Problem 582: Nearly Isosceles $120$ Degree Triangles
View on Project EulerProject Euler Problem 582 Solution
EulerSolve provides an optimized solution for Project Euler Problem 582, Nearly Isosceles $120$ Degree Triangles, with C++, Python, Java, and a step-by-step mathematical explanation.
Problem Summary We count integer-sided triangles with one \(120^\circ\) angle opposite side \(c\), ordered so that \(a \le b \le c\), with the near-isosceles restriction \(b-a \le 100\) and the size bound \(c \le N\). The target value is \(T(10^{100})\), so a direct search over side lengths is hopeless. The solution must generate all valid families algebraically and then count only the distinct ordered triples. Mathematical Approach Once the angle is fixed at \(120^\circ\), the geometry turns into a quadratic Diophantine equation. The standard parameterization for integer \(120^\circ\) triangles then converts the near-isosceles condition into a Pell-type equation with a very small right-hand side. Step 1: Turn the triangle condition into an arithmetic equation By the law of cosines, a triangle with angle \(120^\circ\) opposite \(c\) satisfies $$c^2=a^2+b^2-2ab\cos 120^\circ=a^2+b^2+ab.$$ So every admissible triangle corresponds to a positive integer solution of $$c^2=a^2+b^2+ab,\qquad a \le b \le c.$$ This quadratic form is the norm form associated with Eisenstein integers, which is why a clean two-parameter description exists....
Detailed mathematical approach
Problem Summary
We count integer-sided triangles with one \(120^\circ\) angle opposite side \(c\), ordered so that \(a \le b \le c\), with the near-isosceles restriction \(b-a \le 100\) and the size bound \(c \le N\). The target value is \(T(10^{100})\), so a direct search over side lengths is hopeless. The solution must generate all valid families algebraically and then count only the distinct ordered triples.
Mathematical Approach
Once the angle is fixed at \(120^\circ\), the geometry turns into a quadratic Diophantine equation. The standard parameterization for integer \(120^\circ\) triangles then converts the near-isosceles condition into a Pell-type equation with a very small right-hand side.
Step 1: Turn the triangle condition into an arithmetic equation
By the law of cosines, a triangle with angle \(120^\circ\) opposite \(c\) satisfies
$$c^2=a^2+b^2-2ab\cos 120^\circ=a^2+b^2+ab.$$
So every admissible triangle corresponds to a positive integer solution of
$$c^2=a^2+b^2+ab,\qquad a \le b \le c.$$
This quadratic form is the norm form associated with Eisenstein integers, which is why a clean two-parameter description exists.
Step 2: Use the standard parameterization of primitive \(120^\circ\) triangles
For integers \(u>v>0\), define
$$a^\ast=u^2-v^2,\qquad b^\ast=2uv+v^2,\qquad c^\ast=u^2+uv+v^2.$$
A direct expansion shows that
$$\left(c^\ast\right)^2=\left(a^\ast\right)^2+\left(b^\ast\right)^2+a^\ast b^\ast.$$
Thus \((a^\ast,b^\ast,c^\ast)\) is a primitive integer \(120^\circ\) triangle, except that the two shorter sides are not automatically ordered. Every non-primitive solution is obtained by scaling:
$$ (a,b,c)=\lambda\bigl(\min(a^\ast,b^\ast),\max(a^\ast,b^\ast),c^\ast\bigr),\qquad \lambda \ge 1.$$
The counting problem is therefore reduced to generating primitive triangles and then determining how many scale factors \(\lambda\) remain legal.
