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12:30 -13:30 pm
Speaker: Kunal Marwaha
Room: JCL 298
Bounds on approximating Max kXOR with quantum and classical local algorithms
Hybrid quantum-classical methods offer a new paradigm for tackling challenging learning and optimization tasks. While quantum approaches to combinatorial optimization such as the quantum approximate optimization algorithm (QAOA) have attracted much recent attention, relatively few results are known concerning their potential for quantum advantage. To clarify this, a recent line of work has sought to compare the performance of low-depth realizations of QAOA with local classical algorithms, where in each case the algorithm’s output for each variable depends only on a fixed neighborhood around that variable. We continue this research direction on the combinatorial optimization problem Max kXOR, a generalization of two problems previously studied with quantum algorithms.
Kunal is a first-year Ph.D student in quantum computing advised by Bill Fefferman. He previously worked as a software engineer and still makes a lot of online hobby projects. He especially likes to play foosball in the grad lounge.