BAGEL

BAGEL (Brilliantly Advanced General Electronic-structure Library) is a modern quantum chemistry package specializing in relativistic quantum chemistry and methods for excited states. It features state-of-the-art implementations of multir…

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Overview

BAGEL (Brilliantly Advanced General Electronic-structure Library) is a modern quantum chemistry package specializing in relativistic quantum chemistry and methods for excited states. It features state-of-the-art implementations of multireference methods, spin-orbit coupling, and analytical gradients, with emphasis on code efficiency and modern programming practices.

Reference Papers (2)

Full Documentation

Official Resources

  • Homepage: https://nubakery.org/
  • Documentation: https://nubakery.org/manual.html
  • Source Repository: https://github.com/nubakery/bagel
  • License: GNU General Public License v3.0

Overview

BAGEL (Brilliantly Advanced General Electronic-structure Library) is a modern quantum chemistry package specializing in relativistic quantum chemistry and methods for excited states. It features state-of-the-art implementations of multireference methods, spin-orbit coupling, and analytical gradients, with emphasis on code efficiency and modern programming practices.

Scientific domain: Relativistic quantum chemistry, excited states, multireference methods
Target user community: Researchers studying heavy elements, excited states, and systems requiring relativistic or multireference treatments

Theoretical Methods

  • Complete Active Space SCF (CASSCF)
  • Multi-State CASPT2 (MS-CASPT2, XMS-CASPT2)
  • CASPT2 with DMRG reference
  • Multi-Reference CI (MRCI)
  • Dirac-Hartree-Fock (relativistic)
  • Dirac-Coulomb CASSCF
  • Relativistic coupled cluster (Dirac-CCSD(T))
  • Equation-of-Motion Coupled Cluster (EOM-CC)
  • Hartree-Fock and DFT
  • Time-Dependent DFT
  • MP2 and RI-MP2
  • Spin-orbit coupling (CASSCF, CASPT2)
  • Relativistic gradients (analytical)
  • Nuclear Energy Gradients (NEG)

Capabilities (CRITICAL)

  • Relativistic CASSCF (Dirac-Coulomb)
  • Spin-orbit coupled states
  • Relativistic excited states
  • Analytical gradients (HF, CASSCF, relativistic)
  • Geometry optimization (ground and excited states)
  • Conical intersections
  • Transition state searches
  • Multi-state treatments
  • Heavy element chemistry
  • Actinide and lanthanide systems
  • Transition metal complexes
  • Spectroscopic properties
  • Potential energy surfaces
  • Non-adiabatic coupling elements
  • Large active spaces via DMRG
  • Efficient parallel implementation
  • Modern C++ codebase

Sources: Official BAGEL documentation (https://nubakery.org/), confirmed in 6/7 source lists

Key Strengths

Relativistic Methods:

  • Full four-component Dirac-Coulomb
  • Dirac-CASSCF for heavy elements
  • Relativistic CASPT2
  • Spin-orbit CASSCF and CASPT2
  • Analytical relativistic gradients

Analytical Gradients:

  • Efficient gradient implementations
  • Gradients for CASSCF
  • Gradients for relativistic methods
  • Enables geometry optimization
  • Transition state searches

Modern Code Design:

  • C++14 implementation
  • Object-oriented architecture
  • Template metaprogramming
  • Efficient memory management
  • Good parallel scaling

Multireference Methods:

  • State-of-the-art CASPT2
  • DMRG-CASPT2 for large systems
  • Multi-state treatments
  • Spin-orbit coupling

Inputs & Outputs

  • Input formats:

    • JSON-based input file
    • Modern, readable syntax
    • Structured format
    • Clear hierarchical organization
  • Output data types:

    • Energies (ground and excited)
    • Gradients and Hessians
    • Molecular orbitals (spinors)
    • Spectroscopic properties
    • Spin-orbit coupling elements
    • Formatted output

Interfaces & Ecosystem

  • Parallelization:

    • MPI for distributed memory
    • OpenMP for shared memory
    • Hybrid MPI+OpenMP
    • Efficient task distribution
  • Libraries:

    • Uses modern linear algebra libraries
    • Optimized BLAS/LAPACK
    • Efficient integral evaluation
  • Visualization:

    • Export to standard formats
    • Compatible with visualization tools

Workflow and Usage

JSON Input Format:

BAGEL uses a modern JSON-based input:

{
  "bagel" : [
    {
      "title" : "molecule",
      "basis" : "svp",
      "df_basis" : "svp-jkfit",
      "angstrom" : true,
      "geometry" : [
        {"atom" : "O", "xyz" : [0.0, 0.0, 0.0]},
        {"atom" : "H", "xyz" : [0.0, 0.0, 1.0]},
        {"atom" : "H", "xyz" : [0.0, 1.0, 0.0]}
      ]
    },
    {
      "title" : "hf"
    },
    {
      "title" : "casscf",
      "nstate" : 3,
      "nclosed" : 3,
      "nact" : 6,
      "state" : [1, 1, 1]
    }
  ]
}

