Here's my code:
def last_digit(n1, n2)
array = (n1.to_i ** n2.to_i).to_s.split("")
array[-1].to_i
end
TEST: The last decimal digit of (2^200)^(2^300), which has over 10^92 decimal digits, is 6
I'm trying to return the last digit of a last number and I'm sure this correct but when I run tests 2 return as failing.
I think it's due to the numbers being too large, how do I get this code to remain accurate no matter how large it gets.
And also how do I deal with NaN, I've searched and struggled to find anything useful.
Thanks for your help.
There's an effective algorithm which assumes that only the last digit of a number being powered matters. Please, try it out on your tests and feel free to correct any flaw in this implementation that you'll find by running them
def digit_of_power(digit, n)
digit = digit % 10
case digit
when 0, 1, 5, 6 then digit
else
digit_of_square = digit * digit
if n.even?
digit_of_power(digit_of_square, n / 2)
else
digit * digit_of_power(digit_of_square, (n - 1) / 2) % 10
end
end
end
This is my solution
def last_digit(n1, n2)
return 1 if n2 == 0
return 0 if n1 == 0
exp = (n2 % 4 == 0) ? 4 : n2 % 4
return (n1**exp) % 10
end
You might want to read this article (finding the last digit of a power) for a more detailed explanation of the solution to this math problem.
Take a look at the following table:
You can see that the maximum length for cycle repetition is 4.
For instance:
2 * 2 = 4
4 * 2 = 8
8 * 2 = 16
16 * 2 = 32
32 * 2 = 64
64 * 2 = 128
128 * 2 = 256
256 * 2 = 512
The last digit in 32 is 2 ( as it is in 512), meaning that after multiplying the digit by 4, it will repeat itself.
The algorithm follows this logic:
You reduce the exponent, knowing that if it is divisible by 4, its new value is 4 because multiplying it 4 times gives you the last digit according to the table above. Otherwise, its value is n2 % 4.
As a final step you do this n1^exp % 10 because you only need the last number.
Note:
I tested it successfully with large numbers.
n1 = 38710248912497124917933333333284108412048102948908149081409204712406
n2 = 226628148126342643123641923461846128214626
By the way, I realize I am late in responding to your question. I just think it might be helpful for someone else someday.
Code
ENDINGS = [[0,0,0,0], [1,1,1,1], [2,4,8,6], [3,9,7,1], [4,6,4,6],
[5,5,5,5], [6,6,6,6], [7,9,3,1], [8,4,2,6], [9,1,9,1]]
def last_digit_of_power(digit, power)
return 1 if power.zero?
ENDINGS[digit][(power-1) % 4]
end
Examples
Let's try it for power equal to 5 and then 6.
(5..6).each do |power|
puts "\npow = #{power}"
(0..9).each {|digit| puts "#{digit}: #{last_digit_of_power(digit, power)}"}
end
pow = 5
0: 0
1: 1
2: 2
3: 3
4: 4
5: 5
6: 6
7: 7
8: 8
9: 9
pow = 6
0: 0
1: 1
2: 4
3: 9
4: 6
5: 5
6: 6
7: 9
8: 4
9: 1
Explanation
This uses the same algorithm as employed by #Igor, but I've implemented it differently. It is known (and can be easily demonstrated) that the last digit of each digit 0-9 taken to increasing powers cycles among at most 4 digits. Consider the digit 3, for example. Since
[1,2,3,4,5].map { |power| 3**power }
#=> [3, 9, 27, 81, 243]
the last digits of 3 taken to each of those 5 powers is [3, 9, 7, 1, 3]. Since the last digit of 3**5 is the same as the last digit of 3**1, we infer than the last digit of 3**6 will be the same as the last digit of 3**(6-4) (3**2), which is 9, and so on.
