Open research mathematics, native to Node

See what exists.
See how good it is.
See what comes next.

This is the living implementation map for Sage.js: concrete capabilities, evidence about their maturity, and a prioritized research roadmap.

Explore capabilities View source

Start using Sage.js

One command, or one npm package.

Native installer

Downloads the release for your platform and verifies its SHA-256 checksum.

curl -fsSL https://github.com/sagemathinc/sagejs/releases/latest/download/install.sh | sh

Native preview v0.1.1 · Linux x64/arm64, Windows x64, macOS arm64

npm

Installs the Sage.js command line and JavaScript embedding package.

npm install -g @sagemath/sagejs

npm preview v0.1.0 · the unified v0.2 release is next

sagejs --install-jupyter-kernel adds Sage.js to JupyterLab, CoCalc, or another Jupyter environment.

Implementation map

Capabilities and evidence

Status says whether something works, confidence says how strongly it is tested, and scope says how much of the mathematical surface is present.

Certified: exact semantics cross-checked Tested: focused regression coverage Prototype: useful, deliberately narrow Planned: designed or prioritized

Scope is independent of confidence. Broad surface covers most everyday workflows in that area; Substantial slice covers several coherent API families; Focused slice is deliberately narrower; Foundation exposes core building blocks for the next layer. Measured scores always state numerator, denominator, unit, reference, and audit date; ~ estimates are explicitly labeled expert workflow estimates. “Audit pending” is shown when no defensible denominator exists yet. Open Scope for the method and searchable API-family inventory.

Competitive audit

Every capability has a concrete next lane.

Scope denominators, independent comparison systems, representative workflows, and performance cases are tracked separately. Open Competitive audit on any capability to see its proposed unit of completion and a stable gap ID suitable for parallel work.

—primary gap lanes

—existing benchmark suites

—planned benchmark suites

—comparison-system families

Measured performance

One transparent pilot, not an opaque score

Median elapsed time logarithmic visual scale

System	Operation	Proof semantics	Median

Environment and reproduction command

Priorities

The next research frontier

Priority is independent of maturity: mature foundations still need optimization and broader interfaces.

How quality is judged

Readable implementation. Independent truth.

Sage-compatible semantics

SageMath is the default behavioral specification. Intentional differences are documented and tested.

Multiple mathematical oracles

PARI/GP, Magma, Oscar, Hecke, and Nemo provide independent answers and performance reference points.

Evidence before labels

Focused regressions, exhaustive small cases, randomized differential tests, and benchmarks support maturity claims.

Readable research software

Algorithms should be understandable and changeable by mathematicians and agents, with native kernels where speed matters.