{"id":1057,"date":"2017-10-13T11:08:26","date_gmt":"2017-10-13T15:08:26","guid":{"rendered":"http:\/\/blog.richmond.edu\/math320\/?p=1057"},"modified":"2017-10-13T11:08:26","modified_gmt":"2017-10-13T15:08:26","slug":"modulus-of-continuity","status":"publish","type":"post","link":"https:\/\/blog.richmond.edu\/math320\/2017\/10\/13\/modulus-of-continuity\/","title":{"rendered":"Modulus of Continuity"},"content":{"rendered":"<p><em>By: Rhiannon Begley and Shuyi Chen<\/em><\/p>\n<h3>Introduction<\/h3>\n<p>In class we have begun to and will continue to discuss functions, their continuity, and their limits at a particular point. Although we can determine the continuity and limits of functions with the tools we have learned in class, we cannot determine how quickly the function is converging to its limit at that point. In this paper, we will discuss a concept called a modulus of continuity that is used to quantify the rate of convergence of a function at a particular point of continuity.<\/p>\n<h3>Definitions<\/h3>\n<p>We will begin by simply stating the definitions we will work with in the remainder of this report.<\/p>\n<p><strong>Definition<\/strong>: A function <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma+%3A%5B0%2C%5Cinfty%29%5Crightarrow+%5B0%2C%5Cinfty%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma :[0,&#92;infty)&#92;rightarrow [0,&#92;infty)\" class=\"latex\" \/> is called a modulus of continuity if <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma%280%29%3D0&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma(0)=0\" class=\"latex\" \/> and <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Clim_%7Bd%5Crightarrow+0%5E%7B%2B%7D%7D%5Csigma%28d%29%3D0&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;lim_{d&#92;rightarrow 0^{+}}&#92;sigma(d)=0\" class=\"latex\" \/>.<\/p>\n<p><strong>Definition<\/strong>: <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%3A+A%5Crightarrow+%5Cmathbb%7BR%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f: A&#92;rightarrow &#92;mathbb{R}\" class=\"latex\" \/> is continuous at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c%5Cin+A&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c&#92;in A\" class=\"latex\" \/> with (local) modulus of continuity <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma\" class=\"latex\" \/> if there exists a <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cdelta+%3E0+&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;delta &gt;0 \" class=\"latex\" \/> so that <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%5Cleq+%5Csigma+%28%7Cx-c%7C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|&#92;leq &#92;sigma (|x-c|)\" class=\"latex\" \/> for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cx-c%7C%3C%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|x-c|&lt;&#92;delta\" class=\"latex\" \/>.<\/p>\n<h3>The Modulus of Continuity as a Rate of Convergence<\/h3>\n<p>Let&#8217;s break this down by looking at a sequence <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%28x_n%29%3D%28c%2B%5Cfrac%7B1%7D%7Bn%7D%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"(x_n)=(c+&#92;frac{1}{n})\" class=\"latex\" \/>. This sequence provides a sampling of points in a small <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;delta\" class=\"latex\" \/> neighborhood around $c$. This is converging to <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c\" class=\"latex\" \/> at a rate of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cfrac%7B1%7D%7Bn%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;frac{1}{n}\" class=\"latex\" \/>. Now consider our function <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/>. The rate at which <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x_n%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x_n)\" class=\"latex\" \/> converges to <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28c%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(c)\" class=\"latex\" \/> is <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28%5Cfrac%7B1%7D%7Bn%7D%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(&#92;frac{1}{n})\" class=\"latex\" \/>. Compare that to the rate at which <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma%28%7Cx_n-c%7C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma(|x_n-c|)\" class=\"latex\" \/> converges to 0. This rate is <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma%28%7C%5Cfrac%7B1%7D%7Bn%7D%7C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma(|&#92;frac{1}{n}|)\" class=\"latex\" \/>. So, for this <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;delta\" class=\"latex\" \/> neighborhood around <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c\" class=\"latex\" \/>, if <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28%5Cfrac%7B1%7D%7Bn%7D%5Cleq%C2%A0%5Csigma%28%7C%5Cfrac%7B1%7D%7Bn%7D%7C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(&#92;frac{1}{n}&#92;leq\u00a0&#92;sigma(|&#92;frac{1}{n}|)\" class=\"latex\" \/>, then <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma\" class=\"latex\" \/> is a local modulus of continuity for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/>.