qutip-sandbox

A sandbox for exploring QuTiP (Quantum Toolbox in Python) — installation, canonical examples, and a "hello world" exercise.

Setup

python3.13 -m venv .venv
.venv/bin/pip install -r requirements.txt
.venv/bin/python -c "import qutip; qutip.about()"

Requires Python ≥ 3.10 (QuTiP 5).

Scripts

scripts/run_examples.py

The pip package ships no runnable example scripts (official examples live as notebooks in qutip-tutorials), so this script adapts three canonical examples from the QuTiP 5 docs:

1. Basics — states, operators, expectation values (verifies ⟨n⟩ = |α|² for a coherent state)
2. Dissipative qubit dynamics — the docs' front-page mesolve example
3. Driven damped cavity — steady-state Lorentzian response via steadystate

.venv/bin/python scripts/run_examples.py

scripts/hello_qutip.py — the hello world exercise

Rabi oscillations of a driven qubit. This is the natural QuTiP hello world because it is the smallest simulation that exercises the library's whole core workflow:

build a Hamiltonian → evolve a state (sesolve/mesolve) → measure observables (expect) → visualize (Bloch)

It is also self-verifying: the ideal evolution has the closed form ⟨σz⟩(t) = cos(Ωt), and the script asserts the numerical result matches to <1e-4 (observed error ~1.6e-5). It then adds T1 amplitude damping to show the oscillations decohere — the regime where you actually need a numerical toolbox.

.venv/bin/python scripts/hello_qutip.py

Outputs in output/:

• hello-rabi-oscillations.png — ⟨σz⟩(t): ideal vs analytic vs damped
• hello-bloch-sphere.png — the damped trajectory spiraling into the Bloch sphere

scripts/run_microtubule_qif.py — arXiv:2602.02868v1 implementation

Implements the published model from Gassab, Pusuluk & Craddock, Quantum Information Flow in Microtubule Tryptophan Networks:

• extracts the eight Trp chromophores from data/1JFF.pdb
• uses the CD2/CE2 midpoint and 46.2 degree in-plane Trp 1La transition-dipole convention used by the cited microtubule construction work
• builds the coherent dipole coupling matrix Delta and collective decay matrix G from Eqs. 9-10
• diagonalizes H_eff = H0 + Delta - iG/2
• evolves superradiant, subradiant, coherent, mixed, and localized preparations with a trace-preserving Lindblad equation in the single-excitation-plus-ground space
• computes site populations, pair L1 coherence, correlated coherence helpers, logarithmic negativity, mutual information helpers, and trace-distance backflow helpers

.venv/bin/python scripts/run_microtubule_qif.py
.venv/bin/python -m pytest -q tests/test_model_measures.py

Outputs in output/microtubule-qif/:

• sites.csv, matrices.npz, modes.csv, summary.json
• spectrum.png
• dynamics-{superradiant,subradiant,coherent,mixed}.png
• localized-injections.png

Larger ordered assemblies can be built for spectral analysis:

.venv/bin/python scripts/run_microtubule_qif.py --assembly one-spiral --skip-dynamics
.venv/bin/python scripts/run_microtubule_qif.py --static-disorder-cm 200 --skip-dynamics

The paper's exact molecular-dynamics structural-disorder ensemble and author code are not bundled with the arXiv source, so this repo implements the ordered 1JFF reconstruction plus parameterized static disorder and random positional/dipole jitter. See docs/paper-2602.02868/implementation-notes.md and docs/paper-2602.02868/reproduction-gap-report.md.

The static walkthrough UI is docs/paper-2602.02868/ui/index.html; it can be opened directly in a browser and uses the generated plots in output/microtubule-qif/.

Environment

Verified with QuTiP 5.3.0, NumPy 1.26.4, SciPy 1.17.1, matplotlib 3.11.0 on Python 3.13.2 (macOS arm64, Accelerate BLAS).