meet the meQuanics - Quantum Computing Discussions meQuanics

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/4KIXVQtR9Qw

Free-Fermion Solutions and Frustration Graphs  

TITLE: Characterization of free-fermion-solvable spin models via graph invariants 

SPEAKER: Dr Adrian Chapman 

AFFILIATION: ARC Centre of Excellence for Engineered Quantum Systems (EQUS), University of Sydney, Australia 

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

ABSTRACT:  Finding exact solutions to spin models is a fundamental problem of many-body physics. A workhorse technique for exact solution methods is mapping to an effective description by noninteracting fermions. The paradigmatic example of this is the Jordan-Wigner transformation for finding an exact solution to the one-dimensional XY model. Another important example is the exact free-fermion solution to the two-dimensional Kitaev honeycomb model.  I will describe a framework for recognizing general models which can be solved this way by utilizing the tools of graph theory. Our construction relies on a connection to the graph-theoretic problem of recognizing line graphs, which has been solved optimally. A corollary of this result is a complete set of constant-sized frustration structures which obstruct a free-fermion solution. We classify the kinds of Pauli symmetries which can be present in models for which a free-fermion solution exists, and we find that they correspond to either: (i) gauge qubits, (ii) cycles on the free-fermion hopping graph, or (iii) the fermion parity. Clifford symmetries, except in finitely-many cases, must be symmetries of the free-fermion Hamiltonian itself. We expect our characterization to motivate a renewed exploration of free-fermion-solvable models, and I will close with an elaborate discussion of how we expect to generalize our framework beyond generator-to-generator mappings.  

RELATED ARTICLES: Characterization of solvable spin models via graph invariants. Quantum 4, 278 (2020). Characterization of solvable spin models via graph invariants: quantum-journal.org/papers/q-2020-06-04-278/  

OTHER LINKS: Adrian Chapman Webpage: https://equs.org/users/adrian-chapman

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/2syrO_asU5Y

Hardness of Random Circuit Sampling (Google's supremacy experiment) 

TITLE: Cayley Path and Quantum Supremacy SPEAKER: Dr Ramis Movassagh 

AFFILIATION: MIT-IBM Watson AI Lab, Cambridge MA, USA 

HOSTED BY: Prof Michael Bremner, UTS Centre for Quantum Software and Information 

ABSTRACT: Given the large push by academia and industry (e.g., IBM and Google), quantum computers with hundred(s) of qubits are at the brink of existence with the promise of outperforming any classical computer. Demonstration of computational advantages of noisy near-term quantum computers over classical computers is an imperative near-term goal. The foremost candidate task for showing this is Random Circuit Sampling (RCS), which is the task of sampling from the output distribution of a random circuit. This is exactly the task that recently Google experimentally performed on 53-qubits. Stockmeyer's theorem implies that efficient sampling allows for estimation of probability amplitudes. Therefore, hardness of probability estimation implies hardness of sampling. We prove that estimating probabilities to within small errors is #P-hard on average (i.e. for random circuits), and put the results in the context of previous works. Some ingredients that are developed to make this proof possible are construction of the Cayley path as a rational function valued unitary path that interpolate between two arbitrary unitaries, an extension of Berlekamp-Welch algorithm that efficiently and exactly interpolates rational functions, and construction of probability distributions over unitaries that are arbitrarily close to the Haar measure. 

RELATED ARTICLES: Unitary-valued paths, and an algebraic proof technique in complexity theory: https://ramismovassagh.wordpress.com/... Cayley path and quantum computational supremacy: A proof of average-case #P−hardness of Random Circuit Sampling with quantified robustness: https://arxiv.org/abs/1909.06210 Efficient unitary paths and quantum computational supremacy: A proof of average-case hardness of Random Circuit Sampling: https://arxiv.org/abs/1810.04681 

OTHER LINKS: Ramis Movassagh Personal Webpage: https://ramismovassagh.wordpress.com/ 

MIT-IBM Watson AI Lab: https://mitibmwatsonailab.mit.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/Dg6Q_F9uI8s

Silicon spin qubits gain traction for large-scale quantum computation and simulation.  

TITLE: A Scalable “Spins-Inside” Quantum Processor and Simulator SPEAKER: Prof Lieven Vandersypen 

AFFILIATION: QuTech, Kavli Institute of Nanoscience, Dept of Quantum Nanoscience, Delft University of Technology, Netherlands 

HOSTED BY: Dr JP (Juan Pablo) Dehollain, UTS Centre for Quantum Software and Information  

ABSTRACT:  Excellent control of over physical 50 qubits has been achieved, but can we also realize 50 fault-tolerant qubits? Here quantum bits encoded in the spin state of individual electrons in silicon quantum dot arrays have emerged as a highly promising avenue. In this talk, I will present our vision of a large-scale spin-based quantum processor, and our ongoing work to realize this vision. I will also show how the same platform offers a powerful platform for analog quantum simulation of Fermi-Hubbard physics and quantum magnetism.  

