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closed as off-topic by Arthur Fischer Sep 18 '14 at 10:37

  • This question does not appear to be about Mathematics Stack Exchange or the software that powers the Stack Exchange network within the scope defined in the help center.
If this question can be reworded to fit the rules in the help center, please edit the question.

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I have added a [sandbox] tag to allow people ignore it more easily (via software support of ignoring tags), and since it seems that we have two sandboxes now, a tag may seem a bit more in place here. –  Asaf Karagila Jul 18 '12 at 8:35
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(+1) For thinking outside the (sand)box. –  cardinal Jul 18 '12 at 19:40
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At the suggestion of the moderators, I have gone and changed the associated owners of all the answers here to the Community user. This way, the original owners will not receive excess pings for each time another user uses the draft space for their work. Enjoy! –  Grace Note Oct 5 '12 at 14:45
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To prevent crashes I've found the "Bookmarks to disable/enable MathJax", provided in here, pretty useful. –  leo Dec 17 '12 at 18:03
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This "sandbox" is being closed to prevent the creation of new answers. To start a draft, simply edit one of the existing free answers. –  Arthur Fischer Sep 18 '14 at 10:37

17 Answers 17

Meanwhile I got it...

Equality

Denote for readability: $$\mathcal{D}:=\mathcal{D}N=\mathcal{D}N^*=:\mathcal{D}^*$$

Remind for reducibility:* $$PN\subseteq NP\iff N\left(\mathcal{S}^{(\perp)}\cap\mathcal{D}\right)\subseteq\mathcal{S}^{(\perp)}\quad(P\mathcal{D}\subseteq\mathcal{D})$$

For the domain: $$P\mathcal{D}^*=P\mathcal{D}\subseteq\mathcal{D}=\mathcal{D}^*$$

Check invariance: $$\varphi\in\mathcal{S}\cap\mathcal{D}^*:\quad\langle N^*\varphi,\chi\rangle=\langle\varphi,N\chi\rangle=0\quad(\chi\in\mathcal{S}^\perp\cap\mathcal{D})$$ $$\psi\in\mathcal{S}^\perp\cap\mathcal{D}^*:\quad\langle N^*\psi,\chi\rangle=\langle\psi,N\chi\rangle=0\quad(\chi\in\mathcal{S}\cap\mathcal{D})$$

By denseness one gets: $$N\left(\mathcal{S}^{(\perp)}\cap\mathcal{D}^*\right)\subseteq\mathcal{S}^{(\perp)}$$

For polynomials note: $$PN^k{N^*}^l\subseteq N^kP{N^*}^l\subseteq N^k{N^*}^lP$$

Denote the domain: $$\mathcal{D}_0:=\bigcup_{R>0}\mathcal{R}E(B_R)\subseteq\bigcup_{k,l=0}^\infty\mathcal{D}N^k{N^*}^l$$

Regard dense elements: $$\overline{\mathcal{D}_0}=\mathcal{H}:\quad\varphi\in\mathcal{S}^{(\perp)}\cap\mathcal{D}_0$$

They have compact support: $$\Omega_\varphi:=\operatorname{supp}\nu_\varphi\subseteq\overline{B_{R_\varphi}}$$

So polynomials are dense: $$\overline{\mathcal{P}(\Omega_\varphi)}=\overline{\mathcal{C}(\Omega_\varphi)}=\mathcal{L}^2(\Omega_\varphi)$$

Thus one obtains: $$E(A)\varphi=\lim_np_n(N,N^*)\varphi\in\overline{\mathcal{S}^{(\perp)}}=\mathcal{S}^{(\perp)}$$

By density one has:** $$\varphi\in\mathcal{S}^{(\perp)}:\quad\varphi=\lim_n\varphi_n\quad(\varphi_n\in\mathcal{S}^{(\perp)}\cap\mathcal{D}_0)$$

By continuits one gets: $$E(A)\varphi=\lim_nE(A)\varphi_n\in\overline{\mathcal{S}^{(\perp)}}=\mathcal{S}^{(\perp)}$$

Concluding equality.

