#!/usr/bin/python3 -O

from math import sqrt, log2, ceil, floor, gcd
import random
import sys
from builtins import ValueError


"""This script factorises a natural number given as a command line
parameter into its prime factors. It first attempts to use trial
division to find very small factors, then uses Brent's version of the
Pollard rho algorithm [1] to find slightly larger factors. If any large
factors remain, it uses the Self-Initializing Quadratic Sieve (SIQS) [2]
to factorise those.
[1] Brent, Richard P. 'An improved Monte Carlo factorization algorithm.'
    BIT Numerical Mathematics 20.2 (1980): 176-184.
[2] Contini, Scott Patrick. 'Factoring integers with the self-
    initializing quadratic sieve.' (1997).
"""

# Some tuning parameters
MAX_DIGITS_POLLARD = 30
POLLARD_QUICK_ITERATIONS = 20
MIN_DIGITS_POLLARD_QUICK2 = 45
POLLARD_QUICK2_ITERATIONS = 25
SIQS_TRIAL_DIVISION_EPS = 25
SIQS_MIN_PRIME_POLYNOMIAL = 400
SIQS_MAX_PRIME_POLYNOMIAL = 4000

# Number of iterations for the Miller-Rabin primality test
MILLER_RABIN_ITERATIONS = 50


class Polynomial:
    """A polynomial used for the Self-Initializing Quadratic Sieve."""

    def __init__(self, coeff=[], a=None, b=None):
        self.coeff = coeff
        self.a = a
        self.b = b

    def eval(self, x):
        res = 0
        for a in self.coeff[::-1]:
            res *= x
            res += a
        return res


class FactorBasePrime:
    """A factor base prime for the Self-Initializing Quadratic Sieve."""

    def __init__(self, p, tmem, lp):
        self.p = p
        self.soln1 = None
        self.soln2 = None
        self.tmem = tmem
        self.lp = lp
        self.ainv = None


def lowest_set_bit(a):
    b = (a & -a)
    low_bit = -1
    while (b):
        b >>= 1
        low_bit += 1
    return low_bit


def to_bits(k):
    """Return a generator that returns the bits of k, starting from the
    least significant bit, using True for 1s, and False for 0s.
    """
    k_binary = bin(k)[2:]
    return (bit == '1' for bit in k_binary[::-1])


def pow_mod(a, k, m):
    """Return a^k mod m."""
    r = 1
    b = a
    for bit in to_bits(k):
        if bit:
            r = (r * b) % m
        b = (b * b) % m
    return r


def is_quadratic_residue(a, p):
    """Return whether a is a quadratic residue modulo a prime p."""
    return legendre(a, (p - 1) // 2, 1, p) == 1


def legendre(a, q, l, n):
    x = q ** l
    if x == 0:
        return 1

    z = 1
    a %= n

    while x != 0:
        if x % 2 == 0:
            a = (a ** 2) % n
            x //= 2
        else:
            x -= 1
            z = (z * a) % n
    return z


def sqrt_mod_prime(a, p):
    """Return the square root of a modulo the prime p. Behaviour is
    undefined if a is not a quadratic residue mod p."""
    # Algorithm from http://www.mersennewiki.org/index.php/Modular_Square_Root
    assert a < p
    assert is_probable_prime(p)
    if a == 0:
        return 0
    if p == 2:
        return a
    if p % 2 == 0:
        return None
    p_mod_8 = p % 8
    if p_mod_8 == 1:
        # Shanks method
        q = p // 8
        e = 3
        while q % 2 == 0:
            q //= 2
            e += 1
        while True:
            x = random.randint(2, p - 1)
            z = pow_mod(x, q, p)
            if pow_mod(z, 2 ** (e - 1), p) != 1:
                break
        y = z
        r = e
        x = pow_mod(a, (q - 1) // 2, p)
        v = (a * x) % p
        w = (v * x) % p
        while True:
            if w == 1:
                return v
            k = 1
            while pow_mod(w, 2 ** k, p) != 1:
                k += 1
            d = pow_mod(y, 2 ** (r - k - 1), p)
            y = (d ** 2) % p
            r = k
            v = (d * v) % p
            w = (w * y) % p
    elif p_mod_8 == 5:
        v = pow_mod(2 * a, (p - 5) // 8, p)
        i = (2 * a * v * v) % p
        return (a * v * (i - 1)) % p
    else:
        return pow_mod(a, (p + 1) // 4, p)


