Rina Wehbe, PhD candidate
David R. Cheriton School of Computer Science
Anastasia Kuzminykh, PhD candidate
David R. Cheriton School of Computer Science
While technologies exist that are either marketed for or can be adapted to the monitoring of toddlers and school-age children, parents' perspectives on these technologies have received only limited attention.
Jeff Avery, PhD candidate
David R. Cheriton School of Computer Science
Despite the ubiquity of touch-based input and the availability of increasingly computationally powerful touchscreen devices, there has been comparatively little work on enhancing basic canonical gestures such as swipe-to-pan and pinch-to-zoom.
Joel Reardon, Assistant Professor
Department of Computer Science, University of Calgary
Zhucheng Tu, Master’s candidate
David R. Cheriton School of Computer Science
Lei Zou, Institute of Computer Science and Technology
Peking University
Barzan Mozafari, Department of Computer Science and Engineering
University of Michigan
Weicong Ma, Master’s candidate
David R. Cheriton School of Computer Science
Chunhao Wang, PhD candidate
David R. Cheriton School of Computer Science
We give a dissipative quantum search algorithm that is based on a novel dissipative query model. If there are $N$ items and $M$ of them are marked, this algorithm performs a fixed-point quantum search using $O(\sqrt{N/M}\log(1/\epsilon))$ queries with error bounded by $\epsilon$. In addition, we present a continuous-time version of this algorithm in terms of Lindblad evolution.
Chunhao Wang, PhD candidate
David R. Cheriton School of Computer Science
We present a quantum algorithm for simulating the dynamics of Hamiltonians that are not necessarily sparse. Our algorithm is based on the assumption that the entries of the Hamiltonian are stored in a data structure that allows for the efficient preparation of states that encode the rows of the Hamiltonian. We use a linear combination of quantum walks to achieve a poly-logarithmic dependence on the precision.