Acoustic Limit for the Boltzmann equation in Optimal Scaling

Σχετικά έγγραφα
Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.

Example Sheet 3 Solutions

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

2 Composition. Invertible Mappings

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in

C.S. 430 Assignment 6, Sample Solutions

Uniform Convergence of Fourier Series Michael Taylor

STABILITY FOR RAYLEIGH-BENARD CONVECTIVE SOLUTIONS OF THE BOLTZMANN EQUATION

Homework 3 Solutions

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

Concrete Mathematics Exercises from 30 September 2016

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.

Section 8.3 Trigonometric Equations

EE512: Error Control Coding

HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:

Solutions to Exercise Sheet 5

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS

4.6 Autoregressive Moving Average Model ARMA(1,1)

1 String with massive end-points

derivation of the Laplacian from rectangular to spherical coordinates

Matrices and Determinants

Every set of first-order formulas is equivalent to an independent set

SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018

Finite Field Problems: Solutions

Fractional Colorings and Zykov Products of graphs

Approximation of distance between locations on earth given by latitude and longitude

Areas and Lengths in Polar Coordinates

D Alembert s Solution to the Wave Equation

Homework 8 Model Solution Section

Other Test Constructions: Likelihood Ratio & Bayes Tests

Second Order RLC Filters

Iterated trilinear fourier integrals with arbitrary symbols

Finite difference method for 2-D heat equation

Second Order Partial Differential Equations

ST5224: Advanced Statistical Theory II

6.3 Forecasting ARMA processes

Math221: HW# 1 solutions

Forced Pendulum Numerical approach

Partial Differential Equations in Biology The boundary element method. March 26, 2013

Practice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1

Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013

w o = R 1 p. (1) R = p =. = 1

The Simply Typed Lambda Calculus

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions

Areas and Lengths in Polar Coordinates

Inverse trigonometric functions & General Solution of Trigonometric Equations

Section 7.6 Double and Half Angle Formulas

( y) Partial Differential Equations

5. Choice under Uncertainty

Higher Derivative Gravity Theories

Lecture 34 Bootstrap confidence intervals

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3

6.1. Dirac Equation. Hamiltonian. Dirac Eq.

Solvability of Brinkman-Forchheimer equations of flow in double-diffusive convection

Statistical Inference I Locally most powerful tests

Solution Series 9. i=1 x i and i=1 x i.

Tridiagonal matrices. Gérard MEURANT. October, 2008

Global nonlinear stability of steady solutions of the 3-D incompressible Euler equations with helical symmetry and with no swirl

Congruence Classes of Invertible Matrices of Order 3 over F 2

DESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.

The Pohozaev identity for the fractional Laplacian

ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems

Appendix to Technology Transfer and Spillovers in International Joint Ventures

Problem Set 3: Solutions

Pg The perimeter is P = 3x The area of a triangle is. where b is the base, h is the height. In our case b = x, then the area is

Geodesic Equations for the Wormhole Metric

de Rham Theorem May 10, 2016

2. Let H 1 and H 2 be Hilbert spaces and let T : H 1 H 2 be a bounded linear operator. Prove that [T (H 1 )] = N (T ). (6p)

Reminders: linear functions

Strain gauge and rosettes

Bounding Nonsplitting Enumeration Degrees

Srednicki Chapter 55

( ) 2 and compare to M.

Optimal Parameter in Hermitian and Skew-Hermitian Splitting Method for Certain Two-by-Two Block Matrices

On the Galois Group of Linear Difference-Differential Equations

ECE598: Information-theoretic methods in high-dimensional statistics Spring 2016

New bounds for spherical two-distance sets and equiangular lines

Derivation of Optical-Bloch Equations

Differential equations

Exercises to Statistics of Material Fatigue No. 5

ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2

ORDINAL ARITHMETIC JULIAN J. SCHLÖDER

Differentiation exercise show differential equation

Arithmetical applications of lagrangian interpolation. Tanguy Rivoal. Institut Fourier CNRS and Université de Grenoble 1

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics

wave energy Superposition of linear plane progressive waves Marine Hydrodynamics Lecture Oblique Plane Waves:

DERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C

Space-Time Symmetries

Exercise 1.1. Verify that if we apply GS to the coordinate basis Gauss form ds 2 = E(u, v)du 2 + 2F (u, v)dudv + G(u, v)dv 2

A Two-Sided Laplace Inversion Algorithm with Computable Error Bounds and Its Applications in Financial Engineering

A Note on Intuitionistic Fuzzy. Equivalence Relation

CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS

Empirical best prediction under area-level Poisson mixed models

MA 342N Assignment 1 Due 24 February 2016

Transcript:

