qutip

qutip is a skill for Claude Code, Codex from Lord1Egypt/scientific-agent-toolkit. It costs 72 tokens per session (2,572 once invoked), scanned A, a copy of qutip, MIT.

A Python library for simulating quantum systems, including systems that lose energy or become disturbed by their environment. Open quantum systems are quantum systems affected by such outside influences.

In plain words
What is it for?
Use it to model master equations, Lindblad dynamics, decoherence, quantum optics, cavity QED, and educational quantum simulations.
Why use it?
It lets researchers study quantum dynamics without building every mathematical solver from scratch.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to model master equations, Lindblad dynamics, decoherence, quantum optics, cavity QED, and educational quantum simulations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lord1egypt/scientific-agent-toolkit/qutip
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Lord1Egypt/scientific-agent-toolkit --skill qutip
Clone the repo
git clone --depth 1 https://github.com/Lord1Egypt/scientific-agent-toolkit

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for qutip

README.md
[![agentmods](https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/qutip/github.svg)](https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/qutip)
Your own site
<a href="https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/qutip"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/qutip/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for qutip

Your own site · 80×15
<a href="https://agentmods.dev/skills/lord1egypt/scientific-agent-toolkit/qutip"><img src="https://agentmods.dev/badge/skills/lord1egypt/scientific-agent-toolkit/qutip.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,572 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 98% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.02572
Opus 5 $0.00036 $0.01286
Sonnet 5 $0.00014 $0.00514
Haiku 4.5 $0.00007 $0.00257

Measured 9d ago against content hash b3095174fe66, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

qutip scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

98% identical to qutip — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

scientific-skills/qutip/SKILL.md · 317 lines

How it starts

The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.

QuTiP: Quantum Toolbox in Python

Overview

QuTiP provides comprehensive tools for simulating and analyzing quantum mechanical systems. It handles both closed (unitary) and open (dissipative) quantum systems with multiple solvers optimized for different scenarios.

Installation

uv pip install qutip

Optional packages for additional functionality:

# Quantum information processing (circuits, gates)
uv pip install qutip-qip

# Quantum trajectory viewer
uv pip install qutip-qtrl

Quick Start

from qutip import *
import numpy as np
import matplotlib.pyplot as plt

# Create quantum state
psi = basis(2, 0)  # |0⟩ state

# Create operator
H = sigmaz()  # Hamiltonian

# Time evolution
tlist = np.linspace(0, 10, 100)
result = sesolve(H, psi, tlist, e_ops=[sigmaz()])

# Plot results
plt.plot(tlist, result.expect[0])
plt.xlabel('Time')
plt.ylabel('⟨σz⟩')
plt.show()

Core Capabilities

1. Quantum Objects and States

Create and manipulate quantum states and operators:

# States
psi = basis(N, n)  # Fock state |n⟩
psi = coherent(N, alpha)  # Coherent state |α⟩
rho = thermal_dm(N, n_avg)  # Thermal density matrix

# Operators
a = destroy(N)  # Annihilation operator
H = num(N)  # Number operator
sx, sy, sz = sigmax(), sigmay(), sigmaz()  # Pauli matrices

# Composite systems
psi_AB = tensor(psi_A, psi_B)  # Tensor product

See references/core_concepts.md for comprehensive coverage of quantum objects, states, operators, and tensor products.

2. Time Evolution and Dynamics

Multiple solvers for different scenarios:

# Closed systems (unitary evolution)
result = sesolve(H, psi0, tlist, e_ops=[num(N)])

# Open systems (dissipation)
c_ops = [np.sqrt(0.1) * destroy(N)]  # Collapse operators
result = mesolve(H, psi0, tlist, c_ops, e_ops=[num(N)])

# Quantum trajectories (Monte Carlo)
result = mcsolve(H, psi0, tlist, c_ops, ntraj=500, e_ops=[num(N)])

Solver selection guide:

  • sesolve: Pure states, unitary evolution
  • mesolve: Mixed states, dissipation, general open systems
  • mcsolve: Quantum jumps, photon counting, individual trajectories
  • brmesolve: Weak system-bath coupling
  • fmmesolve: Time-periodic Hamiltonians (Floquet)

Read the full file on GitHub · 317 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 317 lines · 72 tokens per session scan A b3095174fe66

Subscribe to this mod's changes

qutip is a skill published in the GitHub repository Lord1Egypt/scientific-agent-toolkit (3 stars, last pushed 3mo ago), licensed MIT. It adds 72 tokens to every session and 2,572 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to qutip, differing in 2 lines, and is treated as a copy.

Related

Other skills, from other repositories

cellxgene-census-query

Query CZ CELLxGENE Census (61M+ cells). Filter by cell type/tissue/disease, retrieve expression data, and integrate with scanpy/PyTorch for population-scale single-cell analysis. Use this skill when: (1) Querying single-cell expression data by cell type, tissue, or disease, (2) Exploring available single-cell datasets…

PharMolix/OpenBioMed · 105 tokens

alterlab-deep-research

Runs a 13-agent deep research pipeline for rigorous academic work on any topic across 7 modes (full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis), covering research-question formulation, Socratic mentoring, methodology…

AlterLab-IEU/AlterLab-Academic-Skills · 239 tokens

alterlab-imaging-data-commons

Query and download public cancer imaging data from the NCI Imaging Data Commons (IDC) using the idc-index Python package, filtering by metadata, visualizing in-browser, and checking licenses, with no authentication required. Use when obtaining large-scale radiology (CT, MR, PET) or digital pathology DICOM datasets for…

AlterLab-IEU/AlterLab-Academic-Skills · 90 tokens

alterlab-pyhealth

Develops, tests, and deploys clinical machine learning models with the PyHealth healthcare AI toolkit. Use when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare…

AlterLab-IEU/AlterLab-Academic-Skills · 117 tokens

alterlab-cobrapy

Build and analyze genome-scale constraint-based metabolic models with COBRApy — flux balance analysis (FBA), flux variability analysis (FVA), gene and reaction knockouts, flux sampling, and SBML model I/O. Use when simulating metabolic networks, predicting growth or knockout phenotypes, or running systems-biology and…

AlterLab-IEU/AlterLab-Academic-Skills · 91 tokens

alterlab-deeptools

Process and visualize deep-sequencing coverage with the deepTools CLI — convert BAM to bigWig (bamCoverage), build log2 ratio tracks (bamCompare), run QC (multiBamSummary correlation, PCA, plotFingerprint), apply the ATAC-seq Tn5 shift (alignmentSieve --ATACshift), and make TSS/peak heatmaps and profiles…

AlterLab-IEU/AlterLab-Academic-Skills · 173 tokens