Now suppose we wished to calculate the last digit of 3**15. We see that it will be the same as the last digit of 3**(15-4) (3**11), which in turn will equal the last digit of 3**7 and then the last digit 3**3, but we already know the last of these, which is 7. It follows that the last digit of 3**power is
[3, 9, 7, 1][(power-1) % 4]
ENDINGS provides the last digits for powers 1-4 for each of the digits 0-9. Note the cycle length is 1 for 0, 1, 5 and 6, is 2 for 4 and 9 and is 4 for 2, 3, 7 and 8. It's most convenient, however, to use a cycle length of 4 for all 10 digits.
ENDINGS[digit] equals the four endings of digit taken to the powers of 1, 2, 3 and 4. The last digit of the digit digit taken to the power power therefore equals
ENDINGS[digit][(power-1) % 4]
Related
There is such an encoding algorithm: we're given some number x, let's say 7923. We add zeros to the end and the beginning of it - 079230. Now we sum digits, beginning from the right side - the first digit with the second, the second with the third etc. If the sum is bigger than 9, we subtract 10 from it and move 1 to the next operation.
So for the example of 079230: 0+3 = 3, 3+2=5, 2+9=11, 9+7+1=17, 7+0+1=8. Our encoded number are the results of the operations, so we end with a number: 87153.
Now, we are given the encoded number, but with one digit missing - for example 871X3. Now we need to decode it - get 7923 from it.
So shortly speaking - 871X3 is the input, the output should be 7923. Only one digit could be missing.
That is kind of weird problem for me. I guess we need to deduce somehow the original number, maybe with some backtracking? The first digit of original number could be the first digit of encoded number or that digit minus 1. But I can't see any path leading from here to the solution.
Look at your algorithm: this is merely performing long multiplication. The "encoded" number is the original times 11.
Since the multiplier is greater than 9, there can be only one possibility for the missing digit. Find it with modular arithmetic. Put in 0 as the missing digit and check:
87103 mod 11 ==> 5
Now, the "parity" of the number changes with the position. Counting from the right, even-numbered positions will return the missing digit itself (factors of 0, 99, 9999, 999999, etc. will drop out). Odd-numbered positions will give the additive inverse: subtract that digit from 11 to get the missing one. For the given example, try this for each of the digits:
87150 mod 11 ==> 8 missing digit is 3 (11-8)
87103 mod 11 ==> 5 missing digit is 5
87053 mod 11 ==> 10 missing digit is 1 (11-10)
80153 mod 11 ==> 7 missing digit is 7
7153 mod 11 ==> 3 missing digit is 8 (11-3)
say the digits of the original number are, from left to right, d,c,b,a.
0 + a mod 10 = 3, so a = 3
3 + b mod 10 = 5, so b = 2
2 + c mod 10 = 1, so c = 9
9 + 1 + d mod 10 = 7, so d = 7
7 + 1 mod 10 = 8, as expected.
Simple question but, I see exclusive and inclusive when referring to number ranges.
For example, this is a line from an algorithms book:
The following function prints the powers of 2 from 1 through n (inclusive).
What is meant by this? What makes a number range inclusive or exclusive?
In Computer Science, inclusive/exclusive doesn't apply to algorithms, but to a number range (more specifically, to the endpoint of the range):
1 through 10 (inclusive)
1 2 3 4 5 6 7 8 9 10
1 through 10 (exclusive)
1 2 3 4 5 6 7 8 9
In mathematics, the 2 ranges above would be:
[1, 10]
[1, 10)
You can remember it easily:
Inclusive - Including the last number
Exclusive - Excluding the last number
The following function prints the powers of 2 from 1 through n (inclusive).
This means that the function will compute 2^i where i = 1, 2, ..., n, in other words, i can have values from 1 up to and including the value n. i.e n is Included in Inclusive
If, on the other hand, your book had said:
The following function prints the powers of 2 from 1 through n (exclusive).
This would mean that i = 1, 2, ..., n-1, i.e. i can take values up to n-1, but not including, n, which means i = n-1 is the highest value it could have.i.e n is excluded in exclusive.