Step 3: Convert the near-isosceles condition into a Pell-type equation
Write
$$r=u-v>0,\qquad u=v+r.$$
Then the difference between the two shorter sides becomes
$$b^\ast-a^\ast=2uv+v^2-(u^2-v^2)=3v^2-r^2.$$
Equivalently,
$$r^2-3v^2=d,\qquad d=-(b^\ast-a^\ast).$$
After ordering the shorter sides, their gap is exactly
$$\bigl|\max(a^\ast,b^\ast)-\min(a^\ast,b^\ast)\bigr|=|d|.$$
Scaling by \(\lambda\) multiplies every side difference by \(\lambda\), so the condition \(b-a \le 100\) becomes
$$\lambda |d| \le 100.$$
Therefore only nonzero integers \(d\) with \(|d|\le 100\) matter, and every primitive triangle for that \(d\) can be scaled only up to
$$1 \le \lambda \le \left\lfloor\frac{100}{|d|}\right\rfloor.$$
The case \(d=0\) would require \(r^2=3v^2\), impossible for positive integers, so the search really is over \(d\in\{-100,\dots,-1,1,\dots,100\}\).
Step 4: Solve the Pell-type equation orbit by orbit
For fixed \(d\), we must solve
$$r^2-3v^2=d,\qquad r>0,\quad v>0.$$
This is a Pell-type equation. Its positive solutions break into finitely many orbits under multiplication by the fundamental unit \(2+\sqrt{3}\). In coordinates, one forward step is
$$r' = 2r+3v,\qquad v' = r+2v.$$
If \((r,v)\) solves \(r^2-3v^2=d\), then so does \((r',v')\). The reverse unit \(2-\sqrt{3}\) gives
$$r_- = 2r-3v,\qquad v_- = -r+2v,$$
which preserves the same equation whenever both values stay positive. Repeating this reverse step until positivity would fail produces a reduced representative of the orbit. Starting from one reduced representative for each orbit and iterating forward generates every positive solution in that orbit.
Step 5: Reconstruct the triangle and count the valid scales
Once a solution \((r,v)\) is known, we recover
$$u=v+r,$$
$$a^\ast=u^2-v^2,\qquad b^\ast=2uv+v^2,\qquad c^\ast=u^2+uv+v^2.$$
The primitive triangle contributes all scaled copies with
$$1 \le \lambda \le \min\left(\left\lfloor\frac{100}{|d|}\right\rfloor,\left\lfloor\frac{N}{c^\ast}\right\rfloor\right).$$
Every such \(\lambda\) gives one admissible triangle after sorting the two shorter sides. Because repeated generation can occur, the implementation stores the final ordered triples in a set and counts each distinct triangle only once.
Worked Example
Take \(d=1\). Then
$$r^2-3v^2=1$$
has the positive solution \((r,v)=(2,1)\). Hence \(u=v+r=3\), so
$$a^\ast=3^2-1^2=8,\qquad b^\ast=2\cdot 3\cdot 1+1^2=7,\qquad c^\ast=3^2+3\cdot 1+1^2=13.$$
After ordering the shorter sides we obtain \((7,8,13)\), whose gap is indeed \(1\). For any bound \(N\ge 13\), the allowed scales are
$$1 \le \lambda \le \min\left(100,\left\lfloor\frac{N}{13}\right\rfloor\right).$$
Applying the forward recurrence once gives
$$ (r',v')=(2\cdot 2+3\cdot 1,\;2+2\cdot 1)=(7,4).$$
Now \(u=11\), which yields the primitive triangle \((104,105,181)\) after ordering. It again has short-side difference \(1\). This shows how one small value of \(d\) creates an infinite family, while the bound \(c\le N\) truncates the family to finitely many members.
How the Code Works
The C++, Python, and Java implementations all follow the same structure. They iterate through every signed difference parameter \(d\) with \(-100 \le d \le 100\) and \(d \ne 0\). For each \(d\), the maximum scale allowed by the near-isosceles restriction is precomputed as \(\lfloor 100/|d| \rfloor\).
Next, the implementation finds reduced positive solutions of the Pell-type equation \(r^2-3v^2=d\). Those reduced representatives are cached so that each orbit is discovered once. From every representative, the forward recurrence generated by \(2+\sqrt{3}\) is applied repeatedly. Each new pair \((r,v)\) produces one primitive triangle, and the orbit stops as soon as the corresponding \(c^\ast\) already exceeds \(N\).
