This project supports theoretical research and education on the implementation of a special purpose quantum computer with practical devices.
Quantum computers with 50-100 qubits and decoherence times not long enough for general-purpose quantum computing can now be built in laboratories. With such devices, a quantum simulator, a special-purpose quantum computer, may be able to solve problems that cannot be solved with classical computers. A prerequisite to implementing quantum simulation is to prepare the simulator in an appropriate many-body ground state, something that could also benefit the solution of combinatorial optimization problems. These many-body states are often unknown, highly entangled, and hard to prepare with quantum logic gates. Despite previous efforts, it remains a challenging question to prepare such many-body states with high fidelity. The PI aims to develop a universal and implementable algorithm to efficiently and accurately generate such many-body ground states by coupling the quantum simulator to an auxiliary system that induces nonlinearity. This novel approach exploits a generic but unique property of nonlinear systems to suppress unwanted transitions between the ground state and the excited states. The objectives of this project include the development of the general framework for the algorithm, benchmarking the algorithm, and studying the effect of circuit noise. The algorithm will be tested on four models that represent problems of different interests in quantum simulation. Both numerical simulation using classical computers and hardware emulation using a superconducting cloud platform will be employed to test the algorithm. Because it exploits generic nonlinear dynamics, this algorithm can be applied to a broad range of problems.
The project not only has potential scientific impact on quantum computing and quantum simulation, but it can also open the door to a new direction that uses nonlinear physics for efficient quantum computing. The educational component of this project will broaden the participation of women and minority students and improve the diversity of the workforce in quantum technology. The PI will develop a course on advanced quantum computing, actively recruit students and postdocs from underrepresented groups, and organize activities with the women-in-STEM group and the Society of Physics Students at UC Merced. These activities will engage students at UC Merced, a Hispanic serving institute, in quantum research.
This project supports theoretical research and education on the implementation of quantum simulation with noisy intermediate-scale quantum devices.
A quantum simulator is a special-purpose quantum computer that can solve classically-hard problems. Efficient preparation of a many-body system in its ground state is a prerequisite for exploring quantum dynamics and many-body correlations in quantum simulators. Understanding the feasibility and limits on state preparation also benefits the study of combinatorial optimization problems in adiabatic quantum computing. Despite previous efforts, it remains a challenging question to prepare many-body states with high fidelity due to the lack of knowledge of the energy spectrum, the rapid decrease of energy gaps with the size of the quantum simulator, and the limited decoherence times in practical devices. The PI aims to develop a universal and implementable algorithm to efficiently and accurately generate many-body ground states by coupling a quantum simulator to an auxiliary system that induces nonlinearity. This novel approach exploits the unique dynamics in the vicinity of bifurcation points, which is a generic property in nonlinear systems, to enable self-governed adiabatic evolution with significantly suppressed diabatic transitions. The project includes three objectives: 1. developing the generic framework, operational protocol, and requirements on the quantum circuits for the algorithm, 2. benchmarking the algorithm and comparing its performance with other methods, and 3. qualitatively studying the effect of circuit noise. The algorithm will be tested on four models representing different interests in quantum simulation: the transverse-field Ising model, an exact-cover problem, a finite-sized Jaynes-Cummings lattice, and toy models with multiple energy gaps. Both numerical simulation and hardware emulation using the IBM Q cloud platform will be employed to test the algorithm. Because it exploits generic nonlinear dynamics, this algorithm can be applied to a broad range of problems without knowledge of the energy spectrum or the construction of unphysical multipartite interactions.
The project not only has potential scientific impact on quantum computing and quantum simulation, but it can also open the door to a new direction that uses nonlinear physics for efficient quantum computing. The educational component of this project will broaden the participation of women and minority students and improve the diversity of the workforce in quantum technology. The PI will develop a course on advanced quantum computing, actively recruit students and postdocs from underrepresented groups, and organize activities with the women-STEM group and the Society of Physics Students at UC Merced. These activities will engage students at UC Merced, a Hispanic serving institute, in quantum research.
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.
