Keynote Speaker

Jay-Gambetta-466x466-c

Quantum Software for the Utility-Scale and Beyond

Jay M. Gambetta

IBM Quantum | IBM Fellow and Vice President IBM Quantum

KEY01 — Monday, September 16, 2024 @ 8:00–9:30 Eastern Time (EST) — UTC-4

 

Biography

Dr. Jay M. Gambetta is the Vice President in charge of IBM’s overall Quantum initiative. He was named as an IBM Fellow in 2018 for his leadership in advancing superconducting quantum computing and establishing IBM’s quantum strategy to bring quantum computing to the world, and to make the world quantum safe.

Under his leadership, IBM was first to demonstrate a cloud-based quantum computing platform; a platform that has grown to become the predominant quantum service utilized by 600,000+ users to run over 3 trillion quantum circuits. These users include 300+ members of the IBM Quantum Network, representing forward-thinking academic, industry, and governmental organizations focused on building a quantum-native ecosystem. IBM Quantum continues to expand in the market by providing Quantum as a Service utilizing the IBM Quantum System One and Two series of devices, and to date has deployed over 70 quantum systems online, building the foundations of the quantum industry. In addition, he was responsible for the creation and early development of Qiskit; the leading open-source quantum computing software development kit, allowing users to build, optimize, and execute quantum circuits on hardware from a multitude of quantum service providers.

Dr. Gambetta received his Ph.D. in Physics from Griffith University in Australia. He is a Fellow of the American Physical Society, IEEE Fellow, and has over 130 publications in the field of quantum information science with over 41,000 citations.

Abstract

With quantum computers comprised of over 100 qubits now generally accessible, a multitude of demonstrations at this utility scale have been performed. Although the focus is typically on the scale, quality, and speed of the quantum hardware, it is imperative that the classical computing infrastructure underpinning quantum computing architectures be performant and reliable, in lockstep with quantum hardware improvements. It must also be scalable to meet the eventual needs of an error-corrected quantum platform. This includes the tools and capabilities needed for the tight integration between scalable quantum and classical computing resources necessary to enable Quantum Centric Supercomputing. Moreover, as quantum platforms continue to mature, software needs to support the continued abstraction away from quantum circuits and operators, which is necessary for the widespread adoption of quantum computing as a computational resource.

In this talk, Jay M. Gambetta provides an overview of the progress to date made at IBM Quantum in these areas. Through in-depth open-source benchmarking, it becomes evident that the focus on performance and reliability for Qiskit makes it the preeminent quantum software development kit for constructing, manipulating, and optimizing quantum circuits at the utility scale and beyond. This advantage is extended with the Qiskit Transpiler Service, which further improves the optimization of quantum circuits while simultaneously reducing overall runtime using reinforcement learning. Efforts to create an open and transparent quantum benchmarking platform for the community will also be discussed. For Quantum Computational Scientists working above the level of quantum assembly code, a catalog of Qiskit Functions, created by both IBM Quantum and select partners, is announced. This catalog targets several domain-specific application areas and error mitigation services, utilizing Qiskit Runtime and the managed resource capabilities of Qiskit Serverless. The advantages that these functions offer will be demonstrated through several examples. An open user execution framework allows for independent verification of these claims.

Taken together, the simultaneous focus on both quantum hardware and classical software performance promises to accelerate the journey towards useful quantum computation in the coming years.