Bit depth
The number of bits used per sample, setting how finely amplitude is quantised.
At a glance
Key signals
0% cross fields · reaches 1 more
- Signal Processing
- Audio Engineering
- Explanation
- Examples
- Misconception
- Sourced relations 3
- Attribution
Dependencies
What this concept builds on and what it makes possible — derived from the atlas’s dependency, causal and structural relations, not from every related edge.
Enables · leads to
Dynamic rangedepends onBit depthEstablished
dynamic range depends on bit depth.
Mechanism: In digital audio the usable dynamic range is set by the bit depth.
- Wikipedia (English & German editions) verifiedmoderate evidence
System context
Bit depthis part ofDigital audioEstablished
bit depth is part of digital audio.
Mechanism: Bit depth is one of the two numbers (with sample rate) defining a PCM format.
- Wikipedia (English & German editions) verifiedmoderate evidence
Structural role & consequence
Interpreted from the current atlas graph — what the connections mean, not just how many there are.
Currently dark in the atlas: no key date stored · 3 of 3 of its relations lack claim-level evidence.
atlas representation · Describes the current Thinking OS representation, not the state of the world.
Exercises 2 annotated mental models — a concept that connects several thinking patterns.
curated · Curated annotations, not a derived measure.
Structural neighbourhood: 3 → 16 → 53 concepts reachable within 3 hops.
structural · Structural reach — being reachable is not the same as being understood.
All 3 of its relationships stay within its own discipline — a field-specific concept in the current atlas.
structural · Structural graph analysis — not a claim of importance, causation or history.
cross-field
3 within-field, 0 cross-field
Strengths & constraints
Constraints
- Evidence coverage currently thin in the atlas — few of its relationships carry claim-level evidence. atlas representation
- No dated history stored — the atlas records no key date for this concept. atlas representation
Conditions
- Read structurally — most of its relationships carry no external evidence yet, so claims here are graph-derived. structural
Dependency radial
What this concept builds on (left) and what it makes possible (right) — derived from dependency and causal relations.
What builds on this
1 concept build on this directly, 1 in total, across 3 disciplines.
Structural downstream reach along dependency edges — not a claim of historical necessity.
Seen through each discipline
How this concept sits in each of its fields — derived from its real connections in the graph, not asserted.
Through this lens it connects to Digital audio, Dynamic range and Quantization noise.
Through this lens it connects to Digital audio and Dynamic range.
Related ideas to explore
Concepts that look related but are not yet connected here — candidates for a connection to reason about, not established links.
This idea also appears in…
The same structure shows up in other disciplines. These are real recurrences drawn from the graph — a starting point for asking “what carries over, and what changes?”
Information36 disciplines · 32 concepts
Trade-offs42 disciplines · 33 concepts
Concepts
shares a mental model
shares a mental model
shares a mental model
shares a mental model
shares a mental model
shares a mental model
Mental models at work here
Information
Anything that reduces uncertainty. It can be encoded into a signal, sent across a channel, and decoded — and noise can corrupt it on the way.
Ask: what did the receiver not know before, and what does the message let them rule out?
Trade-offs
When getting more of one thing means accepting less of another, because resources or constraints are limited.
Ask what you give up (the opportunity cost) to gain what you want.
- Connects 3 other ideas across 2 disciplines.
- Most of its connections are of the “Kind & structure” kind.
- It exercises 2 reusable thinking patterns.
Derived from the graph’s real structure — observations, not a score.
Sources
- Wikipedia (English & German editions) verifiedmoderate evidence
- Bit-depth scalable video coding using inter-layer prediction from high bit-depth layer (2009) verified
- Filter-Flow-Based Bit-Depth Expansion (2022) verified