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A new inversion algorithm (PyMDS) based on the Pyro library to use chlorine 36 data as a aleoseismological tool on normal fault scarps

Paleoseismology (study of earthquakes that occurred before records were kept and before instruments can record them) provides useful information such as recurrence periods and slip rate to assess seismic hazard and better understand fault mechanisms. Chlorine 36 is one of the paleoseismological tools that can be used to date scarp exhumation associated with earthquakes events.
We propose an algorithm, PyMDS, that uses chlorine 36 data sampled on a fault scarp to retrieve seismic sequences (age and slip associated to each earthquake) and long term slip rate on a normal fault.
We show that the algorithm, based on Hamiltonian kernels, can successfully retrieve earthquakes and long term slip rate on a synthetic dataset. The precision on the ages can vary between few thousand years for old earthquakes (>5000 yr BP) and down to few hundreds of years for the most recent ones (

Ketersediaan
225551.136Perpustakaan BIG (Eksternal Harddisk)Tersedia
Informasi Detail
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Penerbit
Amsterdam : Elsevier.,
Deskripsi Fisik
7 hlm PDF, 3.302 KB
Bahasa
Inggris
ISBN/ISSN
2590-1974
Klasifikasi
551.136
Tipe Isi
text
Tipe Media
-
Tipe Pembawa
-
Edisi
Vol.25, February 2025
Subjek
Modelling
Paleoseismology
Python
Cosmogenic nuclides
36Cl
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • A new inversion algorithm (PyMDS) based on the Pyro library to use chlorine 36 data as a aleoseismological tool on normal fault scarps
    Paleoseismology (study of earthquakes that occurred before records were kept and before instruments can record them) provides useful information such as recurrence periods and slip rate to assess seismic hazard and better understand fault mechanisms. Chlorine 36 is one of the paleoseismological tools that can be used to date scarp exhumation associated with earthquakes events. We propose an algorithm, PyMDS, that uses chlorine 36 data sampled on a fault scarp to retrieve seismic sequences (age and slip associated to each earthquake) and long term slip rate on a normal fault. We show that the algorithm, based on Hamiltonian kernels, can successfully retrieve earthquakes and long term slip rate on a synthetic dataset. The precision on the ages can vary between few thousand years for old earthquakes (>5000 yr BP) and down to few hundreds of years for the most recent ones (
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