Research Directions

Research

Quantum algorithms, excited-state and relativistic theory, materials simulation, and software infrastructure for chemistry.

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Four connected directions define the group’s research program, from quantum algorithms for molecules to materials simulation and software development.

01 Quantum Chemistry on Quantum Computers 02 Relativistic, Excited States, and Challenging Electronic Structure 03 Materials Simulation Using Tools from Quantum Chemistry 04 Software for Quantum Computing and Quantum Chemistry

Quantum Chemistry on Quantum Computers

The Asthana Group develops quantum and quantum-classical methods for electronic-structure simulation, with an emphasis on turning quantum computing into a practical tool for chemically meaningful problems. Our work spans ground states, excited states, response properties, and robust subspace formulations, with a particular focus on methods that combine chemical rigor, numerical stability, and relevance to emerging hardware. We are especially interested in identifying the regimes where quantum algorithms can move beyond proof-of-principle demonstrations and toward genuine quantum utility for chemistry.

Selected highlights

Generalized Eigenvalue Problem in Subspace-Based Excited-State Methods for Quantum Computers Prince Frederick Kwao et al., J. Chem. Theory Comput. 22, 6, 2892-2903 (2026)
Exact and Tunable Quantum Krylov Subspaces via Unitary Decomposition Ayush Asthana, arXiv:2512.11788 (2025)
Quantum self-consistent equation-of-motion method for computing molecular excitation energies, ionization potentials, and electron affinities on a quantum computer Ayush Asthana et al., Chem. Sci. 14, 2405 (2023)
Quantum simulation of molecular response properties Ashutosh Kumar et al., J. Chem. Theory Comput. 19, 9136 (2023)
Chemically decisive benchmarks on the path to quantum utility Srivathsan Poyyapakkam Sundar et al., arXiv:2601.10813 (2026)
NSF EPSCoR Fellow award (2024)
NSF ExpandQISE award (2024)

See full publications list

Relativistic, Excited States, and Challenging Electronic Structure

A central theme of the group is the development of theory for electronically challenging molecules, especially excited states, strong correlation, and heavy-element systems where relativistic and spin-orbit effects are essential. We aim to connect modern excited-state quantum chemistry, relativistic many-body theory, and emerging quantum-algorithm ideas to build methods that remain reliable in regimes where standard approximations often break down. This work provides a foundation for studying chemically important systems in which one or all of electronic excitation, strong correlation, and relativity must be treated to achieve predictive computational results.

Selected highlights

Analytic gradients for spinor-based relativistic exact-two-component equation-of-motion coupled-cluster singles and doubles method Chaoqun Zhang et al., J. Chem. Phys. 159, 244113 (2023)
Quantum simulation of molecular response properties Ashutosh Kumar et al., J. Chem. Theory Comput. 19, 9136 (2023)
Mapping the Electronic Structure of the Uranium(VI) Dinitride Molecule, UN₂ Gaoxiang Liu et al., J. Phys. Chem. A 124, 6486 (2020)
NSF ExpandQISE award (2024)
UND Early Career grant (2023)

See full publications list

Materials Simulation Using Tools from Quantum Chemistry

We are also interested in bringing the language, methods, and standards of quantum chemistry into materials simulation. The broader goal is to use systematically improvable many-body methods, quantum-classical workflows, and chemically motivated benchmarks to study correlated materials with the same quantitative mindset used in molecular theory. This direction connects electronic-structure theory, quantum computing, and data-driven modeling, and it supports applications ranging from benchmark design to quantum-classical simulation of strongly correlated materials.

Selected highlights

DOE ARPA-E QC3 project, Quantum-Classical Ab Initio Co-Simulation of Unconventional Superconductors (2026-2029)

Software for Quantum Computing and Quantum Chemistry

Software development is an important part of our research program. We build and maintain tools that make quantum-computing methods for chemistry easier to develop, test, and use, with an emphasis on subspace methods, benchmarking, and automated derivation of many-body equations. These efforts are meant not only to support the group’s own research, but also to provide infrastructure that can accelerate broader progress in quantum chemistry and quantum computing.

Selected highlights

QCANT Research codebase for quantum-computing methods in chemistry, especially subspace and excited-state workflows.
BenchmarkQC Benchmarking suite for chemically relevant quantum-utility studies across diverse correlation regimes.
AutoGen-wick Python package for automated derivation of UCC and coupled-cluster many-body equations.

See software page