stream Graph Navigator framework, which uses a directed graph of elements connected through named pads. It pulls elements from sgn ecosystem packages like sgn-ts for time series and data sources like sgn-ligo and arrakis.
Jocelyn: A single invocation processes an arbitrary list of channels through one pipeline. Each channel's final trigger stream is routed to its own pad on a single shared HDF5 feature sink.
Subrahmanyan: The configuration object, DataSourceInfo, lets both analyses consume any of three data-source backends: offline frame caches, the low latency shared memory buffer, and the arrakis distribution service.
Vera: So the point is that they’ve created a unified package that handles both analyses with one set of tools.
Jocelyn: It allows for a single configuration object, output schema, and dependency tree to manage both analyses. It makes setting up these complex characterization workflows much simpler.
Subrahmanyan: This moves the work from being two separate, heavy pipelines to one cohesive system managed by a single interface.
Conclusion: Vera: So, looking at the title "Unified matched-filter and excess-power pipeline for gravitational-wave detector characterization," it really sums up what they did. They took two established methods and merged them into one unified pipeline.
Jocelyn: It’s about taking the operational burden off people who are trying to characterize detectors, letting them manage one package instead of two different ones.
Subrahmanyan: The implication is that for those working on detector characterization, this framework offers a single place to go for both matched filter and excess power searches.
Vera: It specifically addresses the latency issue by aiming to get Q-transform triggers to commissioners within tens of seconds of acquisition, which is a key operational goal.
Jocelyn: And the work establishes that the Q-plane construction and excess-power statistic reproduce the omicron trigger population on archival strain data to within about twenty percent in every frequency band that hosts scattered light and other transient noise classes <ref:2608.09804#pg2>.
Subrahmanyan: So, what this means for cosmology or structure formation is that we have a robust tool now for extracting those specific types of signals from detector data, which is crucial input for those larger cosmological models.
Vera: The open-source release provides the implementation and validation suite needed to migrate existing workflows. It’s there to help people move away from the older gstreamer-one point zero dependency toward this native Python approach <ref:2608.09804#pg1>.
Jocelyn: It closes a long-standing latency gap by making those Q-transform triggers more accessible in time for rapid follow-up or monitoring activities.
Episode: Daily Summary for 2026-11-01
November 01, 2026
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Introduction to the show: ident: Astrophysics. The day in astrophysics: observations, models and what the data forces.
Vera: It's the first of November, twenty twenty-six, and this is the day's research.
Jocelyn: 8 new papers came out today.
Vera: I'm Vera.
Jocelyn: And I'm Jocelyn, here with Subrahmanyan.
Vera: We'll take the day in one pass, then pull out the papers we're staying with.
Jocelyn: Start us off with NEXUS: Quick Release Notes.
The day's research: Vera: We need requirements for out of band rejection in CMB experiments. This is crucial because they have strict sensitivity goals.
Jocelyn: Mousset et al. models the optical response and sky emissions to determine power outside the bandpass affects detection and thermal load.
Subrahmanyan: That results in attenuation factors in decibels that guide filter design for hardware buildout.
Vera: Understanding those constraints dictates how we build hardware to capture faint signals we are looking for.
Jocelyn: Goisman et al. modeled galaxy completeness using archival HST data and found ETC predictions were less accurate than their analysis.
Subrahmanyan: That suggests a need for more realistic source modeling in those applications.
Vera: DINOspec introduces a framework aligning vision and spectral encoders using lightweight adapters for classification improvement.
Jocelyn: It improves galaxy morphology classification but shows no consistent improvement in redshift prediction over the baseline AION-1 model.
Subrahmanyan: sgnax unifies two transient trigger searches into a single Python package for operational advantage.
Vera: That allows both the sine-Gaussian matched filter search and the Qtransform excess-power search to run from one configuration object.
Jocelyn: The papers cover setting requirements on out of band rejection for next generation CMB experiments, application to LiteBIRD, and NEXUS quick release notes.
Subrahmanyan: DINOspec covers efficient multimodal alignment of vision and spectral foundation models for astronomy.
Vera: FARSim presents a fast surrogate framework for radio detection of ultra high energy cosmic rays by reusing reference data.
Jocelyn: SKYSURF VIII modeling completeness data compares predictions to the Hubble Space Telescope exposure time calculator.
Subrahmanyan: That work suggests accurately assessing image source completeness is critical for interpreting telescope data measurements.