Acoustic Limit for the Boltzmann equation in Optimal Scaling Joint work with Yan Guo and Ning Jiang Courant Institute March 4, 2009 Kinetic FRG Young Researchers Workshop

The Boltzmann equation t F + v x F = Q(F, F )

The Boltzmann equation t F + v x F = Q(F, F ) Q(F 1, F 2 )(v) = b(v u, ω){f 1 (v )F 2 (u ) F 1 (v)f 2 (u)}dω du R 3 S 2 where v = v [(v u) ω]ω and u = u + [(v u) ω]ω

The Boltzmann equation t F + v x F = Q(F, F ) Q(F 1, F 2 )(v) = b(v u, ω){f 1 (v )F 2 (u ) F 1 (v)f 2 (u)}dω du R 3 S 2 where v = v [(v u) ω]ω and u = u + [(v u) ω]ω Here, we take b(v u, ω) v u γ for 3 < γ 1 0 γ 1 : hard potentials (γ = 0 for Maxwell molecules, γ = 1 for hard spheres) 3 < γ < 0 : soft potentials

The Boltzmann equation t F + v x F = Q(F, F ) Q(F 1, F 2 )(v) = b(v u, ω){f 1 (v )F 2 (u ) F 1 (v)f 2 (u)}dω du R 3 S 2 where v = v [(v u) ω]ω and u = u + [(v u) ω]ω Here, we take b(v u, ω) v u γ for 3 < γ 1 0 γ 1 : hard potentials (γ = 0 for Maxwell molecules, γ = 1 for hard spheres) 3 < γ < 0 : soft potentials Collision invariants {1, v k, v 2 } Q(F, F )dv = Q(F, F )v k dv = Q(F, F ) v 2 dv = 0 R 3 R 3 R 3

Dimensionless Form and Scalings

Dimensionless Form and Scalings St t F ε + v x F ε = 1 Kn Q(F ε, F ε ) ; St = ε s, Kn = ε q

Dimensionless Form and Scalings St t F ε + v x F ε = 1 Kn Q(F ε, F ε ) ; St = ε s, Kn = ε q F ε = µ + δ ε G ε ; Ma = δ ε (ε m ), Re Ma Kn

Dimensionless Form and Scalings St t F ε + v x F ε = 1 Kn Q(F ε, F ε ) ; St = ε s, Kn = ε q F ε = µ + δ ε G ε ; Ma = δ ε (ε m ), Re Ma Kn q = 1, m = 0, s = 0 : Compressible Euler (F ε F ) q = 1, m > 0, s = 0 : Acoustic Waves (G ε G)

Dimensionless Form and Scalings St t F ε + v x F ε = 1 Kn Q(F ε, F ε ) ; St = ε s, Kn = ε q F ε = µ + δ ε G ε ; Ma = δ ε (ε m ), Re Ma Kn q = 1, m = 0, s = 0 : Compressible Euler (F ε F ) q = 1, m > 0, s = 0 : Acoustic Waves (G ε G) Longer time scale (G ε G) q = 1, m = 1, s = 1 : Incompressible Navier-Stokes-Fourier q = 1, m > 1, s = 1 : Stokes-Fourier q > 1, m = 1, s = 1 : Incompressible Euler-Fourier

Two Modern Frameworks

Two Modern Frameworks Start from DiPerna-Lions global renormalized solutions to Boltzmann equations Justify the convergence to global weak solutions of incompressible Navier-Stokes, Stokes, and Euler flows and compressible acoustic system

Two Modern Frameworks Start from DiPerna-Lions global renormalized solutions to Boltzmann equations Justify the convergence to global weak solutions of incompressible Navier-Stokes, Stokes, and Euler flows and compressible acoustic system (Bardos, Golse, Levermore, Lions, Masmoudi, Saint-Raymond)

Two Modern Frameworks Start from DiPerna-Lions global renormalized solutions to Boltzmann equations Justify the convergence to global weak solutions of incompressible Navier-Stokes, Stokes, and Euler flows and compressible acoustic system (Bardos, Golse, Levermore, Lions, Masmoudi, Saint-Raymond) Start from smooth solutions to fluid equations Construct solutions to Boltzmann equations via Hilbert or Chapman-Enskog expansions