Inclusion

For the domain issue: $$\int|f|^2\mathrm{d}\nu_{P\varphi}=\lim_n\int|s_n|^2\mathrm{d}\nu_{P\varphi}=\lim_n\|s_n(E)P\varphi\|^2\\=\lim_n\|Ps_n(E)\varphi\|^2 \leq\lim_n\|s_n(E)\varphi\|^2=\lim_n\int|s_n|^2\mathrm{d}\nu_\varphi=\int|f|^2\mathrm{d}\nu_\varphi<\infty$$

And they act same: $$Pf(E)\varphi=P\lim_ns_n(E)\varphi=\lim_n Ps_n(E)\varphi=\lim s_n(E)P\varphi=f(E)P\varphi$$

Concluding inclusion.

Strictness

Consider the case: $$\|\mathrm{supp}E\|=\infty:\quad\mathcal{D}N\subsetneq\mathcal{H}$$

Then one has: $$\mathcal{D}(0N)=\mathcal{D}N\subsetneq\mathcal{H}=\mathcal{D}(0)=\mathcal{D}(N0)$$

Concluding strictness.

*See the thread: Characterization

**See the flaw: Denseness

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Adjoint Formula

It holds the relations: $$\mathrm{ad}_\varepsilon(A)=\delta\tau_{+\varepsilon}[A]e^{i\varepsilon H}=e^{i\varepsilon H}\delta\tau_{-\varepsilon}[A]$$

They are derivations: $$\mathrm{ad}_\varepsilon(AB)=\mathrm{ad}_\varepsilon(A)B+A\mathrm{ad}_\varepsilon(B)$$

And they vanish on: $$\mathrm{ad}_\varepsilon(e^{itH})=i[\delta H_\varepsilon,e^{itH}]=0$$

By iteration one gets: $$\mathrm{ad}_\varepsilon^N(A)=\delta\tau_{+\varepsilon}^N[A]e^{Ni\varepsilon H}=e^{Ni\varepsilon H}\delta\tau_{-\varepsilon}^N[A]$$

Also they commute: $$\tau_\varepsilon,\mathrm{id}\in\mathcal{B}(\mathcal{B}(\mathcal{H})):\quad\tau_\varepsilon\circ\mathrm{id}=\mathrm{id}\circ\tau_\varepsilon$$

And they preserve: $$\tau:\mathbb{R}\to\mathcal{B}(\mathcal{B}(\mathcal{H})):\quad\tau^{\varepsilon+\varepsilon'}=\tau^\varepsilon\circ\tau^{\varepsilon'}$$

By Newton's formula: $$\delta\tau_\varepsilon^N=\frac{1}{\varepsilon^N}\sum_{n=0}^N\binom{N}{n}(-1)^{N-n}\tau^{n\varepsilon}$$

So one derives at: $$\mathrm{ad}_\varepsilon^N(A)=\frac{1}{\varepsilon^N}\sum_{n=0}^N\binom{N}{n}(-1)^{N-n}\tau^{n\varepsilon}[A]e^{iN\varepsilon H}$$

Concluding formula.

Taylor Expansion

Regard an expansion: $$F_\varepsilon\in\mathcal{C}^N(\mathbb{R},E):\quad F_\varepsilon=P^\varepsilon_K+R^\varepsilon_K$$

For Taylor polynomial:* $$\frac{1}{\varepsilon^N}\sum_{n=0}^N\binom{N}{n}(-1)^{N-n}P^\varepsilon_K(n\varepsilon)\stackrel{K=N-1}{=}0$$

Suppose one has: $$\|F_\varepsilon^{(N)}(n\varepsilon s)\|^{\varepsilon\neq0}_{s\in[0,1]}<\infty:\quad F_\varepsilon^{(N)}(n\varepsilon s)\stackrel{\varepsilon\to0}{\to} F_0^{(N)}(0)$$

For Taylor remainder:* $$\lim_{\varepsilon\to0}\frac{1}{\varepsilon^N}\sum_{n=0}^N\binom{N}{n}(-1)^{N-n}R_K(n\varepsilon)\stackrel{K=N-1}{=}F_0^{(N)}(0)$$

Concluding expansion.

