# Events - Computing

Sep
15
Tue
2020
QSEC Quantum Computing Seminar Series: 09/15/2020, Optimal two-qubit circuits for universal fault-tolerant quantum computation, by Andrew Glaudell of Booz Allen Hamilton
Sep 15 @ 12:00 pm – 1:00 pm

##### Invited Speaker: Andrew Glaudell, Booz Allen Hamilton & GMU Mathematical Sciences Department

Topic: Optimal Two-Qubit Circuits for Universal Fault-Tolerant Quantum Computation

Location: Zoom

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester. The series will be kicked off on Tuesday September 15 with Mathematics Adjunct faculty Dr. Andrew Glaudell giving a short presentation. These events are free and open to the public. For any questions, contact qsec@gmu.edu. Below is the abstract of Dr. Glaudell’s talk and meeting information:

Abstract
We study two-qubit circuits over the Clifford+CS gate set which consists of Clifford gates together with the controlled-phase gate CS=diag(1,1,1,i). The Clifford+CS gate set is universal for quantum computation and its elements can be implemented fault-tolerantly in most error-correcting schemes with magic state distillation. However, since non-Clifford gates are typically more expensive to perform in a fault-tolerant manner, it is desirable to construct circuits that use few CS gates. In the present paper, we introduce an algorithm to construct optimal circuits for two-qubit Clifford+CS operators. Our algorithm inputs a Clifford+CS operator U and efficiently produces a Clifford+CS circuit for U using the least possible number of CS gates. Because our algorithm is deterministic, the circuit it associates to a Clifford+CS operator can be viewed as a normal form for the operator. We give a formal description of these normal forms as walks over certain graphs and use this description to derive an asymptotic lower bound of 5log(1/epsilon)+O(1) on the number CS gates required to epsilon-approximate any 4×4 unitary matrix.

Meeting Information
Join Zoom Meeting ID: 913 3925 3115 Passcode: 570565
https://gmu.zoom.us/j/91339253115?pwd=RkNBMlY5Rnl1OFNYSGNMTVhBdzNKUT09
One tap mobile
+13017158592,,91339253115#,,,,,,0#,,570565# US (Germantown)

Sep
22
Tue
2020
[MQA Seminar] Quantum Basics for the Curious: A Fireside Chat with Nobel Laureate Dr. Bill Phillips @ Zoom
Sep 22 @ 2:00 pm – 3:00 pm

##### Laurie Locascio, VP for Research; University of Maryland

RSVP

Curious about the buzz around quantum, but don’t really understand what the big deal is? Want to understand how the quantum revolution applies to you but don’t have a background in physics?

If so, please join the Mid-Atlantic Quantum Alliance (MQA) for a fireside chat between University of Maryland’s Vice President for Research, Dr. Laurie Locascio, and Nobel Laureate Dr. Bill Phillips. Dr. Phillips is a renowned science communicator in addition to being a leading scientist, and currently serves as a NIST Fellow and a University of Maryland Distinguished University Professor. This fireside chat will include a discussion of Dr. Phillips’ Nobel journey, a basic introduction to quantum physics, and answers to burning questions about the promise of emerging quantum technologies.

This fireside chat will be the first in a series of MQA virtual events that will dive more deeply into the remarkable capabilities that advances in quantum are unlocking for computing, sensing and ultra-secure communications — and how these will help to address real-world challenges. This MQA introductory series will help to connect potential customers and end-users with the research community to accelerate the innovation of quantum products that are responsive to actual needs and deliver value. To get more
the mailing list or email Dr. John Sawyer (jsawyer2@umd.edu).

About the MQA: The Greater National Capital Region is one of the leading quantum powerhouses in the world; the Mid-Atlantic Quantum Alliance (MQA) brings the region’s extraordinary capabilities across academia, industry, non-profits, and government together to build a vibrant ecosystem that accelerates quantum innovation and impact. QSEC represents Mason as a founding and active member of the MQA.