Two Modern Frameworks Start from DiPerna-Lions global renormalized solutions to Boltzmann equations Justify the convergence to global weak solutions of incompressible Navier-Stokes, Stokes, and Euler flows and compressible acoustic system (Bardos, Golse, Levermore, Lions, Masmoudi, Saint-Raymond) Start from smooth solutions to fluid equations Construct solutions to Boltzmann equations via Hilbert or Chapman-Enskog expansions (Caflisch, De Masi, Esposito, Lebowitz, Guo)

Acoustic Limit Acoustic scaling t F ε + v x F ε = 1 ε Q(F ε, F ε ), F ε = µ 0 + δg ε µ 0 1 (2π) 3/2 exp( v 2 2 ), δ 0 as ε 0 (δ = εm )

Acoustic Limit Acoustic scaling t F ε + v x F ε = 1 ε Q(F ε, F ε ), F ε = µ 0 + δg ε µ 0 1 (2π) 3/2 exp( v 2 2 ), δ 0 as ε 0 (δ = εm ) Formal Acoustic limit ε(g ε + v x G ε ) + LG ε = δq(g ε, G ε ) { σ + v u + By letting ε 0, LG = 0 G = ( v 2 3 2 ) } θ µ 0

Acoustic Limit Acoustic scaling t F ε + v x F ε = 1 ε Q(F ε, F ε ), F ε = µ 0 + δg ε µ 0 1 (2π) 3/2 exp( v 2 2 ), δ 0 as ε 0 (δ = εm ) Formal Acoustic limit ε(g ε + v x G ε ) + LG ε = δq(g ε, G ε ) { σ + v u + By letting ε 0, LG = 0 G = ( v 2 3 2 ) } θ µ 0 G ε formally satisfy the local conservation laws and thus σ, u, θ satisfy the acoustic system t σ + x u = 0, t u + x (σ + θ) = 0, σ(x, 0) = σ 0 (x) u(x, 0) = u 0 (x) 3 2 tθ + x u = 0, θ(x, 0) = θ 0 (x)

Rigorous Justification In the framework of renormalized solutions

Rigorous Justification In the framework of renormalized solutions Golse-Levermore (CPAM, 02) : the convergence for m > 1 2 Jiang-Levermore-Masmoudi (08) : the case m = 1 2 Due to the lack of local conservation laws and regularity of renormalized solutions, the case m < 1 2 remains an open question

Rigorous Justification In the framework of renormalized solutions Golse-Levermore (CPAM, 02) : the convergence for m > 1 2 Jiang-Levermore-Masmoudi (08) : the case m = 1 2 Due to the lack of local conservation laws and regularity of renormalized solutions, the case m < 1 2 remains an open question In the framework of classical solutions J-Jiang (08) : global-in-time uniform convergence for the case m = 1

Rigorous Justification In the framework of renormalized solutions Golse-Levermore (CPAM, 02) : the convergence for m > 1 2 Jiang-Levermore-Masmoudi (08) : the case m = 1 2 Due to the lack of local conservation laws and regularity of renormalized solutions, the case m < 1 2 remains an open question In the framework of classical solutions J-Jiang (08) : global-in-time uniform convergence for the case m = 1 The purpose of this work is to establish the acoustic limit in optimal scaling (0 < m < 1) via a recent L 2 L setting.

Main Theorem Theorem (Guo-J-Jiang) Let τ > 0 be any given time and let σ(0, x) = σ 0 (x), u(0, x) = u 0 (x), θ(0, x) = θ 0 (x) H s, s 4 be any given initial data to the acoustic system. Then,

Main Theorem Theorem (Guo-J-Jiang) Let τ > 0 be any given time and let σ(0, x) = σ 0 (x), u(0, x) = u 0 (x), θ(0, x) = θ 0 (x) H s, s 4 be any given initial data to the acoustic system. Then, there exist an ε 0 > 0 and a δ 0 > 0 such that for each 0 < ε ε 0 and 0 < δ δ 0, there exists a constant C > 0 so that sup G ε (t) G(t) + sup G ε (t) G(t) 2 C{ ε 0 t τ 0 t τ δ + δ} where ε δ 0 as ε 0, and C depends only on τ and the initial data σ 0, u 0, θ 0.