def inv_mod(a, m):
    """Return the modular inverse of a mod m."""
    return eea(a, m)[0] % m


def eea(a, b):
    """Solve the equation a*x + b*y = gcd(a,b).
    Return (x, y, +/-gcd(a,b)).
    """
    if a == 0:
        return (0, 1, b)
    x = eea(b % a, a)
    return (x[1] - b // a * x[0], x[0], x[2])


def is_probable_prime(a):
    """Perform the Miller-Rabin primality test to determine whether the
    given number a is a prime. Return True if the number is a prime
    with very high probability, and False if it is definitely composite.
    """
    if a == 2:
        return True
    if a == 1 or a % 2 == 0:
        return False
    return primality_test_miller_rabin(a, MILLER_RABIN_ITERATIONS)


def primality_test_miller_rabin(a, iterations):
    m = a - 1
    lb = lowest_set_bit(m)
    m >>= lb

    for _ in range(iterations):
        b = random.randint(2, a - 1)
        j = 0
        z = pow_mod(b, m, a)
        while not ((j == 0 and z == 1) or z == a - 1):
            if (j > 0 and z == 1 or j + 1 == lb):
                return False
            j += 1
            z = (z * z) % a

    return True


def siqs_factor_base_primes(n, nf):
    """Compute and return nf factor base primes suitable for a Quadratic
    Sieve on the number n.
    """
    global small_primes
    factor_base = []
    for p in small_primes:
        if is_quadratic_residue(n, p):
            t = sqrt_mod_prime(n % p, p)
            lp = round(log2(p))
            factor_base.append(FactorBasePrime(p, t, lp))
            if len(factor_base) >= nf:
                break
    return factor_base


def siqs_find_first_poly(n, m, factor_base):
    """Compute the first of a set of polynomials for the Self-
    Initialising Quadratic Sieve.
    """
    p_min_i = None
    p_max_i = None
    for i, fb in enumerate(factor_base):
        if p_min_i is None and fb.p >= SIQS_MIN_PRIME_POLYNOMIAL:
            p_min_i = i
        if p_max_i is None and fb.p > SIQS_MAX_PRIME_POLYNOMIAL:
            p_max_i = i - 1
            break

    # The following may happen if the factor base is small, make sure
    # that we have enough primes.
    if p_max_i is None:
        p_max_i = len(factor_base) - 1
    if p_min_i is None or p_max_i - p_min_i < 20:
        p_min_i = min(p_min_i, 5)

    target = sqrt(2 * float(n)) / m
    target1 = target / ((factor_base[p_min_i].p + 
                         factor_base[p_max_i].p) / 2) ** 0.5

    # find q such that the product of factor_base[q_i] is approximately
    # sqrt(2 * n) / m; try a few different sets to find a good one
    best_q, best_a, best_ratio = None, None, None
    for _ in range(30): 
        a = 1
        q = []

        while a < target1:
            p_i = 0
            while p_i == 0 or p_i in q:
                p_i = random.randint(p_min_i, p_max_i)
            p = factor_base[p_i].p
            a *= p
            q.append(p_i)

        ratio = a / target

        # ratio too small seems to be not good
        if (best_ratio is None or (ratio >= 0.9 and ratio < best_ratio) or
                    best_ratio < 0.9 and ratio > best_ratio):
            best_q = q
            best_a = a
            best_ratio = ratio
    a = best_a
    q = best_q

    s = len(q)
    B = []
    for l in range(s):
        fb_l = factor_base[q[l]]
        q_l = fb_l.p
        assert a % q_l == 0
        gamma = (fb_l.tmem * inv_mod(a // q_l, q_l)) % q_l
        if gamma > q_l // 2:
            gamma = q_l - gamma
        B.append(a // q_l * gamma)

    b = sum(B) % a
    b_orig = b
    if (2 * b > a):
        b = a - b

    assert 0 < b
    assert 2 * b <= a
    assert ((b * b - n) % a == 0)

    g = Polynomial([b * b - n, 2 * a * b, a * a], a, b_orig)
    h = Polynomial([b, a])
    for fb in factor_base:
        if a % fb.p != 0:
            fb.ainv = inv_mod(a, fb.p)
            fb.soln1 = (fb.ainv * (fb.tmem - b)) % fb.p
            fb.soln2 = (fb.ainv * (-fb.tmem - b)) % fb.p

