Niladri Gomes

Research interest:  Quantum computing algorithms, Condensed matter physics

My current research involves developing novel algorithms for quantum computers to solve scientific problems and beyond. Due to the highly noisy and expensive nature of quantum devices, it is crucial to have a deep understanding of their hardware architecture to develop NISQ (noisy intermediate-scale quantum) algorithms. Thus, I am keen on collaborating with interdisciplinary teams to improve my knowledge of the device and develop algorithms that are resource-efficient. I am also interested in exploring other aspects of advanced numerical methods. I completed my Ph.D. in computational condensed matter physics at the University of Arizona, where I developed codes for the Path Integral Renormalization Group (PIRG) method to study superconductivity in two-dimensional materials.

Education:

• Ph.D., Physics, University of Arizona 

Find me on Google Scholar for a complete list of publications.

Publications:

• Computing the many-body Green's function with adaptive variational quantum dynamics, Niladri Gomes, David B Williams-Young, Wibe A de Jong, Journal of Chemical Theory and Computation, 2023.
• Adaptive variational quantum minimally entangled typical thermal states for finite temperature simulations, João C Getelina, Niladri Gomes, Thomas Iadecola, Peter P Orth, Yong-Xin Yao, SciPost Phys., 2023.

Preprints:

1. A hybrid method for quantum dynamics simulation, Niladri Gomes, Jia Yin, Siyuan Niu,  Chao Yang, and Wibe Albert de Jong, arXiv:2307.15231, 2023.
2. Adaptive variational simulation for open quantum systems,  Huo Chen, Niladri Gomes, Siyuan Niu and Wibe Albert de Jong, arXiv:2305.06915, 2023.

3.  Nearly-optimal state preparation for quantum simulations of lattice gauge theories, Christopher F. Kane, Niladri Gomes, and Michael Kreshchuk, arXiv:2310.13757,  2023.