Adjoint Variation

By the previous thread: $$\left.\frac{\mathrm{d}^N}{\mathrm{d}t^N}\right|_{t=n\varepsilon s}\tau^t[A]e^{iN\varepsilon H}\varphi=\tau^{n\varepsilon s}[\mathrm{ad}^N(A)]e^{iN\varepsilon H}\varphi$$

They admit a dominant: $$\|\tau^{n\varepsilon s}[\mathrm{ad}^N(A)]e^{iN\varepsilon H}\varphi\|\leq\|\mathrm{ad}^N(A)\|\cdot\|\varphi\|$$

And converge pointwise: $$\tau^{n\varepsilon s}[\mathrm{ad}^N(A)]e^{iN\varepsilon H}\varphi\stackrel{\varepsilon\to0}{\to}\mathrm{ad}^N(A)\varphi$$

So the above gives: $$\mathrm{ad}^N(A)\varphi=\lim_{\varepsilon\to0}\mathrm{ad}_\varepsilon^N(A)\varphi=:\mathrm{ad}_0^N(A)\varphi$$

The dominant bounds: $$\|\mathrm{ad}_\varepsilon(A)\|_{\varepsilon\neq0}\leq\|\mathrm{ad}_0^N(A)\|=\|\mathrm{ad}^N(A)\|<\infty$$

Concluding adjoint variation.

Mourre Adjoint

Regard the core: $$\mathcal{D}^M:=\bigcap_{m=0}^M\mathcal{D}(H^m):\quad\overline{(H^m)_{\mathcal{D}^M}}=H$$

And regular functions: $$\eta(\varphi,\psi):=\langle\tau[A]\varphi,\psi\rangle\in\mathcal{C}^M(\mathbb{R},\mathbb{C})$$

By induction one gets: $$\eta^{(M)}_0(\varphi,\psi)=i^M\sum_{m=0}^M\binom{M}{m}(-1)^{M-m}\langle AH^m\varphi,H^{M-m}\psi\rangle$$

Note that it holds: $$\eta^{(m)}_{n\varepsilon s}(\varphi,\psi)=\eta^{(m)}_0(e^{-in\varepsilon sH}\varphi,e^{-in\varepsilon sH}\psi)$$

They admit a dominant: $$|\langle\tau^{n\varepsilon s}[A]e^{iN\varepsilon H}H^m\varphi,H^{M-m}\psi\rangle|\leq\|A\|\cdot\|H^m\varphi\|\cdot\|H^{M-m}\psi\|$$

And converge pointwise: $$\langle\tau^{n\varepsilon s}[A]e^{iN\varepsilon H}H^m\varphi,H^{M-m}\psi\rangle\stackrel{\varepsilon\to0}{\to}\langle AH^m\varphi,H^{M-m}\psi\rangle$$

So the above gives: $$\eta_0^{(N)}(\varphi,\psi)=\lim_{\varepsilon\to0}\langle\mathrm{ad}_\varepsilon^N(A)\varphi,\psi\rangle=:\langle\mathrm{ad}_0^N\varphi,\psi\rangle$$

That gives the bound: $$|\eta^{(N)}_\theta(\varphi,\psi)|=\lim_{\varepsilon\to0}|\langle\mathrm{ad}_\varepsilon^N(A)e^{-i\theta H}\varphi,e^{-i\theta H}\psi\rangle|\leq\|\mathrm{ad}_\varepsilon^N(A)\|_{\varepsilon\neq0}\|\varphi\|\cdot\|\psi\|$$

Set another expansion: $$\eta_\theta(\varphi,\psi)=\sum_{l=0}^{L=N-1}\frac{1}{l!}\eta^{(l)}_0(\varphi,\psi)\theta^l+\frac{N}{N!}\theta^{N}\int_0^1(1-s)^{(N-1)}\eta^{(N)}_{\theta s}(\varphi,\psi)\mathrm{d}s$$

Note the trivial bound: $$|\eta_\theta(\varphi,\psi)|=|\langle\tau^\theta[A]\varphi,\psi\rangle|\leq\|A\|\cdot\|\varphi\|\cdot\|\psi\|$$

That implies bounds:** $$|\eta^{(l)}_0(\varphi,\psi)|\leq\|\eta^{(l)}_0\|\cdot\|\varphi\|\cdot\|\psi\|$$

Especially one has: $$|\langle iA\varphi,H\psi\rangle-\langle iAH\varphi,\psi\rangle|=|\eta^{(1)}_0(\varphi,\psi)|\leq\|\eta^{(1)}_0\|\cdot\|\varphi\|\cdot\|\psi\|$$

Concluding Mourre adjoint.

*See the thread: Binomial

**Here is a flaw: Summands not positive!

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This is only a check!

