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<titleInfo><title>Modeling of chemical reaction systems with detailed balance using gradient structures</title></titleInfo>


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<name type="personal">
  <namePart type="given">Jan</namePart>
  <namePart type="family">Maas</namePart>
  <role><roleTerm type="text">author</roleTerm> </role><identifier type="local">4C5696CE-F248-11E8-B48F-1D18A9856A87</identifier><description xsi:type="identifierDefinition" type="orcid">0000-0002-0845-1338</description></name>
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  <namePart type="given">Alexander</namePart>
  <namePart type="family">Mielke</namePart>
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  <identifier type="local">JaMa</identifier>
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  <namePart>Optimal Transport and Stochastic Dynamics</namePart>
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<name type="corporate">
  <namePart>Taming Complexity in Partial Differential Systems</namePart>
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<abstract lang="eng">We consider various modeling levels for spatially homogeneous chemical reaction systems, namely the chemical master equation, the chemical Langevin dynamics, and the reaction-rate equation. Throughout we restrict our study to the case where the microscopic system satisfies the detailed-balance condition. The latter allows us to enrich the systems with a gradient structure, i.e. the evolution is given by a gradient-flow equation. We present the arising links between the associated gradient structures that are driven by the relative entropy of the detailed-balance steady state. The limit of large volumes is studied in the sense of evolutionary Γ-convergence of gradient flows. Moreover, we use the gradient structures to derive hybrid models for coupling different modeling levels.</abstract>

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<originInfo><publisher>Springer Nature</publisher><dateIssued encoding="w3cdtf">2020</dateIssued>
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<relatedItem type="host"><titleInfo><title>Journal of Statistical Physics</title></titleInfo>
  <identifier type="issn">0022-4715</identifier>
  <identifier type="eIssn">1572-9613</identifier>
  <identifier type="arXiv">2004.02831</identifier>
  <identifier type="MEDLINE">33268907</identifier>
  <identifier type="ISI">000587107200002</identifier><identifier type="doi">10.1007/s10955-020-02663-4</identifier>
<part><detail type="volume"><number>181</number></detail><detail type="issue"><number>6</number></detail><extent unit="pages">2257-2303</extent>
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<chicago>Maas, Jan, and Alexander Mielke. “Modeling of Chemical Reaction Systems with Detailed Balance Using Gradient Structures.” &lt;i&gt;Journal of Statistical Physics&lt;/i&gt;. Springer Nature, 2020. &lt;a href=&quot;https://doi.org/10.1007/s10955-020-02663-4&quot;&gt;https://doi.org/10.1007/s10955-020-02663-4&lt;/a&gt;.</chicago>
<ieee>J. Maas and A. Mielke, “Modeling of chemical reaction systems with detailed balance using gradient structures,” &lt;i&gt;Journal of Statistical Physics&lt;/i&gt;, vol. 181, no. 6. Springer Nature, pp. 2257–2303, 2020.</ieee>
<apa>Maas, J., &amp;#38; Mielke, A. (2020). Modeling of chemical reaction systems with detailed balance using gradient structures. &lt;i&gt;Journal of Statistical Physics&lt;/i&gt;. Springer Nature. &lt;a href=&quot;https://doi.org/10.1007/s10955-020-02663-4&quot;&gt;https://doi.org/10.1007/s10955-020-02663-4&lt;/a&gt;</apa>
<ista>Maas J, Mielke A. 2020. Modeling of chemical reaction systems with detailed balance using gradient structures. Journal of Statistical Physics. 181(6), 2257–2303.</ista>
<short>J. Maas, A. Mielke, Journal of Statistical Physics 181 (2020) 2257–2303.</short>
<ama>Maas J, Mielke A. Modeling of chemical reaction systems with detailed balance using gradient structures. &lt;i&gt;Journal of Statistical Physics&lt;/i&gt;. 2020;181(6):2257-2303. doi:&lt;a href=&quot;https://doi.org/10.1007/s10955-020-02663-4&quot;&gt;10.1007/s10955-020-02663-4&lt;/a&gt;</ama>
<mla>Maas, Jan, and Alexander Mielke. “Modeling of Chemical Reaction Systems with Detailed Balance Using Gradient Structures.” &lt;i&gt;Journal of Statistical Physics&lt;/i&gt;, vol. 181, no. 6, Springer Nature, 2020, pp. 2257–303, doi:&lt;a href=&quot;https://doi.org/10.1007/s10955-020-02663-4&quot;&gt;10.1007/s10955-020-02663-4&lt;/a&gt;.</mla>
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