$operatornamegrad(f)$ definition and extra basis term.

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Some preliminary definitions. On page 342 of Lee's Smooth Manifold he concludes that $hatg(operatornamegrad f)(X) = Xf$ where $hatg$ is the isomorphism between $TM to T^*M$, the tangent bundle and co-tangent bundle.



Now according to Lee, $hatg^-1(omega) = g^ijomega_j fracpartial partial x^j$



But what I found is that,




beginalign hatg(hatg^-1(df))(X)
&=hatg(g^ijfracpartial fpartial x^j fracpartial partial
x^j)(X)\
&=g_ijg^ijfracpartial fpartial x^jfracpartial partial
x^j X^i\ &=fracpartial fpartial x^jfracpartial partial
x^j X^i \ &= X^i fracpartial fpartial x^j fracpartial
partial x^j textbecause g is symmetric, so we can bring X to the
front
endalign




But $Xf = X^i(x)fracpartial fpartial x^j$. So there is an extra basis term coming out of my reduction. What's going on?







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    up vote
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    Some preliminary definitions. On page 342 of Lee's Smooth Manifold he concludes that $hatg(operatornamegrad f)(X) = Xf$ where $hatg$ is the isomorphism between $TM to T^*M$, the tangent bundle and co-tangent bundle.



    Now according to Lee, $hatg^-1(omega) = g^ijomega_j fracpartial partial x^j$



    But what I found is that,




    beginalign hatg(hatg^-1(df))(X)
    &=hatg(g^ijfracpartial fpartial x^j fracpartial partial
    x^j)(X)\
    &=g_ijg^ijfracpartial fpartial x^jfracpartial partial
    x^j X^i\ &=fracpartial fpartial x^jfracpartial partial
    x^j X^i \ &= X^i fracpartial fpartial x^j fracpartial
    partial x^j textbecause g is symmetric, so we can bring X to the
    front
    endalign




    But $Xf = X^i(x)fracpartial fpartial x^j$. So there is an extra basis term coming out of my reduction. What's going on?







    share|cite|improve this question
























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      Some preliminary definitions. On page 342 of Lee's Smooth Manifold he concludes that $hatg(operatornamegrad f)(X) = Xf$ where $hatg$ is the isomorphism between $TM to T^*M$, the tangent bundle and co-tangent bundle.



      Now according to Lee, $hatg^-1(omega) = g^ijomega_j fracpartial partial x^j$



      But what I found is that,




      beginalign hatg(hatg^-1(df))(X)
      &=hatg(g^ijfracpartial fpartial x^j fracpartial partial
      x^j)(X)\
      &=g_ijg^ijfracpartial fpartial x^jfracpartial partial
      x^j X^i\ &=fracpartial fpartial x^jfracpartial partial
      x^j X^i \ &= X^i fracpartial fpartial x^j fracpartial
      partial x^j textbecause g is symmetric, so we can bring X to the
      front
      endalign




      But $Xf = X^i(x)fracpartial fpartial x^j$. So there is an extra basis term coming out of my reduction. What's going on?







      share|cite|improve this question














      Some preliminary definitions. On page 342 of Lee's Smooth Manifold he concludes that $hatg(operatornamegrad f)(X) = Xf$ where $hatg$ is the isomorphism between $TM to T^*M$, the tangent bundle and co-tangent bundle.



      Now according to Lee, $hatg^-1(omega) = g^ijomega_j fracpartial partial x^j$



      But what I found is that,




      beginalign hatg(hatg^-1(df))(X)
      &=hatg(g^ijfracpartial fpartial x^j fracpartial partial
      x^j)(X)\
      &=g_ijg^ijfracpartial fpartial x^jfracpartial partial
      x^j X^i\ &=fracpartial fpartial x^jfracpartial partial
      x^j X^i \ &= X^i fracpartial fpartial x^j fracpartial
      partial x^j textbecause g is symmetric, so we can bring X to the
      front
      endalign




      But $Xf = X^i(x)fracpartial fpartial x^j$. So there is an extra basis term coming out of my reduction. What's going on?









