Abstract Generated abstract
The paper studies the probability that a Markov random point in Euclidean space enters a small moving neighborhood of a time-dependent differentiable submanifold. Using the Kolmogorov equation for the transition density, it constructs local coordinate frames adapted to the diffusion operator and to the tangent and conjugate subspaces of the manifold, reducing the boundary analysis to harmonic functions on associated ellipsoids. The main result gives the leading asymptotic term, for codimension at least three, as an integral over time and over the moving manifold of the transition density multiplied by a coefficient determined by the ellipsoidal cross section, with an error of higher order in the neighborhood radius. A separate logarithmic asymptotic formula is noted for codimension two.
Full Text
Reports of the Academy of Sciences of the USSR
- Volume 159, No. 2
MATHEMATICS
E. F. MISHCHENKO
ON THE PROBABILITY THAT A RANDOM POINT FALLS INTO A SMALL NEIGHBORHOOD OF A MOVING MANIFOLD
(Presented by Academician L. S. Pontryagin on 16 V 1964)
Let two objects move in the \(n\)-dimensional Euclidean space \(R^n\): a \(k\)-dimensional twice differentiable submanifold \(M\), changing its form and position according to the law
\[ M=M_s, \tag{1} \]
and a random point of Markov type, whose probability density \(p(\sigma,x,s,y)\) satisfies the Kolmogorov equation \((^1)\)
\[ \frac{\partial p}{\partial \sigma} + a^{ij}(\sigma,x)\frac{\partial^2 p}{\partial x^i\partial x^j} + b^i(\sigma,x)\frac{\partial p}{\partial x^i} =0. \tag{2} \]
Let its \(n\)-dimensional \(\varepsilon\)-neighborhood \(U(M)\) move together with \(M\). It is required to compute the probability that the random point enters the neighborhood \(U(M)\) during the time interval \(\sigma \leq s \leq \tau\).
In the present note the principal term of this probability is found. In the case when the manifold \(M\) is simply a controlled point, and \(U(M)\) is an \(n\)-dimensional ball of radius \(\varepsilon\) with center at this point, the problem was solved in \((^2,^3)\).
In what follows it is assumed that \(n-k \geq 3\).
In order to write down the formula obtained, we first make several constructions.
It is known (cf. \((^2)\)) that the sought probability \(\varphi(\sigma,x,\tau)\) (where \(x\) is the initial position of the random point at the time \(s=\sigma\)) is a solution of equation (2) under the conditions
\[ \varphi(\tau,x,\tau)=0, \]
\[ \varphi(\sigma,x,\tau)=1,\qquad x\in V(M_\sigma), \tag{3} \]
where \(V(M)\) is the boundary of the neighborhood \(U(M)\).
Through each point \(m_s\) of the manifold \(M_s\) draw the tangent plane \(P(m_s)\). Then choose \(n\) linearly independent vectors \(e_1,e_2,\ldots,e_n\), issuing from the point \(m_s\), so that: a) \(e_1,e_2,\ldots,e_k\) belong to \(P(m_s)\); b) in the coordinate system \(\xi^1,\xi^2,\ldots,\xi^n\), referred to the basis \(e_1,e_2,\ldots,e_n\), the differential operator
\[ a^{ij}(s,m_s)\frac{\partial^2}{\partial x^i\partial x^j} \tag{4} \]
is written in the form of the Laplace operator
\[ \sum_{\nu=1}^{n}\frac{\partial^2}{(\partial \xi^\nu)^2}. \tag{5} \]
The subspace conjugate to \(P(m_s)\), spanned by the vectors \(e_{k+1},\ldots,e_n\), will be denoted by \(Q(m_s)\).
The set of points of the subspace \(Q(m_s)\) at a distance \(\varepsilon\) (in the metric \(R^n\)) from the plane \(P(m_s)\) is an ellipsoid \(E_{m_s}\). Let its equation in the coordinates \(\xi\) be
\[ \sum_{i,j=k+1}^{n} c_{ij}\xi^i\xi^j=\varepsilon^2. \tag{6} \]
Obviously, up to small terms of higher order in \(\varepsilon\), we have
\[
V(M_s)=E_{m_s}\times M_s .
\tag{7}
\]
In what follows, denote by \(w(\xi^{k+1},\ldots,\xi^n)\) the harmonic function that vanishes as \(|\xi|\to\infty\) and is equal to unity on the ellipsoid \(E'_{m_s}\), singled out in \(Q(m_s)\) by the equation
\[
\sum_{i,j=k+1}^{n} c_{ij}\xi^i\xi^j=1 .
\]
It is known that \(w\) can be represented in the form
\[
w=\frac{\alpha(m_s)}{\rho^{\,n-k-2}}+\Pi(\xi^{k+1},\ldots,\xi^n),
\tag{8}
\]
where
\[
\rho^2=(\xi^{k+1})^2+\cdots+(\xi^n)^2,
\]
\(\alpha(m_s)\) is uniquely determined by the dimensions of the ellipsoid \(E'_{m_s}\), and \(\Pi\) is the double-layer potential produced by the ellipsoid \(E'_{m_s}\) at the point \((\xi^{k+1},\ldots,\xi^n)\). Differentiating the right- and left-hand sides of relation (8) in the direction \(\rho\) and then taking the integral over the surface \(E'_{m_s}\), we readily verify that
\[
\int_{E'_{m_s}} \frac{\partial w}{\partial \rho}\,dE'_{m_s}
=
\frac{4\pi^{(n-k)/2}}{\Gamma[(n-k)/2-1]}\,\alpha(m_s)
=
\beta(m_s),
\tag{9}
\]
where \(\Gamma\) is Euler’s gamma function.