Idea of Proof

Idea of Proof The acoustic system is the linearization about the homogeneous state [1, 0, 1] of the compressible Euler system t ρ + (u )ρ + ρ u = 0 ρ t u + ρ(u )u + ρ T + T ρ = 0 t T + (u )T + 2 3 T u = 0 (1)

Idea of Proof The acoustic system is the linearization about the homogeneous state [1, 0, 1] of the compressible Euler system t ρ + (u )ρ + ρ u = 0 ρ t u + ρ(u )u + ρ T + T ρ = 0 t T + (u )T + 2 3 T u = 0 (1) Instead of estimating G ε G directly, make a detour in two steps

Idea of Proof The acoustic system is the linearization about the homogeneous state [1, 0, 1] of the compressible Euler system t ρ + (u )ρ + ρ u = 0 ρ t u + ρ(u )u + ρ T + T ρ = 0 t T + (u )T + 2 3 T u = 0 (1) Instead of estimating G ε G directly, make a detour in two steps The first step is to show for µ δ = ρ δ (t,x) exp [2πT δ (t,x)] 3/2 F ε µ δ = O(ε) } { [v uδ (t,x)] 2 local Maxwellians 2T δ (t,x) defined from the solutions of (1) constructed from the acoustic initial data ρ 0 = 1 + δσ 0, u 0 = δu 0, T 0 = 1 + δθ 0

Idea of Proof The acoustic system is the linearization about the homogeneous state [1, 0, 1] of the compressible Euler system t ρ + (u )ρ + ρ u = 0 ρ t u + ρ(u )u + ρ T + T ρ = 0 t T + (u )T + 2 3 T u = 0 (1) Instead of estimating G ε G directly, make a detour in two steps The first step is to show for µ δ = ρ δ (t,x) exp [2πT δ (t,x)] 3/2 F ε µ δ = O(ε) } { [v uδ (t,x)] 2 local Maxwellians 2T δ (t,x) defined from the solutions of (1) constructed from the acoustic initial data ρ 0 = 1 + δσ 0, u 0 = δu 0, T 0 = 1 + δθ 0 before the time of possible shock formation, which is of the order of 1 δ in the acoustic scaling longer than any fixed time τ

Idea of Proof The second step is to show µ δ µ 0 = δg + O(δ 2 ) within the time scale of 1 δ

Idea of Proof The second step is to show µ δ µ 0 = δg + O(δ 2 ) within the time scale of 1 δ Such an estimate confirms that the solution G of the acoustic equation is the first order (linear) approximation of the Euler equations

Idea of Proof The second step is to show µ δ µ 0 = δg + O(δ 2 ) within the time scale of 1 δ Such an estimate confirms that the solution G of the acoustic equation is the first order (linear) approximation of the Euler equations The proof of Theorem : G ε (t) G(t) = F ε (t) µ 0 G(t) δ

Idea of Proof The second step is to show µ δ µ 0 = δg + O(δ 2 ) within the time scale of 1 δ Such an estimate confirms that the solution G of the acoustic equation is the first order (linear) approximation of the Euler equations The proof of Theorem : Rewrite F ε (t) µ 0 δ G ε (t) G(t) = F ε (t) µ 0 G(t) δ G(t) = F ε (t) µ δ (t) δ + µδ (t) µ 0 δg(t) δ Therefore, sup G ε (t) G(t) + sup G ε (t) G(t) 2 C{ ε 0 t τ 0 t τ δ + δ}

Refined Estimates of Acoustic and Euler solutions

Refined Estimates of Acoustic and Euler solutions Introduce difference variables (σd δ, uδ d, θδ d ) given by the second order perturbation in δ of Euler solutions ρ δ = 1 + δσ + δ 2 σ δ d, uδ = δu + δ 2 u δ d, T δ = 1 + δθ + δ 2 θ δ d

Refined Estimates of Acoustic and Euler solutions Introduce difference variables (σd δ, uδ d, θδ d ) given by the second order perturbation in δ of Euler solutions ρ δ = 1 + δσ + δ 2 σ δ d, uδ = δu + δ 2 u δ d, T δ = 1 + δθ + δ 2 θ δ d Indeed, (σd δ, uδ d, θδ d ) satisfy the linear system of equations t σ δ d + (u δ )σ δ d + ρ δ u δ d + δ[ σ u δ d + ( u)σ δ d] = (σu) ρ δ t u δ d + ρ δ (u δ )u δ d + ρ δ θ δ d + T δ σ δ d + δ[( t u)σ δ d + ρ δ (u δ d )u + θ δ d σ + σ δ d θ] = σ t u ρ δ (u )u (σθ) t θ δ d + (u δ )θ δ d + 2 3 T δ u δ d + δ[ θ u δ d + 2 3 ( u)θδ d] = u θ 2 3 θ u

