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Wansur's blog

By Wansur, history, 6 days ago, translation, In English

2013A — Zhan's Blender

First to solve: rob00

Solution
Code

2013B — Battle For Survive

First to solve: neal

Solution
Code

2013C — Password Cracking

First to solve: Pagode_Paiva

Solution
Code

2013D — Minimize the Difference

First to solve: edogawa_something

Solution
Code

2013E — Prefix GCD

First to solve: meme

Solution
Code

2013F1 — Game in Tree (Easy Version)

First to solve: EnofTaiPeople

Solution
Code with segment tree
Code in O(n)

2013F2 — Game in Tree (Hard Version)

First to solve: rainboy

Solution
Code
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5 days ago, # |
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Problem E originally meant a solution without a gready, but what are rich in :)

And in F you need to separately figure out when the first / second player wins if he starts at his top, because otherwise it hurts a lot)

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    5 days ago, # ^ |
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    I have another solution of $$$E$$$ and I wonder if it is intended.

    Enumerate $$$a_1$$$. Note all the divisors of $$$a_1$$$ as $$$d_1,d_2,\ldots,d_m$$$. We can check if there is $$$a_j$$$ such that $$$\gcd(a_1,a_j)=d_k$$$ for every divisors.

    Note $$$dp_{i,j}$$$ as the max sum when $$$\gcd(a_1,\ldots,a_i)=j$$$. We only accept transform $$$dp_{i,j} \rightarrow dp_{i+1,k}(k<j)$$$ so $$$i$$$ is small ($$$log(maxa)$$$).

    So the complexity is $$$log(maxa) \cdot m^2$$$ for an $$$a_1$$$.

    The maximum number of divisors may be $$$240$$$, but if we tag the calculated numbers and skip them, the average $$$m$$$ is around $$$10$$$.

    The final complexity is $$$O(n \cdot \log(maxa) \cdot \overline{m^2})$$$.

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      4 days ago, # ^ |
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      how do you check if there is a number that will turn N into one of its divisor D ?

      i thought of inclusion exclusion on the prime factors to determine if there exists such a number X that doesnt include any of the prime factors to turn N into D but it seems like u didnt use inclusion exclusion so how did u do it ?

      edit : seems like u only did it for one number

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        4 days ago, # ^ |
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        Let's assume $$$d_1<d_2< \cdots <d_m$$$.

        Note $$$cnt1_x$$$ as the total of multiple of $$$x$$$, and $$$cnt2_x$$$ as the total of $$$a_i$$$ such that $$$\gcd(a_1,a_i)=x$$$.

        For $$$i=m$$$ to $$$1$$$, do $$$cnt_2[d_i]+=cnt1[d_i]$$$, and $$$cnt_2[d_j]-=cnt_2[d_i]$$$ $$$(d_i=k\cdot d_j)$$$. The complexity is $$$O(m^2)$$$.

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5 days ago, # |
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:< could someone explain why cout<<ceil(double(n) / min(x,y)); in A led to WA

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    5 days ago, # ^ |
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    There are two reasons this may cause issue

    first (which is mostly the issue here), the output will be in scientific notation

    cout << ceil(1e9 / 2); // 5e+08
    

    this can be solved by casting the output to long/int

    cout << (long long)ceil(1e9 / 2); // 500000000
    

    Another issue which usually happens with large numbers is that double may not be precise enough, for example

    long long x = 1e18;
    x -= 2
    cout << (long long)ceil((double)x / 2) // 500000000000000000;
    

    Here the answer is off by 1 because double is not precise enough, a good solution for both these issues is to not use double for calculating ceil, instead you can calculate it using this

    $$$ceil(a/b) = floor((a + b - 1) / b)$$$

    Which can be written like this:

    long long a = 1e18, b = 2;
    a -= 2;
    cout << (a + b - 1) / b; // 499999999999999999
    
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    5 days ago, # ^ |
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    use (long long)ceill(..) instead

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5 days ago, # |
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My solution for problem C:

  • First binary search to find maximum consecutive one and zero's. You can binary search over array such as [0, 1, 11, 111, 1111 ...] for 1 and when result of binary search is 0 for 1 that means there aren't any 1 in password.

  • Now you can try both possible combination of max consecutive one and max consecutive zero. For ex let's say max_consec_one = 3, max_consec_zero = 4, so either 1110000 or 0000111 has to be a substring.

  • From the above example if max_consec_one = 3 and 1110000 is valid substring that means on left of this substring there has to be some amount of zero's and same logic for right. To find this cnt of zero's for left and one's for right you can again binary search.

