Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session T28: Quantum in Industry: Spanning the Full Quantum Software StackInvited Live Streamed
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Sponsoring Units: DQI Chair: Michael Biercuk, University of Sydney Room: McCormick Place W-190A |
Thursday, March 17, 2022 11:30AM - 12:06PM |
T28.00001: Improving quantum computer performance with machine learning Invited Speaker: Yuval Baum Excitement about the promise of quantum computers is tempered by the reality that the hardware remains exceptionally fragile and error-prone, forming a bottleneck in the development of novel applications. In this talk we will introduce the concept and experimental implementation of quantum control, providing a pathway to maximizing hardware performance in near term systems, and forming a complement to quantum error correction in future systems. We will describe the challenge of designing low error and robust quantum logic and present a series of experiments on cloud-accessible superconducting quantum computers, demonstrating how redefining the analog waveforms used to implement quantum logic gates can lead to improvements in gate error, resilience against fabrication variance, and resilience against temporal drifts. We will then present the first demonstration of Deep Reinforcement Learning (DRL) to autonomously design a Universal gateset showing superior performance to calibrated default gates. DRL-designed two-qubit cross-resonance gates exhibit ~2.5X improvements relative to standard gates, and obviate the need for additional compensating signals designed to mitigate crosstalk. We demonstrate drift-robust two-qubit gate performance at the level of ~99.5% fidelity (near T1 limits) up to 25 days from gate design with no recalibration, while default gates require recalibration every 12-24 hours. These experiments reveal a pathway to autonomously designing error-robust quantum logic at scale across complex systems with unknown couplings and Hamiltonian terms. We will complement my talk by showing that such machine-learning based automated routines can lead to dramatic algorithmic improvements on current mid-scale devices. We show up to 25X improvements in success probability of both deterministic algorithms, such as QFT and BV, and hybrid algorithms such as QAOA and VQE. |
Thursday, March 17, 2022 12:06PM - 12:42PM |
T28.00002: Qiskit runtime, a quantum-classical execution platform for cloud-accessible quantum computers Invited Speaker: Blake R Johnson The infrastructure challenges of quantum computing has motivated many providers of quantum computing hardware to focus on a cloud access model for their machines. In most cases, these cloud models expose a circuit interface for users to submit requests for execution. Unfortunately, such circuit interfaces are poorly suited to typical workloads that require looping or iterative interactions between quantum and classical computations such as found in variational algorithms, calibration routines, etc. The Qiskit Runtime aims to address this performance bottleneck by hosting both the quantum and classical parts of a computation within a unified system infrastructure. In this talk, I will show the architecture of the Qiskit Runtime, demonstrate the performance benefit on model workloads, and discuss future enhancements to incorporate the Qiskit Runtime into a Quantum Serverless platform. |
Thursday, March 17, 2022 12:42PM - 1:18PM |
T28.00003: Perspectives on application-specific quantum computers Invited Speaker: Ines de Vega Quantum computers require major hardware developments to meet their expectations. In IQM we take inspiration from classical, application specific integrated chips (ASICs) to develop application specific quantum computers, or Q-ASICs, where the hardware and the quantum algorithms are co-designed to optimize the computational power [1]. Some of the tools used to build Q-ASICs include combining digital with analog operations [2], adapting the chip topology [3] or considering computational elements beyond qubits, such as resonators or quantum circuit refrigerators. In this talk we provide an overview of this approach and discuss some of the recent results obtained in our teams [4,5]. |
Thursday, March 17, 2022 1:18PM - 1:54PM |
T28.00004: A full-stack software environment for superconducting qubits Invited Speaker: Ilana Wisby As in many other industrial computing sectors, there is an increasing trend for users to care when tasks are run, with a focus on accuracy and execution time, but no burden relating to how the task is performed. As Quantum computing is increasingly exploited for industrial problems, users who care how tasks are executed, stage by stage, will become increasingly niche. As a full hardware stack QCaaS provider, a key piece of our offering is to make the quantum hardware and instructions accessible. The QCaaS abstraction provides an exciting model for our purposes, with the potential to scale and improve services continuously with little or no interruption to clients. |
Thursday, March 17, 2022 1:54PM - 2:30PM |
T28.00005: Programming for scale with Azure Quantum Invited Speaker: Krysta M Svore The power of Azure, accelerated by Quantum. Quantum computers are accelerators to large-scale classical compute and receive instructions and cues from classical processors. The success of quantum computation requires seamless integration in a high-performance cloud, to enable hyperscale workloads with complex, hybrid quantum-classical processing. It also requires scaling up; commercial quantum advantage will require more than 1M physical qubits, and the software stack must enable efficient performance of the quantum machine. This quantum-classical compute fabric promises to help remake our global economy, by offering new capabilities to help solve some of our planet’s biggest challenges—in energy, climate, agriculture, and health—and across a broad span of industrial sectors, including computational chemistry, materials science, and nuclear and particle physics. I’ll share the types of problems such an industrial-scale quantum machine will accelerate in the cloud, and how you can program and develop towards these advances today with Azure Quantum. I’ll also share how co-design of the software stack and the hardware device can enable significant advances toward scaling up. |
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