u x + u y = x u . u(x, 0) = e x2 The characteristics satisfy dx dt = 1, dy dt = 1

Similar documents
x 0, x 1,...,x n f(x) p n (x) = f[x 0, x 1,..., x n, x]w n (x),

ÇÙÐ Ò ½º ÅÙÐ ÔÐ ÔÓÐÝÐÓ Ö Ñ Ò Ú Ö Ð Ú Ö Ð ¾º Ä Ò Ö Ö Ù Ð Ý Ó ËÝÑ ÒÞ ÔÓÐÝÒÓÑ Ð º Ì ÛÓ¹ÐÓÓÔ ÙÒÖ Ö Ô Û Ö Ö ÖÝ Ñ ¹ ÝÓÒ ÑÙÐ ÔÐ ÔÓÐÝÐÓ Ö Ñ

An Example file... log.txt

: œ Ö: =? À =ß> real numbers. œ the previous plane with each point translated by : Ðfor example,! is translated to :)

Applications of Discrete Mathematics to the Analysis of Algorithms

This document has been prepared by Sunder Kidambi with the blessings of

A Language for Task Orchestration and its Semantic Properties

2 Hallén s integral equation for the thin wire dipole antenna

Lund Institute of Technology Centre for Mathematical Sciences Mathematical Statistics

Framework for functional tree simulation applied to 'golden delicious' apple trees

Arbeitstagung: Gruppen und Topologische Gruppen Vienna July 6 July 7, Abstracts

F(jω) = a(jω p 1 )(jω p 2 ) Û Ö p i = b± b 2 4ac. ω c = Y X (jω) = 1. 6R 2 C 2 (jω) 2 +7RCjω+1. 1 (6jωRC+1)(jωRC+1) RC, 1. RC = p 1, p

106 Chapter 5 Curve Sketching. If f(x) has a local extremum at x = a and. THEOREM Fermat s Theorem f is differentiable at a, then f (a) = 0.

LOWELL. MICHIGAN, THURSDAY, MAY 23, Schools Close. method of distribution. t o t h e b o y s of '98 a n d '18. C o m e out a n d see t h e m get

Matrices and Determinants

SME 3023 Applied Numerical Methods

LA PRISE DE CALAIS. çoys, çoys, har - dis. çoys, dis. tons, mantz, tons, Gas. c est. à ce. C est à ce. coup, c est à ce

SKMM 3023 Applied Numerical Methods

Radu Alexandru GHERGHESCU, Dorin POENARU and Walter GREINER


Examination paper for TFY4240 Electromagnetic theory

Juan Juan Salon. EH National Bank. Sandwich Shop Nail Design. OSKA Beverly. Chase Bank. Marina Rinaldi. Orogold. Mariposa.

I118 Graphs and Automata

T i t l e o f t h e w o r k : L a M a r e a Y o k o h a m a. A r t i s t : M a r i a n o P e n s o t t i ( P l a y w r i g h t, D i r e c t o r )

SME 3023 Applied Numerical Methods

Pose Determination from a Single Image of a Single Parallelogram

SKMM 3023 Applied Numerical Methods

Lecture 16: Modern Classification (I) - Separating Hyperplanes

arxiv:hep-ph/ v1 10 May 2001

Two-scale homogenization of a hydrodynamic Elrod-Adams model

An Introduction to Optimal Control Applied to Disease Models

B œ c " " ã B œ c 8 8. such that substituting these values for the B 3 's will make all the equations true

( ) and then eliminate t to get y(x) or x(y). Not that the

ENGI 4430 Line Integrals; Green s Theorem Page 8.01

Automatic Control III (Reglerteknik III) fall Nonlinear systems, Part 3

Multi-agent learning

Periodic monopoles and difference modules

PH Nuclear Physics Laboratory Gamma spectroscopy (NP3)

JEE-ADVANCED MATHEMATICS. Paper-1. SECTION 1: (One or More Options Correct Type)

Ordinary Differential Equations (ODEs)

SOLUTION THE ASSOCIATION OF MATHEMATICS TEACHERS OF INDIA BHASKARA CONTEST - FINAL - JUNIOR CLASS - IX & X

Planning for Reactive Behaviors in Hide and Seek

8œ! This theorem is justified by repeating the process developed for a Taylor polynomial an infinite number of times.

póåíüéëáë ~åç `Ü~ê~ÅíÉêáò~íáçå çñ pê O pá R k U Wbì O müçëéüçê rëáåö píêçåíáìã `~êäçñóä~íé

Part I consists of 14 multiple choice questions (worth 5 points each) and 5 true/false question (worth 1 point each), for a total of 75 points.

