Binary Exponentiation & Modular Arithmetic
From “Why is this confusing?” to “This is obvious now”
Some concepts in computer science don’t feel hard because they are complex —
they feel hard because we try to compute instead of understanding.
Binary exponentiation is one such concept.
This blog captures a real learning journey:
starting with confusion around large exponents and modular arithmetic,
and ending with a clear, reusable mental model you’ll never forget.
1. The Problem That Started It All
We were asked to compute:
At first glance, it feels intimidating:
101 is a large exponent
Direct multiplication is impossible
Modulo arithmetic feels tricky
But the key realization is this:
The problem is not “big numbers” — the problem is “wrong approach”.
2. Why Naive Exponentiation Fails
The naive way:
2 × 2 × 2 × … (101 times)
Problems:
Takes O(n) time
Numbers grow extremely large
Completely impractical in real systems
In cryptography, competitive programming, and system algorithms, this approach is unusable.
So the question becomes:
How do we reduce 101 multiplications to just a few?
3. The First Breakthrough: Binary Representation
Instead of working in decimal, we switch to binary.
Convert exponent to binary
101₁₀ = 1100101₂
This means:
101 = 64 + 32 + 4 + 1
So we rewrite:
2¹⁰¹ = 2⁶⁴ × 2³² × 2⁴ × 2¹
This single step changes everything.
4. The Core Idea: Binary Exponentiation
Binary exponentiation works using repeated squaring:
2¹
2² = (2¹)²
2⁴ = (2²)²
2⁸ = (2⁴)²
2¹⁶ = (2⁸)²
2³² = (2¹⁶)²
2⁶⁴ = (2³²)²
Now we only need log₂(101) ≈ 7 squaring operations.
Time Complexity
✅ O(log n)
instead of
❌ O(n)
This is why binary exponentiation is foundational in:
cryptography
modular arithmetic
competitive programming
5. Why Modulo Makes This Even Better
A critical rule of modular arithmetic:
(a × b) mod m = ((a mod m) × (b mod m)) mod m
This means:
We can reduce at every step
Numbers never become large
Correctness is preserved
This rule was the source of early confusion — and the source of clarity once understood.
6. Watching the Pattern Emerge (mod 7)
Now compute powers of 2 modulo 7:
| Power | Value | mod 7 |
|---|---|---|
| 2¹ | 2 | 2 |
| 2² | 4 | 4 |
| 2⁴ | 16 | 2 |
| 2⁸ | 4 | 4 |
| 2¹⁶ | 2 | 2 |
| 2³² | 4 | 4 |
| 2⁶⁴ | 2 | 2 |
🔁 Pattern discovered:
Powers of 2 modulo 7 alternate between 2 and 4
This is the “aha moment”.
Now suddenly:
2³² ≡ 4 (mod 7)
makes complete sense.
7. Final Computation: 2¹⁰¹ mod 7
Recall:
2¹⁰¹ = 2⁶⁴ × 2³² × 2⁴ × 2¹
Substitute modulo values:
2⁶⁴ ≡ 2
2³² ≡ 4
2⁴ ≡ 2
2¹ ≡ 2
Multiply:
2 × 4 × 2 × 2 = 32
Reduce:
32 mod 7 = 4
✅ Final Answer
2¹⁰¹ ≡ 4 (mod 7)
That’s why the board confidently ends with:
32 ≡ 4 (mod 7)
8. The Algebra That Explains Everything
Another key clarification came from algebra:
If:
a = d·q₁ + r₁
b = d·q₂ + r₂
Then:
a·b = d·(…) + r₁·r₂
Which means:
(a·b) % d = (r₁·r₂) % d
In plain English:
Only remainders matter in modular multiplication.
This is the mathematical backbone of modular exponentiation.
9. The Mental Model You Should Remember Forever
Binary Exponentiation
“Build the exponent using binary bits and repeated squaring.”
Modular Exponentiation
“Reduce at every step so numbers never grow.”
If you remember just this, you’ll never be stuck again.
10. One-Line Viva / Interview Answer
“Binary exponentiation computes a^b in O(log b) time by repeated squaring, and modular reduction at each step keeps numbers small while preserving correctness.”
11. Why This Matters Beyond Exams
This isn’t just math.
This thinking appears in:
encryption
hashing
distributed systems
performance optimization
It trains you to:
look for structure
avoid brute force
reason about patterns
trust mathematics instead of raw computation
Final Takeaway
This session proved something important:
Confusion is not a weakness — it’s a signal that understanding is forming.
Once the structure is visible, the solution feels inevitable.
Binary exponentiation stops being a trick and becomes a tool you own.
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