Inferring Meteoroid Properties with Dynamic Nested Sampling: A Case Study of Orionid and Capricornid Shower Meteors

TL;DR

This work introduces a fully automated Bayesian framework that uses Dynamic Nested Sampling to invert an erosion-fragmentation meteoroid model from simultaneous EMCCD luminosity measurements and CAMO deceleration data. Validation with synthetic meteors confirms robust recovery of input parameters and uncertainties, and application to 15 real meteors (9 Orionids, 6 Capricornids) yields posterior distributions for mass, bulk density, and fragmentation behavior. Orionids cluster around low bulk densities ($\sim$159 kg/m^3) consistent with porous cometary material, while Capricornids are denser on average ($\sim$333 kg/m^3) with indications of a second, higher-density component near $\sim$1300 kg/m^3, aligning with more cohesive fragments. Sensitivity analyses show luminous efficiency $\tau$ is a dominant fixed-parameter influence on inferred densities, underscoring the need for accurate $\tau$ constraints. Overall, the method provides rigorous, automated characterization of meteoroid properties and is scalable to larger shower and sporadic meteor samples across orbital classes, enhancing risk assessment for spacecraft and enabling detailed compositional inferences across meteor populations.

Abstract

Accurate estimation of meteoroid bulk density is crucial for assessing spacecraft impact hazards from sub-millimeter to millimeter-sized meteoroids. Previous studies often used manual tuning or optimization methods to fit ablation and fragmentation models to optical meteor data, but subjective choices made physical properties and uncertainties difficult to compare. We develop a global, statistically robust method that uses Dynamic Nested Sampling to fit an erosion-fragmentation model to meteor light curves and deceleration measured by the Canadian Automated Meteor Observatory (CAMO) mirror tracking system and Electron-Multiplied CCD (EMCCD) cameras. Applied to 15 shower meteors, the method returns posterior distributions and Bayesian evidences for single- and double-fragmentation scenarios. Tests on four synthetic cases recover the known inputs, with best-guess solutions matching the true parameters. For 9 Orionids and 6 Alpha Capricornids with masses 1e-6 to 1e-5 kg, the median bulk density is 159 (+558/-57) kg/m3 for Orionids and 333 (+1089/-114) kg/m3 for Alpha Capricornids. Orionids are consistent with low-density cometary material, while Alpha Capricornids are systematically denser and show a second density cluster near 1300 kg/m3, consistent with higher-density asteroidal material. This framework enables automated, statistically rigorous characterization of meteoroid properties and will be extended to larger samples of shower and sporadic meteors across orbital classes.

Figures (53)

• Figure 1: On the left is shown two EMCCD cameras (02G, 02F) at Elginfield observatory positioned at 70$^{\circ}$ and 40$^{\circ}$ elevations. On the middle, the window below which the narrow-field CAMO camera (02T) at Elginfield observatory is shown. The image on the right shows the map where the cameras are located and the meteor trail of a detected meteor.
• Figure 2: Smearing effect for an EMCCD recorded Orionid meteor. The dashed gray line shows the raw simulation, while the solid black line includes temporal integration over 0.03125 seconds. The top panels display real EMCCD data (left) detected by camera 02G with the chosen leading edge pick point as a red cross and the simulated integrated trail (right). Integration shifts the peak and smooths the light curve.
• Figure 3: Effect of temporal integration on a CAP simulation. The integrated and raw simulations are nearly identical, reflecting the lower velocity and reduced smearing of the CAP meteor.
• Figure 4: Scatter plot of apparent meteor magnitude vs. SNR for three meteors, each observed by two cameras (six datasets total). Note that the X axis is in log scale. Each color indicates a separate meteor-camera pair - the designations indicate observations from different sites (01 - Tavistock; 02 - Elginfield), the camera pair (F - high altitude pointing, G lower altitude pointing cameras) followed by the date and time of the recorded event. The dashed black line (slope $m=1$) is the best-fit relation for CAP data, used to assign an initial noise estimate for the first detection frames. The systematic scatter above and below the ideal line reflects variations in real-world observing conditions.
• Figure 5: Top: The lag of a Capricornid meteor (points) and the dervied fit (black) with annotated time t$_0$. Each color indicates measurements from a separate camera. Bottom: Fit residuals and a histogram of residuals.