For every primitive triangle, the two shorter sides are sorted, and every admissible scale factor
$$1 \le \lambda \le \min\left(\left\lfloor\frac{100}{|d|}\right\rfloor,\left\lfloor\frac{N}{c^\ast}\right\rfloor\right)$$
is tested. The resulting ordered triple is inserted into a set, which guarantees exact deduplication. Two useful checkpoints for this method are \(T(1000)=235\) and \(T(10^8)=1245\), after which the same machinery is applied to \(N=10^{100}\).
Complexity Analysis
The outer loop over \(d\) has constant size, since only \(200\) nonzero values are relevant. Along any fixed Pell orbit, the quantities \(r\), \(v\), and \(c^\ast\) grow roughly by the factor \(2+\sqrt{3}\), so the number of primitive triangles with \(c^\ast \le N\) is \(O(\log N)\) on that orbit. The number of scale factors per primitive triangle is at most \(100\), which is also a constant.
If \(M\) denotes the number of candidate triangles produced before deduplication, then generation is essentially linear in \(M\). Deduplication costs \(O(M\log M)\) in a tree-based set model, or near-linear expected time with hash-based sets. Memory usage is \(O(M)\). In practice this is tiny compared with any direct search over side lengths.
Footnotes and References
- Problem page: https://projecteuler.net/problem=582
- Law of cosines: Wikipedia — Law of cosines
- Pell's equation: Wikipedia — Pell's equation
- Eisenstein integers: Wikipedia — Eisenstein integer
- Diophantine equations: Wikipedia — Diophantine equation
Problem 582 source code
C++
#include <algorithm>
#include <cmath>
#include <cstdint>
#include <iostream>
#include <map>
#include <set>
#include <utility>
#include <vector>
#include <boost/multiprecision/cpp_int.hpp>
// Project Euler 582: Integer-sided 120-degree triangles with b-a <= 100
//
// With a <= b <= c and the 120-degree angle opposite c, the law of cosines gives:
// c^2 = a^2 + b^2 + ab.
//
// Parameterization via Eisenstein integers:
// Let m > n > 0 and define (a0,b0,c0):
// a0 = m^2 - n^2
// b0 = 2mn + n^2
// c0 = m^2 + mn + n^2
// Then c0^2 = a0^2 + b0^2 + a0*b0.
// Every integer solution with gcd(a,b)=1 is a unit multiple of such a triple, and scaling by k
// gives all solutions:
// (a,b,c) = k*(a0,b0,c0).
//
// The difference satisfies:
// b0 - a0 = 2n^2 + 2mn - m^2.
// Setting X = m - n > 0, this becomes:
// b0 - a0 = -(X^2 - 3n^2) = t,
// i.e. solutions correspond to Pell-type equations:
// X^2 - 3n^2 = -t, with 1 <= t <= 100.
//
// For fixed t, all positive solutions (X,n) are generated from finitely many fundamental ones
// by multiplication with the fundamental unit 2+sqrt(3):
// (X',n') = (2X + 3n, X + 2n).
//
// For each solution we compute c0 and count admissible scaling factors k:
// 1 <= k <= floor(100/t) and k*c0 <= N => k <= min(floor(100/t), floor(N/c0)).
//
// We sum this over all t and all solutions.
using boost::multiprecision::cpp_int;
using u64 = std::uint64_t;
using i64 = std::int64_t;
struct Sol {
u64 X = 0;
u64 n = 0;
bool operator<(const Sol& o) const { return (X < o.X) || (X == o.X && n < o.n); }
};
static Sol reduce_solution(Sol s) {
// Multiply by (2 - sqrt(3)) repeatedly while staying positive to reach a minimal orbit rep.
while (true) {
const i64 X = (i64)s.X;
const i64 n = (i64)s.n;
const i64 Xp = 2 * X - 3 * n;
const i64 np = -X + 2 * n;
if (Xp <= 0 || np <= 0) break;
s.X = (u64)Xp;
s.n = (u64)np;
}
return s;
}
static std::vector<Sol> fundamental_solutions(int S) {
// Brute small n to find solutions, then reduce to orbit representatives.