<\/p>\n<p>We can also visualize this for different possible <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma\" class=\"latex\" \/> we will discuss later. If the function remains inside the cones (the yellow highlighted areas), then <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma\" class=\"latex\" \/> is a local modulus of continuity for that function at that point.<\/p>\n<p><a href=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?ssl=1\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"1112\" data-permalink=\"https:\/\/blog.richmond.edu\/math320\/2017\/10\/13\/modulus-of-continuity\/img_03411\/\" data-orig-file=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?fit=3264%2C2448&amp;ssl=1\" data-orig-size=\"3264,2448\" data-comments-opened=\"0\" data-image-meta=\"{&quot;aperture&quot;:&quot;2.2&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;iPhone 6&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;1507891626&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;4.15&quot;,&quot;iso&quot;:&quot;50&quot;,&quot;shutter_speed&quot;:&quot;0.033333333333333&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;1&quot;}\" data-image-title=\"IMG_0341[1]\" data-image-description=\"\" data-image-caption=\"\" data-medium-file=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?fit=300%2C225&amp;ssl=1\" data-large-file=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?fit=600%2C450&amp;ssl=1\" class=\"alignnone size-large wp-image-1112\" src=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411-1024x768.jpg?resize=600%2C450&#038;ssl=1\" alt=\"\" width=\"600\" height=\"450\" srcset=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?resize=1024%2C768&amp;ssl=1 1024w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?resize=300%2C225&amp;ssl=1 300w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?resize=768%2C576&amp;ssl=1 768w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?w=1200 1200w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_03411.jpg?w=1800 1800w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/a><\/p>\n<h3>Examples<\/h3>\n<p>To help illustrate this concept of moduli of continuity, we will consider the common family of moduli (the power functions)<\/p>\n<p style=\"text-align: center\"><img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_p%28d%29%3A%3Dd%5Ep%2C%5Cqquad%5Ctext%7Bfor+%7Dp%3E0.&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_p(d):=d^p,&#92;qquad&#92;text{for }p&gt;0.\" class=\"latex\" \/><\/p>\n<p>In order to show <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_p&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_p\" class=\"latex\" \/> is a moduli of continuity for a function, we need to produce a <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;delta\" class=\"latex\" \/> so that <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%5Cleq+%5Csigma_p+%28%7Cx-c%7C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|&#92;leq &#92;sigma_p (|x-c|)\" class=\"latex\" \/> when <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cx-c%7C%3C%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|x-c|&lt;&#92;delta\" class=\"latex\" \/>.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Example 1<\/strong>: <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x%29%3Da&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x)=a\" class=\"latex\" \/><br \/>\n<b>p=2<\/b>: Consider <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_2%3Dd%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_2=d^2\" class=\"latex\" \/><br \/>\nThen <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%3D%7Ca-a%7C%3D0%5Cleq+%5Csigma_2+%28%7Cx-c%7C%29%3D%28x-c%29%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|=|a-a|=0&#92;leq &#92;sigma_2 (|x-c|)=(x-c)^2\" class=\"latex\" \/>. Since <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=0%5Cleq+%28x-c%29%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"0&#92;leq (x-c)^2\" class=\"latex\" \/> always holds, any <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cdelta+%3E0+&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;delta &gt;0 \" class=\"latex\" \/> will suffice so that <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%5Cleq+%5Csigma_2+%28%7Cx-c%7C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|&#92;leq &#92;sigma_2 (|x-c|)\" class=\"latex\" \/> for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cx-c%7C%3C%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|x-c|&lt;&#92;delta\" class=\"latex\" \/>.<br \/>\nThus <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_2\" class=\"latex\" \/> is a local modulus of continuity for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/> at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c\" class=\"latex\" \/>.