Seminar

Frederic Magniez, Université Paris Diderot

We describe a new quantum paradigm, that we call Quantum Chebyshev’s inequality, to approximate with relative error the mean of any random variable with a number of quantum samples that is linear in the ratio of the square root of the variance to the mean. Classically the dependency is quadratic. To illustrate this method, we apply it to the approximation of frequency moments in the multi-pass streaming model, and to the approximation of the number of edges and triangles in the quantum graph query access model.

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.

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.

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.

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.

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.

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?

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 CO_x, CH₄, and NO_x, 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.

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).

Li Liu

Following my previous seminar talk on embezzlement of entanglement, this talk introduces a more general version of the problem — self-embezzlement. Instead of embezzling a pair of entangled state from a catalyst, self-embezzlement aims to create two copies of the catalyst state using only local operators.