Vera: On ground calibration of the X ray gamma ray and relativistic electron detector onboard TARANIS provides validation tests for its performance.
Jocelyn: The Roman Coronagraph Community Participation Program simulates a pathfinder coronagraph instrument for high contrast demonstration.
Subrahmanyan: sgnax presents an open source pipeline for gravitational wave detector characterization delivering both matched filter and excess power searches.
Lucky paper: 2603.04586: Vera: We're diving into NEXUS Quick Release Notes from JWST here. It shows the survey structure and coverage around the North Ecliptic Pole.
Jocelyn: That survey features two tiers, a Wide tier covering about four hundred arcmin2 with six filters and WFSS spectroscopy, and a Deep tier covering about fifty arcmin2 within that.
Subrahmanyan: The target selection criteria classify objects into seven classes based on science category, with Class four objects making up the bulk of the sample at F444W less than twenty-six magnitudes.
Vera: So we have these classifications: Class zero for transients, Class one for AGNs and little red dots, and so on.
Jocelyn: The data processing releases Quick-reduction MSA spectra files under "/nirspec/fits/" along with target summary files containing MSAID, coordinates, source type, and priority class information.
Subrahmanyan: The scientific outcome is the uniform availability of spectroscopic redshifts for an unbiased flux complete galaxy sample at F444W less than twenty-six magnitudes.
Vera: That uniform redshift availability will substantially improve spectroscopic training sets for photometric redshift estimation.
Jocelyn: Deep Epoch one observed seven hundred fifty-eight objects in total, including those specific notable sources like a z = four point five two two little red-dot and a z = four point four nine six post-starburst galaxy.
Subrahmanyan: Deep Epoch three highlighted a chance alignment of a z = one point four three zero galaxy with an object at z = four point eight eight six, and also identified a dual AGN candidate with MSAID=twenty-five thousand seven hundred forty-five.
Vera: That dual AGN candidate is interesting because it shows the capabilities of this survey for time domain astrophysics and characterization of continuum variability in AGNs.
Jocelyn: The regular cadence of observations opens a new window for high redshift variability studies, allowing us to discover transients and characterize emission line variability in AGNs.
Subrahmanyan: I'm interested in the specific targets selected from the photometric catalog, particularly how those criteria for Class one objects relate to optical or NIR spectra.
Vera: That links back to how we need realistic source modeling when looking at galaxy completeness, which is something Goisman et al. touched on earlier.
Jocelyn: Does this survey structure change the way we think about what kind of science we can do with JWST in the coming years?
Subrahmanyan: It opens up a broad range of investigations spanning stellar and galaxy evolution, black hole growth, and time domain astrophysics based on these deep epoch observations.
Lucky paper: 2608.30503: Vera: So we're looking at DINOspec today. The core problem they are tackling is combining representations learned from separate vision and spectral models because they are hard to reuse and combine directly.
Jocelyn: That difficulty usually comes down to those tokenizers being optimized for the statistics of the training data, which means representations learned from different instruments don't mesh easily.
Subrahmanyan: DINOspec solves this by adopting a structure with a frozen DINOv3-Large vision backbone and a spectral branch operating on tokens from the frozen AION-one tokenizer.
Vera: And the connection between those two branches is through trainable adapters that align the visual and spectral representations using symmetric cross entropy CLIP loss.
Jocelyn: They used paired imaging and spectroscopic observations of the same astrophysical objects, specifically data from Hyper Suprime-Cam for images and Sloan Digital Sky Survey for spectra.
Subrahmanyan: That combined dataset has two hundred nine thousand six hundred thirty object spectra, with cross matched HSC and DESI objects within a one arcsecond radius to get twenty thousand four hundred seventy-two galaxies.
Vera: The key finding is that representation learning and cross modal alignment can be separated, which means independently developed foundation models can be reused.
Jocelyn: They showed improvements in morphology classification F1 score going from zero point seven two to zero point seven eight and spectral classification F1 going from zero point seven zero to zero point seven four, while the redshift prediction R2 score stayed around approximately zero point nine for AION-one baseline.
Subrahmanyan: The paper notes that alignment is most effective when modalities contain complementary information about the physical object, which is why morphology benefits most from joint training versus redshift prediction not benefiting much from it.
Vera: But the authors say that adapter-based alignment using at most seven percent of a full multimodal model parameters successfully combines independently pre trained vision and spectral models.
