結果

問題 No.2936 Sum of Square of Mex
ユーザー vwxyzvwxyz
提出日時 2024-10-12 16:47:51
言語 PyPy3
(7.3.15)
結果
WA  
実行時間 -
コード長 18,488 bytes
コンパイル時間 194 ms
コンパイル使用メモリ 82,308 KB
実行使用メモリ 109,312 KB
最終ジャッジ日時 2024-10-12 16:48:11
合計ジャッジ時間 9,719 ms
ジャッジサーバーID
(参考情報)
judge2 / judge4
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 44 ms
56,960 KB
testcase_01 AC 45 ms
56,832 KB
testcase_02 AC 126 ms
81,032 KB
testcase_03 WA -
testcase_04 AC 46 ms
57,216 KB
testcase_05 AC 46 ms
57,600 KB
testcase_06 AC 45 ms
57,216 KB
testcase_07 WA -
testcase_08 AC 351 ms
104,064 KB
testcase_09 WA -
testcase_10 AC 223 ms
91,932 KB
testcase_11 WA -
testcase_12 AC 228 ms
93,440 KB
testcase_13 WA -
testcase_14 WA -
testcase_15 AC 324 ms
101,736 KB
testcase_16 AC 373 ms
109,000 KB
testcase_17 AC 395 ms
109,312 KB
testcase_18 AC 376 ms
109,312 KB
testcase_19 AC 368 ms
109,312 KB
testcase_20 AC 395 ms
109,140 KB
testcase_21 AC 369 ms
109,184 KB
testcase_22 AC 369 ms
109,056 KB
testcase_23 AC 404 ms
109,184 KB
testcase_24 WA -
testcase_25 WA -
testcase_26 AC 389 ms
108,848 KB
testcase_27 AC 405 ms
109,312 KB
testcase_28 AC 388 ms
109,248 KB
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ソースコード

diff #

def Extended_Euclid(n,m):
    stack=[]
    while m:
        stack.append((n,m))
        n,m=m,n%m
    if n>=0:
        x,y=1,0
    else:
        x,y=-1,0
    for i in range(len(stack)-1,-1,-1):
        n,m=stack[i]
        x,y=y,x-(n//m)*y
    return x,y

class MOD:
    def __init__(self,p,e=None):
        self.p=p
        self.e=e
        if self.e==None:
            self.mod=self.p
        else:
            self.mod=self.p**self.e

    def Pow(self,a,n):
        a%=self.mod
        if n>=0:
            return pow(a,n,self.mod)
        else:
            #assert math.gcd(a,self.mod)==1
            x=Extended_Euclid(a,self.mod)[0]
            return pow(x,-n,self.mod)

    def Build_Fact(self,N):
        assert N>=0
        self.factorial=[1]
        if self.e==None:
            for i in range(1,N+1):
                self.factorial.append(self.factorial[-1]*i%self.mod)
        else:
            self.cnt=[0]*(N+1)
            for i in range(1,N+1):
                self.cnt[i]=self.cnt[i-1]
                ii=i
                while ii%self.p==0:
                    ii//=self.p
                    self.cnt[i]+=1
                self.factorial.append(self.factorial[-1]*ii%self.mod)
        self.factorial_inve=[None]*(N+1)
        self.factorial_inve[-1]=self.Pow(self.factorial[-1],-1)
        for i in range(N-1,-1,-1):
            ii=i+1
            while ii%self.p==0:
                ii//=self.p
            self.factorial_inve[i]=(self.factorial_inve[i+1]*ii)%self.mod

    def Build_Inverse(self,N):
        self.inverse=[None]*(N+1)
        assert self.p>N
        self.inverse[1]=1
        for n in range(2,N+1):
            if n%self.p==0:
                continue
            a,b=divmod(self.mod,n)
            self.inverse[n]=(-a*self.inverse[b])%self.mod

    def Inverse(self,n):
        return self.inverse[n]

    def Fact(self,N):
        if N<0:
            return 0
        retu=self.factorial[N]
        if self.e!=None and self.cnt[N]:
            retu*=pow(self.p,self.cnt[N],self.mod)%self.mod
            retu%=self.mod
        return retu

