Identifying all the 1s in a sea of 0s












2












$begingroup$


I have an $N$-length binary string, the total number of 1s in the string is D. Assume N is much larger than D. Also, D is fairly larger than 1. (For example, N=1000, D=40).



Now, my aim is to find all the 1s in this string with a minimal number of tests.



Could someone suggest any classical methods or existing algorithms addressing such problems?



What constitutes a test:



Tests can be observing the output of a binary operation on a set of bits in the string. (Eg: XOR of randomly picked 5 bits, Boolean sum( OR) of 3 bit sets...)



I would also like to know what are the best method if my test only constitutes finding if any of the digits in a chosen set of digits is 1.










share|cite|improve this question











$endgroup$








  • 5




    $begingroup$
    What kinds of "test" are allowed?
    $endgroup$
    – Hagen von Eitzen
    Jan 16 at 19:24










  • $begingroup$
    If the $1$s are uniformly distributed, I doubt you can do any better than checking each bit one by one.
    $endgroup$
    – Jam
    Jan 16 at 19:25






  • 2




    $begingroup$
    Is checking whether a string contains only zeros one test? That would suggest repeatedly splitting a nonzero string and checking its two parts.
    $endgroup$
    – timtfj
    Jan 16 at 19:35






  • 1




    $begingroup$
    ...or checking the total number $k$ (i.e., sum) of $1$s in a substring another test? If so, then split each substring into $k+1$ substrings and iterate...
    $endgroup$
    – David G. Stork
    Jan 16 at 20:10








  • 2




    $begingroup$
    If each test can only reveal 1 bit of information, it seems like it is impossible to do better than $D$ tests and, without knowing $D$, would require $N$ tests. If $D=1$, then a binary search seems optimal, which is $O(log N)$. Maybe there is an information-theoretic argument to at least get a similar kind of lower bound for general $D$, though the bound may not be optimal?
    $endgroup$
    – Aaron
    Jan 16 at 21:01
















2












$begingroup$


I have an $N$-length binary string, the total number of 1s in the string is D. Assume N is much larger than D. Also, D is fairly larger than 1. (For example, N=1000, D=40).



Now, my aim is to find all the 1s in this string with a minimal number of tests.



Could someone suggest any classical methods or existing algorithms addressing such problems?



What constitutes a test:



Tests can be observing the output of a binary operation on a set of bits in the string. (Eg: XOR of randomly picked 5 bits, Boolean sum( OR) of 3 bit sets...)



I would also like to know what are the best method if my test only constitutes finding if any of the digits in a chosen set of digits is 1.










share|cite|improve this question











$endgroup$








  • 5




    $begingroup$
    What kinds of "test" are allowed?
    $endgroup$
    – Hagen von Eitzen
    Jan 16 at 19:24










  • $begingroup$
    If the $1$s are uniformly distributed, I doubt you can do any better than checking each bit one by one.
    $endgroup$
    – Jam
    Jan 16 at 19:25






  • 2




    $begingroup$
    Is checking whether a string contains only zeros one test? That would suggest repeatedly splitting a nonzero string and checking its two parts.
    $endgroup$
    – timtfj
    Jan 16 at 19:35






  • 1




    $begingroup$
    ...or checking the total number $k$ (i.e., sum) of $1$s in a substring another test? If so, then split each substring into $k+1$ substrings and iterate...
    $endgroup$
    – David G. Stork
    Jan 16 at 20:10








  • 2




    $begingroup$
    If each test can only reveal 1 bit of information, it seems like it is impossible to do better than $D$ tests and, without knowing $D$, would require $N$ tests. If $D=1$, then a binary search seems optimal, which is $O(log N)$. Maybe there is an information-theoretic argument to at least get a similar kind of lower bound for general $D$, though the bound may not be optimal?
    $endgroup$
    – Aaron
    Jan 16 at 21:01














2












2








2





$begingroup$


I have an $N$-length binary string, the total number of 1s in the string is D. Assume N is much larger than D. Also, D is fairly larger than 1. (For example, N=1000, D=40).



Now, my aim is to find all the 1s in this string with a minimal number of tests.



Could someone suggest any classical methods or existing algorithms addressing such problems?



What constitutes a test:



Tests can be observing the output of a binary operation on a set of bits in the string. (Eg: XOR of randomly picked 5 bits, Boolean sum( OR) of 3 bit sets...)



I would also like to know what are the best method if my test only constitutes finding if any of the digits in a chosen set of digits is 1.










share|cite|improve this question











$endgroup$




I have an $N$-length binary string, the total number of 1s in the string is D. Assume N is much larger than D. Also, D is fairly larger than 1. (For example, N=1000, D=40).



Now, my aim is to find all the 1s in this string with a minimal number of tests.



Could someone suggest any classical methods or existing algorithms addressing such problems?



What constitutes a test:



Tests can be observing the output of a binary operation on a set of bits in the string. (Eg: XOR of randomly picked 5 bits, Boolean sum( OR) of 3 bit sets...)



