kshana 0.27.3

क्षण — Sanskrit for the precise instant, the smallest measure of time.
Open, reproducible PNT (positioning, navigation and timing) resilience simulation with published quantum-sensor performance models.

Kshana is an open, reproducible PNT-resilience simulator with quantum-sensor performance models — PNT being positioning, navigation, and timing. This package is a thin PyO3 (abi3, the stable Python binary interface) wrapper over the same Rust engine: you pass a scenario TOML (Tom's Obvious, Minimal Language) string in and get a reproducible JSON (JavaScript Object Notation) result back. It quantifies, in hard numbers, what quantum clocks, quantum inertial sensors, and optical time-transfer buy a navigation system over classical PNT. Every result is reproducible from scenario + seed + engine version, and every sensor parameter is traceable to a published source.

Validated, not asserted. 666/666 AIAA (American Institute of Aeronautics and Astronautics) SGP4 (Simplified General Perturbations 4, the standard satellite-orbit propagator) vectors to 4.12 mm · Cowell force model 0.08 m vs Orekit 12.2 · Galileo 0.61 m / Swarm-A 0.10 m vs real ESA (European Space Agency) precise ephemerides · GCRS→ITRS (Geocentric Celestial Reference System to International Terrestrial Reference System) bit-for-bit vs SOFA/ERFA (the International Astronomical Union's Standards of Fundamental Astronomy library and its open port, Essential Routines for Fundamental Astronomy) · ML (machine-learning) metrics exact vs scikit-learn · 65 of 171 capabilities validated against independent external oracles; 102 honestly labelled Modelled, 4 partner-owned.

Validated against external oracles — every row gated in continuous integration

Each row is checked against an independent external oracle (real dataset, independent reference implementation, or published reference vectors) and re-checked in CI (continuous integration).

Install

pip install kshana

Wheels are built for Linux, macOS, and Windows on each release tag. To build from source instead, use maturin: pip install maturin && maturin develop --features python.

Usage

The example is complete: it carries its own scenario, so it runs as written with nothing else on disk.

import json, kshana

# A complete scenario, not a sketch: scenarios/clock-holdover.toml without its comment
# lines. It runs 2 h, 10 min of GNSS then about 1.8 h with GNSS denied, and asks how long
# a strontium optical clock and a chip-scale atomic clock (CSAC) each hold time to within
# 20 ns. sigma_y(1s) is a clock's Allan deviation at an averaging time of one second;
# q_wf, the white-frequency-noise intensity, is its square.
toml = """
seed = 42
threshold_ns = 20.0

[time]
step_s = 10.0
duration_s = 7200.0

[gnss]
windows = [
  { t0 = 0.0,    t1 = 600.0,  state = "nominal" },
  { t0 = 600.0,  t1 = 7200.0, state = "denied" },
]

[clock_quantum]
id = "optical-sr-lattice"
provenance = "Strontium optical lattice clock, space-oriented goal sigma_y(1s)=1e-15 (Origlia/Schiller/Bongs et al., arXiv:1503.08457); q_wf=sigma_y(1s)^2; ground-demonstrator maturity, not flown; flicker/aging not modeled"
y0   = 5.0e-17
q_wf = 1.0e-30
q_rw = 0.0

[clock_classical]
id = "csac-sa45s"
provenance = "Microchip SA65 / SA.45s CSAC datasheet sigma_y(1s)=3e-10; q_wf=sigma_y(1s)^2; flicker/aging not modeled"
y0   = 5.0e-10
q_wf = 9.0e-20
q_rw = 0.0
"""

result = json.loads(kshana.run(toml))       # the full result document
print(result["quantum"]["fom"]["integrity"])

# The JSON result, the chart as SVG (Scalable Vector Graphics) and a one-line summary,
# all from one engine run:
result_json, chart_svg, summary = kshana.run_full(toml)
print(kshana.version(), summary)

Every other reference scenario is a file under scenarios/ in the repository; pass its text to kshana.run the same way. With the Rust command-line interface (CLI) installed, kshana example <name> prints any of them.

Beyond run / run_full / version, the module exposes run_typed (a structured result object), validate_toml (lint → list of error strings), scenario_kinds (the dispatchable kinds as a Python list of dictionaries), list_kinds (the same metadata as one JSON string — kept as a string so existing callers do not break; call json.loads(kshana.list_kinds()), or use scenario_kinds() for the parsed list), and error_kind (the KshanaError tag for a rejected scenario) — see docs/PYTHON_API.md.

Every figure of merit is labelled validated or modelled; optical-clock figures are space goals on ground hardware (no strontium optical clock has flown). Maturity is not uniform across domains — Earth PNT is real-data validated; deep-space / Mars navigation is simulation-validated; real-mission deep-space OD (orbit determination) is on the roadmap.

Learn more

• Full README & validation matrix → https://github.com/AshfordeOU/kshana
• Live playground (runs in your browser as WebAssembly) → https://kshana.dev
• Python application programming interface (API) → docs/PYTHON_API.md
• Capabilities → docs/CAPABILITY.md
• Validation & provenance → docs/VALIDATION.md · docs/PROVENANCE.md

Licence

Free and open source under the GNU AGPL-3.0-only (the GNU Affero General Public License, version 3 only). A commercial licence is available from Ashforde OÜ (an Estonian private limited company; OÜ = osaühing) for proprietary/closed integration — see LICENSING.md. Professionally developed and maintained by Ashforde OÜ; commercial support, integration, and proprietary extensions available.