  • You can repeat above step until string t reaches the size n of the original string.

I don't know how to prove that it is less than n * 2 queries, but I think it is. I don't know whether this approach is correct. I think my solution has some sort of implementation mistake. Here's my submission

Can someone help me to find out if my approach is incorrect or implementation?

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    5 days ago, # ^ |
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    I spotted a problem in your approach, check out this case:

    111010000

    here max_consec_one = 3, max_consec_zero = 4, yet neither 1110000 nor 0000111 are substrings of the original string

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      4 days ago, # ^ |
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      Thanks, btwn I upvoted you but someone else downvoted you it's kinda funny that you got downvoted for no reason.

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5 days ago, # |
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can anyone explain problem D and E solutions for like why we did what we did . The intuition behind them.

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5 days ago, # |
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You should add the binary search and prefix sum solutions to D as well.

As Sol2/Sol3.

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    5 days ago, # ^ |
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    Please share the prefix sum solution of it

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5 days ago, # |
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So in D you literally said "here is the solution" no explanation to the logic or why it works

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    4 days ago, # ^ |
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    Waiting for the logic explanation! Someone who understood the solution please explain

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5 days ago, # |
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can someone explain the solution to problem D

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    4 days ago, # ^ |
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    The solution written in the editorial and the binary search solution of problem D are basically equivalent.

    If we always keep the array non-decreasing, then performing operations is not advantageous, which means we have the array we needed. So the problem becomes how can we keep the array non-decreasing when we continuously add elements to it. We can use binary search to search the left side of where we add new element, finding the longest interval that can be averaged using the operation that problem provide us. Equally, we can use a stack to finish the same work, just traverse forward(left) one by one. However, simply traverse forward one by one has a complexity of $$$O(N)$$$ that cannot accepted, that's why the editorial records the number of occurrences of duplicate elements.

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      4 days ago, # ^ |
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      I dont understand the binary search solution. Can u illustrate more pls

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        3 days ago, # ^ |
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        You can set the start place fixed at where we add the new element, then binary search the end place between 1 and the start place, a end place is legal with the same condition of the editorial says. And you can use prefix sum to calculate the interval sum in $$$O(1)$$$ complexity. The binary search is correct in that if an interval has a suffix that cannot be averaged, then it cannot be averaged, and this fact ensures the monotonicity that binary search required.

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          3 days ago, # ^ |
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          Can u pls provide a code for that

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          3 days ago, # ^ |
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          after you do binary search as you say, the value of prefix sum may change, and we may update it in complexity $$$O(n)$$$ that can not accepted. Is that rihgt?Is there something I misunderstand?

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            3 days ago, # ^ |
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            You're right, maybe I have something misunderstand about the binary search solution. Thinking...

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              3 days ago, # ^ |
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              I used binary search to find $$$alpha$$$ the lowest maximum obtainable and the $$$beta$$$ largest minimum obtainable with the operation. Then it can be shown that it is possible to build a solution that reaches both of these values. The answer is then $$$alpha-beta$$$

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                39 hours ago, # ^ |
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                After taking long time to read your editorial, i finally managed to slightly understand how the binary search approach works. And it seems there are some > or < wrongs and a 'is' is miss-spelled as 'it'? Sorry for my poor english btw.

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          45 hours ago, # ^ |
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          I thought of the same approach but then while thinking couldn't resolve that how u are modifying the previous values from starting index to the adding index?? See what i mean that when we have a non decreasing monotonous array in our left side then we can use binary search on them to get where the new element fits in, then we can definitly take on the right side of that arrays sum by using prefix sum and then avg that part out.

          But my question is even though we can do this we dont have a method of changing the left portion of the array in O(1). Worst case in changing will turn out to be O(n). Hence the TC will ultimately turn out to be O(n^2), as per myself.

          The solution written above also states the same thing but they dont use the a sorted array instead they are using a stack, where they avg out the values. and keep count variable to indicate how many repetetive copies of it are existing in the left sorted section. This reduces the TC of our approach by a lot like they mentioned "since on each iteration, no more than 2 elements are added to the stack, and each element is removed at most once". Here i cant agree to the second point that each element is removed atmost once!! Like they are inserting more types of values than what are already present there, also the values m,ight be repetetive at different instances of index to be added.

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5 days ago, # |
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sub link Can someone tell me why this is wrong? It's the same as the editorial, only difference being i wrote a simulation for the checking part

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5 days ago, # |
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Wait so long for the editorial

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In problem C: What if there is a substring of the form both t+0 and t+1 in the original string?

