In baseball, a grand slam is a home run hit with all three bases occupied by baserunners ("bases loaded"), thereby scoring four runs—the most possible in one play. According to The Dickson Baseball Dictionary, the term originated in the card game of contract bridge, in which a grand slam involves taking all the possible tricks. The word slam, by itself, usually is connected with a loud sound, particularly of a door being closed with excess force; thus, slamming the door on one's opponent(s), in addition to the bat slamming the ball into a home run.
== Highlights ==
=== Players ===
Roger Connor is...
Can someone please xlarify the meaning of a non dense subset in a metric space. I thought a subset A in ametric space X is said to be non-dense iff it's not dense, i.e. $cl(A)\neq X.$ But strangely enough, our professor gives a weird complicated definition for the same: A set is said to be non-dense iff there exist for every open sphere $B(x,\epsilon)$ another open sphere $B(x_1,\epsilon_1)\subseteq B(x,\epsilon)$ such that $B(x_1,\epsilon_1)$ is free from any point of the set $E.$
Can someone please clarify which is a relatively standard notion?
In the internet I find no articles about non dense sets. Only the term nowhere dense is there everywhere. That makes me even more confused.
@ThomasFinley what your professor calls "non-dense" is called nowhere dense
I never heard of "non-dense" but according to this site for example, its another name for nowhere dense, so I guess some people do use it
the idea is that a nowhere dense set is not only not dense, but its not dense in any open non-empty set
@Jakobian @Claudio this formula by the way, it should be true for partial derivatives, not sure what it would mean for gradients I guess there is some version for that too
@Jakobian In the definition: a set is said to be non-dense iff there exist for every open sphere $B(x,\epsilon)$ another open sphere $B(x_1,\epsilon_1)\subseteq B(x,\epsilon)$ such that $B(x_1,\epsilon_1)$ is free from any point of the set $E.$ we can also replace the open spheres by open sets and even then it seems to coz no problem, isn't it?
Then it becomes: a set is said to be non-dense iff there exist for every open set $U$ another open set $U_1\subseteq U$ such that $U_1\cap E=\phi.$
Imho these two definitions seems to be equivalent, right?
But I'm talking about any random metric space $(X,d).$
I can prove that this is indeed valid for any metric space $(X,d)$ if the following statement holds: Let $x\in X.$ For every $r>0$ there exists a $y\in X$ such that $d(x,y)<r$
Again, my question is: Is the above above statement really valid?
Let the nonempty sets $A,B$ be with the property that $A \cup B= N^* $ and they are disjoint. Determine the functions $f:N^* \to N^* $ with the property that $f(m+n)=f(m)+f(n)$, for any pair $(m,n) \in (A \times A) \cup (B \times B)$.
So I thought of taking the case where both are zero, then we get the fact that $f(0)=0$.
Another interesting thing I discovered is that if we take $n \to -n$ then we have a periodic function $f(m)=f(m-n)+f(0)=f(m+n)$.(idk if this stands cus we have natural numbers but anyway)
How would I prove for two PMFs $P$ and $Q$ on countably infinite support $A$, if $D(P||Q) < \infty \implies \sum_{x} P(x) |\log(\frac{(P(x)}{Q(x)})| < \infty$. I tried to split them over the positive and negative part sums and show each one is finite, but I can't apply the log-sum inequality to do so because I have an infinite support
Defining the set $A^+ = \{x \in A | \frac{P(x)}{Q(x)} \ge 1\}$ and taking $A^-$ to be the complement I can split $D(P||Q)$ into two sums $S_1$ & $S_2$ over each disjoint support. It suffiices to show that $S_1$ (positive sum) or $S_2$ (negative sum) is finite, the easiest way I think is to apply jensens inequality in the form of the log-sum inequality but I can't do that since I don't know if the sum converges absolutely.
Other way I think is to basically show that $S_1$ and $S_2$ can't be infinite, so the partial sums can't be conditionally convergent - however I am unsure of how to start this. I think there is a simpler way...any advice??
$D(P||Q) = \sum_x P(x) \log(\frac{P(x)}{Q(x)})$ - probably want to use that the sum of the pmfs is 1 somehow but I can't see it...
Consider the inverse function which we all know and love. It says that if the function is $C^1$ and the determinant of the Jacobian matrix does not vanish at a given point in the domain, then we are guaranteed a $C^1$ inverse in a neighborhood around that point. Now suppose the determinant of the Jacobian matrix does not vanish at each point of the domain. Does this mean we can form a global inverse of all the local inverses we obtain at each point?
