meet the meQuanics - Quantum Computing Discussions

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://youtu.be/3OS7Pq6JoDY

Q#, a quantum-focused domain-specific language explicitly designed to correctly, clearly and completely express quantum algorithms.   

TITLE: Empowering Quantum Machine Learning Research with Q# 

SPEAKER: Dr Christopher Granade 

AFFILIATION: Quantum Systems, Microsoft, Washington, USA HOSTED BY: A/Prof Chris Ferrie, UTS Centre for Quantum Software and Information  

ABSTRACT: In this talk, I will demonstrate how the Q# quantum programming language can be used to start exploring quantum machine learning, using a binary classification problem as an example. I will describe recent work in QML algorithms for classification, and show how Q# allows implementing and using this classifier through high-level quantum development features. Finally, I will discuss how these approaches can be used as part of a reproducible research process to share your explorations with others.

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://youtu.be/8Cmw5u8fazk

TITLE: Spooky complexity at a distance 

SPEAKER:  Prof Zhengfeng Ji 

AFFILIATION: UTS Centre for Quantum Software and Information, Sydney, Australia 

HOSTED BY: Prof Sven Rogge, Centre for Quantum Computation & Communication Technology (CQC2T)  

ABSTRACT:  In this talk, I will discuss the recent result on the characterisation of the power of quantum multi-prover interactive proof systems, MIP*=RE. After a brief setup of the problem, we will highlight its rich connections and implications to problems in computer science, quantum physics, and mathematics, including the Tsirelson's problem and Connes' embedding problem. In the second half of the talk, we will outline the overall proof strategy and introduce several key techniques employed in the proof.  

RELATED ARTICLES: MIP*=RE: https://arxiv.org/abs/2001.04383

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://youtu.be/jrUpFdUQ6A4

Building a bigger Hilbert space for superconducting devices, one Bloch state at a time.  

TITLE: A new kind of qubit SPEAKER: Prof Tom Stace 

AFFILIATION: School of Mathematics and Physics, University of Queensland 

HOSTED BY: A/Prof. Nathan Langford, UTS Centre for Quantum Software and Information  

ABSTRACT: Noise and errors have been the bottlenecks for building robust quantum machines.  I will describe a proposed new class of superconducting devices that has built-in error rejection.  Fundamentally, the encoding that facilitates this intrinsic robustness comes from the recognition that the Bloch band structure of these systems leads to a much bigger Hilbert spaces than has been traditionally considered.  The extra space affords new qubit encodings, which I describe in two different instantiations.  

OTHER LINKS: Prof Tom Stace University Profile - researchers.uq.edu.au/researcher/1636

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://youtu.be/sUANYeTrmHQ

A scalable tomography for fermonic systems.  

TITLE: A Scalable Fermion Measurement SPEAKER: Dr Chris Jackson 

AFFILIATION: Center for Quantum Information and Control (CQulC), University of New Mexico, Albuquerque, NM  |  UTS Centre for Quantum Software and Information, Sydney, Australia HOSTED BY: A/Prof. Chris Ferrie, UTS Centre for Quantum Software and Information  

ABSTRACT: Fermion systems have a Hilbert space dimension that scales exponentially in the number of modes. Standard tomography thus says that to completely measure an unknown state would require the measurement of exponentially many observables. However, if the parity of a fermion state is known, then there exists a nonadaptive, tomographically complete continuous measurement which only requires the isotropic measurement of quadratically many observables.  The effects of the corresponding POVM are the well known superconducting Bardeen-Cooper-Schrieffer (BCS) coherent states. The BCS coherent states define a manifold which can be used as a phase space to represent fermion quantum information. In this talk, I will introduce the BCS-coherent state POVM, explain the isotropic measurement which implements it, and discuss the geometry of the corresponding phase space.  

OTHER LINKS: Centre for Quantum Information & Control: https://cquic.unm.edu/

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://youtu.be/XSJks4cRDv0

Cryptographic protocols for classical clients to verifiably delegate quantum computation to untrusted quantum servers - the desiderata and their feasibility.  

TITLE: How well can a classical client delegate quantum computation? 

SPEAKER: Dr Kai-Min Chung 

AFFILIATION: Institute of Information Science, Academia Sinica, Taiwan 

HOSTED BY: Prof Zhengfeng Ji, UTS Centre for Quantum Software and Information  

ABSTRACT: In a recent breakthrough, Mahadev (FOCS 2018) constructed the first classical verification of quantum computation (CVQC) protocol that allows a classical client to delegate the computation of a BQP language (i.e., a decision problem) to an efficient quantum server. In this talk, we present several generalizations of Mahadev’s work. In particular, we initiate the study of CVQC protocols for quantum *sampling* problems and construct the first such protocol that allows a classical client to verifiably obtain a sample drawn from a quantum computation from a quantum server. We also construct the first protocol with efficient verification, i.e., the client’s runtime can be sublinear in the quantum time complexity of the delegated computation. Finally, we present a generic compiler that compiles any CVQC protocol to achieve blindness, i.e., the server learns nothing about the client’s input, which leads to the first constant-round blind CVQC protocol.  Based on joint works with Nai-Hui Chia, Takashi Yamakawa, Yi Lee, Han-Husan Lin, and Xiaodi Wu  

REFERENCES: Classical Verification of Quantum Computations with Efficient Verifier: https://arxiv.org/abs/1912.00990

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://youtu.be/yAUSMUYfXlU

So you want to build a useful quantum computer… where to begin?!  

