$operatornamegrad(f)$ 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?
differential-geometry manifolds riemannian-geometry
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down 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?
differential-geometry manifolds riemannian-geometry
add a comment |Â
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?
differential-geometry manifolds riemannian-geometry
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?
differential-geometry manifolds riemannian-geometry
edited Aug 19 at 9:02
Stefan4024
29.2k53276
29.2k53276
asked Aug 19 at 7:37
Hawk
5,27393699
5,27393699
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1 Answer
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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.
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 $omega_i$
â 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.
â 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.
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â Stefan4024
Aug 19 at 10:34
add a comment |Â
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
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.
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 $omega_i$
â 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.
â 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.
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â Stefan4024
Aug 19 at 10:34
add a comment |Â
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.
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 $omega_i$
â 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.
â 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.
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â Stefan4024
Aug 19 at 10:34
add a comment |Â
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.
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.
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 $omega_i$
â 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.
â 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.
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â Stefan4024
Aug 19 at 10:34
add a comment |Â
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 $omega_i$
â 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.
â 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.
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â 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 $omega_i$
â 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 $omega_i$
â 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.
â 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.
â 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.
â 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.
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â 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: $$hatg^-1left(g_1j dx^jright) = g^ijg_1jfracpartial partial x^i = delta_1^i fracpartial partial x^i = fracpartial partial x^1$$
â Stefan4024
Aug 19 at 10:34
add a comment |Â
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