結果

問題 No.2959 Dolls' Tea Party
ユーザー sasa8uyauyasasa8uyauya
提出日時 2024-11-08 23:42:58
言語 PyPy3
(7.3.15)
結果
TLE  
実行時間 -
コード長 8,719 bytes
コンパイル時間 360 ms
コンパイル使用メモリ 82,048 KB
実行使用メモリ 153,444 KB
最終ジャッジ日時 2024-11-08 23:44:21
合計ジャッジ時間 82,477 ms
ジャッジサーバーID
（参考情報） 		judge5 / judge1
このコードへのチャレンジ
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テストケース

テストケース表示
入力 結果 実行時間
実行使用メモリ
testcase_00 AC 90 ms
83,072 KB
testcase_01 AC 92 ms
83,968 KB
testcase_02 AC 91 ms
83,584 KB
testcase_03 AC 104 ms
88,576 KB
testcase_04 AC 92 ms
83,968 KB
testcase_05 AC 92 ms
83,840 KB
testcase_06 AC 2,647 ms
150,472 KB
testcase_07 AC 2,865 ms
152,532 KB
testcase_08 AC 2,702 ms
150,976 KB
testcase_09 TLE -
testcase_10 TLE -
testcase_11 TLE -
testcase_12 TLE -
testcase_13 TLE -
testcase_14 AC 2,760 ms
151,908 KB
testcase_15 AC 2,768 ms
153,444 KB
testcase_16 TLE -
testcase_17 TLE -
testcase_18 TLE -
testcase_19 TLE -
testcase_20 TLE -
testcase_21 AC 2,912 ms
149,768 KB
testcase_22 AC 2,937 ms
149,512 KB
testcase_23 AC 2,926 ms
149,640 KB
testcase_24 AC 90 ms
82,944 KB
testcase_25 AC 89 ms
83,072 KB
testcase_26 AC 90 ms
83,328 KB
testcase_27 AC 2,717 ms
132,740 KB
testcase_28 AC 2,736 ms
132,792 KB
testcase_29 AC 2,751 ms
147,016 KB
testcase_30 AC 2,637 ms
144,800 KB
testcase_31 AC 2,633 ms
145,064 KB
testcase_32 AC 2,577 ms
145,360 KB
testcase_33 AC 2,705 ms
147,896 KB
testcase_34 AC 2,667 ms
147,516 KB
testcase_35 AC 2,710 ms
148,276 KB
testcase_36 AC 2,583 ms
145,200 KB
権限があれば一括ダウンロードができます

ソースコード

diff # 

# FFT
# code from: https://atcoder.jp/contests/practice2/submissions/24974537
# but changed a little
_fft_mod = 998244353
_fft_imag = 911660635
_fft_iimag = 86583718
_fft_rate2 = (911660635, 509520358, 369330050, 332049552, 983190778, 123842337, 238493703, 975955924, 603855026, 856644456, 131300601, 842657263, 730768835, 942482514, 806263778, 151565301, 510815449, 503497456, 743006876, 741047443, 56250497, 867605899)
_fft_irate2 = (86583718, 372528824, 373294451, 645684063, 112220581, 692852209, 155456985, 797128860, 90816748, 860285882, 927414960, 354738543, 109331171, 293255632, 535113200, 308540755, 121186627, 608385704, 438932459, 359477183, 824071951, 103369235)
_fft_rate3 = (372528824, 337190230, 454590761, 816400692, 578227951, 180142363, 83780245, 6597683, 70046822, 623238099,  183021267, 402682409, 631680428, 344509872, 689220186, 365017329, 774342554, 729444058, 102986190, 128751033, 395565204)
_fft_irate3 = (509520358, 929031873, 170256584, 839780419, 282974284, 395914482, 444904435, 72135471, 638914820, 66769500, 771127074, 985925487, 262319669, 262341272, 625870173, 768022760, 859816005, 914661783, 430819711, 272774365, 530924681)

def _butterfly(a):
	n = len(a)
	h = (n - 1).bit_length()
	len_ = 0
	while len_ < h:
		if h - len_ == 1:
			p = 1 << (h - len_ - 1)
			rot = 1
			for s in range(1 << len_):
				offset = s << (h - len_)
				for i in range(p):
					l = a[i + offset]
					r = a[i + offset + p] * rot % _fft_mod
					a[i + offset] = (l + r) % _fft_mod
					a[i + offset + p] = (l - r) % _fft_mod
				if s + 1 != (1 << len_):
					rot *= _fft_rate2[(~s & -~s).bit_length() - 1]
					rot %= _fft_mod
			len_ += 1
		else:
			p = 1 << (h - len_ - 2)
			rot = 1
			for s in range(1 << len_):
				rot2 = rot * rot % _fft_mod
				rot3 = rot2 * rot % _fft_mod
				offset = s << (h - len_)
				for i in range(p):
					a0 = a[i + offset]
					a1 = a[i + offset + p] * rot
					a2 = a[i + offset + p * 2] * rot2
					a3 = a[i + offset + p * 3] * rot3
					a1na3imag = (a1 - a3) % _fft_mod * _fft_imag
					a[i + offset] = (a0 + a2 + a1 + a3) % _fft_mod
					a[i + offset + p] = (a0 + a2 - a1 - a3) % _fft_mod
					a[i + offset + p * 2] = (a0 - a2 + a1na3imag) % _fft_mod
					a[i + offset + p * 3] = (a0 - a2 - a1na3imag) % _fft_mod
				if s + 1 != (1 << len_):
					rot *= _fft_rate3[(~s & -~s).bit_length() - 1]
					rot %= _fft_mod
			len_ += 2
 
