XOR properties in set of numbers

Say I have n positive numbers A1,A2...An and Ak is minimum among them. And d is a number such that (A1-d) ⊕ (A2-d) ⊕ .......(An-1-d) ⊕ (An-d) = 0 where0<=d <= Ak.

I want to know how many d are there . I know I can iterate all possible value of d and take XOR of n number every time and find out but complexity in this case is O(Ak∗n) which is O(n2) in worst case.

Is their any property of XOR which can help us to find number of d in less complexity than this ?

Edit :
Eq: If n=4 and numbers are = 4 6 8 10 then d can be {0,3}as 4 ⊕ 6 ⊕ 8 ⊕ 10 =0and 1 ⊕ 3 ⊕ 5 ⊕ 7 =0

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So is this bitwise XOR? If so, you can do this in O(n) by shifting and bitwise AND-ing. – H2CO3 Oct 22 '12 at 17:45
The xor is commutative, associative and self-inverse. – Jan Dvorak Oct 22 '12 at 17:45
@H2CO3 2 XOR 3 = 1 and 1 XOR 2 = 3 – tesla Oct 22 '12 at 17:48
@H2CO3 I cannot see how – Jan Dvorak Oct 22 '12 at 17:48
Looks similar to stackoverflow.com/questions/12655593/… (yes I know they are completely different questions). – kennytm Oct 22 '12 at 18:13

You can figure out the possible values of d one bit at a time. Consider the equation mod 2:

(A1-d) ⊕ (A2-d) ⊕ .......(A{n-1}-d) ⊕ (An-d) = 0 mod 2


Try 0 and 1 for d, see if either works. Say d==1 is the only assignment that works. Then try the values 1 and 3 in the equation:

(A1-d) ⊕ (A2-d) ⊕ .......(A{n-1}-d) ⊕ (An-d) = 0 mod 4


and so on, taking all valid ds mod 2^i and trying both d and d+2^i mod 2^{i+1}. The reason why this works is that both subtraction and xor do not propagate any information from higher bits to lower bits, so if you find a solution to the mod 2 equation, it remains a solution no matter what the higher-order bits of d are set to.

The running time should be something like O(n * log Ak * #of solutions).

Example:

A = {9,12,23,30}
try d=0,1 mod 2.  Both work.
try d=0,1,2,3 mod 4.  All work.
try d=[0-7] mod 8.  1,3,5,7 work.
try d=[1,9,3,5,7] mod 16. 3,7 work. (no need to check if d>Ak)
now we've tried up to Ak, check the remaining solutions for the remaining
high-order bits.  3 and 7 work.


Example:

A = {4,6,8,10}
try d=0,1 mod 2.  Both work.
try d=0,1,2,3 mod 4.  All work.
try d=0,4,1,2,3 mod 8.  All work.
at this point you've tried all d up to Ak.  Do a final check and 0,3,4 work.

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The original problem is a counting problem. I was hoping for an output-insensitive algorithm. Still, this might be the optimal algorithm for enumeration. +1 – Jan Dvorak Oct 22 '12 at 19:20
The time complexity is not O(log Ak * #d), more like O(log Ak * #d * n) - you have to include the time needed to calculate the XORs. You might be able to reach O(log Ak * #d + n). – Jan Dvorak Oct 22 '12 at 19:25
True, there's an n in there also, I'll add it. – Keith Randall Oct 22 '12 at 19:26
I also conjencture it is possible to reach O(log Ak + #d + n) by finding one solution and generating each next solution in constant time. – Jan Dvorak Oct 22 '12 at 19:29