#discrete-math
1 messages · Page 62 of 1
yea
but this is contradiction since ∅ is the set which for all x, x not in ∅
okok I guess it makes sense
it's just notation thats hard to me
I'll work on that but thx for the explaination
thx
Bumping something from earlier
@vestal bronze @fossil mural
Is there proof to this?
Image
"Recall that since the sampling is without replacement, the unordered sample is uniformly distributed over the set of all combinations of size n chosen from D."
anyone?
i didnt understand the answer there
why E[Xi] = E[Xj] for all i,j
hello!
can anyone tell me why the first one is contingency and not tautology?
if we try to expand the implication statement then
(p^q) -> ~p becomes
~(p*q) + ~p
and by de morgan's law
~(pq) becomes p + q right?
so the end statement should be
p + q + ~p which will be true no matter what
and by de morgan's law
~(pq) becomes p + q right?
no
ohhh
so i assumed it will be
~(pxq) will be ~p x ~q
ohh
got it
i went wrong here
ahhhhh how can i forget that the negation will still stay 🤦♂️
im sorry and thank you so much for pointing it out!!
also if you think about it, it really just wouldn't make much sense for "if p and q are both true, then p is false" to be a tautology
wait tautology means always true right?
yes
im sorry i cant understand what you meant here
ohhh
wait
i got it
well i mean think of any two true statements
yes
agreed
yess i forgot that theres an implication in the statement
thank you so much
i should start thinking logically first
Thank you! 🙏
what is the best way to cut n-dimensional cheese? (you want to get the most possible pieces of cheese)
Is there a bipartite graph where the nodes have the degrees: 3,3,3,3,4,4,6,6,6,6,6,63,3,3,3,4,4,6,6,6,6,6,6?
I drew pictures and came to a conclusion that yes this works but there has gotta be an easier way or pattern I am just not seeing.
I know that the sum of degrees on one side needs to equal the sum of degrees on the other side but I don't exactly know how the nodes are connected here.
Hello does anyone know if adding the negative before "implies" change the structure ??
¬(p -> q)
same way that ¬(p^q) is (¬p V¬q)
or is it just (¬p -> ¬q)
¬(p -> q) and (¬p -> ¬q) not the same thing as far as I understand because (¬p -> ¬q) means not p leads to not q. Whilst the ¬(p -> q) is saying that it is not true that p leads to q but it is not saying that negation of p leads to negation of q.
I think you should like maybe draw truth table
I just did equivalences and what I got is
it's equal to p ^ ¬q
yep
We're learning how to prove Big Oh and I want to know if I am doing it correctly. Here is the question:
Here is my solution
is this harder to show directly? I feel the main part I had struggled with in the direct strategy is showing that there really is an alternating path / justifying it intuitively
yeah probably, i think a doable direct proof would give an algorithm that would prove it exhaustively or something, not sure how you'd do it otherwise
when you assume contradiction and you have the x-perfect matching you just gain so much structure that it's much easier
Yeah I think I was overlooking some details:
I think I'm still trying to wrap my head around the alternating path argument though.
To me I imagine the vertices of X on the top and the vertices of Y on the bottom. we put a downward arrow on any edge that's not in the matching, and an upwards arrow on any edge in the matching.
I saw somewhere that if you can go from an unmatched vertex in X to an unmatched vertex in Y, you can flip the edges along the path to create a larger matching. Though how do we foresee that when we find an augmenting path for our contradiction proof, that we still maintain the same size?
saw somewhere that if you can go from an unmatched vertex in X to an unmatched vertex in Y, you can flip the edges along the path to create a larger matching.
true but not too relevant here because we only need them to stay the same (if it increased we would not actually have such a maximum matching to start with)
Though how do we foresee that when we find an augmenting path for our contradiction proof, that we still maintain the same size
well, the edges switch between being in the matching and out of the matching. we know that the path terminates at a y because if it terminated at an x, that would mean the x has no non-matched edges which is impossible (by assumption), or all of it's unmatched edges are to ys that were already hit. it's a neat exercise to show why this last case isn't possible (short for i can't see how to do it off the top of my head but am certain it's easy). if it terminates at a y then that y must be unmatched so when we flip everything we maintain the cardinality of the matching (because our initial x is matched)
Oh I see, I was thinking it's more like this:
In the augmenting path alternating from X to Y, # of times to go downwards = # of times to go up + 1.
The starting position of your augmenting path (x) was initially matched to something, so there is an up arrow already.
So the number of up arrows and down arrows you can "see" are equal. When we switch them around, they are still equal?
hmmm
sure, that seems good too!
So the number of up arrows and down arrows you can "see" are equal. When we switch them around, they are still equal?
in particular this is true and the important part
Thanks so much ! 🙂 Do you think in order to prove the existence of an alternating path, we need to show that alternating cycles can't exist? Or is that not necessary in this case?
it's fine if we have alternating cycles bc we can switch them! remember that bipartite graphs can't contain odd cycles
I'm trying this out next. this seems like a stronger statement lol, the inequality sort of looks like halls theorem
When approaching this by contradiction,
If every edge of G extends to an X-perfect matching and there is a subset A where |Neighbourhood(A)| <= |A| , I think if we focus on Hall's condition then it's ok when |N(A)|=|A|, but when its |N(A)| < |A|, it contradicts the condition . Though I'm not sure if this is the right way to think about it
how can I uniquely determine a surjective function from a function f: N -> N
first thought was take left inverse but that would require that a) f was injective and b) the left inverses are unique
second thought was to construct a function determined by f whose range contains N \ Im f but idk how
there's nothing canonical popping out to me
why are we multiplying tm by 4 here?
Actually, I saw a hint somewhere that said "It might be easier to work two jobs if we had an identical twin". I'm wondering how I can relate this to the conditions in the statement. I think the intention of the question is that the size of the neighbourhood for the entire subset A is at least 2|A|.
am I misunderstanding something here?
The subset A could be empty right ? but then the statement is not true ?
well there are at least 0 jobs that someone in the empty set is qualified for
if you mean that the converse doesn't hold, then that's not how the logic works, the <= direction says that if that holds for all A then there's a valid matching of people to jobs
wait isnt it "forall subsets A there exists a person p in A such that there exist 2|A| jobs that p is qualified for"?
wait wait
i interpreted it as "there exist 2|A| jobs j such that someone in A is qualified for j"
because if you imagine like, two people, one can do jobs 0 and 1, one can do jobs 2 and 3, then clearly there's a valid matching, but the set of both people does not have anyone who can do 4 jobs
yeah
because the statement seemed odd to me
but yeah I guess I misunderstood it
but it is kind formulated in a kind of weird way
idk if its just that Im not a native speaker
Im still confused though lol
what does the "extends to an" mean here ?
https://math.stackexchange.com/questions/3418000/what-does-it-mean-for-an-edge-to-extend-to-a-matching
ah ok found it
what the hell
isnt the solution a_n = (n+1)2^n?????
cuz the 4a_(n-1) and -4a-(n-1) completely cancel out
how tf did they get that solution
Dilly
rewrite to $a_n - 4a_{n-1} + 4a_{n-2} = (n+1)2^n$ then solve normally. Its $a2^n + b2^n$ for homogenous solution then just add the particular solution, this case $n^2 2^n + 1/6 n^3 2^n$
bDim
what is the "particular solution"?
how do you solve for it?
Recommend chapter3.5 of Elementary Differential Equations and Boundary Value Problems
V - E + F = 2 holds when you consider the exterior of the graph as a face as well.
see here for validation:
wait what
did they delete their post?
yea, i interpreted it the same way as this part: A matching which an edge "extends to" just means a matching which contains that edge as an element.
I tried some sort of contradiction proof for the forward direction but I wasn't sure how to proceed
So assuming every edge of G extends to an X-perfect matching, and there is a subset A, A != 0, A!=X where |N(A)| <= |A|
Does the detail that A != X change anything drastically?
im having trouble showing the <= direction. I think the assumption lets me apply the halls theorem which says there is an existence of a perfect matching. but how do i show every edge extends to one?
I am confused by this. What is given and what do you need to proof, it looks mixed up
to me
Basically
For all x,y elements of A, it fulfills x~y if and only if [x] = [y] (the equivalence cases are equal)
and then my proof is to showcase that
I will look more closely into the exercises you posted and let you know in case I find something
theyre interesting
I think (ii) seems kinda wrong.
If we define equivalence cases as [x] = {y eA: x~y}, then by definition, if we assume x~y, then [x] can be defined as {y eA}
and then i do the same thing but for [y]
When you say ${x\in A : P(x) }$ the x is a variable not a constant.
DootDooter
I'm assuming it for all x
And ${y\in A}$ is kind of ambiguous.
DootDooter
Okay, but in your equivalence class notation [x] and [y] the x and y are particular.
You have specific representatives.
They aren't really variables in the same sense.
Oh so it's an x belonging to their particular context
the above proposition
Like, you want to show for any x,y in A, that x~y iff [x]=[y].
