Anahata : The Unheared Resonance

Figure 2.1: Anahata logo

Figure 2.2: Anahata logo created using open source Blender 3D

AnahatA is an open-source journey, a convergence of the stars and sound, where real stellar data, the mathematics of music theory, and immersive 3D visualizations come together in one interactive space, built upon our custom Astral engine. At its heart, AnahatA is a question: What does it mean to truly listen to the stars not as a metaphor but as music? We draw from the depths of space data gathered by missions like TESS, Kepler, Gaia, and JWST. Each point of light is not an abstract pixel, but a real celestial body, with motion, magnitude, and memory. From their oscillations subtle tremors of light and gravity we uncover frequencies born from within and of extrinsic origin. These are not merely stars. They are storytellers. Through the lens of music theory, we begin to translate the language of the universe using scales, intervals, and harmonics to turn patterns of light into patterns of sound. Each stellar system becomes a melody, each motion a rhythm cosmic music shaped by the laws of both physics and harmony. AnahatA is a space to explore. To drift among the stars, follow the pulse of a distant sun, or tune into a harmony that’s been echoing for eons. And because it’s open-source, you’re free to build, reshape, and expand your own version of the cosmos. AnahatA is a connection - Between light and sound, science and soul, the known and the unspoken. Something ancient, something future. Something we’ve always longed to hear. A grief for something we’ve lost without knowing when: The awe, the silence, the feeling that we are part of something immense, unknowable, and deeply, beautifully ordered. AnahatA - the unheard eternal resonance within all things.

CMAP: Cluster Membership Analysis Program

Figure 1.1: CMAP Module User Interface

Figure 1.2:

This project introduces CMAP, a powerful new tool designed to discover and analyze open star clusters within the Milky Way's most crowded stellar regions. Utilizing data from the Gaia mission, CMAP employs cutting-edge machine learning and statistical modeling to accurately identify individual cluster members, even in dense star fields where traditional methods struggle. CMAP connects directly to the Gaia database, enabling it to extract potential cluster members within a specified search radius. At its core, CMAP leverages advanced Gaussian Mixture Models (GMMs) combined with Bayesian inference and a Dirichlet process prior. This sophisticated approach ensures robust determination of key clustering parameters, leading to highly reliable member identification. Our tool can analyze cluster memberships in both 5-parameter astrometric space (right ascension, declination, proper motions in RA and Dec, and parallax) and 6-parameter space by incorporating Gaia DR3's precise radial velocity measurements. CMAP also handles the estimation of a cluster's astrometric parameters and its distance based on the most probable members. Furthermore, CMAP features an integrated isochrone module that connects with the MESA Isochrones and Stellar Tracks(MIST) library. This allows for efficient isochrone fitting using the identified cluster members, providing crucial estimates for a cluster's age and distance. The fitting module is parallelized for rapid and reliable computations. We are rigorously testing CMAP's effectiveness across a wide range of open clusters, including those nestled in dense fields and those far above the galactic disk. The distance estimates derived from our isochrone models will be carefully benchmarked against those obtained from member parallax measurements. We are confident that CMAP will revolutionize our ability to explore Gaia data, helping us discover old, distant, and previously hidden open clusters throughout our galaxy.

Legolas: Advanced Eclipse Timing Analysis for Binary Star Research

Figure 3.1: Derived ephomerides from TESS Observation of an HW Vir

Figure 3.2: Eclipse timeing calculation

Legolas is our powerful tool for the precise analysis of eclipse timings in binary star systems. It is specifically developed for the astronomical community working with: Eclipsing binaries of all types. Hot binaries, where precise timing is often critical for understanding their evolution and properties. Researchers analyzing data from space missions like TESS and Kepler, which provide vast amounts of photometric data ideal for eclipse timing. Ground-based observers who require exceptionally precise primary and secondary eclipse timings for follow-up observations and accurate ephemeris generation. Scientists engaged in binary modeling, who need robust and accurate eclipse parameters to constrain their theoretical models. Legolas automates the detection of eclipses using sophisticated deterministic algorithms, meticulously optimizing clipped events to ensure accuracy. Once identified, each eclipse is fitted with a hyperbolic model to precisely estimate its mid-point, from which we derive highly accurate ephemerides. These refined parameters are crucial for successfully observing companion objects and understanding the complex dynamics of various eclipsing binaries. Legolas also leverages O-C (Observed minus Calculated) analysis, which is vital for detecting subtle variations in eclipse timings. These variations can point to extrinsic origins, such as the gravitational influence of unseen tertiary companions or other astrophysical phenomena. The tool is designed to extract and analyze both primary and secondary eclipses, if present, and calculates O-C values for both. Additionally, Legolas includes a dedicated module for calculating light-travel time effects (Roemer delay), helping to further unravel the complex orbital mechanics within these systems. With its robust algorithms and comprehensive analysis capabilities, Legolas provides the precision and reliability required by experts in binary star astronomy to advance their research.

Introducing AnahatA: The Unheard Resonance