@psie you were already given a counter-example, but perhaps the most instructive counter-example is the complex eponential $\mathbb{C}\rightarrow\mathbb{C}^{\times},\,z\mapsto\exp(z)$
I'm re-following the course since I passed the written exam last time and I thought I could maintain the vote for the next session and then do the oral part of it but I actually couldn't. But the course material expanded and changed a bit (they added a small measure theory part)
and so here I am, but actually these notes are mine not my professor's, this is just the same example of the book which I kind of expanded with some drawings and additional things hahahha
My professor's says, that: a subset $A$ of a metric space $(X,d)$ is said to be compact in X iff every sequence in $A$ has a convergent subsequence that converges to a point in X which is not necessarily in A. However, a subset A of a metric space $(X,d)$ is said to be compact iff every sequence in $A$ has a convergent subsequence that converges to a point in A.
Is this distinction between the phrases, "a compact subset of a metric space" and "a subset is compact in a metric space X" very standard?
Our professor gives an example : (a,b) is compact in [a,b] where a<b and [a,b] is a subspace of the metric space R equipped with the absolute value metric.
the standard definition here is "a subset of a metric space is compact if every sequence has a subsequence converging in the subset"
Lurie is very funny. "The construction of $\mathrm{Mod}_A^\mathcal{O}(\mathcal{C})^\otimes$ is fairly straightforward" proceeds to give a highly technical definition 2 pages long
In mathematics, a relatively compact subspace (or relatively compact subset, or precompact subset) Y of a topological space X is a subset whose closure is compact.
== Properties ==
Every subset of a compact topological space is relatively compact (since a closed subset of a compact space is compact). And in an arbitrary topological space every subset of a relatively compact set is relatively compact.
Every compact subset of a Hausdorff space is relatively compact. In a non-Hausdorff space, such as the particular point topology on an infinite set, the closure of a compact subset is not necessarily...
I've been torturing myself for the majority of today and am this close to understanding what it means to state that an $\infty$-topos is a presentable $\infty$-category in which all colimits are van Kampen :)
it's a mixture of absolute torture and genuine beauty
I learned yesterday that an edge is cartesian for the codomain fibration $\mathrm{Fun}(\Delta^1,\mathcal{C})\rightarrow\mathcal{C}$ if and only if it classifies a cartesian square in $\mathcal{C}$
so if $\mathcal{C}$ has pullbacks, the codomain fibration is cartesian; and it is always cocartesian
if you now pull this back along a map $\Delta^1\rightarrow\mathcal{C}$ classifying a morphism $f\colon x\rightarrow y$, you have a bicartesian fibration over the interval, which, by straightening-unstraightening both ways, classifies the pushforward-pullback adjunction $f_{\ast}\colon\mathcal{C}^{/x}\leftrightarrows\mathcal{C}^{/y}\colon f^{\ast}$
I found the following definitions for a bounded set in a metric space: Let A be a subset of a metric space (X,d).
Defn 1: A is bounded iff the diameter of A is finite (The defn of diam of a set is the supremum of all d(x,y)s such that $x,y$ are elements in the set)
Defn 2: A is bounded iff $\exists p\in X$ and a $B\in \Bbb R$ such that $d(x,p)\leq B,\forall x\in A.$
@ThomasFinley If you think that the definitions are not equivalent then give an example where something is bounded according to one of the definitions and not bounded according to the other
Ok, if diam (A) is finite then $\exists B\in \Bbb R$ such that for all x,y in A we have $d(x,y)\leq B$. Now, let $a\in A.$ This means that $a\in X\implies d(x,a)\leq B,\forall x\in A$. So, $\exists a\in X$ such that $d(x,a)\leq B,\forall x\in A.$
Conversely, if $\exists k\in X,B\in \Bbb R$ such that $d(x,k)\leq B$ for $x\in A$ then, $\forall x,y\in A$ we have, $d(x,y)\leq d(x,k)+d(k,y)=2B.$
@SoumikMukherjee Isn't this a valid proof of their equivalence?
Define the cohomology of $X$ as a direct sum over the strata: $H^k(X) = \bigoplus_{i=0}^n H^k(X_i),$ where each $H^k(X_i)$ represents the cohomology of the $k_i$-dimensional manifold $X_i$. Does $H^k(X)$ in some fashion, encode contributions of the cohomology over the individual strata, or is this an innacurate conclusion?
