CCI Phase I: NSF Center for Quantum Dynamics on Modular Quantum Devices (CQD-MQD)

The NSF Center for Quantum Dynamics on Modular Quantum Devices (CQD-MQD) is supported by the Centers for Chemical Innovation (CCI) Program of the Division of Chemistry. This Phase I Center is led by Professor Victor Batista from Yale University. Other team members include Professors Michel Devoret from Yale University, Sabre Kais from Purdue University, Lea Ferreira Dos Santos from Yeshiva University, and Eitan Geva from the University of Michigan.

The project is motivated by the huge gap that currently exists between the problems for which a quantum computer could be useful in chemistry and what can actually be simulated today with state-of-the-art quantum computers. The challenge is that most well-known quantum computing (QC) algorithms have hardware requirements that far exceed the capabilities of current state-of-the-art quantum computers by several orders of magnitude.

Closing that QC gap is thus essential to make QC technology finally available to studies of reaction dynamics and spectroscopy, beyond the rather simple proof-of-concept applications that so far have been developed. Demonstrating a new generation of quantum electro-dynamics (cQED) platforms, in conjunction with quantum algorithms and fundamental studies of quantum reaction dynamics, has the potential to change the landscape of quantum simulations and lead to significant advances in chemistry with impact on other fields ranging from biology to materials science to engineering.

Partnerships with the Stern College for Women at Yeshiva University, the Yale Pathways Summer Scholars program, and programs at Purdue and the University of Michigan will be developed to specifically establish an ecosystem for development of a well-trained workforce in quantum information science and in the modeling of molecular systems with quantum devices.

The main goal of the CQD-MQD is to investigate chemical processes by using modular 3D circuit quantum electro-dynamics (cQED) platforms that can enable efficient realizations of molecular problems at the hardware level. An example of the type of quantum dynamical processes to be studied with the proposed quantum computing modules is the dynamics of photoisomerization that initiates the process of vision in vertebrates, involving non-adiabatic quantum dynamics at a conical intersection of potential energy surfaces.

Thus, the CQD-MQD will design bosonic modular circuits described by potential energy surfaces that directly map the corresponding molecular Hamiltonians of interest, thereby enabling quantum simulations with fundamentally new and potentially very efficient quantum devices. The CQD-MQD will embrace a climate of inclusion and diversity so that underrepresented minorities and women are included in the interdisciplinary, team-based research.

Specific goals for Phase I include (i) the design of modular 3D circuit quantum electrodynamics (cQED) platforms for molecular quantum dynamics simulations, (ii) development of algorithms for quantum simulations and quantum computing on the new cQED platforms, and (iii) applications of the developed bosonic modular devices and algorithms to simulations of photo-induced quantum reaction dynamics, vibronic many-body systems; and quantum chemical dynamics in the condensed phase. The CQD-MQD research and training program will establish an ecosystem with emphasis on recruitment and retention of female scientists and other members of underrepresented groups to advance the frontiers of knowledge in this burgeoning field and to train the next-generation workforce.

The scientific and technological outcomes have the potential to be transformative for the quantum simulation of chemical systems and have the potential to out-perform conventional quantum computing platforms and find application across a wide range of molecular systems and quantum phenomena.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.