    def Fact_Inve(self,N):
        if self.e!=None and self.cnt[N]:
            return None
        return self.factorial_inve[N]

    def Comb(self,N,K,divisible_count=False):
        if K<0 or K>N:
            return 0
        retu=self.factorial[N]*self.factorial_inve[K]%self.mod*self.factorial_inve[N-K]%self.mod
        if self.e!=None:
            cnt=self.cnt[N]-self.cnt[N-K]-self.cnt[K]
            if divisible_count:
                return retu,cnt
            else:
                retu*=pow(self.p,cnt,self.mod)
                retu%=self.mod
        return retu
#mod = 998244353
imag = 911660635
iimag = 86583718
rate2 = (911660635, 509520358, 369330050, 332049552, 983190778, 123842337, 238493703, 975955924, 603855026, 856644456, 131300601,
              842657263, 730768835, 942482514, 806263778, 151565301, 510815449, 503497456, 743006876, 741047443, 56250497, 867605899)
irate2 = (86583718, 372528824, 373294451, 645684063, 112220581, 692852209, 155456985, 797128860, 90816748, 860285882, 927414960,
               354738543, 109331171, 293255632, 535113200, 308540755, 121186627, 608385704, 438932459, 359477183, 824071951, 103369235)
rate3 = (372528824, 337190230, 454590761, 816400692, 578227951, 180142363, 83780245, 6597683, 70046822, 623238099,
              183021267, 402682409, 631680428, 344509872, 689220186, 365017329, 774342554, 729444058, 102986190, 128751033, 395565204)
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 % mod
                    a[i + offset] = (l + r) % mod
                    a[i + offset + p] = (l - r) % mod
                if s + 1 != 1 << len_:
                    rot *= rate2[(~s & -~s).bit_length() - 1]
                    rot %= mod
            len_ += 1
        else:
            p = 1 << (h - len_ - 2)
            rot = 1
            for s in range(1 << len_):
                rot2 = rot * rot % mod
                rot3 = rot2 * rot % 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) % mod * imag
                    a[i + offset] = (a0 + a2 + a1 + a3) % mod
                    a[i + offset + p] = (a0 + a2 - a1 - a3) % mod
                    a[i + offset + p * 2] = (a0 - a2 + a1na3imag) % mod
                    a[i + offset + p * 3] = (a0 - a2 - a1na3imag) % mod
                if s + 1 != 1 << len_:
                    rot *= rate3[(~s & -~s).bit_length() - 1]
                    rot %= 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) % mod
                    a[i + offset + p] = (l - r) * irot % mod
                if s + 1 != (1 << (len_ - 1)):
                    irot *= irate2[(~s & -~s).bit_length() - 1]
                    irot %= mod
            len_ -= 1
        else:
            p = 1 << (h - len_)
            irot = 1
            for s in range(1 << (len_ - 2)):
                irot2 = irot * irot % mod
                irot3 = irot2 * irot % 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) * iimag % mod
                    a[i + offset] = (a0 + a1 + a2 + a3) % mod
                    a[i + offset + p] = (a0 - a1 + a2na3iimag) * irot % mod
                    a[i + offset + p * 2] = (a0 + a1 - a2 - a3) * irot2 % mod
                    a[i + offset + p * 3] = (a0 - a1 - a2na3iimag) * irot3 % mod
                if s + 1 != (1 << (len_ - 2)):
                    irot *= irate3[(~s & -~s).bit_length() - 1]
                    irot %= 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]) % mod
    else:
        for i in range(n):
            for j in range(m):
                ans[i + j] = (ans[i + j] + a[i] * b[j]) % mod
    return ans

def convolution_ntt(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] % mod
    butterfly_inv(a)
    a = a[:n + m - 1]
    iz = pow(z, mod - 2, mod)
    for i in range(n + m - 1):
        a[i] = a[i] * iz % 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] % mod
    butterfly_inv(a)
    a = a[:2 * n - 1]
    iz = pow(z, mod - 2, mod)
    for i in range(2 * n - 1):
        a[i] = a[i] * iz % mod
    return a

def convolution(a, b):
    """It calculates (+, x) convolution in mod 998244353. 
    Given two arrays a[0], a[1], ..., a[n - 1] and b[0], b[1], ..., b[m - 1], 
    it calculates the array c of length n + m - 1, defined by

    >   c[i] = sum(a[j] * b[i - j] for j in range(i + 1)) % 998244353.

