Lyte Lab

Applied AI research on local hardware. Geophysics, materials science, and structural reasoning — from Austin, TX.

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4 active projects
All results derived from public sources

Cascadia Slow-Slip Events

Nine events analyzed from 2010–2023 using tremor catalogs (PNSN) and strainmeter data (UNAVCO/EarthScope). Each row shows one event's precursor trajectory metrics.

Slow-Slip Event Trajectories

Event Lead Time Approach Corr Max Distance Drift Rate / Day Signal
Cascadia 2010 Summer 17 days +0.750 1.256 0.044 Strong
Cascadia 2011 Summer 17 days +0.641 1.284 0.041 Strong
Cascadia 2012 Summer 13 days +0.569 1.190 0.035 Strong
Cascadia 2013 Fall 17 days −0.336 1.482 −0.028 Weak
Cascadia 2014 Fall 16 days +0.848 1.011 0.037 Strong
Cascadia 2015–16 Winter 17 days +0.838 3.016 0.161 Strong
Cascadia 2017 Winter 17 days +0.637 1.191 0.044 Strong
Cascadia 2022 Winter 16 days +0.572 1.623 0.054 Strong
Cascadia 2023 Summer 13 days −0.611 1.839 −0.030 Weak

Approach correlation measures monotonic signal increase toward event onset. Positive = precursor detected. Data: PNSN tremor catalogs, UNAVCO strainmeter network. 14-day sliding windows.

Hurricane Landfall Precursors

Eight CONUS hurricane landfalls (2000–2024) analyzed against matched controls. ERA5 reanalysis, 500 hPa geopotential height. Each event paired with a same-location, same-calendar-date control year with no storm.

Hurricane vs. Control Signal Separation

Storm Year Cat Min Pressure Event Corr Control Corr Precursor
Lili 2002 1 963 hPa −0.001 +0.457 No
Emily 2005 3 944 hPa +0.522 −0.329 Yes
Ike 2008 2 950 hPa +0.476 −0.027 Yes
Isaac 2012 1 967 hPa +0.101 −0.297 Yes
Matthew 2016 1 967 hPa −0.093 −0.223 No
Dorian 2019 2 956 hPa +0.641 −0.280 Yes
Ida 2021 4 931 hPa +0.002 +0.110 No
Helene 2024 4 939 hPa +0.518 −0.163 Yes

Approach correlation: Pearson r between day-offset and distance-from-baseline over 30 pre-landfall days. Positive event correlation + negative control = precursor signal. Data: ERA5 reanalysis (ECMWF), HURDAT2 (NHC). Pilot study — 8 events.

Volcanic Monitoring Data Sources

Public data streams we plan to analyze for multi-modal eruption precursor detection. All freely available, spanning decades of observations at well-monitored volcanoes.

Target Data Streams for Volcanic Analysis

Modality Source Instrument / Satellite Cadence Coverage
Seismic Tremor USGS / IRIS Broadband seismometers Continuous Kilauea, St. Helens, Rainier, +160 monitored
Ground Deformation ESA Copernicus Sentinel-1 SAR 6–12 days Global, cm-precision InSAR
SO₂ Emissions NASA / ESA OMI, TROPOMI Daily Global column SO₂
Thermal Anomaly NASA MODIS, VIIRS 2–4x daily Global, sub-km resolution
GPS Displacement EarthScope (UNAVCO) Continuous GPS Continuous Major US volcanoes

Research direction — analysis not yet complete. Starting with Kilauea (2018 lower East Rift Zone eruption) as the best-monitored first case.

We believe AI should run on hardware you own, cost nothing per query, and get smarter every day. Our research runs on Apple Silicon in Austin. No cloud. No API calls. No per-token fees.

Working on geophysics, materials science, or structural reasoning? We'd like to hear from you.