Research

Yuchen Wang

Selected themes across quantum chemistry and many-body theory

1. Quantum computers for quantum chemistry

Quantum computers presents unique opportunities for chemical simulations. From electronic structure to machine learning potential to quantum dynamics, we explore the possibility of "quantum advantage". Special link between quantum state tomography and reduced density matrix is the focus at this point.

Selected papers

  1. Warren, S.; Wang, Y.; Benavides-Riveros, C. L.; Mazziotti, D. A. Quantum algorithm for polaritonic chemistry based on an exact ansatz. Quantum Sci. Technol. 2025, 10, 02LT02.
  2. Wang, Y.; Cianci, C.; Avdic, I.; Dutta, R.; Warren, S.; Allen, B.; Vu, N. P.; Santos, L. F.; Batista, V. S.; Mazziotti, D. A. Characterizing conical intersections of nucleobases on quantum computers. J. Chem. Theory Comput. 2025, 21, 1213-1221.
  3. Warren, S.; Wang, Y.; Benavides-Riveros, C. L.; Mazziotti, D. A. Exact ansatz of fermion-boson systems for a quantum device. Phys. Rev. Lett. 2024, 133, 080202.
  4. Wang, Y.; Mazziotti, D. A. Quantum simulation of conical intersections. Phys. Chem. Chem. Phys. 2024, 26, 11491-11497.
  5. Wang, Y.; Sager-Smith, L. M.; Mazziotti, D. A. Quantum simulation of bosons with the contracted quantum eigensolver. New J. Phys. 2023, 25, 103005.

2. Machine learning for quantum simulation and chemistry

Machine learning provides a route to compress the otherwise rapidly growing circuit representations needed for quantum many-body simulations. In my reinforcement-learning work, the contracted Schrodinger equation update is formulated as a Markov decision process, allowing an agent to choose compact exponential-Ansatz circuit operations from the current residual while retaining high accuracy across molecular geometries.

Selected papers

  1. Wang, Y.; Avdic, I.; Mazziotti, D. A. Shadow ansatz for the many-fermion wave function in scalable molecular simulations on quantum computing devices. Phys. Rev. A 2025, 112, 022432.
  2. Wang, Y.; Mazziotti, D. A. Quantum many-body simulations from a reinforcement-learned exponential Ansatz. Phys. Rev. A 2025, 112, 022403.

3. Mathematical programming in chemistry

Mathematical programming offers a way to turn chemical structure and many-body physics into constrained optimization problems. In reduced density matrix theory, for example, molecular energies can be optimized directly over two-particle reduced density matrices, while N-representability conditions impose semidefinite and related constraints that keep the solution physically meaningful.

Even more exciting is to think about how chemical dynamics can be reformulated as mathematical programming problems. Nature knows it's way of finding the minima, so does every chemical reaction happens on complicated Riemannian manifold.

Selected papers

  1. Wang, Y.; Avdic, I.; Rose, M.; Payne Torres, L. I.; Schouten, A. O.; Sung, K. J.; Mazziotti, D. A. Correlated purification for restoring N-representability in quantum simulation. Phys. Rev. A 2026, 113.
  2. Wang, Y.; Mazziotti, D. A. Electronic excited states from a variance-based contracted quantum eigensolver. Phys. Rev. A 2023, 108, 022814.
  3. Avdic, I.; Wang, Y.; Rose, M.; Payne Torres, L. I.; Schouten, A. O.; Sung, K. J.; Mazziotti, D. A. Constrained shadow tomography for molecular simulation on quantum devices. Chem. Sci. 2026, advance article.

4. Spin-orbit coupling induced dynamics

We have successfully constructed the spin-orbit coupling matrix elements from relativistic electronic structure theory. The spin-orbit coupling forms the spin-orbit conical intersection (SOCI). However, due to the fine-splitting of near degenerate states, the SOCI are not exactly a replica of conical intersection. Instead they present unique topography for spin-polarization simulations.

Selected papers

  1. Wang, Y.; Yarkony, D. R. Conical intersection seams in spin-orbit coupled systems with an even number of electrons: A numerical study based on neural network fit surfaces. J. Chem. Phys. 2021, 155, 174115.
  2. Wang, Y.; Guo, H.; Yarkony, D. R. Internal conversion and intersystem crossing dynamics based on coupled potential energy surfaces with full geometry-dependent spin-orbit and derivative couplings. Nonadiabatic photodissociation dynamics of NH3(A) leading to the NH(X3Σ−, a1Δ) + H2 channel. Phys. Chem. Chem. Phys. 2022, 24, 15060-15067.

5. Diabatic potential energy matrices

We use diabatic potential energy matrices, a generalization of potential energy surfaces, to study nonadiabatic chemistry. I spent times in Prof. Yarkony's group which is known for making probably the most dedicated potential energy matrices from derivative coupling diabatization. My recent focus is on the application of artificial neural networks and the extension to dipoles and spin-orbit couplings.

Selected papers

  1. Wang, Y.; Xie, C.; Guo, H.; Yarkony, D. R. A quasi-diabatic representation of the 1,21A states of methylamine. J. Phys. Chem. A 2019, 123, 5231-5241.
  2. Wang, Y.; Guan, Y.; Yarkony, D. R. On the impact of singularities in the two-state adiabatic to diabatic state transformation: A global treatment. J. Phys. Chem. A 2019, 123, 9874-9880.
  3. Wang, Y.; Guan, Y.; Guo, H.; Yarkony, D. R. Enabling complete multichannel nonadiabatic dynamics: A global representation of the two-channel coupled, 1,21A and 13A states of NH3 using neural networks. J. Chem. Phys. 2021, 154, 094121.
  4. Avanessian, C.; Wang, Y.; Yarkony, D. R. Floquet-engineered photodissociation simulated using coupled potential energy and dipole matrices. J. Phys. Chem. Lett. 2024, 15, 9905-9911.