I have a unitary Matrix which consists of Complex coefficients like A, B C etc
I want to have a complex repres. For A like A = a0* Exp (i Phi) and saying that a0 is real and positiv.
I tried the Assumption option but everytime it doesn't work when i try to look at ComplexConj(A) * A - i alwayd get sth like a0 * Conjugate a0 but it should be a0^2.
Can you please help me?
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I'm puzzled by what I think is a mistake in a partial derivative I'm having Mathematica do for me.
Specifically, this is what I have:
Derivative I'd like to take
I'm trying to take the partial derivative of the following w.r.t. the variable θ (apologies for the formatting):
f=(1/4)(-4e((1+θ)/2)ψ+eN((1+θ)/2)ψ+eN((1+θ)/2-θd)ψ)-s
But the solution Mathematica produces seems very different from the one I get when I take the derivative myself. While Mathematica says the partial derivative of f w.r.t. θ is:
(1/4)eψ(N-2)
By hand, I get and am quite confident the correct answer is instead:
(1/4)eψ(N(1-d)-2)
That is, Mathematica is producing something that drops the variable d when it is differentiating. I've explored different functions that take a derivative in Mathematica, and the possibility that maybe some of the variables I'm using (such as d) might be protected or otherwise special, but I can't say that I know why the answer's so off. This is the first time in the notebook that d appears, so it is not set to 0. For context, I'm trying to confirm that the derivative of the function is positive for values of the variables in certain ranges, and we have d>0 and d<(1/2). Doing this all by hand works but I'm trying to confirm with Mathematica as I will be dealing with more complicated functions and need to make sure I'm having Mathematica produce the right derivatives.
Your didn't add spaces in eN and θd, so it thinks they're some other 2-character variables.
Adding spaces between them gives your expected result:
f[θ,e,N,ψ,d,s] = (1/4) (-4 e ((1+θ)/2) ψ + e N ((1+θ)/2) ψ + e N ((1+θ)/2 - θ d) ψ) - s;
D[f[θ, e, N, ψ, d, s], θ] // FullSimplify
(* 1/4 e (-2 + N - d N) ψ *)
I'm following this paper to implement and Attentive Pooling Network to build a Question Answering system. In chapter 2.1, it speaks about the CNN layer:
where q_emb is a question where each token (word) has been embedded using word2vec. q_emb has shape (d, M). d is the dimension of the word embedding and M the length of the question. In a similar way, a_emb is the embedding of the answer with shape (d, L).
My question is: how is the convolution done and how is it possible that W_1 and b_1 are the same for both the operations? In my opinion at least b_1 should have a different dimension in each case (and it should be a matrix, not a vector....).
At the moment I've implemented this operation in PyTorch:
### Input is a tensor of shape (batch_size, 1, M or L, d*k)
conv2 = nn.Conv2d(1, c, (d*k, 1))
I find that the authors of the paper are trusting the readers to assume/figure out a lot of things here. From what I read, here is what I could gather:
W1 should be a 1 X dk matrix because that is the only shape that would make sense in order to get Q as c X M matrix.
Assuming this, b1 need not be an matrix. From the above, you could get a c X 1 X M matrix which could be reshaped to c X M matrix easily and b1 could be a c X 1 vector which could be broadcasted and added to the rest of the matrix.
Since, c, d and k are hyper parameters, you could easily have the same W1 and b1 for both Q and A.
This is what I think so far, I will re read and edit in case anythings amiss.
I'm doing matrix math in Go using mat64. I have a matrix equation I want to solve, something like: (a * b + c) / (d - e) where a, b, c, d, and e are all matrices with real numbers as elements.
mat64 implements matrix math functions as methods. So, if you wanted to multiply matrix a by b, you'd do something like:
// Multiply a by b:
new := mat64.NewDense(x, y, nil)
new.Mul(a, b)
However, this method becomes unwieldy when you're looking at more complex equations with a whole bunch of steps such as my example above.
So, is there any way to invoke these routines (or methods in Go in general) without using receivers, forcing me to create a boatload of temporary matrices in order to solve a more complex equation, or am I stuck doing this the ugly way?
I hope this hasn't been asked before, if so I apologize.
EDIT: For clarity, the following notation will be used: boldface uppercase for matrices, boldface lowercase for vectors, and italics for scalars.
Suppose x0 is a vector, A and B are matrix functions, and f is a vector function.
I'm looking for the best way to do the following iteration scheme in Mathematica:
A0 = A(x0), B0=B(x0), f0 = f(x0)
x1 = Inverse(A0)(B0.x0 + f0)
A1 = A(x1), B1=B(x1), f1 = f(x1)
x2 = Inverse(A1)(B1.x1 + f1)
...
I know that a for-loop can do the trick, but I'm not quite familiar with Mathematica, and I'm concerned that this is the most efficient way to do it. This is a justified concern as I would like to define a function u(N):=xNand use it in further calculations.
I guess my questions are:
What's the most efficient way to program the scheme?
