Computing a derivative through Lie series












3















Consider the $N$-dimensional autonomous system of ODEs
$$dot{x}= f(x),$$
where a locally unique solution $x(t)$, starting from the initial condition $x$, is denoted as $x(t)=phi(t,x)$. Assume that



$$Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$$



For the system above, assume that $f(x)$ is analytic (that is, its Taylor series converges to $f$ itself). Let the differential operator $L[xi]$ be defined as



$$L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$$



Show that $phi(t,x)$ can be expressed as



$$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



where $L^n[xi]$ is the shorthand notation for



$$L^n[xi]=underbrace{L[L[cdots{L}[xi]}_{ntext{-times}}cdots]]$$




Potentially related questions:





  • How to properly apply the Lie Series

  • Exponential of a function times derivative

  • How to derive these Lie Series formulas


I'm stuck on how to approach this problem. Here is all the information that I have gathered so far -



Through this question, the one dimensional situation states that $e^{apartial}f(x)=f(a+x)$ (we can think of this as a shift operator).



Inside Ordinary Differential Equations and Dynamical Systems by Teschl, we have the following Lemma (Lemma $6.2$ on page $190$ of the text).



Lemma (Straightening out of vector fields): Suppose $f(x_0)neq0$. Then, there is a local coordinate transform $y=varphi(x)$ such that $dot{x}=f(x)$ is transformed to



$$dot{y}=(1,0,...,0)$$



Teschl list a similar problem on page $191$ (problem $6.5$ for one-parameter lie groups) in which he states that



Hint: The Taylor coefficients are the derivatives which can be obtained by
differentiating the differential equation.



So, I think that I need to apply what was done in this question alongside Lemma 6.2. I will have to consider what a vector field means in this context. I might be able to make the assumption that a vector field is just a linear operator. We are given that





  1. $dot{x}= f(x)$ is an autonomous system of ODEs

  2. $x(t)=phi(t,x)$

  3. $Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$

  4. $L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$


and we need to show that



$$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



I also see that Roger Howe wrote a good introduction to lie theory in these notes (he goes through one-parameter lie groups on pages $604-606$).



This appears to be an extremely difficult problem for someone unfamiliar with lie theory. I am going to see if I can figure out a more direct approach.










share|cite|improve this question





























    3















    Consider the $N$-dimensional autonomous system of ODEs
    $$dot{x}= f(x),$$
    where a locally unique solution $x(t)$, starting from the initial condition $x$, is denoted as $x(t)=phi(t,x)$. Assume that



    $$Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$$



    For the system above, assume that $f(x)$ is analytic (that is, its Taylor series converges to $f$ itself). Let the differential operator $L[xi]$ be defined as



    $$L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$$



    Show that $phi(t,x)$ can be expressed as



    $$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



    where $L^n[xi]$ is the shorthand notation for



    $$L^n[xi]=underbrace{L[L[cdots{L}[xi]}_{ntext{-times}}cdots]]$$




    Potentially related questions:





    • How to properly apply the Lie Series

    • Exponential of a function times derivative

    • How to derive these Lie Series formulas


    I'm stuck on how to approach this problem. Here is all the information that I have gathered so far -



    Through this question, the one dimensional situation states that $e^{apartial}f(x)=f(a+x)$ (we can think of this as a shift operator).



    Inside Ordinary Differential Equations and Dynamical Systems by Teschl, we have the following Lemma (Lemma $6.2$ on page $190$ of the text).



    Lemma (Straightening out of vector fields): Suppose $f(x_0)neq0$. Then, there is a local coordinate transform $y=varphi(x)$ such that $dot{x}=f(x)$ is transformed to



    $$dot{y}=(1,0,...,0)$$



    Teschl list a similar problem on page $191$ (problem $6.5$ for one-parameter lie groups) in which he states that



    Hint: The Taylor coefficients are the derivatives which can be obtained by
    differentiating the differential equation.



