Quantum Research Seminars Toronto consist of two 30 min talks about some Quantum Computation topic. Seminars are given by high-level quantum computing researchers with the focus on disseminating their research among other researchers from this field. We encourage to attend researchers regardless of their experience as well as graduate and undergraduate students with particular interest in this field. Basic notions on quantum computing are assumed, but no expertise in any particular subject of this field.
In this 21st series of seminars, the speakers will be Yulong Dong from University of California, Berkeley and Sepehr Ebadi from Harvard University. Their talks are titled "Quantum eigenvalue problems on early fault-tolerant quantum computers" and "Quantum Optimization of Maximum Independent Set Using Rydberg Atom Arrays", respectively.
The event recording, slides and chat history will be published in our Youtube channel and sent to the registered participants.
Looking forward to seeing you all!
Recently, quantum supremacy experiments (by Google in 2019 and by USTC in 2020) have brought quantum computation to the attention of the public and diverse scientific researchers. Quantum computers hold the promise of dramatically accelerating calculations in a wide range of fields, especially in numerical linear algebra. In this talk, I will first develop a tool called quantum eigenvalue transformation of unitary matrices with real polynomials (QET-U). Then, I will introduce a simple but efficient algorithm for preparing ground state and estimating ground energy of a Hamiltonian. The algorithm is based on QET-U and is suitable for early fault-tolerant quantum devices. It outperforms all previous algorithms with a comparable circuit structure for estimating the ground energy. I will also discuss the optimization of the circuit implementation by exploiting the anti-commutation relation of certain quantum spin Hamiltonians.
About the speaker:
Yulong Dong received his B.S. degree from the Department of Chemical Physics in University of Science and Technology of China (USTC) in 2018. He currently pursues the Ph.D. degree in Applied Mathematics in the Department of Mathematics in University of California, Berkeley. His research interest lies broadly in quantum algorithms, numerical linear algebra, applied and numerical analysis of optimization and control theory.
Realizing quantum speedup for solving practically relevant, computationally hard problems is a central challenge in quantum information science. Using Rydberg atom arrays composed of up to 289 coupled qubits in two spatial dimensions, we experimentally investigate quantum optimization algorithms for solving the Maximum Independent Set problem. We use a hardware-efficient encoding associated with Rydberg blockade, realize closed-loop optimization to test several variational algorithms, and subsequently apply them to systematically explore a class of nonplanar graphs with programmable connectivity. We find that the problem's hardness is controlled by the number of correct solutions and the number of local minima. We then experimentally benchmark the quantum algorithm's performance against optimized classical simulated annealing. On the hardest instances, we observe a superlinear quantum speedup in finding exact solutions for sufficiently long evolution times beyond the shallow-circuit-depth regime, and analyze its origins.
About the speaker:
Sepehr is pursuing a PhD in the Department of Physics at Harvard University, advised by Markus Greiner and Mikhail Lukin. Prior to that he obtained his bachelor's degree in Engineering Science (Physics option) from University of Toronto, with an undergraduate research focused on creation of ultracold molecules. His main research interest lies in the intersection of quantum simulation and quantum computing -- utilizing large atom arrays with Rydberg interactions to study novel many-body physics and solve practical computational problems.