Refined Estimates of Acoustic and Euler solutions Introduce difference variables (σd δ, uδ d, θδ d ) given by the second order perturbation in δ of Euler solutions ρ δ = 1 + δσ + δ 2 σ δ d, uδ = δu + δ 2 u δ d, T δ = 1 + δθ + δ 2 θ δ d Indeed, (σd δ, uδ d, θδ d ) satisfy the linear system of equations t σ δ d + (u δ )σ δ d + ρ δ u δ d + δ[ σ u δ d + ( u)σ δ d] = (σu) ρ δ t u δ d + ρ δ (u δ )u δ d + ρ δ θ δ d + T δ σ δ d + δ[( t u)σ δ d + ρ δ (u δ d )u + θ δ d σ + σ δ d θ] = σ t u ρ δ (u )u (σθ) t θ δ d + (u δ )θ δ d + 2 3 T δ u δ d + δ[ θ u δ d + 2 3 ( u)θδ d] = u θ 2 3 θ u The coefficients are smooth and have the uniform bounds up to time τ. The above system can be symmetrized.

Refined Estimates of Acoustic and Euler solutions Standard energy method of linear symmetric hyperbolic system (σd δ, uδ d, θδ d ) H s C (2) and thus (ρ δ 1 δσ, u δ δu, T δ 1 δθ) H s Cδ 2

Refined Estimates of Acoustic and Euler solutions Standard energy method of linear symmetric hyperbolic system and thus (σ δ d, uδ d, θδ d ) H s C (2) (ρ δ 1 δσ, u δ δu, T δ 1 δθ) H s Cδ 2 Consider µ δ as a function of δ and expand it around δ = 0 to derive µ δ (t) = µ 0 + Gδ + µ (δ ) δ 2 2 The uniform boundedness of µ (δ ) 2 + µ (δ ) follows from the uniform estimate (2)

Hilbert Expansion

Hilbert Expansion Following Caflisch, take the form F ε = 5 n=0 εn F n + ε 3 F ε R where F 0,..., F 5 solve the equations (F 0 = µ δ µ) 0 = Q(F 0, F 0 ) { t + v x }F 0 = Q(F 0, F 1 ) + Q(F 1, F 0 )... { t + v x }F 5 = Q(F 0, F 6 ) + Q(F 6, F 0 ) + i+j=6 1 i 5,1 j 5 Q(F i, F j )

Hilbert Expansion Following Caflisch, take the form F ε = 5 n=0 εn F n + ε 3 F ε R where F 0,..., F 5 solve the equations (F 0 = µ δ µ) 0 = Q(F 0, F 0 ) { t + v x }F 0 = Q(F 0, F 1 ) + Q(F 1, F 0 )... { t + v x }F 5 = Q(F 0, F 6 ) + Q(F 6, F 0 ) + Remainder equation for F ε R i+j=6 1 i 5,1 j 5 t F ε R + v xf ε R 1 ε {Q(µ, F ε R ) + Q(F ε R, µ)} Q(F i, F j ) 5 = ε 2 Q(FR ε, F R ε ) + ε i 1 {Q(F i, FR ε ) + Q(F R ε, F i)} + ε 2 A i=1

Compressible Euler Limit Theorem Assume that the solution to the Euler equations [ρ, u, T ] is smooth and ρ(t, x) has a positive lower bound for 0 t τ. Furthermore, assume that the temperature T (t, x) satisfies the condition T M < max T (t, x) < 2T M. Let t [0,τ],x Ω F ε (0, x, v) = µ(0, x, v) + 5 n=1 εn F n (0, x, v) + ε 3 FR ε (0, x, v) 0. Then

Compressible Euler Limit Theorem Assume that the solution to the Euler equations [ρ, u, T ] is smooth and ρ(t, x) has a positive lower bound for 0 t τ. Furthermore, assume that the temperature T (t, x) satisfies the condition T M < max T (t, x) < 2T M. Let t [0,τ],x Ω F ε (0, x, v) = µ(0, x, v) + 5 n=1 εn F n (0, x, v) + ε 3 FR ε (0, x, v) 0. Then there is an ε 0 > 0 such that for 0 < ε ε 0, and for any β 9 2γ 2, there exists a constant C τ (µ, F 1,..F 5 ) such that sup ε 3 2 (1 + v 2 ) β F R ε(t) + sup FR ε(t) 2 0 t τ µ 0 t τ µ C τ {ε 3 2 (1 + v 2 ) β F R ε (0) + FR ε(0) } 2 µ(0) + 1. µ(0)