Depinning transition for domain walls with an internal degree of freedom

Stochastic invariances and Lamperti transformations for Stochastic Processes

Loop parallelization using compiler analysis

Optimal back-to-front airplane boarding

The 25th Annual Virginia Water and Wastewater Rate Report 2013

Page x2 Choose the expression equivalent to ln ÄÄÄ.

Multiple Choice. Compute the Jacobian, (u, v), of the coordinate transformation x = u2 v 4, y = uv. (a) 2u 2 + 4v 4 (b) xu yv (c) 3u 2 + 7v 6

The first order quasi-linear PDEs

Differentiating Functions & Expressions - Edexcel Past Exam Questions

Notes on the Unique Extension Theorem. Recall that we were interested in defining a general measure of a size of a set on Ò!ß "Ó.

solve EB œ,, we can row reduce the augmented matrix

Information Theory. Week 4 Compressing streams. Iain Murray,

solve EB œ,, we can row reduce the augmented matrix

Glasgow eprints Service

Optimal Control of PDEs

Systems of Equations 1. Systems of Linear Equations

Crew of25 Men Start Monday On Showboat. Many Permanent Improvements To Be Made;Project Under WPA

ALLEN. Pre Nurture & Career Foundation Division For Class 6th to 10th, NTSE & Olympiads. å 7 3 REGIONAL MATHEMATICAL OLYMPIAD-2017 SOLUTION

PART I. Multiple choice. 1. Find the slope of the line shown here. 2. Find the slope of the line with equation $ÐB CÑœ(B &.

3.4 Design Methods for Fractional Delay Allpass Filters

Mathematical Tripos Part IA Lent Term Example Sheet 1. Calculate its tangent vector dr/du at each point and hence find its total length.

Margin Maximizing Loss Functions

ACT455H1S - TEST 2 - MARCH 25, 2008

Example Let VœÖÐBßCÑ À b-, CœB - ( see the example above). Explain why

Front-end. Organization of a Modern Compiler. Middle1. Middle2. Back-end. converted to control flow) Representation

" #$ P UTS W U X [ZY \ Z _ `a \ dfe ih j mlk n p q sr t u s q e ps s t x q s y i_z { U U z W } y ~ y x t i e l US T { d ƒ ƒ ƒ j s q e uˆ ps i ˆ p q y

FINAL EXAM CALCULUS 2. Name PRACTICE EXAM

Gene expression experiments. Infinite Dimensional Vector Spaces. 1. Motivation: Statistical machine learning and reproducing kernel Hilbert Spaces

Proving observational equivalence with ProVerif

NPTEL COURSE ON MATHEMATICS IN INDIA: FROM VEDIC PERIOD TO MODERN TIMES

Ú Bruguieres, A. Virelizier, A. [4] Á «Î µà Monoidal

b) The system of ODE s d x = v(x) in U. (2) dt

Thermal Conductivity of Electric Molding Composites Filled with β-si 3 N 4

INRIA Sophia Antipolis France. TEITP p.1

Final exam: Computer-controlled systems (Datorbaserad styrning, 1RT450, 1TS250)

Max. Input Power (W) Input Current (Arms) Dimming. Enclosure

IIE5. Modul Electricity II. Earth s magnetic field

A Robust Adaptive Digital Audio Watermarking Scheme Against MP3 Compression

JEE(Advanced) 2015 TEST PAPER WITH ANSWER. (HELD ON SUNDAY 24 th MAY, 2015) PART - III : MATHEMATICS

A Functional Quantum Programming Language

Math 273, Final Exam Solutions

Soft-decision Decoding of Chinese Remainder Codes

Towards a numerical solution of the "1/2 vs. 3/2" puzzle

µ(, y) Computing the Möbius fun tion µ(x, x) = 1 The Möbius fun tion is de ned b y and X µ(x, t) = 0 x < y if x6t6y 3

Books. Book Collection Editor. Editor. Name Name Company. Title "SA" A tree pattern. A database instance

e) D œ < f) D œ < b) A parametric equation for the line passing through Ð %, &,) ) and (#,(, %Ñ.