Sep
29
Tue
2020
QSEC Quantum Computing Seminar Series: 09/29/2020, Quantum Computing with Qiskit, by Ian Morris of George Mason
Sep 29 @ 12:00 pm – 1:00 pm

Event Record

##### Speaker: Ian Morris, GMU Department of Physics and Astronomy

Topic: Quantum Computing with Qiskit

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester. The upcoming seminar on Tuesday September 29 with Mr. Ian Morris of GMU Department of Physics and Astronomy giving a short tutorial on Qiskit. These events are free and open to the public. For any questions, contact qsec@gmu.edu. Below is the abstract of Mr. Morris’s talk and meeting information:

Abstract
Curious about quantum computing but never had a chance to learn? Come to this hands-on tutorial and see quantum circuits in action!
Qiskit (qiss-kit) is an opensource Software Development Kit created by IBM that provides users access to real quantum computers to run their quantum circuits on. With Qiskit, users are able to execute their quantum circuit code on various quantum hardware architectures ranging from superconducting qubits to trapped ions, access a large set of premade circuits which can serve as benchmarks or building blocks for more complex circuits, and study the impact of noise on quantum circuits using built-in modules for noise characterization and optimization. In addition, Qiskit provides its users with a library of quantum algorithms from which users can draw on to research real world applications from machine learning to chemistry, as well as circuit tutorials, a free online textbook, YouTube explanations, and a blog featuring quantum applications that make learning how to use the SDK very simple. Qiskit’s easy to use interface enables users to start creating and implementing circuits immediately.

Meeting Information
Join Zoom Meeting ID: 913 3925 3115 Passcode: 570565
https://gmu.zoom.us/j/91339253115?pwd=RkNBMlY5Rnl1OFNYSGNMTVhBdzNKUT09
One tap mobile
+13017158592,,91339253115#,,,,,,0#,,570565# US (Germantown)

Oct
20
Tue
2020
QSEC Quantum Computing Seminar Series: 10/20/2020, SWAP Test for Arbitrary Number of Quantum States, by Xavier Gitiaux and Ian Morris of George Mason University @ Zoom
Oct 20 @ 12:00 pm – 1:00 pm
##### Speaker: Xavier Gitiaux, GMU Department of Computer Science; Ian Morris, GMU Department of Physics and Astronomy

Location: Zoom

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester.  These events are free and open to the public. For any questions, contact qsec@gmu.edu.

The upcoming seminar on Tuesday October 20 will be given by Mr. Xavier Gitiaux of GMU Computer Science and Mr. Ian Morris of GMU Physics and Astronomy. This work is jointly advised by GMU Professors Ming Tian of Physics and Maria Emelianenko of Math. Below is the abstract of the talk and meeting information:

Title: SWAP Test for Arbitrary Number of Quantum States

Abstract

SWAP test is a useful primitive in quantum computing: for example, it allows estimating the inner product between two quantum states or the distance between two vectors of classical data. To date, SWAP test have been only implemented between two quantum states at a time. We study how to extend the SWAP test to an arbitrary number n of quantum states. We first design a genetic algorithm that constructs circuits for an arbitrary but small number of quantum states (n=5 to 15) using combination of single-control CSWAP and Hadamard gates. However, when expanded to an arbitrary large number n of quantum gates, these circuits would require a number of copies of quantum states that is exponential in n. Our approach based on single-control CSWAP gates would be outperformed by a naive approach that treats each pair of quantum states separately and requires only a polynomial number of copies of the quantum states. This observation motivates the use and optimization of multi-control CSWAP gates that would allow to execute the SWAP test for each of the n(n-1)/2 pairs with a linear number of copies of the quantum states.

Meeting Information
Join Zoom Meeting ID:934 6880 2063
https://gmu.zoom.us/j/93468802063

Oct
27
Tue
2020
QSEC Quantum Computing Seminar Series: 10/27/2020, Algorithmic Approaches to the MAX-CUT Problem, by Fei Li of George Mason University @ Zoom
Oct 27 @ 12:00 pm – 1:00 pm

Event Record

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester.  These events are free and open to the public. For any questions, contact qsec@gmu.edu.