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    5 days ago, # ^ |
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    You dont care u cant just take any of them and procceed until u hit the end of the string (neither t + 0 nor t + 1 is a substring) with this u will have a suffix of the string then start extending from the left (aka 0 + t or 1 + t until the length of t is n)

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5 days ago, # |
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Regarding E's time complexity as $$$O(n\log^2W)$$$ may be better.

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5 days ago, # |
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In F1, I was trying a solution with simultaneous BFS (from 1 for Alice, and from u for Bob). It doesn't work, but I don't know why. I would appreciate if someone could point out the edge case. At each step, Alice goes to EVERY unseen node in her frontier, marking it as 'seen', after that the neighbours of each of these nodes become her next frontier. Then Bob does the same thing. If at any point a player's frontier is empty, or only have 'seen' nodes, and its that players turn, the player loses.

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    5 days ago, # ^ |
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    See if this may help you: 282194464. It's a simple backtracking solution using DFS, but I don't know why it doesn't TLE (since backtracking usually has exponential/factorial time complexity).

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    4 days ago, # ^ |
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    1
    8
    1 2
    2 3
    1 4 
    4 5
    4 6
    6 7
    6 8
    8 8
    

    In this test case, Bob would win, but your algorithm outputs 'Alice' ?

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    2 days ago, # ^ |
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    This is also my initial thoughts, since the previously shared test didn't fail my program I changed it to make it fail mine, expected output is still Bob:

    Test
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5 days ago, # |
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Wansur I have a practice submission for problem D which was accepted, but I believe it shouldn't, as it has $$$O(n^2)$$$ time complexity. Here's the submission 282154960, and here's a test generator that should make it TLE:

C++

I'm posting this here because there isn't a way to hack my own submission to a past contest.

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5 days ago, # |
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For those of you who don't understand what the tutorial of E is saying:

We want to prove that $$$F(a_1,a_2,\cdots,a_n,x) \ge F(x,a_1,a_2,\cdots,a_n)$$$ where $$$F$$$ is the sum defined in the problem and $$$x$$$ satisfies $$$x < a_1$$$. If this is true, there always exists an optimal solution where is the smallest element is re-arranged to the first position. Here is the proof:

$$$F(a_1,a_2,\cdots,a_n,x) = (\color{red}{a_1}) + \gcd(a_1,a_2) + \gcd(a_1,a_2,a_3) + \cdots + \gcd(a_1,a_2,\cdots,a_n,x)$$$

$$$F(x,a_1,a_2,\cdots,a_n) = (\color{red}{x + \gcd(x,a_1)}) + \gcd(x,a_1,a_2) + \gcd(x,a_1,a_2,a_3) + \cdots + \gcd(x,a_1,a_2,\cdots,a_n)$$$

Because $$$x < a_1$$$ and gcd is always smaller or equal the the difference of two numbers, we have $$$\gcd(x,a_1) \le a_1 -x \implies x + \gcd(x,a_1) \le a_1$$$.

For the rest of the terms, it is easy to observe that the term below is always less than or equal to the corresponding term above since $$$x$$$ is added in the calculation.

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    5 days ago, # ^ |
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    "It can be observed that the gcd will reach 1 in at most 10 iterations." can you please explain it for me?

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      5 days ago, # ^ |
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      $$$a_1$$$ has at most $$$\log(a_1)$$$ (not necessarily distinct) prime factors. In each iteration, at least one of them should be gone, or the $$$\gcd$$$ is already the minimum possible.

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        41 hour(s) ago, # ^ |
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        but why in each time one of them gone? if the left of array are same ,ans they are different from others , it wont go even one. And by the way,qingczha's provement int F(x,a1..an) is wrong ,because in fact for array 3 2 2 2 is wrong,but i dont know why

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          38 hours ago, # ^ |
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          becauze if u don't have any element which is less than last, it means that every left elements are equel to each otehr, and you can stop your loop

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      5 days ago, # ^ |
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      At first, we divided every $$$a_i$$$ by $$$g = gcd(a_1,a_2,...,a_n)$$$. This means that the gcd of some prefix of $$$a$$$ will now eventually reach $$$1$$$ instead of $$$g$$$.

      We are greedily building our new array, with every new element it is guaranteed that the new gcd will be strictly less than the previous (until we reach $$$1$$$ obviously). And since $$$a_i ≤ 10^5$$$, any $$$a_i$$$ can have at most $$$6$$$ distinct primes in its factorization, so we can safely say that the gcd will be reduced to $$$1$$$ in at most $$$10$$$ iterations.

