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	<title>Comments on: 254A, Lecture 8: The mean ergodic theorem</title>
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	<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/</link>
	<description>Updates on my research and expository papers, discussion of open problems, and other maths-related topics.  By Terence Tao</description>
	<lastBuildDate>Fri, 24 May 2013 15:11:30 +0000</lastBuildDate>
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		<title>By: Multiple recurrence and convergence results associated to $F_{p}^{omega}$-actions &#124; What's new</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-230671</link>
		<dc:creator><![CDATA[Multiple recurrence and convergence results associated to $F_{p}^{omega}$-actions &#124; What's new]]></dc:creator>
		<pubDate>Wed, 22 May 2013 00:30:28 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-230671</guid>
		<description><![CDATA[[&#8230;] e.g. this previous blog post. Informally, one can interpret this limit formula as an equidistribution result: if  is drawn at [&#8230;]]]></description>
		<content:encoded><![CDATA[<p>[&#8230;] e.g. this previous blog post. Informally, one can interpret this limit formula as an equidistribution result: if  is drawn at [&#8230;]</p>
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		<title>By: Alok Bakshi</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-215615</link>
		<dc:creator><![CDATA[Alok Bakshi]]></dc:creator>
		<pubDate>Sun, 03 Feb 2013 18:02:14 +0000</pubDate>
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		<description><![CDATA[Dear Professor Tao, have you applied Jensen&#039;s inequality with $latex \phi(x) = x^2$ to obtain (1), because I couldn&#039;t see how Cauchy Schwartz inequality be applied here.