I would also like to know what are the best method if my test only constitutes finding if any of the digits in a chosen set of digits is 1.







combinatorics estimation hypothesis-testing






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Jan 16 at 20:41







Jyotish Robin

















asked Jan 16 at 19:21









Jyotish RobinJyotish Robin

1355




1355








  • 5




    $begingroup$
    What kinds of "test" are allowed?
    $endgroup$
    – Hagen von Eitzen
    Jan 16 at 19:24










  • $begingroup$
    If the $1$s are uniformly distributed, I doubt you can do any better than checking each bit one by one.
    $endgroup$
    – Jam
    Jan 16 at 19:25






  • 2




    $begingroup$
    Is checking whether a string contains only zeros one test? That would suggest repeatedly splitting a nonzero string and checking its two parts.
    $endgroup$
    – timtfj
    Jan 16 at 19:35






  • 1




    $begingroup$
    ...or checking the total number $k$ (i.e., sum) of $1$s in a substring another test? If so, then split each substring into $k+1$ substrings and iterate...
    $endgroup$
    – David G. Stork
    Jan 16 at 20:10








  • 2




    $begingroup$
    If each test can only reveal 1 bit of information, it seems like it is impossible to do better than $D$ tests and, without knowing $D$, would require $N$ tests. If $D=1$, then a binary search seems optimal, which is $O(log N)$. Maybe there is an information-theoretic argument to at least get a similar kind of lower bound for general $D$, though the bound may not be optimal?
    $endgroup$
    – Aaron
    Jan 16 at 21:01














  • 5




    $begingroup$
    What kinds of "test" are allowed?
    $endgroup$
    – Hagen von Eitzen
    Jan 16 at 19:24










  • $begingroup$
    If the $1$s are uniformly distributed, I doubt you can do any better than checking each bit one by one.
    $endgroup$
    – Jam
    Jan 16 at 19:25






  • 2




    $begingroup$
    Is checking whether a string contains only zeros one test? That would suggest repeatedly splitting a nonzero string and checking its two parts.
    $endgroup$
    – timtfj
    Jan 16 at 19:35






  • 1




    $begingroup$
    ...or checking the total number $k$ (i.e., sum) of $1$s in a substring another test? If so, then split each substring into $k+1$ substrings and iterate...
    $endgroup$
    – David G. Stork
    Jan 16 at 20:10








  • 2




    $begingroup$
    If each test can only reveal 1 bit of information, it seems like it is impossible to do better than $D$ tests and, without knowing $D$, would require $N$ tests. If $D=1$, then a binary search seems optimal, which is $O(log N)$. Maybe there is an information-theoretic argument to at least get a similar kind of lower bound for general $D$, though the bound may not be optimal?
    $endgroup$
    – Aaron
    Jan 16 at 21:01








5




5




$begingroup$
What kinds of "test" are allowed?
$endgroup$
– Hagen von Eitzen
Jan 16 at 19:24




$begingroup$
What kinds of "test" are allowed?
$endgroup$
– Hagen von Eitzen
Jan 16 at 19:24












$begingroup$
If the $1$s are uniformly distributed, I doubt you can do any better than checking each bit one by one.
$endgroup$
– Jam
Jan 16 at 19:25




$begingroup$
If the $1$s are uniformly distributed, I doubt you can do any better than checking each bit one by one.
$endgroup$
– Jam
Jan 16 at 19:25




2




2




$begingroup$
Is checking whether a string contains only zeros one test? That would suggest repeatedly splitting a nonzero string and checking its two parts.
$endgroup$
– timtfj
Jan 16 at 19:35




$begingroup$
Is checking whether a string contains only zeros one test? That would suggest repeatedly splitting a nonzero string and checking its two parts.
$endgroup$
– timtfj
Jan 16 at 19:35




1




1




$begingroup$
...or checking the total number $k$ (i.e., sum) of $1$s in a substring another test? If so, then split each substring into $k+1$ substrings and iterate...
$endgroup$
– David G. Stork
Jan 16 at 20:10






$begingroup$
...or checking the total number $k$ (i.e., sum) of $1$s in a substring another test? If so, then split each substring into $k+1$ substrings and iterate...
$endgroup$
– David G. Stork
Jan 16 at 20:10






2




2




$begingroup$
If each test can only reveal 1 bit of information, it seems like it is impossible to do better than $D$ tests and, without knowing $D$, would require $N$ tests. If $D=1$, then a binary search seems optimal, which is $O(log N)$. Maybe there is an information-theoretic argument to at least get a similar kind of lower bound for general $D$, though the bound may not be optimal?
$endgroup$
– Aaron
Jan 16 at 21:01




$begingroup$
If each test can only reveal 1 bit of information, it seems like it is impossible to do better than $D$ tests and, without knowing $D$, would require $N$ tests. If $D=1$, then a binary search seems optimal, which is $O(log N)$. Maybe there is an information-theoretic argument to at least get a similar kind of lower bound for general $D$, though the bound may not be optimal?
$endgroup$
– Aaron
Jan 16 at 21:01










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