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        12 hours ago, # ^ |
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        i know at most $$$log_{2}a_i$$$ not necessarily distinct primes, but why $$$6$$$ distinct primes?

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    4 days ago, # ^ |
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    Could you tell me how to explain the greedy in the tutorial? That means how to prove that $$$x,y,a_1,a_2,a_3,\cdots $$$ is not worser than $$$x,a_1,a_2,a_3,\cdots ,y$$$ if $$$\gcd(x,y)\le \gcd(x,a_1)$$$?

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5 days ago, # |
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Your proof for problem C seems incorrect to me.

In your proof, you mentioned However, after this iteration, we will make only 1 query. But what if that iteration does not exist? For example, you coincidentally reach a suffix of size $$$n - 1$$$ for $$$t$$$, which may take $$$2(n-1)$$$ queries. And after $$$2$$$ more queries, you realized that your $$$t$$$ has reached the end of $$$s$$$. So you need $$$1$$$ additional query to know whether the first character is '0' or '1'. In total, this is $$$2(n - 1) + 2 + 1 = 2n + 1$$$ queries.

In your reference implementation, this case does not actually happen but you may need to address it in your proof.

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    5 days ago, # ^ |
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    I was thinking the same thing. I tried out few test cases and maybe this will clear answer you question —

    Not every operation will cost you 2 queries. Say you start your query with "0", if there is no substring "0", then we are looking at a string "11..11" as answer and this will take exactly 2*n queries. On the contrary, one can argue that answer string can be of the form "011..11", then too if you start your query with "0", you only take one query to get the one substring 2 queries for each character in the other "11..11" part.

    Basically, your suffix of size n-1 will take 2*(n-1) queries only if they are the opposite of the character that you are querying for first( example- answer string — "100000" and you query first for t+"1" and then t+"0" ). But if the first character of answer string is the same as the character you are querying first then you get the whole string and not the suffix ( your answer builds as "10.." )

    I hope I was able to explain!

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    5 days ago, # ^ |
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    If the first characters costs 2 queries, it means the the whole string consists of 1 only(assuming you are querying in the order of 0 and 1). In this case, exactly 2n queries will be used to figure the string out.

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why is the problem D explained without explanation?

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5 days ago, # |
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someone explain solution for task D in a bit elaborate manner.the tutorial is of no use

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4 days ago, # |
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In case you still don't understand the tutorial of D:

The key observation here is: If two consecutive elements $$$a_i > a_{i+1}$$$, it is always not bad to "mix them up", i.e. assign $$$a_i := \lfloor{\frac{a_i+a_{i+1}}{2}}\rfloor$$$ and $$$a_{i+1} \to \lceil{\frac{a_i+a_{i+1}}{2}} \rceil$$$. For instance, (10,1) -> (5,6) and (8,4) -> (6,6). The reason is that: 1. The answer is not worsen since the range is smaller. 2. If in the optimal operation sequence the value of $$$a_i$$$ is transferred to some element of large index instead of $$$a_{i+1}$$$, it is always valid to transfer it from $$$a_{i+1}$$$(Why?).

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    4 days ago, # ^ |
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    what do you mean by transferring ai? can you explain pls

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      4 days ago, # ^ |
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      simply $$$a_i \to a_{i}-1$$$ and $$$a_j \to a_{j}+1$$$ as defined in the problem

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    4 days ago, # ^ |
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    I got this but I am not sure how to simulate all of this?

    I can only think of an O(n^2) solution where you do it n times to get a sorted array.

    I dont get the stack implementation in the editorial :(

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      4 days ago, # ^ |
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      Let's say you have a sorted array $$$a,\cdots,a,b,\cdots,b,c,\cdots,c$$$ where $$$a<b<c$$$ and now you want to append a $$$d$$$ and keep it sorted.

      Firstly, what the stack stores is an efficient representation of the elements in the current array, i.e. $$$[(a,cnt_a),(b,cnt_b),(c,cnt_c)]$$$. Now to add $$$d$$$, we firstly mix it up with $$$c$$$. The result can be calculated in $$$O(1)$$$ because we know the sum and the total count. One slight tricky point is to split the "floor" part and the "ceil" part. For example, we have $$$(10,7)$$$ (7 tens) and mix it up with a $$$1$$$, we know that the sum is $$$10*7+1 = 71$$$ and the count is $$$7+1=8$$$. The result should be $$$[(8,1),(9,7)]$$$. (Try to figure out how $$$1$$$ and $$$7$$$ are calculated.)

