A bit is a binary classical symbol with two distinguishable values, zero and one. A uniform random bit has one bit of information entropy, while a biased binary symbol has less. Sending one bit means transmitting one symbol from this binary alphabet; the mutual information it carries about a particular input need not be one.
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- AAPCS32
- Adder
- Address bus
- Address translation
- Analog-to-digital converter
- An observation can increase entropy
- Approximate quantum counting
- Arithmetic right shift
- ARM architecture family
- Asymptotic remote state preparation by block indexing
- Balanced Boolean function
- Barrel shifter
- Bell correlations versus a classical mixture
- Bernoulli typical-set example
- Binary addition in logarithmic space
- Binary array sum by recursion
- Binary-coded decimal
- Binary counter
- Binary cross-entropy
- Binary entropy
- Binary Markov source
- Binary multiplication
- Binary numeral system
- Binary rate-distortion function
- Binary symmetric channel
- Binary symmetric channel capacity
- Binary translation of a quaternary prefix code
- Birthday probability for hash outputs
- Bit
- Bit complexity
- Bit cost of modular exponentiation
- Bit rate
- Bit rotation
- Bit-serial comparator
- Bit stuffing
- Bit vector
- Block allocation bitmap
- Block code for line coding
- Boltzmann entropy of a two-box occupancy
- Boolean operation
- Borrow
- Buffer cache state model
- Byte
- Cache line
- Carry flag
- Chain decomposition of total correlation
- Chain rule for information entropy
- Chain rule for mutual information
- Channel capacity
- Channel code
- Channel feedback
- CHSH game
- Classical communication lower bound for exact qubit teleportation
- Classical query complexity of linear Boolean function identification
- Clock edge
- CLOCK page replacement
- Coding theory
- Comparator composition
- Conditional entropy
- Conditional expectation choice invariant
- Conditional expectation cut formula
- Conditional expectations algorithm cost
- Conditional expectations cut example
- Conditional expectations for maximum cut
- Conditional mutual information
- Conditioning can destroy independence
- Conditioning reduces entropy
- Coplanar qubit realization of the chained Bell inequality
- Correlated binary variables
- Count leading zeros
- Cross-entropy
- Cyclic ternary channel capacity
- Data compression
- Data processing inequality
- Debounced toggle switch
- Decision tree
- Decision-tree depth
- Decision-tree query cost
- Deflate block framing
- Deflate compression overhead
- Deflate Huffman coding
- Deflate literal byte
- De Morgan dual of a Boolean function
- Dephasing channel
- Differential entropy
- Differential Manchester encoding
- Digital comparator
- Digital register
- Discrete memoryless channel
- Distinct witnesses from incompatible unary predicates
- Double-precision floating-point format
- Entanglement-assisted capacity of a qubit depolarizing channel
- Entropy rate
- Entropy rate and coding length
- Equality in data processing inequality
- Exclusive or
- Exclusive or toggles and parity
- Expected query cost
- Factorial recursion and returning frames
- Fano's inequality
- Fano's inequality via an error indicator
- Field with four elements
- File-system allocation bitmap
- Finite field
- Fixed-length lossy code
- Flip-flop
- Flips versus erasures in a binary channel
- Floating-point addition
- Function oracle
- GHZ-assisted quantum teleportation
- Gray-code counter
- Grayscale
- Half adder
- Half-precision floating-point format
- Hierarchical leading-zero counter
- Huffman code
- Huffman coding
- Huffman sibling contraction
- Huffman sibling property
- Independent events
- Independent random variables
- Independent revelation of a binary variable
- Indexing within a type class
- Information entropy
- Information entropy dominates min-entropy
- Information theory
- Innovations in a binary Markov source
- Input distribution optimization for a binary symmetric channel
- Instruction encoding
- Joint entropy
- Journal replay
- Karatsuba practical crossover
- Karnaugh map
- Kullback-Leibler divergence
- Leaf depth in a code tree
- Logical right shift
- Logic gate
- Logspace composition by recomputation
- Lossy block averaging
- Lossy compression
- Machine word
- Manchester code
- Memoization arithmetic and stack costs
- Min-entropy
- Minority Boolean function
- MIPS architecture
- MIPS I-type instruction
- MIPS R-type instruction
- Modulo-six counter
- Multi-level page table
- Multiplexer
- Mutual information
- Nat (unit)
- Negation
- Noisy parity total correlation
- Nonunique optimal prefix code
- NOT gate
- One-bit heralding of a remote state preparation block
- Optimal prefix code
- Packed restoring division
- Page-reference trace
- Page writeback
- Paging
- Pairwise independence does not imply joint independence
- Pairwise independent events
- Parity constraint and total correlation
- Parity construction of pairwise independent bits
- Parity lower bound for Boolean queries
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- Pixel
- Prefix code for a rare geometric success
- Quadratic-size formula with prescribed model count
- Quantization (signal processing)
- Quantum information
- Quantum information theory
- Radix sort key encoding
- Ramsey number for triangles
- Random evaluation test for a polynomial identity
- Randomized algorithm
- Raster graphics
- Rate-distortion function
- Rate-distortion theory
- Read-only memory
- Reconstruction alphabet
- Recursive process
- Reduced instruction set computer
- Register file
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- Repetition code
- Ripple counter
- Round-robin arbitration
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- Truth value
- Two-level address translation
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A "bit" is the most basic unit of information in computing and digital communications. The term "bit" is short for "binary digit." A bit can have one of two possible values: 0 or 1. In binary notation, these bits are used to represent various forms of data, including numbers, text, images, and more. Bits are fundamental to the workings of computers and digital systems, as they underpin all digital data processing.