Compressible Euler Limit Theorem Assume that the solution to the Euler equations [ρ, u, T ] is smooth and ρ(t, x) has a positive lower bound for 0 t τ. Furthermore, assume that the temperature T (t, x) satisfies the condition T M < max T (t, x) < 2T M. Let t [0,τ],x Ω F ε (0, x, v) = µ(0, x, v) + 5 n=1 εn F n (0, x, v) + ε 3 FR ε (0, x, v) 0. Then there is an ε 0 > 0 such that for 0 < ε ε 0, and for any β 9 2γ 2, there exists a constant C τ (µ, F 1,..F 5 ) such that sup ε 3 2 (1 + v 2 ) β F R ε(t) + sup FR ε(t) 2 0 t τ µ 0 t τ µ C τ {ε 3 2 (1 + v 2 ) β F R ε (0) + FR ε(0) } 2 µ(0) + 1. µ(0) Remark F ε = 5 n=0 εn F n + ε 3 F ε R = F ε µ δ = O(ε)

Proof of Euler Limit Introduce f ε F R ε and h ε {1 + v 2 } β µ F R ε µm } where β 9 2γ 1 2 and µ M = exp { v 2 (2πT M ) 3/2 2T M so that c 1 µ M µ c 2 µ α M for some 1/2 < α < 1

Proof of Euler Limit Introduce f ε F R ε and h ε {1 + v 2 } β µ F R ε µm } where β 9 2γ 1 2 and µ M = exp { v 2 (2πT M ) 3/2 2T M so that c 1 µ M µ c 2 µ α M for some 1/2 < α < 1 L 2 estimates for f ε t f ε + v x f ε + 1 ε Lf ε = { t + v x } µ µ f ε + ε 2 Γ(f ε, f ε ) + 5 i=1 Difficulty is coming from the boxed term v 3 f ε ε i 1 {Γ( F i, f ε ) + Γ(f ε F i, )} + ε 2 Ā µ µ

For any κ > 0 and a = 1/(3 γ) { t + v x } µ f ε, f ε = + µ v κ ε a v κ ε a { x ρ 2 + x u 2 + x T 2 } {1 + v 2 } 3/2 f ε 1 v κ ε a f ε 2 + { x ρ + x u + x T } {1 + v 2 } 3/4 f ε 1 v κ ε a 2 2 C κ ε 2 h ε f ε 2 + C {1 + v 2 } 3/4 Pf ε 1 v κ ε a 2 2 + C {1 + v 2 } 3/4 {I P}f ε 1 v κ ε a 2 2 C κ ε 2 h ε f ε 2 + C f ε 2 2 + Cκ3 γ {I P}f ε 2 ν ε Due to the fact {1 + v 2 } 3/2 f ε {1 + v 2 } γ 3 h ε for β 3/2 + (3 γ) and the fact µ M < Cµ

For any κ > 0 and a = 1/(3 γ) { t + v x } µ f ε, f ε = + µ v κ ε a v κ ε a { x ρ 2 + x u 2 + x T 2 } {1 + v 2 } 3/2 f ε 1 v κ ε a f ε 2 + { x ρ + x u + x T } {1 + v 2 } 3/4 f ε 1 v κ ε a 2 2 C κ ε 2 h ε f ε 2 + C {1 + v 2 } 3/4 Pf ε 1 v κ ε a 2 2 + C {1 + v 2 } 3/4 {I P}f ε 1 v κ ε a 2 2 C κ ε 2 h ε f ε 2 + C f ε 2 2 + Cκ3 γ {I P}f ε 2 ν ε Due to the fact {1 + v 2 } 3/2 f ε {1 + v 2 } γ 3 h ε for β 3/2 + (3 γ) and the fact µ M < Cµ d dt f ε 2 2 + δ 0 2ε {I P}f ε 2 ν C{ ε ε 3/2 h ε +1}( f ε 2 2 + f ε 2 )

L estimates for h ε sup {ε 3/2 h ε (s) } C{ ε 3/2 h 0 + sup f ε (s) 2 + ε 7/2 } 0 s τ 0 s τ

L estimates for h ε sup {ε 3/2 h ε (s) } C{ ε 3/2 h 0 + sup f ε (s) 2 + ε 7/2 } 0 s τ 0 s τ Following Caflisch, define L M g = 1 µm {Q(µ, µ M g) + Q( µ M g, µ)} = {ν(µ) + K}g where ν(µ) = R 3 S 2 b(v v, ω)µ(v )dv dω (1 + v ) γ

L estimates for h ε sup {ε 3/2 h ε (s) } C{ ε 3/2 h 0 + sup f ε (s) 2 + ε 7/2 } 0 s τ 0 s τ Following Caflisch, define L M g = 1 µm {Q(µ, µ M g) + Q( µ M g, µ)} = {ν(µ) + K}g where ν(µ) = R 3 S 2 b(v v, ω)µ(v )dv dω (1 + v ) γ To treat soft potentials, employ a cutoff trick of Guo and Strain

