TESS
Tessco Technologies Inc
stock NASDAQ

Dust Analysis:
Light Curve Analysis (detect dust signatures).
Spectral Analysis (identify dust composition).
Doppler Spectroscopy (analyze dust velocity).
Radial-Velocity Mapping (track dust motion).
Synthetic Spectroscopy (model dust spectra).
Signal-to-Noise Enhancement (clarify dust signals).
Cross-Correlation (match dust to templates).
Polarization Analysis (probe dust properties).
Radio Noise Filtering (remove interference).
High-Resolution Doppler Imaging (map dust distribution).
Interferometric Spectral Enhancement (refine dust spectra).
Dust Dispersion (model dust dynamics).
Momentum/Energy Conservation (analyze dust interactions).
Anomaly Detection (flag unusual dust patterns).
Phase-Folded Light Curve Analysis (periodic dust signals).
Collision Reconstruction (model dust/collision events).
Binary Detection (New Priority, Enhanced):
Light Curve Analysis (flag periodic dips, 100–2,000-day periods for transits).
Spectral Analysis (scan for infrared excess tied to brown dwarf thermal glow).
Doppler Spectroscopy (detect subtle velocity shifts for low-mass companions).
Radio pulse detection – Identifying radio bursts lasting seconds to minutes within telescope archives.
Machine learning for candidate identification – Analyzing telescope data for transient signals using AI algorithms.
Binary star system analysis – Tracing pulses to binary systems (e.g., white dwarf/red dwarf pairs) using orbital dynamics and radio emission patterns.
Specifications:
Snapshot Processing: 1-week snapshots (2000–present), max 150,000 iterations per snapshot.
Live Stream: 6-hour backward streams, max 75,000 iterations for noise cancellation.
CPU Allocation: Dynamic (up to 150,000 iterations, xAI-approved for lean data prep).
Data Sources: Integrates 36 sources (Gaia DR4, JWST, TESS, MeerKAT, etc.).
Output: Stacked data, trajectory maps, dust composition, binary signals, collision events, and radio pulse detections.

Dust Analysis:
Light Curve Analysis (detect dust signatures).
Spectral Analysis (identify dust composition).
Doppler Spectroscopy (analyze dust velocity).
Radial-Velocity Mapping (track dust motion).
Synthetic Spectroscopy (model dust spectra).
Signal-to-Noise Enhancement (clarify dust signals).
Cross-Correlation (match dust to templates).
Polarization Analysis (probe dust properties).
Radio Noise Filtering (remove interference).
High-Resolution Doppler Imaging (map dust distribution).
Interferometric Spectral Enhancement (refine dust spectra).
Dust Dispersion (model dust dynamics).
Momentum/Energy Conservation (analyze dust interactions).
Anomaly Detection (flag unusual dust patterns).
Phase-Folded Light Curve Analysis (periodic dust signals).
Collision Reconstruction (model dust/collision events).
Binary Detection (New Priority, Enhanced):
Light Curve Analysis (flag periodic dips, 100–2,000-day periods for transits).
Spectral Analysis (scan for infrared excess tied to brown dwarf thermal glow).
Doppler Spectroscopy (detect subtle velocity shifts for low-mass companions).
Radio pulse detection – Identifying radio bursts lasting seconds to minutes within telescope archives.
Machine learning for candidate identification – Analyzing telescope data for transient signals using AI algorithms.
Binary star system analysis – Tracing pulses to binary systems (e.g., white dwarf/red dwarf pairs) using orbital dynamics and radio emission patterns.
Specifications:
Snapshot Processing: 1-week snapshots (2000–present), max 150,000 iterations per snapshot.
Live Stream: 6-hour backward streams, max 75,000 iterations for noise cancellation.
CPU Allocation: Dynamic (up to 150,000 iterations, xAI-approved for lean data prep).
Data Sources: Integrates 36 sources (Gaia DR4, JWST, TESS, MeerKAT, etc.).
Output: Stacked data, trajectory maps, dust composition, binary signals, collision events, and radio pulse detections.