Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Sustainable high-performance open-source quantum dynamics and spectroscopy software

Tianyuan Zhang (21756974), Xiasong Li (9906889), Sharon Hammes‐Schiffer, Edward Valeev (3741013), Eugene DePrince (19434835)

Published Jul 22, 2025• 0 citations
Publisher

Abstract

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.

DOI
10.6084/m9.figshare.29614493.v1

Related papers

CDFCI: High-Performance Parallel Software for Quantum Many-Body Eigenvalue Problems

Yuejia Zhang, Zhe Wang, Jianfeng Lu +1 more

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.

arXiv:2605.04483•May 6, 2026•0 citations

macroqc 2.0: An electronic structure theory software for large-scale applications

Uğur Bozkaya, Betül Ermiş, Yavuz Alagöz +2 more

macroqc is a quantum chemistry software package designed for high-accuracy electronic structure computations and large-scale molecular simulations. The macroqc framework provides efficient implementations of energies and analytic gradients for a wide range of many-body perturbation theory and coupled-cluster (CC) methods. In particular, the analytic gradient implementations of second-order Møller-Plesset perturbation theory (MP2), coupled-cluster singles and doubles (CCSD), and CCSD with perturbative triples [CCSD(T)] exhibit excellent computational performance, even in comparison with established commercial quantum chemistry programs. In addition to conventional correlated methods, macroqc incorporates several advanced capabilities, including molecular fragmentation techniques for ground and excited state molecular systems and density-fitted analytic gradients. The software also supports interoperability with selected external packages through a flexible plugin framework, allowing developers to construct customized interfaces and extensions. The notable features of macroqc are the linear-scaling systematic molecular fragmentation (LSSMF) and the cluster-in-molecule (CIM) approaches, which enable the application of high-level post-Hartree-Fock approaches to large molecular systems that would otherwise be computationally prohibitive. Furthermore, the new machine learning (ML) library enables the integration of data-driven approaches into quantum chemical workflows, providing efficient tools for developing and applying ML-based models for molecular property prediction and electronic structure computations. With its combination of efficient implementations, advanced theoretical methods, and extensible design, macroqc is expected to serve as a useful platform for a broad range of computational chemistry applications.

The Journal of Chemical Physics•Oct 22, 2026•0 citations

Quantum Package 2.0: An Open-Source Determinant-Driven Suite of Programs

Yann Garniron, Thomas Applencourt, Kevin E. Gasperich +16 more

, where N is proportional to the system size. Therefore, performing accurate calculations on chemically meaningful systems requires (i) approximations that can lower the computational scaling and (ii) efficient implementations that take advantage of modern massively parallel architectures. Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multireference second-order perturbation theory (PT2). The determinant-driven framework allows the programmer to include any arbitrary set of determinants in the reference space, hence providing greater methodological freedom. The sCI method implemented in Quantum Package is based on the CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively) algorithm which complements the variational sCI energy with a PT2 correction. Additional external plugins have been recently added to perform calculations with multireference coupled cluster theory and range-separated density-functional theory. All the programs are developed with the IRPF90 code generator, which simplifies collaborative work and the development of new features. Quantum Package strives to allow easy implementation and experimentation of new methods, while making parallel computation as simple and efficient as possible on modern supercomputer architectures. Currently, the code enables, routinely, to realize runs on roughly 2 000 CPU cores, with tens of millions of determinants in the reference space. Moreover, we have been able to push up to 12 288 cores in order to test its parallel efficiency. In the present manuscript, we also introduce some key new developments: (i) a renormalized second-order perturbative correction for efficient extrapolation to the full CI limit and (ii) a stochastic version of the CIPSI selection performed simultaneously to the PT2 calculation at no extra cost.

arXiv:1902.08154•Journal of Chemical Theory and Computation•May 13, 2019•171 citations

DCA++: A software framework to solve correlated electron problems with modern quantum cluster methods

