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→Sloppy 理论与物理学
事实上，理论物理学就像一棵树（下图）。高能物理学家研究树的枝条，寻找更接近树干的更统一的理论。在凝聚态物理学中则向外构建，寻找“涌现的”树枝和树叶——描述声音、半导体和超流体的有效理论。但两者有许多相似之处：扩散方程描述了在静止空气中香水如何从皮肤扩散到鼻子。这个方程通常写成连续极限的形式，使用的方法类似于描述凝聚态物理学中许多其他现象——声音、磁铁和超导体——的方法。而磁性的伊辛模型分形过程，通常使用类似于高能物理学中使用的重整化群进行分析。物理学家有一套系统的方法判断哪些参数是stiff（“僵硬”）的，哪些参数是sloppy（“欠定”）的，但是在其它领域中并没有相应的方法，使用sloppy理论的概念可以更准确有效地分析系统<ref>Information geometry and the renormalization group, Archishman Raju, Benjamin B. Machta, James P. Sethna (submitted). </ref><ref>Parameter Space Compression Underlies Emergent Theories and Predictive Models, Benjamin B. Machta, Ricky Chachra, Mark K. Transtrum, James P. Sethna, Science342 604-607 (2013).</ref><ref>Information topology identifies emergent model classes, Transtrum M.K., Hart G., Qiu P. </ref><ref>Structural susceptibility and separation of time scales in the van der Pol Oscillator, Ricky Chachra, Mark K. Transtrum, and James P. Sethna, Phys. Rev. E 86, 026712 (2012). </ref>
事实上，理论物理学就像一棵树（下图）。高能物理学家研究树的枝条，寻找更接近树干的更统一的理论。在凝聚态物理学中则向外构建，寻找“涌现的”树枝和树叶——描述声音、半导体和超流体的有效理论。但两者有许多相似之处：扩散方程描述了在静止空气中香水如何从皮肤扩散到鼻子。这个方程通常写成连续极限的形式，使用的方法类似于描述凝聚态物理学中许多其他现象——声音、磁铁和超导体——的方法。而磁性的伊辛模型分形过程，通常使用类似于高能物理学中使用的重整化群进行分析。物理学家有一套系统的方法判断哪些参数是stiff（“僵硬”）的，哪些参数是sloppy（“欠定”）的，但是在其它领域中并没有相应的方法，使用sloppy理论的概念可以更准确有效地分析系统<ref>Information geometry and the renormalization group, Archishman Raju, Benjamin B. Machta, James P. Sethna (submitted). </ref><ref>Parameter Space Compression Underlies Emergent Theories and Predictive Models, Benjamin B. Machta, Ricky Chachra, Mark K. Transtrum, James P. Sethna, Science342 604-607 (2013).</ref><ref>Information topology identifies emergent model classes, Transtrum M.K., Hart G., Qiu P. </ref><ref>Structural susceptibility and separation of time scales in the van der Pol Oscillator, Ricky Chachra, Mark K. Transtrum, and James P. Sethna, Phys. Rev. E 86, 026712 (2012). </ref>
,甚至物理学领域也在逐渐应用sloppy理论<ref name = “Quinn et.al, 2017”>Model manifolds for probabilistic models: Visualizing theory space: Isometric embedding of probabilistic predictions, from the Ising model to the cosmic microwave background, Katherine N. Quinn, Francesco De Bernardis, Michael D. Niemack, James P. Sethna (submitted). </ref><ref name = “Gutenkunst et.al, 2007”>”Universally Sloppy Parameter Sensitivities in Systems Biology", Ryan N. Gutenkunst, Joshua J. Waterfall, Fergal P. Casey, Kevin S. Brown, Christopher R. Myers, James P. Sethna, PLoS Comput Biol3(10) e189 (2007). (PLoS, doi:10.1371/journal.pcbi.0030189). [Reviewed in NewsBytes of Biomedical Computation Review (Winter 07/08); rated "Exceptional" on Faculty of 1000]. </ref><ref name = “Casey et.al, 2007”>"Optimal experimental design in an EGFR signaling and down-regulation model", Fergal P. Casey, Dan Baird, Qiyu Feng, Ryan N. Gutenkunst, Joshua J. Waterfall, Christopher R. Myers, Kevin S. Brown, Richard A. Cerione, and James P. Sethna, IET Systems Biology 1, 190-202 (2007)</ref>。
,甚至物理学领域也在逐渐应用sloppy理论<ref name = “Quinn et.al, 2017”>Model manifolds for probabilistic models: Visualizing theory space: Isometric embedding of probabilistic predictions, from the Ising model to the cosmic microwave background, Katherine N. Quinn, Francesco De Bernardis, Michael D. Niemack, James P. Sethna (submitted). </ref><ref>”Universally Sloppy Parameter Sensitivities in Systems Biology", Ryan N. Gutenkunst, Joshua J. Waterfall, Fergal P. Casey, Kevin S. Brown, Christopher R. Myers, James P. Sethna, PLoS Comput Biol3(10) e189 (2007). (PLoS, doi:10.1371/journal.pcbi.0030189). [Reviewed in NewsBytes of Biomedical Computation Review (Winter 07/08); rated "Exceptional" on Faculty of 1000]. </ref><ref name = “Casey et.al, 2007”>"Optimal experimental design in an EGFR signaling and down-regulation model", Fergal P. Casey, Dan Baird, Qiyu Feng, Ryan N. Gutenkunst, Joshua J. Waterfall, Christopher R. Myers, Kevin S. Brown, Richard A. Cerione, and James P. Sethna, IET Systems Biology 1, 190-202 (2007)</ref>。
===Sloppy理论对实验的启示及应用===
===Sloppy理论对实验的启示及应用===