Qiskit Quantum Seminar

Currently Playing: Neural Network Decoders for Measurement-Induced Phase Transitions with Michael Gullans

Seminar Series with Michael Gullans Your formal invite to weekly Qiskit videos ► https://ibm.biz/q-subscribe Speaker: Michael Gullans Host: Zlatko Minev, PhD. Abstract: The sustained storage, transmission, or processing of quantum information will likely be a non-equilibrium process that requires monitoring the system and applying some form of feedback to produce fault-tolerance. In this talk, I will discuss a class of models based on random quantum circuits with intermediate measurements that display a similar phenomenology to standard models for fault-tolerance, including the existence of a threshold, but with several helpful simplifications. However, naïve realizations of the threshold require an exponential number of repetitions of the experiment to fully explore the output space of the intermediate measurements. Recently, it has been proposed that this problem can be circumvented by developing efficient entanglement “decoders” that have close parallels to quantum error correction decoders. We show how to leverage modern machine learning tools to devise a neural network decoder to detect the phase transition. We then study the complexity and scalability of this approach and discuss how it can be utilized to detect entanglement phase transitions in generic experiments. Bio: Michael Gullans is a fellow of the Joint Center for Quantum Information and Computer Science (QuICS), a physicist at the National Institute of Standards and Technology (NIST), and an adjunct assistant professor in the Department of Physics and Computer Science at the University of Maryland, College Park. He received his PhD from Harvard University in 2013. He was an NRC postdoc at NIST, then a postdoc at Princeton University prior to rejoining QuICS in 2020. Gullans' research interests center on the theoretical study of quantum information systems and quantum simulators in nonperturbative and strongly interacting limits. His current efforts are focused on the physics of error correction and fault-tolerance in near-term devices and scalable tomography of quantum simulators. A common theme in this research is understanding the role of randomness, noise and disorder in many-body quantum dynamics using the theoretical methods of statistical physics. The long-term goal of the research is to develop quantum simulators into reliable, computational tools for the study of many-body quantum physics and complex systems. -- The Qiskit Seminar Series is a deep dive into various academic and research topics within the quantum community. It will feature community members and leaders every Friday, 12 PM EDT.