{"id":31553,"date":"2017-04-27T02:05:47","date_gmt":"2017-04-27T07:05:47","guid":{"rendered":"http:\/\/blogs.ams.org\/mathgradblog\/?p=31553"},"modified":"2017-04-27T11:11:52","modified_gmt":"2017-04-27T16:11:52","slug":"manifold-66","status":"publish","type":"post","link":"https:\/\/blogs.ams.org\/mathgradblog\/2017\/04\/27\/manifold-66\/","title":{"rendered":"What is a Manifold? (6\/6)"},"content":{"rendered":"<p>In posts 1-3 we were able to reduce all of the geometry of a curve in 3-space to an interval <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Ba%2Cb%5D%5Csubset+%5Cmathbb%7BR%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"[a,b]&#92;subset &#92;mathbb{R}\" class=\"latex\" \/> along with two or three real-valued functions. We also discussed when two sets\u00a0of such data give equivalent (overlapping) curves. This enabled us to patch together a collection of such sets of data\u00a0into one unified spatial curve.<\/p>\n<p>We then studied the specific example of re-defining the metric on the plane so that its geometry is precisely that of a 2-sphere. We saw that for measurements of angles, lengths, and areas, all we need is a dot-product on vectors. Given an open domain in the plane, once we have a dot-product, we will be able to make\u00a0such measurements. Our goal in this post\u00a0is to make the following definition of a manifold more tangible.<\/p>\n<p><!--more--><\/p>\n<p>Begin with a topological space <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\" \/>. (Note we cannot talk about any structure other than continuous\u00a0maps from or to this space.) Assume that for every <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x+%5Cin+X&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x &#92;in X\" class=\"latex\" \/>, there is an open neighborhood <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=N_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"N_x\" class=\"latex\" \/> of <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\" \/> homeomorphic to an open domain <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> in the plane: <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_x+%3A+N_x+%5Clongrightarrow+U_x+.&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _x : N_x &#92;longrightarrow U_x .\" class=\"latex\" \/> These are called &#8220;charts&#8221;, or coordinate maps.<\/p>\n<p>Given this the\u00a0question now is: How do we make sense of the notions of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>-ness and length for a curve <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5Csubset+N_x%5Csubset+X&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C&#92;subset N_x&#92;subset X\" class=\"latex\" \/>? One way we might hope to do this is by using our coordinate maps. That is we say that <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\" \/> is <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> if <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_x%28C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_x(C)\" class=\"latex\" \/> is $C^1$ and we define the length of $C$ to be the length of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_x%28C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_x(C)\" class=\"latex\" \/>.<\/p>\n<p>As illustrated in a picture in the<a href=\"http:\/\/blogs.ams.org\/mathgradblog\/2017\/02\/13\/manifold-56\/\">\u00a0previous post<\/a>, this definition of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>-ness is not a satisfactory one\u00a0because some curves will lie simultaneously in two neighborhoods, say <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> and <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_y&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_y\" class=\"latex\" \/>, and there is no guarantee that if its image in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> is <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>, it must also be <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>\u00a0in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_y&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_y\" class=\"latex\" \/>.<\/p>\n<p>However, the two images are transformed to one another by the map <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_x+%5Ccirc+%5Cphi+_y%5E%7B-1%7D+%3A+U_y+%5Clongrightarrow+U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _x &#92;circ &#92;phi _y^{-1} : U_y &#92;longrightarrow U_x\" class=\"latex\" \/> (See the\u00a0<a href=\"http:\/\/blogs.ams.org\/mathgradblog\/2017\/02\/13\/manifold-56\/\">previous article<\/a> for the reason.) Therefore, if these &#8220;transition maps&#8221; between subsets of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cmathbb%7BR%7D%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;mathbb{R}^2\" class=\"latex\" \/> are <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>, then without ambiguity, we can define a subset of <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\" \/> to be a <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> curve if its image under any (and hence all) of the chart maps is a <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> curve in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cmathbb%7BR%7D%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;mathbb{R}^2\" class=\"latex\" \/>.<\/p>\n<p>The space <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\" \/> together with the data of coordinate charts with the properties above is a 2-dimensional <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> manifold.<\/p>\n<p>As sketched above, for such manifolds, it is meaningful to talk about <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> curves, or <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> functions <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f%3A+X+%5Clongrightarrow+%5Cmathbb%7BR%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f: X &#92;longrightarrow &#92;mathbb{R}\" class=\"latex\" \/>. In the latter case, we say <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 <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> if <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=f+%5Ccirc+%5Cphi+_x%5E%7B-1%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"f &#92;circ &#92;phi _x^{-1}\" class=\"latex\" \/> is\u00a0<img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> for all <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\" \/>.<\/p>\n<p>Hopefully, now, the idea is starting to make sense.\u00a0A <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^2\" class=\"latex\" \/> manifold is\u00a0a topological space with charts whose transition maps are <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^2\" class=\"latex\" \/>. For these manifolds, we can talk about second derivative of functions. A smooth manifold is\u00a0one with smooth, i.e. <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E%5Cinfty&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^&#92;infty\" class=\"latex\" \/>, transition maps&#8230; Well, as is noted in [1, pg. 9], &#8220;Usually additional technical assumptions on the topological space are made to exclude pathological cases. It is customary to require that the space be Hausdorff and second countable.