    return g, h, B


def siqs_find_next_poly(n, factor_base, i, g, B):
    """Compute the (i+1)-th polynomials for the Self-Initialising
    Quadratic Sieve, given that g is the i-th polynomial.
    """
    v = lowest_set_bit(i) + 1
    z = -1 if ceil(i / (2 ** v)) % 2 == 1 else 1
    b = (g.b + 2 * z * B[v - 1]) % g.a
    a = g.a
    b_orig = b
    if (2 * b > a):
        b = a - b
    assert ((b * b - n) % a == 0)

    g = Polynomial([b * b - n, 2 * a * b, a * a], a, b_orig)
    h = Polynomial([b, a])
    for fb in factor_base:
        if a % fb.p != 0:
            fb.soln1 = (fb.ainv * (fb.tmem - b)) % fb.p
            fb.soln2 = (fb.ainv * (-fb.tmem - b)) % fb.p

    return g, h


def siqs_sieve(factor_base, m):
    """Perform the sieving step of the SIQS. Return the sieve array."""
    sieve_array = [0] * (2 * m + 1)
    for fb in factor_base:
        if fb.soln1 is None:
            continue
        p = fb.p
        i_start_1 = -((m + fb.soln1) // p)
        a_start_1 = fb.soln1 + i_start_1 * p
        lp = fb.lp
        if p > 20:
            for a in range(a_start_1 + m, 2 * m + 1, p):
                sieve_array[a] += lp

            i_start_2 = -((m + fb.soln2) // p)
            a_start_2 = fb.soln2 + i_start_2 * p
            for a in range(a_start_2 + m, 2 * m + 1, p):
                sieve_array[a] += lp
    return sieve_array


def siqs_trial_divide(a, factor_base):
    """Determine whether the given number a can be fully factorised into
    primes from the factors base. If so, return the indices of the
    factors from the factor base. If not, return None.
    """
    divisors_idx = []
    for i, fb in enumerate(factor_base):
        if a % fb.p == 0:
            exp = 0
            while a % fb.p == 0:
                a //= fb.p
                exp += 1
            divisors_idx.append((i, exp))
        if a == 1:
            return divisors_idx
    return None


def siqs_trial_division(n, sieve_array, factor_base, smooth_relations, g, h, m,
                        req_relations):
    """Perform the trial division step of the Self-Initializing
    Quadratic Sieve.
    """
    sqrt_n = sqrt(float(n))
    limit = log2(m * sqrt_n) - SIQS_TRIAL_DIVISION_EPS
    for (i, sa) in enumerate(sieve_array):
        if sa >= limit:
            x = i - m
            gx = g.eval(x)
            divisors_idx = siqs_trial_divide(gx, factor_base)
            if divisors_idx is not None:
                u = h.eval(x)
                v = gx
                assert (u * u) % n == v % n
                smooth_relations.append((u, v, divisors_idx))
                if (len(smooth_relations) >= req_relations):
                    return True
    return False


def siqs_build_matrix(factor_base, smooth_relations):
    """Build the matrix for the linear algebra step of the Quadratic Sieve."""
    fb = len(factor_base)
    M = []
    for sr in smooth_relations:
        mi = [0] * fb
        for j, exp in sr[2]:
            mi[j] = exp % 2
        M.append(mi)
    return M


def siqs_build_matrix_opt(M):
    """Convert the given matrix M of 0s and 1s into a list of numbers m
    that correspond to the columns of the matrix.
    The j-th number encodes the j-th column of matrix M in binary:
    The i-th bit of m[i] is equal to M[i][j].
    """
    m = len(M[0])
    cols_binary = [""] * m
    for mi in M:
        for j, mij in enumerate(mi):
            cols_binary[j] += "1" if mij else "0"
    return [int(cols_bin[::-1], 2) for cols_bin in cols_binary], len(M), m


def add_column_opt(M_opt, tgt, src):
    """For a matrix produced by siqs_build_matrix_opt, add the column
    src to the column target (mod 2).
    """
    M_opt[tgt] ^= M_opt[src]


def find_pivot_column_opt(M_opt, j):
    """For a matrix produced by siqs_build_matrix_opt, return the row of
    the first non-zero entry in column j, or None if no such row exists.
    """
    if M_opt[j] == 0:
        return None
    return lowest_set_bit(M_opt[j])


