CDFCI is a shared-memory parallel numerical program for computing low-lying eigenpairs of large-scale, non-relativistic fermionic Hamiltonians. The software is designed to handle a broad class of many-body quantum models, including both ab initio electronic structure Hamiltonians and lattice-based Hamiltonians arising in condensed matter physics. CDFCI combines an efficient coordinate-descent-based selected configuration interaction algorithm with dedicated parallelization strategies, achieving high performance on modern multi-core architectures. Benchmark results on representative quantum chemistry and condensed matter test cases demonstrate that CDFCI attains state-of-the-art accuracy with competitive performance compared to established selected configuration interaction (such as CIPSI or SHCI) and DMRG implementations. The software is open-source, extensively documented, and provides a Python interface for seamless integration with PySCF and other many-body simulation workflows.
CDFCI is a shared-memory parallel numerical program for computing low-lying eigenpairs of large-scale, non-relativistic fermionic Hamiltonians. The software is designed to handle a broad class of many-body quantum models, including both ab initio electronic structure Hamiltonians and lattice-based Hamiltonians arising in condensed matter physics. CDFCI combines an efficient coordinate-descent-based selected configuration interaction algorithm with dedicated parallelization strategies, achieving high performance on modern multi-core architectures. Benchmark results on representative quantum chemistry and condensed matter test cases demonstrate that CDFCI attains state-of-the-art accuracy with competitive performance compared to established selected configuration interaction (such as CIPSI or SHCI) and DMRG implementations. The software is open-source, extensively documented, and provides a Python interface for seamless integration with PySCF and other many-body simulation workflows.
The coordinate descent full configuration interaction (CDFCI) is an accurate and efficient method for calculating ground-state energies of molecular systems. In this work we introduce two perturbative extensions of original CDFCI. We first propose a direct CDFCI + PT to further correct variational energy by perturbation theory. We also propose an iterative perturbative CDFCI (IP-CDFCI) to avoid evaluating the overlarge perturbative space and catch the information encoded in variational stage. In IP-CDFCI, we store three sparse vectors in a Hash table: c, b and d, where c is the variational wave function, b is the compressed approximation of H c and d is the perturbative wave function, respectively. By utilizing the redundant memory in the storage of c, we can calculate perturbation without any extra memory compared to original CDFCI. We also use a strategy to eliminate the expensive repetitive evaluation of diagonal elements of Hamiltonian by creating a vector h which stores the diagonal entries of Hamiltonian. This strategy trades memory usage for computational time and reduces the computing time significantly. Furthermore, we use quadruple-precision floating-point numbers to improve the numerical stability of perturbative energy. We demonstrate the effectiveness of the single-threaded IP-CDFCI and the multithreaded CDFCI + PT, respectively, by performing calculations on several small molecular benchmarks as well as challenging correlated system: the chromium dimer.
Recent developments in the ChronusQuantum (ChronusQ) software package highlight its advanced capabilities in simulating quantum dynamics of both electrons and nuclei, accurately accounting for relativistic and correlation effects, and leveraging high-performance implementations tailored for modern heterogeneous, massively parallel computing architectures. ChronusQ is an open-source tool released under the GNU General Public License v2, designed to solve complex problems in ab initio electronic structure theory. It is developed by a collaborative team across leading research universities and is renowned for its integrated time-dependent quantum mechanical theories, spectral analysis tools, and variational relativistic frameworks. With support from the Office of Advanced Cyberinfrastructure and the Division of Chemistry at the National Science Foundation, the team has expanded ChronusQ's capabilities in several significant directions. We have developed the nuclear-electronic orbital time- dependent configuration interaction (NEO-TDCI) method, which enables accurate treatment of hydrogen tunneling and double excitations—cases where multiconfigurational approaches are essential. Additionally, we introduced the polarizable continuum model and gauge-invariant atomic orbitals, both compatible with NEO, to simulate solvent effects and magnetic properties. ChronusQ has also significantly advanced its relativistic simulation toolkit with the implementation of a four-component relativistic framework, offering a robust foundation for simulating the quantum behavior of heavy atoms, where relativistic effects are particularly pronounced. Building on this, ChronusQ now integrates relativistic coupled cluster (CC) framework and the distributed active space (DAS) framework, providing highly accurate treatments of electron correlation. Key modules in the NEO, CC, and DAS frameworks are implemented with MPI and GPU-parallelized computation. Notably, our DAS framework has set a new benchmark by surpassing the quadrillion-determinant barrier in a numerically exact configuration interaction method. This year, we also enhanced the user and developer experience by redesigning ChronusQ's module structure to support flexible extension and integration of existing features, reliable restart of interrupted calculations, and seamless interfacing with other computational chemistry software. The physical insights enabled by ChronusQ continue to drive innovations in sustainable energy, catalysis, quantum computing, and other domains with immediate societal impact.
