--- title: GWOSC Event Portal url: https://www.emergentmind.com/topics/gwosc-event-portal type: topic --- # GWOSC Event Portal The GWOSC Event Portal is a publicly accessible web application designed to facilitate the galaxy-targeted electromagnetic follow-up of gravitational wave (GW) events detected by detectors such as LIGO and Virgo. The portal addresses the central challenge of multi-messenger astronomy—efficient detection and characterization of decaying transients within the large localization regions typical for GW events—by integrating rapid probabilistic ranking of galaxy hosts, observability constraints, and a user-friendly interface for target selection and data access. ## 1. Functional Overview and Web Application Features The GWOSC Event Portal provides an interactive interface for astronomers to retrieve, filter, and download ranked lists of galaxy targets most likely to host a detected GW event. Users can select the gravitational wave event and specify the desired containment probability for the localization region (e.g., 99%, 90%, or 50%). The interface visualizes the selected galaxies and GW localization contours on an interactive map. Further filtering is available based on observability at user-specified coordinates and times, calculated using the astroplan package. An additional detectability option allows users to determine, for each candidate, whether a kilonova of assumed minimum brightness ($M_{\text{kn,min}} = -17$) would be observable at that distance, indicated by a dedicated table column. The system is designed to deliver these features rapidly to any modern HTML5-compatible web browser, requiring no installation and supporting public, immediate access for community follow-up campaigns [1912.07304]. ## 2. Algorithmic Framework for Galaxy Ranking The core backend algorithm executes galaxy crossmatching and prioritization in response to GW triggers: - **Galaxy Sample Selection**: The process begins by filtering the GLADE V2 galaxy catalogue to include only galaxies within both the 99% sky localization region (as defined by the LIGO/Virgo probability sky map) and a distance window spanning $\text{DISTMEAN} \pm 5\cdot \text{DISTSTD}$, where $\text{DISTMEAN}$ and $\text{DISTSTD}$ are the mean and standard deviation of the GW source distance estimates. - **Probability Scoring**: Every candidate galaxy is evaluated using a composite probability score $S$: - *Localization Probability ($S_{\text{loc}}$)*: The product of the GW sky map pixel probability $p_{\text{loc}}$ and a Gaussian distance probability $p_{\text{dist}}$ centered at $\mu_{\text{dist}}$ with spread $\sigma_{\text{dist}}$, $$ p_{\text{dist}} = N_{\text{dist}} \cdot \exp\left( -\frac{(D - \mu_{\text{dist}})^2}{2\sigma_{\text{dist}}^2} \right). $$ - *Luminosity Weight ($S_{\text{lum}}$)*: The B-band luminosity of the galaxy, derived from apparent magnitude and distance, normalized by the sum over the candidate sample, $$ S_{\text{lum}} = \frac{L_B}{\Sigma L_B}. $$ - *Overall Ranking*: The final score is the product of these components, normalized so that $\sum S = 1$ across all selected galaxies: $$ S = S_{\text{loc}} \cdot S_{\text{lum}} = (p_{\text{loc}} \cdot p_{\text{dist}}) \cdot S_{\text{lum}}. $$ Probabilities are summarily normalized after computation, and only the top 100 entries by rank are retained for display and export [1912.07304]. ## 3. Execution Performance and Automated Operations The algorithm has been validated on events from LIGO/Virgo O3 and earlier observing runs. Typical execution times for producing a ranked catalog are 20–30 seconds, influenced primarily by FITS file size and network conditions. Subsequent static database upload to Amazon S3 and update of the Heroku-hosted website require an additional $\sim$360 seconds. Profiling via Python’s cProfile module has demonstrated significant performance improvements with version V1 of the algorithm, notably by confining processing to the highest-probability sky regions and adjusting distance cuts. These optimizations minimize runtime and risk of missing high-priority targets. The backend is triggered automatically in response to GW triggers during observing runs, enabling near real-time updating of target lists for community observers [1912.07304]. ## 4. Technical Architecture and Platform Integration The system is implemented entirely in Python using the Flask web framework. Major architectural components include: - **Back-End Services**: Galaxy retrieval and scoring logic using ligo.skymap for sky map manipulation and crossmatching, pandas for data operations, and astroplan for observing window calculations. - **Data Storage**: Ranked galaxy lists are stored in a PostgreSQL database hosted on Amazon S3. - **Front-End Delivery**: Interactive tables and maps are rendered via the Flask web server hosted on Heroku. Integration with Aladin DSS enables side-by-side astronomical image visualization. - **Alert Handling**: The pyGCN package allows for real-time ingestion of GW triggers via NASA’s Gamma-ray Coordinates Network (GCN). All functionalities are accessible via the public URL gwtool.watchertelescope.ie [1912.07304]. ## 5. User Interaction and Data Utilization Users interact with the GWOSC Event Portal through a browser-based interface. The workflow includes: 1. Selection of GW event and localization probability threshold. 2. Optional filtering by observatory location, time, and limiting magnitude/observability. 3. Extraction and visualization of the ranked galaxy sample, including names, coordinates, distances, B-band magnitudes, ranking scores, and images. 4. Download of result tables in JSON or ASCII formats for use in follow-up scheduling and observation planning. The user interface is optimized for rapid public access, intentionally limiting dynamic tables to 100 entries for responsiveness but allowing full catalogue exports when required [1912.07304]. ## 6. Planned Enhancements and Future Prospects Planned enhancements for the GWOSC Event Portal include integration of advanced scheduling and tiling algorithms to optimize follow-up coverage, migration to private server infrastructure to reduce database update latency, and refinement of the spatial selection methodology to employ the full three-dimensional localization credible volume rather than two-dimensional projections with distance limits. Such improvements are expected to increase the speed, fidelity, and scientific return of coordinated multi-messenger observations in future GW observing runs, particularly by strengthening the coupling between real-time GW alerts and electromagnetic follow-up infrastructure [1912.07304]. Source: https://www.emergentmind.com/topics/gwosc-event-portal