    It returns an empty list if at least one of a and b are empty.

    Complexity
    ----------

    >   O(n log n), where n = len(a) + len(b).
    """
    n = len(a)
    m = len(b)
    if n == 0 or m == 0:
        return []
    if min(n, m) <= 60:
        return convolution_naive(a, b)
    if a is b:
        return convolution_square(a)
    return convolution_ntt(a, b)

def integrate(a):
    a=a.copy()
    n = len(a)
    assert n > 0
    a.pop()
    a.insert(0, 0)
    inv = [1, 1]
    for i in range(2, n):
        inv.append(-inv[mod%i] * (mod//i) % mod)
        a[i] = a[i] * inv[i] % mod
    return a

def differentiate(a):
    n = len(a)
    assert n > 0
    for i in range(2, n):
        a[i] = a[i] * i % mod
    a.pop(0)
    a.append(0)
    return a

def inverse(a):
    n = len(a)
    assert n > 0 and a[0] != 0
    res = [pow(a[0], mod - 2, mod)]
    m = 1
    while m < n:
        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] % mod
        butterfly_inv(f)
        f = f[m:] + [0]*m
        butterfly(f)
        for i in range(2*m):
            f[i] = f[i] * g[i] % mod
        butterfly_inv(f)
        iz = pow(2*m, mod-2, mod)
        iz = (-iz*iz) % mod
        for i in range(m):
            f[i] = f[i] * iz % mod
        res += f[:m]
        m <<= 1
    return res[:n]

def log(a):
    a = a.copy()
    n = len(a)
    assert n > 0 and a[0] == 1
    a_inv = inverse(a)
    a=differentiate(a)
    a = convolution(a, a_inv)[:n]
    a=integrate(a)
    return a

def exp(a):
    a = a.copy()
    n = len(a)
    assert n > 0 and a[0] == 0
    g = [1]
    a[0] = 1
    h_drv = a.copy()
    h_drv=differentiate(h_drv)
    m = 1
    while m < n:
        f_fft = a[:m] + [0] * m
        butterfly(f_fft)

        if m > 1:
            _f = [f_fft[i] * g_fft[i] % mod for i in range(m)]
            butterfly_inv(_f)
            _f = _f[m // 2:] + [0] * (m // 2)
            butterfly(_f)
            for i in range(m):
                _f[i] = _f[i] * g_fft[i] % mod
            butterfly_inv(_f)
            _f = _f[:m//2]
            iz = pow(m, mod - 2, mod)
            iz *= -iz
            iz %= mod
            for i in range(m//2):
                _f[i] = _f[i] * iz % mod
            g.extend(_f)

        t = a[:m]
        t=differentiate(t)
        r = h_drv[:m - 1]
        r.append(0)
        butterfly(r)
        for i in range(m):
            r[i] = r[i] * f_fft[i] % mod
        butterfly_inv(r)
        im = pow(-m, mod - 2, mod)
        for i in range(m):
            r[i] = r[i] * im % mod
        for i in range(m):
            t[i] = (t[i] + r[i]) % mod
        t = [t[-1]] + t[:-1]

        t += [0] * m
        butterfly(t)
        g_fft = g + [0] * (2 * m - len(g))
        butterfly(g_fft)
        for i in range(2 * m):
            t[i] = t[i] * g_fft[i] % mod
        butterfly_inv(t)
        t = t[:m]
        i2m = pow(2 * m, mod - 2, mod)
        for i in range(m):
            t[i] = t[i] * i2m % mod
    
        v = a[m:min(n, 2 * m)]
        v += [0] * (m - len(v))
        t = [0] * (m - 1) + t + [0]
        t=integrate(t)
        for i in range(m):
            v[i] = (v[i] - t[m + i]) % mod

        v += [0] * m
        butterfly(v)
        for i in range(2 * m):
            v[i] = v[i] * f_fft[i] % mod
        butterfly_inv(v)
        v = v[:m]
        i2m = pow(2 * m, mod - 2, mod)
        for i in range(m):
            v[i] = v[i] * i2m % mod
        
