Alumni

Friday, January 25, 2019 12:30 pm - 12:30 pm EST (GMT -05:00)

PhD Thesis Defence

Formal Methods in Quantum Circuit Design

PhD Candidate: Matthew Amy
Supervisor: Michele Mosca

Oral defence in QNC B204.

The design and compilation of correct, efficient quantum circuits is integral to the future operation of quantum computers. This thesis makes contributions to the problems of optimizing and verifying quantum circuits, with an emphasis on the development of formal models for such purposes. We also present software implementations of these methods, which together form a full stack of tools for the design of optimized, formally verified quantum oracles.

In his own words, Marc Morin is “addicted to the game.”

Morin is the CEO and co-founder at Auvik Networks, pronounced awe-vik, as in awesome. “It’s like having a child who does way better than you and it’s awesome,” Morin explained at the CryptoWorks21 Distinguished Lecture last fall. Elaborating on his evolving role as a CEO in a tech company, he shared lessons learned­—the mistakes he made and the things he got right—during his personal journey as a serial technology entrepreneur. 

Friday, January 25, 2019 11:45 am - 11:45 am EST (GMT -05:00)

RAC1 Journal Club/Seminar Series

Spontaneous Raman emission in cold atoms inside a hollow-core waveguide

Taehyun Yoon, Institute for Quantum Computing

Cold atoms confined inside hollow-core waveguides enable strong-matter interactions, thus offer a unique platform for studies of quantum and non-linear optics. We developed an experimental system that traps cesium atoms in a magneto optical trap (MOT) and loads these atoms into a hollow core photonic crystal fiber using a dipole trap at cesium magic wavelength (935 nm), which removes the AC-Stark shift of the optical transition and suppresses the inhomogeneous broadening.

Monday, January 7, 2019 2:30 pm - 2:30 pm EST (GMT -05:00)

Quadratic speedup in finding a marked vertex via quantum walk

Stacey Jeffery, QuSoft, Research Centre for Quantum Software

A random walk on a graph, P, with marked vertex set M, finds a marked vertex using a O(HT(P,M)) steps of the walk, where HT(P,M) is the hitting time. Previous quantum algorithms could detect the presence of a marked vertex in O(sqrt{HT(P,M)}) steps, or find a marked vertex in O(sqrt{HT(P,M)}) steps if M contained at most one vertex, but the case of finding in the presence of multiple marked vertices was left as an open problem.

Friday, January 11, 2019 1:00 pm - 1:00 pm EST (GMT -05:00)

Quantum Rangefinding

Stefan Frick, University of Bristol, UK

Rangefinding has many applications in navigation, civil engineer, construction, military, surveillance and security. Most commonly rangefinders estimate the distance to an object by measuring the time of flight of light for the journey to and returning from the target. Conventional techniques use lasers for illumination in state of the art rangefinding systems. However, the particular state of light lasers produce makes them easy to detect.

Tuesday, December 18, 2018 11:00 am - 11:00 am EST (GMT -05:00)

Fault-tolerant resource estimation of quantum random-access memories

PhD Seminar: Olivia Di Matteo

Quantum random-access memories (qRAM) are required by numerous quantum algorithms. In many cases, qRAM queries are the limiting factor in the implementation of these algorithms. In the limit of a large number of queries, there will be a massive resource overhead, as in this regime it is not possible to bypass the need for active error correction. In this talk, I will present our work towards quantifying this overhead. We will explore a variety of different qRAM circuits designed to query classical bits in superposition.

Friday, March 8, 2019 11:45 am - 11:45 am EST (GMT -05:00)

RAC1 Journal Club/Seminar Series

Crafting high-dimensional tools for photonic quantum networks with tailored nonlinear optics

John Donohue, Institute for Quantum Computing

The time-frequency degree of freedom of light offers an intrinsically high-dimensional encoding space which is naturally compatible with waveguide devices and fiber infrastructure. However, coherent manipulation and measurement the information-carrying modes presents a challenge due to the sub-picosecond timescales inherent to downconversion-based photon sources. In this talk, I will discuss methods based on ultrafast pulse shaping and sum-frequency generation to address these temporal modes.

Thursday, December 13, 2018 2:30 pm - 2:30 pm EST (GMT -05:00)

Applied Mathematics Colloquium: Quantum Universe

Neil Turok, Perimeter Institute

Observations reveal the cosmos to be astonishingly simple, and yet deeply puzzling, on the largest accessible scales. Why is it so nearly symmetrical? Why is there a cosmological constant (or dark energy) and what fixes its value? How did everything we see emerge from a singular “point” in the past?

Friday, December 14, 2018 1:15 pm - 1:15 pm EST (GMT -05:00)

RAC1 Journal Club/Seminar Series

Wavelength selective thermal emitters using nitride quantum wells and photonic crystals

Dr. Dongyeon Daniel Kang, Kyoto University

Wavelength selective thermal emitters are highly desired for the development of the compact/energy-efficient spectroscopic sensing systems capable of detecting various gases such as COx, CH4, and NOx, which are strongly needed in environmental science, medical care, and other industrial applications. In addition, for the latter applications, dynamic control of thermal emission intensity is important for such emitters because synchronous detection can increase the signal-to-noise ratio significantly.

Friday, December 7, 2018 2:00 pm - 2:00 pm EST (GMT -05:00)

Quantum Advantage in Learning Parity with Noise

Daniel Kyungdeock Park, Korea Advanced Institute of Science and Technology

Machine learning is an interesting family of problems for which near-term quantum devices can provide considerable advantages. In particular, exponential quantum speedup is recently demonstrated in learning a Boolean function that calculates the parity of a randomly chosen input bit string and a hidden bit string in the presence of noise, the problem known as learning parity with noise (LPN).