&#8221;<\/p>\n<p><strong>Definition: <\/strong>&#8220;A <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5Er&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^r\" class=\"latex\" \/> n-manifold&#8221; is a Hausdorff and second countable topological space, with charts that map into open domains of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cmathbb%7BR%7D%5En&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;mathbb{R}^n\" class=\"latex\" \/> such that the\u00a0transition maps are <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5Er&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^r\" class=\"latex\" \/>.<\/p>\n<p>Where did the metric go?! How do we measure lengths?<\/p>\n<p>Remember I said we might try to\u00a0define the length of a curve <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5Csubset+N_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C&#92;subset N_x\" class=\"latex\" \/> by saying it is equal to the length of the\u00a0curve \u00a0<img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_x%28C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_x(C)\" class=\"latex\" \/> lying in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/>? Well, this begs the question: How do we compute the length of <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_x%28C%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_x(C)\" class=\"latex\" \/>, because <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> might have a metric other than the usual Euclidean one.\u00a0For example,\u00a0recall the metric on the plane from our example in the <a href=\"http:\/\/blogs.ams.org\/mathgradblog\/2016\/12\/02\/manifold-46\/\">fourth post<\/a> in this series. This means we run into a problem similar to the one we had when defining <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>-ness. If each <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> has its own metric, then a curve on the manifold may\u00a0have different\u00a0lengths, depending on the chart we use\u00a0for the measurement. This will make the length undefinable by looking at charts, unless, some\u00a0very intricate compatibility assumptions are\u00a0imposed on the metrics of the <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/>&#8216;s.<\/p>\n<p>The good\u00a0news is that one usually takes a different approach: A metric is built on the manifold upfront, rather than pieced together from collection of metrics on various <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/>&#8216;s that happen to magically be compatible in an complex manner. The key thing\u00a0that makes this direct construction on the metric on a manifold possible, is the existence\u00a0of &#8220;the tangent space&#8221;.<\/p>\n<p>Fix a point <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=x+%5Cin+X&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"x &#92;in X\" class=\"latex\" \/>, a <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/> manifold. In a chart <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _1\" class=\"latex\" \/>, the point <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 represented by <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_1+%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _1 (x)\" class=\"latex\" \/>. Since <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_2+%5Ccirc+%5Cphi+_1%5E%7B-1%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _2 &#92;circ &#92;phi _1^{-1}\" class=\"latex\" \/> is bijective and <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=C%5E1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"C^1\" class=\"latex\" \/>, its derivative at the point <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_1+%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _1 (x)\" class=\"latex\" \/> existences, and is a <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=2%5Ctimes2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"2&#92;times2\" class=\"latex\" \/> invertible matrix, mapping vectors centered at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_1+%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _1 (x)\" class=\"latex\" \/> to vectors centered at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_2+%28x%29.&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _2 (x).\" class=\"latex\" \/> Thus, if we fix a vector <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=v_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"v_1\" class=\"latex\" \/> at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_1+%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _1 (x)\" class=\"latex\" \/>, then in any other chart <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_%5Cgamma&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_&#92;gamma\" class=\"latex\" \/> there is\u00a0a corresponding vector <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=v_%5Cgamma&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"v_&#92;gamma\" class=\"latex\" \/> centered at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_%5Cgamma+%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_&#92;gamma (x)\" class=\"latex\" \/>. We call this collection of vectors, one from each chart, &#8220;a tangent vector to <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\" \/> at <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\" \/>.&#8221; By varying <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=v_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"v_1\" class=\"latex\" \/> in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_1&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_1\" class=\"latex\" \/>, we see that the collection of all tangent vectors to <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\" \/> at <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 one-to-one relation with the vector space of all vectors centered at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi+_1%28x%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi _1(x)\" class=\"latex\" \/>, which in turn is a copy of the vector space <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cmathbb%7BR%7D%5E2.&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;mathbb{R}^2.\" class=\"latex\" \/> Thus, this collection is naturally a vector space. We denote it by <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=T_xX&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"T_xX\" class=\"latex\" \/>. The key feature is that the tangent spaces were constructed from charts and not from an ambient space in which <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\" \/> sits in.