TITLE: Building Google’s Quantum Computer 

SPEAKER: Dr Marissa Giustina 

AFFILIATION: Google AI Quantum, Google Research, CA, USA 

HOSTED BY: A/Prof Nathan Langford, UTS Centre for Quantum Software and Information  

ABSTRACT: The Google AI Quantum team develops chip-based circuitry that one can interact with (control and read out) and which behaves reliably according to a simple quantum model. Such quantum hardware holds promise as a platform for tackling problems intractable to classical computing hardware. While the demonstration of a universal, fault-tolerant, quantum computer remains a goal for the future, it has informed the design of a prototype with which we have recently controlled a quantum system of unprecedented scale.  This talk introduces Google’s quantum computing effort from both hardware and quantum-information perspectives, including an overview of recent technological developments and some recent results.  

RELATED ARTICLES:  Quantum supremacy using a programmable superconducting processor: 

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.

https://www.youtube.com/watch?v=N1We-MpoJlM&t=5s

SEMINAR 1 

TITLE: Understanding Crosstalk in Quantum Processors 

SPEAKER: A/Prof Robin Blume-Kohout 

AFFILIATION: Quantum Performance Lab, Sandia National Laboratories, Albuquerque, New Mexico 

HOSTED BY: A/Prof Chris Ferrie, UTS Centre for Quantum Software and Information  

ABSTRACT:  Multi-qubit quantum processors fail – i.e., deviate from ideal behavior – in many ways. One of the most important, especially as the number of qubits grows, is crosstalk. But “crosstalk” refers to a wide range of distinct phenomena. In this talk, I will present a precise and rigorous framework that we have developed for defining and classifying crosstalk errors, and compare it to existing ad hoc definitions. Then, I will present two protocols that we are deploying to detect and characterize crosstalk, and show how we are using them to break down and demystify the error behavior of testbed-class quantum processors in the wild.

SEMINAR 2 

TITLE: Hold the onion: using fewer circuits to characterize your qubits 

SPEAKER: Dr Erik Nielsen 

AFFILIATION: Quantum Performance Lab, Sandia National Laboratories, Albuquerque, New Mexico 

HOSTED BY: A/Prof Chris Ferrie, UTS Centre for Quantum Software and Information  

ABSTRACT: Model-based quantum tomography protocols like gate set tomography optimize a noise model with some number of parameters in order to fit experimental data.  As the number of qubits increases, two issues emerge: 1) the number of model parameters grows, and 2) the cost of propagating quantum states (density matrices) increases exponentially.   The first issue can be addressed by considering reduced models that limit errors to being low-weight and geometrically local.  In this talk, we focus on the second issue and present a method for performing approximate density matrix propagation based on perturbative expansions of error generators.  The method is tailored to the likelihood optimization problem faced by model-based tomography protocols.  We will discuss the advantages and drawbacks of using this method when characterizing the errors in up to 8-qubit systems.

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.  

Building better deep learning representations for quantum mixed states by adding quantum layers to classical probabilistic models.  

TITLE: Quantum-probabilistic Generative Models and Variational Quantum Thermalization 

SPEAKER: Guillaume Verdon 

AFFILIATION: X (formerly Google X), California, USA 

HOSTED BY: A/Prof. Chris Ferrie, Centre for Quantum Software and Information  

ABSTRACT:  We introduce a new class of generative quantum-neural-network-based models called Quantum Hamiltonian-Based Models (QHBMs). In doing so, we establish a paradigmatic approach for quantum-probabilistic hybrid variational learning of quantum mixed states, where we efficiently decompose the tasks of learning classical and quantum correlations in a way which maximizes the utility of both classical and quantum processors. In addition, we introduce the Variational Quantum Thermalizer (VQT) algorithm for generating the thermal state of a given Hamiltonian and target temperature, a task for which QHBMs are naturally well-suited. The VQT can be seen as a generalization of the Variational Quantum Eigensolver (VQE) to thermal states: we show that the VQT converges to the VQE in the zero temperature limit. We provide numerical results demonstrating the efficacy of these techniques in several illustrative examples. In addition to the introduction to the theory and applications behind these models, we will briefly walk through their numerical implementation in TensorFlow Quantum.  

RELATED ARTICLES: Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm: https://arxiv.org/abs/1910.02071

TensorFlow Quantum: A Software Framework for Quantum Machine Learning: https://arxiv.org/abs/2003.02989 

OTHER LINKS: X: https://x.company/

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk with an exclusive 10min interview with each of our presenters.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.  Click the link below to see the talk uploaded to the meQuanics podcast from Daniel Grier from the University of Waterloo and the Institute for Quantum Computing.

https://www.youtube.com/watch?v=El7JAmvUQ1U

During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series.  With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk with an exclusive 10min interview with each of our presenters.  I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.  Click the link below to see the talk uploaded to the meQuanics podcast from Maria Schuld from Xanadu and the University of Kwazulu Natal.

https://www.youtube.com/watch?v=RKdFNJtTeeA