L estimates for h ε sup {ε 3/2 h ε (s) } C{ ε 3/2 h 0 + sup f ε (s) 2 + ε 7/2 } 0 s τ 0 s τ Following Caflisch, define L M g = 1 µm {Q(µ, µ M g) + Q( µ M g, µ)} = {ν(µ) + K}g where ν(µ) = R 3 S 2 b(v v, ω)µ(v )dv dω (1 + v ) γ To treat soft potentials, employ a cutoff trick of Guo and Strain Smooth cutoff function 0 χ m 1 such that for any m > 0, χ m (s) 1 for s m and χ m (s) 0 for s 2m. Split K = K m + K c. K m g(v) Cm 3+γ ν(µ) g and K c g(v) = R 3 l(v, v )g(v )dv where the kernel l satisfies l(v, v ) C m exp{ c v v 2 } v v (1 + v + v ) 1 γ.

Letting K w g wk( g w ) where w(v) = {1 + v 2 } β t h ε + v x h ε + ν(µ) ε hε + 1 ε K w h ε = ε2 w + 5 i=1 ε i 1 w {Q(F i, hε µ M µm w Q( hε µ M µm w, hε µ M ) w ) + Q( hε µ M, F i )} + ε 2 Ã, w

Letting K w g wk( g w ) where w(v) = {1 + v 2 } β t h ε + v x h ε + ν(µ) ε hε + 1 ε K w h ε = ε2 w + 5 i=1 ε i 1 By Duhamel s principle 0 w {Q(F i, hε µ M µm w Q( hε µ M µm w, hε µ M ) w ) + Q( hε µ M, F i )} + ε 2 Ã, w h ε (t, x, v) = exp{ νt ε }hε (0, x vt, v) t ( ) ν(t s) 1 exp{ } 0 ε ε K w m h ε (s, x v(t s), v)ds t ( ) ν(t s) 1 exp{ } 0 ε ε K w c h ε (s, x v(t s), v)ds t ( ν(t s) ε 2 w + exp{ } Q( hε µ M, hε ) µ M ) (s, x v(t s), v)ds ε µm w w +...

t ( ) ν(t s) 1 exp{ } 0 ε ε K w m h ε (s, x v(t s), v)ds t Cm 3+γ exp{ 0 ν(t s) } ν ds sup h ε (t) Cm 3+γ ε ε 0 t τ sup h ε (t) 0 t τ

t ( ) ν(t s) 1 exp{ } 0 ε ε K w m h ε (s, x v(t s), v)ds t Cm 3+γ exp{ 0 And since w µm Q( hε µm t 0 exp{ 0 ν(t s) } ν ds sup h ε (t) Cm 3+γ ε ε 0 t τ w, hε µm w ( ν(t s) ε 2 w } ε µm Q( hε µ M w ) Cν(µ) h ε 2 sup h ε (t) 0 t τ, hε ) µ M ) (s, x v(t s), v)ds w t Cε 2 ν(µ)(t s) exp{ }ν(µ) h ε (s) 2 ε ds Cε 3 sup h ε (s) 2 0 s t

t ( ) ν(t s) 1 exp{ } 0 ε ε K w m h ε (s, x v(t s), v)ds t Cm 3+γ exp{ 0 And since w µm Q( hε µm t 0 exp{ 0 ν(t s) } ν ds sup h ε (t) Cm 3+γ ε ε 0 t τ w, hε µm w ( ν(t s) ε 2 w } ε µm Q( hε µ M w ) Cν(µ) h ε 2 sup h ε (t) 0 t τ, hε ) µ M ) (s, x v(t s), v)ds w t Cε 2 ν(µ)(t s) exp{ }ν(µ) h ε (s) 2 ε ds Cε 3 sup h ε (s) 2 0 s t Let l w (v, v ) be the corresponding kernel associated with Kw c. t ( ) ν(t s) 1 exp{ } 0 ε ε K w c h ε (s, x v(t s), v)ds 1 t ν(t s) exp{ } l w (v, v )h ε (s, x v(t s), v ) dv ds ε 0 ε R 3