So you start by saying, take x and y in A. Assume x~y.
ok hang on
Okay, now take a in [x], how do you know a is in [y] as well?
what does ~ stand for in your course?
An equivalence relation.
is it equivilance relation
alright
in the courses I attented that was not the canonical symbol
afaik
that was confusing
Because we assumed x~y
now I got it
they also use capital "r" so R
Yeah, but this is a, a may not be x or y.
xRy
So what steps tell you a is in [y]?
symmetry?
Not immediately. (If at all depending on how you define [x])
What does $a\in [x]$ mean?
DootDooter
If a is in the equivalence case then x~a?
Yeah, by definition. So how does that give you a in [y]?
You may or may not need symmetry but there's a particular equiv relation prop you will need to use with your assumptions.
transitivity
since we assume: x~y, then we follow these steps
x~a
a~y
x~y
Yep that'll do it
if a~y wasn't the case, then x~y couldn't be while x~a
Then by definition a is in [y].
How would you explain that succinctly because in my head it makes sense
but I can't put it into words
You don't really need to argue by contra fwiw.
You know x~a, and x~y, by symmetry y~x, x~a so by transitivity, y~a.
So I can just put:
By transitivity:
(x~a) - assumed
(a~y) - inferred
(x~y) - assumed
just transitivity isn't actually enough for this, you also need symmetry
It's more like, let a be in [x]. By definition x~a, by our assumption we have y~x using symmetry so by transitivity y~a...
oh because a~x so x~a
?
You can apply symmetry to either x~a or x~y.
Ok thank you that's much better
It kinda depends on how you define [x]. Because you can do it as [x]={y in A : x ~y} or [x]={y in A : y~x}
They are the same sets by symmetry.
and then i have to do the converse to prove the other side right
But if you're being super strict you need to be mindful of it ig.
That's true
So what you showed proves $[x] \subseteq [y]$. You'd probably want to say something about how similar stuff gives you the other inclusion to conclude the equality you need.
DootDooter
For the converse you basically just need to unpack definitions as well. If [x]=[y], you know nice facts about a set x is a member of by the earlier parts of the problem.
Or just reflexivity.
What's the role of reflexivity here
x~x right? What set does that tell you x is in?
in [x]
So, x~x right? That told you x is in [x]. But [x]=[y]. So x is in [y] now too yeah?
What does the last step tell you about x and y?
oh because we already proved this way =>
Well we're proving the converse. So we'd assume [x]=[y] and need to show x~y.
We already did the other direction yeah
So then if x is in [y] then y~x and then by symmetry x~y
Yep.
To recap for the converse we assume [x]=[y], we know x~x, so x is in [x] and we follow this reasoning until x~y basically.
Ok I think I got it, thank you very much
if a set X is uncountable we can still write $X = \bigcup_{x \in X} {x}$ right
okeyokay
yes
so in showing that there is no set containing all singletons could we assume there was, then show that the power set contains all sets using this
...the power set would not contain every set
it would contain every set which all of its elements are singletons
oh wait u right
its union would contain every set
or use replacement to send every singleton to the set it's the singleton of
or regularity because this set would be ill-founded
or directly a russell's-paradox-style argument, constructing the set of all singletons that aren't elements of the sets they contain
so something like if S is a set containing every singleton and x is a set then {x} is in S, and x is in {x} which is in S, so x is in the union over S
yep
nice
What is the opposite of (non-) discrete math?
continous math?
What is the difference?
well "discrete maths" is a... honestly fairly vague term for anything discrete
it is not concrete? haha
the obvious thing that isn't discrete is the real numbers
René Descartes called it "imaginary"
idk what you mean by "concrete"
I want to find the general coefficient of x^k in (x+1)(x^2+1)...(x^n+1)
I just a want a push in the right direction cause I think we can define some sort of a recursive sequence to do that
my approach is basically splitting the power into 1s and then finding how many groupings of 1s will give an acceptable coefficient
so for example for x^6
(1+1+1+1+1+1)=6 -> 1
(1)+(1+1+1+1+1)=6 -> 1
(1+1)+(1+1+1+1)=6 (2 ways to do this, either by constructing x^4 from x^3 and x, or simply multiplying x^4 into x^2) -> 2
(1+1+1)+(1+1+1)=6 (not possible cause this would require two x^3) -> 0
then adding these up to get 1+1+2=4, hence the coefficient of x^6 would be 4
n(n-1)2^(n-2)
We roll two fair 6-sided dice. Each one of the 36 possible outcomes is assumed to be
equally likely.
Given that the roll results in a sum of 4 or less, find the conditional probability
that doubles are rolled.
why is 1/18 a wrong answer?
nvm i got it
I am trying to do this question by transforming it into a graph problem. The question implies the checkerboard is a two-colourable graph, so is the subset S. So it is bipartite. But I'm not sure what to do knowing this
this isnt bipartite right?
its 2 colorable so i would say it is
how? I tried the two coloring and it looked like an odd length cycle?
if I'm not mistaken you can just partition the graph into the middle three vertices and the other three remaining ones
ohh i made a mistake, mb, thansk for help!
yeah like this
how can i proof that the sum of the distances in a graph of order n is maximum on a path? I know that this is minimum on a complete graph
is graph thery on-topic here?
yes
thanks!
i have a dynamic programming problem that i'm trying to solve: given a tree on $n$ nodes, determine whether it contains a maximal independent set (i.e. a vertex set with no two vertices sharing an edge) of size exactly $k$
i think i want to have a DP array of size $n \times k$ but i'm struggling a bit to see the right recurrence relation
PatrickC
Is there a closed formula (or anything at all) for the number of ways to seat k pairs of people on n chairs, where no pair is allowed sit next to each other?
I'm trying to reach the hint so I can prove this, can someone let me know if this is the right way to do it?
Assume there is an $X$-perfect matching and assume for contradiction that for every $x \in X$ there is an edge incident with $x$ that does not extend to an $X$-perfect matching. \\
So if we make a subgraph without these edges, it should still have an $X$-perfect matching. Also, in the original graph, for every subset $A$ of $X$ we had that $|A| \leq N(A)$. So in subgraph we need $|A| = |N(A)|$, because if $|A| > |N(A)|$ there can't be an $X$-perfect matching by Hall's Theorem which is a contradiction.
clementine
why here does it say "S is not equal to the null set". If S is an element of the positive integers, isn't it by default not the null set, or any set for that matter? is it supposed to say "S is a subset of positive integers"?
yeah i think that's supposed to say $S \subseteq \mathbb{Z}^+$
bee [it/its]
claiming that an integer is bounded below also doesn't make much sense yeah
and also S is more the kind of variable name you use for a set than for a number
there are multiple ways, no? for example, if the cardinality of the range is equal to the cardinality of the codomain, then the function is onto
no that's not true
it's not?
it's true if the codomain is finite
mb yes this is what i meant
just reading straight from the definitions:
to prove f is injective, assume f(x) = f(y), and prove x = y
to prove f is surjective, take any y and find an x such that f(x) = y
your textbook probably
for my textbook, there's a glossary at the end of each chapter
so go to ur sets chapter and read the glossary, go the functions chapter and read the glossary
Could someone help me
This is prob very basic
But I’m having trouble with the concept of trees
,rccw
how does this establish that R is not transitive?
i mean I already came up with a counterexample, but i'm trying to see how this would suffice
yeah that doesn't particularly look like a counterexample by itself, is there more on the next page or something?
no there isn't lol
it's alright
i just took mmod 2
mod 2
and constanat function 0 and constant function 1
to show that a relation isn't transitive you'd want to give three objects a,b,c satisfying aRb, bRc, and ¬aRc
so yeah basically you'd want something that's 0 infinitely many times and 1 infinitely many times as the "in-between" function, the b in this
can somebody explain what they mean by this highlighted sentence please
is it just saying that A has cardinality equal to the product of w with itself countably many times
which has same cardinality as w
Am I going crazy? I feel like multiplying by a^{p-1} is useless since it's congruent on both sides either way. I only did it to satisfy the question
What are you confused about
x= x*a^(p-1) = b*a^(-1) * 1 = b * a^(-1)*a^(p-1) = b*a^(p-2)
The whole point of it was to just to express x in another equivalent form (it seems)
Ah ok sounds good
I was just getting tripped up because a^{-1}b mod p is congruent to a^{p-2}b mod p by fermat's, but you're right they probably just wanted us to express it another way and use fermat's
honestly that looks like some lines that were supposed to be there have been removed
like that's just two sentence fragments and they don't actually fit together into a sentence, and given the conspicuous line break i think someone messed up while editing this text and some lines vanished
Would anyone be able to explain to be how this argument established equality of the single sum and double sum. I am at the point where I understand how they are computing how many f(k) terms show appear in the double sum but I just don't understand how we are getting equality such that we can recast it as a weighted single sum
The bracket is the floor function
I guess the real confusion is the last paragraph. Like okay I get for a fixed k, f(k) appears in the sums [N/k] times but I don't understand how we are not missing any terms (under counting) or over counting in some fashion
Could anyone help me discover an invariant for this problem? I have found a monoinvarient (posted it in the help page) but it didnt help me much. The problem: There is an integer in each square of an 8 × 8 board. In one move, we may choose any 4 × 4 or 3 × 3 square and add 1 to each integer in the chosen square. Can we always get a board with each entry being even?
