Overview

Quantas is a scientific software project for the quantitative analysis of solid-state properties from theoretical or experimental data. The current Quantas 2.0 series turns the historical program into a reusable Python library with equivalent access from the command line and, in the future, from a separate graphical interface.

Scientific domains currently covered by Quantas include:

  • Harmonic thermodynamics (HA) from phonon frequencies and q-point weights;

  • Quasi-harmonic thermodynamics (QHA), including equilibrium volume, expansion, and derived thermoelastic properties;

  • Elasticity, including tensor analysis, stability, averaging, directional properties, and 2D/3D visualization;

  • SEISMIC, based on the Christoffel equation and dedicated to phase/group velocities, polarization, and derived seismic observables;

  • Equations of state (EOS) in the P–V, V–T, and P–V–T domains;

  • Thermoelasticity, with quasi-static pressure-temperature evolution of the elastic tensor and interoperability with SEISMIC.

Design principles

Quantas 2.0 follows a small number of explicit architectural principles.

  1. Scientific reliability before cleanup or optimization. Numerical conventions, units, and historical behavior are preserved unless a correction is scientifically justified and validated.

  2. One scientific workflow, multiple frontends. API, CLI, and future GUI must agree numerically and consume the same passive contracts whenever possible.

  3. Frontend-neutral core. The numerical core must not depend on Click, Rich, Dash, Matplotlib, Plotly, terminal streams, or progress bars.

  4. Native HDF5 persistence. Quantas stores normalized inputs, options, results, warnings, and methodological provenance in a consistent result envelope.

  5. Stable public Python API. The only supported Python surface is quantas.api.

How to read this manual

A recommended reading order is:

  1. Capabilities

  2. Installation

  3. Getting started

  4. Concepts and conventions

  5. Scientific background

  6. Implementation and workflows

  7. Tutorials

This structure intentionally separates:

  • scientific background;

  • workflow logic;

  • tutorial execution;

  • normative API and CLI reference.

That separation is essential to keep the manual readable for researchers, command-line users, Python users, and future contributors.