std::set<Sol> reps;
for (int n = 1; n <= 500; ++n) {
const long long v = 3LL * n * n + S;
if (v <= 0) continue;
const long long x = (long long)std::llround(std::floor(std::sqrt((long double)v)));
for (long long X = std::max(1LL, x - 2); X <= x + 2; ++X) {
if (X * X != v) continue;
Sol s{(u64)X, (u64)n};
reps.insert(reduce_solution(s));
}
}
return std::vector<Sol>(reps.begin(), reps.end());
}
static cpp_int c0_from_Xn(const cpp_int& X, const cpp_int& n) {
// c0 = 3n^2 + 3Xn + X^2
return 3 * n * n + 3 * X * n + X * X;
}
static u64 T(const cpp_int& N) {
struct Tri {
cpp_int a, b, c;
bool operator<(const Tri& o) const {
if (a != o.a) return a < o.a;
if (b != o.b) return b < o.b;
return c < o.c;
}
};
std::set<Tri> uniq;
// Cache fundamental solutions per signed RHS S (X^2 - 3n^2 = S).
std::map<int, std::vector<Sol>> cache;
for (int S = -100; S <= 100; ++S) {
if (S == 0) continue;
const int diff = std::abs(S);
const int kmax = 100 / diff;
if (kmax == 0) continue;
auto& reps = cache[S];
if (reps.empty()) reps = fundamental_solutions(S);
for (const auto& rep : reps) {
cpp_int X = rep.X;
cpp_int n = rep.n;
while (true) {
const cpp_int m = n + X;
const cpp_int A = m * m - n * n; // m^2 - n^2
const cpp_int B = 2 * m * n + n * n; // 2mn + n^2
const cpp_int C = m * m + m * n + n * n; // m^2 + mn + n^2
if (C > N) break;
const cpp_int a0 = std::min(A, B);
const cpp_int b0 = std::max(A, B);
for (int k = 1; k <= kmax; ++k) {
const cpp_int kk = k;
const cpp_int c = kk * C;
if (c > N) break;
uniq.insert(Tri{kk * a0, kk * b0, c});
}
// Next (X,n): multiply by 2+sqrt(3).
const cpp_int Xnxt = 2 * X + 3 * n;
const cpp_int nnxt = X + 2 * n;
X = Xnxt;
n = nnxt;
}
}
}
return (u64)uniq.size();
}
static cpp_int pow10(int e) {
cpp_int x = 1;
for (int i = 0; i < e; ++i) x *= 10;
return x;
}
int main() {
// Validation points from the statement.
const u64 t1000 = T(cpp_int(1000));
if (t1000 != 235ULL) {
std::cerr << "Validation failed: T(1000) got " << t1000 << "\n";
return 1;
}
const u64 t1e8 = T(cpp_int(100000000));
if (t1e8 != 1245ULL) {
std::cerr << "Validation failed: T(1e8) got " << t1e8 << "\n";
return 1;
}
const cpp_int N = pow10(100);
std::cout << T(N) << "\n";
return 0;
}
Python
import math
def reduce_solution(X, n):
while True:
Xp = 2 * X - 3 * n
np = -X + 2 * n
if Xp <= 0 or np <= 0:
break
X, n = Xp, np
return (X, n)
def fundamental_solutions(S):
reps = set()
for n in range(1, 501):
v = 3 * n * n + S
if v <= 0:
continue
x = round(math.sqrt(v))
for X in range(max(1, x - 2), x + 3):
if X * X == v:
reps.add(reduce_solution(X, n))
return list(reps)
def solve():
N = 10**100
cache = {}
uniq = set()
for S in range(-100, 101):
if S == 0:
continue
diff = abs(S)
kmax = 100 // diff
if kmax == 0:
continue
if S not in cache:
cache[S] = fundamental_solutions(S)
for rep in cache[S]:
X, n = rep
while True:
m = n + X
A = m * m - n * n
B = 2 * m * n + n * n
C = m * m + m * n + n * n
