If $A \subseteq B \subseteq X$ and we know that $X$ deformation retracts to $A$, can we say that $B$ also deformation retracts $A$?
Let $H$ be the deformation retraction of $X$ onto $A$. I was thinking that $F(b,t) = H(\iota (b),t) = H(b,t)$ would be a deformation retraction of $B$ onto $A$, but there is no reason to think that $H(b,t)$ will stay in $B$...
New thoughts about how to think about matrices and tensors:
Linear functions y=ax+b: one input value gives one output value, and such output can be normalised
Matrices and 2nd order tensors Ax=b: one ordered pair of inputs (x,y) gives one output value. The output can be normalised in the sense that the output is the combination of the unit output of the first and the unit output of the second
3rd order tensors: one ordered triples (x,y,z) gives one output value. and the output can likewise be decomposed similarly
Laurent series: Let's say I have to get the laurent series for (1/(z)(z-1)) in powers of z. Can I multiply 1/z by the series expansion I get from (1/(z-1)) to get my result?
Would anyone like to explain to me what it means that the/a Hesse-Matrix is positive semidefinite ?
As far as I know, you can have imaginary eingenvalues in the Hessematrices I am dealing with, what in a sense means that you can have negative curvature components (interpreting the Hesse Matrix as second derivative of some scalar function $\Bbb R \to R^n$.
Though "they say" its positive semidefinite and give the "whole thing" a ">0" sign.
Wait, its about the diagonal part of $$\frac{\partial^2 <\Psi(x)|\hat{H}|\Psi(x)>}{\partial x^2}$$, the claim is that this has only positive eigenvalues ... hmmm ..
Ok its the diagonal part of the symmetric part (does it make sense?) @Leaky
In economics, dynamic inconsistency or time inconsistency is a situation in which a decision-maker's preferences change over time in such a way that a preference can become inconsistent at another point in time. This can be thought of as there being many different "selves" within decision makers, with each "self" representing the decision-maker at a different point in time; the inconsistency occurs when not all preferences are aligned.
The term "dynamic inconsistency" is more closely affiliated with game theory, whereas "time inconsistency" is more closely affiliated with behavioral economics....
@Rithaniel Yes you are right thanks, I haven't explained correctly, I wanted to say that the bigger set resizes accordingly to the smaller. But this just confuses you. Let's just say that the sets have the same amount of elements
@quallenjäger If the original curve is $C^k$, the reparametrized curve will also be $C^k$. Note that arclength $s(t)$ of a $C^k$ curve parametrized by $t$ is again $C^k$ (because you integrate a $C^{k-1}$ function).
@Rudi: The real Hessian is a (real) symmetric matrix. If you're dealing with complex functions, probably the Hessian is the matrix of partials $\partial^2 f/\partial z_j\partial \bar z_k$? This will be Hermitian.
@TedShifrin Hi Ted! In general we deal with complex stuff, but in both cases the eigenvalues are real, though can be positive. For time independent QM, you can show that you can write everything real.
@quallenjäger: It's invertible as long as the original curve is regular (nowhere-zero velocity). That's the usual requirement for working with parametrized curves. Otherwise, of course, if the curve stops and sits somewhere for a while, you won't get an inverse.
@TedShifrin I am a bit lost, I mean $\alpha'(t)=0$ could also occur if the path changes its direction? it doesn't really has to be a point, where $s(t)=s(t')$ for some $t'>t$?
So what I am currently struggling is, what would be the sufficient condition to ensure that the reparametrized path to be $C^k$
Ok, then I have a problem. :D I would allow a general $C^1$ path, which I will allow stopping and change direction. I would like to know if I can reparametrize such path to a C^1 path with unit speed.
So, even though I started with a $C^\infty$ curve (doing $(t^2,0)$ or yours), arclength is only $C^1$. Now let's think about reparametrizing. Obviously, you can't do it continuously because the tangent vector to the arclength-parametrized curve would literally have to switch directions (as a unit vector) at the origin.
So there is no differentiable reparametrization by arclength.
@quallenjäger: To be specific, Darboux's Theorem tells you that the derivative always has the intermediate value property (even without assuming $C^1$), so there can be no differentiable such function.
Need some clarification on the definition of a term. In group theory, does "countably generated" means that the group has (a) countably many elements, or that it needs (b) countably many unique generators?
Okay, that makes sense. Though, that makes me think of a though I had a while back. Infinite sums are always of the form $\sum_{n\in\mathbb{N}} f(n)$. What if you were to somehow have a sum over an uncountable set?
If the derivative is nowhere-zero and varies continuously, then it cannot change direction at a point. It follows from basic stuff that the image is actually a $C^1$ $1$-dimensional manifold, @quallenjäger.
@Rithaniel: Note that you're using more than countability there. You're using an ordering, too.
No, I don't think so, @quallenjäger. Work out that theorem I told you about real-valued functions. Derivatives must have the intermediate value theorem, always.
There is no differentiable parametrization of $y=|x|$, no matter how hard you try, @quallenjäger.
With nowhere zero derivative, I mean.
Of course you can slow down, stop, and turn the corner.