        for i in range(min(n - m, m)):
            a[m + i] = v[i]
        
        m *= 2
    return a

def power(a,k):
    n = len(a)
    assert n>0
    if k==0:
        return [1]+[0]*(n-1)
    l = 0
    while l < len(a) and not a[l]:
        l += 1
    if l * k >= n:
        return [0] * n
    ic = pow(a[l], mod - 2, mod)
    pc = pow(a[l], k, mod)
    a = log([a[i] * ic % mod for i in range(l, len(a))])
    for i in range(len(a)):
        a[i] = a[i] * k % mod
    a = exp(a)
    for i in range(len(a)):
        a[i] = a[i] * pc % mod
    a = [0] * (l * k) + a[:n - l * k]
    return a

def sqrt(a):
    if len(a) == 0:
        return []
    if a[0] == 0:
        for d in range(1, len(a)):
            if a[d]:
                if d & 1:
                    return None
                if len(a) - 1 < d // 2:
                    break
                res=sqrt(a[d:]+[0]*(d//2))
                if res == None:
                    return None
                res = [0]*(d//2)+res
                return res
        return [0]*len(a)
    
    sqr = Tonelli_Shanks(a[0],mod)
    if sqr == None:
        return None
    T = [0] * (len(a))
    T[0] = sqr
    res = T.copy()
    T[0] = pow(sqr,mod-2,mod) #T:res^{-1}
    m = 1
    two_inv = (mod + 1) // 2
    F = [sqr]
    while m <= len(a) - 1:
        for i in range(m):
            F[i] *= F[i]
            F[i] %= mod
        butterfly_inv(F)
        iz = pow(m, mod-2, mod)
        for i in range(m):
            F[i] = F[i] * iz % mod
        delta = [0] * (2 * m)
        for i in range(m):
            delta[i + m] = F[i] - a[i] - (a[i + m] if i+m<len(a) else 0)
        butterfly(delta)
        G = [0] * (2 * m)
        for i in range(m):
            G[i] = T[i]
        butterfly(G)
        for i in range(2 * m):
            delta[i] *= G[i]
            delta[i] %= mod
        butterfly_inv(delta)
        iz = pow(2*m, mod-2, mod)
        for i in range(2*m):
            delta[i] = delta[i] * iz % mod
        for i in range(m, min(2 * m, len(a))):
            res[i] = -delta[i] * two_inv%mod
            res[i]%=mod
        if 2 * m > len(a) - 1:
            break
        F = res[:2 * m]
        butterfly(F)
        eps = [F[i] * G[i] % mod for i in range(2 * m)]
        butterfly_inv(eps)
        for i in range(m):
            eps[i] = 0
        iz = pow(2*m, mod-2, mod)
        for i in range(m,2*m):
            eps[i] = eps[i] * iz % mod
        butterfly(eps)
        for i in range(2 * m):
            eps[i] *= G[i]
            eps[i] %= mod
        butterfly_inv(eps)
        for i in range(m, 2 * m):
            T[i] = -eps[i]*iz
            T[i]%=mod
        iz = iz*iz % mod
        m <<= 1
    return res

def division_modulus(f,g):
    n=len(f)
    m=len(g)
    while m and g[m-1]==0:
        m-=1
    assert m
    if n>=m:
        fR=f[::-1][:n-m+1]
        gR=g[:m][::-1][:n-m+1]+[0]*max(0,n-m+1-m)
        qR=convolution(fR,inverse(gR))[:n-m+1]
        q=qR[::-1]
        r=[(f[i]-x)%mod for i,x in enumerate(convolution(g,q)[:m-1])]
        while r and r[-1]==0:
            r.pop()
    else:
        q,r=[],f.copy()
    return q,r

def taylor_shift(a,c):
    a=a.copy()
    n=len(a)
    #MD=MOD(mod)
    #MD.Build_Fact(n-1)
    for i in range(n):
        a[i]*=MD.Fact(i)
        a[i]%=mod
    C=[1]
    for i in range(1,n):
        C.append(C[-1]*c%mod)
    for i in range(n):
        C[i]*=MD.Fact_Inve(i)
        C[i]%=mod
    a=convolution(a,C[::-1])[n-1:]
    for i in range(n):
        a[i]*=MD.Fact_Inve(i)
        a[i]%=mod
    return a