In simple terms, inclusive means within and the number n, while exclusive means within and without the number n.
Note: that each argument should be marked its "clusivity"/ "participation"
# 1 (inclusive) through 5 (inclusive)
1 <= x <= 5 == [1, 2, 3, 4, 5]
# 1 (inclusive) through 5 (exclusive)
1 <= x < 5 == [1, 2, 3, 4]
# 1 (exclusive) through 5 (inclusive)
1 < x <= 5 == [2, 3, 4, 5]
# 1 (exclusive) through 5 (exclusive)
1 < x < 5 == [2, 3, 4]
The value of n inclusive 2 and 5 [2,5]
including both the numbes in case exclusive only the first is included
programming terms n>=2 && n<=5
The value of of n exlcusive of 2 and 5 [2,5)
n>=2 && n<5
There are multiple ways to find out the same and I tried using bitwise operation as -
if(((n<<3) - n)%7 == 0 ) {
print "divide by 7";
}
Is there any other more efficient way?
As we can find if number is multiple of 3 using below algorithm -
If difference between count of odd set bits (Bits set at odd positions) and even set bits is multiple of 3 then so is the number.
Can we generalize the above algorithm for other numbers too?
So if your number is representable by a hardware-supported integer, and the hardware has a division or modulo operations, you should just use those. It is simpler, and probably faster than anything you will write. To even compete with the hardware, you must use an assembler and use other faster instructions better than the hardware manufacturers did, and without the advantage of undocumented tricks they could use but you can not.
Where this question becomes interesting is where arbitrarily large integers are involved. Modulo has some tricks for that. For instance, I can tell you that 100000000010000010000 is divisible by 3, even though my brain is a horribly slow math processor compared to a computer, because of these properties of the % modulo operator:
(a+b+c) % d = ( (a%d) + (b%d) + (c%d) ) %d
(n*a) % d = ( (a%d) + (a%d) + (a%d) +... (n times) ) %d = (n*(a%d)) %d
Now note that:
10 % 3 = 1
100 % 3 = (10 * (10%3)) % 3 = 10%3 = 1
1000 % 3 = (10 * (100%3)) %3 = 1
etc...
So that to tell if a base-10 number is divisible by 3, we simply sum the digits and see if the sum is divisible by 3
Now using the same trick with a large binary number expressed in octal or base-8 (also pointed out by #hropyatr above in comments), and using divisibility by 7, we have the special case:
8 % 7 = 1
and from that we can deduce that:
(8**N) % 7 = (8 * (8 * ( ... *( 8 * (8%7) % 7 ) % 7 ) ... %7 = 1
so that to "quickly" test divisibility by 7 of an arbitrarily large octal number, all we need to do is add up its octal base-8 digits and try dividing that by 7.
Finally, the bad news.
The code posted:
if ( (n<<3 - n) % 7 ==0 ) ... is not a good test for divisibility by 7.
because it is always yields true for any n (as pointed out by #Johnathan Leffler)
n<<3 is multiplication by 8, and will equal 8n
So for instance 6 is not divisible by 7,
but 6<<3 = 48 and 48 - 6 = 42, which is divisible by 7.
If you meant right shift if ( (n>>3 - n ) % 7 == 0 ) that doesn't work either. Test it with 49, 49//8 is 6, 6-49 is -43 and although 49 is divisible by 7, -43 is not.
The simplest test, if (n % 7 ) == 0 is your best shot until n overflows hardware, and at that point you can find a routine to represent n in octal, and sum the octal digits modulo 7.
I think if(n%7 == 0) is more efficient way to check divisibility by 7.
But if you are dealing with large numbers and can't directly do modulus operation then this might help:
A number of the form 10x + y is divisible by 7 if and only if x − 2y is divisible by 7. In other words, subtract twice the last digit from the number formed by the remaining digits. Continue to do this until a number known to be divisible by 7 is obtained. The original number is divisible by 7 if and only if the number obtained using this procedure is divisible by 7.