def _butterfly_inv(a):
	n = len(a)
	h = (n - 1).bit_length()
	len_ = h
	while len_:
		if len_ == 1:
			p = 1 << (h - len_)
			irot = 1
			for s in range(1 << (len_ - 1)):
				offset = s << (h - len_ + 1)
				for i in range(p):
					l = a[i + offset]
					r = a[i + offset + p]
					a[i + offset] = (l + r) % _fft_mod
					a[i + offset + p] = (l - r) * irot % _fft_mod
				if s + 1 != (1 << (len_ - 1)):
					irot *= _fft_irate2[(~s & -~s).bit_length() - 1]
					irot %= _fft_mod
			len_ -= 1
		else:
			p = 1 << (h - len_)
			irot = 1
			for s in range(1 << (len_ - 2)):
				irot2 = irot * irot % _fft_mod
				irot3 = irot2 * irot % _fft_mod
				offset = s << (h - len_ + 2)
				for i in range(p):
					a0 = a[i + offset]
					a1 = a[i + offset + p]
					a2 = a[i + offset + p * 2]
					a3 = a[i + offset + p * 3]
					a2na3iimag = (a2 - a3) * _fft_iimag % _fft_mod
					a[i + offset] = (a0 + a1 + a2 + a3) % _fft_mod
					a[i + offset + p] = (a0 - a1 +
										 a2na3iimag) * irot % _fft_mod
					a[i + offset + p * 2] = (a0 + a1 -
											 a2 - a3) * irot2 % _fft_mod
					a[i + offset + p * 3] = (a0 - a1 -
											 a2na3iimag) * irot3 % _fft_mod
				if s + 1 != (1 << (len_ - 1)):
					irot *= _fft_irate3[(~s & -~s).bit_length() - 1]
					irot %= _fft_mod
			len_ -= 2
 
def _convolution_naive(a, b):
	n = len(a)
	m = len(b)
	ans = [0] * (n + m - 1)
	if n < m:
		for j in range(m):
			for i in range(n):
				ans[i + j] = (ans[i + j] + a[i] * b[j]) % _fft_mod
	else:
		for i in range(n):
			for j in range(m):
				ans[i + j] = (ans[i + j] + a[i] * b[j]) % _fft_mod
	return ans
 
def _convolution_fft(a, b):
	a = a.copy()
	b = b.copy()
	n = len(a)
	m = len(b)
	z = 1 << (n + m - 2).bit_length()
	a += [0] * (z - n)
	_butterfly(a)
	b += [0] * (z - m)
	_butterfly(b)
	for i in range(z):
		a[i] = a[i] * b[i] % _fft_mod
	_butterfly_inv(a)
	a = a[:n + m - 1]
	iz = pow(z, _fft_mod - 2, _fft_mod)
	for i in range(n + m - 1):
		a[i] = a[i] * iz % _fft_mod
	return a
 
 
def _convolution_square(a):
	a = a.copy()
	n = len(a)
	z = 1 << (2 * n - 2).bit_length()
	a += [0] * (z - n)
	_butterfly(a)
	for i in range(z):
		a[i] = a[i] * a[i] % _fft_mod
	_butterfly_inv(a)
	a = a[:2 * n - 1]
	iz = pow(z, _fft_mod - 2, _fft_mod)
	for i in range(2 * n - 1):
		a[i] = a[i] * iz % _fft_mod
	return a
 
 
def convolution(a, b):
	n = len(a)
	m = len(b)
	if n == 0 or m == 0:
		return []
	if min(n, m) <= 0:
		return _convolution_naive(a, b)
	if a is b:
		return _convolution_square(a)
	return _convolution_fft(a, b)
# ----

# 1/F
# 必要 : a[0] != 0
# 前提 : FFT
def poly_inv(a, length = None):
	if length == None: M = len(a)
	else: M = length
	if M <= 0: return []
	n = len(a)
	r = pow(a[0], _fft_mod-2, _fft_mod)
	m = 1
	res = [r]
	while m < M:
		f = a[:min(n,2*m)] + [0]*(2*m-min(n,2*m))
		g = res + [0]*m
		_butterfly(f)
		_butterfly(g)
		for i in range(2*m):
			f[i] = f[i] * g[i] % _fft_mod
		_butterfly_inv(f)
		f = f[m:] + [0]*m
		_butterfly(f)
		for i in range(2*m):
			f[i] = f[i] * g[i] % _fft_mod
		_butterfly_inv(f)
		iz = pow(2*m, _fft_mod-2, _fft_mod)
		iz = (-iz*iz) % _fft_mod
		for i in range(m):
			f[i] = f[i] * iz % _fft_mod
		res += f[:m]
		m <<= 1
	return res[:M]