      If mix-up with currently largest element(i.e. $$$c$$$) would cause the the result to be smaller than the second largest element(i.e. $$$b$$$), the first mix-up is actually not needed and we include $$$(b,cnt_b)$$$ in the mix-up as well. We keep the inclusion until the result satisfies the sorted-ness.

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        4 days ago, # ^ |
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        Ohh got this, we can do the 7,1 by the sum and average value or something.

        Thanks a lot!!

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Problem C can also be solved with O( n + 2 * log(n) ) complexity. Use binary search to find the longest continuous string of 0's using queries. Then we can build the right side of the string with 1's and check with queries. If it's not a substring we replace the 1 with 0 and continue until we reach fill the string or we end up with more 0's consecutively than what we found to be the longest. Next we use binary search to query how many of the ending 0's are also apart of the confirmed substring we know from the last query section. This will finish constructing the right side of the string. To find the answer, we now add 1's to the front of the string and query, if it's not a substring then the answer is to replace the 1 with a 0.

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  • My solution for problem D :
Solution
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    4 days ago, # ^ |
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    Cool solution understood that better than in the editorial

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    4 days ago, # ^ |
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    Wait isn't min going to change when min > mx — y? a[i+1] += (a[i] — (mx-y)) a[i] = mx-y

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      4 days ago, # ^ |
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      • min might change , but the min wont decrease , I am not saying that min wont change , min might change but the change is that min does not decrease , it will always either remain same or increase .
      • So reducing the maximum element will not decrease the min ,
      • so the value = max(a1,a2,..an) — min(a1,a2,...,an) . here when we are reducing the max then , the min might increase or remain the same , so it is always optimal to reduce the max . if min increases that means it is coming closer to the max hence the value is decreasing .
      • Also initially I have stated the assumption : Suppose it is possible to make maximum element of the array A from mx to mx-y .
      • for example a = [18 , 9 , 12 ,18 , 6]
      • initially mx = 18 and mn = 6;

      • now let us just make mx to mx-2 , 18 to 16
      • a = [16 , 11 , 12 , 16 , 8]
      • Do you see that in this newly formed array ,mx = 16 and mn = 8 , here mn is increasing , and mx is decreasing , so the overall value will decrease . from initially value = 18-6 = 12 to value = 16-8 = 8.
      • I think from above example you are able to get the idea that decreasing the maximum element wont decrease the mn , but min might increase or remain same . since max is decreasing and min is increasing overall the value is decreasing . is this helpful ?
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        4 days ago, # ^ |
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        what i mean is that what if mx — y gets smaller than min

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          4 days ago, # ^ |
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          That is not possible , mx is changed to mx-y and mx-y < mn (you are saying this) You can look at the last element = a[n] , a[n] >= minimum(mn), we are making all the elements a[i] <= mx-y ; since the last element = a[n] >= mn , the last element can only increase . so you can not make a[n] to mx-y which is mx-y < mn . So the condition you mentioned can never happen , is this helpful ?

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            4 days ago, # ^ |
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            thx, yes it was helpful, thats indeed good solution, bro what's your real rating

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    4 days ago, # ^ |
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    perfect explanation, thanks you

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    4 days ago, # ^ |
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    This is what I want to do but I have difficulty coming up with binary search part. Thank you.

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4 days ago, # |
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Why the code of F1 can solve the problem in O(n)? Thank you!

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4 days ago, # |
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Problem D. I saw a solution that we can binary search upper and lower bounds simultaneously. And I had tried this and got AC. But I'm very confused that how to prove this two independent operations is correct?

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3 days ago, # |
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In the case of a buffed up C , how to get to the answer in less than 2*N queries?

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3 days ago, # |
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I wrote a more detailed editorial for problem D, if anyone is interested https://mirror.codeforces.com/blog/entry/134292

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3 days ago, # |
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In the D problem, in authors solution as we are putting any element in stack only if it is larger than the previous one, as result max is at the top of stack and min should be at bottom, so taking minimum of all elements of stack(first element) should also give minimum but it is giving wa on tc3. Also, since the tc is large i cant work it out, any idea as to what might be the problem. WA_solution

Thanks in advance

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    3 days ago, # ^ |
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    1. wrong answer 1st numbers differ, the first case is not very large(n = 20)
    2. $$$1\le a_i\le 10^{12}$$$ & const ll INF = INT_MAX/10;
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      2 days ago, # ^ |
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      Thanks alot, it was a total blunder by me :(