the idea is that you want to somehow control what adding 1 to every square of a 3x3 and 4x4 subboard looks like
if you consider a 3x3 subboard, adding 1 to every integer changes the parity so that's not quite helpful for us; instead, let's consider restricting one of its rows
(i.e. if we consider any 3x3 subboard and add 1 to every integer except for 1 row, then this does not change the parity of the sum of the elements of the board barring a select number of rows)
you can do a similar analysis for any 4x4 subboard
Suppose you repeatedly flip a fair coin until three consecutive flips match the pat-
tern HHT or the pattern TTH occurs. What is the probability you will see HHT
first? Define a suitable probability space that models the coin flipping and use it to
explain your answer.
can someone help me with this
i dont understand how the answer is 2/3
it should be 1/8 im so lost
How can I show that $2^k+2k+1 < 2^{k+1}$ for $k > 4$
rabbits_advocate
by graphing
it is for an induction proof
i have reached this final inequality that i need to prove by manipulating the expression
See what you can do with knowing 2^(k+1)=2*2^(k)=2^(k)+2^(k)
So a necessary condition might be now showing 2k+1<2^k for k>4
So maybe try showing 2k+1<2k+k=3k<k^2<2^k for k>=5
how a set where every non-empty subset has a minimal (not the least) element called in English?
It would make more sense to ask what a relation that obeys the condition would be called and the the answer would be that such a relation is called well-founded
thanks!
It would make more sense to ask what a relation that obeys the condition would be called
well, I mean, I'm just used to saying (R, A) is, for example, a well ordered set
If S is a function such that-
S = {(x, y) | x belongs to [a, b] and y belongs to [p, q]}
where a, b, p, q are real numbers
||it is given that S is a subjective-function||
is it possible to have another subjective function R such that-
R = {(x,y) | x belongs to [a, 2b], y belongs to [p, q]}
(i am not an undergrad in math btw apologies if this question is irrelevant to the channel)
Yeah, I don't think there's a term exactly like that, you need to talk of a "set with a well-founded order" or something along those lines.
god, I now have SE-anxiety
for that there I'd get 12 down votes in 3m xD
thanks!
I've been thinking about this for a while, but I still have no idea where to start :c
does anybody have a hint they'd be willing to give me?
terminology wise, d_x is the degree of x, and a cut vertex is one such that removing it from G disconnects G
Wtf is a cut vertex
I said it already
G-x its disconnected
Assume contradiction

my line of thinking was more like somehow applying Menger's thm
I was thinking about considering any x with d_x >= 3, and letting a, b, c be 3 of its neighbours
then... hold on
nvm idk what I'm doing 
which one was Menger’s
Disregard.... I figured it out 
size of smallest vertex cut for x and y = max # of pairwise vertex disjoint paths from x to y
I was thinking something like
G being a graph with no even cycles would mean that every cycle is odd, perhaps that might be useful for you
see it’s true for n, then at n+1 go through and remove any single non-cutting vertex
Then doing some gluing arguments
But idk if that actually works like I’d want it to
uwah
(Since obviously G sans v also has no even cycles)
graph theory is kinda funky
it's kind of like combinatorics
the result might be intuitive but formally arguing it is pain

I'm thinking something along the lines of consider three neighbors A,B,C of x, if x isn't a cut vertex, then each two of these points has a path connecting them that doesn't pass through x, and that path has odd length.
Now combine those paths to get an even cycle somehow, getting a contradiction.
yea that's my idea as well
you basically want to force the vertex to somehow arrive at an even cycle
if G - x were to be connected
specifically, since G - x is connected, then there exist a path P_{u, v} that connects the neighbours u, v of x; then in the graph G, you can obtain a cycle by going x -> u ~> v -> x
prove that if a vertex not discconect the graph, there are an even cycle
that tells you something about the path from u to v (since G has no even cycle)
consider a third neighbour z and by the same reasoning above, you can deduce something about the length of the path P_{u, z}
An urn contains N balls enumerated from 1 to N. Let X be the largest number drawn in n drawings,
when random sampling with replacement is used.
(a) Find E(X) as a function of N and n.
(b) Approximate E(X) for large N and constant n.
(c) Approximate E(X) for large n and constant N.
i need help with this question
idk if you're still awake, but I solved the problem!
thank you so much! 
This question said to use "Menger's" as a hint but I didn't do anything of that sort. My understanding was that its not necessary (Also Im not sure how to make use of it).
What I did is contradiction saying that suppose VertexConnectivity > EdgeConnectivity
If edge connectivity = x, then this implies there are x edges I need to remove to disconnect my graph.
Let E be these edges. If I remove a vertex at the endpoint of each edge in E, those edges will be removed too. So if I delete |E| = x of these vertices, this will disconnect the graph.
So this contradicts VertexConnectivity > EdgeConnectivity. Is my approach valid?
if you delete a vertex you may delete multiple edges, your argument seems to assume you only delete vertices of degree 1
Ah yeah its not strongly worded I realize. Maybe i can talk about induced subgraph without these vertices
Would mengers be better instead? I just couldn't recognize how I'd apply it.
So I know that there are two variants of Menger, Edge menger and Vertex menger theorem.
WLOG,
Vertex Menger says the minimum size of an s,t vertex separator = the largest # of **vertex **disjoint paths from s to t.
And a corollary of it is that G is k-connected iff for every 2 distinct vertices s and t, there are at least k **vertex **disjoint paths from s to t.
Yeah
Also Vertex seperator is a set S where G - S either disconnects the graph or reduces it to a single vertex
yeah
if you have these paths, you know you must remove at most one edge from each path to make the graph disconnected, and you definitely don't need to delete more vertices than that to achieve the same thing
right?
I think this is because you need to remove the "middle" of each path to prevent yourself from going from S to T. When you delete a vertex in the middle of a path (it is an endpoint of an edge), it will delete edges that it is connceted to
yeah you will delete many more edges but that's ok
at least that's how I understood the question
yes that is possible from what i can see too
but whats stopping us from talking about an induced subgraph without the vertices? I thought that would also work if we do a proof by contradiction
what's the contradiction?
That VertexConnectivity > EdgeConnectivity, but we show we can find an even smaller vertex connectivity
hmm, how do you know that you need to delete fewer or the same # of vertices?
i can have a strategy: look at each edge, mark an arbitrary endpoint for deletion if none of its endpoints have been marked yet.
Otherwise if an endpoint is marked to be deleted, do nothing and process the rest of the edges.
On each edge we are marking at most 1 vertex for deletion
so |marked| <= |E|?
Yes sounds like that would work too
can I have a hint for b)? IMO it seems canonical to associate each function from X/Y to {0, 1} with its domain to get a function into f^{-1}(the empty set), but this function definitely isn't injective
just because two functions have the same domain does not of course imply that they're equal
oh nvm maybe i can assign each function to their preimage of 0
oh i'm being pretentious and using it as an adjective
here canonical means natural choice
the first thing that comes to mind
yes
how, exactly does it imply it?
clearly applying only axiom of regularity doesn't help, since we can have A in A[*] and ø in A, and so ø is that element which was guaranteed to be disjoint from A
but where do I apply the pairing tho?
[*] (aiming for contradiction ofc)
let S be a set, then {S} is a set by pairing. then regularity finishes it
what exactly does it finish?
S = empty set
{S} is a perfectly valid set
i mean, let me elaborate
here we just assume S is a set, right?
nothing more?
regularity says "every non-empty set contains an element disjoint from itself"
sps S is a set. then {S} is a nonempty set. thus S \cap {S} = empty set by regularity...
I mean, I still don't see what's wrong with that intersection
if S were an empty set, then of course
emptyset intersect {empty set} is an empty set
we only require {S} to be non-empty
not S itslef
we can just take them as separate cases if you want, clearly emptyset is not an element of emptyset, then for any nonempty set we are done by the above argument
i guess im kind of confused by ur objection
if S and {S} do not contain any of the same elements then you cannot have S \in S
it's 4:35am where I'm from rn xD
so I might be trippin
I will then come back to it after some sleep 
yeah
but that's what you wrote in the first place
idk how you meant to connect A in A and a statement about {A} ({S} in ur nonation)
thanks anyway tho!
hope it will be more clear to be after proper sleep
Hello, could someone recommend interesting graph theory exercises where König's theorem or Hall's theorem are needed?
I think the idea is to remove a perfect matching from a k-regular bipartite graph and apply the same argument to it, but how do i justify that the k-regular graph initially has a perfect matching?
I'm trying to say |A| <= |N(A)|. I made a mistake saying that since its k-regular that |A|k = |N(A)| so it follows |A| <= |N(A)| but this sounds flawed after a second look. any advice?
the graph is bipartite, so let the partite be (X, Y) and consider any subset A of X. We will denote the set of edges incident to A by E(A) and the set of edges incident to N(A) by E(N(A)).
