結果
| 問題 |
No.1907 DETERMINATION
|
| コンテスト | |
| ユーザー |
Sumitacchan
|
| 提出日時 | 2022-02-05 19:34:31 |
| 言語 | C++17 (gcc 13.3.0 + boost 1.87.0) |
| 結果 |
WA
|
| 実行時間 | - |
| コード長 | 7,820 bytes |
| コンパイル時間 | 3,023 ms |
| コンパイル使用メモリ | 214,968 KB |
| 最終ジャッジ日時 | 2025-01-27 20:32:24 |
|
ジャッジサーバーID (参考情報) |
judge5 / judge1 |
(要ログイン)
| ファイルパターン | 結果 |
|---|---|
| sample | AC * 4 |
| other | AC * 49 WA * 14 |
ソースコード
#include <bits/stdc++.h>
#include <atcoder/modint>
using namespace std;
using namespace atcoder;
struct fast_ios { fast_ios(){ cin.tie(0); ios::sync_with_stdio(false); cout << fixed << setprecision(20); }; } fast_ios_;
#define FOR(i, begin, end) for(int i=(begin);i<(end);i++)
#define REP(i, n) FOR(i,0,n)
#define IFOR(i, begin, end) for(int i=(end)-1;i>=(begin);i--)
#define IREP(i, n) IFOR(i,0,n)
using ll = long long;
const int mod = 998244353;
using mint = modint998244353;
using mvec = vector<mint>;
using mmat = vector<mvec>;
#define debug(x) cout << #x << "=" << x << endl;
#define vdebug(v) { cout << #v << "=" << endl; REP(i_debug, (int)v.size()){ cout << v[i_debug] << ","; } cout << endl; }
#define mdebug(m) { cout << #m << "=" << endl; REP(i_debug, (int)m.size()){ REP(j_debug, (int)m[i_debug].size()){ cout << m[i_debug][j_debug] << ","; } cout << endl;} }
// Library Checker "Characteristic Polynomial" より引用
// https://judge.yosupo.jp/submission/68640
namespace LibraryChecker {
template <typename T> std::vector<T> characteristic_polynomial(std::vector<std::vector<T>> M) {
assert(M.empty() or M.size() == M[0].size());
int n = M.size();
// reduce M to upper Hessenberg form
for (int j = 0; j < n - 2; j++) {
for (int i = j + 2; i < n; i++) {
if (M[i][j] != 0) {
std::swap(M[j + 1], M[i]);
for (int k = 0; k < n; k++) std::swap(M[k][j + 1], M[k][i]);
break;
}
}
if (M[j + 1][j] == 0) continue;
auto inv = T(1) / M[j + 1][j];
for (int i = j + 2; i < n; i++) {
auto coef = M[i][j] * inv;
for (int k = j; k < n; k++) M[i][k] -= coef * M[j + 1][k];
for (int k = 0; k < n; k++) M[k][j + 1] += coef * M[k][i];
}
}
// compute the characteristic polynomial of upper Hessenberg matrix M
std::vector<std::vector<T>> p(n + 1);
p[0] = {T(1)};
for (int i = 0; i < n; i++) {
p[i + 1].resize(i + 2);
for (int j = 0; j <= i; j++) {
p[i + 1][j + 1] += p[i][j];
p[i + 1][j] -= p[i][j] * M[i][i];
}
T betas = 1;
for (int j = i - 1; j >= 0; j--) {
betas *= M[j + 1][j];
T coef = -betas * M[j][i];
for (int k = 0; k <= j; k++) p[i + 1][k] += coef * p[j][k];
}
}
return p[n];
}
} // namespace LibraryChecker
mmat read_matrix(int N){
mmat M(N, mvec(N));
REP(i, N) REP(j, N){
int x; cin >> x;
M[i][j] = x;
}
return M;
}
void write_matrix(mmat M){
int N = M.size();
REP(i, N){
REP(j, N) cout << M[i][j].val() << ',';
cout << endl;
}
}
mmat mult_matrix(mmat A, mmat B){
int N = A.size();
mmat C(N, mvec(N));
REP(i, N) REP(j, N) REP(k, N) C[i][j] += A[i][k] * B[k][j];
return C;
}
//swap M[i,:] and M[j,:]
void swap_row(mmat &M, int i, int j){
assert(i != j);
M[i].swap(M[j]);
}
//swap M[:,i] and M[:,j]
void swap_column(mmat &M, int i, int j){
assert(i != j);
int N = M.size();
REP(k, N) swap(M[k][i], M[k][j]);
}
//M[i,:]-=a*M[j:]
void sbt_row(mmat &M, int i, int j, mint a){
assert(i != j);