Urs R. Hähner, Gonzalo Álvarez, Thomas Maier +4 more

We present the first open release of the DCA++ project, a high-performance research software framework to solve quantum many-body problems with cutting edge quantum cluster algorithms. DCA++ implements the dynamical cluster approximation (DCA) and its DCA+ extension with a continuous self-energy. The algorithms capture nonlocal correlations in strongly correlated electron systems, thereby giving insight into high-Tc superconductivity. The code’s scalability allows efficient usage of systems at all scales, from workstations to leadership computers. With regard to the increasing heterogeneity of modern computing machines, DCA++ provides portable performance on conventional and emerging new architectures, such as hybrid CPU–GPU, sustaining multiple petaflops on ORNL’s Titan and CSCS’ Piz Daint supercomputers. Moreover, we show how sustainable and scalable development of the code base has been achieved by adopting standard techniques of the software industry. These include employing a distributed version control system, applying test-driven development and following continuous integration. Program Title: DCA++ Program Files doi: http://dx.doi.org/10.17632/482jm5cv77.1 Licensing provisions: BSD-3-Clause Programming language: C++14 and CUDA Nature of problem: Understanding the fascinating physics of strongly correlated electron systems requires the development of sophisticated algorithms and their implementation on leadership computing systems. Solution method: The DCA++ code provides a highly scalable and efficient implementation of the dynamical cluster approximation (DCA) and its DCA+ extension.

arXiv:1901.01047•Computer Physics Communications•Jan 17, 2019•36 citations

Quantum Electrodynamics Coupled-Cluster at Scale: High-Performance Implementation for Complex Systems

Nicholas P. Bauman, Himadri Pathak, Marcus D. Liebenthal +4 more

Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. We discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.

Journal of Chemical Theory and Computation•Dec 15, 2025•2 citations

Recent implementations in kylin 1.3: Improved computational efficiency of ab initio DMRG and a spin-adapted version of EC-MRCI

Yinxuan Song, Yingqi Tian, Yifan Cheng +1 more

Accurate evaluation of electron correlations is essential for the reliable quantitative description of electronic structures in strongly correlated systems, including bond-dissociating molecules, polyradicals, large conjugated molecules, and transition metal complexes. To provide a user-friendly tool for studying such challenging systems, our team developed Kylin 1.0 [J. Comput. Chem. 44, 1316 (2023)], an ab initio quantum chemistry program designed for efficient density matrix renormalization group (DMRG) and post-DMRG methods, enabling high-accuracy calculations with large active spaces. We have now further advanced the software with the release of Kylin 1.3, featuring optimized DMRG algorithms and an improved tensor contraction scheme in the diagonalization step. Benchmark calculations on the Mn4CaO5 cluster demonstrate a remarkable speed-up of up to 16 fater than Kylin 1.0. Moreover, a more user-friendly and efficient algorithm [J. Chem. Theory Comput. 17, 3414 (2021)] for sampling configurations from DMRG wavefunction is implemented as well. Additionally, we have also implemented a spin-adapted version of the externally contracted multi-reference configuration interaction (EC-MRCI) method [J. Phys. Chem. A 128, 958 (2024)], further enhancing the program’s efficiency and accuracy for electron correlation calculations.

