Let $n\ge 2$ and let $S^{n-1}$ be the unit sphere on $\mathbb{R}^n$ equipped with geodesic distance $d$ and the uniform probability measure $\mu$. For $x\in\mathbb{R}^n$ with $|x| <1, $ we consider the probability measure on $S^{n-1}$ given by
It is the so-called Moebius measure we are working on. In fact, this probability is the image of $\mu$ under the Moebius transformation. The factor $\dfrac{(1-|x|^2)^{\frac{n-1}{2}}}{(1-(x, y))^{n-1}}$ is known as the invariant Poisson kernel $P(x, y)$: as a function of $x, $ it is not harmonic but satisfies the equation $\tilde{\Delta} P(\cdot, y)=0, $ where $\tilde{\Delta}$ denotes the invariant Laplacian operator (the reader is referred to [3] for further information on this measure).
Let $M$ be a connected complete Riemannian manifold with Riemannian metric $d$ and $\nabla$ is the gradient on $M.$ Let $\mathcal{M}_1(M)$ be the space of all probabilities on $M.$ Given any $\mu\in \mathcal{M}_1(M), $ we say that
1. $\mu$ satisfies a Poincaré inequality with a non-negative constant $C$ if for any smooth function $f: M\to\mathbb{R}$, there exists a constant $C\ge 0$ such that
The optimal constant above is denoted by $C_{\rm P}(\mu)$.
2. $\mu$ satisfies a logarithmic Sobolev inequality with a constant $C\ge 0$ if for any smooth function $f: M\to\mathbb{R}$ with $\mu(f^2)=1, $
We denote by $C_{\rm LS}(\mu)$ the optimal logarithmic Sobolev constant.
3. $\mu$ satisfies a Sobolev inequality with exponent $p\ge 1, $ if there exists one positive constant $C$ such that for any $f: M \to\mathbb{R}$ smooth enough,
In fact, the classical Poincaré inequality corresponds to the case $p=1$ and the logarithmic Sobolev inequality turns out to the limit case when $p$ tends to $2$ since
where
is the relative entropy of $f^2$ under $\mu_x^n.$ It was proved in [4] that
is increasing on $p$ for given $f.$
In this paper, we consider the Poincaré inequality, logarithmic Sobolev inequality and Sobolev inequality for Moebius measures on the unit circle.
In [3], Schechtman and Schmuckenschläger proved that $\mu_x^n$ with any $|x| <1$ has a uniform Gaussian concentration property, which is similar to the one of $\mu^n_0$. In [5], they obtained logarithmic Sobolev and Poincaré inequalities for harmonic measures on unit sphere $S^{n-1}$ for $n\ge 3$ and in [2] they had similar results for harmonic measures when $n=2$. And then in [1], they obtained Sobolev inequalities for harmonic measures when $n\ge 2.$
Following the idea in [5], they obtained in [6] similar results for Moebius measures on unit sphere for $n\ge 3.$ In this paper, we will work on the Moebius measures on unit circle
with $x\in\mathbb{R}^2, |x| <1$ and $\mu$ the uniform probability on the unit circle.
The main result of this paper is the following.
Theorem 1 Let $\mu_x$ be the Moebius measure on the unit circle. We have
a) the optimal Poincaré constant $C_{\rm P}(\mu_x)$ satisfies
b) the optimal logarithmic Sobolev constant $C_{\rm LS}(\mu_x)$ satisfies
c) the optimal Sobolev constant $C_{p}(\mu_{x})$ satisfies
for $1 <p <2.$
We first present a crucial lemma, which combines a particular case of Lemma 1.1 in [2] and a lemma in [1].