The spectrum is neglible: $$0\leq\lambda_\mathbb{C}(\sigma(H))\leq\lambda_\mathbb{C}(\mathbb{R})=0$$

By functional calculus: $$\langle\left(-\frac{1}{\pi}\int_{\mathbb{C}\setminus\mathbb{R}}\frac{\overline{\partial}f_E(z)}{z-H}\mathrm{d}\lambda_\mathbb{C}(z)\right)\varphi,\psi\rangle=-\frac{1}{\pi}\int_{\mathbb{C}\setminus\mathbb{R}}\int_{\sigma(H)}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\mu_{\varphi\psi}(\lambda)\mathrm{d}\lambda_\mathbb{C}(z)$$

By Fubini's theorem: $$-\frac{1}{\pi}\int_{\mathbb{C}\setminus\mathbb{R}}\int_{\sigma(H)}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\mu_{\varphi\psi}(\lambda)\mathrm{d}\lambda_\mathbb{C}(z)=-\frac{1}{\pi}\int_{\sigma(H)}\int_{\mathbb{C}\setminus\mathbb{R}}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\lambda_\mathbb{C}(z)\mathrm{d}\mu_{\varphi\psi}(\lambda)$$

By dominated convergence: $$\int_{\mathbb{C}\setminus\mathbb{R}}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\lambda_\mathbb{C}(z)=\lim_{\varepsilon\to0^+}\int_{|\Im z|\geq\varepsilon}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\lambda_\mathbb{C}(z)$$

Note the identity: $$\mathrm{d}\lambda_\mathbb{C}=\mathrm{d}x\mathrm{d}y:\quad\mathrm{d}\overline{z}\wedge\mathrm{d}z=2i\mathrm{d}x\wedge\mathrm{d}y$$

By holomorphy one gets: $$d\left(\frac{f_E(z)}{z-\lambda}\mathrm{d}z\right)=\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\overline{z}\wedge\mathrm{d}z$$

By Stokes' theorem: $$\frac{1}{2i}\int_{|\Im z|\geq\varepsilon}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\overline{z}\wedge\mathrm{d}z=\frac{1}{2i}\int_{|\Im z|=\varepsilon}\frac{f_E(z)}{z-\lambda}\mathrm{d}z$$

Regard the integrand: $$h(\varepsilon):=\frac{f_E(x+i\varepsilon)}{x-\lambda+i\varepsilon}-\frac{f_E(x-i\varepsilon)}{x-\lambda-i\varepsilon}$$

By almost analyticity: $$\overline{\partial}f_E\restriction_\mathbb{R}=0:\quad f_E(x\pm i\varepsilon)\approx f(x)\pm(-i)f'(x)\varepsilon$$

The integrand becomes: $$h(\varepsilon)\approx\frac{1}{\pi}\frac{\varepsilon}{(x-\lambda)^2+\varepsilon^2}(-2\pi i)\left\{f(x)+f'(x)(x-\lambda)\right\}$$

The nascent delta gives: $$\lim_{\varepsilon\to0^+}\frac{1}{2i}\int_{-\infty}^\infty h(\varepsilon)\mathrm{d}x=\frac{1}{2i}(-2\pi i)f(\lambda)=-\pi f(\lambda)$$

Inserting the expression: $$-\frac{1}{\pi}\int_{\mathbb{C}\setminus\mathbb{R}}\frac{\overline{\partial}f_E(z)}{z-\lambda}\mathrm{d}\lambda_\mathbb{C}(z)=-\frac{1}{\pi}\int_{\sigma(H)}(-\pi)f(\lambda)\mathrm{d}\mu_{\varphi\psi}(\lambda)=\langle f(H)\varphi,\psi\rangle$$

Concluding Helffer-Sjöstrand.

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The problem says, Find the rate of change of $$(x,y,z) = x/z + y/z$$ with respect to t along the curve $$r(t) = \sin^2{t}[ i] + \cos^2{t}[j] + 1/(2t)[k]$$

The answer is apparently

$$(z/z^2)(2\sin{t}\cos{t}) - (z/z^2)(2\sin{t}\cos{t}) + (-x-y/z^2)(-2/4t^2)$$

i get everyting except where the $$(z/z^2)$$ comes from. should the partial derivative of x and y just be z?

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Question: How is $x,y,z$ done?

Motivation: I have been working on a problem in field $\alpha$ in regards to $\beta$ and I have come across a problem $\zeta$


What I have tried: Blahblahblah....[working,methods]$$$$$$$$$$$$


How do I fix this?

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This answer is free to be used.

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This post is available for use.