def multipoint_evaluation(f, x):
    n = len(x)
    sz = 1 << (n - 1).bit_length()
    g = [[1] for _ in range(2 * sz)]
    for i in range(n):
        g[i + sz] = [-x[i], 1]
    for i in range(1, sz)[::-1]:
        g[i] = convolution(g[2 * i],g[2 * i + 1])
    g[1] =division_modulus(f,g[1])[1]
    for i in range(2, 2 * sz):
        g[i]=division_modulus(g[i>>1],g[i])[1]
    res = [g[i + sz][0] if g[i+sz] else 0 for i in range(n)]
    return res

def Chirp_Z_transform(f,q,M):
    if q==0:
        if f:
            return f[0]%mod
        else:
            return 0
    if M==0:
        return []
    N=len(f)
    pow_q=[1]+[q]*(N+M-2)
    inve_q=pow(q,mod-2,mod)
    pow_inve_q=[1]+[inve_q]*(N+M-2)
    for _ in range(2):
        for i in range(1,N+M-1):
            pow_q[i]*=pow_q[i-1]
            pow_q[i]%=mod
            pow_inve_q[i]*=pow_inve_q[i-1]
            pow_inve_q[i]%=mod
    a=[f[i]*pow_inve_q[i]%mod for i in range(N-1,-1,-1)]
    b=pow_q
    ab=convolution(a,b)
    return [ab[j+N-1]*pow_inve_q[j]%mod for j in range(M)]

def relaxed_convolution(N,f):
    retu=[0]*N
    A,B=[],[]
    C=None
    for i in range(N):
        a,b=f(i,C)
        A.append(a)
        B.append(b)
        pow2=1
        while (i+2)%pow2==0:
            if pow2==i+2:
                break
            elif pow2*2==i+2:
                tpl=((i+1-pow2,i+1,i+1-pow2,i+1),)
            else:
                tpl=((pow2-1,2*pow2-1,i+1-pow2,i+1),(i+1-pow2,i+1,pow2-1,2*pow2-1),)
            for la,ra,lb,rb in tpl:
                for j,c in enumerate(convolution(A[la:ra],B[lb:rb]),la+lb):
                    if j<N:
                        retu[j]+=c
                        retu[j]%=mod
            pow2*=2
        C=retu[i]
    return retu

def Berlekamp_Massey(A,mod):
    n = len(A)
    B, C = [1], [1]
    l, m, p = 0, 1, 1
    for i in range(n):
        d = A[i]
        for j in range(1, l + 1):
            d += C[j] * A[i - j]
            d %= mod
        if d == 0:
            m += 1
            continue
        T = C.copy()
        q = pow(p, mod - 2, mod) * d % mod
        if len(C) < len(B) + m:
            C += [0] * (len(B) + m - len(C))
        for j, b in enumerate(B):
            C[j + m] -= q * b
            C[j + m] %= mod
        if 2 * l <= i:
            B = T
            l, m, p = i + 1 - l, 1, d
        else:
            m += 1
    res = [-c % mod for c in C[1:]]
    return res

def BMBM(A,N,mod):
    deno=[1]+[-c for c in Berlekamp_Massey(A,mod)]
    nume=[0]*(len(deno)-1)
    for i in range(len(A)):
        for j in range(len(deno)):
            if i+j<len(nume):
                nume[i+j]+=A[i]*deno[j]
                nume[i+j]%=mod
    return Bostan_Mori(nume,deno,N,mod=mod)

N,M=map(int,input().split())
mod=998244353
MD=MOD(mod)
MD.Build_Fact(N)
C=[None]*(N+1)
P0=[(-1)**c*MD.Pow(M-c,N)%mod*MD.Fact_Inve(c)%mod for c in range(N+1)]
P1=[MD.Fact_Inve(c) for c in range(N+1)]
P=convolution(P0,P1)
for m in range(N+1):
    C[m]=P[m]*MD.Fact(m)%mod
ans=sum(m*m*C[m]%mod for m in range(N+1))%mod
print(ans)
0