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<article language="en">
	<journal>
		<journal_title>Solid Earth Discussions</journal_title>
		<journal_url>www.solid-earth-discuss.net</journal_url>
		<eissn>1869-9537</eissn>
		<volume_number>2</volume_number>
		<issue_number>1</issue_number>
		<publication_year>2010</publication_year>
	</journal>
	<doi>10.5194/sed-2-43-2010</doi>
	<article_url>http://www.solid-earth-discuss.net/2/43/2010/</article_url>
	<abstract_html>http://www.solid-earth-discuss.net/2/43/2010/sed-2-43-2010.html</abstract_html>
	<fulltext_pdf>http://www.solid-earth-discuss.net/2/43/2010/sed-2-43-2010.pdf</fulltext_pdf>
	<start_page>43</start_page>
	<end_page>67</end_page>
	<publication_date>2010-03-04</publication_date>
	<article_title content_type="html">The stochastic quantization method and its application to the numerical simulation of volcanic conduit dynamics under random  conditions</article_title>
	<authors>
		<author numeration="1" affiliations="1,4">
			<name>E. Peruzzo</name>
			<email>e.peruzzo@sns.it</email>
		</author>
		<author numeration="2" affiliations="2">
			<name>M. Barsanti</name>
		</author>
		<author numeration="3" affiliations="2">
			<name>F. Flandoli</name>
		</author>
		<author numeration="4" affiliations="3">
			<name>P. Papale</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126,     Pisa, Italy</affiliation>
		<affiliation numeration="2" content_type="html">Dipartimento di Matematica Applicata,     Università di Pisa, Via Buonarroti 1c, 56127, Pisa, Italy</affiliation>
		<affiliation numeration="3" content_type="html">Istituto Nazionale di Geofisica e Vulcanologia, Sezione di     Pisa, Via della Faggiola 32, 56126, Pisa, Italy</affiliation>
		<affiliation numeration="4" content_type="html">Invited contribution by E. Peruzzo, one of the EGU  Young Scientists Outstanding Poster Paper (YSOPP) Award winners 2009.</affiliation>
	</affiliations>
	<abstract content_type="html">Stochastic Quantization (SQ) is a method for the approximation of a
  continuous probability distribution with a discrete one. The
  proposal made in this paper is to apply this technique to reduce the
  number of numerical simulations for systems with uncertain inputs,
  when estimates of the output distribution are needed. This question
  is relevant in volcanology, where realistic simulations are very
  expensive and uncertainty is always present. We show the results of
  a benchmark test based on a one-dimensional steady model of magma
  flow in a volcanic conduit.</abstract>
	<references>
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</article>