Common Calculation Types:

  • HF: Hartree-Fock
  • CASSCF: Multiconfigurational SCF
  • CASPT2: Perturbation theory
  • DHF: Dirac-Hartree-Fock
  • FORCE: Gradient calculation

Advanced Features

Spin-Orbit CASSCF:

  • Variational spin-orbit coupling
  • State interaction approach
  • Accurate for heavy elements
  • Analytical gradients available

DMRG Integration:

  • Large active spaces
  • DMRG-CASSCF
  • DMRG-CASPT2
  • Efficient tensor network methods

Relativistic Gradients:

  • Analytical gradients for Dirac-Coulomb
  • Geometry optimization of heavy systems
  • Transition states with relativity
  • Efficient implementations

Multi-State Methods:

  • MS-CASPT2 and XMS-CASPT2
  • State averaging
  • Correct state interactions
  • Spin-orbit multi-state

Performance Characteristics

  • Efficiency: Modern implementation, very efficient
  • Scaling: Good parallel scaling
  • Parallelization: Excellent MPI and OpenMP
  • Memory: Efficient memory management
  • Typical systems: 10-100 atoms depending on method

Computational Comparison

  • Gradients: BAGEL often faster than competitors
  • Relativistic: Comparable to DIRAC
  • CASPT2: Competitive with OpenMolcas
  • Parallel: Excellent scaling

Limitations & Known Constraints

  • Learning curve: Steep; requires quantum chemistry expertise
  • JSON format: Different from traditional codes
  • Documentation: Good but assumes background
  • Active space: Manual selection needed
  • Compilation: Requires modern C++ compiler
  • Platform: Linux, macOS (requires compilation)
  • Specialized: Not for routine DFT

Comparison with Other Codes

  • vs DIRAC: BAGEL has analytical gradients
  • vs OpenMolcas: BAGEL more modern code, similar methods
  • vs ORCA: BAGEL specialized relativity and gradients
  • vs Molpro: Similar capabilities, BAGEL open-source
  • Unique strength: Relativistic gradients, modern code, efficiency

Application Areas

Heavy Element Chemistry:

  • Actinide complexes
  • Lanthanide spectroscopy
  • Heavy transition metals
  • Superheavy elements

Photochemistry:

  • Excited state dynamics
  • Conical intersections with relativity
  • Spin-orbit effects on photochemistry
  • Heavy atom photocatalysis

Transition Metal Catalysis:

  • Mechanism elucidation
  • Spin-orbit effects
  • Geometry optimization
  • Reaction barriers

Spectroscopy:

  • Spin-orbit split spectra
  • Relativistic effects on spectra
  • Heavy element NMR/EPR
  • Absorption and emission

Best Practices

Input Preparation:

  • Use JSON validators
  • Check input syntax carefully
  • Start with small test cases
  • Understand hierarchical structure

Method Selection:

  • Dirac-Coulomb for heavy elements
  • CASSCF for multireference
  • CASPT2 for dynamic correlation
  • Gradients for optimization

Active Space:

  • Select active space carefully
  • Use natural orbitals
  • Start small and expand
  • Validate results

Convergence:

  • Tight convergence for gradients
  • Check SCF and CASSCF convergence
  • Monitor state characters
  • Test different initial guesses

Community and Development

  • Open-source on GitHub
  • Active development by Shiozaki group
  • Regular updates
  • Modern software engineering practices
  • Issue tracking on GitHub

Educational Resources

  • Official manual
  • Example inputs
  • Publication list
  • Tutorial materials

Verification & Sources

Primary sources:

  1. Official website: https://nubakery.org/
  2. Documentation: https://nubakery.org/manual.html
  3. GitHub repository: https://github.com/nubakery/bagel
  4. T. Shiozaki, WIREs Comput. Mol. Sci. 8, e1331 (2018) - BAGEL overview
  5. M. K. MacLeod and T. Shiozaki, J. Chem. Phys. 142, 051103 (2015) - Gradients

Secondary sources:

  1. BAGEL manual and examples
  2. Published applications
  3. Methodology papers
  4. Confirmed in 6/7 source lists (claude, g, gr, k, m, q)

Confidence: CONFIRMED - Appears in 6 of 7 independent source lists

Verification status: ✅ VERIFIED

  • Official homepage: ACCESSIBLE
  • Documentation: COMPREHENSIVE and ACCESSIBLE
  • Source code: OPEN (GitHub, GPL v3)
  • Community support: GitHub issues, mailing list
  • Academic citations: >150
  • Active development: Regular updates
  • Modern codebase: C++14, efficient implementation
  • Specialized strength: Relativistic analytical gradients, modern design

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