SHARC

SHARC is a comprehensive ab initio molecular dynamics software suite for excited-state dynamics simulations using trajectory surface hopping. It enables the study of photochemical and photophysical processes including internal conversion…

2. TDDFT & EXCITED-STATE 2.5 Hybrid & Specialized VERIFIED 1 paper
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Overview

SHARC is a comprehensive ab initio molecular dynamics software suite for excited-state dynamics simulations using trajectory surface hopping. It enables the study of photochemical and photophysical processes including internal conversion, intersystem crossing, and photodissociation. SHARC interfaces with major quantum chemistry codes to obtain electronic structure data and supports various types of couplings including spin-orbit and non-adiabatic couplings.

Reference Papers (1)

Full Documentation

Official Resources

  • Homepage: https://sharc-md.org/
  • Documentation: https://sharc-md.org/?page_id=50
  • Source Repository: https://github.com/sharc-md/sharc
  • License: GNU General Public License v3.0

Overview

SHARC is a comprehensive ab initio molecular dynamics software suite for excited-state dynamics simulations using trajectory surface hopping. It enables the study of photochemical and photophysical processes including internal conversion, intersystem crossing, and photodissociation. SHARC interfaces with major quantum chemistry codes to obtain electronic structure data and supports various types of couplings including spin-orbit and non-adiabatic couplings.

Scientific domain: Photochemistry, excited-state dynamics, nonadiabatic processes, intersystem crossing Target user community: Researchers studying light-induced chemical reactions, photophysics, and ultrafast dynamics

Theoretical Methods

  • Trajectory Surface Hopping (TSH)
  • Fewest-Switches Surface Hopping (FSSH)
  • Landau-Zener surface hopping
  • Non-adiabatic coupling vectors
  • Spin-orbit couplings (SOC)
  • Decoherence corrections
  • Velocity rescaling and adjustment
  • SHARC propagator (diagonal representation)
  • MCH propagator (molecular Coulomb Hamiltonian)

Capabilities (CRITICAL)

  • Excited-state molecular dynamics
  • Non-adiabatic dynamics simulations
  • Intersystem crossing (ISC) dynamics
  • Internal conversion pathways
  • Spin-orbit coupled dynamics
  • Wigner sampling for initial conditions
  • Newton-X interface for initial conditions
  • Trajectory analysis and plotting
  • Ensemble averaging and statistics
  • Time-resolved property propagation
  • Dipole moments and transition properties
  • Natural transition orbitals
  • Population dynamics

Sources: Official SHARC documentation, GitHub repository, J. Chem. Theory Comput. 2019

Key Strengths

Arbitrary Couplings:

  • Non-adiabatic couplings
  • Spin-orbit couplings
  • Dipole couplings (laser fields)
  • Simultaneous treatment of all couplings
  • Flexible coupling definitions

Extensive QC Interfaces:

  • OpenMolcas (CASSCF/CASPT2/MS-CASPT2)
  • ORCA (TDDFT, MRCI)
  • TURBOMOLE (TDDFT, CC2, ADC(2))
  • ADF (TDDFT)
  • Gaussian (TDDFT)
  • Columbus (MRCI)
  • BAGEL (CASPT2)

Analysis Tools:

  • Trajectory visualization
  • Population analysis
  • Reaction pathway analysis
  • Statistical convergence
  • Property time-evolution

Machine Learning Integration:

  • SchNarc interface
  • ML potential energy surfaces
  • Neural network dynamics
  • Accelerated sampling

Inputs & Outputs

  • Input formats:

    • SHARC input files
    • Geometry files (XYZ)
    • Wigner ensemble distributions
    • QC interface templates
  • Output data types:

    • Trajectory files
    • Population dynamics
    • Geometries and velocities
    • Electronic state data
    • Hopping statistics
    • Property evolution

Interfaces & Ecosystem

  • QC programs: OpenMolcas, ORCA, TURBOMOLE, ADF, Gaussian, Columbus, BAGEL
  • Visualization: VMD, PyMOL, trajectory viewers
  • ML integration: SchNarc (neural network potentials)
  • Initial conditions: Newton-X interface, Wigner sampling
  • Post-processing: Python analysis scripts, matplotlib

Advanced Features

SHARC Propagator:

  • Diagonal representation of electronic states
  • Proper treatment of couplings
  • Energy conservation
  • Momentum adjustment schemes

Laser Field Dynamics:

  • Time-dependent electric fields
  • Dipole coupling terms
  • Photoexcitation modeling
  • Pulse shape control

Adaptive Sampling:

  • Efficient trajectory selection
  • Importance sampling
  • Enhanced statistics

Performance Characteristics

  • Speed: Determined by QC interface
  • Accuracy: Based on underlying electronic structure method
  • System size: Limited by QC method (typically <500 atoms)
  • Parallelization: Embarrassingly parallel trajectory ensemble

Computational Cost

  • Dynamics: Overhead minimal compared to QC
  • Bottleneck: Electronic structure calculations
  • Typical: Hundreds to thousands of trajectories
  • Resources: HPC cluster recommended

Limitations & Known Constraints

  • Electronic structure: Requires external QC program
  • System size: Limited by QC method
  • Classical nuclei: Ignores nuclear quantum effects
  • Decoherence: Model-dependent corrections
  • Basis set: Must be consistent across trajectory

Comparison with Other Codes

  • vs Newton-X: SHARC handles arbitrary couplings, both TSH
  • vs NEXMD: SHARC more general interfaces, NEXMD semiempirical focus
  • vs CPMD/CP2K: SHARC specialized for hopping, general codes have Ehrenfest
  • Unique strength: Spin-orbit couplings, arbitrary coupling treatment, extensive interfaces

Application Areas

Photochemistry:

  • Bond photodissociation
  • Ring opening/closing reactions
  • Proton/hydrogen transfer
  • Isomerization dynamics

Photophysics:

  • Intersystem crossing rates
  • Phosphorescence mechanisms
  • Triplet state dynamics
  • Heavy-atom effects

Biological Systems:

  • DNA photodamage
  • Retinal photoisomerization
  • Photoreceptor proteins
  • Chromophore dynamics

Best Practices

Method Selection:

  • CASPT2/MS-CASPT2 for accuracy
  • TDDFT for larger systems
  • Careful active space selection
  • Validate with static calculations

Ensemble Size:

  • Statistical convergence analysis
  • Typically 100-500 trajectories
  • Check property convergence
  • Consider trajectory weights

Analysis:

  • Population dynamics
  • Branching ratios
  • Time constants
  • Mechanism identification

Community and Support

  • Open-source GPL v3
  • Active development (González and Truhlar groups)
  • Tutorial materials available
  • Regular workshops
  • Published methodology papers

Verification & Sources

Primary sources:

  1. Official website: https://sharc-md.org/
  2. GitHub repository: https://github.com/sharc-md/sharc
  3. S. Mai et al., WIREs Comput. Mol. Sci. 8, e1370 (2018)
  4. M. Richter et al., J. Chem. Theory Comput. 7, 1253 (2011)

Secondary sources:

  1. SHARC tutorials and documentation
  2. Published applications
  3. Workshop materials

Confidence: VERIFIED - Active open-source project

Verification status: ✅ VERIFIED

  • Official homepage: ACCESSIBLE
  • Documentation: ACCESSIBLE
  • Source code: OPEN (GitHub, GPL v3)
  • Community support: Active (developers, tutorials)
  • Academic citations: >500
  • Active development: Regular releases
  • Specialized strength: Arbitrary couplings, extensive QC interfaces, spin-orbit dynamics

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