<\/p>\n<p><b>p=1<\/b>: Consider <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1%3Dd&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1=d\" class=\"latex\" \/><br \/>\nThen <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%3D%7Ca-a%7C%3D0%5Cleq+%5Csigma_1+%28%7Cx-c%7C%29%3D%7Cx-c%7C&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|=|a-a|=0&#92;leq &#92;sigma_1 (|x-c|)=|x-c|\" class=\"latex\" \/>. Since <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=0%5Cleq+%7Cx-c%7C&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"0&#92;leq |x-c|\" class=\"latex\" \/> always holds, any <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cdelta+%3E0+&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;delta &gt;0 \" class=\"latex\" \/> will suffice so that <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%5Cleq+%5Csigma_1+%7Cx-c%7C&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|&#92;leq &#92;sigma_1 |x-c|\" class=\"latex\" \/> for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cx-c%7C%3C%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|x-c|&lt;&#92;delta\" class=\"latex\" \/>. Thus <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1\" class=\"latex\" \/> is a local modulus of continuity for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/> at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c\" class=\"latex\" \/>.<\/p>\n<p>Similarly, the function <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x%29%3Da&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x)=a\" class=\"latex\" \/> is continuous at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c%5Cin+A&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c&#92;in A\" class=\"latex\" \/> with (local) modulus of continuity <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_p&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_p\" class=\"latex\" \/> no matter what <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=p&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"p\" class=\"latex\" \/> we choose. This makes sense intuitively, since <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/> is a constant function. It is already at its limit point no matter what <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x\" class=\"latex\" \/> in the domain we choose, so it will always converge to its limit quicker than, or at least at the same rate, as any other function we could choose.<\/p>\n<p><strong>Example 2<\/strong>:\u00a0<img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x%29%3Dx%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x)=x^2\" class=\"latex\" \/><br \/>\n<strong>p=1<\/strong>:\u00a0Consider <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1%3Dd&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1=d\" class=\"latex\" \/><\/p>\n<p><a href=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?ssl=1\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" data-attachment-id=\"1107\" data-permalink=\"https:\/\/blog.richmond.edu\/math320\/2017\/10\/13\/modulus-of-continuity\/img_0338\/\" data-orig-file=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?fit=3967%2C1755&amp;ssl=1\" data-orig-size=\"3967,1755\" data-comments-opened=\"0\" data-image-meta=\"{&quot;aperture&quot;:&quot;1.8&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;iPhone 7&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;1507861411&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;3.99&quot;,&quot;iso&quot;:&quot;32&quot;,&quot;shutter_speed&quot;:&quot;0.033333333333333&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;8&quot;}\" data-image-title=\"IMG_0338\" data-image-description=\"\" data-image-caption=\"\" data-medium-file=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?fit=300%2C133&amp;ssl=1\" data-large-file=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?fit=600%2C265&amp;ssl=1\" class=\"alignnone wp-image-1107 size-large\" src=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878-1024x453.jpg?resize=600%2C265&#038;ssl=1\" alt=\"\" width=\"600\" height=\"265\" srcset=\"https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?resize=1024%2C453&amp;ssl=1 1024w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?resize=300%2C133&amp;ssl=1 300w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?resize=768%2C340&amp;ssl=1 768w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?w=1200 1200w, https:\/\/i0.wp.com\/blog.richmond.edu\/math320\/files\/2017\/10\/IMG_0338-e1507903557878.jpg?w=1800 1800w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/a><\/p>\n<p>We will think about this example using the picture above. The double-edged cone area is where <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cf%28x%29-f%28c%29%7C%5Cleq+%5Csigma_1+%7Cx-c%7C&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|f(x)-f(c)|&#92;leq &#92;sigma_1 |x-c|\" class=\"latex\" \/> for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cx-c%7C%3C%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|x-c|&lt;&#92;delta\" class=\"latex\" \/>. If the <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x)\" class=\"latex\" \/> (where <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x\" class=\"latex\" \/> is in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%7Cx-c%7C%3C%5Cdelta&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"|x-c|&lt;&#92;delta\" class=\"latex\" \/>) falls into the double-edges cones, it pretends the local modulus of continuity.<br \/>\nWhen <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c%5Cin%28-1%2C1%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c&#92;in(-1,1)\" class=\"latex\" \/>, all of the points in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x%29%3Dx%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x)=x^2\" class=\"latex\" \/> fall into the double-edged cones. Thus <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1\" class=\"latex\" \/> is a local moduli of continuity for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/> when looking at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c%5Cin%28-1%2C1%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c&#92;in(-1,1)\" class=\"latex\" \/>.