sarcopsy

That seems right I guess

oops

Doesn't it toggle the four neighbors?

i think

Well in an infinite grid you just make a parity argument

@DHMO Oh, ok. That being said I've always thought of the trig functions $sin^2(x)$ as the exception to the rule rather than the other way around

@AlessandroCodenotti Thanks, I'll remind you!

@DHMO If your codomain of $f$ doesn't have multiplication defined then it's going to fail, I guess

@AlessandroCodenotti These kind of things annoy me to no end haha

@AlessandroCodenotti It would be very nice if you could! Thanks

@AlessandroCodenotti Yeah, if that was the case it immediately follows, but with this definition of primitive I'm not sure if it works

@AlessandroCodenotti But there seems to be many variants of 'primitive' floating around so its a bit confusing and I wanted to clear it up as well

@Socrates np

@AlessandroCodenotti Gallian defines primitive as $F(a)\cong E$ iff $a$ primitive where $E$ is an extension of $F$ and $a$ in $E$

@Socrates $f(0) = 0, f(1) = 0$. Then set $A = \{0\}$ and $B = \{1\}$

The multiplicative group $GF(p^n)^* := GF(p^n) - {0}$ is shown to be cyclic. If we consider $GF(p^n)$ as a extension of $GF(p)$, does a primitive element $a$ in $GF(p^n)$ necessarily generate $GF(p^n)^*$?

If $E$ is an extension of $F$, Gallian defines a primitive element of $E$ to be $a\in E$ such that $F(a)\cong E$

I have a question about finite fields

Hello people

@Simple Not immediately, since $|Y-X|$ isn't linear, so you would split into cases where $Y \ge X$ and $X \gt Y$

@Simple So you're done right

@Simple i.e. The probability that 'something happens' is 1

@Simple Do you know that for a function to be a probability mass function then the sum of the function over all the all the possible values the random variable can attain is 1?

@Simple No I mean the probability $P(Y\gt 0)$

@Simple What is the probability that $Y$ takes on a non-negative number then?

@Simple Well does $Y=0$ and $Y > 0$ cover all the possible values that $Y$ can take on?

@Simple If $Y$ takes on only non-negative values, then what is $P(Y=0) + P(Y>0)$?

@Simple No, I mean that Poisson random variables are meant to be used for $Y\ge 0$ only.

@Simple Do you know that Poisson variables are only non-negative?

@Simple What's $P(Y=0) + P(Y\gt 0)$?

@Simple An indicator function is 0 when the condition (in this case $Y>0$) is false and 1 when the condition is true. You are right in that you are summing the Poisson, but there's an easier way to calculate it without having to do any sums

@Simple When is $X=1$?

@Simple No, that's the probability that $Y=1$, not $X=1$

@Simple No, your formula for $X=1$ is wrong

@Simple Yup, so whats $P(X=0)$ and $P(X=1)$? That's the mass function of $X$

@Simple Er I don't think the probability is 0 at $Y=0$

Well then it's 0 when Y is 0, and 1 otherwise, so what are the corresponding probabilities?

@Simple $I_{[Y\gt 0]}$ is an indicator variable?

@Vrouvrou What are $C_E$ and $C_F$ and the other variables

What are the variables supposed to be

but its a distinction i guess

just being pedantic >_>

yeah, but the typed out proof says that 'every neighbourhood is of the form (open interval)'

well technically an open set in the standard topology is not an open interval either, but a union of open intervals? I think

that seems like a strange way to ask questions

Its not like I do this on a regular basis haha

I was sleeping too late so I decided to fix it

@ForeverMozart No, I was too lazy to get up haha

I slept 16 hours yesterday to fix my sleep schedule, feels good

@Astyx and @SimpleArt I guess.. haha