def siqs_solve_matrix_opt(M_opt, n, m):
    """
    Perform the linear algebra step of the SIQS. Perform fast
    Gaussian elimination to determine pairs of perfect squares mod n.
    Use the optimisations described in [1].
    [1] Koç, Çetin K., and Sarath N. Arachchige. 'A Fast Algorithm for
        Gaussian Elimination over GF (2) and its Implementation on the
        GAPP.' Journal of Parallel and Distributed Computing 13.1
        (1991): 118-122.
    """
    row_is_marked = [False] * n
    pivots = [-1] * m
    for j in range(m):
        i = find_pivot_column_opt(M_opt, j)
        if i is not None:
            pivots[j] = i
            row_is_marked[i] = True
            for k in range(m):
                if k != j and (M_opt[k] >> i) & 1:  # test M[i][k] == 1
                    add_column_opt(M_opt, k, j)
    perf_squares = []
    for i in range(n):
        if not row_is_marked[i]:
            perfect_sq_indices = [i]
            for j in range(m):
                if (M_opt[j] >> i) & 1:  # test M[i][j] == 1
                    perfect_sq_indices.append(pivots[j])
            perf_squares.append(perfect_sq_indices)
    return perf_squares


def siqs_calc_sqrts(square_indices, smooth_relations):
    """Given on of the solutions returned by siqs_solve_matrix_opt and
    the corresponding smooth relations, calculate the pair [a, b], such
    that a^2 = b^2 (mod n).
    """
    res = [1, 1]
    for idx in square_indices:
        res[0] *= smooth_relations[idx][0]
        res[1] *= smooth_relations[idx][1]
    res[1] = sqrt_int(res[1])
    return res


def sqrt_int(n):
    """Return the square root of the given integer, rounded down to the
    nearest integer.
    """
    a = n
    s = 0
    o = 1 << (floor(log2(n)) & ~1)
    while o != 0:
        t = s + o
        if a >= t:
            a -= t
            s = (s >> 1) + o
        else:
            s >>= 1
        o >>= 2
    assert s * s == n
    return s


def kth_root_int(n, k):
    """Return the k-th root of the given integer n, rounded down to the
    nearest integer.
    """
    u = n
    s = n + 1
    while u < s:
        s = u
        t = (k - 1) * s + n // pow(s, k - 1)
        u = t // k
    return s


def siqs_factor_from_square(n, square_indices, smooth_relations):
    """Given one of the solutions returned by siqs_solve_matrix_opt,
    return the factor f determined by f = gcd(a - b, n), where
    a, b are calculated from the solution such that a*a = b*b (mod n).
    Return f, a factor of n (possibly a trivial one).
    """
    sqrt1, sqrt2 = siqs_calc_sqrts(square_indices, smooth_relations)
    assert (sqrt1 * sqrt1) % n == (sqrt2 * sqrt2) % n
    return gcd(abs(sqrt1 - sqrt2), n)


def siqs_find_factors(n, perfect_squares, smooth_relations):
    """Perform the last step of the Self-Initialising Quadratic Field.
    Given the solutions returned by siqs_solve_matrix_opt, attempt to
    identify a number of (not necessarily prime) factors of n, and
    return them.
    """
    factors = []
    rem = n
    non_prime_factors = set()
    prime_factors = set()
    for square_indices in perfect_squares:
        fact = siqs_factor_from_square(n, square_indices, smooth_relations)
        if fact != 1 and fact != rem:
            if is_probable_prime(fact):
                if fact not in prime_factors:
                    prime_factors.add(fact)

                while rem % fact == 0:
                    factors.append(fact)
                    rem //= fact

                if rem == 1:
                    break
                if is_probable_prime(rem):
                    factors.append(rem)
                    rem = 1
                    break
            else:
                if fact not in non_prime_factors:
                    non_prime_factors.add(fact)

    if rem != 1 and non_prime_factors:
        non_prime_factors.add(rem)
        for fact in sorted(siqs_find_more_factors_gcd(non_prime_factors)):
            while fact != 1 and rem % fact == 0:
                factors.append(fact)
                rem //= fact
            if rem == 1 or is_probable_prime(rem):
                break

    if rem != 1:
        factors.append(rem)
    return factors


def siqs_find_more_factors_gcd(numbers):
    res = set()
    for n in numbers:
        res.add(n)
        for m in numbers:
            if n != m:
                fact = gcd(n, m)
                if fact != 1 and fact != n and fact != m:
                    if fact not in res:
                        res.add(fact)
                    res.add(n // fact)
                    res.add(m // fact)
    return res