<\/p>\n<p><a href=\"http:\/\/blogs.ams.org\/mathgradblog\/files\/2017\/04\/tangent.jpg\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-medium wp-image-31589\" src=\"http:\/\/blogs.ams.org\/mathgradblog\/files\/2017\/04\/tangent-300x169.jpg\" alt=\"\" width=\"300\" height=\"169\" srcset=\"https:\/\/blogs.ams.org\/mathgradblog\/files\/2017\/04\/tangent-300x169.jpg 300w, https:\/\/blogs.ams.org\/mathgradblog\/files\/2017\/04\/tangent-768x432.jpg 768w, https:\/\/blogs.ams.org\/mathgradblog\/files\/2017\/04\/tangent-1024x576.jpg 1024w, https:\/\/blogs.ams.org\/mathgradblog\/files\/2017\/04\/tangent.jpg 1366w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/><\/a><\/p>\n<p><strong>Definition<\/strong>: &#8220;A metric&#8221; on <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 a choice of an inner product on each of the tangent spaces <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=T_xX&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"T_xX\" class=\"latex\" \/> that continuously depends on <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\" \/>.<\/p>\n<p>In our example of the plane with the metric of a sphere, attached at each <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%28x%2Cy%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"(x,y)\" class=\"latex\" \/>, we think of a copy of the vector space <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cmathbb%7BR%7D%5E2&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;mathbb{R}^2\" class=\"latex\" \/>. Then the inner product of the plane centered at <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%28x%2Cy%29&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"(x,y)\" class=\"latex\" \/> is <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cfrac%7B4%7D%7B1%2Br%5E2%7D&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;frac{4}{1+r^2}\" class=\"latex\" \/> times the usual inner product of the plane.<\/p>\n<p>What happens is that for the low dimensional tangible cases where we have a hyper-surface in a Euclidean space this abstract notion of a tangent space coincides with the &#8220;tangent plane&#8221; to the surface. For example, the tangent space to the sphere in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=R%5E3&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"R^3\" class=\"latex\" \/> is the copy of 2-plane touching the sphere at one point. The vectors in this tangent can be alternatively viewed as vectors in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=R%5E3&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"R^3\" class=\"latex\" \/>, and therefore, their inner product is defined. Therefore, by &#8220;cheating&#8221;, most visualizable spaces come with an inner product. (This is, of course, far from being the only one.) Notice we are cheating, because, we are not supposed to work with an ambient space. Here we look at the ambient space to come up with an inner product, and then forget about the ambient space again, thus, ending with a metric in the manifold sense.<\/p>\n<p><strong>Definition: <\/strong>A Riemannian manifold is a smooth manifold equipped with a smooth inner-product.<\/p>\n<p>Riemannian manifolds are where we can do measurements. As said above, we deform the inner product on <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> according to the one on the manifold: If two vectors tangent to the manifold have a dot product equal to <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=t&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"t\" class=\"latex\" \/>, we define their images under <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=%5Cphi_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"&#92;phi_x\" class=\"latex\" \/> to have the same inner product in the metric that will be induced on <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/>. Then, we measure lengths of curves in <img decoding=\"async\" src=\"https:\/\/s0.wp.com\/latex.php?latex=U_x&#038;bg=ffffff&#038;fg=000&#038;s=0&#038;c=20201002\" alt=\"U_x\" class=\"latex\" \/> by this new metric. Similarly, areas can be discussed. Moreover, metric opens up the rich study of &#8220;curvature&#8221; on manifolds.<\/p>\n<p><strong>End-note:<\/strong> Why do we begin with a topological space, rather than with the sets\u00a0of data I discussed earlier? That is, could we begin with a collection of open domains along with transition maps of certain smoothness, and call this collection a manifold? The answer is that, there may be many ways of patching together the pieces of data. For instance, one could always decide to leave all patches disconnected and have a union of disjoint manifolds, or decide not to patch even when the data is compatible. Thus, beginning with sets of info, there are too many possibilities, and therefore it is wise to start with a topological space as our &#8220;canvas&#8221; onto which more delicate details will be painted.<\/p>\n<p>[1] Vladimir G. Ivancevic, <em>Applied Differential Geometry: A Modern Introduction<\/em>, (2007).<\/p>\n<div style=\"margin-top: 0px; margin-bottom: 0px;\" class=\"sharethis-inline-share-buttons\" ><\/div>","protected":false},"excerpt":{"rendered":"<p>In posts 1-3 we were able to reduce all of the geometry of a curve in 3-space to an interval along with two or three real-valued functions. We also discussed when two sets\u00a0of such data give equivalent (overlapping) curves. This &hellip; <a href=\"https:\/\/blogs.ams.org\/mathgradblog\/2017\/04\/27\/manifold-66\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n<div style=\"margin-top: 0px; margin-bottom: 0px;\" class=\"sharethis-inline-share-buttons\" data-url=https:\/\/blogs.ams.org\/mathgradblog\/2017\/04\/27\/manifold-66\/><\/div>\n","protected":false},"author":118,"featured_media":0,"comment_status":"open","ping_status":"closed","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":""},"categories":[12,1],"tags":[262,124,295],"class_list":["post-31553","post","type-post","status-publish","format-standard","hentry","category-math","category-uncategorized","tag-manifold","tag-math","tag-topology"],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p3gbww-8cV","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/posts\/31553","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/users\/118"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/comments?post=31553"}],"version-history":[{"count":18,"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/posts\/31553\/revisions"}],"predecessor-version":[{"id":31591,"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/posts\/31553\/revisions\/31591"}],"wp:attachment":[{"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/media?parent=31553"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/categories?post=31553"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.ams.org\/mathgradblog\/wp-json\/wp\/v2\/tags?post=31553"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}