Jocelyn: That suggests domain specific encoders aren't always necessary because domain adaptation can happen through those alignment modules containing at most one hundred six parameters.
Subrahmanyan: The success of DINOv3 as a vision backbone implies that you don't always need custom encoders if you have strong unimodal representations already in place.
Episode: The Roman Coronagraph Community Participation Program: corgisim - a simulation suite for the Nancy Grace Roman Space Telescope Coronagraph Instrument
In short: The corgisim package is an open-source Python simulation suite developed for NASA's Roman Space Telescope Coronagraph Instrument. It allows researchers to simulate high-contrast imaging, polarimetry, and spectroscopy by modeling the entire process from astrophysical scene setup to EMCCD detector response. This tool enables pre-launch calibration, pipeline testing, and observation planning.
November 01, 2026
Episode: On-ground calibration of the X-ray, gamma-ray, and relativistic electron detector onboard TARANIS
In short: On-ground calibration of TARANIS's XGRE detector validated its performance by testing it with real hardware and flight models. This process determined energy ranges, resolution, and effective areas for X-rays, gamma rays, and electrons. The results successfully validated the simulation model used for the mission.
November 01, 2026
Episode: DINOspec: Efficient Multimodal Alignment of Vision and Spectral Foundation Models for Astronomy
In short: DINOspec combines pre-trained vision and spectral models from separate sources by using lightweight adapters to align their representations. This method improves galaxy morphology classification (F1: 0.72->0.78) while reusing existing foundation models, showing alignment is most effective when modalities offer complementary information.
November 01, 2026
Episode: SKYSURF VIII -- Modeling SKYSURF Completeness Data for Comparison to the Hubble Space Telescope Exposure Time Calculator
In short: The study modeled galaxy completeness using Hubble Space Telescope data to assess measurement accuracy. They simulated objects and fitted models for exposure time and background effects, finding that existing Exposure Time Calculators (ETC) underestimate completeness limits by 1-2 magnitudes for extended galaxies.
November 01, 2026
Episode: NEXUS: Quick Release Notes
In short: NEXUS is a JWST survey around the North Ecliptic Pole designed to facilitate follow-up studies through regular Quick Data Releases. It features a Wide tier for broad imaging and a Deep tier for detailed spectroscopy. This provides uniform spectroscopic redshifts, improving photometric redshift training sets and enabling high-redshift variability studies.
November 01, 2026
Episode: FARSim: a fast RF-chain-aware trigger-screening surrogate for radio detection of ultra-high-energy cosmic rays
In short: FARSim is a fast surrogate framework designed to rapidly screen radio detection triggers for ultra-high-energy cosmic rays without running expensive full simulations for every configuration. It reconstructs ground plane radio footprints from a reduced library using physical principles like geomagnetic and charge-excess decomposition, allowing researchers to quickly evaluate different array layouts and trigger settings.
November 01, 2026
Episode: Setting requirements on out-of-band rejection for next-generation CMB experiments. Application to the LiteBIRD instrument
In short: The study determined stringent out-of-band rejection requirements for next-generation CMB experiments like LiteBIRD by modeling instrument response and sky emissions. The analysis showed that detection chain effects, specifically increased detector noise and poor component separation, drive the most demanding requirements. The highest attenuation factors needed are for high out-of-band power (AH).
November 01, 2026
Episode: The day in conversation for 2026-10-31
October 31, 2026
Episode: Daily Summary for 2026-10-31
October 31, 2026
Episode: Environmental Noise Challenges for the Einstein Telescope - A Review
October 31, 2026
Episode: Automatic astrometric calibration of low-cost all-sky cameras
October 31, 2026
Episode: Characterization of the CSST Survey Camera CCDs: I. basic electro-optical performance
In short: This research characterized 31 flight-model Charge-Coupled Devices (CCDs) for China's Space-station Survey Telescope (CSST). It established a performance baseline, confirming that all detectors meet or exceed specifications for high sensitivity. Key findings include a full-well capacity over 80 ke− and median readout noise around 3.6 e− rms, validating their suitability for the upcoming large-area survey.
October 31, 2026
Episode: Infrasound Newtonian Noise Estimation at the Einstein Telescope Candidate Site Sos Enattos
In short: The study analyzed seasonal changes in atmospheric infrasound at Sos Enattos to estimate its impact on Newtonian noise for the Einstein Telescope. Results show that while underground deployment is necessary to keep noise below design limits, depth alone is insufficient. Controlling local sources and future laboratory equipment will be crucial for meeting detector sensitivity requirements.