def siqs_choose_nf_m(d):
    """Choose parameters nf (sieve of factor base) and m (for sieving
    in [-m,m].
    """
    # Using similar parameters as msieve-1.52
    if d <= 34:
        return 200, 65536
    if d <= 36:
        return 300, 65536
    if d <= 38:
        return 400, 65536
    if d <= 40:
        return 500, 65536
    if d <= 42:
        return 600, 65536
    if d <= 44:
        return 700, 65536
    if d <= 48:
        return 1000, 65536
    if d <= 52:
        return 1200, 65536
    if d <= 56:
        return 2000, 65536 * 3
    if d <= 60:
        return 4000, 65536 * 3
    if d <= 66:
        return 6000, 65536 * 3
    if d <= 74:
        return 10000, 65536 * 3
    if d <= 80:
        return 30000, 65536 * 3
    if d <= 88:
        return 50000, 65536 * 3
    if d <= 94:
        return 60000, 65536 * 9
    return 100000, 65536 * 9


def siqs_factorise(n):
    """Use the Self-Initializing Quadratic Sieve algorithm to identify
    one or more non-trivial factors of the given number n. Return the
    factors as a list.
    """
    dig = len(str(n))
    nf, m = siqs_choose_nf_m(dig)

    factor_base = siqs_factor_base_primes(n, nf)

    required_relations_ratio = 1.05
    success = False
    smooth_relations = []
    prev_cnt = 0
    i_poly = 0
    while not success:
        required_relations = round(len(factor_base) * required_relations_ratio)
        enough_relations = False
        while not enough_relations:
            if i_poly == 0:
                g, h, B = siqs_find_first_poly(n, m, factor_base)
            else:
                g, h = siqs_find_next_poly(n, factor_base, i_poly, g, B)
            i_poly += 1
            if i_poly >= 2 ** (len(B) - 1):
                i_poly = 0
            sieve_array = siqs_sieve(factor_base, m)
            enough_relations = siqs_trial_division(
                n, sieve_array, factor_base, smooth_relations,
                g, h, m, required_relations)

            if (len(smooth_relations) >= required_relations or
                i_poly % 8 == 0 and len(smooth_relations) > prev_cnt):
                prev_cnt = len(smooth_relations)

        M = siqs_build_matrix(factor_base, smooth_relations)
        M_opt, M_n, M_m = siqs_build_matrix_opt(M)

        perfect_squares = siqs_solve_matrix_opt(M_opt, M_n, M_m)

        factors = siqs_find_factors(n, perfect_squares, smooth_relations)
        if len(factors) > 1:
            success = True
        else:
            required_relations_ratio += 0.05

    return factors


def check_factor(n, i, factors):
    while n % i == 0:
        n //= i
        factors.append(i)
        if is_probable_prime(n):
            factors.append(n)
            n = 1
    return n


def trial_div_init_primes(n, upper_bound):
    """Perform trial division on the given number n using all primes up
    to upper_bound. Initialise the global variable small_primes with a
    list of all primes <= upper_bound. Return (factors, rem), where
    factors is the list of identified prime factors of n, and rem is the
    remaining factor. If rem = 1, the function terminates early, without
    fully initialising small_primes.
    """
    global small_primes
    is_prime = [True] * (upper_bound + 1)
    is_prime[0:2] = [False] * 2
    factors = []
    small_primes = []
    max_i = sqrt_int(upper_bound)
    rem = n
    for i in range(2, max_i + 1):
        if is_prime[i]:
            small_primes.append(i)
            rem = check_factor(rem, i, factors)
            if rem == 1:
                return factors, 1

            for j in (range(i ** 2, upper_bound + 1, i)):
                is_prime[j] = False

    for i in range(max_i + 1, upper_bound + 1):
        if is_prime[i]:
            small_primes.append(i)
            rem = check_factor(rem, i, factors)
            if rem == 1:
                return factors, 1

    return factors, rem


def pollard_brent_f(c, n, x):
    """Return f(x) = (x^2 + c)%n. Assume c < n.
    """
    x1 = (x * x) % n + c
    if x1 >= n:
        x1 -= n
    assert x1 >= 0 and x1 < n
    return x1