The recorded seminar on Tuesday October 27 was given by Professor Fei Li of GMU Computer Science. Below is the abstract of the talk:

##### Speaker: Professor Fei Li, GMU Department of Computer Science

Title: Algorithmic Approaches to the MAX-CUT Problem

Abstract

In this talk, I am going to present three approximation algorithms to deal with the NP-hard problem MAX-CUT. The first one is a 0.5-approximation randomized algorithm, which can be de-randomized to be a deterministic one with the same performance. The second approximation algorithm is also a randomized algorithm and it has an approximation ratio 0.878. The third algorithm is a quantum approximation optimization algorithm (QAOA) with an approximation ratio 0.6942 on 3-regular graphs. In this talk, I will compare these algorithmic approaches. I will also discuss the inapproximability and some of my thoughts on solving MAX-CUT.

Nov
10
Tue
2020
QSEC Quantum Computing Seminar Series: 11/10/2020, Improving Quantum Simulation of Fermionic Systems, by Kianna Wan of Stanford University
Nov 10 @ 1:00 pm – 2:00 pm

QSEC’s Computing subgroup will host the next QC seminar on Tuesday, 11/10 at 1pm. Note that the time is different from usual.

Join Zoom Meeting ID: 934 6880 2063

https://gmu.zoom.us/j/93468802063

Title: Improving Quantum Simulation of Fermionic Systems

Speaker: Ms. Kianna Wan, PhD Candidate of Physics Department, Stanford University

Abstract: Quantum simulation is one of the most anticipated applications of quantum computers. Many recent advances have focused on the simulation of fermionic systems, such as quantum chemistry and lattice models. In this talk, I review some basic ideas behind state-of-the-art algorithms for quantum simulation. I then show how one of the main subroutines can be performed in logarithmic depth when applied to any fermionic system. This immediately yields an asymptotic reduction in runtime for the simulation of a large class of models.

The quantum computing subgroup meets weekly, usually at 12pm Tuesdays. If you are interested in staying up to date, please join the Slack channel at https://join.slack.com/t/masonquantumcomputing/shared_invite/zt-gof00ck7-9H~sciLYg0r8nGpf5R3xnQ

For more QSEC events, please check https://qsec.gmu.edu/events.

Dec
1
Tue
2020
QSEC Quantum Computing Seminar Series: 12/01/2020, Classic and Quantum Approximation Algorithms for Weighted MAX-CUT – An Empirical Study, by Cheng Zhang of George Mason
Dec 1 @ 12:00 pm – 1:00 pm

##### Speaker: Cheng Zhong, GMU Department of Computer Science

Topic: Classic and Quantum Approximation Algorithms for Weighted MAX-CUT – An Empirical Study

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester. The upcoming seminar on Tuesday December 1 will be given by Mr. Cheng Zhong of GMU Department of Computer Science. These events are free and open to the public. For any questions, contact qsec@gmu.edu. Below is the abstract of Mr. Zhong’s talk and meeting information:

Abstract
Quantum computing plays an important role in improving optimization algorithms’ performance, in terms of running time and near-optimality. Recently, quantum approximation optimization algorithms (QAOA) make it possible to tackle with some combinatorial optimization problems. In this talk, I will present the QisKit implementation of QAOA in weighted max-cut problem, which is NP-hard for classic computers. Then, I am going to compare its performance with a classical max-cut algorithm. The result shows some interesting features of QAOA. I will also talk more about my thoughts of the quantum algorithm implementation.

Meeting Information
Join Zoom Meeting ID:934 6880 2063
https://gmu.zoom.us/j/93468802063

Feb
2
Tue
2021
QSEC Quantum Computing Seminar Series Kickoff Meeting @ Zoom
Feb 2 @ 12:00 pm – 1:00 pm

##### Date: 2/02/2021, 12pm
Seminar Series on Quantum Computing, Kickoff Meeting

QSEC’s quantum computing group will organize and host a seminar series throughout the semester. The upcoming seminar on Tuesday February 2 will be a kickoff meeting. These events are free and open to the public. For any questions, contact qsec@gmu.edu.