October 31, 2026
Episode: Options for Compression of radio interferometry data: lossy compression of visibilities and lossless compression of uv-visibility grids for the MHONGOOSE survey
October 31, 2026
Episode: Gaussian process-based Bayesian imaging of bolometric (sub-)millimetre data
In short: The study introduces maria-nifty, a Gaussian process-based Bayesian framework for reconstructing sky maps from single-dish sub-millimeter data. It uses modular generative models to separate astronomical signals from atmospheric noise and provides uncertainty quantification. Applied to the RXJ1347 galaxy cluster, the method cleanly separates extended cluster emission from a compact source, yielding a smoother map than traditional maximum-likelihood methods.
October 31, 2026
Episode: Estimator Precision and Selection for Up-the-Ramp Sampling with a High-Read-Noise InGaAs Camera
In short: The study compares Ordinary Least Squares (OLS) and Correlated Double Sampling (CDS) estimators against Generalized Least Squares (GLS) for sampling high-read-noise InGaAs cameras. It establishes a precision criterion based on the ratio η = fT/σ2R to guide selection, showing OLS is better below η=10 and CDS above it. The work validates these rules against observed temporal covariance.
October 31, 2026
Episode: Revisiting the Unknown Unknowns in Transient Astrophysics with the SKA Telescopes
In short: The SKA telescopes will explore 'unknown unknowns' in transient astrophysics by embracing machine learning and commensal observing. This approach expands the search beyond known sources, leveraging large data volumes and multi-wavelength data to discover new transient populations and phenomena.
October 31, 2026
Episode: Community Lessons from builders of infrared multi-object spectrographs
In short: Community builders shared lessons on designing infrared multi-object spectrographs for cryogenic use, informing future instruments like MIRMOS. Key takeaways include prioritizing vibration damping for coolers, performing detailed finite element analysis for flexure compensation, and starting software development early to ensure successful on-site commissioning.
October 31, 2026
Episode: Optimization of Petal-Shaped Occulters for Exo-Earth Observation
In short: This study optimizes petal-shaped occulters for exoplanet observation by minimizing Fresnel diffraction effects. By decomposing the required transmission profile onto a basis of circular occulters, researchers found an efficient method to achieve starlight rejection better than 10^-12. The optimization involves tuning weights and radii iteratively to minimize residual stellar flux.
October 31, 2026
Episode: A design concept for the High Resolution Imager on the Habitable Worlds Observatory
October 31, 2026
Episode: Demonstrating the integration of a photonic lantern with an all-fiber-based nulling interferometer
October 31, 2026
Episode: Assessing the Predictability of delta Scuti Variable Stars for Spacecraft Navigation
October 31, 2026
Episode: In search of the third dimension in Compton X-ray polarimeters
In short: Traditional Compton polarimeters only measure azimuthal angles, ignoring scattering angle effects that cause systematic errors for off-axis sources. This work proposes reading light signals at both ends of scintillator bars to estimate the depth of interaction (DoI). This DoI information allows the AI system to constrain the scattering angle, improving event reconstruction accuracy and sensitivity.
October 31, 2026
Episode: A robust super-time-stepping scheme for Ohmic and ambipolar diffusion
In short: A new Runge-Kutta-Gegenbauer (RKG) super-time-stepping scheme was developed to explicitly integrate non-ideal MHD equations involving Ohmic and ambipolar diffusion. This method enhances robustness against strong diffusion and boundary errors, offering excellent stability for strongly diffusive regimes where traditional explicit methods fail, leading to more accurate simulations of astrophysical plasmas.
October 31, 2026
Episode: Science-driven design and performance evaluation of a Silicon Laue Component lens for hard X-ray polarimetry
In short: Researchers designed a Silicon Laue Component lens to study hard X-ray polarimetry from black holes and neutron stars in the 80–200 keV band. The design provides continuous energy coverage but struggles to maintain a high sensitivity threshold across the entire range, suggesting further material optimization is needed for full mission implementation.
October 31, 2026
Episode: A Covariance-Aware Framework for Spatially Resolved Exoplanet Biosignature Inference with the Solar Gravitational Lens
In short: The SGL mission concept is a follow-on observatory designed to provide spatially resolved and correlated spectra of a single high-priority exoplanet. The central finding is that spatially resolved spectroscopy can preserve parameter information that disk-integrated spectra lose, provided the analysis accounts for regional cloud/gas/surface covariance. This capability allows testing whether atmospheric and surface features are physically coherent on the planet.