RELATED ARTICLES: Physics Today 72(8), 38 (2019) npj Quantum Information 3, 34 (2017) Nature 555, 633 (2018) Science 359, 1123 (2018) Phys. Rev. X 9, 021011 (2019) Nature 579, 528 (2020) Nature 580, 355 (2020)  

OTHER LINKS: Vandersypen Lab: qutech.nl/vandersypen-lab/ Delft University of Technology: https://www.tudelft.nl/

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/rOKpLd4X9jE

Finding the ground state of the Hubbard model using hybrid quantum-classical computing.  

TITLE: Strategies for solving the Fermi-Hubbard model on near-term quantum computers 

SPEAKER: Lana Mineh 

AFFILIATION: Quantum Engineering Technology Labs, University of Bristol, UK 

HOSTED BY: Prof Michael Bremner, UTS Centre for Quantum Software and Information  

ABSTRACT:  The Fermi-Hubbard model is of fundamental importance in condensed-matter physics, yet is extremely challenging to solve numerically. Finding the ground state of the Hubbard model using variational methods has been predicted to be one of the first applications of near-term quantum computers. Here we carry out a detailed analysis and optimisation of the complexity of variational quantum algorithms for finding the ground state of the Hubbard model, including costs associated with mapping to a real-world hardware platform. The depth complexities we find are substantially lower than previous work. We performed extensive numerical experiments for systems with up to 12 sites. The results suggest that the variational ansätze we used -- an efficient variant of the Hamiltonian Variational ansatz and a novel generalisation thereof -- will be able to find the ground state of the Hubbard model with high fidelity in relatively low quantum circuit depth. Our experiments include the effect of realistic measurements and depolarising noise. If our numerical results on small lattice sizes are representative of the somewhat larger lattices accessible to near-term quantum hardware, they suggest that optimising over quantum circuits with a gate depth less than a thousand could be sufficient to solve instances of the Hubbard model beyond the capacity of classical exact diagonalisation.  

RELATED ARTICLES:  Strategies for solving the Fermi-Hubbard model on near-term quantum computers: https://arxiv.org/abs/1912.06007 

OTHER LINKS: Quantum Engineering Technology Labs: bristol.ac.uk/qet-labs

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/a5aa-vU2AHo

Controls and frames: A new approach to quantum noise spectroscopy  

TITLE: Noise Cancellation and your Quantum Computer 

SPEAKER: Dr Gerardo Paz Silva 

AFFILIATION: Centre for Quantum Dynamics, Griffith University, Brisbane, Qld, Australia 

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

ABSTRACT: Noise cancellation, as in everyday headphones, requires the ability to characterize & filter out the noise affecting a system one wants to protect. The last few years have seen the birth of increasingly more powerful Quantum Noise Spectroscopy (QNS) protocols, capable of characterizing the noise affecting a quantum system of interest. However, while many of these protocols have been experimentally verified, all demonstrations have been so far limited to characterizing injected noise. More importantly, even theoretically a fully general protocol is still non-existent. In this talk I will introduce our new approach to the problem, which overcomes these limitations. I will argue that by characterizing only the portions of the noise that are relevant a given set of control capabilities, e.g., available to a particular experiment, many of the existing difficulties in designing a fully general QNS protocol disappear. I describe the key ingredients allowing this and exemplify our results via two paradigmatic examples.  

OTHER LINKS: Centre for Quantum Dynamics, Griffith University griffith.edu.au/centre-quantum-dynamics

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/7wbK_9Sjnv8

Protecting and leveraging quantum machine learning algorithms on a future quantum internet  

TITLE: Introducing Adversarial Quantum Learning: Security and machine learning on the quantum internet 

SPEAKER: Assistant Professor Nana Liu 

AFFILIATION: Shanghai Jiao Tong University, PR China 

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

ABSTRACT:  In the classical world, there is a powerful interplay between security and machine learning deployed in a network, like on the modern internet. What happens when the learning algorithms and the network itself can be quantum? What are the new problems that can arise and can quantum resources offer advantages to their classical counterparts? We explore these questions in a new area called adversarial quantum learning, that combines the area of adversarial machine learning, which investigates security questions in machine learning, and quantum information. For the first part of the talk, I’ll introduce adversarial machine learning and some exciting potential prospects for contributions from quantum information and computation. For the second part of the talk, I’ll present two new works on adversarial quantum learning. Here we are able to quantify the vulnerability of quantum algorithms for classification against adversaries and learn how to leverage quantum noise to improve its robustness against attacks.    

RELATED ARTICLES: Vulnerability of quantum classification to adversarial perturbations: https://arxiv.org/abs/1905.04286Quantum noise protects quantum classifiers against adversaries: https://arxiv.org/abs/2003.09416 

OTHER LINKS: nanaliu.weebly.com/