For example, the number 371: 37 − (2×1) = 37 − 2 = 35; 3 − (2 × 5) = 3 − 10 = −7; thus, since −7is divisible by 7, 371 is divisible by 7.
Another method is multiplication by 3. A number of the form 10x + y has the same remainder when divided by 7 as 3x + y. One must multiply the leftmost digit of the original number by 3, add the next digit, take the remainder when divided by 7, and continue from the beginning: multiply by 3, add the next digit, etc.
For example, the number 371: 3×3 + 7 = 16 remainder 2, and 2×3 + 1 = 7.
This method can be used to find the remainder of division by 7.
P.S: reference
I'm preparing for my interviews and came across this question:
Write a program to check if a number n is of x^y form. It is known that n, x and y are integers and that x and y are greater than 2.
I thought of taking log and stuff but couldn't certainly figure out how to check if the number is of the form. Could any of you please help? :)
"Taking the log and stuff" is the way to go. Note that N > 1 is never a^b for integer a and b > log_2(N). So you can check floor(N^(1/b))^b = N for each integer b between 2 and log_2(N). You have to do about log(N) many exponentiations, each of which produces a number at most the size of N.
This is far faster than #dasblinkenlight's solution, which requires you to factor N first. (No polynomial-time algorithm---that is, polynomial in the number of bits in N, is known for integer factorisation. However, integer exponentiation with a small exponent can be done in polynomial time.)
One way to solve this would be to factorize n, count the individual factors, and find the greatest common denominator of the counts. If GCD is 1, the answer is "no". Otherwise, the answer is "yes".
Here are some examples:
7, prime factor 7 (one time). We have one factor repeated once. Answer "no", because the GCD is 1.
8, prime factors 2 (3 times). We have one factor with the count of three. Answer "yes", because GCD is 3.
144, prime factors 2 (4 times) 3 (2 times). GCD of 4 and 2 is 2, so the answer is "yes".
72, prime factors 2 (3 times) 3 (2 times). GCD of 3 and 2 is 1, so the answer is "no".
There are a lot of good answers, but I see modulo arithmetics is still missing.
Depending on the magnitude of the numbers to check, it might be useful to classify them by their last bits. We can easily create a table with possible candidates.
To show how it works, let us create such a table for 4 last bits. In that case we have 16 cases to consider:
0^2, 0^3, ... : 0 mod 16
1^2, 1^3, ... : 1 mod 16
2^2, 2^3, ... : 0, 4, 8 mod 16
3^2, 3^3, ... : 9, 11, 1, 3 mod 16
4^2, 4^3, ... : 0 mod 16
5^2, 5^3, ... : 9, 13, 1, 5 mod 16
6^2, 6^3, ... : 4, 8, 0 mod 16
7^2, 7^3, ... : 1, 7 mod 16
8^2, 8^3, ... : 0 mod 16
9^2, 9^3, ... : 9, 1 mod 16
10^2,10^3, ... : 4, 8, 0 mod 16
11^2,11^3, ... : 9, 3, 1, 11 mod 16
12^2,12^3, ... : 0 mod 16
13^2,13^3, ... : 9, 5, 1, 13 mod 16
14^2,14^3, ... : 4, 8, 0 mod 16
15^2,15^3, ... : 1, 15 mod 16
The table is more useful the other way round; which bases x are possible for a given number n = x^y.
0: 0, 2, 4, 6, 8, 10, 12, 14 mod 16
1: 1, 3, 5, 7, 9, 11, 13, 15
2: -
3: 3, 11
4: 2, 6, 10, 14
5: 5, 13
6: -
7: 7
8: 2, 6, 10, 14
9: 3, 5, 9, 11, 13
10: -
11: 3, 11
12: -
13: 5, 13
14: -
15: 15
So, just by looking at the four last bits over one quarter of numbers can be discarded immediately.