October 31, 2026
Episode: The day in conversation for 2026-10-29
October 30, 2026
Episode: Daily Summary for 2026-10-29
October 30, 2026
Episode: The day in conversation for 2026-10-30
October 30, 2026
Episode: Daily Summary for 2026-10-30
October 30, 2026
Episode: Directional Anisotropic Sensitivity Curves for Pulsar Timing Arrays
In short: This framework converts directional Fisher information into effective sensitivity curves on a sky map to distinguish between different estimators for measuring gravitational wave background anisotropy. It allows researchers to characterize how pulsar timing arrays respond to directional signals, recover injected hotspots, and predict future array sensitivity across various mathematical bases.
October 30, 2026
Episode: HEL1OS on Aditya-L1 Mission: Operations, Data Processing and Monitoring of Sun in Hard X-rays
In short: The segment discusses a paper titled Learning nuclear mass systematics with hybrid quantum-classical mixtures of experts, focusing on how it combines quantum and classical methods to predict nuclear mass systematics. The discussion covers the model's training data, performance metrics like the 15 percent reduction in mean squared error compared to pure models, computational costs for running multiple simulations, and the limitations regarding generalization outside the training set.
October 30, 2026
Episode: Modeling Dependence Structures in Astronomical Multi-Band Time Series Data via Multi-Output Gaussian Processes
In short: The study examines three ways to model how different photometric bands vary together in astronomical time series using multi-output Gaussian processes: covariance-based, SDE-based, and latent-process approaches. The key finding is that the choice of dependence structure significantly impacts scientific interpretation; for instance, one approach is better for characterizing observed variability while another is superior for inferring physical mechanisms like reverberation mapping.
October 30, 2026
Episode: Ushering in sub-arcsecond angular resolution observatories in the far-infrared: The case for a double-Fourier interferometer
In short: The paper argues that achieving sub-arcsecond resolution in far-infrared astronomy requires a space-based double-Fourier interferometer (DFI). This technique is necessary to resolve fine structures in star formation, exoplanetary systems, and galaxies. The DFI promises an order of magnitude improvement over current ground facilities by leveraging cryocoolers and sensitive detectors.
October 30, 2026
Episode: An improvement to the spatial discretisation in the Astrophysical Weighted Particle Hydrodynamics method
In short: The study introduces new approximations for node weights and centroids in Astrophysical Weighted Particle Hydrodynamics (AWPH) to enhance spatial discretization accuracy. By deriving these approximations from Taylor-series expansions of the kernel function and support function, the authors propose a more accurate method than previously used ones. The findings suggest that while these improvements are significant for the cubature rule itself, their impact on the final physical solution depends on node clustering.
October 30, 2026
Episode: Daily Summary for 2026-10-27
October 29, 2026
Episode: The day in conversation for 2026-10-27
October 29, 2026
Episode: Daily Summary for 2026-10-27
October 29, 2026
Episode: Daily Summary for 2026-10-16
October 29, 2026
Episode: The day in conversation for 2026-10-19
October 29, 2026
Episode: Daily Summary for 2026-10-19
October 29, 2026
Episode: Daily Summary for 2026-10-20
October 29, 2026
Episode: Daily Summary for 2026-10-21
October 29, 2026
Episode: Daily Summary for 2026-10-26
October 29, 2026
Episode: The day in conversation for 2026-10-28
October 29, 2026
Episode: Daily Summary for 2026-10-28
October 29, 2026
Episode: Mock Observations for the CSST Mission: CPI-C -- Targets for High Contrast Imaging
In short: CPISM is a Python simulation program for the CPI-C instrument on CSST that generates realistic Level 0 data and synthetic observations. It simulates stellar and planetary properties, optical effects, instrumental noise, and cosmic ray artifacts to optimize target selection and observation strategies for high-contrast exoplanet imaging. The results provide a foundation for validating pipelines and planning future missions.
October 29, 2026
Episode: The day in conversation for 2026-10-14
October 28, 2026
Episode: The day in conversation for 2026-10-16
October 28, 2026
Episode: The day in conversation for 2026-10-19
October 28, 2026
Episode: The day in conversation for 2026-10-20
October 28, 2026
Episode: The day in conversation for 2026-10-21
October 28, 2026
Episode: The day in conversation for 2026-10-26
October 28, 2026