Chinese Journal of Chemical Physics•Aug 1, 2025•5 citations
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.
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.
macroqc is a quantum chemistry software package designed for high-accuracy electronic structure computations and large-scale molecular simulations. The macroqc framework provides efficient implementations of energies and analytic gradients for a wide range of many-body perturbation theory and coupled-cluster (CC) methods. In particular, the analytic gradient implementations of second-order Møller-Plesset perturbation theory (MP2), coupled-cluster singles and doubles (CCSD), and CCSD with perturbative triples [CCSD(T)] exhibit excellent computational performance, even in comparison with established commercial quantum chemistry programs. In addition to conventional correlated methods, macroqc incorporates several advanced capabilities, including molecular fragmentation techniques for ground and excited state molecular systems and density-fitted analytic gradients. The software also supports interoperability with selected external packages through a flexible plugin framework, allowing developers to construct customized interfaces and extensions. The notable features of macroqc are the linear-scaling systematic molecular fragmentation (LSSMF) and the cluster-in-molecule (CIM) approaches, which enable the application of high-level post-Hartree-Fock approaches to large molecular systems that would otherwise be computationally prohibitive. Furthermore, the new machine learning (ML) library enables the integration of data-driven approaches into quantum chemical workflows, providing efficient tools for developing and applying ML-based models for molecular property prediction and electronic structure computations. With its combination of efficient implementations, advanced theoretical methods, and extensible design, macroqc is expected to serve as a useful platform for a broad range of computational chemistry applications.
, where N is proportional to the system size. Therefore, performing accurate calculations on chemically meaningful systems requires (i) approximations that can lower the computational scaling and (ii) efficient implementations that take advantage of modern massively parallel architectures. Quantum Package is an open-source programming environment for quantum chemistry specially designed for wave function methods. Its main goal is the development of determinant-driven selected configuration interaction (sCI) methods and multireference second-order perturbation theory (PT2). The determinant-driven framework allows the programmer to include any arbitrary set of determinants in the reference space, hence providing greater methodological freedom. The sCI method implemented in Quantum Package is based on the CIPSI (Configuration Interaction using a Perturbative Selection made Iteratively) algorithm which complements the variational sCI energy with a PT2 correction. Additional external plugins have been recently added to perform calculations with multireference coupled cluster theory and range-separated density-functional theory. All the programs are developed with the IRPF90 code generator, which simplifies collaborative work and the development of new features. Quantum Package strives to allow easy implementation and experimentation of new methods, while making parallel computation as simple and efficient as possible on modern supercomputer architectures. Currently, the code enables, routinely, to realize runs on roughly 2 000 CPU cores, with tens of millions of determinants in the reference space. Moreover, we have been able to push up to 12 288 cores in order to test its parallel efficiency. In the present manuscript, we also introduce some key new developments: (i) a renormalized second-order perturbative correction for efficient extrapolation to the full CI limit and (ii) a stochastic version of the CIPSI selection performed simultaneously to the PT2 calculation at no extra cost.
We present the first open release of the DCA++ project, a high-performance research software framework to solve quantum many-body problems with cutting edge quantum cluster algorithms. DCA++ implements the dynamical cluster approximation (DCA) and its DCA+ extension with a continuous self-energy. The algorithms capture nonlocal correlations in strongly correlated electron systems, thereby giving insight into high-Tc superconductivity. The code’s scalability allows efficient usage of systems at all scales, from workstations to leadership computers. With regard to the increasing heterogeneity of modern computing machines, DCA++ provides portable performance on conventional and emerging new architectures, such as hybrid CPU–GPU, sustaining multiple petaflops on ORNL’s Titan and CSCS’ Piz Daint supercomputers. Moreover, we show how sustainable and scalable development of the code base has been achieved by adopting standard techniques of the software industry. These include employing a distributed version control system, applying test-driven development and following continuous integration. Program Title: DCA++ Program Files doi: http://dx.doi.org/10.17632/482jm5cv77.1 Licensing provisions: BSD-3-Clause Programming language: C++14 and CUDA Nature of problem: Understanding the fascinating physics of strongly correlated electron systems requires the development of sophisticated algorithms and their implementation on leadership computing systems. Solution method: The DCA++ code provides a highly scalable and efficient implementation of the dynamical cluster approximation (DCA) and its DCA+ extension.
Coupled-cluster theory (CC) is a highly accurate and versatile method for simulating complex interactions within quantum systems. The extension of CC theory to model mixed electron-photon processes with quantum electrodynamics (QED) has improved our capability to predict cavity-modified chemistry, a field where photons are used as cost-effective and eco-friendly alternatives to catalyze/inhibit chemical reactions. However, calculations with CC methods, even without incorporating QED effects, are often prohibitively expensive. Simulations of larger systems require scalable infrastructures that exist for traditional CC methods but not for QED-CC methods. As such, we present a GPU-enabled, high-performance, open-source implementation of the quantum electrodynamics coupled-cluster method with single and double excitations (QED-CCSD) within the ExaChem quantum chemistry software package. ExaChem relies on the Tensor Algebra for Many-body Methods (TAMM) infrastructure: a parallel heterogeneous tensor library designed to achieve scalable performance on modern heterogeneous supercomputing platforms. We discuss theoretical foundations, algorithmic details, and numerical benchmarks to showcase the larger systems that ExaChem can simulate and how the integration of photonic degrees-of-freedom alters their ground-state properties.
Accurate evaluation of electron correlations is essential for the reliable quantitative description of electronic structures in strongly correlated systems, including bond-dissociating molecules, polyradicals, large conjugated molecules, and transition metal complexes. To provide a user-friendly tool for studying such challenging systems, our team developed Kylin 1.0 [J. Comput. Chem. 44, 1316 (2023)], an ab initio quantum chemistry program designed for efficient density matrix renormalization group (DMRG) and post-DMRG methods, enabling high-accuracy calculations with large active spaces. We have now further advanced the software with the release of Kylin 1.3, featuring optimized DMRG algorithms and an improved tensor contraction scheme in the diagonalization step. Benchmark calculations on the Mn4CaO5 cluster demonstrate a remarkable speed-up of up to 16 fater than Kylin 1.0. Moreover, a more user-friendly and efficient algorithm [J. Chem. Theory Comput. 17, 3414 (2021)] for sampling configurations from DMRG wavefunction is implemented as well. Additionally, we have also implemented a spin-adapted version of the externally contracted multi-reference configuration interaction (EC-MRCI) method [J. Phys. Chem. A 128, 958 (2024)], further enhancing the program’s efficiency and accuracy for electron correlation calculations.