22nd Annual SQuInT Workshop!

Program

SESSION 2: Near-term quantum devices and implementations Chair: (Justin Dressel (Chapman))
10:30am - 11:00am	Sam Gunn, University of Texas, Austin On the classical hardness of spoofing linear cross-entropy benchmarking
	Abstract. Recently, Google announced the first demonstration of quantum computational supremacy with a programmable superconducting processor. Their demonstration is based on collecting samples from the output distribution of a noisy random quantum circuit, then applying a statistical test to those samples called Linear Cross-Entropy Benchmarking (Linear XEB). This raises a theoretical question: how hard is it for a classical computer to spoof the results of the Linear XEB test? In this short note, we adapt an analysis of Aaronson and Chen [2017] to prove a conditional hardness result for Linear XEB spoofing. Specifically, we show that the problem is classically hard, assuming that there is no efficient classical algorithm that, given a random n-qubit quantum circuit C, estimates the probability of C outputting a specific output string, say 0^n, with variance even slightly better than that of the trivial estimator that always estimates 1/2^n. Our result automatically encompasses the case of noisy circuits.
11:00am - 11:30am	Eleanor Rieffel, NASA - Ames Research Center Utilizing NISQ devices for evaluating quantum algorithms
	Abstract. With the advent of quantum supremacy, we have an unprecedented opportunity to explore quantum algorithms in new ways. The emergence of general-purpose quantum processors opens up empirical exploration of quantum algorithms far beyond what has been possible to date. Challenging computational problems arising in the practical world are often tackled by heuristic algorithms. While heuristic algorithms work well in practice, by definition they have not been analytically proven to be the best approach or to outperform the best previous approach. Instead, heuristic algorithms are empirically tested on benchmark and real-world problems. With the empirical evaluation NISQ hardware enables, we expect a broadening of established applications of quantum computing. What to run and how best to utilize these still limited quantum devices to gain insight into quantum algorithms remain open research questions. We discuss opportunities and challenges for using NISQ devices to evaluate quantum algorithms, including in elucidating quantum mechanisms and their uses for quantum computational purposes, in the design of novel or refined quantum algorithms, in compilation, error-mitigation, and robust algorithms design, and in techniques for evaluating quantum algorithms empirically.
11:30am - 12:00pm	Hristo Djidjev, Los Alamos National Laboratory Peering into the anneal process of a quantum annealer
	Abstract. To solve an optimization problem using a commercial quantum annealer, one has to represent the problem of interest as an Ising or QUBO (quadratic unconstrained binary optimization) problem and submit its coefficients to the annealer, which then returns a user-specified number of low-energy solutions. It will be useful to know what happens in the quantum processor during the anneal process so that one could design better algorithms or suggest improvements to the hardware. However, existing quantum annealers are not able to directly extract such information from the processor. Hence, in this work we propose to use advanced features of the newest annealer generation, the D-Wave 2000Q (DW2KQ), to indirectly infer information about the anneal process evolution. Specifically, DW2KQ allows users to customize the anneal schedule, that is, the schedule with which the anneal fraction is changed from the start to the end of the anneal. Using this feature, we design a set of modified anneal schedules whose outputs can be used to generate information about the states of the system at equally spaced time points during a standard anneal of Q. With this process, called slicing, we obtain approximate distributions of lowest-energy anneal solutions as the anneal time evolves. We use our technique to obtain a variety of insights into DW2KQ such as when individual bits in an evolving solution flip during the anneal process and when they stabilize, and the freeze-out points for individual qubits.

SQuInT Chief Organizer
Akimasa Miyake, Associate Professor
amiyake@unm.edu

SQuInT Co-Organizer
Brian Smith, Associate Professor UO
bjsmith@uoregon.edu

SQuInT Program Committee
Postdoctoral Fellows:
Markus Allgaier (UO OMQ)
Sayonee Ray (UNM CQuIC)
Pablo Poggi (UNM CQuIC)
Valerian Thiel (UO OMQ)

SQuInT Event Co-Organizers (Oregon)
Jorjie Arden
jarden@uoregon.edu
Holly Lynn
hollylyn@uoregon.edu

SQuInT Event Administrator (Oregon)
Brandy Todd

SQuInT Administrator (CQuIC)
Gloria Cordova
gjcordo1@unm.edu
505 277-1850

SQuInT Founder
Ivan Deutsch, Regents' Professor, CQuIC Director
ideutsch@unm.edu

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Southwest Quantum Information and Technology

22nd Annual SQuInT Workshop February 8-10, 2020
Eugene, Oregon

Program

SESSION 2: Near-term quantum devices and implementations

Southwest Quantum Information and Technology

22nd Annual SQuInT Workshop February 8-10, 2020Eugene, Oregon

Program

SESSION 2: Near-term quantum devices and implementations

22nd Annual SQuInT Workshop February 8-10, 2020
Eugene, Oregon