(1) Every edge incident to a vertex in A is incident to a vertex in N(A), so E(A) \subseteq E(N(A)).
(2) The graph is k-regular, so |E(A)| = k|A| and |E(N(A))| = k|N(A)|
(1) + (2) together imply Hall's condition
it might be worth mentioning that because the graph is bipartite, edges go from X to Y so A \cap N(A) is empty, which is why the reasoning here works
do hypergeometric functions always have compact support?
my instinct wants to say yes, because if the index goes negative, eventually one of the factors becomes 0, and then that kills anything beyond that point
but i dont see how that can necessarily always work on the other side as well, and there is an issue if the summation has a term like (2n+1)!
Ohh wait, I think I confused X-perfect and perfect matching. What we showed is X-perfect matching right? Perfect matching to me means that everyone in X and everyone in Y is matched to someone which I think I didn't justify.
I want to claim that if i remove edges that belong to the perfect matching, then the graph becomes (k-1)-regular,
yes you have the right idea
what we have rn is that the graph has an X-perfect matching
you now want to extend that to a perfect matching
i.e. what you want to try and prove is that |X| = |Y|
I see, I think I'm supposed to use the fact that the number of edges from X to Y is k|X| and number of edges from Y to X is k|Y| somehow since the question talks about k-regularity
Not sure how to formally talk about it though, like because its bipartite each edge is counted "once"? Because I'm trying to go to k|X| = k|Y|
well
the graph is bipartite
so edges can only go from X to Y and vice versa
so every X -> Y edge is also an Y -> X edge
and neither overcount or undercount the number of edges
so you have that k|X| = k|Y| which implies that |X| = |Y|
it's just a corollary of the property that G is k-regular and bipartite
👍
Giveaway Letter:
|| D ||
@lusty loom @bronze shuttle @final turret @copper oar
no winners
is there by chance kinda like a path that i can follow or checklist to see which formula for combanatorics i can use
like a flowchart
I mean, it does not directly answer ur question, but still might be helpful
usually, this 'feeling' is just developed by solving problems
bc a flowchart will most likely fail when u need to apply say two techniques
otherwisd the flowchart would have to be enormously big and unreadable to contain anything other than the trivial cases
the twelvefold way is what frownyfrog just posted, but it is only a chart for a certain class of combinatorial formulas, namely the number of ways to count the subsets of a set given a combination of additional special properties
however, in general this is not possible. if such a complete flowchart existed, we could probably solve all combinatorics problems (depending on definitions)
but there is a way to meet you halfway there
- consider the act of counting as a constructive method, where its base "pieces" are, say, the twelvefold way or whatever else you already know is verified to be correct
for example, suppose I want to find the number of permutations of A,B,C. i know that it is 3! = 3x2x1. but what do the numbers 3,2,1 represent and why do we multiply?
the 3 represents the number of choices in the set {1,2,3}, the 2 represents the number of choices in {1,2}, and 1 the choices in {1}
multiplication means we must make one choice in each of the three sets. for instance,
{1,2,3} -> 2
{1,2} -> 1
{1} -> 1
now we have a set of rules that maps (2,1,1) to our permutation. take the 2nd letter B, then the 1st of the remaining letters A, and the 1st of the remaining letters C. (2,1,1) gives BAC
we know this structure is counted correctly because we "built" the list of permutations correctly
- we can verify any part of the counting problem by either forming a bijection or checking for both overcounting and undercounting
more details: https://m.youtube.com/watch?v=uxjAHkn4VFI
To see an example of how bijections can transform a hard problem into an easier one, check out the previous video of the series: https://www.youtube.com/watch?v=3B-D3w292TI
If you want to see some more examples of where these ideas can be applied, try these problems: https://www.youtube.com/watch?v=LUVKuyfpe2I
My Patreon: https://www.patreon.c...
a bijection is the most direct way to verify the count is correct, but if you have a larger problem split into cases, youre going to need to think in terms of the coverage of the cases, like overcounting and undercounting, maybe utilizing inclusion-exclusion as needed
if you can count the pieces, then use the pieces to build the larger picture, that is as close as you can get to a flowchart that tells you which formula is correct
for more "atomic" formulas youre probably using step 2, for more complex formulas or for applying the formulas to problems youll likely use step 1
dont hesitate to ping or dm me if any of that was confusing or unclear
i'm back after some sleep xD
tried as follows, but it proved nothing
any directions?
if we never define what a set is, then what does the vanilla equality sign, from the first-order logic, check?
yes, it's «extended» by the extensionality axiom, but assume for a moment we didn't have that axiom
how do we even transform the human notation A={ø, {ø}} into pure first-order logic?
problem resolved
- assume A is a valid ZF set
- then S:={A, A}={A} is also a valid set
- by extensionality it must have at least one element, call it m in S, disjoint from S
- So, it should be that m=A int S={A} = ø
- IF we had A in A, then we must not have it in {A}, i.e. A != A. Contradiction
The expected number of dancers falling on stage dur-
ing a contest is .3. What is the probability that during the
next contest, (a) no dancer falls on stage and (b) 3 or more
dancers fall on stage? Explain your reasoning.
why is it possion?
it's poisson because, assuming all dancers are the same, as is typically assumed in these kinds of idealized math problems, each dancer has an equal probability of falling at any time, distributed randomly across a continuous span of time
what makes it poisson is that, there is a small chance that a dancer could in theory fall and then get up and then immediately fall again
theoretically there is no limit to the number of times a dancer could fall
this is the kind of distribution that a poisson distribution is modeling
Hey, is anyone familiar with error correcting codes? I'm working on a practice problem about correcting n-bit strings in k places using randomization while communicating as least of information as possible, but I'm getting a bit stuck.
this would be false right?
i'm planning to self-study discrete math, does anyone know a website with good notes?
i think its false ye
what is meant by a discrete math course varies enormously from one institution to another, more so than for most other courses
see what's on ur curriculum, and find textbooks/notes for those things separatly
for example, my discrete math course includes ZFC, combinatorics and automatas
all of those are independent and one could spend an entire life studying each part
here are thee textbooks for set theory I like (author on the right)
and there is an amazing playlist on YT that gives some nice overview and context for the zfc axioms
can someone walk me through this please
thank u!!
anyone? 😭
anyone really keen on group theory
tryna prove this isomorphism without using a function which all the answers use
(R,+) and (R+, x)
the answers just use e^x
which yeah like works
but it feels dirty to use lol
wait nvm there is a group theory one
Can Menger's theorem be proven using Hall's theorem?
there are a few equivalent definitions for the nth catalan number, how is it defined for you?
yes; i believe you can do hall's theorem => maxflow-mincut theorem => menger's theorem
I mean, it halves each time
for 64 it will be 6 steps
for 1024 ten
not that many ig
A way to think about this function is that you’re really just adding 1 everytime you recurse. So now you want to think about how many times you’re recursing in terms of k
what part are you struggling with? because i think if you knew all the definitions then this problem is very straightforward
can anyone tell me if this is correct pleaseee
/offtopic/
u know what, I'm making my lecture notes dark. thank you for inspo! 
thats chatgpt but sure
lol
Send help
Ah yes, of course, I know that path. I am looking for a direct proof of Menger's theorem using Hall's theorem.
simply recall what it means for a relation to be a function
then notice x = y for x, y >= 0 implies x * x = y * x = y * y.
check if this holds
formally, if (x, y) in f and (x, z) in f, show that it implies y=z
The discrete mathematics book that I'm reading is saying that Floyd-Warshall Alogrithm has time complexity O(n^2), but clearly these are three nested for loops, with one comparison in each iteration, so it must be O(n^3), am I missing something?
Also, this algorithm is categorised as shortest path algorithm, but it only gives the value of the shortest path, not the path itself. However, we can keep track of each k in the step 2, thus obtaining the shortest path, right? Am I correct?
you are correct in that Floyd-Warshall is O(n^3)
FW is the canonical algorithm for APSP so it gives you the length of the shortest path from any pair of vertices; there are natural extensions to FW that gives you the explicit shortest path
just like how Dijkstra and BFS only gives you the length of the shortest paths for weighted and unweighted graphs from a single source, but it can be extended to give you the actual path
{(a,b) | a and b share a common parent}
Could someone explain me one thing. Is it reflexive or not? According to ChatGPT it is not reflexive, but I'm think it is
thats more of a language question than a math question
can you share something with yourself?
Yeah, it is strange, but if a and a are the same age then it is reflexive. That is we share the same age, don't we?
I got it. If it is like {(a, b) | a and b have the same parent} then it is reflexive
Am I right?
reflexive would be that (a,a) so the set is reflexive if an only if every person shares a parent with themselves. which personally i would say sure
So you think that you can share a parent with yourself ?
sure. but thats kind of a language game. without a pure definition of what it means to share a parent i cant tell you with 100% certainty what the asker of the question would want.
but my intuitive sense tells me yes.