    So, I think that I need to apply what was done in this question alongside Lemma 6.2. I will have to consider what a vector field means in this context. I might be able to make the assumption that a vector field is just a linear operator. We are given that





    1. $dot{x}= f(x)$ is an autonomous system of ODEs

    2. $x(t)=phi(t,x)$

    3. $Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$

    4. $L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$


    and we need to show that



    $$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



    I also see that Roger Howe wrote a good introduction to lie theory in these notes (he goes through one-parameter lie groups on pages $604-606$).



    This appears to be an extremely difficult problem for someone unfamiliar with lie theory. I am going to see if I can figure out a more direct approach.










    share|cite|improve this question



























      3












      3








      3








      Consider the $N$-dimensional autonomous system of ODEs
      $$dot{x}= f(x),$$
      where a locally unique solution $x(t)$, starting from the initial condition $x$, is denoted as $x(t)=phi(t,x)$. Assume that



      $$Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$$



      For the system above, assume that $f(x)$ is analytic (that is, its Taylor series converges to $f$ itself). Let the differential operator $L[xi]$ be defined as



      $$L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$$



      Show that $phi(t,x)$ can be expressed as



      $$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



      where $L^n[xi]$ is the shorthand notation for



      $$L^n[xi]=underbrace{L[L[cdots{L}[xi]}_{ntext{-times}}cdots]]$$




      Potentially related questions:





      • How to properly apply the Lie Series

      • Exponential of a function times derivative

      • How to derive these Lie Series formulas


      I'm stuck on how to approach this problem. Here is all the information that I have gathered so far -



      Through this question, the one dimensional situation states that $e^{apartial}f(x)=f(a+x)$ (we can think of this as a shift operator).



      Inside Ordinary Differential Equations and Dynamical Systems by Teschl, we have the following Lemma (Lemma $6.2$ on page $190$ of the text).



      Lemma (Straightening out of vector fields): Suppose $f(x_0)neq0$. Then, there is a local coordinate transform $y=varphi(x)$ such that $dot{x}=f(x)$ is transformed to



      $$dot{y}=(1,0,...,0)$$



      Teschl list a similar problem on page $191$ (problem $6.5$ for one-parameter lie groups) in which he states that



      Hint: The Taylor coefficients are the derivatives which can be obtained by
      differentiating the differential equation.



      So, I think that I need to apply what was done in this question alongside Lemma 6.2. I will have to consider what a vector field means in this context. I might be able to make the assumption that a vector field is just a linear operator. We are given that





      1. $dot{x}= f(x)$ is an autonomous system of ODEs

      2. $x(t)=phi(t,x)$

      3. $Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$

      4. $L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$


      and we need to show that



      $$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



      I also see that Roger Howe wrote a good introduction to lie theory in these notes (he goes through one-parameter lie groups on pages $604-606$).



      This appears to be an extremely difficult problem for someone unfamiliar with lie theory. I am going to see if I can figure out a more direct approach.










      share|cite|improve this question
















      Consider the $N$-dimensional autonomous system of ODEs
      $$dot{x}= f(x),$$
      where a locally unique solution $x(t)$, starting from the initial condition $x$, is denoted as $x(t)=phi(t,x)$. Assume that



      $$Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$$



      For the system above, assume that $f(x)$ is analytic (that is, its Taylor series converges to $f$ itself). Let the differential operator $L[xi]$ be defined as



      $$L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$$



      Show that $phi(t,x)$ can be expressed as



      $$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



      where $L^n[xi]$ is the shorthand notation for



      $$L^n[xi]=underbrace{L[L[cdots{L}[xi]}_{ntext{-times}}cdots]]$$




      Potentially related questions:





      • How to properly apply the Lie Series

      • Exponential of a function times derivative

      • How to derive these Lie Series formulas


      I'm stuck on how to approach this problem. Here is all the information that I have gathered so far -



      Through this question, the one dimensional situation states that $e^{apartial}f(x)=f(a+x)$ (we can think of this as a shift operator).



      Inside Ordinary Differential Equations and Dynamical Systems by Teschl, we have the following Lemma (Lemma $6.2$ on page $190$ of the text).



