Speaker
Description
Reliable earthquake forecasting remains limited by sparse and indirect observables, and by the difficulty of accessing stress evolution at seismogenic depths. Many proposed electromagnetic precursor methods rely on detecting signals after they propagate out of the Earth crust, where attenuation, scattering, and environmental noise complicate detection and signal interpretation. We propose ERMES (Earthquake Reconnaissance using Muon beam Evolution in Silicon dioxide) [1] as an active probing technique that targets the source region directly, measuring stress-linked fields in situ rather than inferring them from far-field emissions.
ERMES interrogates quartz-rich rocks around a known active fault using a collimated, high-energy muon beam. Tectonic stress induces piezoelectric electric fields within quartz fabrics; these near-field structures act on traversing muons and imprint stress information onto the beam transverse phase space (for example centroid shift and angular spread) measurable at an exit detector. Kilometer-scale penetration requires TeV-class muons: transport studies indicate that a 10 TeV beam can traverse about 3 km of crystalline rock while retaining analyzable phase-space signatures. To strengthen post-target diagnostics, we introduce a compact muonic lens concept to refocus and condition the transmitted beam before measurement, improving sensitivity to small stress-driven perturbations. Because this regime involves extremely thick targets where secondary production and energy-loss straggling matter, we cross-validated long-baseline transport and background predictions using independent Monte Carlo toolchains (FLUKA and Geant4). We also define a proof-of-principle path at existing facilities, using GeV-class muons through stressed granite slabs and a zero-generation surrogate test with 20-150 MeV electrons through single quartz crystals under controlled compressive load.
By enabling continuous, active monitoring of tectonic stress evolution at depth, ERMES could provide earlier and more reliable precursor observables to support seismic hazard assessment and civil-protection decision timelines.
[1] (Physical Review Research 7, 043336)