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2 days ago, # |
Rev. 2   Vote: I like it 0 Vote: I do not like it

[DELETED]

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44 hours ago, # |
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Could anyone share the DP solution for E? Please brighten me :))

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42 hours ago, # |
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#include <bits/stdc++.h>
using namespace std;

#ifdef LOCAL
// #include "..\debugging.h"
#endif

#define int long long
using vi = vector<int>;
using vc = vector<char>;
using vb = vector<bool>;
using vd = vector<double>;
using vs = vector<string>;
using pi = pair<int, int>;
using vvi = vector<vector<int>>;
using vcb = vector<vector<bool>>;
using vvc = vector<vector<char>>;
using mi = map<int, int>;
using si = set<int>;


#define endl "\n"
#define all(x) begin(x), end(x)
#define sz(x) int((x).size())
#define fmap(name, x) mi name; for(auto it:x) ++name[it]
#define F first
#define S second
#define elif else if
#define PB emplace_back
#define MP make_pair
#define REPi(a, b) for (int i = a; i < b; i++)
#define REP(i, a, b) for (int i = a; i < b; i++)
#define REPO(a) for (int i = 0; i < a; i++)
#define vvl(ab, r, c, v)  vvi ab(r, vector<int>(c, v))
#define dbg(v)  cout << #v << " = " << (v) << endl;

const long long mod = 1000000007ll, mod2 = 998244353ll;

int dist(vvi &tree, int p, int node, int p2 = -1) {
    int ans = 1;
    for(int c: tree[node])
        if(c != p && c != p2) {
            ans = max(ans, dist(tree, node, c )+1);
        }
    return ans;
}

void path(vvi &tree, int node, int target, int p, vi &ans) {
    for(int i: tree[node]) {
        if(i == p)
            continue;
        ans.PB(i);
        if(i == target) {
            return;
        }
        path(tree, i, target, node, ans);
        if(ans.back() != target)
            ans.pop_back();
    }
}

signed main() {
    ios::sync_with_stdio(false);
    cin.tie(nullptr);

    int t;
    cin >> t;
    while(t--){
        int n;
        cin >> n;

        vvi tree(n);
        for(int i=1; i<n; ++i) {
            int u, v;
            cin >> u >> v;
            --u, --v;
            tree[u].PB(v);
            tree[v].PB(u);
        }

        int u, v;
        cin >> u >> v;
        --u, --v;

        vi adist(n, 0), bdist(n, 0), p = {-1, 0};
        path(tree, 0, u, -1, p);
        p.PB(-1);

        int m = p.size()-2;
        vi dp(m);

        for(int i=1; i<m+1; ++i)
            dp[i-1] = dist(tree, p[i-1], p[i], p[i+1]);


        vi a(m), b(m);
        for(int i=m-1; i>=0; --i) {
            a[i] = dp[i] + i;
            b[i] = dp[i] + m-i-1;
        }

        vi suffdp(m, b.back());
        vi predp(m,a.front());
        for(int i =1 ;i<m-1;i++){
            predp[i] = max(a[i],predp[i-1]);
        }
        for(int i=m-2; i>=0; --i)
            suffdp[i] = max(suffdp[i+1], b[i]);

        // dbg(p);
        // dbg(a);
        // dbg(b);
        // dbg(dp);
        // dbg(suffdp);
        // dbg(predp);


        int start = 0, end = m-1;
        int counter = 1;
        while(start < end){
            if(counter && a[start] > suffdp[start+1] || !counter && b[end] > predp[end-1] ){
                counter = !counter;
                break;
            }
            if(counter)
                start++;
            else
                end--;

            counter = !counter;
        }

        if(start == end)
            counter = !counter;
        cout << (counter?"Bob" : "Alice") << endl;
    }

    return 0;
}

can someone explain why this is wrong for F1.

Basically I tried to find the path from 1 to u. For every path value I found Dp(max depth not on path)

then I checked for early exit. If this makes sense

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41 hour(s) ago, # |
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I wonder in problem E.Is there a dp in The right time complexity ? Like "wuhudsm"we can Note dpi,j as the max sum when gcd(a1,…,ai)=j.But at least it cost O(n*n),because enumerate i cost N,and State transition cost N. It is at least O(N*N)

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14 hours ago, # |
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So can we have a rigorous mathematical proof for the solution of problem B?

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12 hours ago, # |
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the $$$A$$$ and $$$B$$$ in E's editorial are sequences, or elements, or the gcd of a sequence?