      Lemma (Straightening out of vector fields): Suppose $f(x_0)neq0$. Then, there is a local coordinate transform $y=varphi(x)$ such that $dot{x}=f(x)$ is transformed to



      $$dot{y}=(1,0,...,0)$$



      Teschl list a similar problem on page $191$ (problem $6.5$ for one-parameter lie groups) in which he states that



      Hint: The Taylor coefficients are the derivatives which can be obtained by
      differentiating the differential equation.



      So, I think that I need to apply what was done in this question alongside Lemma 6.2. I will have to consider what a vector field means in this context. I might be able to make the assumption that a vector field is just a linear operator. We are given that





      1. $dot{x}= f(x)$ is an autonomous system of ODEs

      2. $x(t)=phi(t,x)$

      3. $Big(frac{partial}{partial{x}}phi(t,x)Big)f(x)=f(phi(t,x))$

      4. $L[xi]=f(x)boldsymbol{cdot}nabla{xi}=sum_{n=1}^{N}f_i(x)frac{partial{xi}}{partial{x_i}}$


      and we need to show that



      $$phi(t,x)=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$



      I also see that Roger Howe wrote a good introduction to lie theory in these notes (he goes through one-parameter lie groups on pages $604-606$).



      This appears to be an extremely difficult problem for someone unfamiliar with lie theory. I am going to see if I can figure out a more direct approach.







      differential-equations lie-groups differential-operators






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited 2 days ago









      Bernard

      118k639112




      118k639112










      asked 2 days ago









      Axion004

      279212




      279212






















          2 Answers
          2






          active

          oldest

          votes


















          0














          For any differentiable function $B:Bbb R^ntoBbb R^n$ we know from chain rule and differential equation that
          begin{align}
          frac{∂}{∂t}B(ϕ(t,x))&=frac{∂B}{∂x}(ϕ(t,x))cdot frac{∂}{∂t}ϕ(t,x)
          \
          &=frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))
          \
          &=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B].
          end{align}

          So along a solution we get $frac{∂}{∂t}=L_{ϕ(t,x)}$. Now apply this to the translation operator resp. the Taylor expansion
          $$
          ϕ(t,x)=expleft(tfrac{∂}{∂s}right)ϕ(s,x)Big|_{s=0}
          =expleft(tL_{ϕ(s,x)}right)[ϕ(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]Big|_{s=0}
          $$

          The same remains true if you replace the exponential by the exponential series.






          share|cite|improve this answer





















          • I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
            – Axion004
            yesterday












          • Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
            – LutzL
            yesterday










          • Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
            – Axion004
            12 hours ago










          • I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
            – Axion004
            10 hours ago












          • This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
            – LutzL
            4 hours ago



















          0














          Here is my interpretation of the first answer.



          Suppose we have a differentiable function $xi:Bbb R^ntoBbb R^n$ where $frac{partial}{partial{t}}phi(t,x)=f(phi(t,x))$. We know by the chain rule that
          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(phi(t,x))cdot frac{partial}{partial{t}}phi(t,x)
          \
          &=frac{partialxi}{partial{x}}(phi(t,x))cdot f(phi(t,x))
          \
          &=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))
          end{align*}



          where $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}$ is the directional derivative of the function $xi$ in the direction of f. This is defined as



          $$dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$$



          Therefore,



          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))\
          &=sum_{i=1}^n frac{partialxi}{partial{x_i}}(x(t)) f_i(x(t))
          \&=sum_{i=1}^n f_i(phi(t,x))frac{partialxi}{partial{x_i}}(phi(t,x))
          =L_{phi(t,x)}[xi]
          end{align*}



          So along a solution we get $frac{partial}{partial{t}}=L_{phi(t,x)}$. Next, apply this to the translation operator via the Taylor expansion
          $$
          phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}
          =expleft(tL_{phi(s,x)}right)[phi(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]
          $$

          If we then replace the exponential with the exponential series, we have
          $$
          phi(t,x)=expleft(tL_{x}right)[x]=Big(sum_{n = 0}^{infty} frac{left(tL_{x}right)^n}{n!}Big)[x]=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$