Use the Duhamel expression again 1 t ε exp{ 0 t ν(t s) } l w (v, v )h ε (s, x v(t s), v ) dv ds ε R 3 1 ν(t s) exp{ } sup l w (v, v ) dv ε 0 ε v R 3 exp{ νs ε }hε (0, x v(t s) v s, v )ds + 1 t ν(t s) ε 2 exp{ } l w (v, v ) ε R 3 s 0 0 + 1 ε 2 t s 0 +... exp{ ν(v )(s s 1 ) } {K m h ε }(s 1, x v(t s) v (s s 1 ), v ) dv ds 1 ds ε ν(t s) exp{ } ε 0 R 3 R 3 l w (v, v )l w (v, v ) exp{ ν(v )(s s 1 ) }h ε (s 1, x v(t s) v (s s 1 ), v ) dv dv ds 1 ds ε

The estimate for double l term : Divide into Case 1 : v N Case 2 : v N, v 2N or v 2N, v 3N Case 3a : v N, v 2N, v 3N, and s s 1 κε Case 3b : v N, v 2N, v 3N, and s s 1 κε

The estimate for double l term : Divide into Case 1 : v N Case 2 : v N, v 2N or v 2N, v 3N Case 3a : v N, v 2N, v 3N, and s s 1 κε Case 3b : v N, v 2N, v 3N, and s s 1 κε To see how to get f ε 2, in Case 3b, integrate over v to get C N h ε (s 1, x (s s 1 )v, v ) dv v 2N { } 1/2 C N 1 Ω (x (s s 1 )v ) h ε (s 1, x (s s 1 )v, v ) 2 dv v 2N C N κ 3/2 ε 3/2 { y x 1 (s s 1)3N C N{(s s 1 ) 3/2 + 1} κ 3/2 ε 3/2 h ε (s 1, y, v ) 2 dy { h ε (s 1, y, v ) 2 dy Ω } 1/2 } 1/2 Here we have made a change of variable y = x (s s 1 )v, and for s s 1 κε, dy dv 1 κ 3 ε 3

Thus approximate version of Case 3b C t 0 B C N,κ ε 7/2 C N,κ ε 7/2 C N,κ ε 3/2 s εκ 0 e ν(v)(t s) ε e ν(v )(s s 1 ) ε l N (v, v )l N (v, v ) h ε (s 1, x 1 (s s 1 )v, v ) ds 1 dv dv ds t s κε 0 0 v 3N t s κε 0 0 { v 3N e ν(v)(t s) ε e ν(v )(s s 1 ) ε {(s s 1 ) 3/2 + 1} { sup f ε (s) 2 0 s t 1/2 h ε (s 1, y, v ) dy} 2 dv ds 1 ds Ω e ν(v)(t s) ε e ν(v )(s s 1 ) ε {(s s 1 ) 3/2 + 1} Ω f ε (s 1, y, v ) 2 dydv } 1/2 ds 1 ds

Thus approximate version of Case 3b C t 0 B C N,κ ε 7/2 C N,κ ε 7/2 C N,κ ε 3/2 s εκ 0 e ν(v)(t s) ε e ν(v )(s s 1 ) ε l N (v, v )l N (v, v ) h ε (s 1, x 1 (s s 1 )v, v ) ds 1 dv dv ds t s κε 0 0 v 3N t s κε 0 0 { v 3N e ν(v)(t s) ε e ν(v )(s s 1 ) ε {(s s 1 ) 3/2 + 1} { sup f ε (s) 2 0 s t 1/2 h ε (s 1, y, v ) dy} 2 dv ds 1 ds Ω e ν(v)(t s) ε e ν(v )(s s 1 ) ε {(s s 1 ) 3/2 + 1} Ω f ε (s 1, y, v ) 2 dydv } 1/2 ds 1 ds In summary, one can obtain for any κ > 0 and large N > 0,

sup {ε 3/2 h ε (s) } {Cm γ+3 + C N,m κ + C m 0 s t N } sup {ε 3/2 h ε (s) } 0 s t +Cε 7/2 + C ε,n ε 3/2 h 0 + εc sup {ε 3/2 h ε (s) } 2 0 s t +C m,n,κ sup f ε (s) 2 0 s t

sup {ε 3/2 h ε (s) } {Cm γ+3 + C N,m κ + C m 0 s t N } sup {ε 3/2 h ε (s) } 0 s t +Cε 7/2 + C ε,n ε 3/2 h 0 + εc sup {ε 3/2 h ε (s) } 2 0 s t +C m,n,κ sup f ε (s) 2 0 s t For sufficiently small ε > 0, first choosing m small, then N sufficiently large, and finally letting κ small so that {Cm γ+3 + C N,m κ + Cm N } < 1 2, one gets sup {ε 3/2 h ε (s) } C{ ε 3/2 h 0 + sup f ε (s) 2 + ε 7/2 } 0 s τ 0 s τ and this completes the proof.