If we take number 13726423, its remainder by 16 is 7, and thus if it is of the form we are interested in, it must be (16 n+7)^y.
For most numbers the number of divisors to try is quite limited. In practice, the table could me much larger, e.g., 16 bits.
A simple optimization with binary numbers is to remove the trailing zeros. This makes it unnecessary to worry about even numbers, and y must be a factor of the number of the zeros removed.
If we still have too much work, we can create another modulo table. The other could be, e.g. modulo 15. The equivalent table looks like this:
0: 0
1: 1, 2, 4, 7, 8, 11, 13, 14
2: 2, 8
3: 3, 12
4: 2, 4, 7, 8, 13
5: 5
6: 3, 6, 9, 12
7: 7, 13
8: 2, 8
9: 3, 9, 12
10: 5, 10
11: 11
12: 3, 12
13: 7, 13
14: 14
As our number from the previous example (13726423) is 13 modulo 15, then x = (15 m +7) or (15 m +13). As there are no common factors in 15 and 16, the valid numbers are 240 p + 7 and 240 p + 103. By two integer divisions and two table lookups we have managed to limit the possible values of x to 1/120 of numbers.
If the tables are largish, the number of possible x s is easy to limit to a very low number. For example, with tables of 65536 and 65535 elements the cycle is 4294901760, so for any number below approximately 1.6 x 10^19 the two tables give a short unique list of possible values of x.
If you can factor n, then it is easy to find an answer by examining the multiplicities of the factors. But the usual use for determining if a number is a perfect power is as a preliminary test for some factoring algorithms, in which case it is not realistic to find the factors of n.
The trick to determining if a number is a perfect power is to know that, if the number is a perfect power, then the exponent e must be less than log2 n, because if e is greater then 2e will be greater than n. Further, it is only necessary to test prime es, because if a number is a perfect power to a composite exponent it will also be a perfect power to the prime factors of the composite component; for instance, 215 = 32768 = 323 = 85 is a perfect cube root and also a perfect fifth root. Here is pseudocode for a function that returns b if there is some exponent e such that be = n or 0 if there is not; the function root(e,n) returns the e-th root of n:
function perfectPower(n)
for p in primes(log2(n))
b = floor(root(p,n))
if b**p == n return b
return 0
I discuss this function at my blog.
Alternatively, if factorization is too hard, you can exploit your maths library and try many values of x or y until you find one that works.
Trying for y will be less work, if you have an operation "y-th root of n" available (it could be masquerading under the name of "x to the power of 1/y"). Just try all integer values of y larger than 2 until either you find one that gives an integer answer, or the result drops below 2. If n is a standard 32-bit integer, then it will take no more than 32 attempts (and, more generally, if n is a m-bit integer, then it will take no more than m attempts).
If you do not have "y-th root of n" available, you can try all x's with the operation "log base x of n", until you get an integer answer or the result drops below 2. This will take more work since you need to check all values up until square root of x. I think it should be possible to optimize this somehow and "home in" on potential integer results.
The exponent y is easily bounded 2 ≤ y ≤ log_2(n) . Test each y in that range. If it exists, x will be the integer yth root of n.
The point is while x determines y and vice versa, the search space for y is much smaller, so you should search y rather than x (which could be as large as sqrt(n)).
How to find out the units digit of a certain number (e.g. 3 power 2011). What logic should I use to find the answer to this problem?
For base 3:
3^1 = 3
3^2 = 9
3^3 = 27
3^4 = 81
3^5 = 243
3^6 = 729
3^7 = 2187
...
That is the units digit has only 4 possibilities and then it repeats in ever the same cycle.
