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:
- Official website: https://nubakery.org/
- Documentation: https://nubakery.org/manual.html
- GitHub repository: https://github.com/nubakery/bagel
- T. Shiozaki, WIREs Comput. Mol. Sci. 8, e1331 (2018) - BAGEL overview
- M. K. MacLeod and T. Shiozaki, J. Chem. Phys. 142, 051103 (2015) - Gradients
Secondary sources:
- BAGEL manual and examples
- Published applications
- Methodology papers
- 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