We develop a multithreaded parallel coordinate descent full configuration interaction algorithm (mCDFCI) for the electronic structure ground-state calculation in the configuration interaction framework. The FCI problem is reformulated as an unconstrained minimization problem and tackled by a modified block coordinate descent method with a deterministic compression strategy. mCDFCI is designed to prioritize determinants based on their importance, with block updates enabling efficient parallelization on shared-memory, multicore computing infrastructure. We demonstrate the efficiency of the algorithm by computing an accurate benchmark energy for the chromium dimer in the Ahlrichs SV basis (48e, 42o), which explicitly includes 2.07 × 10 9 variational determinants. We also provide the binding curve of the nitrogen dimer under the cc-pVQZ basis set (14e, 110o). Benchmarks show up to 79.3% parallel efficiency on 128 cores.
We present a prototype implementation of the Quantum-Selected Configuration Interaction (QSCI) method on a heterogeneous platform that integrates quantum simulation with high-performance computing (HPC). In this workflow, a GPU-based simulator emulates a quantum processor to prepare and sample reference states via the variational quantum eigensolver (VQE), while CPU nodes perform optimization and large-scale subspace diagonalization using EigenExa. This design enables seamless coordination between quantum state preparation and numerical linear algebra within HPC environments. The framework efficiently handles subspace dimensions up to 100,000 and exhibits favorable scaling with system size. Benchmark experiments on hydrogen chains demonstrate that relatively large systems can be processed within practical runtimes, highlighting the potential of hybrid HPC-QC integration for scalable quantum chemistry.
We present ffsim, an open-source software library for fast simulation of fermionic quantum circuits. ffsim exploits conservation of particle number and the z component of spin, symmetries present in a wide range of fermionic systems, to dramatically reduce memory usage and simulation time compared to general-purpose quantum circuit simulators. Compared to FQE, a library with similar functionality, ffsim differs in software design and is faster on a representative set of simulation benchmarks. Beyond state vector evolution by basic fermionic gates, ffsim offers a number of additional features including variational ansatzes, Hamiltonian time evolution via Trotter-Suzuki product formulas, efficient sampling of Slater determinants, seamless integration with Qiskit and PySCF, and comprehensive documentation. We demonstrate ffsim's capabilities on scientific applications involving quantum circuits of up to 64 qubits.
The Many-Body Adaptive Configuration Interaction Suite (MACIS) is a modern C++ software infrastructure for the development of selected-configuration interaction (sCI) methods for the fermionic many-body problem in quantum chemistry and materials science. MACIS provides a high-performance, parallel implementation of the Adaptive Sampling Configuration Interaction (ASCI) method as related solvers such as self-consistent orbital optimization and the evaluation of excited states and spectral functions. Unlike existing sCI software, MACIS is developed as a modular software infrastructure which allows it to exist both as a standalone sCI solver and as a library to integrate into existing many-body codes. This modularity allows MACIS to be quickly extensible, including its integration with other sCI methods and high-performance solvers.