Power Digit Sum
and the sum of its digits is .
What is the sum of the digits of the number ?
Implementations
// Answer: 1366
#include <iostream>#include <vector>#include <sstream>#include <algorithm>
int power_digit_sum(size_t max){ std::vector<int> numbers; numbers.push_back(1);
std::cout << std::endl;
for (size_t i = 0; i < max; i++) { int carry = 0;
std::for_each(numbers.begin(),numbers.end(),[&carry](int& n){ n *= 2; n += carry; carry = ( n >= 10 )?1:0; n -= (carry * 10); });
if( 0 != carry ){ numbers.push_back(carry); } }
int total = 0;
for (auto itr = numbers.rbegin() ; itr != numbers.rend() ; itr++) { total += *itr; }
return total;}
#if ! defined UNITTEST_MODEint main(int argc, char const *argv[]) { std::cout << "Answer: " << power_digit_sum(15) << std::endl; std::cout << "Answer: " << power_digit_sum(1000) << std::endl; return 0;}#endif // #if ! defined UNITTEST_MODESolution Notes
Mathematical Background
This problem involves computing , a 302-digit number, and summing its digits. Direct computation with standard integer types fails since exceeds the range of 64-bit integers.
The number of digits in is approximately . For , this gives about 301.0 digits, matching the actual result.
Algorithm Analysis
Big integer multiplication by repeated doubling: Start with 1, then repeatedly multiply by 2 and handle carry when digits exceed 9. Store the number as an array of digits.
Digit-by-digit summation: Convert the final number to a string or iterate through digit array, summing each digit.
Time complexity: O(n) where n=1000 is the exponent. Space complexity: O(d) where d≈301 is the number of digits.
Key Insights
- Standard integer types cannot hold (max unsigned 64-bit is )
- Array-based arbitrary-precision arithmetic handles very large numbers
- The result has 302 digits and digit sum of 1,366
- Each doubling operation requires carry propagation through all digits
- The algorithm scales well for even larger exponents
Educational Value
This problem teaches:
- Arbitrary-precision arithmetic implementation
- Array-based number representation
- Carry propagation in multiplication
- The limitations of built-in integer types
- When custom algorithms are needed for large numbers
- Digit manipulation and summation techniques
- Exponential growth and its computational implications