      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Aug 19 at 9:02









      Stefan4024

      29.2k53276




      29.2k53276










      asked Aug 19 at 7:37









      Hawk

      5,27393699




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          First of all you have mixed the indices a bit. In the first line we should have



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^colorrediright) X$$



          For the second line you shouldn't keep $Y=g^ijfracpartial fpartial x^jfracpartial partial x^i$ when you evaluate $g$. Instead you should just take the $k$-th component. This is explicitly stated at the beggining of p. 342. Indeed $hatg(Y)(X)$ should produce a number, not a vector like in your case. Thus we would get:



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^iright) X = g_ik X^i g^kjfracpartial fpartial x^j = delta^j_i X^i fracpartial fpartial x^j = X^ifracpartial fpartial x^i = Xf$$



          Note that $Xf = X^ifracpartial fpartial x^colorredi$, not $Xf = X^ifracpartial fpartial x^j$, as you have mentioned in the last line.



          REMARK: The reason why I take the $k$-th component is because we have already used $j$ for the coordinate representation of $hatg^-1(df)$. Thus $g(X)(Y) = g_ijX^iY^k$. In fact I believe that this is the reason behind your confusion in the probem.






          share|cite|improve this answer




















          • Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
            – Hawk
            Aug 19 at 9:16










          • @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
            – Stefan4024
            Aug 19 at 10:21










          • @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
            – Stefan4024
            Aug 19 at 10:34







          • 1




            @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
            – Stefan4024
            Aug 19 at 10:34











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          First of all you have mixed the indices a bit. In the first line we should have



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^colorrediright) X$$



          For the second line you shouldn't keep $Y=g^ijfracpartial fpartial x^jfracpartial partial x^i$ when you evaluate $g$. Instead you should just take the $k$-th component. This is explicitly stated at the beggining of p. 342. Indeed $hatg(Y)(X)$ should produce a number, not a vector like in your case. Thus we would get:



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^iright) X = g_ik X^i g^kjfracpartial fpartial x^j = delta^j_i X^i fracpartial fpartial x^j = X^ifracpartial fpartial x^i = Xf$$



          Note that $Xf = X^ifracpartial fpartial x^colorredi$, not $Xf = X^ifracpartial fpartial x^j$, as you have mentioned in the last line.



          REMARK: The reason why I take the $k$-th component is because we have already used $j$ for the coordinate representation of $hatg^-1(df)$. Thus $g(X)(Y) = g_ijX^iY^k$. In fact I believe that this is the reason behind your confusion in the probem.






          share|cite|improve this answer




















          • Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
            – Hawk
            Aug 19 at 9:16










          • @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
            – Stefan4024
            Aug 19 at 10:21










          • @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
            – Stefan4024
            Aug 19 at 10:34







          • 1




            @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
            – Stefan4024
            Aug 19 at 10:34















          up vote
          1
          down vote



          accepted










          First of all you have mixed the indices a bit. In the first line we should have



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^colorrediright) X$$



          For the second line you shouldn't keep $Y=g^ijfracpartial fpartial x^jfracpartial partial x^i$ when you evaluate $g$. Instead you should just take the $k$-th component. This is explicitly stated at the beggining of p. 342. Indeed $hatg(Y)(X)$ should produce a number, not a vector like in your case. Thus we would get:



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^iright) X = g_ik X^i g^kjfracpartial fpartial x^j = delta^j_i X^i fracpartial fpartial x^j = X^ifracpartial fpartial x^i = Xf$$



          Note that $Xf = X^ifracpartial fpartial x^colorredi$, not $Xf = X^ifracpartial fpartial x^j$, as you have mentioned in the last line.



          REMARK: The reason why I take the $k$-th component is because we have already used $j$ for the coordinate representation of $hatg^-1(df)$. Thus $g(X)(Y) = g_ijX^iY^k$. In fact I believe that this is the reason behind your confusion in the probem.






          share|cite|improve this answer




















          • Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
            – Hawk
            Aug 19 at 9:16










          • @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
            – Stefan4024
            Aug 19 at 10:21










          • @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
            – Stefan4024
            Aug 19 at 10:34







          • 1




            @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
            – Stefan4024
            Aug 19 at 10:34













          up vote
          1
          down vote



          accepted







          up vote
          1
          down vote



          accepted






          First of all you have mixed the indices a bit. In the first line we should have



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^colorrediright) X$$



          For the second line you shouldn't keep $Y=g^ijfracpartial fpartial x^jfracpartial partial x^i$ when you evaluate $g$. Instead you should just take the $k$-th component. This is explicitly stated at the beggining of p. 342. Indeed $hatg(Y)(X)$ should produce a number, not a vector like in your case. Thus we would get:



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^iright) X = g_ik X^i g^kjfracpartial fpartial x^j = delta^j_i X^i fracpartial fpartial x^j = X^ifracpartial fpartial x^i = Xf$$



          Note that $Xf = X^ifracpartial fpartial x^colorredi$, not $Xf = X^ifracpartial fpartial x^j$, as you have mentioned in the last line.