Lemma 2.1 Define
for $0 <a <1.$ We have, respectively,
(1) the corresponding Poincaré constant satisfies
(2) similarly, the optimal logarithmic Sobolev constants satisfy
here $\lambda^{DD}(\nu_{|x|})$ is defined as
(3) the optimal Sobolev constant satisfies
Define the diffusion operator $\mathcal{L}_a$ as
for any smooth function $f: [0, \pi]\to\mathbb{R}.$ The corresponding Dirichlet form is
The optimal Poincaré constant $C_{\rm P}(\nu_a)=\frac{1}{\lambda_1(\nu_{a})}, $ where $\lambda_1(\nu_a)$ has classic variational formula
Put $f(\theta)=1-a\cos\theta.$ We get
and
So by the variational formula
Therefore we have $C_{\rm P}(\nu_a)\ge 1.$ Now we work on the upper bound for $C_{\rm P}(\nu_a).$ The variational formula for $\lambda_1(\nu_a)$ by Chen in [7] could be understood as
Set $\rho(\theta)=1-a\cos \theta-\sqrt{1-a^2}$, it is easy to see that $\rho$ is strictly increasing on $[0, \pi]$ and $ \nu_a(\rho) =0. $ Thus
where the first equality comes true by the fact that for $\alpha\in [0, \pi], $
And the last but second equality holds by the fact
Step 1 Lower bound for $\lambda^{DD}(\nu_a)$. Choose $f$ as $f(\theta)=\sin\theta$ for $\theta\in [0, \pi].$ Clearly, $f$ satisfies
So by Theorem 1.1 in [8],
In fact, for $0\le a\le 1, $
Now, combining the upper and lower bound for $\lambda_1(\nu_a)$ as well as the lower bound for $\lambda^{DD}(\nu_a)$, we have by Lemma 2.1,
The part a) of Theorem 1 follows.
By (2.3), it is clear that the median of $\nu_a$ is $\theta_a=\arccos a.$ Define
with $r=\frac12$ or $r=e^2.$ It is trivial to check that
for any $0 <\beta <\alpha <\pi.$
Step 1 Upper bound for $S_{\rm LS}^+(a, e^2)$ and $S_{\rm LS}^-(a, e^2)$. For given $b>0$, $x\log(1+b/x)$ is increasing on $x>0.$ We have by (3.1),
where the last inequality is true since $\frac{2}{\pi}\le \frac{\sin x}{x}\le 1$ for any $x\in (0, \frac{\pi}{2}).$
Similarly, by (3.2) and the fact $\sin\theta_a=\sqrt{1-a^2}, $ we have
Step 2 Lower bound for $S_{\rm LS}^+(a, \frac12)$. Choosing $\alpha=\frac{2\pi}3, $ we have by (3.1) that
Therefore from the monotonicity of $x\log(1+b/x)$ for $x>0$ when $b>0, $ it holds
Barthe-Roberto's characterization for logarithmic Sobolev constants tells (see [9])
Therefore, it follows from (3.3), (3.4) and (3.5) that
By (2.4), we have
Thereby by Lemma 2.1, we get
which completes the proof of b) of Theorem 1.
Define
It is easy to check that both $x(1-(1+\frac{C}{x})^\frac{p-2}{p})$ and $1-(1+x)^{(p-2)/p}$ are increasing on $\mathbb{R}_+$ for $C>0.$ Recalling the estimates
for any $0 <\beta <\alpha <\pi.$ We get
where the second inequality holds by $\frac{x}{\sin x}\leq\frac{\pi}{2}, \; \forall x\in(0, \pi/2)$.
Similarly, we get
Finally, Barthe-Roberto's characterization for Sobolev constant guarantees that
Set $f=\frac{1-a\cos\theta}{\sqrt{1-a^2}}, $ then
By Lemma 2.4 in [1], we know
where the last inequality holds by the facts that $r(1-(1+\frac{C}{r})^\frac{p-2}{p})$ is increasing and $\frac{1}{1-\sqrt{1-a^2}}\ge 1$. Combining (4.5), (4.6), $\frac{1}{\lambda^{DD}(\nu_{a})}\leq\log4$ and Lemma 2.1 together, we have
which completes the proof of theorem.