Electronic Resource

Detection of Mars Normal Modes From S1222a Event and Seismic Hum

التفاصيل البيبلوغرافية
العنوان: Detection of Mars Normal Modes From S1222a Event and Seismic Hum
المؤلفون: Agence Nationale de la Recherche (France), Lognonné, Philippe, Schimmel, Martin, Stutzmann, Eleonore, Davis, P., Drilleau, M., Sainton, G., Kawamura, T., Panning, M.P., Banerdt, W. B.
بيانات النشر: American Geophysical Union 2023
نوع الوثيقة: Electronic Resource
مستخلص: We present the first detection of normal modes on Mars using the vertical records from InSight's broad-band seismometer following the marsquake that occurred on sol 1222. The proposed catalog lists 60 potential eigenfrequencies between 3 and 12 mHz. Due to their low signal-to-noise ratio, these normal modes were detected using the phasor walkout approach. The normal modes amplitudes are consistent with the upper limit of the S1222a magnitude and with high quality factors. Additionally, we provide the first detection of a Martian hum before the quake for several of these frequencies. The proposed frequencies are at about 1-sigma of those predicted by published models based on body wave travel time inversions. Our detection of normal modes is the first made on a terrestrial planet other than Earth and opens the way for future interior models that incorporate both normal modes frequencies, surface waves velocities and body wave travel times.
مصطلحات الفهرس: Evidence of free oscillations excited by a seismic event and background oscillations on Mars, low signal-to-noise ratio seismic record, phasor walkout analysis, Normal mode frequencies can be used to narrow down published Mars interior models obtained from body wave travel time inversions, artículo
URL: http://hdl.handle.net/10261/347907
Publisher's version
http://dx.doi.org/10.1029/2023GL103205
Sí
الاتاحة: Open access content. Open access content
https://creativecommons.org/licenses/by-nc-nd/4.0
openAccess
Other Numbers: CTK oai:digital.csic.es:10261/347907
Geophysical Research Letters, 50(12): e2023GL103205 (2023)
1431962731
المصدر المساهم: CSIC
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رقم الانضمام: edsoai.on1431962731
قاعدة البيانات: OAIster