352 APPENDIX B. CURVILINEAR COORDINATES

What about the divergence of a vector field? The divergence of a vector field F definedon U is a scalar field, div(F ) which from calculus is

∂Fk

∂yk (y) = Fk,k (y)

in terms of the usual rectangular coordinates y. The reason the above equation holds inthis case is that ek (y) is a constant and so the Christoffel symbols are zero. We want anexpression for the divergence in arbitrary coordinates. From Theorem B.6.1,

F i, j (y) = Fr

,s (x)∂xs

∂y j∂yi

∂xr

From 2.27,

=

(∂Fr (x)

∂xs +Fk (x)

{rks

}(x)

)∂xs

∂y j∂yi

∂xr .

Letting j = i yields

div(F ) =

(∂Fr (x)

∂xs +Fk (x)

{rks

}(x)

)∂xs

∂yi∂yi

∂xr

=

(∂Fr (x)

∂xs +Fk (x)

{rks

}(x)

sr

=

(∂Fr (x)

∂xr +Fk (x)

{rkr

}(x)

). (2.37)

{rkr

}is simplified using the description of it in Theorem B.6.2. Thus, from this theorem,

{rrk

}=

g jr

2

[∂gr j

∂xk +∂gk j

∂xr −∂grk

∂x j

]Now consider g jr

2 times the last two terms in [·] . Relabeling the indices r and j in the secondterm implies

g jr

2∂gk j

∂xr −g jr

2∂grk

∂x j =g jr

2∂gk j

∂xr −gr j

2∂g jk

∂xr = 0.

Therefore, {rrk

}=

g jr

2∂gr j

∂xk . (2.38)

Now recall g≡ det(gi j) = det(G)> 0 from Theorem B.1.6. Also from the formula for theinverse of a matrix and this theorem,

g jr = Ar j (detG)−1 = A jr (detG)−1

where Ar j is the r jth cofactor of the matrix (gi j) . Also recall that

g =n

∑r=1

gr jAr j no sum on j.

352 APPENDIX B. CURVILINEAR COORDINATESWhat about the divergence of a vector field? The divergence of a vector field F’ definedon U isa scalar field, div (F’) which from calculus isOF“aye (y)= Fi (y)in terms of the usual rectangular coordinates y. The reason the above equation holds inthis case is that e; (y) is a constant and so the Christoffel symbols are zero. We want anexpression for the divergence in arbitrary coordinates. From Theorem B.6.1,i _ pr ax oy!Fly) = Fs(®) 55 oe(Se rref fhe) BeFrom 2.27,Letting j =i yieldsdiv(F) = (SS+r io) ks \ (ey) So= (52 +r @{ § b@)s- (49s r@{ f be). @.37){ i: \ is simplified using the description of it in Theorem B.6.2. Thus, from this theorem,{ r \. gi” [23 4 28k - aark 2 | daxk — ax’ — AxiNow consider x times the last two terms in |-]. Relabeling the indices r and j in the secondterm impliesgl Og; gl Aan — gl” O8K; — B"! OB ik ~02 ax’ 2 daxi 2 Ox” 2 Ox”r _ gi" Og,{ rk \. “a xk (2.38)Now recall g = det (g;;) = det (G) > 0 from Theorem B.1.6. Also from the formula for theinverse of a matrix and this theorem,Therefore,gl” =A") (detG)~' = AM" (detG)~!where A’J is the rj‘ cofactor of the matrix (g;;). Also recall thatg= grjA" no sum on j.nr=1