I’m agree with you, but it turns out that there is a difference between “the same” and “a common”
Sorry, my bad
Let's go through each option
What do you think about i, is there a set that has no subsets?
Is it correct if I set t(n)=t(n-1)+t(n-2)+n for t>=3 for part a?
Yeah
But it’s weird cuz the root of characteristic equation will be 1.62 and -0.62
Kinda messy compared to calculation steps of other examples
is this how you write "The function f(x), which maps integers greater than 10 to a positive integer, is equal to x - 10"?
When specifying the domain and codomain, you should write only the name of the function
The domain and codomain and the rule of assignment should be stated separately also
\begin{align*}
f: { &x \in \bZ \mid x > 10 } \to \bZ^+ \
f(x) = &x-10
\end{align*}
so would it be something like
$f: {x \in \mathbb{Z} | x > 0 }
oh u got it first
cool
The second line can be rewritten as f: x |-> x-10 as well
A Loner Bean
People would usually write $f \colon A \to B; x \mapsto x-10$.
$\mathbf{Boytjie}$
Usually aligned beneath each other :)
interesting problem
no way you're here too
hows it been man
i'm confused as to what this question is asking, could someone clarify?
is it asking about how many possible mappings there are?
nvm i got it
"assign 0 to 1 and n" does this mean f(n) = 0 and f(1) = 0, or that f(0) = 1 and f(0) = n?
whats the question?
yeah so its the first thing you said
well while we're here, i'm confused on part a
also you cant have a function that maps the same value to different values
if n = 1, then it wouldn't mapping to different values
that was my thinking ig
one-to-one means that the cardinality of the domain must be less than or equal to the cardinality of the codomain, right?
yeah there are no one-to-one functions here
so if n is any value greater than 2, there's no one-to-one
but what if n = 2?
oh yeah
it says "n is a positive integer"
if n=1 or n=2 then yes
so, for all possible values of n, i'd suppose there would be 6 different mappings
2^1 + 2^2
theres only 2 possible 1-1 functions when n=2
u right
1-1 means that each element in the domain maps to a different value
okay for part c i'm intuiting n - 1 but
idk how i'd prove it mathematicallty
i'm proving it to myself by saying that we can imagine the mappings as a bitstring, where a 0 at position i means that the function maps i to 0, and 1 at position i means that the function maps i to 0. the nth position must be a 0, and from there, only 1 of the (n-1) positions may be a 1. so it's how many (n-1) digit bitstrings can be created with only one usage of the number 1
which is equal to (n-1)
oh, it's 2(n-1), because the nth position can either map to 1 or to 0
but idk the actual mathematical process of arriving there
what is this asking me to input? am i supposed to calculate the sum using the n(n+1)/ 2 ?
Yes
anyone know a tool that you can plug set builder notation into and get the set?
I've tried looking at wolfram
but it doesn't understand me (or i dont know how to use it properly)
and the ones i found online are a bit too simple
for instance i want to be able to get a few values for this set
${( nx+1,y^2+1) \colon x,y \epsilon N, (n \epsilon Z, n >= 0) } $
adam
Compile Error! Click the
reaction for more information.
(You may edit your message to recompile.)
hello dear peers and elders. I would like to know the best resources for discrete maths on youtube.
Ahem* Ahem*
AHEM* AHEM* AHEM* (agressively)
https://youtube.com/playlist?list=PLHXZ9OQGMqxersk8fUxiUMSIx0DBqsKZS&si=8bQnGF-alnXCtyIl I haven't watched this full course but I've seen some of his vids and I think it could be good
i cant wrap my mind around this, so i understand up to the step where 2^k+1 < (k+2)! ( k+3). how is (k+2)! x 2 = (k+2)! ( k+3)
It doesn't state that (k+2)! * 2 = (k+2)! * (k+3) either
k > 1 is assumed, so 2 < k+3 and (k+2)! * 2 < (k+2)! * (k+3)
By transitivity, 2^{k+1} < (k+2)!*2 would imply 2^{k+1} < (k+2)!(k+3)
I want to prove that a tree with n vertices has n - 1 edges. I prove by induction. For n = 1 it's clear, such tree has no edges. Now assume that a tree with n - 1 vertices has n - 2 edges. If we add a vertex to such tree so that it remains a tree, it can only be a leaf node or and extension of a leaf node. So it will add 1 more edge to the graph thus increasing total number of edges to n - 1. Proof is complete (?)
Can someone verify it?
Technically it's fine as long as you know that every tree can be constructed by repeatedly adding vertices to the tree of 1 vertex. If you think it requires a separate proof and don't really feel like proving that, you need to change how the induction step is formulated. For example, say G is a tree with n vertices, there must exist a leaf v (I am assuming this has been shown) and G\{v} must be a tree. The rest should be obvious
What's your definition of tree?
There are several characterizations and it's a common exercise to prove they're equivalent.
In fact, for a finite graph, being connected and having |E| = |V| - 1 is equivalent to any of the other characterizations.
A connected graph that has no circuits
For induction, you want to start with a tree on n+1 vertices and remove a leaf to get a tree with n vertices and use the inductive hypothesis on that.
Can you assume every tree has at least 1 leaf node, or is that something you have to prove?
(In this context, a "leaf" is any vertex v with deg(v) = 1.)
Hi, can anyone please explain why this proof is incorrect? The solutions manual says the proof is incorrect because it assumes what we’re trying to prove and works its way to a well known fact. I’m not sure I fully understand how that makes the proof incorrect. I’ll appreciate any additional help with this. Thanks.
They start with the given statement, call it P(x, y), and simplify it to a tautology. This means what they are showing is only that P(x, y) implies truth, but that doesn't tell you anything about the truth value of P(x, y) (recall that True => True and False => True)
In general proofs should start with statements that have already been proven to be true, not the other way around
Got it! Also this explanation is very helpful for thinking about how to go about writing a proof for it. Thank you!
Hi, can someone help me explain how to solve this problem? Given a set M= {1, 2, 3, ..., 99, 100}. How many placements without repetitions exist of the elements of the set M of four elements each that contain: a) number 47, b) simultaneous 17 and 47
I tried to solve this problem, but i don't know is my solution correct. Solutions 4 options for the number 47 and placement from 99 to 3. 4*A(97, 3)
If by placement, you mean “without order”, then you simply need to choose 3 more elements to make your set of four elements. So you then have C(99, 3). If by placement you mean “with order”, then each unordered set has 4! ways of being chosen. So this gives you 4! * C(99, 3)
For (b), it’s similar but this time you want to force both 17 and 47 in the set already, so you have 98 more choices to pick/choose 2 more elements
do we use an equal sign or a logically equivalent sign when dealing with propositional functions?
p(x) = (2x = x + x) or p(x) ≡ (2x = x + x)
i would use $p(x) \iff 2x = x + x$
kaue
I like $p(x) := 2x = x + x$
Morrow
Here is an interesting question. Let's say G = {a, b, c} is a group with three elements with an operation *
Now since G is a group, there is a neutral element in it. Let's call it the element a
Now let's say that b*b=a
What can you then say about what is b?
so then how would we use it in an assumption?
You wouldn't say "Assume $p(x) \Longleftrightarrow 2x = x + x$", since that assumption isn't that they're both true, it's that they're equivalent. I want to state "P(x) is equivalent to blahblahblah and they're both true"
Alrighty
you can do \iff???? bruh i have been using
Longleftrightarrow
for like a year 😭
the iff acts like an "equals" for statements, this is its truth table:
False iff False --> True
False iff True --> False
True iff False --> False
True iff True --> True
yep it stands for "if and only if"
i know how iff works, but what i'm saying is that in the assumption of a proof, you say "Assume p(x) is true". if i say "Assume $p(x) \iff q(x)$", I'm just saying that they're equivalent. I want to state that they're equivalent AND they're true.
wha
oh it think i'm using the underscore
breh
Alrighty
couln't you just say "Assume p(x) is true" or "assume 2x = x + x"?
i'm doing proof by induction, my professor wants me to state the propositional function AND the actual function so we can perform algebra on it
so like
he wants the p(k) and the (2k = k + k)
and he wants us to assume they're both true
i guess i could do like $p(k) \land (2k = k + k)$, but this makes them seem like they're two separate things
Alrighty
Seems like you're trying to do two things at the same time, i would just define p(x) as 2x = x + x and then assume p(k) is true for some k
professor wants it, not me
i do define it earlier that p(x) \iff 2x = x + x
but he's weird ig and wants me to include the definition and the function in the assumption
would something like "Assume p(k) is true for some k, so we have 2k = k + k" do it?
probably
Assume $\forall k (p(k)), \therefore 2k = k + k$
Alrighty
?
