method-mf

Performs self-consistent mean-field calculations for quantum lattice models in Julia.

60|92|Updated Apr 30, 2026
One-click install
npx skills add https://github.com/QuantumBFS/quantum.harness --skill method-mf
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: method-mf
Source: https://github.com/QuantumBFS/quantum.harness/tree/main/skills/method-mf
Command: npx skills add https://github.com/QuantumBFS/quantum.harness --skill method-mf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill provides a rapid, self-consistent baseline for quantum lattice models, allowing researchers to quickly estimate order parameters and phase diagrams without the high computational cost of fully correlated methods.

Core Features & Use Cases

  • Mean-field decoupling of lattice fermion models (Hartree-Fock) and spin models (Weiss).
  • Generation of reference states to seed more advanced correlated methods like DMRG, VMC, or QMC.
  • Identification of candidate broken symmetries and phase boundaries in quantum systems.

Quick Start

Run the mean-field self-consistent loop for the specified lattice model using the canonical Julia stack.

Frequently Asked Questions about method-mf

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform a self-consistent mean-field calculation for quantum lattice models?

To perform a self-consistent mean-field calculation, this skill executes a self-consistent-field iteration loop and convergence verification for quantum lattice models. It handles Hartree-Fock for fermions and Weiss decoupling for spins.

What is the best way to estimate phase diagrams for quantum systems without high computational cost?

Estimating phase diagrams without high computational cost is achieved by identifying candidate broken symmetries and phase boundaries using self-consistent mean-field approximations for quantum lattice models.

Can I generate reference configurations for correlated computational methods like DMRG or QMC?

Yes, you can generate reference configurations to seed correlated computational methods like DMRG, VMC, or QMC. The skill produces these reference states from self-consistent mean-field decoupling.

Do I need a Julia environment to run self-consistent-field iterations?

Yes, a stable Julia environment is required to execute the self-consistent-field iteration loop and convergence verification. The skill uses the canonical Julia stack to ensure proper calculation stability.

When should I use Hartree-Fock mean-field over fully correlated methods for quantum systems?

You should use Hartree-Fock mean-field when you need a rapid baseline to estimate order parameters for fermion models without the high computational cost of fully correlated methods. It is ideal for initial phase boundary identification.