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Mathematical Analysis, Probability and Applications – Plenary Lectures: ISAAC 2015, Macau, China PDF

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Springer Proceedings in Mathematics & Statistics Tao Qian Luigi G. Rodino Editors Mathematical Analysis, Probability and Applications – Plenary Lectures ISAAC 2015, Macau, China Springer Proceedings in Mathematics & Statistics Volume 177 Springer Proceedings in Mathematics & Statistics This book series features volumes composed of selected contributions from workshops and conferences in all areas of current research in mathematics and statistics, including operation research and optimization. In addition to an overall evaluation of the interest, scientific quality, and timeliness of each proposal at the hands of the publisher, individual contributions are all refereed to the high quality standards of leading journals in the field. Thus, this series provides the research community with well-edited, authoritative reports on developments in the most exciting areas of mathematical and statistical research today. More information about this series at http://www.springer.com/series/10533 Tao Qian Luigi G. Rodino (cid:129) Editors Mathematical Analysis, – Probability and Applications Plenary Lectures ISAAC 2015, Macau, China 123 Editors TaoQian Luigi G.Rodino Faculty of Science andTechnology Department ofMathematics University of Macao University of Turin Taipa Turin Macao Italy ISSN 2194-1009 ISSN 2194-1017 (electronic) SpringerProceedings in Mathematics& Statistics ISBN978-3-319-41943-5 ISBN978-3-319-41945-9 (eBook) DOI 10.1007/978-3-319-41945-9 LibraryofCongressControlNumber:2016945107 MathematicsSubjectClassification(2010): 35QXX,46EXX,60GXX ThisworkispublishedundertheauspicesoftheInternationalSocietyofAnalysis,itsApplicationsand Computation(ISAAC). ©SpringerInternationalPublishingSwitzerland2016 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authorsortheeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinor foranyerrorsoromissionsthatmayhavebeenmade. Printedonacid-freepaper ThisSpringerimprintispublishedbySpringerNature TheregisteredcompanyisSpringerInternationalPublishingAGSwitzerland Preface The present volume is a collection of papers devoted to current research topics in mathematical analysis, probability and applications, including the topics in math- ematicalphysicsandnumericalanalysis.Itoriginatesfromplenarylecturesgivenat the 10th International ISAAC Congress, held during 3–8 August 2015 at the University of Macau, China. The papers, authored by eminent specialists, aim at presenting to a large audi- ence some of the attractive and challenging themes of modern analysis: (cid:129) Partial differential equations of mathematical physics, including study of the equations of incompressible viscous flows, and of the Tricomi, Klein–Gordon and Einstein–de Sitter equations. Governing equations offluid membranes are also considered in this volume. (cid:129) Fourier analysis and applications, in particular construction of Fourier and Mellin-type transform pairs for given planar domains, multiplication and com- position operators for modulation spaces, harmonic analysis of first-order sys- tems on Lipschitz domains. (cid:129) Reviewsofresultsonprobability,concerninginparticularthebi-freeextension ofthefreeprobabilityandasurveyofBrownianmotionbasedontheLangevin equation with white noise. (cid:129) Numerical analysis, in particular sparse approximation by greedy algorithms, and theory of reproducing kernels, with applications to analysis and numerical analysis. The volume also includes a contribution on visual exploration of complex functions:thetechniqueofdomaincolouringallowstorepresentcomplexfunctions as images, and it draws surprisingly mathematics near the modern arts. v vi Preface Besides plenary talks, about 300 scientific communications were delivered during the Macau ISAAC Congress. Their texts are published in an independent volume.Onthewhole,thecongressdemonstrated,inparticular,theincreasingand major role of Asian countries in several research areas of mathematical analysis. Taipa, Macao Tao Qian Turin, Italy Luigi G. Rodino March 2016 Contents A Review of Brownian Motion Based Solely on the Langevin Equation with White Noise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 L. Cohen Geometry-Fitted Fourier-Mellin Transform Pairs. . . . . . . . . . . . . . . . . 37 Darren Crowdy First Order Approach to LP Estimates for the Stokes Operator on Lipschitz Domains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Alan McIntosh and Sylvie Monniaux The Study of Complex Shapes of Fluid Membranes, the Helfrich Functional and New Applications . . . . . . . . . . . . . . . . . . . 77 Zhong-Can Ou-Yang and Zhan-Chun Tu Multiplication and Composition in Weighted Modulation Spaces. . . . . . 