Define the Itô stochastic equation in the sense of [13]:d ˜∇Yt (x) = P ˜∇Yt(x 0 ),Y t(x)d ˜∇Yt (x 0 ) (4.2)Remark : The above equation is well defined, for x sufficiently close to x 0 ,because d T −t (X t (x), X t (x 0 )) is a finite variation process, with bounded derivative(by a short computation and [18], [6]).Let ˜// 0,tbe the parallel transport, associated to the connection ˜∇, over the semimartingale Y t (x 0 ).In the next lemma, we will explain the relationship between the two paralleltransport ˜// 0,tand // T 0,t.Lemma 4.1 Let (e i ) i=1..n be a orthonormale of (T M x0 , g(T )) thend((// T 0,t) −1 dπ ˜// 0,t)(0, e i ) = 1 2 (//T 0,t) −1 ( ∂ ∂ tg(T − t)) #T −t (dπ ˜// 0,t(0, e i )) dt.Proof :The parallel transport ˜// 0,tdoes not modify the time vector, i.e.,˜// −1(t,X t)(0, ...) = (0, ...),as can be shown for every curves, and hence for the semi-martingale Y t by thetransfer principle.We can identify T (0,x0 )I × M and T x0 M with the help of (0, v) ↦−→ v. Hence(// T 0,t) −1 dπ ˜// 0,t: T (0,x0 )I × M → T x0 Mbecomes an element in M n,n (R).Recall that // T 0,t = Ut T U T,−10 . By definition of D S,t given in (1.2). We get usingthe shorthand e i = U0 T ẽ i , with (ẽ i ) i=1..n an orthonormal frame of R n ,∗d((// T 0,t) −1 dπ ˜// 0,t) = ∗d(〈(// T 0,t) −1 dπ ˜// 0,te i , e j 〉 T ) i,j= ∗d(〈dπ ˜// 0,te i , // T 0,te j 〉 T −t ) i,j(= 〈D S,T −t dπ ˜// 0,te i , Ut T ẽ j 〉 T −t+ ∂ (g(T − t))(dπ ˜// ∂ 0,te i , Ut T ẽ j ) dtt+〈dπ ˜//)0,te i , D S,T −t Ut T ẽ j 〉 T −t .i,j5621
We also have:D S,T −t dπ ˜// 0,te i = V −1dπ ˜// 0,t e i((∗d(dπ ˜// 0,te i )) v T −t)= V −1dπ ˜// 0,t e i((ddπd ev ei (∗d ˜// 0,t)) v T −t)= V −1dπ ˜// 0,t e i(ddπ(d ev ei (∗d ˜// 0,t ))ṽ)= 0.Where we have used in the last equality the fact that ˜// 0,tis the ˜∇ horizontal liftof Y t . The third one may be seen for curves, it comes from the definition of ˜∇.Following computations similar to one in the first section, we have by (1.5):.∗d((// T 0,t) −1 dπ ˜// 0,t) i,j = ∂ ∂ tg(T − t)(dπ ˜// 0,te i , Ut T ẽ j ) dt+ 〈dπ ˜// 0,te i , D S,T −t Ut T ẽ j 〉 T −t= ∂ ∂ tg(T − t)(dπ ˜// 0,te i , Ut T ẽ j ) dt+ 〈dπ ˜// ∑0,te i , − 1 d ∂2 α=1 ∂ tg(T − t)(Ut T ẽ j , Ut T ẽ α )Ut T ẽ α 〉 T −t dt= ∂ ∂ tg(T − t)(dπ ˜// 0,te i , Ut T ẽ j ) dt∑− 1 d ∂2 α=1 ∂ tg(T − t)(Ut T ẽ j , Ut T ẽ α )〈dπ ˜// 0,te i , Ut T ẽ α 〉 T −t dt= 1 ∂2 ∂ tg(T − t)(dπ ˜// 0,te i , Ut T ẽ j ) dt.In the general case, and by previous identification:d((// T 0,t) −1 dπ ˜// 0,t)(0, e i ) = 1 2∑j∂∂ tg(T − t)(dπ ˜// 0,te i , U T t ẽ j )e j dt (4.3)= 1 2 (//T 0,t) −1 ( ∂ ∂ tg(T − t)) #T −t (dπ ˜// 0,t(0, e i )) dt.(4.4)Differentiating (4.2) along a geodesic curve beginning at (0, x 0 ) with velocity(v t , v) and using corollary 3.17 in [3] we get:˜// 0,td ( ˜//−10,t T Y t(v t , v) ) = − 1 2 ˜R(T Y t (v t , v), dY t (x 0 ))dY t (x 0 ),where ˜R is the curvature tensor.Let v ∈ T x M we write:T X t v := dπT Y t (0, v).In a more canonical way than theorem 3.2, we have the following proposition.5722
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