We can now formulate the following proposition:
The solution of equation (2) under conditions (3) can be represented in the form
\[
\varphi(\sigma,x,\tau)
=
\varepsilon^{\,n-k-2}
\int_{\sigma}^{\tau} ds
\int_{M_s}
p(\sigma,x,s,m_s)\,\beta(m_s)\,dM_s
+
\omega(\sigma,x,\tau,\varepsilon),
\tag{10}
\]
where \(\omega\) has magnitude of order \(\varepsilon^{\,n-k-1}\) for any point \(x\) separated from the manifold \(M_\sigma\) by a finite distance independent of \(\varepsilon\).
In formula (10) the inner integration is carried out over the entire manifold \(M_s\), the volume element in which is induced at each point by the frame \(e_1,e_2,\ldots,e_k\). It is easy to see that this definition of volume depends only on the coefficients \(a^{ij}\) of equation (2) and does not depend on the permissible arbitrariness in the choice of the frame \(e_1,\ldots,e_k\).
The scheme of proof of the proposition just formulated is as follows. The function
\[
\Phi(\sigma,x,\tau)
=
\varepsilon^{\,n-k-2}
\int_{\sigma}^{\tau} ds
\int_{M_s}
p(\sigma,x,s,m_s)\,\beta(m_s)\,dM_s
\tag{11}
\]
is a solution of equation (2) outside the manifold \(M_\sigma\) and satisfies the first of conditions (3). But it does not satisfy the second, boundary condition (3). It turns out, however, that one can construct an \(n\)-dimensional ellipsoidal neighborhood of the manifold \(M_\sigma\) on whose boundary the values of the solutions \(\Phi(\sigma,x,\tau)\) and \(\varphi(\sigma,x,\tau)\) essentially coincide. Let us construct this neighborhood.
For this, in each subspace \(Q(m_\sigma)\) take the ellipsoid \(E^*_{m_\sigma}\) singled out by the equation
\[
\rho=\varepsilon,
\tag{12}
\]
and set
\[
V^*(M_\sigma)=E^*_{m_\sigma}\times M_\sigma .
\tag{13}
\]
The surface \(V^*\) is precisely the boundary of the neighborhood of the manifold \(M_\sigma\) that we need. We emphasize that, generally speaking, \(V^*\) does not coincide with \(V\).
Now, using the known asymptotic representations of the function \(p(\sigma, x, s, y)\) (cf., for example, \((^2)\)) and carrying out elementary, although rather cumbersome, calculations, we find that for \(x_0 \in V^*(M_\sigma)\)
\[ \Phi(\sigma, x_0, \tau)=\alpha(m_{0\sigma})+\omega_1(\sigma, x_0, \tau, \varepsilon), \tag{14} \]
where \(\omega_1\) is of order \(O(1)\) for \(\tau-\sigma \leqslant \varepsilon\) and vanishes as \(\varepsilon \to 0\) when \(\tau-\sigma>\varepsilon\). Here \(m_{0\sigma}\) denotes the projection of the point \(x_0\) onto the manifold \(M_\sigma\) in the direction of the plane \(Q(m_\sigma)\).
On the other hand, using a method which is a natural analogue of the method of \((^2)\), we can write the solution \(\varphi(\sigma, x, \tau)\) in a certain special form, from which it is directly seen that
\[ \varphi(\sigma, x_0, \tau)=\alpha(m_{0\sigma})+\omega_2(\sigma, x_0, \tau, \varepsilon), \tag{15} \]
where \(\omega_2\) has the same asymptotic character with respect to \(\varepsilon\) as \(\omega_1\).
Comparing relations (14) and (15), it is now not difficult to derive formula (10).
In conclusion we note that in the case \(n-k=2\) the simpler formula is valid
\[ \varphi(\sigma, x, \tau)=\frac{2\pi}{|\ln \varepsilon|} \int_{\sigma}^{\tau} ds \int_{M_s} p(\sigma, x, s, m_s)\,dM_s +o\!\left(\frac{1}{|\ln \varepsilon|}\right). \]
It is easily obtained if one uses a result of S. M. Nikol’skii \((^4)\).
Mathematical Institute named after V. A. Steklov
Academy of Sciences of the USSR
Received
9 V 1964
CITED LITERATURE
\(^1\) A. N. Kolmogoroff, Math. Ann., 104, 415 (1931).
\(^2\) E. F. Mishchenko, L. S. Pontryagin, Izv. AN SSSR, ser. matem., 25, 477 (1961).
\(^3\) A. N. Kolmogorov, E. F. Mishchenko, L. S. Pontryagin, DAN, 145, No. 5 (1962).
\(^4\) S. M. Nikol’skii, Theory of Probability and Its Applications, 9, issue 2 (1964).