---
description: The terms WARM uses, defined as this code uses them, with a pointer to where each is explained or measured.
---
# Glossary
Terms are defined as this code and these docs use them. Where a term is measured, the entry
points at the page and the committed results file.
## Vector-symbolic memory
Hypervector
: A very long vector, thousands of dimensions, used as a code for a thing. Unrelated
hypervectors are nearly orthogonal, so random ones almost never collide. WARM uses sparse
binary hypervectors (`EntangledHVec`): `D` dimensions with about `D/256` bits set. See
[What "holographic" means here](../concepts/holographic.md).
Atom
: The hypervector for a name, relation or word. Generated deterministically from a hash seed,
so the same atom is the same vector in every process and no codebook is stored.
Bind
: Combine two hypervectors into one that resembles neither, used to tie a role to a filler.
On sparse index sets it is the symmetric difference (XOR). Binding the result with the role
again recovers a noisy copy of the filler.
Bundle
: Superpose many hypervectors into one that stays similar to each of them, by counting per
index and keeping the indices above a threshold. The bundle cannot list its members; it can
only be asked whether a given item resembles it.
Permute
: A cyclic shift of every index. It encodes order: `bind_ordered(a, b)` differs from
`bind_ordered(b, a)`.
Superposition
: Several items stored in the same vector at once. Capacity is finite; see
[Capacity limits](../concepts/capacity.md) for the tested range.
Resonance
: Recalling an item by similarity: unbind with a key, then find the stored vector the result
most resembles. The interactive demo on the [home page](../index.md) shows it with
dense binary vectors.
Cleanup
: Snapping a noisy vector back to the nearest stored atom. WARM uses a modern Hopfield network
(sparse softmax attention over the stored atoms) for it.
Resonator network
: A network that factors a bound product back into its parts by iterating cleanup on each
factor in turn.
Meaning memory
: The optional layer that stores facts as composite vectors and answers relational and
multi-hop queries. It is where the algebra is used; document search is not.
Triple
: A `(subject, relation, object)` fact. The triple store keeps an exact symbolic index next to
the composite vectors.
Superposition floor
: The ratio of stored pairs `M` to dimensions `D` beyond which blind recovery from a random-code
superposition fails; measured near `M/D = 0.27`. It is a property of the random code, not an
information-theoretic wall. See [Superposition floor](../SUPERPOSITION-FLOOR.md).
## Document search
Chunk
: A passage of a document, 256 words by default. A chunk keeps its text, stemmed term counts,
optional embeddings you supply, and its byte range in the source.
Byte-offset hit
: A search result that carries the passage text and the start and end byte of that passage in
the source document, so a UI can highlight it.
BM25
: The lexical ranking function WARM uses over stemmed terms (Porter/Snowball English).
Exact cosine
: Dense similarity computed against every stored embedding, with no approximation.
Hybrid search
: BM25 and exact cosine run together and fused, by a min-max normalised blend by default or by
reciprocal rank fusion (`fusion: "rrf"`).
RRF (reciprocal rank fusion)
: Combining ranked lists by summing the inverse of each item's rank in each list.
## Storage
Store
: A directory holding one engine's data. It persists there and reopens with the same
arguments.
Arena
: The memory-mapped segmented log that holds vector and document frames. Compaction writes a
new generation and swaps it in atomically. See
[Production readiness](../production-readiness.md).
Tenant
: One isolated store inside `warm-server`. A client names its tenant on every request.
## Measurement
nDCG@10
: Normalised discounted cumulative gain over the top 10 results: a rank-aware relevance score
from 0 to 1.
Recall@k
: The share of the true top-k neighbours (or relevant documents) that appear in the first `k`
results.
QPS
: Queries per second. WARM benchmarks report single-threaded QPS, one query at a time.
ANN
: Approximate nearest neighbour search: a faster index that may miss true neighbours.
HNSW
: Hierarchical navigable small-world graph, the ANN index used by FAISS, hnswlib and Lucene,
the comparison baselines.
VGraph
: WARM's quantized graph index in `core::qgraph::vertex`: a Vamana-style graph with one
low-bit code per vertex and a residual code for the re-rank. See the
[benchmarks](../PUBLIC-BENCHMARKS.md).
Load gate
: The rule that a timing run counts only if the machine's one-minute load average is below a
set limit. Runs above it are reported but marked indicative.
Dev split
: The frozen set of questions used for tuning. Held-out questions are not touched until a
final single run.