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Log Base 2 Calculator

Calculate the binary logarithm (log base 2) of any positive number. Log base 2 answers the question: "2 raised to what power equals this number?" It is fundamental in computer science, information theory, binary systems, and algorithm complexity analysis.

Formula

log₂(x) = ln(x) / ln(2) = log₁₀(x) / log₁₀(2)

The binary logarithm can be computed using the change of base formula. Since ln(2) ≈ 0.693147, you can divide the natural log of any number by 0.693147 to get its log base 2.

Log Base 2 Reference Table

xlog₂(x)Meaning
102^0 = 1
212^1 = 2
422^2 = 4
832^3 = 8
1642^4 = 16
3252^5 = 32
6462^6 = 64
12872^7 = 128
25682^8 = 256
51292^9 = 512
1,024102^10 = 1,024
2,048112^11 = 2,048
4,096122^12 = 4,096
8,192132^13 = 8,192
65,536162^16 = 65,536
1,048,576202^20 = 1,048,576

Frequently Asked Questions

What is log base 2 used for?

Log base 2 is used in computer science (binary search has O(log₂ n) complexity), information theory (bits of information), audio engineering (octaves), and any system based on powers of 2.

What is log₂(1)?

log₂(1) = 0, because 2⁰ = 1. The logarithm of 1 in any base is always 0.

What is log₂(0)?

log₂(0) is undefined. The logarithm of zero does not exist because no power of 2 can equal zero.

How is log₂ related to bits?

The number of bits needed to represent N distinct values is ⌈log₂(N)⌉. For example, 256 values need log₂(256) = 8 bits (1 byte).

Log Base 2 vs Log Base 10 vs Natural Log

The three most common logarithm bases serve different purposes. Log base 2 (binary logarithm, lb) is fundamental in computer science and information theory — it tells you how many bits are needed to represent a value. Log base 10 (common logarithm, log) is used in engineering, decibel calculations, pH chemistry, and the Richter scale. Natural log (ln, base e ≈ 2.718) appears in calculus, continuous growth/decay, and physics. They are all related by the change of base formula: log_b(x) = ln(x) / ln(b).

Applications in Computer Science

  • Algorithm complexity: Binary search runs in O(log₂ n) time — searching 1 million items takes only 20 comparisons
  • Data structures: Balanced binary trees (AVL, Red-Black) have height log₂(n), giving O(log n) lookup
  • Information theory: Shannon entropy measures information in bits using log₂ — coined by Claude Shannon in 1948
  • Networking: IP subnetting uses powers of 2 — a /24 subnet has 2⁸ = 256 addresses
  • Audio: Each octave doubles frequency — the number of octaves between two frequencies is log₂(f₂/f₁)
  • Compression: Huffman coding efficiency is measured against the entropy (log₂-based) of the source

Powers of 2 in Computing

Understanding log base 2 is inseparable from understanding powers of 2 in computing. Memory sizes (RAM, storage), bus widths, color depths, and addressing all use powers of 2. A 32-bit system can address 2³² = 4,294,967,296 bytes (4 GB). A 64-bit system can theoretically address 2⁶⁴ = 18.4 exabytes. The log₂ of these values tells you the bit width needed: log₂(4 GB) = 32 bits.