          Note: I am trying to justify that



          $$phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$$



          I don't see how to get to this equality from



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$$



          We have that



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(x)$$



          So,



          $$frac{partial}{partial{x}}phi(t,x)=1$$



          But, any further manipulation that I can think of does not lead to $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. The derivation must be related to the Taylor series expansion.






          share|cite|improve this answer























          • $h$ is a scalar, like $t$. There is no $h_i$.
            – LutzL
            13 hours ago











          Your Answer





          StackExchange.ifUsing("editor", function () {
          return StackExchange.using("mathjaxEditing", function () {
          StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
          StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
          });
          });
          }, "mathjax-editing");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "69"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: true,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: 10,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          noCode: true, onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });














          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3060913%2fcomputing-a-derivative-through-lie-series%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          2 Answers
          2






          active

          oldest

          votes








          2 Answers
          2






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          0














          For any differentiable function $B:Bbb R^ntoBbb R^n$ we know from chain rule and differential equation that
          begin{align}
          frac{∂}{∂t}B(ϕ(t,x))&=frac{∂B}{∂x}(ϕ(t,x))cdot frac{∂}{∂t}ϕ(t,x)
          \
          &=frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))
          \
          &=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B].
          end{align}

          So along a solution we get $frac{∂}{∂t}=L_{ϕ(t,x)}$. Now apply this to the translation operator resp. the Taylor expansion
          $$
          ϕ(t,x)=expleft(tfrac{∂}{∂s}right)ϕ(s,x)Big|_{s=0}
          =expleft(tL_{ϕ(s,x)}right)[ϕ(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]Big|_{s=0}
          $$

          The same remains true if you replace the exponential by the exponential series.






          share|cite|improve this answer





















          • I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
            – Axion004
            yesterday












          • Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
            – LutzL
            yesterday










          • Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
            – Axion004
            12 hours ago










          • I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
            – Axion004
            10 hours ago












          • This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
            – LutzL
            4 hours ago
















          0














          For any differentiable function $B:Bbb R^ntoBbb R^n$ we know from chain rule and differential equation that
          begin{align}
          frac{∂}{∂t}B(ϕ(t,x))&=frac{∂B}{∂x}(ϕ(t,x))cdot frac{∂}{∂t}ϕ(t,x)
          \
          &=frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))
          \
          &=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B].
          end{align}

          So along a solution we get $frac{∂}{∂t}=L_{ϕ(t,x)}$. Now apply this to the translation operator resp. the Taylor expansion
          $$
          ϕ(t,x)=expleft(tfrac{∂}{∂s}right)ϕ(s,x)Big|_{s=0}
          =expleft(tL_{ϕ(s,x)}right)[ϕ(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]Big|_{s=0}
          $$

          The same remains true if you replace the exponential by the exponential series.






          share|cite|improve this answer





















          • I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
            – Axion004
            yesterday












          • Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
            – LutzL
            yesterday










          • Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
            – Axion004
            12 hours ago










          • I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
            – Axion004
            10 hours ago












          • This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
            – LutzL
            4 hours ago














          0












          0








          0






          For any differentiable function $B:Bbb R^ntoBbb R^n$ we know from chain rule and differential equation that
          begin{align}
          frac{∂}{∂t}B(ϕ(t,x))&=frac{∂B}{∂x}(ϕ(t,x))cdot frac{∂}{∂t}ϕ(t,x)
          \
          &=frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))
          \
          &=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B].
          end{align}

          So along a solution we get $frac{∂}{∂t}=L_{ϕ(t,x)}$. Now apply this to the translation operator resp. the Taylor expansion
          $$
          ϕ(t,x)=expleft(tfrac{∂}{∂s}right)ϕ(s,x)Big|_{s=0}
          =expleft(tL_{ϕ(s,x)}right)[ϕ(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]Big|_{s=0}
          $$

          The same remains true if you replace the exponential by the exponential series.






          share|cite|improve this answer












          For any differentiable function $B:Bbb R^ntoBbb R^n$ we know from chain rule and differential equation that
          begin{align}
          frac{∂}{∂t}B(ϕ(t,x))&=frac{∂B}{∂x}(ϕ(t,x))cdot frac{∂}{∂t}ϕ(t,x)
          \
          &=frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))
          \
          &=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B].
          end{align}