int N = M.size();
REP(k, N) M[i][k] -= a * M[j][k];
}
//M[:,i]-=a*M[:,j]
void sbt_column(mmat &M, int i, int j, mint a){
assert(i != j);
int N = M.size();
REP(k, N) M[k][i] -= a * M[k][j];
}
//M[i,:]*=a;
void mult_row(mmat &M, int i, mint a){
int N = M.size();
REP(k, N) M[i][k] *= a;
}
template <typename T>
T determinant(vector<vector<T>> A){
int N = A.size();
for(int j = 0; j < N; j++) assert((int)A[j].size() == N);
T m1 = 0; m1 -= 1; // -1, mintでバグらないように
T d = 1;
for(int j = 0; j < N; j++){
int i0 = -1;
for(int i = j; i < N; i++) if(!(A[i][j] == 0)){
i0 = i;
break;
}
if(i0 == -1) return 0;
if(i0 != j){
d *= m1;
A[j].swap(A[i0]);
}
d *= A[j][j];
for(int i = j + 1; i < N; i++){
if(A[i][j] == 0) continue;
T alpha = A[i][j] / A[j][j];
for(int k = j; k < N; k++){
A[i][k] -= A[j][k] * alpha;
}
}
}
return d;
}
struct fast_random
{
uint32_t x;
fast_random(int seed = 2463534242): x(seed){}
uint32_t xorshift(){
x ^= (x << 13);
x ^= (x >> 17);
x ^= (x << 5);
return x;
}
//random integer in [a, b]
uint32_t randint(uint32_t a, uint32_t b){
return a + xorshift() % (b - a + 1);
}
double uniform(){
return (double)xorshift() / UINT32_MAX;
}
double uniform(double a, double b){
return a + uniform() * (b - a);
}
};
fast_random rng;
//return a random matrix with determinant 1
mmat random_matrix(int N){
while(true){
mmat A(N, mvec(N));
REP(i, N) REP(j, N) A[i][j] = rng.randint(0, mod - 1);
mint D = determinant(A);
if(D.val() != 0){
REP(j, N) A[0][j] /= D;
return A;
}
}
}
bool solve(mmat A, mmat B, mvec &ans){
/*
X *
O D
の形にする
ここで、X=xI-M (Mは定数行列), Dは定数のみの上三角行列
Xのサイズはrank(B)
Dは正則でなければならない
*/
int N = A.size();
//まずX求める
int rankB = 0;
mint factor = 1;
REP(d, N){
int x = -1, y = -1;
FOR(i, d, N){
FOR(j, d, N){
if(B[i][j].val() != 0){
x = i; y = j;
break;
}
}
if(x != -1) break;
}
if(x == -1) break;
rankB++;
if(x != d){
swap_row(A, x, d);
swap_row(B, x, d);
factor *= -1;
}
if(y != d){
swap_column(A, y, d);
swap_column(B, y, d);
factor *= -1;
}
FOR(i, d + 1, N){
mint a = B[i][d] / B[d][d];
sbt_row(A, i, d, a);
sbt_row(B, i, d, a);
}
FOR(j, d + 1, N){
mint a = B[d][j] / B[d][d];
sbt_column(A, j, d, a);
sbt_column(B, j, d, a);
}
factor *= B[d][d];
mult_row(A, d, (mint)1 / B[d][d]);
B[d][d] = 1;
}
// 右下整理してDを求める
FOR(d, rankB, N){
int x = -1, y = -1;
FOR(i, d, N){
FOR(j, d, N){
if(A[i][j].val() != 0){
x = i; y = j;
break;
}
}
if(x != -1) break;
}
if(x == -1) return false;
if(x != d){
swap_row(A, x, d);
factor *= -1;
}
if(y != d){
swap_column(A, y, d);
factor *= -1;
}
FOR(i, d + 1, N){
mint a = A[i][d] / A[d][d];
sbt_row(A, i, d, a);
}
FOR(j, 0, d){
mint a = A[d][j] / A[d][d];
sbt_column(A, j, d, a);
}
}
IFOR(d, rankB, N){
FOR(j, 0, d){
mint a = A[d][j] / A[d][d];
sbt_column(A, j, d, a);
}
factor *= A[d][d];
}
mmat X(rankB, mvec(rankB));
REP(i, rankB) REP(j, rankB) X[i][j] = -A[i][j];
ans = LibraryChecker::characteristic_polynomial(X);
ans.resize(N + 1);
REP(i, N + 1) ans[i] *= factor;
return true;
}
int main(){
int N; cin >> N;
auto A = read_matrix(N);
auto B = read_matrix(N);
auto R = random_matrix(N);
auto A0 = mult_matrix(R, A), B0 = mult_matrix(R, B);
mvec ans(N + 1, 0);
solve(A0, B0, ans);
REP(i, N + 1) cout << ans[i].val() << endl;
return 0;
}
Sumitacchan