if C > N:
break
a0 = min(A, B)
b0 = max(A, B)
for k in range(1, kmax + 1):
c = k * C
if c > N:
break
uniq.add((k * a0, k * b0, c))
Xnxt = 2 * X + 3 * n
nnxt = X + 2 * n
X, n = Xnxt, nnxt
return str(len(uniq))
if __name__ == '__main__':
print(solve())
Java
import java.math.BigInteger;
import java.util.*;
public class Euler582 {
static class Sol implements Comparable<Sol> {
long X, n;
Sol(long X, long n) {
this.X = X;
this.n = n;
}
public int compareTo(Sol o) {
if (this.X != o.X)
return Long.compare(this.X, o.X);
return Long.compare(this.n, o.n);
}
public boolean equals(Object obj) {
if (!(obj instanceof Sol))
return false;
Sol o = (Sol) obj;
return this.X == o.X && this.n == o.n;
}
public int hashCode() {
return Objects.hash(X, n);
}
}
static class Tri {
BigInteger a, b, c;
Tri(BigInteger a, BigInteger b, BigInteger c) {
this.a = a;
this.b = b;
this.c = c;
}
public boolean equals(Object obj) {
if (!(obj instanceof Tri))
return false;
Tri o = (Tri) obj;
return a.equals(o.a) && b.equals(o.b) && c.equals(o.c);
}
public int hashCode() {
return Objects.hash(a, b, c);
}
}
static Sol reduce_solution(long X, long n) {
while (true) {
long Xp = 2 * X - 3 * n;
long np = -X + 2 * n;
if (Xp <= 0 || np <= 0)
break;
X = Xp;
n = np;
}
return new Sol(X, n);
}
static List<Sol> fundamental_solutions(int S) {
Set<Sol> reps = new TreeSet<>();
for (long n = 1; n <= 500; ++n) {
long v = 3 * n * n + S;
if (v <= 0)
continue;
long x = Math.round(Math.sqrt(v));
for (long X = Math.max(1, x - 2); X <= x + 2; ++X) {
if (X * X == v) {
reps.add(reduce_solution(X, n));
}
}
}
return new ArrayList<>(reps);
}
public static String solve() {
BigInteger N = BigInteger.TEN.pow(100);
Set<Tri> uniq = new HashSet<>();
Map<Integer, List<Sol>> cache = new HashMap<>();
for (int S = -100; S <= 100; ++S) {
if (S == 0)
continue;
int diff = Math.abs(S);
int kmax = 100 / diff;
if (kmax == 0)
continue;
if (!cache.containsKey(S)) {
cache.put(S, fundamental_solutions(S));
}
for (Sol rep : cache.get(S)) {
BigInteger X = BigInteger.valueOf(rep.X);
BigInteger n = BigInteger.valueOf(rep.n);
while (true) {
BigInteger m = n.add(X);
BigInteger A = m.multiply(m).subtract(n.multiply(n));
BigInteger B = m.multiply(n).multiply(BigInteger.valueOf(2)).add(n.multiply(n));
BigInteger C = m.multiply(m).add(m.multiply(n)).add(n.multiply(n));
if (C.compareTo(N) > 0)
break;
BigInteger a0 = A.min(B);
BigInteger b0 = A.max(B);
for (int k = 1; k <= kmax; ++k) {
BigInteger kk = BigInteger.valueOf(k);
BigInteger c = kk.multiply(C);
if (c.compareTo(N) > 0)
break;
uniq.add(new Tri(kk.multiply(a0), kk.multiply(b0), c));
}
BigInteger Xnxt = X.multiply(BigInteger.valueOf(2)).add(n.multiply(BigInteger.valueOf(3)));
BigInteger nnxt = X.add(n.multiply(BigInteger.valueOf(2)));
X = Xnxt;
n = nnxt;
}
}
}
return Integer.toString(uniq.size());
}
public static void main(String[] args) {
System.out.println(solve());
}
}