          So along a solution we get $frac{∂}{∂t}=L_{ϕ(t,x)}$. Now apply this to the translation operator resp. the Taylor expansion
          $$
          ϕ(t,x)=expleft(tfrac{∂}{∂s}right)ϕ(s,x)Big|_{s=0}
          =expleft(tL_{ϕ(s,x)}right)[ϕ(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]Big|_{s=0}
          $$

          The same remains true if you replace the exponential by the exponential series.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered 2 days ago









          LutzL

          56.4k42054




          56.4k42054












          • I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
            – Axion004
            yesterday












          • Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
            – LutzL
            yesterday










          • Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
            – Axion004
            12 hours ago










          • I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
            – Axion004
            10 hours ago












          • This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
            – LutzL
            4 hours ago


















          • I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
            – Axion004
            yesterday












          • Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
            – LutzL
            yesterday










          • Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
            – Axion004
            12 hours ago










          • I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
            – Axion004
            10 hours ago












          • This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
            – LutzL
            4 hours ago
















          I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
          – Axion004
          yesterday






          I'm having trouble following $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. For the first equality, $frac{∂B}{∂x}(ϕ(t,x))cdot f(ϕ(t,x))=sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))$, you must be taking a partial derivative in every direction (since we are working in $Bbb R^n$). I don't see how one can justify $sum_{i=1}^n frac{∂B}{∂x_i}(ϕ(t,x)) f_i(ϕ(t,x))=L_{ϕ(t,x)}[B]$. This must follow from the definition of the differential operator.
          – Axion004
          yesterday














          Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
          – LutzL
          yesterday




          Simple manipulation of linear Taylor polynomials gives $$B(x(t+h))=B(x(t)+f(x(t))h+O(h^2)=B(x(t))+B'(x(t))f(x(t))h+O(h^2).$$ Inside $B'(x)v$ with $v=f(x)h$ is the directional derivative in direction $v$, $B'(x)v=sum v_ifrac∂{∂x_i}B(x)$. Replacing back $v=f(x)h$ gives exactly the definition of $L$, so that $B(x(t+h))=B(x(t))+L[B](x(t))h+O(h^2)$. There is nothing more to it.
          – LutzL
          yesterday












          Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
          – Axion004
          12 hours ago




          Perhaps, to avoid using the Taylor series expansion, one could apply the definition of the directional derivative and conclude that $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$.
          – Axion004
          12 hours ago












          I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
          – Axion004
          10 hours ago






          I'm guessing that there is a logical reason why $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. I tried reviewing it tonight and couldn't see how this was formed. I coudn't derive this starting from $frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$.
          – Axion004
          10 hours ago














          This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
          – LutzL
          4 hours ago




          This is just the simple Taylor expansion $x(t)=sumfrac{x^{(k)}}{k!}t^k=(exp(tD)x)(0)$. $t$ is here a constant, so it looks bad to have the derivative for $t$, thus changing it to $s$.
          – LutzL
          4 hours ago











          0














          Here is my interpretation of the first answer.



          Suppose we have a differentiable function $xi:Bbb R^ntoBbb R^n$ where $frac{partial}{partial{t}}phi(t,x)=f(phi(t,x))$. We know by the chain rule that
          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(phi(t,x))cdot frac{partial}{partial{t}}phi(t,x)
          \
          &=frac{partialxi}{partial{x}}(phi(t,x))cdot f(phi(t,x))
          \
          &=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))
          end{align*}



          where $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}$ is the directional derivative of the function $xi$ in the direction of f. This is defined as



          $$dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$$



          Therefore,



          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))\
          &=sum_{i=1}^n frac{partialxi}{partial{x_i}}(x(t)) f_i(x(t))
          \&=sum_{i=1}^n f_i(phi(t,x))frac{partialxi}{partial{x_i}}(phi(t,x))
          =L_{phi(t,x)}[xi]
          end{align*}