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Given: Points $A(-2\mid-2)$ and $B(1\mid2)$.
Goal: Find point $C(x\mid y)$ such that
(1) $\overline{AC}=\overline{BC}$,
(2) $C$ is north of the x-axis, and
(3) Triangle $ABC$ has an area of 10 units.
Solution: The perpendicular-bisector of $AB$ is $6x+8y+3=0$. Any point on this line, together with the base $AB$ can be the vertex of an isosceles triangle. The degenerate conic (two parallel lines) $(4x-3y+2)^2=400$ is the locus of all points that, together with the base $AB$, form triangles of 10 units area. This locus intersects the perpendicular-bisector at two points. One of these is south of the x-axis and can therefore be disregarded. The one we want is $C(-3.7\mid2.4)$.

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Blah

blah

The remaining case is the one where $x_B(0) \neq 0$ and $\tilde y_B(0) > 0$. Since $\tilde y'_B(t) < -1$ when $\tilde y_B(t) > 0$, the trajectory reaches the line $\tilde y = 0$ in finite time. Let $T > 0$ be the earliest such time.

Assume for the sake of contradiction that $(x_B(T), \tilde y_B(T)) = (0,0)$. We define sequences $(t_n)_{n \geq 0}$ of times and $(u_n)_{n \geq 0}$ of $\tilde y$-coordinates (plus, for convenience, $x_n = x_B(t_n)$ and $\tilde y_n = \tilde y_B(t_n)$) as follows. The initial conditions will be $t_0 = 0$ and $u_0 = \tilde y_B(0)$. Then, suppose $t_n < T$ and $u_n > 0$ are such that $(x_n, \tilde y_n)$ and $(x_0, u_n)$ are at the same polar angle. Choose $t_{n+1} \in (t_n, T)$ such that \begin{equation} \tag{*} \label{ratio} \frac{\tilde y_n}{x_n} = \frac{F_2(x_{n+1}, \tilde y_{n+1})}{F_1(x_{n+1}, \tilde y_{n+1})} \equiv \frac{\tilde y_{n+1} + \sqrt{x_{n+1}^2 + \tilde y_{n+1}^2}}{x_{n+1}}; \end{equation} such a time exists due to Cauchy's mean value theorem. Since $t_n < T \implies \tilde y_n > 0$, the above ratio has the same sign as $x_n$ and thus $x_0$. It also has the same sign as $x_{n+1}$ (see item 2 of the earlier list). Thus, there exists a $u_{n+1} > 0$ such that $(x_0, u_{n+1})$ has the same polar angle as $(x_{n+1}, \tilde y_{n+1})$.

However, observe that by \eqref{ratio} and item 2, $$ \frac{u_n}{x_0} = \frac{u_{n+1} + \sqrt{x_0^2 + u_{n+1}^2}}{x_0}, $$ which implies $u_{n+1} < u_n - x_0$. This means that $u_n < u_0 - n x_0$ for all $n \geq 0$, contradicting the fact that the $u_n$ are all positive.

Thus even in this last case, $B$ is eventually side-by-side with $A$, after which $B$ is doomed to fall further and further behind $A$ forever.


     

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for t:=1 to 10 $$\theta_{\mathrm{new}}:=\theta-\alpha \frac{1}{1000}\sum \limits_{i=1}^{1000} \left(h(x^{(i)},\theta)-y^{(i)}\right)x^{(i)}$$

for t:=1 to 10 $$\begin{array}{lcl} \\ \theta_{\mathrm{new}}&:=&\theta\\ \theta_{\mathrm{new}}&:=&\theta_{\mathrm{new}}-\alpha \frac{1}{1000}\left(h(x^{(1)},\theta)-y^{(1)}\right)x^{(1)}\\ \theta_{\mathrm{new}}&:=&\theta_{\mathrm{new}}-\alpha \frac{1}{1000}\left(h(x^{(2)},\theta)-y^{(2)}\right)x^{(2)}\\ &\vdots& \\ \theta_{\mathrm{new}}&:=&\theta_{\mathrm{new}}-\alpha \frac{1}{1000}\left(h(x^{(1000)},\theta)-y^{(1000)}\right)x^{(1000)} \\ \theta&:=&\theta_{\mathrm{new}} \end{array}$$

for t:=1 to 10 $$\begin{array}{lcl} \\ \theta&:=&\theta-\alpha \left(h(x^{(1)},\theta)-y^{(1)}\right)x^{(1)}\\ \theta&:=&\theta-\alpha \left(h(x^{(2)},\theta)-y^{(2)}\right)x^{(2)}\\ &\vdots& \\ \theta&:=&\theta-\alpha \left(h(x^{(1000)},\theta)-y^{(1000)}\right)x^{(1000)} \\ \end{array}$$