Is RecurrenceTable a way to go?
EDIT
It was a bit more complicated than I tought. I'm providing more details in order to obtain a more thorough response.
Before doing the recurrence, I'm having problems understanding how to program the functions A, B and f.
Matrices A and B are functions of the time step dt = 1/T and the space step dx = 1/M, where T and M are the number of points in the {0 < x < 1, 0 < t} region. This is also true for vector the function f.
The dependance of A, B and f on x is rather tricky:
A and B are upper and lower triangular matrices (like a tridiagonal matrix; I suppose we can call them multidiagonal), with defined constant values on their diagonals.
Given a point 0 < xs < 1, I need to determine it's representative xn in the mesh (the closest), and then substitute the nth row of A and B with the function v( x) (transposed, of course), and the nth row of f with the function w( x).
Summarizing, A = A(dt, dx, xs, x). The same is true for B and f.
Then I need do the loop mentioned above, to define u( x) = step[T].
Hope I've explained myself.
I'm not sure if it's the best method, but I'd just use plain old memoization. You can represent an individual step as
xstep[x_] := Inverse[A[x]](B[x].x + f[x])
and then
u[0] = x0
u[n_] := u[n] = xstep[u[n-1]]
If you know how many values you need in advance, and it's advantageous to precompute them all for some reason (e.g. you want to open a file, use its contents to calculate xN, and then free the memory), you could use NestList. Instead of the previous two lines, you'd do
xlist = NestList[xstep, x0, 10];
u[n_] := xlist[[n]]
This will break if n > 10, of course (obviously, change 10 to suit your actual requirements).
Of course, it may be worth looking at your specific functions to see if you can make some algebraic simplifications.
I would probably write a function that accepts A0, B0, x0, and f0, and then returns A1, B1, x1, and f1 - say
step[A0_?MatrixQ, B0_?MatrixQ, x0_?VectorQ, f0_?VectorQ] := Module[...]
I would then Nest that function. It's hard to be more precise without more precise information.
Also, if your procedure is numerical, then you certainly don't want to compute Inverse[A0], as this is not a numerically stable operation. Rather, you should write
A0.x1 == B0.x0+f0
and then use a numerically stable solver to find x1. Of course, Mathematica's LinearSolve provides such an algorithm.
I'm trying to parse a string in a self-made language into a sort of tree, e.g.:
# a * b1 b2 -> c * d1 d2 -> e # f1 f2 * g
should result in:
# a
* b1 b2
-> c
* d1 d2
-> e
# f1 f2
* g
#, * and -> are symbols. a, b1, etc. are texts.
Since the moment I know only rpn method to evaluate expressions, and my current solution is as follows. If I allow only a single text token after each symbol I can easily convert expression first into RPN notation (b = b1 b2; d = d1 d2; f = f1 f2) and parse it from here:
a b c -> * d e -> * # f g * #
However, merging text tokens and whatever else comes seems to be problematic. My idea was to create marker tokens (M), so RPN looks like:
a M b2 b1 M c -> * M d2 d1 M e -> * # f2 f1 M g * #
which is also parseable and seems to solve the problem.
That said:
Does anyone have experience with something like that and can say it is or it is not a viable solution for the future?
Are there better methods for parsing expressions with undefined arity of operators?
Can you point me at some good resources?
Note. Yes, I know this example very much resembles Lisp prefix notation and maybe the way to go would be to add some brackets, but I don't have any experience here. However, the source text must not contain any artificial brackets and also I'm not sure what to do about potential infix mixins like # a * b -> [if value1 = value2] c -> d.
Thanks for any help.
EDIT: It seems that what I'm looking for are sources on postfix notation with a variable number of arguments.
I couldn't fully understand your question, but it seems what you want is a grammar definition and a parser generator. I suggest you take a look at ANTLR, it should be pretty straightforward with it to define a grammar for either your original syntax or the RPN.
Edit: (After exercising self-criticism, and making some effort to understand the question details.) Actually, the language grammar is unclear from your example. However, it seems to me, that the advantages of the prefix/postfix notations (i.e. that you need neither parentheses nor a precedence-aware parser) stem from the fact that you know the number of arguments every time you encounter an operator, therefore you know exactly how many elements to read (for prefix notation) or to pop from the stack (for postfix notation). OTOH, I beleive that having operators which can have variable number of arguments makes prefix/postfix notations not simply difficult to parse but outright ambiguous. Take the following expression for example:
# a * b c d
Which of the following three is the canonical form?
(a, *(b, c, d))
(a, *(b, c), d)
(a, *(b), c, d)
Without knowing more about the operators, it is impossible to tell. Of course you could define some sort of greedyness of the operators, e.g. * is greedier than #, so it gobbles up all the arguments. But this would beat the purpose of a prefix notation, because you simply wouldn't be able to write down the second variant from the above three; not without additinonal syntactic elements.
Now that I think of it, it is probably not by sheer chance that none of the programming languages I know support operators with a variable number of arguments, only functions/procedures.