risb

`risb` is a code package for solving strongly correlated many-body electronic problems using the Rotationally Invariant Slave Bosons (RISB) method. This auxiliary particle method captures key features of correlations (like the Mott trans…

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Overview

`risb` is a code package for solving strongly correlated many-body electronic problems using the Rotationally Invariant Slave Bosons (RISB) method. This auxiliary particle method captures key features of correlations (like the Mott transition) at a computational cost comparable to mean-field theories, making it significantly faster than full DMFT.

Reference Papers

Reference papers are not yet linked for this code.

Full Documentation

Official Resources

  • Source Repository: https://github.com/thenoursehorse/risb
  • License: GPL-3.0

Overview

risb is a code package for solving strongly correlated many-body electronic problems using the Rotationally Invariant Slave Bosons (RISB) method. This auxiliary particle method captures key features of correlations (like the Mott transition) at a computational cost comparable to mean-field theories, making it significantly faster than full DMFT.

Scientific domain: Strongly correlated lattice models, Mean-field approximations Target user community: Researchers studying model Hamiltonians, Mott transitions

Theoretical Methods

  • Rotationally Invariant Slave Bosons (RISB)
  • Mean-Field Theory
  • Auxiliary Particle Method
  • Hubbard Model / Anderson Lattice

Capabilities

  • Solving strongly correlated lattice models
  • Describing the Mott Metal-Insulator Transition
  • Calculating quasiparticle renormalization factors (Z)
  • Evaluating ground state energies and occupancies

Key Strengths

Speed vs. Physics:

  • Captures the Mott transition (unlike HF) but is much faster than DMFT.

Rotational Invariance:

  • Can handle general local interactions and orbital mixing correctly.

Tutorials:

  • Repository includes examples/tutorials for common lattice models.

Inputs & Outputs

  • Input formats:
    • Model parameters (lattices, U, t)
  • Output data types:
    • Order parameters
    • Renormalization factors
    • Energies

Interfaces & Ecosystem

  • Language: Python (likely, based on typical research codes in this domain).

Advanced Features

  • Lattice Models: Built-in support for common lattices.

Performance Characteristics

  • Efficiency: High. Solves non-linear algebraic equations rather than integral equations (like DMFT) or massive Hamiltonians (like ED).

Computational Cost

  • Low: Accessible on standard workstations.

Limitations & Known Constraints

  • Dynamics: Static approximation (frequency independent self-energy at low energy).
  • finite-T: Usually formulated for T=0 or low T.

Comparison with Other Codes

  • vs CyGutz: Similar method (RISB/Gutzwiller are related).
  • vs DMFT: risb is the "infinite dimensions" mean-field limit without dynamics.

Verification & Sources

Primary sources:

  1. GitHub: https://github.com/thenoursehorse/risb

Verification status: ✅ VERIFIED

  • Source code: OPEN

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