Editing Monte Carlo method (section)

===Physical sciences===
{{Computational physics}}
{{See also|Monte Carlo method in statistical physics}}
Monte Carlo methods are very important in [[computational physics]], [[physical chemistry]], and related applied fields, and have diverse applications from complicated [[quantum chromodynamics]] calculations to designing [[heat shield]]s and [[aerodynamics|aerodynamic]] forms as well as in modeling radiation transport for radiation dosimetry calculations.<ref>{{cite journal |doi=10.1088/0031-9155/59/4/R151 |pmid=24486639 |volume=59 |issue=4 |title=GPU-based high-performance computing for radiation therapy |journal=Physics in Medicine and Biology |pages=R151–R182 |bibcode=2014PMB....59R.151J |year=2014 |author-last1=Jia |author-first1=Xun |author-last2=Ziegenhein |author-first2=Peter |author-last3=Jiang |author-first3=Steve B |pmc=4003902 }}</ref><ref>{{cite journal |doi=10.1088/0031-9155/59/6/R183 |volume=59 |issue=6 |title=Advances in kilovoltage x-ray beam dosimetry | journal=Physics in Medicine and Biology |pages=R183–R231 |bibcode=2014PMB....59R.183H |pmid=24584183 |date=Mar 2014 |author-last1=Hill |author-first1=R. | last2=Healy |author-first2=B. |author-last3=Holloway |author-first3=L. |author-last4=Kuncic |author-first4=Z. |author-last5=Thwaites |author-first5=D. |author-last6=Baldock |author-first6=C. |s2cid=18082594 }}</ref><ref>{{cite journal |doi=10.1088/0031-9155/51/13/R17 |pmid=16790908 |volume=51 |issue=13 |title=Fifty years of Monte Carlo simulations for medical physics |journal=Physics in Medicine and Biology |pages=R287–R301 |bibcode=2006PMB....51R.287R |year=2006 |author-last1=Rogers |author-first1=D.W.O. |s2cid=12066026 }}</ref> In [[statistical physics]], [[Monte Carlo molecular modeling]] is an alternative to computational [[molecular dynamics]], and Monte Carlo methods are used to compute [[statistical field theory|statistical field theories]] of simple particle and polymer systems.<ref name=":0" /><ref>{{harvnb|Baeurle|2009}}</ref> [[Quantum Monte Carlo]] methods solve the [[many-body problem]] for quantum systems.<ref name="kol10" /><ref name="dp13" /><ref name="dp04" /> In [[Radiation material science|radiation materials science]], the [[binary collision approximation]] for simulating [[ion implantation]] is usually based on a Monte Carlo approach to select the next colliding atom.<ref>{{cite journal|author-last1=Möller |author-first1=W. |author-last2=Eckstein |author-first2=W. |date=March 1, 1984 |title=Tridyn — A TRIM simulation code including dynamic composition changes |journal=Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms |volume=2 |issue=1 |pages=814–818 |doi=10.1016/0168-583X(84)90321-5 |bibcode=1984NIMPB...2..814M}}</ref> In experimental [[particle physics]], Monte Carlo methods are used for designing [[particle detector|detectors]], understanding their behavior and comparing experimental data to theory. In [[astrophysics]], they are used in such diverse manners as to model both [[galaxy]] evolution<ref>{{harvnb|MacGillivray|Dodd|1982}}</ref> and microwave radiation transmission through a rough planetary surface.<ref>{{harvnb|Golden|1979}}</ref> Monte Carlo methods are also used in the [[Ensemble forecasting|ensemble models]] that form the basis of modern [[Numerical weather prediction|weather forecasting]].