Normally, when you're doing induction you are assuming for a specific value k, to then try to prove for k + 1
not for all k
if you were to use universal quantifier, you would use $\exists$
kaue
we have our basis step which proves that p(k) for the smallest value on the domain, but then we have to prove that p(k) -> p(k+1) for all k in the domain
"it's true for all values in the domain" is the conclusion, when you are doing the inductive step you assume for a single value k, and then prove its true for k + 1
and if k + 1 is true so is k + 2, etc.
assume $\exists k \in \mathbb{N}$ such that $p(k)$ is true, this means $2k = k + k$
kaue
The syntax doesn't really matter. The professor is trying to make sure you're clear on what the proposition is and what variable you're inducting over, which will both help him see what you're confused about and help you avoid common mistakes w/ inductive proofs.
\\
I'd just say: Let $P(k)$ be the proposition that $2 \cdot k = k + k$ and write $$P(k) := 2\cdot k = k + k$$
$P(0)$ is clear. Then if you write out what $P(S(k))$ means it will become clear what you need to prove. Here $S(k)$ is the successor of $k$. You get: $$P(S(k)) := 2 \cdot S(k) = S(k) + S(k)$$
Well, how is multiplication defined? The recursive part of the definition is something like: $$a \cdot S(b) = a + (a \cdot b)$$
The left-hand side of the equation for $P(S(k))$ is $2 \cdot S(k)$, which looks just like the left-hand side of the definition of multiplication. How convenient!
Cufflink
Compile Error! Click the
reaction for more information.
(You may edit your message to recompile.)
The purpose of this approach is that if you have a clear, explicit expression for $P(k)$ then writing out $P(S(k))$ is almost mindless: find every $k$ in the expression for $P(k)$ and replace it with $S(k)$.
Cufflink
How can you define the notion of a set rigorously?
After some research I can say that that wasnt a bad response since it seems fundamental @vestal bronze
im just gonna stick with the good old "ignore the meaning, if it stops working change the axioms" ig
the problem with my definition is that it's actually about mutisets, where it matters how many times you have the same thing
sets are like, " for each thing you either have it or not", you define a set by defining what things are in and what are out
and then the problem is that you would assume the set can have itself
paradox yay
so you can't give a short intuitive definition, it's jsut that speciific thing
my problem was more with recursivity than intuition
Every definition is an expression of something in terms of something else. What would a satisfactorily rigorous definition of a "set" look like?
In other areas of math, we might call a definition "rigorous" if it can be framed in terms of sets and acceptable set operations + theorems.
But that's not available here.
Youre right
My question was wrong to begin with
Set :: List Set
apart from the mentioned earlier paradox, that makes sense i think
It's not wrong, but it means one has to interrogate the nature of "rigorous" and "definition"
yea its a good definition
from what I can think of now, the notion of lists seems to be fundamental
I meant my expectations and question contradicted themselves
thanks for answering my questions though
well the issue with this is that sets aren't ordered and can be infinite, and also List has more than one fixed point so this doesn't uniquely specify what Set is, and also some type constructors have no fixed points so in general defining types recursively this way might lead to contradictions
well you'd need an infinite list... ok yeah i guess if "List" counts a list of length omega then that works
list is a pair (thing, list)
thing is the first thing
so it's already optionally infintie
ok that's another case where the definition is recursive and ends up having more than one fixed point
right, it's also optionally not a pair
what
Cant you define it as a classification of objects?
objects are things
and classication is whatever it might be
well that's even less of a definition than "Set = List Set" is
like you've just moved the issue to defining "classification"
isnt it fundamental though since its rooted in patern recognition?
and also it's not clear how something like "all of the sets that don't contain themselves" isn't a classification
a set is a singleton set, or a union of two sets, or an empty set
at the point where you're saying things like that you are no longer doing mathematics, you are doing philosophy
maybe it covers uncountable now idk
this might include uncountable things
isnt math based on phisolophy?
"might" as in this defines a proper class of distinct notions of "set", which includes "all of the sets" but also "only the finite sets" or "only the countable sets" or various bizarre middle grounds like "everything that is a union of a subset of R and a finite set"
The fixed-point lemma for normal functions is a basic result in axiomatic set theory stating that any normal function has arbitrarily large fixed points (Levy 1979: p. 117). It was first proved by Oswald Veblen in 1908.
well i don't know what you mean by "based on", but in any sense that's relevant to this conversation, no
mathematical proofs can be checked by computers, philosophy can't (it can't even be checked by humans)
anything which isn't literally a syntactically valid string of symbols in the formal language that you're using, is not a definition, because you cannot explain to a computer what the definition means and what a correct proof involving it would look like
I mean that you can have phisolophy without math but not vice versa. It implies that you need philosophy to define math, if my understanding of the definition of philosophy is correct.
(of course in practice humans don't actually communicate purely in computer-readable piles of symbols, but still, this is what the standard of mathematical rigour means, anything that cannot be converted into something computer-readable is either not mathematics or just wrong)
I mean that you can have phisolophy without math but not vice versa.
i think this is wrong but it doesn't seem like the most important point to address so let's skip it for now
It implies that you need philosophy to define math
maybe you do in order to "define math", in the sense of philosophy, but in mathematics "definition" means something different to that
cufflink said that rigour means that it can be defined by set theory
but we are talking about defining the actual sets
...i think "rigour means definable in set theory" is just imprecise/wrong tbh
but anyway, the fact that we're defining sets doesn't mean that what the word "definition" means changes
what is the correct definition then?
well, in what context?
if you're working in ZFC and want to know what "sets" are, well they're just all of the objects
so sets := all objects?
if what you really mean is "how do you explain to a computer the kind of thing humans do when proving things about sets", then i think the best answer is something like the axioms of ZFC, although exactly which axiom system... will depend on which humans you're talking about and what they're doing
in ZFC, yes
That's not what I said!
What did you mean?
yes
in the sense that "x is an object" in this context is just always a true statement
interesting
Someone looking for a "rigorous definition" is looking for a definition that they find satisfactory in some way. Every definition of something is given in terms of something else, however.
In most mathematical contexts, what satisfies someone's demand for a "rigorous definition" is a definition given in terms of sets and their operations.
In other words, such a definition usually suffices, but that doesn't mean it's necessary.
There might well be other objects that would satisfy their demand for a "rigorous definition", if only we could adequately conceive of them.
That makes more sense now
But someone looking for a "rigorous definition of set" isn't going to be satisfied by defining sets in terms of sets, even assuming you can somehow do it in a non-circular way.
Hence the hope in the 19th century of people like Frege that set-talk could be reduced to pure logic.
are the variables free because there is no "for some" or "for all" in this thing??
nvm he covered it in the next minute
Well what's the standard way to show that something is a subset of something else? We begin by taking some arbitrary element of the former, and showing it must be an element of the latter.
So suppose that y is some element of [a]. What does this mean in terms of the relation? Note that you know a ~ b, so what does this imply?
Are multiplicative inverses unique?
I did a quick proof that I think means they have to be, but I wanted to check
Yes
Let b,c be two inverses of a, then:
b = be
= b(ac)
= (ba)c
= ec
= c
Yep ok, that's what I did basically
I'm just a bit confused
aren't axioms recursive?
For example. We say that Powerset axiom states the following:
Given set A, there is ZF(C) set P s.t. x in P <==> x subset A
so, when we said there exists a set P, we have to guarantee is satisfies the Axiom of Power set. But we are right in the middle of defining what that even means!
the axioms don't define what sets are
we just have "set" as an undefined term and then the axioms are some assumptions about the properties of sets
so, instead of saying «there is a ZF(C) set P», I should've just said «there is a set P», right?
yeah it's just "there is a set P"
wait, but don't we have to asses it's a 'ZF' set to have any usefulness from the axioms?
for example, that not-necessarily-ZF-set might be a set that contains all the sets..
cause in the powerset axiom, we asses there is just a set, not the more restricted notion of a ZF set
well according to the axioms there can't be a set that contains all sets, because then (by the axiom of separation) it would have a subset which is the set of all sets that don't contain themselves, and this is a contradiction
there can't be a zf set, right?
i.e. a set that satisfies those axioms..
i feel I'm confused..
the axiom of separation doesn't say "every zf set"
it's not an individual set that satisfies the axioms of ZF(C)
it's more like, some meaning of the word set satisfies the axioms of ZF(C)
to check if the axioms of ZFC are true you need to know about all of the sets and their membership relation
for instance if you declare that a "set" is one of the letters A, B, C, and that the membership relation is {(A, B)}, then this isn't a model of ZFC, because for instance the axiom of extensionality fails, A and C have the same elements but they aren't the same set
if a "set" is a natural number, with n \in m iff the nth binary digit of m is 1, then this is "almost" a model of ZFC, but it doesn't satisfy the axiom of infinity
maybe it would help if we look at a simpler theory?
consider the theory with a symbol < and the axioms:
- for all a,b,c, if a < b and b < c then a < c
- for all a,b, if a != b then either a < b or b < a
- for all a, a < a is false
this is just the axioms of a total order
then one model of this theory is the natural numbers, with the obvious < relation
the integers are another model of this theory
but it wouldn't make any sense to take some random object like 4 and ask if it's an "ordered object"
an order is on a set
oh, I don't know what a model is, yet : (
just the basics of ZF axioms
basically it's just "a structure that the axioms are true in"
for instance my claim that N is a model of this expands into just
- for all natural numbers a,b,c, if a < b and b < c then a < c
etc.
so we basically 'define' what a set is, in a model, right?
