258 lines
6 KiB
C++
258 lines
6 KiB
C++
#include <bits/stdc++.h> // {{{
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// https://codeforces.com/blog/entry/96344
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#pragma GCC optimize("O2,unroll-loops")
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#pragma GCC target("avx2,bmi,bmi2,lzcnt,popcnt")
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using namespace std;
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template <typename T>
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[[nodiscard]] static T MIN() {
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return std::numeric_limits<T>::min();
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}
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template <typename T>
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[[nodiscard]] static T MAX() {
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return std::numeric_limits<T>::max();
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}
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template <typename T>
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[[nodiscard]] static T sc(auto &&x) {
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return static_cast<T>(x);
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}
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template <typename T>
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[[nodiscard]] static T sz(auto &&x) {
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return static_cast<T>(x.size());
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}
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#define prln(...) std::println(__VA_ARGS__)
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#define pr(...) std::print(__VA_ARGS__)
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#ifdef LOCAL
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#define dbgln(...) std::println(__VA_ARGS__)
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#define dbg(...) std::print(__VA_ARGS__)
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#endif
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inline static void NO() {
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prln("NO");
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}
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inline static void YES() {
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prln("YES");
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}
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using ll = long long;
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using ld = long double;
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template <typename T>
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using ve = std::vector<T>;
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template <typename T, size_t N>
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using ar = std::array<T, N>;
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template <typename T1, typename T2>
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using pa = std::pair<T1, T2>;
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template <typename... Ts>
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using tu = std::tuple<Ts...>;
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template <typename... Ts>
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using dq = std::deque<Ts...>;
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template <typename... Ts>
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using qu = std::queue<Ts...>;
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template <typename... Ts>
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using pq = std::priority_queue<Ts...>;
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template <typename... Ts>
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using st = std::stack<Ts...>;
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auto lb = [](auto... args) {
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return std::lower_bound(args...);
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};
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auto ub = [](auto... args) {
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return std::upper_bound(args...);
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};
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#define ff first
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#define ss second
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#define eb emplace_back
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#define pb push_back
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#define all(x) (x).begin(), (x).end()
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#define rall(x) (x).rbegin(), (x).rend()
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// }}}
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#include <ext/pb_ds/assoc_container.hpp>
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#include <ext/pb_ds/tree_policy.hpp>
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using namespace __gnu_pbds;
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// https://mirror.codeforces.com/blog/entry/124683
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namespace hashing {
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using i64 = std::int64_t;
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using u64 = std::uint64_t;
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static const u64 FIXED_RANDOM =
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std::chrono::steady_clock::now().time_since_epoch().count();
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#if USE_AES
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std::mt19937 rd(FIXED_RANDOM);
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const __m128i KEY1{(i64)rd(), (i64)rd()};
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const __m128i KEY2{(i64)rd(), (i64)rd()};
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#endif
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template <class T, class D = void>
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struct custom_hash {};
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template <class T>
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inline void hash_combine(u64 &seed, T const &v) {
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custom_hash<T> hasher;
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seed ^= hasher(v) + 0x9e3779b97f4a7c15 + (seed << 12) + (seed >> 4);
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};
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template <class T>
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struct custom_hash<T,
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typename std::enable_if<std::is_integral<T>::value>::type> {
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u64 operator()(T _x) const {
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u64 x = _x;
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#if USE_AES
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__m128i m{i64(u64(x) * 0xbf58476d1ce4e5b9u64), (i64)FIXED_RANDOM};
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__m128i y = _mm_aesenc_si128(m, KEY1);
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__m128i z = _mm_aesenc_si128(y, KEY2);
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return z[0];
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#else
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x += 0x9e3779b97f4a7c15 + FIXED_RANDOM;
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x = (x ^ (x >> 30)) * 0xbf58476d1ce4e5b9;
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x = (x ^ (x >> 27)) * 0x94d049bb133111eb;
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return x ^ (x >> 31);
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#endif
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}
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};
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template <class T>
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struct custom_hash<T, std::void_t<decltype(std::begin(std::declval<T>()))>> {
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u64 operator()(T const &a) const {
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u64 value = FIXED_RANDOM;
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for (auto &x : a)
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hash_combine(value, x);
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return value;
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}
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};
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template <class... T>
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struct custom_hash<std::tuple<T...>> {
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u64 operator()(const std::tuple<T...> &a) const {
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u64 value = FIXED_RANDOM;
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std::apply(
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[&value](T const &...args) {
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(hash_combine(value, args), ...);
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},
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a);
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return value;
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}
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};
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template <class T, class U>
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struct custom_hash<std::pair<T, U>> {
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u64 operator()(std::pair<T, U> const &a) const {
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u64 value = FIXED_RANDOM;
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hash_combine(value, a.first);
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hash_combine(value, a.second);
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return value;
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}
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};
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}; // namespace hashing
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#ifdef PB_DS_ASSOC_CNTNR_HPP
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template <class Key, class Value = null_type>
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using hashtable = gp_hash_table<
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Key, Value, hashing::custom_hash<Key>, std::equal_to<Key>,
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direct_mask_range_hashing<>, linear_probe_fn<>,
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hash_standard_resize_policy<hash_exponential_size_policy<>,
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hash_load_check_resize_trigger<>, true>>;
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#endif
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#ifdef PB_DS_TREE_POLICY_HPP
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template <typename T>
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using multitree = tree<T, null_type, std::less_equal<T>, rb_tree_tag,
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tree_order_statistics_node_update>;
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template <class Key, class Value = null_type>
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using rbtree = tree<Key, Value, std::less<Key>, rb_tree_tag,
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tree_order_statistics_node_update>;
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#endif
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void solve() {
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// division/math is weak point, but good amortized analysis
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// should be able to evaluate/come up with S(n=10^5)
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// instead of typing it into python
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// series/real analysis weakness
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// NOTE: better workflow for testing, i can't be certain if i would've tested
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// with 10^5 numbers 1..10^5 because i was on an airplane, but i tested it now
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int n;
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cin >> n;
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ve<ll> a(n);
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hashtable<int, int> f;
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for (auto &e : a) {
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cin >> e;
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++f[e];
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}
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ve<int> sieve(n + 1, 0);
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for (auto [k, v] : f) {
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ll K = k;
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while (K <= n) {
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sieve[K] += v;
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K += k;
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}
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}
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// TC: O(n + n + n / 2 + n / 3 + n / 4)
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// with n <= 10^5, that's O(14 n), which should be fine
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prln("{}", *max_element(all(sieve)));
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/*
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n + n / 2 + n / 3 + n / 4
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1 + 1 / 2 + 1 / 3 + 1 / 4
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a, 2a, 3a, 4a
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b, 2b, 3b, 4b
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c, 2c, 3c, 4c
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looking for number most frogs hit
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most frequent common multiple
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can't scan frog hop distances
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sort them
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a
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b
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makes sense to choose earliest hop in common for now
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lcm(a, b), ans = 2 (NOTE: if <= 10^9)
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find c: trap: lcm(a, b, c), ans = 3
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or don't: lcm(a, b), lcm(c) = c
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^ prob dp?
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binary search on place to trap, check if can trap:
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time-wise yes
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if can trap a at position x? x % a = 0
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no monotonic search space?
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consider iterating from trap=1..n
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how many frogs can i trap?
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number of frogs s.t. trap % frog = 0
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*/
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}
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int main() { // {{{
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cin.tie(nullptr)->sync_with_stdio(false);
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cin.exceptions(cin.failbit);
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int t = 1;
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cin >> t;
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while (t--) {
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solve();
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}
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return 0;
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}
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// }}}
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