Redoing the Foundations of Decision Theory

Lecture 11: Regression Methods I (Linear Regression)

Price discount model for coordination of dual-channel supply chain under e-commerce

OC330C. Wiring Diagram. Recommended PKH- P35 / P50 GALH PKA- RP35 / RP50. Remarks (Drawing No.) No. Parts No. Parts Name Specifications

Lecture 11: Regression Methods I (Linear Regression)

Problem 1 (From the reservoir to the grid)

ENGI 4430 Line Integrals; Green s Theorem Page 8.01


Infinite Dimensional Vector Spaces. 1. Motivation: Statistical machine learning and reproducing kernel Hilbert Spaces

Transcription:

Õ 83-25 Þ ÛÐ Þ Ð ÚÔÜØ Þ ÝÒ Þ Ô ÜÞØ ¹ 3 Ñ Ð ÜÞ u x + u y = x u u(x, 0) = e x2 ÝÒ Þ Ü ÞØ º½ dt =, dt = x = t + c, y = t + c 2 We can choose c to be zero without loss of generality Note that each characteristic (the lines y = x + c 2 ) intersects the line y = 0, on which the initial data is given, exactly once, the lution will be well-defined in the whole plane with general lution dt = t u u = t + c 3 e t The initial condition is given on y = 0, ie at t = c 2 and then we have u = e x2 = e c2 2 Thus e c2 2 = c2 + c 3 e c 2, and The lution on the characteristic is c 3 = e c 2 ( + c2 + e c2 2) u = t + e (t+c 2) ( + c 2 + e c2 2) It just remains to write the lution in terms of x and y: we have x = t y = t + c 2 t = x c 2 = y x the lution is u = x + e y ( + (y x) + e (y x)2) It is a good idea to check!

u x + xu y = y 2xu u(0, y) = ÝÒ Þ Ü ÞØ º¾ dt =, dt = x x = t + c, y = 2 (t + c ) 2 + c 2 We can choose c to be zero without loss of generality Note that each characteristic (the parabolas y = 2 x2 + c 2 ) intersects the line x = 0, on which the initial data is given, exactly once, the lution will be well-defined in the whole plane Writing this as dt = 2 t2 + c 2 2tu dt + 2tu = 2 t2 + c 2 we see there is an integrating factor e t2 and d ( e t 2 u ) ( ) = dt 2 t2 + c 2 e t2, u = e t2 (c 3 + t ( ) ) 2 s2 + c 2 e s2 ds The initial condition is given on x = 0, ie at t = 0 and then we have u = y = c 3 Thus c 3 should be taken to be and the lution on the characteristic is u = e t2 ( + t ( ) ) 2 s2 + c 2 e s2 ds It just remains to write the lution in terms of x and y: we have x = t y = 2 t2 + c 2 t = x c 2 = y 2 x2 the lution is x ( ) ) u = e ( x2 + 2 (s2 x 2 ) + y e s2 ds It is a good idea to check!

