# Why does it matter at what point I replace?

I need to find four orthogonal linear combinations of complicated functions, that vanish at four different points.

I use (LK4 is defined below, but its shape should have nothing to do with my problem)

NMinimize[LK4[{a, b, c, d}, I, 0, 0, 0, 0], {a, b, c, d}]

and get a result, as replacement rule (using MachinePrecision)

{3.3493*10^-17, {a -> 2.34594, b -> -1.80385, c -> 2.51873, d -> 0.2406}}

Now if I create a vector for these coefficients

P1 = {a, b, c, d}/.%[]

and call the function with this vector I get a different result than by replacing directly in the function call:

LK4[{a, b, c, d}, I, 0, 0, 0, 0]/.%%[] returns 3.3493*10^-17, while LK4[P1, I, 0, 0, 0, 0] returns 0.373542.

What's worse is that LK4[({a, b, c, d}/.%%%%[]), 0, 0, 0, 0] also returns the inaccurate result 0.373542.

What I wanted to do is find a linear combination that minimizes at the first spot, then define a coefficient vector from that and minimize at the second spot with the constraint that the coefficient vector has to be orthogonal to the first. LK4[{a, b, c, d}, tau, xi1, xi2, x, y] normalizes the coefficient vector btw.

How can I get Mathematica to assign appropriately precise values upon using the replacement rule?

I tried setting the precision to 100 instead of MachinePrecision, but with the very same results.

Definition of LK4:

    Phi[j_, qM_, x_, y_, tau_, xi1_, xi2_] :=
Surd[2 qM Im[tau]/Abs[tau]^2, 4] Exp[
I 2 Pi (xi1 x + xi2 y)]  Exp[- Pi I Conjugate[tau]/Abs[tau]^2 (
j^2/qM + qM x^2) +
2 Pi I j Conjugate[tau]/Abs[tau]^2 (x + tau y)] *
N[EllipticTheta[3,
Pi Conjugate[tau]/Abs[tau]^2 (qM (x + tau y) - j),
Exp[ -Pi I Conjugate[tau]/Abs[tau]^2 qM]], 20];
PhiEven[j_, qM_, x_, y_, tau_, xi1_, xi2_] :=
Phi[j, qM, x, y, tau, xi1, xi2] /; j == 0;
PhiEven[j_, qM_, x_, y_, tau_, xi1_, xi2_] :=
Phi[j, qM, x, y, tau, xi1, xi2] /;
qM/2 \[Element] Integers && j == qM/2;
PhiEven[j_, qM_, x_, y_, tau_, xi1_, xi2_] :=
1/Sqrt (Phi[j, qM, x, y, tau, xi1, xi2] +
Phi[qM - j, qM, x, y, tau, xi1, xi2]);
PhiOdd[j_, qM_, x_, y_, tau_, xi1_, xi2_] :=
1/Sqrt (Phi[j, qM, x, y, tau, xi1, xi2] -
Phi[qM - j, qM, x, y, tau, xi1, xi2]) /; j != 0 && j != qM/2;
LK4[coeff_, tau_, xi1_, xi2_, x_, y_] :=
Sum[coeff[[a]]/(Sqrt@Total[coeff^2]) PhiEven[a - 1, 6, x, y, tau,
xi1, xi2], {a, 1, 4}];

• What is the definition of f? – Mr.Wizard May 8 '15 at 9:56
• updated the post with the lengthy definition – Neuneck May 8 '15 at 10:05
• Your LK4 function takes 6 arguments, whereas the f function in your example only takes three, a vector and two numbers. Those don't seem consistent. Can you explain further? – MarcoB May 8 '15 at 23:21
• As I tried to explain abobe the last block of code, f is LK4 with tau = i and xi1 = xi2 = 0. – Neuneck May 9 '15 at 13:45

## 1 Answer

Look at

LK4[{a, b, c, d}, I, 0, 0, 0, 0] What has happened is that the a in the argument {a, b, c, d} has been replaced by {1, 2, 3, 4} in the Sum[..., {a, 1, 4}] code in the definition of LK4.

If you change the definition of LK4 to use a different iterator, you get consistent results:

LK4[coeff_, tau_, xi1_, xi2_, x_, y_] :=
Sum[coeff[[a1]]/(Sqrt@Total[coeff^2]) PhiEven[a1 - 1, 6, x, y, tau, xi1, xi2],
{a1, 1, 4}]


This happens because, according to the docs, Sum effectively uses Block to "localize" the iterator variable a. This means that any instances of a in the expression of the (evaluated) summand, such as an a in coeff argument {a, b, c, d}, will be replaced by 1, 2, etc.

• Geez, this is embarrasing... Thank you! – Neuneck May 11 '15 at 11:44
• @Neuneck You're welcome. It can be a convenient side-effect of Sum, Table, etc., but easy to overlook since it is hidden from view. If (1) the vector coeff is always real and (2) you make PhiEven have the Attribute Listable, then you can define LK4 by Normalize[coeff] . PhiEven[Range[0, 3], 6, x, y, tau, xi1, xi2] without introducing a iterator to trap you. Alternatively, you could use Total and Map: Total[coeff[[#]]/(Sqrt@Total[coeff^2]) PhiEven[# - 1, 6, x, y, tau, xi1, xi2] & /@ Range]. – Michael E2 May 11 '15 at 12:51
• That idea with Total works amazingly well! I generalized the definitions even and everything works as intended. +100 :P – Neuneck May 11 '15 at 13:06
• @Neuneck, Thank you for the bonus. Best – Michael E2 May 19 '15 at 11:52