Meeting Information

Join Zoom Meeting ID: 609 431 5466

https://gmu.zoom.us/j/6094315466

Feb
9
Tue
2021
QSEC Quantum Computing Seminar Series: Quantum Logspace Algorithm for Powering Matrices with Bounded Norm, by Wei Zhan of Princeton
Feb 9 @ 12:00 pm – 1:00 pm
##### Speaker: Wei Zhan, Princeton University

Topic: Quantum Logspace Algorithm for Powering Matrices with Bounded Norm

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester. The upcoming seminar will be given by Mr. Wei Zhan of Princeton University. These events are free and open to the public. For any questions, contact qsec@gmu.edu. Below is the abstract of Mr. Zhong’s talk and meeting information:

Abstract
We give a quantum logspace algorithm for powering contraction matrices, that is, matrices with spectral norm at most 1. The algorithm gets as an input an arbitrary n×n contraction matrix A, and a parameter T ≤ poly(n) and outputs the entries of A^T, up to (arbitrary) polynomially small additive error. The algorithm applies only unitary operators, without intermediate measurements.
We use this algorithm to show that the class of quantum logspace algorithms with only quantum memory and with intermediate measurements is equivalent to the class of quantum logspace algorithms with only quantum memory without intermediate measurements. This shows that the deferred-measurement principle, a fundamental principle of quantum computing, applies also for quantum logspace algorithms (without classical memory). More generally, we give a quantum algorithm with space O(S + log T ) that takes as an input the description of a quantum algorithm with quantum space S and time T, with intermediate measurements, and simulates it unitarily with polynomially small error, without intermediate measurements.

Bio:
Wei Zhan is a fourth year Ph.D student in the theory group of the Department of Computer Science at Princeton University, advised by Prof. Ran Raz. His research interest lies in computational complexity theory, especially in space-bounded computation.

Meeting Information
Zoom: https://gmu.zoom.us/j/6094315466

Mar
9
Tue
2021
QSEC Quantum Computing Seminar Series: Quantum algorithms for escaping from saddle points, by Dr. Tongyang Li of MIT
Mar 9 @ 12:00 pm – 1:00 pm
##### Speaker: Dr. Tongyang Li, Center for Theoretical Physics, Massachusetts Institute of Technology

Topic: Quantum algorithms for escaping from saddle points

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester. These events are free and open to the public. For any questions, contact qsec@gmu.edu.

Abstract
We initiate the study of quantum algorithms for escaping from saddle points with a provable guarantee. Given a function f: R^{n} -> R, our quantum algorithm outputs an $\epsilon$-approximate local minimum using $\tilde{O}(\log^{2} n/\epsilon^{1.75})$ queries to the quantum evaluation oracle (i.e., the zeroth-order oracle). Compared to the classical state-of-the-art algorithm by Jin et al. with $\tilde{O}(\log^{6} n/\epsilon^{1.75})$ queries to the gradient oracle (i.e., the first-order oracle), our quantum algorithm is polynomially better in terms of $n$ and matches its complexity in terms of $1/\epsilon$. Our quantum algorithm is built upon two techniques: First, we replace the classical perturbations in gradient descent methods by simulating quantum wave equations, which constitutes the polynomial speedup in $n$ for escaping from saddle points. Second, we show how to use a quantum gradient computation algorithm due to Jordan to replace the classical gradient queries in nonconvex optimization by quantum evaluation queries with the same complexity, extending the same result from convex optimization due to van Apeldoorn et al. and Chakrabarti et al. Finally, we also perform numerical experiments that support our quantum speedup.

Speaker’s Bio:
Tongyang Li is currently a postdoctoral associate at the Center for Theoretical Physics, Massachusetts Institute of Technology. He received Master’sand PhD degrees from the Department of Computer Science, the University of Maryland in 2018 and 2020, respectively. He received B.E. from the Institute for Interdisciplinary Information Sciences, Tsinghua University and B.S. from the Department of Mathematical Sciences, Tsinghua University, both in 2015. He was a recipient of the IBM Ph.D. Fellowship, the NSF QISE-NET Triplet Award, and the Lanczos Fellowship. His research focuses on designing quantum algorithms for machine learning and optimization.

