Change Log

Change Log#

Mar-10-2026: v0.2.0a1#

This is a major update with drastic performance improvements, new features, and a new workflow automation package (jqmc-workflow).

Performance#

  • Drastic speedups: MCMC, VMC, and LRDMC are all significantly faster than the previous version thanks to pervasive use of fast-update algorithms throughout the code.

  • LU -> SVD replacement: Replaced LU factorizations with SVD across determinant, geminal, GFMC_n, and GFMC_t modules, greatly improving numerical stability for ill-conditioned matrices.

  • GEMM optimization: Converted matrix-vector operations to matrix-matrix (GEMM) operations in Coulomb potential, determinant, and Jastrow factor modules for better GPU utilization.

  • Cartesian / Spherical AO conversion: Implemented Cartesian AO <-> Spherical AO conversion. Cartesian GTOs are substantially faster than spherical GTOs on GPUs, so users can now exploit this for better throughput.

  • ECP fast computation: Implemented compute_ecp_coulomb_potential_fast for efficient pseudopotential evaluation.

  • vmap + jit fix: vmap-ed functions are now explicitly wrapped with jit, as vmap does not automatically JIT-compile the mapped function.

  • Removed mpi4jax dependency for CG: Conjugate gradient (CG) solver now uses pure MPI on CPUs, eliminating the mpi4jax dependency.

Optimization#

  • Adaptive learning rate for Stochastic Reconfiguration: Implemented a linear-method-inspired automatic learning-rate adjustment scheme, leading to dramatically faster optimization convergence.

  • Molecular orbital optimization: Added MO optimization for JSD wavefunctions via the projection method with Attacalite-Sorella regularization.

  • Geminal AO -> MO projection: Implemented AO overlap matrix computation and geminal AO -> MO projection for constrained optimization.

New features#

  • LRDMC force calculations: Implemented LRDMC atomic forces with the Pathak–Wagner regularization.

  • Jastrow functions: Added jastrow_1b_type ('exp' / 'pade') and jastrow_2b_type ('pade' / 'exp') fields to Jastrow_one_body_data and Jastrow_two_body_data, enabling runtime selection of the one-body and two-body Jastrow functional forms.

    • Exponential form: \(u(r) = \frac{1}{2b}(1 - e^{-br})\)

    • Padé form: \(u(r) = \frac{r}{2(1 + br)}\)

Bug fixes#

  • Fixed force calculations producing NaN values; added NaN checks in all tests.

  • Fixed MCMC memory overflow caused by storing r_up_history / r_dn_history.

  • Fixed wavefunction without Jastrow not working for MCMC.

  • Fixed missing NN-Jastrow derivatives in _GFMC_n_debug.

Infrastructure#

  • Restart file format change: Switched restart files from pickle-based *.chk to HDF5-based *.h5. Note: backward compatibility with old *.chk files is not maintained.

  • jqmc_workflow package: Introduced the jqmc_workflow automation package for orchestrating multi-stage QMC pipelines (WF conversion → VMC optimization → MCMC / LRDMC production) with automatic step estimation, checkpointing, and remote job management.

  • Removed SWCT_data: Cleaned up legacy SWCT_data class as part of codebase refactoring.

  • More comprehensive tests: Substantially expanded the test suite to cover the new features and improve overall reliability.

  • Expanded examples: Reorganized and enriched the examples/ directory with 11 end-to-end tutorials (jqmc-example01–jqmc-example08, jqmc-workflow-example01–jqmc-workflow-example03) covering single-point VMC/LRDMC, force calculations, GPU walker-scaling benchmarks, interaction-energy workflows, and PES scans with automated jqmc_workflow pipelines.

Feb-5-2026: v0.1.0#

  • Release of the first stable version of jQMC.

Known Limitations#

  • Periodic Boundary Condition (PBC) calculations are being implemented for the next major release.

Jan-23-2026: v0.1.0a3#

  • Release of the third alpha version of jQMC.

Key Features#

  • Analytical derivatives:

    • Implemented analytical gradients and Laplacians for atomic and molecular orbitals in both spherical and Cartesian GTO bases.

    • JAX autograd is now used primarily for validating the analytical gradients.

    • Logarithmic derivatives of the wavefunction and derivatives of atomic force calculations still use JAX autograd.

  • Testing precision:

    • Tightened and systematized decimal controls in tests, improving overall reliability.

  • Fast updates:

    • Expanded fast-update implementations to more functions, yielding significant speedups in both MCMC and GFMC modules.

Jan-14-2026: v0.1.0a1#

  • Release of the second alpha version of jQMC.

Key Features#

  • Neural Network Jastrow:

    • Introduced NNJastrow, a PauliNet-inspired neural network architecture for many-body Jastrow factors, enabling more accurate wavefunction ansatz.

  • Optimization Control:

    • Implemented proper gradient masking mechanisms (e.g., with_param_grad_mask). This allows for selectively freezing or optimizing specific parameter blocks (One-body, Two-body, Three-body, NN, and Geminal coefficients) during the VMC optimizations.

Enhancements & Fixes#

  • I/O: Changed the storage format for hamiltonian_data from pickled binary files to HDF5 (.h5) for better portability and compatibility.

  • Documentation: Updated README.md, docstrings, and API references to reflect recent changes and fix Sphinx warnings.

  • CI/CD: Updated pre-commit configurations and GitHub workflow triggers.

  • Code Quality: Refactored code based on suggestions and improved type hinting.

Aug-20-2025: v0.1.0a0#

  • Release of the first alpha version of jQMC.

We are pleased to announce the first alpha release of jQMC, a Python-based Quantum Monte Carlo package built on JAX.

Key Features#

  • JAX-based Core: Fully utilizes JAX’s Just-In-Time (JIT) compilation and automatic vectorization (vmap) for high-performance simulations on GPUs and TPUs.

  • Algorithms:

    • Variational Monte Carlo (VMC): Supports wavefunction optimization via Stochastic Reconfiguration (SR) and Natural Gradient methods.

    • Lattice Regularized Diffusion Monte Carlo (LRDMC): A stable and efficient projection method for ground state calculations.

  • Wavefunctions:

    • Ansatz: Supports Jastrow-Slater Determinant (JSD) and Jastrow-Antisymmetrized Geminal Power (JAGP).

    • Jastrow Factors: Includes One-body, Two-body, Three/Four-body terms.

    • Determinant Types: Single Determinant (SD), Antisymmetrized Geminal Power (AGP), and Number-constrained AGP (AGPn).

  • I/O & Interoperability:

    • TREX-IO Support: Interfaces with the TREX-IO library (HDF5 backend) for standardized input of molecular structure and basis sets (Cartesian & Spherical GTOs).

  • Parallelization:

    • MPI Support: Implements mpi4py for efficient parallelization across multiple nodes.

  • Documentation:

    • Comprehensive technical notes on Wavefunctions, VMC, LRDMC, and JAX implementation details.

    • Examples demonstrating usage for various systems (H2, N2, Water, etc.).

Known Limitations (Alpha)#

  • Periodic Boundary Conditions (PBC) are currently in development.

  • Atomic force calculations with spherical harmonics are computationally intensive on current JAX versions.

  • Complex wavefunctions are not yet supported.