95 citations · 221 across the 5 of their papers we have counts for
7 papers · 1 filter
A new versatile method for the reconstruction of scintillator-based muon telescope events
Raphaël Bajou, Marina Rosas-Carbajal, Jacques Marteau
This paper presents a new method to process the data recorded with muon telescopes. We have developed this processing method for the plastic scintillator-based hodoscopes located a…
A multi-decadal view of the heat and mass budget of a volcano in unrest: La Soufrière de Guadeloupe (French West Indies)
David E. Jessop, Séverine Moune, Roberto Moretti +11
Particularly in the presence of a hydrothermal system, many volcanoes output large quantities of heat through the transport of water from deep within the edifice to the surface. Th…
Middle-atmosphere dynamics observed with a portable muon detector
Matias Tramontini, Marina Rosas-Carbajal, Christophe Nussbaum +2
In the past years, large particle-physics experiments have shown that muon rate variations detected in underground laboratories are sensitive to regional, middle-atmosphere tempera…
Abrupt changes of hydrothermal activity in a lava dome detected by combined seismic and muon monitoring
Y. Le Gonidec, M. Rosas-Carbajal, J. de Bremond d'Ars +5
The recent 2014 eruption of the Ontake volcano in Japan recalled that hydrothermal fields of moderately active volcanoes have an unpredictable and hazardous behavior that may endan…
Three-dimensional density structure of La Soufrieère de Guadeloupe lava dome from simultaneous muon radiographies and gravity data
Marina Rosas-Carbajal, Kevin Jourde, Jacques Marteau +3
Muon imaging has recently emerged as a powerful method to complement standard geophysical tools in the understanding of the Earth's subsurface. Muon measurements can yield a radiog…
Two-dimensional probabilistic inversion of plane-wave electromagnetic data: Methodology, model constraints and joint inversion with electrical resistivity data
M. Rosas-Carbajal, N. Linde, T. Kalscheuer +1
Probabilistic inversion methods based on Markov chain Monte Carlo (MCMC) simulation are well suited to quantify parameter and model uncertainty of nonlinear inverse problems. Yet,…