@ModularMindset you defined it to encode this data perfectly
well, not the relations, but all of the strata cohomology
I don't know why you would make this definition
it seems redundant
if you want to measure how the information of the strata relates to the whole, you should consider something like $\varprojlim_i H^k(X_i)$. ...but then $\varinjlim_i H_k(X_i)$ strikes me as the better option
perhaps not if you scrutinize enough, but the fact that there's a workable description of how to compute colimits in $\mathrm{Cat}_{\infty}$ at all is still crazy
@BenSteffan Yes that is a fair point - I did calculate that the Euler char. is zero which should tell me that the cohomology (number of holes) is in some sense "balanced." Although I'm not sure what "balanced" really means yet
I do know about the betti numbers in this context
fwiw that Euler char. calcuation hints at a toroidal like structure
Here's a problem from Spivak's Calculus on Manifolds, which comes right after the inverse function theorem (IFT).
> Problem Let $A\subset \mathbb R^n$ be an open set and $f:A\to\mathbb R^n$ a continuously differentiable injective function such that $\det f'(x)\neq 0$ for all $x$. Show that $f(A)$ is an open set and $f^{-1}:f(A)\to A$ is differentiable. Show also that $f(B)$ is open for any open set $B\subset A$.
Suggested solution For every $y\in f(A)$, there is an $x\in A$ with $f(x)=y$. By the IFT, there is an open subset $U\subset A$ and an open subset $V\subset\mathbb R^n$ such that $x\in U$ and $f(U)=V$. ...
Question Why does the IFT imply that $f(U)=V$? It says that $x\in U$ and $f(x)\in V$, but why would $f(U)=V$? (see the IFT below)
So, $|z|<2$ is equivalent to $\frac{|z|}2 <1$. In $\frac{1}{(2-z)^2}=\frac 1{(2(1-z/2))^2}$
So, a part from the $1/4$, you're interested in the LS of $\frac 1{(1-z/2)^2}$. The formula you found differentiating the geometric series works when $|z|/2<1$
So you write the series and you're done
For $|z|>2$, note that $\frac 2{|z|}<1$ and then you manipulate $f(z)$ to be in the conditions to apply the geometric series when $\frac 2{|z|}<1$
In my book, they say that if $T$ is a bounded linear map between normed spaces $X$ and $Y$, then $\|Tx\|\leq\|T\| \|x\|$ holds. Here the norm on $T$ is the familiar operator norm, i.e. the $\sup$ over the unit ball of $\|Tx\|$. Looking at the proof of the inequality, it really seems to depend on the operator norm. E.g. does the inequality hold for the norm $\|T\|_\infty=\max\limits_{1\leq i\leq n}\sum_{j=1}^\infty |T_{ij}|$?
psie yes the proof is specific to the operator norm. note e.g. that if \| \| is one norm on a space c > 0 then c \| \| is also a norm on the same space. so if X and Y and T are given but the norms are "up for playing around with" you can potentially get whatever you want as values for the ingredients in the left and right hand sides of that inequality.
@psie not exactly sure what you are asking, given a norm (or norms, really, for $X,Y$) then there is an induced norm on operators. However, the norm you gave is an operator norm for $\|x\|_\infty$.
psie: to ask whether the inequality holds or not in some altered set of facts, you should specify all of the norms, not just the norm you plan to use on T
psie: note that what "the operator norm" is depends on what norms you choose on X and Y, and that inequality would hold for any choices of norms on X and Y as long as T is bounded and you use the corresponding operator norm for ||T||.
we have talked elsewhere about how context is often used to supply meaning for symbols like \| \| that would otherwise be overloaded with subscripts, and that there are good reasons for this. but again, if you find yourself in a situation where you find yourself focusing on this stuff, i would feel very free to invent your own notation and decorate accordingly.
e.g. [as one choice not a universal choice] writing \| \|_V for the norm on the normed space V, and letting B(X,Y) denote the space of bounded linear maps, and understanding this notation to include not just the set of maps but the operator norm induced from the norms on X and Y, you'd get: \|Tx\|_Y \leq \|T\|_{B(X,Y)} \|x\|_X true for any normed spaces X, Y
psie: i'm not sure i understand what X and Y even are in that example. I only understand that T, an operator from X to Y, apparently has (entries?) T_ij associated it, with i from 1 to n and j from 1 to infty.
@BenSteffan Yeah that's possible, the proof of that doesn't take long (1/4 page maybe) and it still seems to be more elegant than the proof Wikipedia gives using adjugates
I have developed all the calculations finally: $$ g = x^TA^TAx-2b^TAx \Rightarrow \nabla g = \partial_{\mathbf{x}}g = 2x^TA^TA-2b^TA, \text{ for } A \ne [0]_{m \times n}, b \ne \mathbf{0} $$