Quantum Research Seminars Toronto consist of two 30 min talks about some Quantum Computation topic. Seminars are given by high-level quantum computing researchers with the focus on disseminating their research among other researchers from this field. We encourage to attend researchers regardless of their experience as well as graduate and undergraduate students with particular interest in this field. Basic notions on quantum computing are assumed, but no expertise in any particular subject of this field.

In this 9th series of seminars, the speakers will be Tobias Haug (Imperial College London) and Ian MacCormack (University of Chicago). Their talks are titled "Quantum Assisted Eigensolver and Simulator" and "Branching Quantum Convolutional Neural Networks: Using Mid-Circuit Measurements to Increase Expressivity of Short-Depth Variational Ansatzes", respectively.

We will send a Zoom link to those who register for this event 2 days, 2 hours and 10 min before the event starts.

The event recording, slides and chat history will be published in our Youtube channel and sent to the registered participants.

Looking forward to seeing you all!

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Talk 1:

Quantum Assisted Eigensolver and Simulator

Abstract:

Noisy intermediate-scale quantum (NISQ) computers may be able to perform tasks which surpass the ability of classical computers for industrially relevant tasks. A key challenge is to find quantum algorithms that utilize NISQ computers with their inherent limitations effectively. Many NISQ algorithms such as the variational quantum algorithm are often difficult to train or require too many resources to run effectively on current hardware.

Here, we propose a new generation of NISQ algorithms, the Quantum Assisted Eigensolver (IQAE) to find the ground state of Hamiltonians, and the Quantum Assisted Simulator (QAS) to evolve (open) quantum systems. The algorithms utilize the idea of linear combination of quantum states.

In contrast to variational quantum algorithms, our algorithms circumvent the barren plateau problem by construction and do not require any quantum-classical feedback loop, which speeds up computation on cloud based quantum computers. Further, our algorithms avoid complicated measurements such as the Hadamard test. The entire framework is compatible with existing experimental capabilities and has been successfully implemented on the IBM quantum computer.

Ref: IQAE , QAS , GQAS , QAE , TD-QAS

About the speaker:

Tobias Haug is a researcher at Imperial College London and graduating PhD student at the Centre for Quantum Technologies in Singapore. Previously, he has been staying at NTT in Japan and the University of Catania in Italy. He received his Masters from the University of Erlangen in Germany. His research interest lie at the intersection of quantum computing, quantum simulation and artificial intelligence. Recently, he proposed together with his collaborator Kishor Bharti a new generation of NISQ algorithms as well as methods to enhance variational quantum algorithms.

Talk 2:

Branching Quantum Convolutional Neural Networks: Using Mid-Circuit Measurements to Increase Expressivity of Short-Depth Variational Ansatzes

Abstract

We introduce the bQCNN, a variation of the quantum (convolutional) neural network in which outcomes from mid-circuit measurements of subsets of qubits inform subsequent quantum gate operations. This leads to a classical branching structure in which each branch contains its own set of trainable, parameterized entangling gates, resulting in significantly more parameters as compared to a depth-matched standard QCNN architecture. We demonstrate training tasks in which the bQCNN significantly outperforms a comparable QCNN of the same circuit depth. Using data from noisy simulations, we discuss the advantages that mid-circuit-measurement based circuits can offer as variational ansatzes in NISQ devices.

Ref.: https://arxiv.org/abs/2012.14439

About the speaker:

Ian MacCormack is a graduate student at the University of Chicago and a research consultant for Aliro Quantum Technologies. His research interests are at the intersection of condensed matter physics, quantum information theory, and quantum computing. With previous work focusing on entanglement in many-body quantum systems, he has recently expanded his focus to include the development and implementation of NISQ algorithms.