...kind of
i'd say it's more, a model is a possible meaning for what a "set" is
but like, there's loads of them
ZFC can't prove or disprove the continuum hypothesis, which is that there's no set with cardinality strictly between the natural numbers and the real numbers, and the way we know that is that we can construct a model of ZFC where the continuum hypothesis is true and another model where it's false
but yes in the sense that the theory ZFC itself doesn't really say what a "set" is (just some properties that we expect sets to have), and a model does
from a philosophical platonist perspective the reason we're doing all of this is that we think there's some "real" universe of sets (which would be a model of ZFC), but we don't know how to define what exactly it is so we kind of just wrote down some statements that should obviously be true about it, and ended up with ZFC
I'd think of it more like this.
We have some vague, intuitive conception of a mathematical object, like number or function or set. If we want to prove things about them we have to make our conception precise enough to do math with them.
Axiomatic systems like ZFC aren't a "definition" of set per se. They're more like one attempt to make our conception precise enough that we can do math with them.
So, the power set axiom is saying something more like:
Under this conception of set, if I can talk about some set
Athen I can talk about the set of all subsets ofA.If you presented a conception of set and power set such that
Awas a set but it had no power set then I'm committing myself to saying thatAisn't a set or that I have to change my conception of set/powerset.
Take something less tricky like the axiom of pairing: if A and B are sets then I can talk about a set containing just those two sets and nothing else, designated {A,B}.
If someone told me there were sets you couldn't pair like that, I wouldn't say "You're wrong, the axiom of pairing says..."
I'd say "Their conception of 'set' must be very different from mine."
That when they say "set" and I say "set" we mean different things.
yes, yes
that is clear: we don't define what a set is, but say what it should behave like
what confuses me tho is that it seems those 'what it should behave like' conditions are resursively defined on top of each other(?)
Sure. I mean, how do you feel about Peano Arithmetic?
|| if I have enough fingers on my hand to verify the result, then I believe in it xD /s ||
ok with it
Ok, but there are lots of things about PA that you can't verify with your fingers.
yeah, sure
that's why I put /s at the end
i'm ok with PA
Right, well, it's giving a particular conception of number.
If you're ok with pulling the successor function S "from the void", so to speak, then why not also be ok with talking about the power set in the same way?
If I have a natural number n then S(n) is also a natural number.
If I have a set A then P(A) is also a set.
Part of the awkwardness are the restrictions in the formal language of set theory. It consists of a bunch of variable and constant symbols, but only a single binary relation ∈. That means you can't talk about "functions" directly.
yeah, that is move convincing!
thx!
What does it mean for some set X to be the power set of some other set A?
It means that S ∈ X if and only if S ⊆ A.
So we say: "For all sets A, there exists a set X such that: for all sets S S ∈ X if and only if S ⊆ A."
Ok, but formally we have to unwind S ⊆ A, too, so it only uses ∈.
Well, S ⊆ A means "For all sets w, if w ∈ S then w ∈ A"
So the full power set axiom is that concept, but expressed using only first-order logic and a single binary relation ∈.
Sometimes our axioms really do seem to capture something, e.g., when there's exactly one model up to isomorphism. Such a theory is called "categorical": https://en.wikipedia.org/wiki/Categorical_theory
In mathematical logic, a theory is categorical if it has exactly one model (up to isomorphism). Such a theory can be viewed as defining its model, uniquely characterizing the model's structure.
In first-order logic, only theories with a finite model can be categorical. Higher-order logic contains categorical theories with an infinite model. Fo...
For example, using second-order logic, there's exactly one model of Peano Arithmetic up to isomorphism.
So if you and I both commit to second-order PA then any apparent mismatch between our conceptions is a matter of us labeling things differently (or at least one of us being wrong).
Dedekind wrote a famous paper in the late 19th century called "What are numbers and what should they be?" where he first laid out a lot of the contemporary axiomatic characterizations of things like "infinite set": http://aleph0.clarku.edu/~djoyce/numbers/dedekind.pdf
another (probably more dump, but I'm just starting out) question:
to show that there cannot be a set U that contains all sets, we might say:
- Assume it exists
- by AoSeparation, take its subset, call it A, with the formula phi x not in x
- Then: A in A <==>^"def" A not in A
correct?
yep
similar one:
given a set A, show that the collection of x's, s.t. x not in A, is not a set
assume this is indeed a set. call it B. then B is defined as:
forall x [ x in B <==> x not in A ]
checking: A in B <==>^"def" A not in A
all good?
/ going thru some exercises without answer sheet /
You're supposed to conclude with a contradiction. In the previous proof that contradiction followed from A in A <-> A notin A. So while what you've written so far isn't wrong, you're also not quite done yet.
oh, yeah, my bad
didn't notice it. I thought for some reason I wrote A in A (not B) <--> A not in A
thx
then ig a better way would be to try to construct a set of all sets like this:
A union overline(A)
where overline(A) is the set of elements that do not belong to A
so, we have x in A u ov(A) <==> x in A or x not in A <==> foral x
but I've already shown that a set of all sets cannot exist. so..
That works 👍
is there difference between the two?
feels like the second one will also include e's that are not in A
i.e. False=>* is true
I don't get the second one, it seems to claim that everything is an element of A (which is very unlikely to hold)
The first one seems fine as a definition of intersection
well, I was trying to come up with a definition for int A
but I just didn't know which of those is the correct one
The second one can't be true, because it says that every e is an element of A, so A is the set of everything
The first one is fine
my concern is that if we say forall e [e in A ==> {....}]
then it might accidentially include either e's in A, or x's in int A, that aren't meant to be there, because of False=>Anything is true
{x | \forall e (e \in A \land x \in e)} would simply be empty, no matter the choice of A
So that doesn't sound like a good definition for the intersection
If e is not in A, then the implication is vacuously true and we don't care whether or not x belongs to e (which is the correct way to go about it)
If e is in A, then x has to be in e, which is also what we want
But look. Take e not in A. Then that thing is vacuously true. So, it implies some x (can be anything) is in the intersection, no?
No, because the implication has to hold for every e
well the implication has to be true for every e simultaneously
For the e which are not in A it holds vacuously, and for the e which are in A it might hold and it might not
So "practically" all we need to check is what happens for the e which are in A
But for all of those, x has to belong to e
i'll meditate on this one: don't get it atm
You've got the universal quantifier there
if you imagine there were only five sets $s_1, s_2, s_3, s_4, s_5$
bee [it/its]
then a forall reduces to just a conjunction $(s_1 \in A \to x \in s_1) \land (s_2 \in A \to x \in s_2) \land (s_3 \in A \to x \in s_3) \land (s_4 \in A \to x \in s_4) \land (s_5 \in A \to x \in s_5)$
bee [it/its]
now if for instance $A = {s_1, s_4, s_5}$
bee [it/its]
right
then $s_1 \in A \to x \in s_1$ is just $s_1$, because the hypothesis is true
I think i see where you are going
bee [it/its]
$s_2 \in A \to x \in s_2$ is just true
bee [it/its]
and so on for all the others
so you get $x \in s_1 \land \top \land \top \land x \in s_4 \land x \in s_5$
bee [it/its]
and then the two conditions that are true essentially just vanish, like if you had added 0 or multiplied by 1
$x \in s_1 \land x \in s_4 \land x \in s_5$, exactly what we wanted
bee [it/its]
i think i got it now
thankss! 
That's generally why implication is defined the way it is (which confuses a lot of people), in particular why "false -> anything" is a true implication.
Because it means that in this kind of statements with universal quantifiers, all that actually matters is the cases where the antecedent of the implication is true.
When it's false, the implication holds either way so we don't care.
But when it's true, we also need the second part of the implication to be true, and that's the only significant scenario
Hey y'all do you know a good book to learn about Discrete Mathematics? I need help specifically with Topic 1 -> Preliminary concepts and number theory. Topic 2 -> Sets, Functions and Counting. Topic 3 -> Graph Theory, Topic 4 -> Classical Propositional Logic.
Do you think this book will help me? Cause rn i'm really struggling with discrete maths
I don't know you. I couldn't possibly say.
Do you know any other books? I'm looking if that book is in my uni's library
btw, what if A=empty?
i.e. \bigcap \varnothing = ?
forall e [ e in A => ... ] will evaluate to true
so will this intersection contain, well, everything?
Sort of, there's a discussion here: https://math.stackexchange.com/questions/959201/the-intersection-of-an-empty-family-of-sets
oh, interesting
Thanks!
Typically when you work with unions and intersections, all your sets are subsets of a common space, and universal quantifiers are understood to only apply to element of that space, in which case the intersection of an empty family would be the whole space.