With the help of Euler's theorem we can show that this holds for any integer n, meaning their units digit will repeat after at most 4 consecutive exponents. Looking only at the units digit of an arbitrary product is equivalent to taking the remainder of the multiplication modulo 10, for example:
2^7 % 10 = 128 % 10 = 8
It can also be shown (and is quite intuitive) that for an arbitrary base, the units digit of any power will only depend on the units digit of the base itself - that is 2013^2013 has the same units digit as 3^2013.
We can exploit both facts to come up with an extremely fast algorithm (thanks for the help - with kind permission I may present a much faster version).
The idea is this: As we know that for any number 0-9 there will be at most 4 different outcomes, we can as well store them in a lookup table:
{ 0,0,0,0, 1,1,1,1, 6,2,4,8, 1,3,9,7, 6,4,6,4,
5,5,5,5, 6,6,6,6, 1,7,9,3, 6,8,4,2, 1,9,1,9 }
That's the possible outcomes for 0-9 in that order, grouped in fours. The idea is now for an exponentiation n^a to
first take the base mod 10 => := i
go to index 4*i in our table (it's the starting offset of that particular digit)
take the exponent mod 4 => := off (as stated by Euler's theorem we only have four possible outcomes!)
add off to 4*i to get the result
Now to make this as efficient as possible, some tweaks are applied to the basic arithmetic operations:
Multiplying by 4 is equivalent to shifting two to the left ('<< 2')
Taking a number a % 4 is equivalent to saying a&3 (masking the 1 and 2 bit, which form the remainder % 4)
The algorithm in C:
static int table[] = {
0, 0, 0, 0, 1, 1, 1, 1, 6, 2, 4, 8, 1, 3, 9, 7, 6, 4, 6, 4,
5, 5, 5, 5, 6, 6, 6, 6, 1, 7, 9, 3, 6, 8, 4, 2, 1, 9, 1, 9
};
int /* assume n>=0, a>0 */
unit_digit(int n, int a)
{
return table[((n%10)<<2)+(a&3)];
}
Proof for the initial claims
From observing we noticed that the units digit for 3^x repeats every fourth power. The claim was that this holds for any integer. But how is this actually proven? As it turns out that it's quite easy using modular arithmetic. If we are only interested in the units digit, we can perform our calculations modulo 10. It's equivalent to say the units digit cycles after 4 exponents or to say
a^4 congruent 1 mod 10
If this holds, then for example
a^5 mod 10 = a^4 * a^1 mod 10 = a^4 mod 10 * a^1 mod 10 = a^1 mod 10
that is, a^5 yields the same units digit as a^1 and so on.
From Euler's theorem we know that
a^phi(10) mod 10 = 1 mod 10
where phi(10) is the numbers between 1 and 10 that are co-prime to 10 (i.e. their gcd is equal to 1). The numbers < 10 co-prime to 10 are 1,3,7 and 9. So phi(10) = 4 and this proves that really a^4 mod 10 = 1 mod 10.
The last claim to prove is that for exponentiations where the base is >= 10 it suffices to just look at the base's units digit. Lets say our base is x >= 10, so we can say that x = x_0 + 10*x_1 + 100*x_2 + ... (base 10 representation)
Using modular representation it's easy to see that indeed
x ^ y mod 10
= (x_0 + 10*x_1 + 100*x_2 + ...) ^ y mod 10
= x_0^y + a_1 * (10*x_1)^y-1 + a_2 * (100*x_2)^y-2 + ... + a_n * (10^n) mod 10
= x_0^y mod 10
where a_i are coefficients that include powers of x_0 but finally not relevant since the whole product a_i * (10 * x_i)^y-i will be divisible by 10.
You should look at Modular exponentiation. What you want is the same of calculating n^e (mod m) with m = 10. That is the same thing as calculating the remainder of the division by ten of n^e.