          REMARK: The reason why I take the $k$-th component is because we have already used $j$ for the coordinate representation of $hatg^-1(df)$. Thus $g(X)(Y) = g_ijX^iY^k$. In fact I believe that this is the reason behind your confusion in the probem.






          share|cite|improve this answer












          First of all you have mixed the indices a bit. In the first line we should have



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^colorrediright) X$$



          For the second line you shouldn't keep $Y=g^ijfracpartial fpartial x^jfracpartial partial x^i$ when you evaluate $g$. Instead you should just take the $k$-th component. This is explicitly stated at the beggining of p. 342. Indeed $hatg(Y)(X)$ should produce a number, not a vector like in your case. Thus we would get:



          $$hatg(hatg^-1(df))(X)
          =hatgleft(g^ijfracpartial fpartial x^jfracpartial partial
          x^iright) X = g_ik X^i g^kjfracpartial fpartial x^j = delta^j_i X^i fracpartial fpartial x^j = X^ifracpartial fpartial x^i = Xf$$



          Note that $Xf = X^ifracpartial fpartial x^colorredi$, not $Xf = X^ifracpartial fpartial x^j$, as you have mentioned in the last line.



          REMARK: The reason why I take the $k$-th component is because we have already used $j$ for the coordinate representation of $hatg^-1(df)$. Thus $g(X)(Y) = g_ijX^iY^k$. In fact I believe that this is the reason behind your confusion in the probem.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered Aug 19 at 8:56









          Stefan4024

          29.2k53276




          29.2k53276











          • Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
            – Hawk
            Aug 19 at 9:16










          • @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
            – Stefan4024
            Aug 19 at 10:21










          • @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
            – Stefan4024
            Aug 19 at 10:34







          • 1




            @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
            – Stefan4024
            Aug 19 at 10:34

















          • Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
            – Hawk
            Aug 19 at 9:16










          • @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
            – Stefan4024
            Aug 19 at 10:21










          • @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
            – Stefan4024
            Aug 19 at 10:34







          • 1




            @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
            – Stefan4024
            Aug 19 at 10:34
















          Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
          – Hawk
          Aug 19 at 9:16




          Reading this again, I think I figured out my problem. Lee's notations are really easy to mess up. In my brain I know $hatg$ and its inverse are different, but translating that via my hand is something different. Basically $hatg$ strips off the basis vectors in $TM$ and leaves you with their components and $hatg^-1$ strips off the basis vectors in $T^*M$ (I guess they would just be the linear functionals 1-forms $dx^mu$) and leave you with their smooth components $omega_i$
          – Hawk
          Aug 19 at 9:16












          @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
          – Stefan4024
          Aug 19 at 10:21




          @Hawk Well, if you are applying $hatg(Y)$ to some vector field $X$ you can think that it strips the basis vectors and combines the coordinates of $Y$ and $X$ in a nice manner. Similar thing happens when you apply $hatg^-1(omega)$ to a function $f$. I guess that way of seeing it would help you during such evaluation.
          – Stefan4024
          Aug 19 at 10:21












          @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
          – Stefan4024
          Aug 19 at 10:34





          @Hawk However what $hatg$ really does is it sends vector fields to covector fields, while $hatg^-1$ does the opposite. So $hatg$ "switches" between the basis $leftfracpartial partial x^jright$ and its dual basis $leftdx^iright$ in some nice manner.
          – Stefan4024
          Aug 19 at 10:34





          1




          1




          @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
          – Stefan4024
          Aug 19 at 10:34





          @Hawk This could be best seen by applying $hatg$ to a coordinate vector fields. So we have: $$hatgleft(fracpartial partial x^1right) = g_ijleft(fracpartial partial x^1right)^i dx^j = g_1j dx^j$$ Now apply the inverse to $g_1j dx^j$ to get: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
          – Stefan4024
          Aug 19 at 10:34













           

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