Habitable Worlds Observatory Simulations with 60m Starshades Demonstrate Exoplanet Imaging Throughput at 500-1000nm

Simulating the detection of Earth-like exoplanets presents a significant computational challenge, yet is crucial for designing future missions like the Habitable Worlds Observatory. Jamila S. Taaki from the Michigan Institute for Data Science, alongside Farzad Kamalabadi and Athol J. Kemball from the University of Illinois at Urbana-Champaign, and colleagues, now present a new method for efficiently simulating the imaging performance of starshades, devices designed to block starlight and reveal orbiting planets. Their work focuses on accurately modelling core throughput, a key measure of a telescope’s light-gathering ability, and demonstrates how a 60-metre starshade paired with a segmented telescope can achieve optimal performance. By implementing a novel Fourier sampling technique, the Bluestein Fast Fourier Transform, within their open-source PyStarshade package, the team significantly reduces computational demands, paving the way for more detailed and realistic simulations of exoplanet detection.

Starshade Simulation, Diffraction and Polarization Modeling

Scientists are developing detailed computational models to simulate starshade missions, a promising technique for directly imaging exoplanets. Starshades function as external screens that block starlight, allowing the faint light from orbiting planets to be observed. Accurately simulating these missions presents a significant computational challenge, requiring precise modeling of how light diffracts, polarizes, and is affected by imperfections in the optical system. The Angular Spectrum Method propagates light waves through optical systems, while the Finite-Difference Time-Domain method numerically solves equations governing light’s interaction with complex structures. Researchers also investigate methods for modeling aberrations, imperfections in optical systems that distort the wavefront, and utilize post-processing techniques to enhance planet signals. The team utilizes PyStarshade, a Python-based simulation tool, alongside commercial software.

A key focus is evaluating the trade-off between accuracy and computational cost, as more accurate methods often require significantly more processing power. The methods are validated against analytical results or experimental data to ensure reliability, and scalability is crucial for modeling realistic mission scenarios. Researchers also analyze potential sources of error in the simulations to understand their impact on the results. This work addresses the need for detailed characterization of starshade performance, particularly concerning core throughput with segmented and obscured telescope apertures, a critical factor for hybrid mission designs. This advancement enabled high-fidelity simulations of core throughput, a measure of light intensity in the central core of a planet-like source’s point-spread-function. The study focused on a 60-meter starshade, simulating its performance with both segmented and obscured telescope apertures. Results demonstrate that a segmented off-axis telescope aperture achieves an optimal core throughput of 68 percent, measured within a photometric aperture, while an additionally obscured aperture yields 66 percent throughput. These findings are significant because core throughput directly influences exposure times and predicted exoplanet yield, thereby impacting overall mission design and efficiency. The team implemented these methods within PyStarshade, an open-source Python package offering flexible diffraction tools and imaging simulations for starshades.

Starshade Performance Yields 68 Percent Throughput

Scientists have achieved a breakthrough in simulating the performance of starshades, external screens designed to suppress starlight and enable direct imaging of exoplanets. Researchers developed a detailed optical model of a starshade and performed simulations to characterize its performance with segmented and obscured telescope apertures. The team measured core throughput, a critical metric defining exposure time and potential exoplanetary yield, within a photometric aperture.

Results demonstrate an optimal core throughput of 68 percent is achievable using a segmented off-axis telescope aperture, and with an additionally obscured aperture, the core throughput remains high, reaching 66 percent. Scientists developed a sophisticated optical model to accurately predict the performance of a 60-meter starshade in blocking starlight and enhancing the visibility of orbiting planets. The simulations demonstrate that a starshade paired with a segmented off-axis telescope can achieve a core throughput of 68 percent, a key metric for efficient exoplanet detection, even with obscured apertures achieving 66 percent throughput.

Researchers validated the model by simulating solar system imaging at various inclinations, providing realistic predictions of the telescope’s ability to detect faint signals from distant worlds. This work establishes a robust framework for evaluating starshade designs and optimizing future missions aimed at characterizing potentially habitable exoplanets. The open-source Python package, PyStarshade, developed as part of this work, will facilitate further investigation and development in this field.