#950 - Pirate Treasure
A band of pirates has come into a hoard of treasure, and must decide how to distribute it amongst themselves. The treasure consists of identical, indivisible gold coins.
According to pirate law, the distribution of treasure must proceed as follows:
- The most senior pirate proposes a distribution of the coins.
- All pirates, including the most senior, vote on whether to accept the distribution.
- If at least half of the pirates vote to accept, the distribution stands.
- Otherwise, the most senior pirate must walk the plank, and the process resumes from step 1 with the next most senior pirate proposing another distribution.
The happiness of a pirate is equal to \(-\infty\) if he doesn't survive; otherwise, it is equal to \(c + p\cdot w\), where \(c\) is the number of coins that pirate receives in the distribution, \(w\) is the total number of pirates who were made to walk the plank, and \(p\) is the bloodthirstiness of the pirate.
The pirates have a number of characteristics:
- Greed: to maximise their happiness.
- Ruthlessness: incapable of cooperation, making promises or maintaining any kind of reputation.
- Shrewdness: perfectly rational and logical.
Consider the happiness \(c(n,C,p) + p\cdot w(n,C,p)\) of the most senior surviving pirate in the situation where \(n\) pirates, all with equal bloodthirstiness \(p\), have found \(C\) coins. For example, \(c(5,5,\frac{1}{10}) = 3\) and \(w(5,5,\frac{1}{10})=0\) because it can be shown that if the most senior pirate proposes a distribution of \(3,0,1,0,1\) coins to the pirates (in decreasing order of seniority), the three pirates receiving coins will all vote to accept. On the other hand, \(c(5,1,\frac{1}{10}) = 0\) and \(w(5,1,\frac{1}{10}) = 1\): the most senior pirate cannot survive with any proposal, and then the second most senior pirate must give the only coin to another pirate in order to survive.
Define \(\displaystyle T(N,C,p) = \sum_{n=1}^N \left ( c(n,C,p) + w(n,C,p) \right )\). You are given that \(T(30,3,\frac{1}{\sqrt{3}}) = 190\), \(T(50,3,\frac{1}{\sqrt{31}}) = 385\), and \(T(10^3, 101, \frac{1}{\sqrt{101}}) = 142427\).
Find \(\displaystyle \sum_{k=1}^6 T(10^{16},10^k+1,\tfrac{1}{\sqrt{10^k+1}})\). Give the last 9 digits as your answer.
Problem text © Project Euler, licensed under CC BY-NC-SA 4.0. Original: projecteuler.net/problem=950. Published Saturday, 14th June 2025, 08:00 pm. Solved by 132 members at time of mirroring.
Why this is useful
Optimization. A genuine objective is optimised over a choice set - the same shape as calibration and optimal-execution problems (Phases 10, 16).
We classify relevance honestly - not every Euler problem is a trading application.
Prerequisites
Lessons that prepare you:
10.4 Algorithms: Gradient Descent and Newton's Method · 10.1 Convex Sets and Convex Functions · 19.14 Computational Complexity, Feasibility Estimation, and Proving Algorithms Correct · 19.4 Exact Arithmetic: Big Integers, Rationals, and Floating-Point Traps · 19.3 Modular Arithmetic, Inverses, and Fast Exponentiation · 19.10 Search: Backtracking, Branch-and-Bound, Binary Search, Meet-in-the-Middle
Recommended stepping-stone problems: #103 · #190 · #183
Concepts: optimization brute-force-reduction
Likely techniques: exact-rational meet-in-middle modular-exponentiation
Learning mode
Pick how much scaffolding you want. Your choice is remembered per problem.
Understand the problem
- What exactly is the input to problem 950? Is it a bound (10^16), a supplied dataset, or a definition you must generate from?
- What is the required output - restate it precisely: a single residue (the answer is reduced modulo a given number, so keep everything in modular arithmetic from the start).
- Which objects exactly are in scope, and which are excluded by the wording (strict vs non-strict inequality, 'distinct', 'proper', 'below' vs 'up to')?
- What do the arguments of c(n,C,p), w(n,C,p) mean, and what is the value's type (count, sum, probability)?
- What are the edge cases: the smallest legal object, zero/one, ties, and the boundary at exactly 10^16?
- Why is brute force hard HERE specifically? Estimate the number of candidates implied by 10^16 and the cost of testing one.
- Which optimization fact would, if true, collapse the search - and can you state it as a testable claim before you look for a proof?
Predict & plan (before you code)
- Predict the strategy: in one sentence, what will your solution do? (The classification says optimization / meet-in-middle - do you agree, and why?)
- Predict the complexity of your intended method in terms of N = 10^16, and the wall-clock time you expect. Write both down now.
- Predict the key data structure: what is stored, keyed by what, and how large will it get at full scale?
- Predict the failure mode: what is most likely to break - an off-by-one on the bound, a definition misread, precision, or memory?
- Predict the output of the small case from rung 3 BEFORE running it (the statement says: "You are given that T(30,3, frac 1sqrt3) = 190, T(50,3, frac 1sqrt31) = 385, and T(10^3, 101, frac 1sqrt101) = 142427.") - then run it. A surprise here is worth more than an hour of debugging later.
Scratchpad
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Python workbench
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Check your answer
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Progressive hints
Optimization
You have a correct answer. That is the start of the learning, not the end.
- Reduce the time complexity. What is the bottleneck, and what mathematical fact removes it?
- Reduce memory. Can you stream, or keep only the last k states?
- Replace brute force with a closed form, a sieve, a recurrence, or a symmetry argument.
- Prove the optimized version computes the same thing.
- Compare two implementations and time them.
Explain it
Which step of your solution were you least confident about, and what evidence would settle it?
What did you try first, and what specifically made you abandon it - a proof, a timing, or a wrong small-case answer?
Where did the optimization structure do the real work? Name the single observation that collapsed the search space.
Could you have reached the meet-in-middle idea faster? Which words in the statement were pointing at it, and did you notice them?
What was the bug that cost you the most time, and what CLASS of bug was it (off-by-one, definition misread, precision, state under-specified)?
How would your solution change if the bound 10^16 were multiplied by 1000? Does it survive, or does it need a different idea?
What is the honest complexity of what you wrote (not what you intended), and where is the remaining slack?
Which problem you have already solved is this most similar to, and what is the shared skeleton - is it really 'meet-in-middle' underneath?
State the transferable technique in one sentence, without mentioning this problem's story at all.
Self-assess (mastery is not a correct number)
You reach Mastered only when you have solved it, rated yourself at least Solid across the dimensions, and written a real explanation.
Confidence
Low confidence schedules this problem for spaced review, even if you solved it.
Mastery check
- Variation: change the bound (or a rule) in the statement. Does your method still work? What breaks first?
- Constraints: if the limit were 10× larger, which step fails, and what would you replace it with?
- Related problem: #103 · #190 · #183
- Transfer: where else does this technique appear? Name a lesson and a real computational setting.
- Spaced re-attempt: come back after the review interval and re-solve it with no hints.