[&lt;i&gt; To show $latex \int_X f^2\ d\mu \geq (\int_X f\ d\mu)^2$, one can either use Jensen, or else apply Cauchy-Schwarz to the functions $latex f$ and $latex 1$. -T&lt;/i&gt;]]]></description>
		<content:encoded><![CDATA[<p>Dear Professor Tao, have you applied Jensen&#8217;s inequality with <img src='http://s0.wp.com/latex.php?latex=%5Cphi%28x%29+%3D+x%5E2&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='&#92;phi(x) = x^2' title='&#92;phi(x) = x^2' class='latex' /> to obtain (1), because I couldn&#8217;t see how Cauchy Schwartz inequality be applied here.</p>
<p>[<i> To show <img src='http://s0.wp.com/latex.php?latex=%5Cint_X+f%5E2%5C+d%5Cmu+%5Cgeq+%28%5Cint_X+f%5C+d%5Cmu%29%5E2&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='&#92;int_X f^2&#92; d&#92;mu &#92;geq (&#92;int_X f&#92; d&#92;mu)^2' title='&#92;int_X f^2&#92; d&#92;mu &#92;geq (&#92;int_X f&#92; d&#92;mu)^2' class='latex' />, one can either use Jensen, or else apply Cauchy-Schwarz to the functions <img src='http://s0.wp.com/latex.php?latex=f&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='f' title='f' class='latex' /> and <img src='http://s0.wp.com/latex.php?latex=1&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='1' title='1' class='latex' />. -T</i>]</p>
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	<item>
		<title>By: Terence Tao</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-197059</link>
		<dc:creator><![CDATA[Terence Tao]]></dc:creator>
		<pubDate>Wed, 28 Nov 2012 00:52:19 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-197059</guid>
		<description><![CDATA[Yes; I recommend the exercise of verifying that the definition given in the Wikipedia article is indeed the orthogonal projection to the Hilbert space $latex L^2({\mathcal B})$ (this is also alluded to in Section 5 of the Wikipedia article, as well as in equation (14) of the present article), and that in the case when the factor $latex {\mathcal B}$ is generated by a discrete random variable, the definition collapses (outside of an event of probability zero, at least) to the definition given in Notes 0 (or at the beginning of the Wikipedia article); this is alluded to in Remark 6 of these notes.]]></description>
		<content:encoded><![CDATA[<p>Yes; I recommend the exercise of verifying that the definition given in the Wikipedia article is indeed the orthogonal projection to the Hilbert space <img src='http://s0.wp.com/latex.php?latex=L%5E2%28%7B%5Cmathcal+B%7D%29&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='L^2({&#92;mathcal B})' title='L^2({&#92;mathcal B})' class='latex' /> (this is also alluded to in Section 5 of the Wikipedia article, as well as in equation (14) of the present article), and that in the case when the factor <img src='http://s0.wp.com/latex.php?latex=%7B%5Cmathcal+B%7D&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='{&#92;mathcal B}' title='{&#92;mathcal B}' class='latex' /> is generated by a discrete random variable, the definition collapses (outside of an event of probability zero, at least) to the definition given in Notes 0 (or at the beginning of the Wikipedia article); this is alluded to in Remark 6 of these notes.</p>
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		<title>By: Jack</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-197052</link>
		<dc:creator><![CDATA[Jack]]></dc:creator>
		<pubDate>Wed, 28 Nov 2012 00:12:52 +0000</pubDate>
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		<description><![CDATA[In this note, the &quot;conditional expectation&quot; is defined as the projection on the closed subspace of a Hilbert space. I learned another version on [this Wikipedia article] (http://en.wikipedia.org/wiki/Conditional_expectation#Formal_definition).  And I also see one in 254A Note 0
(http://terrytao.wordpress.com/2010/01/01/254a-notes-0-a-review-of-probability-theory/#as-rem), which is for the discrete random variables. Are they essentially the same?]]></description>
		<content:encoded><![CDATA[<p>In this note, the &#8220;conditional expectation&#8221; is defined as the projection on the closed subspace of a Hilbert space. I learned another version on [this Wikipedia article] (<a href="http://en.wikipedia.org/wiki/Conditional_expectation#Formal_definition" rel="nofollow">http://en.wikipedia.org/wiki/Conditional_expectation#Formal_definition</a>).  And I also see one in 254A Note 0<br />
(<a href="http://terrytao.wordpress.com/2010/01/01/254a-notes-0-a-review-of-probability-theory/#as-rem" rel="nofollow">http://terrytao.wordpress.com/2010/01/01/254a-notes-0-a-review-of-probability-theory/#as-rem</a>), which is for the discrete random variables. Are they essentially the same?</p>
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		<title>By: Advanced Analyis, Notes 5: Hilbert spaces (Application: Von Neumann&#8217;s mean ergodic theorem) &#171; Noncommutative Analysis</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-187542</link>
		<dc:creator><![CDATA[Advanced Analyis, Notes 5: Hilbert spaces (Application: Von Neumann&#8217;s mean ergodic theorem) &#171; Noncommutative Analysis]]></dc:creator>
		<pubDate>Tue, 30 Oct 2012 08:26:28 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-187542</guid>
		<description><![CDATA[[...] operators-on-Hilbert-space theory, by proving von Neumann&#8217;s mean ergodic theorem. See also this treatment by Terry Tao on his [...]]]></description>
		<content:encoded><![CDATA[<p>[...] operators-on-Hilbert-space theory, by proving von Neumann&#8217;s mean ergodic theorem. See also this treatment by Terry Tao on his [...]</p>
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		<title>By: Walsh&#8217;s ergodic theorem, metastability, and external Cauchy convergence &#171; What&#8217;s new</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-185893</link>
		<dc:creator><![CDATA[Walsh&#8217;s ergodic theorem, metastability, and external Cauchy convergence &#171; What&#8217;s new]]></dc:creator>
		<pubDate>Thu, 25 Oct 2012 18:10:50 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-185893</guid>
		<description><![CDATA[[...] averages, namely the orthogonal projection of  to the -invariant factors. (See for instance my lecture notes on this theorem.) While this theorem ostensibly involves measure theory, it can be abstracted to the more general [...]]]></description>
		<content:encoded><![CDATA[<p>[...] averages, namely the orthogonal projection of  to the -invariant factors. (See for instance my lecture notes on this theorem.) While this theorem ostensibly involves measure theory, it can be abstracted to the more general [...]</p>
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		<title>By: Rex</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-173991</link>
		<dc:creator><![CDATA[Rex]]></dc:creator>
		<pubDate>Sun, 23 Sep 2012 03:06:12 +0000</pubDate>
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		<description><![CDATA[Typo: where you write &quot;Now observe (using (10)) that $latex \frac{1}{N} \frac{\lambda^{N}-\lambda}{\lambda-1}$ is bounded in magnitude by 1...&quot;

I think you want:

$latex \frac{1}{N} \frac{\lambda^{N}-1}{\lambda-1}$

&lt;i&gt;[Corrected, thanks - T.]&lt;/i&gt;]]></description>
		<content:encoded><![CDATA[<p>Typo: where you write &#8220;Now observe (using (10)) that <img src='http://s0.wp.com/latex.php?latex=%5Cfrac%7B1%7D%7BN%7D+%5Cfrac%7B%5Clambda%5E%7BN%7D-%5Clambda%7D%7B%5Clambda-1%7D&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='&#92;frac{1}{N} &#92;frac{&#92;lambda^{N}-&#92;lambda}{&#92;lambda-1}' title='&#92;frac{1}{N} &#92;frac{&#92;lambda^{N}-&#92;lambda}{&#92;lambda-1}' class='latex' /> is bounded in magnitude by 1&#8230;&#8221;</p>
<p>I think you want:</p>
<p><img src='http://s0.wp.com/latex.php?latex=%5Cfrac%7B1%7D%7BN%7D+%5Cfrac%7B%5Clambda%5E%7BN%7D-1%7D%7B%5Clambda-1%7D&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='&#92;frac{1}{N} &#92;frac{&#92;lambda^{N}-1}{&#92;lambda-1}' title='&#92;frac{1}{N} &#92;frac{&#92;lambda^{N}-1}{&#92;lambda-1}' class='latex' /></p>
<p><i>[Corrected, thanks - T.]</i></p>
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		<title>By: Terence Tao</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-173924</link>
		<dc:creator><![CDATA[Terence Tao]]></dc:creator>
		<pubDate>Sat, 22 Sep 2012 23:00:51 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-173924</guid>
		<description><![CDATA[(a) yes; see http://terrytao.wordpress.com/2008/01/08/254a-lecture-1-overview/

(b) Not directly, though in practice one can often derive recurrence results for non-invertible ergodic systems from the invertible case by a lifting trick, see e.g. Exercise 9 of http://terrytao.wordpress.com/2008/01/15/254a-lecture-4-multiple-recurrence/ for an instance of this.]]></description>
		<content:encoded><![CDATA[<p>(a) yes; see <a href="http://terrytao.wordpress.com/2008/01/08/254a-lecture-1-overview/" rel="nofollow">http://terrytao.wordpress.com/2008/01/08/254a-lecture-1-overview/</a></p>
<p>(b) Not directly, though in practice one can often derive recurrence results for non-invertible ergodic systems from the invertible case by a lifting trick, see e.g. Exercise 9 of <a href="http://terrytao.wordpress.com/2008/01/15/254a-lecture-4-multiple-recurrence/" rel="nofollow">http://terrytao.wordpress.com/2008/01/15/254a-lecture-4-multiple-recurrence/</a> for an instance of this.</p>
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		<title>By: Rex</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-173860</link>
		<dc:creator><![CDATA[Rex]]></dc:creator>
		<pubDate>Sat, 22 Sep 2012 19:20:24 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-173860</guid>
		<description><![CDATA[Just to make sure we have the same conventions:

In the definition of measure-preserving system, when you say &quot;$latex T$ is invertible&quot;, you mean that the map $latex T: X \longrightarrow X$ is a (measurable) bijection, so that $latex T^{-1}$ is defined on the level of sets?

In this case, we are not considering examples such as the doubling map on the circle? I think some other texts only require that $latex T$ satisfy $latex \mu(T^{-1} E) = \mu(E)$ for all measurable $latex E \subset X$.]]></description>
		<content:encoded><![CDATA[<p>Just to make sure we have the same conventions:</p>
<p>In the definition of measure-preserving system, when you say &#8220;<img src='http://s0.wp.com/latex.php?latex=T&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='T' title='T' class='latex' /> is invertible&#8221;, you mean that the map <img src='http://s0.wp.com/latex.php?latex=T%3A+X+%5Clongrightarrow+X&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='T: X &#92;longrightarrow X' title='T: X &#92;longrightarrow X' class='latex' /> is a (measurable) bijection, so that <img src='http://s0.wp.com/latex.php?latex=T%5E%7B-1%7D&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='T^{-1}' title='T^{-1}' class='latex' /> is defined on the level of sets?</p>
<p>In this case, we are not considering examples such as the doubling map on the circle? I think some other texts only require that <img src='http://s0.wp.com/latex.php?latex=T&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='T' title='T' class='latex' /> satisfy <img src='http://s0.wp.com/latex.php?latex=%5Cmu%28T%5E%7B-1%7D+E%29+%3D+%5Cmu%28E%29&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='&#92;mu(T^{-1} E) = &#92;mu(E)' title='&#92;mu(T^{-1} E) = &#92;mu(E)' class='latex' /> for all measurable <img src='http://s0.wp.com/latex.php?latex=E+%5Csubset+X&amp;bg=ffffff&amp;fg=545454&amp;s=0' alt='E &#92;subset X' title='E &#92;subset X' class='latex' />.</p>
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		<title>By: Rex</title>
		<link>http://terrytao.wordpress.com/2008/01/30/254a-lecture-8-the-mean-ergodic-theorem/#comment-146643</link>
		<dc:creator><![CDATA[Rex]]></dc:creator>
		<pubDate>Sun, 10 Jun 2012 11:40:10 +0000</pubDate>
		<guid isPermaLink="false">http://terrytao.wordpress.com/?p=250#comment-146643</guid>
		<description><![CDATA[On second thought, I suppose the norms could be different.]]></description>
		<content:encoded><![CDATA[<p>On second thought, I suppose the norms could be different.</p>
]]></content:encoded>
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