I see your point. The problem that $(t^3,t^2)$ worked is because we can guarantee the continuity of the derivative by shrinking its tangent vector length. But if we keep the length as constant, then the only way to guarantee the continuity of the derivative is that the direction is closed to each other right?
But you can certainly modify this in $\Bbb R^2$ by considering the map to the unit circle, which can be (locally) parametrized by a subset of $\Bbb R$.
I don't understand, would the intermediate theorem mean, that for any two tangent vectors $f(a)=v,f(b)=w$, which can be thought as a function on the unit circle, there must be a point $\psi$ on the arc enclosed by $v,w $, such that $f'(s)=\psi$ for some $s\in[a,b]$
No, the converse. If $f$ maps to a particular arc in the unit circle (you have to remove a point to start with), then every point in the arc between $v$ and $w$ must be a value of $f$ somewhere.
I'm a few years late but here isn't the Serre proof the one using Bass-Serre theory to say that a group acting freely on a tree is free rather than going through covering spaces theory? @Balarka
Also my functional analysis is rusty, but I should review it for a course I want to take next term so this might be a good occasion to think about some FA
@AlessandroCodenotti I guess so. Bass-Serre theory gives the more general Kurosh subgroup theorem
If $G = A * B$ then subgroups are all of the form (free) * (free product of conjugates of subgroups of A) * (free product of conjugates of subgroups of B)
In class we only saw the usual subgroups of free groups are free as follow: By Bass-Serre theory a group acting freely on a tree is free, let $H\subseteq G$ with $G$ free, then $H$ acts freely on the Cayley graph of $G$ (wrt a free generating set) so it must be free
Let's see if I can reconstruct the proof of Kurosh subgroup theorem. $K(G, 1) = K(A, 1) * K(B, 1)$, so $\widetilde{K(G, 1)}$ looks like $Cayley(F_2)$ with vertex spaces being $K(A, 1)$ and $K(B, 1)$ alternatively and edges being one-point unions. This is what is known as a "graph of groups"
$G$ acts freely on this by deck transformations, and the quotient is $K(G, 1)$. The cover corresponding to $H \leq G$ is $\widetilde{K(G, 1)}/H$. The free action on the total space of this graph of groups restricts to an $H$-action on $Cayley(F_2)$
The graph of groups corresponding to this is $Cayley(F_2)/H$ with vertex spaces being stabilizers of the $G$-action on $Cayley(F_2)$. But those are conjugate to $A$ or $B$. The edge spaces are one-point union again.
$\widetilde{K(G, 1)}/H$ is $K(H, 1)$, so fundamental group of this recovers $H$. Collect the loops, that gives a contribution of a free group. Collect the "$A$ vertices", that gives a contribution of a free product of conjugates of $A \leq G$. Collect the "$B$ vertices", that gives a contribution of a free product of conjugates of $B \leq G$.
@BalarkaSen Er, I meant subgroups of conjugates of A, B, etc. The vertex spaces of $Cayley(F_2)/H$ are vertex spaces of $v \in Cayley(F_2)$ left invariant by some subgroup $K \leq \text{Stab}_v(G)$, quotiented by $K$.
Let $F$ be a field. The minimal polynomial of a Jordan Block $J_d(\lambda)$ of length $d$ to an eigenvalue $\lambda\in F$ is $(X-\lambda)^d$. My professor urged to see this by considering $F^d\cong F[X]/((X-\lambda)^d)$. Multiplication with $X$ induces a linear map on the right-hand space whose minimal polynomial is $(X-\lambda)^d$, but I don't see the correspondence to left multiplication with $J_d(\lambda)$ on $F^d$. Can anyone set me on the right path?
@topologicalmagician: If you remember being taught to check for extraneous roots in high school, this is part of the same thing. For example, when you solve $x=\sqrt{x+2}$ you show that if $x=\sqrt{x+2}$, then $x^2=x+2$, so $x=2$ or $x=-1$. However, checking for extraneous roots is asking whether the converse holds. So, yes, solving an equation is giving an iff ...
I don't really understand why you want to be so formal. I can't imagine a situation where you'd prove some statement like you envision instead of just showing that something exists, and is unique.
As Mike says, you're being very symbolic about it, so it's better to understand what you're doing. Yes, once you have a solution $x$, to establish that it's the unique solution, of course you typically show that if you have any ("other") solution $y$, then you must have $y=x$. On the other hand, you might have an algebraic argument where every step is an "iff" and then there's no need to make a separate argument.
Before you do fancy abstract stuff, I would recommend learning (1) differential geometry in $\Bbb R^3$ (curves and surfaces), (2) differentiable manifolds in $\Bbb R^n$ (Guillemin & Pollack).
For the former (e.g., my text that is freely available), you need solid multivariable calculus and some linear algebra. For the latter, you need multivariable analysis (understanding the derivative as a linear map and the inverse function theorem).
Depends on your background. I'm fond of my own textbook (for which there are lectures on YouTube). If you've had a serious real analysis course already, you could look at Munkres's Analysis on Manifolds ... Thanks to a @Balarka for plugging me. :P
When you're deeper into grad school and have an adviser then you should hope you remain interested in whatever you chose because it becomes hard to switch