          So along a solution we get $frac{partial}{partial{t}}=L_{phi(t,x)}$. Next, apply this to the translation operator via the Taylor expansion
          $$
          phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}
          =expleft(tL_{phi(s,x)}right)[phi(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]
          $$

          If we then replace the exponential with the exponential series, we have
          $$
          phi(t,x)=expleft(tL_{x}right)[x]=Big(sum_{n = 0}^{infty} frac{left(tL_{x}right)^n}{n!}Big)[x]=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$





          Note: I am trying to justify that



          $$phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$$



          I don't see how to get to this equality from



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$$



          We have that



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(x)$$



          So,



          $$frac{partial}{partial{x}}phi(t,x)=1$$



          But, any further manipulation that I can think of does not lead to $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. The derivation must be related to the Taylor series expansion.






          share|cite|improve this answer























          • $h$ is a scalar, like $t$. There is no $h_i$.
            – LutzL
            13 hours ago
















          0














          Here is my interpretation of the first answer.



          Suppose we have a differentiable function $xi:Bbb R^ntoBbb R^n$ where $frac{partial}{partial{t}}phi(t,x)=f(phi(t,x))$. We know by the chain rule that
          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(phi(t,x))cdot frac{partial}{partial{t}}phi(t,x)
          \
          &=frac{partialxi}{partial{x}}(phi(t,x))cdot f(phi(t,x))
          \
          &=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))
          end{align*}



          where $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}$ is the directional derivative of the function $xi$ in the direction of f. This is defined as



          $$dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$$



          Therefore,



          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))\
          &=sum_{i=1}^n frac{partialxi}{partial{x_i}}(x(t)) f_i(x(t))
          \&=sum_{i=1}^n f_i(phi(t,x))frac{partialxi}{partial{x_i}}(phi(t,x))
          =L_{phi(t,x)}[xi]
          end{align*}



          So along a solution we get $frac{partial}{partial{t}}=L_{phi(t,x)}$. Next, apply this to the translation operator via the Taylor expansion
          $$
          phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}
          =expleft(tL_{phi(s,x)}right)[phi(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]
          $$

          If we then replace the exponential with the exponential series, we have
          $$
          phi(t,x)=expleft(tL_{x}right)[x]=Big(sum_{n = 0}^{infty} frac{left(tL_{x}right)^n}{n!}Big)[x]=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$





          Note: I am trying to justify that



          $$phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$$



          I don't see how to get to this equality from



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$$



          We have that



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(x)$$



          So,



          $$frac{partial}{partial{x}}phi(t,x)=1$$



          But, any further manipulation that I can think of does not lead to $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. The derivation must be related to the Taylor series expansion.






          share|cite|improve this answer























          • $h$ is a scalar, like $t$. There is no $h_i$.
            – LutzL
            13 hours ago














          0












          0








          0






          Here is my interpretation of the first answer.



          Suppose we have a differentiable function $xi:Bbb R^ntoBbb R^n$ where $frac{partial}{partial{t}}phi(t,x)=f(phi(t,x))$. We know by the chain rule that
          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(phi(t,x))cdot frac{partial}{partial{t}}phi(t,x)
          \
          &=frac{partialxi}{partial{x}}(phi(t,x))cdot f(phi(t,x))
          \
          &=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))
          end{align*}



          where $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}$ is the directional derivative of the function $xi$ in the direction of f. This is defined as



          $$dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$$



          Therefore,



          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))\
          &=sum_{i=1}^n frac{partialxi}{partial{x_i}}(x(t)) f_i(x(t))
          \&=sum_{i=1}^n f_i(phi(t,x))frac{partialxi}{partial{x_i}}(phi(t,x))
          =L_{phi(t,x)}[xi]
          end{align*}



          So along a solution we get $frac{partial}{partial{t}}=L_{phi(t,x)}$. Next, apply this to the translation operator via the Taylor expansion
          $$
          phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}
          =expleft(tL_{phi(s,x)}right)[phi(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]
          $$

          If we then replace the exponential with the exponential series, we have
          $$
          phi(t,x)=expleft(tL_{x}right)[x]=Big(sum_{n = 0}^{infty} frac{left(tL_{x}right)^n}{n!}Big)[x]=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$





          Note: I am trying to justify that



          $$phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$$



          I don't see how to get to this equality from



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$$



          We have that



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(x)$$



          So,



          $$frac{partial}{partial{x}}phi(t,x)=1$$



          But, any further manipulation that I can think of does not lead to $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. The derivation must be related to the Taylor series expansion.






          share|cite|improve this answer














          Here is my interpretation of the first answer.