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\newpage \section{Central extensions} \subsection*{General terminologies:} An injective group homomorphism is called a monomorphism, and a surjective group homomorphism is called an epimorphism. These are denoted by the mapping symbol $\hookrightarrow$ and $\twoheadrightarrow$ respectively. This definition holds in the categories $\text{FinGrp},\text{AbGrp},\text{Grp}$ \subsection*{Definition of an exact sequence:} A sequence of homomorphisms, is called exact if we have:

$$1\overset{\phi_1}{\to} N \overset{\phi_2}{\to} G \overset{\phi_3}{\to} H \overset{\phi_4}{\to} 1$$ where we have the following:

$$\text{Im}(\phi_1) =\ker(\phi_2)$$ $$\text{Im}(\phi_2) =\ker(\phi_3)$$ $$\text{Im}(\phi_3) =\ker(\phi_4)$$

\subsection*{Quick Example of a short exact sequence}

$$0\hookrightarrow \Bbb Z \overset{\times n}{\hookrightarrow} \mathbb Z \twoheadrightarrow \mathbb Z/n \twoheadrightarrow 0$$

$$\text{Im}(\phi_1) = 0 = \ker(\phi_2)$$ $$\text{Im}(\phi_2) = n\mathbb Z = \ker(\phi_3)$$ $$\text{Im}(\phi_3) = \mathbb{Z}/n = \ker(\phi_4)$$

\subsection*{Definition of an extension:} An extension of a group $G$ by a group $A$ is given by an exact sequence of group homomorphisms:

$$1\hookrightarrow A \hookrightarrow E \twoheadrightarrow G \twoheadrightarrow 1$$

This extension is called central if $A$ is abelian and the image of the monomorphism from $A\hookrightarrow E$ is in the center of $E$. \newpage \subsection*{Example of a central extension: Discrete Heisenberg group}

The Heisenburg group is also a lie group. It is not only a group but with topology inherited from $\Bbb R^3$ it becomes a smooth manifold with applications in Fourier analysis, quantum mechanics and other subjects. We will consider the discrete Heisenburg group, for simplicity. $$$$ Why do we care about central extensions? Finding group extensions is hard. Split extensions are the easiest to classify, these are semi-direct products, and general extensions are not much better than impossible to classify. This Heisenburg group is an example of one that doesn't split.

$$H_3(\mathbb{Z})$$

$$H_3(\mathbb{Z})= \begin{bmatrix}1&x&z\\0&1&y\\0&0&1 \end{bmatrix}|a,b,c\in \mathbb Z$$

[don't need to say]: We have the relations $z=xyx^{-1}y^{-1},xz=zx,yz=zy$

[don't need to say]: It has generators $$x=\begin{bmatrix}1&1&0\\0&1&0\\0&0&1\end{bmatrix},y=\begin{bmatrix}1&0&0\\0&1&1\\0&0&1\end{bmatrix},z=\begin{bmatrix}1&0&1\\0&1&0\\0&0&1\end{bmatrix}$$

The center of this is: $\begin{bmatrix}1&0&z\\0&1&0\\0&0&1\end{bmatrix}$

and we have a central extension from the short exact sequence: $$I\hookrightarrow N = Z(H_3(\Bbb Z)) \hookrightarrow H_3{\Bbb Z} \twoheadrightarrow \Bbb H_3(\Bbb Z)/N \twoheadrightarrow I$$

Since $N$ is the center, this is a central extension as long as we can show that the sequence is exact:

What we are working with in disguise: $$1\hookrightarrow \Bbb Z \hookrightarrow H_3{\Bbb Z} \twoheadrightarrow \Bbb Z^2 \twoheadrightarrow 1$$

$$\text{Im}(\phi_1)=I=\ker(\phi_2)$$ $$\text{Im}(\phi_2)=N=\ker(\phi_3)$$ $$\text{Im}(\phi_3)=H_3(\mathbb Z)/N=\ker(\phi_4)$$

The explicit maps are:

$$\phi_2: (0,0,z)\mapsto \begin{bmatrix}1&0&z\\0&1&0\\0&0&1\end{bmatrix},\phi_3: \begin{bmatrix}1&x&z\\0&1&y\\0&0&1\end{bmatrix}\mapsto (x,y,0)$$

[don't need to say:] $1=(0,0,0)$ [don't need to say:] $H/N$ is not a subgroup, it is a quotient group

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A presheaf on a category $J$ is a functor $J^{\text{op}}\to\mathbf{Set}$. The category of presheaves on $J$, denoted $\hat J$, with natural transformations as arrows is an example of functor category, and every category $J$ embeds into $\hat J=\mathbf{Set}^{J^{\text{op}}}$ via the Yoneda embedding $Y:x\mapsto J(-,x)$.