You are probably interested in the Right-to-left binary method to calculate it, since it's the most time-efficient one and the easiest not too hard to implement. Here is the pseudocode, from Wikipedia:
function modular_pow(base, exponent, modulus)
result := 1
while exponent > 0
if (exponent & 1) equals 1:
result = (result * base) mod modulus
exponent := exponent >> 1
base = (base * base) mod modulus
return result
After that, just call it with modulus = 10 for you desired base and exponent and there's your answer.
EDIT: for an even simpler method, less efficient CPU-wise but more memory-wise, check out the Memory-efficient section of the article on Wikipedia. The logic is straightforward enough:
function modular_pow(base, exponent, modulus)
c := 1
for e_prime = 1 to exponent
c := (c * base) mod modulus
return c
I'm sure there's a proper mathematical way to solve this, but I would suggest that since you only care about the last digit and since in theory every number multiplied by itself repeatedly should generate a repeating pattern eventually (when looking only at the last digit), you could simply perform the multiplications until you detect the first repetition and then map your exponent into the appropriate position in the pattern that you built.
Note that because you only care about the last digit, you can further simplify things by truncating your input number down to its ones-digit before you start building your pattern mapping. This will let you to determine the last digit even for arbitrarily large inputs that would otherwise cause an overflow on the first or second multiplication.
Here's a basic example in JavaScript: http://jsfiddle.net/dtyuA/2/
function lastDigit(base, exponent) {
if (exponent < 0) {
alert("stupid user, negative values are not supported");
return 0;
}
if (exponent == 0) {
return 1;
}
var baseString = base + '';
var lastBaseDigit = baseString.substring(baseString.length - 1);
var lastDigit = lastBaseDigit;
var pattern = [];
do {
pattern.push(lastDigit);
var nextProduct = (lastDigit * lastBaseDigit) + '';
lastDigit = nextProduct.substring(nextProduct.length - 1);
} while (lastDigit != lastBaseDigit);
return pattern[(exponent - 1) % pattern.length];
};
function doMath() {
var base = parseInt(document.getElementById("base").value, 10);
var exp = parseInt(document.getElementById("exp").value, 10);
console.log(lastDigit(base, exp));
};
console.log(lastDigit(3003, 5));
Base: <input id="base" type="text" value="3" /> <br>
Exponent: <input id="exp" type="text" value="2011"><br>
<input type="button" value="Submit" onclick="doMath();" />
And the last digit in 3^2011 is 7, by the way.
We can start by inspecting the last digit of each result obtained by raising the base 10 digits to successive powers:
d d^2 d^3 d^4 d^5 d^6 d^7 d^8 d^9 (mod 10)
--- --- --- --- --- --- --- --- ---
0 0 0 0 0 0 0 0 0
1 1 1 1 1 1 1 1 1
2 4 8 6 2 4 8 6 2
3 9 7 1 3 9 7 1 3
4 6 4 6 4 6 4 6 4
5 5 5 5 5 5 5 5 5
6 6 6 6 6 6 6 6 6
7 9 3 1 7 9 3 1 7
8 4 2 6 8 4 2 6 8
9 1 9 1 9 1 9 1 9
We can see that in all cases the last digit cycles through no more than four distinct values. Using this fact, and assuming that n is a non-negative integer and p is a positive integer, we can compute the result fairly directly (e.g. in Javascript):
function lastDigit(n, p) {
var d = n % 10;
return [d, (d*d)%10, (d*d*d)%10, (d*d*d*d)%10][(p-1) % 4];
}
... or even more simply:
function lastDigit(n, p) {
return Math.pow(n % 10, (p-1) % 4 + 1) % 10;
}
lastDigit(3, 2011)
/* 7 */
The second function is equivalent to the first. Note that even though it uses exponentiation, it never works with a number larger than nine to the fourth power (6561).
The key to solving this type of question lies in Euler's theorem.
This theorem allows us to say that a^phi(m) mod m = 1 mod m, if and only if a and m are coprime. That is, a and m do not divide evenly. If this is the case, (and for your example it is), we can solve the problem on paper, without any programming what so ever.