          Suppose we have a differentiable function $xi:Bbb R^ntoBbb R^n$ where $frac{partial}{partial{t}}phi(t,x)=f(phi(t,x))$. We know by the chain rule that
          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(phi(t,x))cdot frac{partial}{partial{t}}phi(t,x)
          \
          &=frac{partialxi}{partial{x}}(phi(t,x))cdot f(phi(t,x))
          \
          &=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))
          end{align*}



          where $dfrac{partialxi(x)}{partial{x}}cdot{f(x)}$ is the directional derivative of the function $xi$ in the direction of f. This is defined as



          $$dfrac{partialxi(x)}{partial{x}}cdot{f(x)}=nabla{xi(x)}boldsymbol{cdot}f(x)=sum_{n=1}^{N}frac{partial{xi}}{partial{x_i}}f_i(x)$$



          Therefore,



          begin{align*}
          frac{partial}{partial{t}}xi(phi(t,x))&=frac{partialxi}{partial{x}}(x(t))cdot f(x(t))\
          &=sum_{i=1}^n frac{partialxi}{partial{x_i}}(x(t)) f_i(x(t))
          \&=sum_{i=1}^n f_i(phi(t,x))frac{partialxi}{partial{x_i}}(phi(t,x))
          =L_{phi(t,x)}[xi]
          end{align*}



          So along a solution we get $frac{partial}{partial{t}}=L_{phi(t,x)}$. Next, apply this to the translation operator via the Taylor expansion
          $$
          phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}
          =expleft(tL_{phi(s,x)}right)[phi(s,x)]Big|_{s=0}
          =expleft(tL_{x}right)[x]
          $$

          If we then replace the exponential with the exponential series, we have
          $$
          phi(t,x)=expleft(tL_{x}right)[x]=Big(sum_{n = 0}^{infty} frac{left(tL_{x}right)^n}{n!}Big)[x]=sum_{n=0}^{infty}frac{t^n}{n!}L^n[x]$$





          Note: I am trying to justify that



          $$phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$$



          I don't see how to get to this equality from



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(phi(t,x))$$



          We have that



          $$frac{partial}{partial{x}}phi(t,x)f(x)=f(x)$$



          So,



          $$frac{partial}{partial{x}}phi(t,x)=1$$



          But, any further manipulation that I can think of does not lead to $phi(t,x)=expleft(tfrac{partial}{partial{s}}right)phi(s,x)Big|_{s=0}$. The derivation must be related to the Taylor series expansion.







          share|cite|improve this answer














          share|cite|improve this answer



          share|cite|improve this answer








          edited 10 hours ago

























          answered 15 hours ago









          Axion004

          279212




          279212












          • $h$ is a scalar, like $t$. There is no $h_i$.
            – LutzL
            13 hours ago


















          • $h$ is a scalar, like $t$. There is no $h_i$.
            – LutzL
            13 hours ago
















          $h$ is a scalar, like $t$. There is no $h_i$.
          – LutzL
          13 hours ago




          $h$ is a scalar, like $t$. There is no $h_i$.
          – LutzL
          13 hours ago


















          draft saved

          draft discarded




















































          Thanks for contributing an answer to Mathematics Stack Exchange!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          Use MathJax to format equations. MathJax reference.


          To learn more, see our tips on writing great answers.





          Some of your past answers have not been well-received, and you're in danger of being blocked from answering.


          Please pay close attention to the following guidance:


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3060913%2fcomputing-a-derivative-through-lie-series%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          Popular posts from this blog

          An IMO inspired problem

          Management

          Investment