xu x + yu y = u(, y) = y ÝÒ Þ Ü ÞØ º Ó ÜÞØ ÐÝ Ü Ñ Þ Ò dt = x, dt = y x = c e t, y = c 2 e t The characteristics are half lines through (0, 0) e t is always positive the characteristics never reach (0, 0) (There is al a characteristic which is a single point the point (0, 0) corresponding to c = c 2 = 0) The initial data is specified on the line x = This intersects (once) with each of the characteristics in the half-plane x > 0, we expect a lution in this region Given that x > 0 we can choose c = without loss of generality with lution dt =, u = t + c 3 The initial data is specified at x =, ie t = 0 At t = 0 we have y = c 2 and u = t 3 to impose the condition u(, y) = y we must take c 3 = c 2 Thus the lution on the characteristic is u = t + c 2 It just remains to write the lution in terms of x and y: we have x = e t y = c 2 e t t = log x c 2 = y x the lution is u = log x + y x It is easy to check this satisfies both the equation and the initial condition It is defined everywhere except on the y axis (x = 0) But it is only the lution of our problem in the region x > 0 No characteristics connect the initial data and the region x < 0

Ñ º ÝÒÒ Ö Û p ÜÝ xu x + yu y = pu ÝÒ Þ ÞÒ ÛÒ u(x, y) ÚÛÔ Ø º Ð ÖÒ ÐÖ u(x, y) = y ØÝ ÔÞ Þ ÞÒ ÛÒ Ñ u(x, y) ¹Ý Ó ÞÔ Ð Ó Ý Þ ÛÐ Ý u(x, y) ÐÝ ÞÜ Ñ Þ Ò ºu(x, y) Þ ÚÒ x 2 + y 2 = ºp ÐÝ ÜÝØ ÜÖ dt = x, dt = y x = c e t, y = c 2 e t The characteristics are half lines through (0, 0) e t is always positive the characteristics never reach (0, 0) (There is al a characteristic which is a single point the point (0, 0) corresponding to c = c 2 = 0) Each half-line intersects (once) with the circle x 2 + y 2 = we expect a lution on the whole plane except at the point (0, 0) dt = pu, with lution u = c 3 e pt The initial data is specified on the circle x 2 + y 2 = which a characteristic intersects when (c 2 + c 2 2)e 2t =, ie when e t = (c 2 +c2 2 )/2 On the circle we want to impose u(x, y) = y ie c 3 e pt = c 2 e t c 3 = c 2 (c 2 + c 2 2) (p )/2 Thus the lution on a characteristic is u = c 2 (c 2 + c 2 2) (p )/2 e pt It just remains to write the lution in terms of x and y: we have x = c e t (c 2 + c2 2 )/2 e t = x 2 + y 2 the lution is y = c 2 e t c 2 = (c 2 +c2 2 )/2 u = y(x 2 + y 2 ) (p )/2 y x 2 +y 2 It is easy to check this satisfies both the equation and the initial condition What about the domain of definition of the lution? It certainly is defined on the whole plane except possibly at (0, 0) At (0, 0) there are several possibilities: ( ) If p < then the lution is not defined ( ) If p =, 3, 5, the lution is defined and the lution is infinitely differentiable at (0, 0) ( ) If p takes other values bigger than the lution is defined, but it is only differentiable a finite number of times (in fact not at all if < p < 3)

Ö Ð Ó ÜÞØ Ñ Û Ñ º yu x xu y = u? u(x, 0) = x, x > 0 ÛÒÔ dt = y, dt = x x = c sin t, y = c cost (There is another constant of integration which we can ignore) The characteristics are circles centered at (0, 0) We are given an initial condition on the positive x- axis (not including the origin) This intersects every characteristic once except for the characteristic consisting of the single point (0, 0) But the characteristics are closed curves this is not enough to guarantee a lution with lution dt = u, u = c 2 e t The initial data is specified on the half line y = 0, x > 0 The characteristic intersects the initial line when t = 2 π, we need to choose c 2 such that c 2 e π/2 = c In other words, the lution on the characterstic is u = c e t π/2 It just remains to write the lution in terms of x and y: we have Thus the lution is u = x = c sin t y = c 2 cos t t = arctan ( x y ) c = x 2 + y 2 x 2 + y 2 e arctan ( x y) 2 π = x 2 + y 2 e arctan( x) y It is easy to check this satisfies both the equation and the initial condition But the definition of arctan means this formula is multivalued : as we go round the point (0, 0) (in an anticlockwise direction) the arctan increases by 2π This is a result of the closed trajectories In the normal sense of the word, there is no lution