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.