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Let n=2 and C be a symmetric two by two matrix and let $X = \left(X_{1,j}; X_{2,j}\right)_{j=1}^T$ be a two by T real matrix matrix. We consider a following generating function.

\begin{equation} U(t) := \frac{1}{n} \int\limits_{{\mathbb R}^{2 T}} Tr\left[ e^{\frac{\imath t}{T} X X^T} \right] \cdot e^{-\frac{1}{2} Tr\left[ C^{-1} X X^T \right]} \frac{\prod_{j=1}^T dX_{1,j} dX_{2,j}}{\sqrt{(2\pi)^{2T}} \sqrt{\det(C)^T}} \end{equation}

By expanding the first term in the integrand in a Taylor series in t we and integrating term by term we easily establish that: \begin{eqnarray} U(0) &=& 1 \\ \left.\frac{d U(t)}{d \imath t} \right|_{t=0} &=& Tr[C] \\ \left.\frac{d^2 U(t)}{d (\imath t)^2} \right|_{t=0} &=& Tr[C^2](1+\frac{1}{T}) + Tr[C]^2 \frac{2}{T} \\ \end{eqnarray}

Now, let us try to compute the generating function in a different way. We perform a singular value decomposition of the matrix X X^T. We have: \begin{equation} X X^T = U {\mathcal D} U^{-1} \end{equation} where $U$ is a unitary matrix and ${\mathcal D}$ is a diagonal matrix with real entries $s_1,s_2$. We have: \begin{equation} U(t) = \frac{1}{((2 \pi)^2 c_1 c_2)^{T/2}n}\int\limits_{{\mathbb R}_+^2} d s_1 d s_2 (s_2-s_1)^2 (s_1 s_2)^{\frac{T-3}{2}} \left(e^{\frac{\imath t s_1}{T}}+e^{\frac{\imath t s_2}{T}}\right) \cdot \underbrace{\int\limits_{U(2)} dU e^{-\frac{1}{2}Tr\left(C^{-1} U {\mathcal D} U^{-1}\right)}}_{J} \end{equation} Here I used the formula for the joint-probability density of eigenvalues of an ensemble of random matrices (see http://en.wikipedia.org/wiki/Wishart_distribution for example). The last integral on the right-hand side is an integration over the group of two dimensional unitary matrices. We can do that integral owing to the Harish-Chandra-Itzykson-Zuber formula. We have: \begin{equation} J = {\mathcal A}_T \frac{(e^{-\frac{s_1}{2 c_1}-\frac{s_2}{2 c_2}} - e^{-\frac{s_1}{2 c_2}-\frac{s_2}{2 c_1}})}{(\frac{1}{c_1}-\frac{1}{c_2})(s_1-s_2)} \end{equation} where the proportionality constant ${\mathcal A}_T$ depends on $T$ only. Inserting the above into the equation for $U(t)$ we get: \begin{equation} U(t) = \frac{{\mathcal A}_T}{((2 \pi)^2 c_1 c_2)^{T/2}(\frac{1}{c_1}-\frac{1}{c_2})n}\int\limits_{{\mathbb R}_+^2} d s_1 d s_2 (s_2-s_1) (s_1 s_2)^{\frac{T-3}{2}} \left(e^{\frac{\imath t s_1}{T}}+e^{\frac{\imath t s_2}{T}}\right) \cdot (e^{-\frac{s_1}{2 c_1}-\frac{s_2}{2 c_2}} - e^{-\frac{s_1}{2 c_2}-\frac{s_2}{2 c_1}}) \end{equation} Now we set ${\mathcal A}_T=1$ and we use Mathematica to compute the value of our generating function and its derivatives at zero. We have: \begin{eqnarray} U(0) &=& {\mathcal B} \\ \frac{1}{\imath} U^{'}(0) &=& {\mathcal B} \frac{T+1}{2 T} Tr[C] \\ \frac{1}{\imath^2} U^{''}(0) &=& {\mathcal B} \frac{T+1}{2 T} \left[(1+\frac{1}{T})Tr[C^2] + \frac{4}{T} (Tr[C])^2 \right] \end{eqnarray}

where ${\mathcal B} = 4 \sqrt{c_1 c_2} \pi^{-T} \Gamma[(T-1)/2] \Gamma[(T+1)/2]$. These results are clearly different from those stated on the very top. What is the reason for this? I suspect that there is something wrong with the joint-denstity of eigenvalues in the integral over $s_1$ and $s_2$ but I cannot figure out what is wrong. Can anybody help me?

Przemo
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1 Answers1

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I have calculated this integral in Spectral density of a sample covariance matrix in a Gaussian Random Ensemble . There were two bugs in the above reasoning. Firstly, the Harish-Chandra-Itzykson-Zuber formula does not hold in here because we need to integrate over the orthogonal group rather than over the unitary group. In that former case there is no closed form expression for the integral in question but instead the integral is expressed through generalized Bessel functions. Secondly, there was also a bug in the Jacobian from the matrix elements to the eigenvalues.

Przemo
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