103 Maximilian Reich and Winfried Sickel A Reproducing Kernel Theory with Some General Applications. . . . . . 151 Saburou Saitoh Sparse Approximation by Greedy Algorithms . . . . . . . . . . . . . . . . . . . 183 V. Temlyakov The Bi-free Extension of Free Probability . . . . . . . . . . . . . . . . . . . . . . 217 Dan-Virgil Voiculescu Stability of the Prandtl Boundary Layers. . . . . . . . . . . . . . . . . . . . . . . 235 Y.-G. Wang Visual Exploration of Complex Functions . . . . . . . . . . . . . . . . . . . . . . 253 Elias Wegert Integral Transform Approach to Time-Dependent Partial Differential Equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 Karen Yagdjian vii A Review of Brownian Motion Based Solely on the Langevin Equation with White Noise L.Cohen Abstract WegiveahistoricalandmathematicalreviewofBrownianmotionbased solely on the Langevin equation. We derive the main statistical properties with- outbringinginexternalandsubsidiaryissues,suchastemperature,Focker-Planck equations, the Maxwell–Boltzmann distribution, spectral analysis, the fluctuation- dissipationtheorem,amongmanyothertopicsthataretypicallyintroducedindiscus- sionsoftheLangevinequation.Themethodweuseistheformalsolutionapproach, whichwasthestandardmethoddevisedbythefoundersofthefield.Inaddition,we givesomerelevanthistoricalcomments. · · · · Keywords Brownianmotion Langevinequation History Einstein Whitenoise 1 Introduction Thetwoseeminglysimpleequations(asoriginallywritten) ∂f(x,t) ∂2f(x,t) =D (1) ∂t ∂x2 and d2x dx m =−6πμa +X (2) dt2 dt revolutionized our understanding of the of the universe and ushered an incredible numberofphysicalandmathematicalideas[11].ThefirstequationisduetoEinstein [13],whoseaimwastoshowthatatomsexist;thesecondisduetoLangevin[26], whobroughtforthanewperspectiveregardingboththephysicsandmathematicsof Einstein’sidea. B L.Cohen ( ) CityUniversityofNewYork,695ParkAve.,NewYork,NY10065,USA e-mail:[email protected] ©SpringerInternationalPublishingSwitzerland2016 1 T.QianandL.G.Rodino(eds.),MathematicalAnalysis,Probability andApplications–PlenaryLectures,SpringerProceedings inMathematics&Statistics177,DOI10.1007/978-3-319-41945-9_1 2 L.Cohen ItisoftensaidthatBrown[3]discoveredBrownianmotion,Einsteinexplainedit, Langevinsimplifiedit,andPerrin[31]provedit;thislistingmissestotallythemoti- vationsandwonderfulhistoryofthesubject[11].BrowndidnotdiscoverBrownian motion, but did study it extensively. Einstein was not aware of Brownian motion; hepredicted Brownianmotiontoobtainamacroscopicmanifestationofatomsthat could be measured. Equation(1) is the equation for the probability density for the Brownianparticleatpositionxandtimet.Hederivedthestandarddeviationofthe visibleBrownianparticlethatcouldbeexperimentallyverifiedifindeedatomsexist. Hesolvedexplicitlyforthestandarddeviationofposition, (cid:2) √ λ = x2 = 2Dt (3) x and connected the parameters with the temperature of the medium, and the yet unnamed Avogadro number, a number that few believed in, and had never been measured or estimated at that time. Of course, Eq.(1) was known for 100 years beforeEinstein;itisthefamousheatequationfirstderivedbyFourier.Howeverthat isnotrelevant.WhatisimportantisthatEinsteinderivedtheprobabilitydensityfor positionoftheBrownianparticle.Perrinhadalreadybeenworkingontheissueof the existence of atoms, and his motivation was certainly heightened by Einstein’s results.HeexperimentallyverifiedEq.(3),andhenceverifiedtheEinsteinideathat therandom“invisible”microscopicatomscanmanifestamacroscopiceffectwhich canbemeasured[31]. Equation(2)wasthestartofthefieldofrandomdifferentialequationandisnow calledtheLangevinequation.Thewayitstands,itisNewton’sequationofmotion wherethelefthandismasstimestheacceleration,thefirsttermontherightisthe forceof“friction”whichisproportionaltothevelocity,andthesecondterm,X,is anadditionalforce.InLangevin’swords:“X isindifferentlypositiveandnegative”. X is what we now call the random force. Langevin’s insight was to realize that to obtainthemainresultofEinstein,Eq.(3),onedoesnothavetosolveandderivethe probability density, but one can obtain the second moment simply from Newton’s equation and moreover that one can obtain it in a relatively simple manner. The Langevin equation has been applied to numerous fields and to a wide variety of physical situations. Random differential equations have become standard in many branchesofscienceandhasproducedrichmathematics[7, 21–23, 27, 28, 35, 36, 39, 45]. 1.1 TheAimofThisArticle Theauthor’sinvolvementwithBrownianmotion[1,2,8]startedwithhisattemptto understandandapplythetheoryofChandrasekharandvonNeumann[4–6]regarding therandommotionofstars,asubjectthatisfundamentalinstellardynamics,because itistherandommotionthatisimportantintheevolutionofacollectionofstars,such

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