If you're not in a fixed space, then yeah, the intersection of an empty family would be the set of everything, which is a problem (and you should probably bypass it by refusing to consider an intersection of empty family)
I was trying to pin-point where exactly the proof that bigcap A is not a set breaks down when A=ø, but I couldn't..
in that phi(x)
if cal(F) is empty, then indeed phi(x) is true for all x
but the thing is – this is just a separation
we will get at most bigcup F, and no more
so idk where the potential «set that contains all the sets» pops up
wait, what
why do we need to include x in c?
(obviously it must somehow fix the issue, but I just don't get the motivation for asserting that in particular)
/ related to the same question above /
$c\cap\bigcap A$ is a set by separation (since $c$ is a set) and $c\cap\bigcap A=\bigcap A$ since $c\in A$ and hence $\bigcap A\subseteq c$
Neverbloom
no, I absolutely understand that it gives the desired result
after all, (x in c AND x in A\{c}) is just (x in A)
i don't get the motivation for that step
well to apply separation we need a set that we're constructing a subset of
Sure, but that requires an additional axiom and doesn't really do anything better than just picking an element from the family
i mean, I'm rather looking to see where exactly my attempted proof, using this axiom of union, shoulda failed
compared to finding the optimal proof (?)
you probably have already explained it; sorry if I don't get it :[
Your proof only shows that ${x\in\bigcup\mathcal{F}\mid \varphi(x)}$ is a set, you'd still want to show that ${x\in\bigcup\mathcal{F}\mid \varphi(x)}=\bigcap\mathcal{F}$ and that will require the assumption that $\mathcal{F}$ is nonempty.
Neverbloom
hmm
A real argument why separating from the union isn't a terribly good idea:
The proof that picks an element out of the family to separate from actually proves that the intersection of any nonempty class is a set.
Taking intersections of proper classes does come up every so often (for example when constructing omega as the intersection of all inductive sets) and then the proof that separates from the union doesn't go through since the union of a proper class is again a proper class (good exercise!)
thank you for the input!
I will come back to that later
(I will. I literally saved ur reply in notion xD)
Six X ' s have to be placed in thesquares of the figure below, such that each rowcontains atleast one X. In how many different wayscan this be done?
If I start choosing subsets of an nset, how many must I choose before, the collection of chosen subsets covers [n]? Worst case is choosing all n singletons, but say I assume I choose a subsets of some cardinality first, is there a name for this?
How does one x in each row not satisfy "each row contains one X"?
If we place 4 xs in the row 2 and 2xs in the row 1 then row 3 is all empty soi this unsatisfies the condition
Oh you have to place 6 total
Yuh read the text first 😭
Sry
Ots alr
Since the six xs fill up most of the diagram, it can be helpful to think of this by counting the 2 squares that will be left open
I am thinking of placing the first 3 xs in each row so that they satisfy the min 1x condition
@true venture what u think
That's what I though of first, but then when you place the remaining 3 xs you get some overlap
Yuh
If you can account for that then that way could work, but for me seems easier to count the empty squares
Can we jsut delete those overlaps by counting
We need to leave two squares open. If we number the squares 1-8, going left to right, top to bottom. Then we can count the pairs of empty squares by the first number of the pair.
Also the pairs are all (a,b) a<b.
Then since this is small you can think if I leave Square 1 open what others can I leave open, if I leave 2 open....
Should i tell u the answer
Do you have it, let me add them up see if we get the same
Its 26
Yea I get 26 too
Yes i get that u need to leave 2 squares empty right
- 1 2 *
3 4 5 6 - 7 8 *
So if we leave Square 1 open, what other squares greater than 1 could I leave open?
Any one from the 7 squares
Really Square 2?
Yea
Can we do by my method
So, leaving Square 1 open there are 6 other square greater than 1 I can leave open. Then repeat this for the rest of the square and sum
Idk if I know 😅.
Okay but can u try that way
Idk, it's maybe like double counting
I have a problem but I don't understand the answer really, could someone help me please?
The problem is: There are 4 people on an elevetor in a building and the building has 10 floors, how many possibilities are there for 2 person to get out on each a different floor and then 2 to go together on the left over floors?
The answer given is: 109(4 choose 2). Can someone explain or is this wrong?
ping me please
4320
Among the 10 floors, you must choose 2, then choose 2 people in an ordered way (who will go to those two floors), then choose one from the remaining 8 floors. In total: C(10,2)*4*3*8
this isn't possible, right?
A={{1}}
B={2}
C={{2}}
D={1}
oh...
thanks!
Ig I was a bit intimidated by the number of curly braces xD
after you replied, came up with another example (after I was sure it is possible xD):
A={{ø}}
B=ø
C={ø}
D={ø}
yeah basically the trick is just, you want A = {D} and {B} = C
cool little exercise 🙂
now I know why we don't define ordered pairs this way
did I miss anything?
Seems fine
I'm stuck trying to prove that a bipartite graph G=(A,B) with maximum degree \Delta has a matching of size at least |E(G)|/\Delta. I know the chromatic index is \Delta but not much else, unsure how to proceed
got it, I got a hint from SO, show that the size of the smallest vertex cover must be geq this number
Use Konig theorem
Yeah
is a pair a set? my graph theory textbook says that an edge set isn't a family but I was always under the impression that a pair is a set of two things
In ordinary set theory, everything is a set -- we construct things out of sets because we want to provide a foundation for mathematics purely in terms of sets. So yes, in particular a pair is a set.
However, this is the important part -- the pair (a,b) is NOT equal to {a, b}.
I forget the standard construction of this, but it doesn't really matter in this case.
The point is that although it is technically a set, you should think of it as its own thing with its own rules.
(a, b) is typically not going to be equal to (b, a), whereas {a, b} = {b, a}, for example.
Is'nt {a, {a, b}} a common construction?
That way the second element of ordered pair is the one that contains the other element need to go a level deeper, not trying to explain it 😛
Something like that, yeah. It doesn't really matter.
I can't remember ever using the fact that f is injective iff it has left-inverse and similar for surjective/right-inverse
what are some applications of this little proposition?
if i have a class of 50, of x boys and y girls, 30<x<40
I want to split the class into smaller groups of 5 that are preferably more gender balanced, so ratio of 3:2 between genders is best, 4:1 is less desirable, 5:0 is worst.
Is it correct to say that even in the best case scenario ill still need x-30 groups with ratio of 4:1
This is such a broad question that the simple and obvious examples are probably escaping me right now, but some very random stuff that just came to me without thinking about it much:
- [left-invertible -> injective] If one defines the naturals (up to unique iso) as a triple (N, 0 \in N, s : N -> N) for which there is a unique homomorphism to any other such triple then one can prove that s is injective (one of peano's axioms) by constructing a predecessor function (which is the left-inverse of s),
- [surjective -> right-invertible] Surjections are essentially the same thing as partitions, in particular you could construct a right-inverse to a quotient map [-] : A -> A/~ which picks representatives out of each equivalence class.
You can combine one direction of one theorem with the converse of the other theorem to get two corollaries:
- (i) [injective -> left-invertible + right-invertible -> surjective] If there exists an injection from X to Y (with X nonempty) then there exists a surjection going the other way,
- (ii) [surjective -> right-invertible + left-invertible -> injective] If there exists a surjection from X to Y then there exists an injection going the other way.
These two essentially allow you to go back-and-forth between two notions of what it means for a set to have cardinality less than or equal to another set (remember that |X| \leq |Y| iff there is an injection from X to Y). The latter (ii) is also known as the partition principle.
One example where (classical) mathematicians often implicitly use (i) is in the proof that |A| < |P(A)|. That |A| \leq |P(A)| is clear since {-} is an injection, showing that |P(A)| \leq |A| does not hold boils down to showing that there can be no injection from P(A) to A. But using the contrapositive of (i) with X = P(A) (which is nonempty) and Y = A tells them that it would be sufficient to instead show that there is no surjection from A to P(A), which is precisely the statement of Cantor's theorem.
Other than that, I would consider neither of these propositions to really be that innocent. That every left-invertible function is injective (and similarly for right-invertible and surjective) is easy to prove and unremarkable, but neither of the converses are that uncontroversial.
Every surjection having a right-inverse is famously equivalent to choice. This shouldn't come as a surprise if one identifies surjections with partitions since then this proposition essentially reads that every partition on a set has a choice function. Whether (ii) implies choice is a still open question.
Meanwhile in constructive mathematics, the proposition that every injection (out of an inhabited set) has a left-inverse, proposition (i) and the law of excluded middle are all equivalent. So a constructivist would even reject the preceeding proof that |A| < |P(A)| (though there are ways to prove this constructively).
Every surjection having a right-inverse is famously equivalent to choice
oh wow, interesting!
Alluffi actually skipped over it somehow (probably bc he decided to use naive set theory ):
wait, abt the second example
did u really mean just pick a representative from each eq class?
that might not be a function, right?
Why wouldn't it be?
length of period of a rational number (2 and 5 dont divide denominator and denominator isnt 1) is the order of 10 modulo the denominator right?
check the axioms
But correct me if im wrong, isn't one of the axioms of a field that each element in the field has a a number such that adding it to the number makes it equal 0?