Meeting Information
Join Zoom Meeting ID:609 431 5466

https://gmu.zoom.us/j/6094315466

Apr
20
Tue
2021
QSEC Quantum Computing Seminar Series: 4/20/2021, Sample-efficient learning of quantum many-body systems, by Anurag Anshu of Berkeley
Apr 20 @ 12:00 pm – 1:00 pm

##### Speaker: Anurag Anshu, University of California, Berkeley

Topic: Sample-efficient learning of quantum many-body systems

QSEC’s quantum computing subgroup will organize and host a seminar series throughout the upcoming semester. These events are free and open to the public. For any questions, contact qsec@gmu.edu. Below is the abstract of Mr. Zhong’s talk and meeting information:

Abstract
We study the problem of learning the Hamiltonian of a quantum many-body system given samples from its Gibbs (thermal) state. The classical analog of this problem, known as learning graphical models or Boltzmann machines, is a well-studied question in machine learning and statistics. In this work, we give the first sample-efficient algorithm for the quantum Hamiltonian learning problem. In particular, we prove that polynomially many samples in the number of particles (qudits) are necessary and sufficient forlearning the parameters of a spatially local Hamiltonian in l_2-norm. Our main contribution is in establishing the strong convexity of the log-partition function of quantum many-body systems, which along with the maximum entropy estimation yields our sample-efficient algorithm. Classically, the strong convexity for partition functions follows from the Markov property of Gibbs distributions. This is, however, known to be violated in its exact form in the quantum case. We introduce several new ideas to obtain an unconditional result that avoids relying on the Markov property of quantum systems, at the cost of a slightly weaker bound. In particular, we prove a lower bound on the variance of quasi-local operators with respect to the Gibbs state, which might be of independent interest. Our work paves the way toward a more rigorous application of machine learning techniques to quantum many-body problems.

Speaker’s Bio:
Anurag Anshu is a postdoctoral researcher at the University of California, Berkeley. Prior to this, he was a joint postdoctoral researcher at the Institute for Quantum Computing and the Perimeter Institute for Theoretical Physics, Waterloo. He obtained his PhD from the Centre for Quantum Technologies, National University of Singapore, on August 31, 2018, in Computer Science. He is interested in quantum complexity theory, quantum many-body physics, quantum communication and quantum learning theory.

Meeting Information
Join Zoom Meeting ID:609 431 5466

https://gmu.zoom.us/j/6094315466

Apr
22
Thu
2021
[Quantum Week] An Introduction to Quantum, by Dr. Patrick Vora of GMU
Apr 22 @ 9:00 am – 9:30 am
[Quantum Week] Quantum Computing: What Is It? by Dr. Maria Emelianenko of GMU
Apr 22 @ 9:30 am – 9:45 am
[Quantum Week] Information of Mason’s Master’s Concentration of Quantum Information Science & Engineering, by Dr. Jessica Rosenberg and Dr. Mingzhen Tian of GMU
Apr 22 @ 9:45 am – 10:00 am
[Quantum Week] Research Showcase: Optimal Two-Qubit Quantum Circuit Synthesis, by Jacob Weston and Connor Mooney of GMU
Apr 22 @ 10:00 am – 10:30 am
[Quantum Week] Research Showcase: Quantum Algorithms for Urban Air Mobility, by Xavier Gitiaux of GMU
Apr 22 @ 10:30 am – 11:00 am
[Quantum Week] Program a Real Quantum Computer: Qiskit Introduction, by Ian Morris of GMU
Apr 22 @ 11:00 am – 11:30 am
Apr
23
Fri
2021
[Quantum Week] Panel Discussion: Career Opportunities in Quantum
Apr 23 @ 11:00 am – 12:00 pm

Panelists:

Dr. Patrick Vora, Director of QSEC & Associate Professor of Physics, GMU

Dr. Jacob Farinholt, Lead Quantum Scientist, Booz Allen Hamilton

Dr. Brandon Rodenburg, Physicist and Quantum Information Scientist, MITRE Corporation

Dr. Neil Zimmerman, Atom Scale Device Group Leader, NIST

Quantum Week Event Information: https://qsec.gmu.edu/events/quantum-week/

Virtual Conference Hall: https://gather.town/app/iYPdUV0zfX1sVNVx/QSEC%20Quantum%20Week

[Quantum Week] Virtual Poster & Info Session
Apr 23 @ 2:00 pm – 3:00 pm

Quantum Week Event Information: https://qsec.gmu.edu/events/quantum-week/

Virtual Conference Hall of the Poster Session: https://gather.town/app/iYPdUV0zfX1sVNVx/QSEC%20Quantum%20Week

QSEC working groups meet regularly in form of informal workshops and/or roundtable discussions. Check the Computing/Materials/Sensing/Education subgroup pages for more information.