# 多点評価
# x に評価したい点を配列で入れよう！
def multi_eval(x, a):
	n = len(x)
	siz = 1 << (n-1).bit_length()

	g = [[1] for i in range(2 * siz)]

	for i in range(n):
		g[i + siz] = [-x[i], 1]

	for i in range(siz-1, 0, -1):
		g[i] = convolution(g[2 * i], g[2 * i + 1])
	
	for i in range(1, 2 * siz):
		if i == 1: f = a[::]
		else: f = g[i >> 1]
		m = len(f) - len(g[i]) + 1
		v = convolution(f[::-1][:m], poly_inv(g[i][::-1], m))[m-1::-1]
		w = convolution(v, g[i])
		g[i] = f[::]
		h = g[i]

		for j in range(len(w)):
			h[j] -= w[j]
			h[j] %= _fft_mod
		
		while len(h) > 1 and h[-1] == 0:
			h.pop()
	
	return [g[i+siz][0] for i in range(n)]


# DEF MOD FACT
mod = _fft_mod
N = 10**6 + 5
fact = [1]*(N+1)
factinv = [1]*(N+1)

for i in range(2, N+1):
	fact[i] = fact[i-1] * i % mod

factinv[-1] = pow(fact[-1], mod-2, mod)
for i in range(N-1, 1, -1):
	factinv[i] = factinv[i+1] * (i+1) % mod

def cmb(a, b):
	if (a < b) or (b < 0): return 0
	return fact[a] * factinv[b] % mod * factinv[a-b] % mod

# log(F)
# 必要 : a[0] = 1
# 前提 : FFT, inv
def poly_log(a, length = None):
	if length == None: M = len(a)
	else: M = length
	if M <= 0: return []
	n = len(a)
	if n == 1: return [0] * M
	b = [a[i+1] * (i+1) % _fft_mod for i in range(n-1)]
	t = convolution(b, poly_inv(a, length = M))
	return [0] + [t[i] * factinv[i+1] % _fft_mod * fact[i] % _fft_mod for i in range(M-1)]

# exp(F)
# 必要 : a[0] = 0
# 前提 : FFT, inv, log
def poly_exp(a, length = None):
	if length == None: M = len(a)
	else: M = length
	if M <= 0: return []
	n = len(a)
	m = 1
	res = [1]
	while m < M:
		f = a[:min(n,2*m)] + [0]*(2*m-min(n,2*m))
		#print(res)
		v = poly_log(res, length = 2*m)
		w = [(f[i]-v[i])%_fft_mod for i in range(2*m)]
		w[0] = (w[0]+1)%_fft_mod
		g = convolution(res, w)
		res += g[m:2*m]
		m <<= 1
	return res[:M]

def poly_pow_nonzero(a, m, l):
	n = len(a)
	bais = pow(a[0], m, _fft_mod)
	invs = pow(a[0], _fft_mod-2, _fft_mod)
	r = [a[i] * invs % _fft_mod for i in range(n)]
	r = poly_log(r, length = l)
	for i in range(l):
		r[i] = r[i] * m % _fft_mod
	r = poly_exp(r, length = l)
	for i in range(l):
		r[i] = r[i] * bais % _fft_mod
	return r


def poly_pow(a, m, l):
	n = len(a)
	ind = 0
	for i in range(n):
		if a[i] != 0:
			ind = i
			break
	if ind * m >= l:
		return [0] * l
	return [0] * (ind * m) + poly_pow_nonzero(a[ind:], m, l-ind*m)

# DEF MOD FACT はされています！！6


n,K=map(int,input().split())
a=[min(K,int(x)) for x in input().split()]
M=998244353
fa=[1,1]
fb=[1,1]
for i in range(2,10**4+1):
  fa+=[fa[-1]*i%M]
  fb+=[fb[-1]*(M//i)*fb[M%i]*fa[M%i-1]*(-1)%M]
fc=lambda n,k:fa[n]*fb[k]*fb[n-k]%M if n>=k>=0 else 0
q2=[]
q3=[0]*(K+1)
for j in range(K+1):
  q3[j]=fb[j]
  q2+=[poly_log(q3)]
g=[0]*(K+1)
for i in range(1,K+1):
  if K%i==0:
    c=[0]*(K+1)
    for v in a:
      c[v//(K//i)]+=1
    q=[0]*(i+1)
    for j in range(1,i+1):
      if c[j]>0:
        for k in range(i+1):
          if k<len(q2[j]):
            q[k]+=q2[j][k]*c[j]
            q[k]%=M
    q=poly_exp(q)
    g[i]=q[i]*fa[i]%M
ans=0
from math import gcd
for i in range(K):
  ans+=g[gcd(i,K)]
  ans%=M
print(ans*pow(K,M-2,M)%M)
0