<\/p>\n<p>When <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c%5Cnot%5Cin%28-1%2C1%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c&#92;not&#92;in(-1,1)\" class=\"latex\" \/>,say <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x%3D2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x=2\" class=\"latex\" \/>, the graph of the function <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%28x%29%3Dx%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f(x)=x^2\" class=\"latex\" \/>\u00a0(the green highlighted part)\u00a0does not go inside the double-edged cones. Thus <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1\" class=\"latex\" \/> is not a local moduli of continuity for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/> when looking at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c%5Cnot%5Cin%28-1%2C1%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c&#92;not&#92;in(-1,1)\" class=\"latex\" \/>.<\/p>\n<h3>Connection to Derivatives<\/h3>\n<p>A simple way to see whether the graph of function falls into the cones that describe the modulus of continuity is to compare the slope of the function at the point <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c\" class=\"latex\" \/> with the slope of the modulus of continuity.<br \/>\nFor example: when <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x%3D2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x=2\" class=\"latex\" \/> ,The function is differentiable and has a slope of 4 at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x%3D2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x=2\" class=\"latex\" \/>. The function is growing locally with a rate of 4. But we are comparing it with <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1%3Dd&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1=d\" class=\"latex\" \/> with a growth rate of 1. The graph of the function stays outside of the cone.<br \/>\nSo for any slope that is larger than 1, <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1\" class=\"latex\" \/> is not a local modulus of continuity for that function at that point.<\/p>\n<p>Similarly, considering <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1%28d%29%3Dmd&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1(d)=md\" class=\"latex\" \/>. The m is the slope of the cones that describe the modulus of continuity. Any derivative of the function at a point that is greater than m means <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1\" class=\"latex\" \/> is not a local modulus of continuity for that function at that point. So in general,\u00a0<img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Csigma_1%3Dmd&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;sigma_1=md\" class=\"latex\" \/> is a local modulus of continuity for <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f\" class=\"latex\" \/> at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=c&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"c\" class=\"latex\" \/> if <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=m%5Cgeq+f%27%28c%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"m&#92;geq f&#039;(c)\" class=\"latex\" \/>.<\/p>\n<h3>References<\/h3>\n<p><a href=\"https:\/\/arxiv.org\/pdf\/math\/0607672.pdf\">https:\/\/arxiv.org\/pdf\/math\/0607672.pdf<\/a><\/p>\n<p><a href=\"https:\/\/www.revolvy.com\/main\/index.php?s=Modulus%20of%20continuity&amp;item_type=topic\">https:\/\/www.revolvy.com\/main\/index.php?s=Modulus%20of%20continuity&amp;item_type=topic<\/a><\/p>\n<p><a href=\"http:\/\/www.stat.cmu.edu\/~cshalizi\/754\/notes\/lecture-08.pdf\">http:\/\/www.stat.cmu.edu\/~cshalizi\/754\/notes\/lecture-08.pdf<\/a><\/p>\n<p><a href=\"http:\/\/fourier.eng.hmc.edu\/e176\/lectures\/NM\/node3.html\">http:\/\/fourier.eng.hmc.edu\/e176\/lectures\/NM\/node3.html<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>By: Rhiannon Begley and Shuyi Chen Introduction In class we have begun to and will continue to discuss functions, their continuity, and their limits at a particular point. Although we can determine the continuity and limits of functions with the tools we have learned in class, we cannot determine how quickly the function is converging [&hellip;]<\/p>\n","protected":false},"author":3532,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[58818],"tags":[],"class_list":["post-1057","post","type-post","status-publish","format-standard","hentry","category-class-blogs"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p7L4E1-h3","jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/posts\/1057","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/users\/3532"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/comments?post=1057"}],"version-history":[{"count":0,"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/posts\/1057\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/media?parent=1057"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/categories?post=1057"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.richmond.edu\/math320\/wp-json\/wp\/v2\/tags?post=1057"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}