LaQX: A JAX Toolkit for Neural Quantum State Simulations of Lattice Quantum Many-Body Models
Neural quantum states provide accurate variational representations for interacting lattice fermions and spins. Turning a new ansatz into a reproducible calculation, however, requires coordinated implementations of the Hamiltonian, sampling, optimization, observables, and accelerator parallelism. We present LaQX (Lattice Quantum simulation based on jaX), an open-source neural quantum state library based on JAX that organizes these components through common functional interfaces. Beyond ground-state variational Monte Carlo, LaQX supports excited-state calculations, Green's Function Monte Carlo refinement, adiabatic evolution, and real-time evolution with time-dependent variational Monte Carlo. It consolidates methods developed in recent high-accuracy neural quantum state studies of the Hubbard model and frustrated magnets, and the package has been used to investigate the triangular-lattice Hofstadter-Hubbard model. We document these capabilities with reproducible calculations for Hubbard, $J_1$-$J_2$ Heisenberg, altermagnetic Hubbard, and interacting Hofstadter models. Function-oriented modules separate the scientific components and limit the source context needed for extensions by human developers and large language models. Source code, documentation, and executable examples are available at bytedance/laqx.
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LaQX: A JAX Toolkit for Neural Quantum State Simulations of Lattice Quantum Many-Body Models Neural quantum states provide accurate variational representations for interacting lattice fermions and spins. Turning a new ansatz into a reproducible calculation, however, requires coordinated implementations of the Hamiltonian, sampling, optimization, observables, and accelerator parallelism. We present LaQX (Lattice Quantum simulation based on jaX), an open-source neural quantum state library based on JAX that organizes these components through common functional interfaces. Beyond ground-state variational Monte Carlo, LaQX supports excited-state calculations, Green's Function Monte Carlo refinement, adiabatic evolution, and real-time evolution with time-dependent variational Monte Carlo. It consolidates methods developed in recent high-accuracy neural quantum state studies of the Hubbard model and frustrated magnets, and the package has been used to investigate the triangular-lattice Hofstadter-Hubbard model. We document these capabilities with reproducible calculations for Hubbard, $J_1$-$J_2$ Heisenberg, altermagnetic Hubbard, and interacting Hofstadter models. Function-oriented modules separate the scientific components and limit the source context needed for extensions by human developers and large language models. Source code, documentation, and executable examples are available at bytedance/laqx.