Note that your category $\cal A$ can be identified with $\hat{\Bbb N}$ since $\Bbb N=\Bbb N^{\text{op}}$ and every endomorphism determines a functor from the monoid $\Bbb N$ to $\mathbf{Set}$.

A nice property of a $\hat J$ for small $J$ is that it is Cartesian closed. Given any presheaves $B$ and $C$, if there exists an exponential $C^B$, then by Yoneda's lemma $$ C^B(x)=\text{Nat}(J(-,x),C^B-) = \hat J(Y(x),C^B)\cong \hat J(Y(x)×B,C) $$ and the arrow $C^B(x)\to C^B(y)$ is the function precomposing with $Yf×1_B$. So we only need to check that this presheaf is really the exponential. So we define $ε:C^B×B\Rightarrow C$ as $$ \begin{align} ε_x:\hat J(J(-,x)×B,C)×B(x) &\to C(x) \\ (\sigma,b)\qquad &\mapsto \sigma_x(1_x,b) \end{align} $$ It is easy to check that $ε$ is natural.

Note how similar this is to the construction in your case. Setting $J=\Bbb N, B=α,$ and $C=β$, and noting that $Y(\bullet)$ is the functor sending every $k\in \Bbb N$ to the addition "$...+k$", we get $β^α(\bullet)=\mathcal A(s×α,β)$. Precomposing with $s^k×1_α$ is the same as causing $h$ to be applied to $(n+k,a)$ instead of $(n,a)$. And the transformation $ε_x$ sends a map $h$ and an element $a\in α(\bullet)$ to $h(0,a)$.

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Let $M$ be a monoid. A homomorphism $\varphi:M\to N$ recognizes $L\subset M$, if $L=\varphi^{-1}(\varphi(L))$. A monoid $N$ recognizes $L \subset M$, if there exists a homomorphism $\varphi:M\to N$ that recognizes $L$. A subset of $M$ is recognizable, if it is recognized by a finite monoid. The family $\operatorname{REC}(M)$ of recognizable sets over $M$ is defined as the set of recognizable subsets of $M$.

A similar definition can be found in "J.-E. Pin, Mathematical Foundations of Automata Theory", and already "S. Eilenberg, Automata, Languages, and Machines" defines recognizable sets.

A deterministic $M$-automaton $\mathcal A=(Q,\cdot,q_0,F)$ consists of a set of states $Q$, a transition function $\cdot:Q\times M\to Q$, an initial state $q_0\in Q$, and a set of final states $F\subset Q$. For $q\in Q$ and $u,v\in M$, the transition function has to satisfy $$\begin{array}{rcl}(q\cdot u)\cdot v &=& q \cdot (uv)\\ q\cdot 1 &=& q\end{array}$$ The subset of $M$ accepted by $\mathcal A$ is $$L(\mathcal A) = \{u\in M|q_0\cdot u\in F\}$$

If $Q$ is a finite set, then $\mathcal A$ is said to have finitely many states.

I found this definition in chapter 7 Automatentheorie of the German text book "Volker Diekert, Manfred Kufleitner, Gerhard Rosenberger: Diskrete algebraische Methoden: Arithmetik, Kryptographie, Automaten und Gruppen”. There we also find the following theorem:

Theorem 7.10 Let $L\subset M$. The following statements are equivalent:

  1. $L$ is recognizable, i.e. $L\in \operatorname{REC}(M)$.
  2. $L$ gets accepted by a deterministic $M$-automaton with finitely many states.
  3. The "minimal automaton $\mathcal A_L$" has finitely many states.
  4. The "syntactic monoid $\operatorname{Synt}(L)$" is finite.

I have the impression that this definition of deterministic $M$-automata is unsuitable for characterizing deterministic finite state transducers as deterministic $\Sigma^*\times \Sigma^*$-automata.

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