def pollard_brent_find_factor(n, max_iter=None):
    """Perform Brent's variant of the Pollard rho factorisation
    algorithm to attempt to a non-trivial factor of the given number n.
    If max_iter > 0, return None if no factors were found within
    max_iter iterations.
    """
    y, c, m = (random.randint(1, n - 1) for _ in range(3))
    r, q, g = 1, 1, 1
    i = 0
    while g == 1:
        x = y
        for _ in range(r):
            y = pollard_brent_f(c, n, y)
        k = 0
        while k < r and g == 1:
            ys = y
            for _ in range(min(m, r - k)):
                y = pollard_brent_f(c, n, y)
                q = (q * abs(x - y)) % n
            g = gcd(q, n)
            k += m
        r *= 2
        if max_iter:
            i += 1
            if (i == max_iter):
                return None

    if g == n:
        while True:
            ys = pollard_brent_f(c, n, ys)
            g = gcd(abs(x - ys), n)
            if g > 1:
                break
    return g


def pollard_brent_quick(n, factors):
    """Perform up to max_iter iterations of Brent's variant of the
    Pollard rho factorisation algorithm to attempt to find small
    prime factors. Restart the algorithm each time a factor was found.
    Add all identified prime factors to factors, and return 1 if all
    prime factors were found, or otherwise the remaining factor.
    """
    rem = n
    while True:
        if is_probable_prime(rem):
            factors.append(rem)
            rem = 1
            break

        digits = len(str(n))
        if digits < MIN_DIGITS_POLLARD_QUICK2:
            max_iter = POLLARD_QUICK_ITERATIONS
        else:
            max_iter = POLLARD_QUICK2_ITERATIONS

        f = pollard_brent_find_factor(rem, max_iter)
        if f and f < rem:
            if is_probable_prime(f):
                factors.append(f)
                assert rem % f == 0
                rem //= f
            else:
                rem_f = pollard_brent_quick(f, factors)
                rem = (rem // f) * rem_f
        else:
            break
    return rem


def check_perfect_power(n):
    """Check if the given integer is a perfect power. If yes, return
    (r, b) such that r^b == n. If no, return None. Assume that
    global small_primes has already been initialised and that n does
    not have any prime factors from small_primes.
    """
    largest_checked_prime = small_primes[-1]
    for b in small_primes:
        bth_root = kth_root_int(n, b)
        if bth_root < largest_checked_prime:
            break
        if (bth_root ** b == n):
            return (bth_root, b)
    return None


def find_prime_factors(n):
    """Return one or more prime factors of the given number n. Assume
    that n is not a prime and does not have very small factors, and that
    the global small_primes has already been initialised. Do not return
    duplicate factors.
    """
    perfect_power = check_perfect_power(n)
    if perfect_power:
        factors = [perfect_power[0]]
    else:
        digits = len(str(n))
        if digits <= MAX_DIGITS_POLLARD:
            factors = [pollard_brent_find_factor(n)]
        else:
            factors = siqs_factorise(n)

    prime_factors = []
    for f in set(factors):
        for pf in find_all_prime_factors(f):
            prime_factors.append(pf)

    return prime_factors


def find_all_prime_factors(n):
    """Return all prime factors of the given number n. Assume that n
    does not have very small factors and that the global small_primes
    has already been initialised.
    """
    rem = n
    factors = []

    while rem > 1:
        if is_probable_prime(rem):
            factors.append(rem)
            break

        for f in find_prime_factors(rem):
            assert is_probable_prime(f)
            assert rem % f == 0
            while rem % f == 0:
                rem //= f
                factors.append(f)

    return factors


def product(factors):
    """Return the product of all numbers in the given list."""
    prod = 1
    for f in factors:
        prod *= f
    return prod


def factorise(n):
    """Factorise the given integer n >= 1 into its prime factors."""

    if type(n) != int or n < 1:
        raise ValueError("Number needs to be an integer >= 1")

    if n == 1:
        return []

    if is_probable_prime(n):
        return [n]

    factors, rem = trial_div_init_primes(n, 1000000)


    if rem != 1:
        digits = len(str(rem))
        if digits > MAX_DIGITS_POLLARD:
            
            rem = pollard_brent_quick(rem, factors)
        if rem > 1:
            for fr in find_all_prime_factors(rem):
                factors.append(fr)

    factors.sort()
    assert product(factors) == n
    for p in factors:
        assert is_probable_prime(p)
    return factors


if __name__ == '__main__':
    x=int(input())
    l=list(map(int,input().strip().split()))
    cnt2 = sum(l)
    #print(l)
    for N in l:
        #print(N)
        for i in factorise(N):
            #print(i)
            N = N//i
            cnt2 += N
    print(cnt2)