Let's solve for the unit digit of 3^2011, as in your example. This is equivalent to 3^2011 mod 10.
The first step is to check is 3 and 10 are co-prime. They do not divide evenly, so we can use Euler's theorem.
We also need to compute what the totient, or phi value, is for 10. For 10, it is 4. For 100 phi is 40, 1000 is 4000, etc.
Using Euler's theorem, we can see that 3^4 mod 10 = 1. We can then re-write the original example as:
3^2011 mod 10 = 3^(4*502 + 3) mod 10 = 3^(4*502) mod 10 + 3^3 mod 10 = 1^502 * 3^3 mod 10 = 27 mod 10 = 7
Thus, the last digit of 3^2011 is 7.
As you saw, this required no programming whatsoever and I solved this example on a piece of scratch paper.
You ppl are making simple thing complicated.
Suppose u want to find out the unit digit of abc ^ xyz .
divide the power xyz by 4,if remainder is 1 ans is c^1=c.
if xyz%4=2 ans is unit digit of c^2.
else if xyz%4=3 ans is unit digit of c^3.
if xyz%4=0
then we need to check whether c is 5,then ans is 5
if c is even ans is 6
if c is odd (other than 5 ) ans is 1.
Bellow is a table with the power and the unit digit of 3 to that power.
0 1
1 3
2 9
3 7
4 1
5 3
6 9
7 7
Using this table you can see that the unit digit can be 1, 3, 9, 7 and the sequence repeats in this order for higher powers of 3. Using this logic you can find that the unit digit of (3 power 2011) is 7. You can use the same algorithm for the general case.
Here's a trick that works for numbers that aren't a multiple of a factor of the base (for base 10, it can't be a multiple of 2 or 5.) Let's use base 3. What you're trying to find is 3^2011 mod 10. Find powers of 3, starting with 3^1, until you find one with the last digit 1. For 3, you get 3^4=81. Write the original power as (3^4)^502*3^3. Using modular arithmetic, (3^4)^502*3^3 is congruent to (has the same last digit as) 1^502*3^3. So 3^2011 and 3^3 have the same last digit, which is 7.
Here's some pseudocode to explain it in general. This finds the last digit of b^n in base B.
// Find the smallest power of b ending in 1.
i=1
while ((b^i % B) != 1) {
i++
}
// b^i has the last digit 1
a=n % i
// For some value of j, b^n == (b^i)^j * b^a, which is congruent to b^a
return b^a % B
You'd need to be careful to prevent an infinite loop, if no power of b ends in 1 (in base 10, multiples of 2 or 5 don't work.)
Find out the repeating set in this case, it is 3,9,7,1 and it repeats in the same order for ever....so divide 2011 by 4 which will give you a reminder 3. That is the 3rd element in the repeating set. This is the easiest way to find for any given no. say if asked for 3^31, then the reminder of 31/4 is 3 and so 7 is the unit digit. for 3^9, 9/4 is 1 and so the unit will be 3. 3^100, the unit will be 1.
If you have the number and exponent separate it's easy.
Let n1 is the number and n2 is the power. And ** represents power.
assume n1>0.
% means modulo division.
pseudo code will look like this
def last_digit(n1, n2)
if n2==0 then return 1 end
last = n1%10
mod = (n2%4).zero? ? 4 : (n2%4)
last_digit = (last**mod)%10
end
Explanation:
We need to consider only the last digit of the number because that determines the last digit of the power.
it's the maths property that count of possibility of each digits(0-9) power's last digit is at most 4.
1) Now if the exponent is zero we know the last digit would be 1.
2) Get the last digit by %10 on the number(n1)
3) %4 on the exponent(n2)- if the output is zero we have to consider that as 4 because n2 can't be zero. if %4 is non zero we have to consider %4 value.
4) now we have at most 9**4. This is easy for the computer to calculate.
take the %10 on that number. You have the last digit.