APS March Meeting 2022: Quantum Machines’ All-Star Lineup
While sports fans have their own March Madness, we physicists enjoy APS March Meeting Madness instead. We couldn’t be more excited that Meeting Madness is starting back up again! Not only is it the biggest event of the year in physics, but after two long Covid-stricken years, we’ll be finally seeing the community face to face (or mask to mask) this year.
So, which physicists’ talks are you putting in your roster? If you’re still looking to fill up spots on your March Meeting lineup, take a look below at the exciting talks that our team will be sharing this year. Here’s a quick glance at the QM Scientific Lineup.
The QM team has also been putting together in-depth workshops and live booth demos for you every day of the conference. Get ready for exciting sessions on implementations of quantum control on quantum error correction, neutral atom arrays, and more! Check out the full schedule here.
P.S. We’ve heard there might be some legendary players joining us this year at the QM booth (#609). Be sure to follow us on social to find out more, and join us at APS to meet the legends in person (hint, you might even be able to take a few of them back home with you)!
Reducing the Sensitivity of Quantum Gates to Laser Intensity Noise via Real-Time Feedback on Gate Parameters
Abstract: Quantum processors using laser fields to drive qubits suffer from laser intensity fluctuations which limit gate fidelities. Mitigation of such noise processes via feedback was up until now only available via low bandwidth sequencers running on CPUs (allowing at best for shot to shot corrections) or on FPGA processors and analog circuits that take orders of magnitude longer to develop and iterate on. In this talk, we demonstrate a novel hardware and software architecture allowing the generation of high bandwidth (>250kHz) feedback programs written in a Turing-complete, high-level programming language called QUA. The approach is based on the real-time synthesis of signals using QM’s pulse processor, a novel chip architecture and instruction set designed to generate quantum circuits.
The pulse processor allows adapting gate waveforms in real-time based on acquired error signals such as laser intensity fluctuations measured on fast photodiodes. The user can write arbitrary control programs in QUA, which are then compiled and run in real-time on the pulse processor establishing feedback bandwidths exceeding 250kHz, often limited by latencies introduced by propagation delays in the lab.
Bridging the Gap Between NISQ Variational Algorithms and SW/HW Architectures Constraints
Abstract: Variational algorithms are key candidate algorithms for achieving a quantum advantage in the NISQ era. Variational algorithms require close communication between classical algorithms running on a classical processor such as CPUs and quantum circuits running on a quantum processor. Efficient communication between the two, and fast reconfiguration of the quantum control sequence is key to achieving maximal utilization of quantum computation resources.
Here we discuss quantum control software/hardware architectures constraints and bottlenecks for variational algorithms execution and how both the algorithms as well as the SW/HW architectures may be considered together to enable optimized performance and utilization, which could accelerate the timeline towards such an advantage.
Accelerating the Timeline for Practical QEC With Highly Configurable Control Platforms – Parts 1 + 2
Abstract: While quantum computers have the potential to solve important problems beyond the reach of any classical technology, error rates pose a great challenge towards the realization of a practical machine. Quantum Error Correction (QEC) codes aim to reduce those error rates by encoding quantum information non-locally through the use of multiple physical qubits and are considered today as one of the most promising paths towards fault-tolerant quantum computation.
In order to cope with those emerging issues, there is a dire need to deploy a flexible control platform, allowing the formulation and execution of QEC, which requires efficient real-time processing and control flow features to push available quantum hardware to its limits.
In this talk, we elaborate on the classical control schemes in QEC and demonstrate how they are concretely implemented on QM’s Quantum Orchestration Platform (QOP) to enhance performance. We show how the technology behind this platform enables fast, flexible design and exploration of QEC protocols while providing unmatched performance. In particular, we discuss novel adaptive error syndrome measurements and repeat until success protocols introduced in recent works and their seamless implementation on the platform.
Entropy: A Lab Manager Software That Lowers the Lab Entropy and Boosts Your Productivity
Abstract: Running computations on quantum processors requires calibration of a growing number of qubits while allowing execution of complex control sequences. This joins a host of additional challenges such as collecting, sorting, and gaining insight into the experimental data records. However, human real-time cognitive processing capacity in the lab remains limited. To scale up, we need to provide a good contextual interface between experimental protocol, results, and narrative.
We present Entropy, a software solution that manages complex experimental workflows, provides drilled-down views on the system in both real-time and off-line and ensures a consistent and future-proof record of lab operations. Entropy enables automatic calibration, easy debugging, and universally hyperlinked and searchable experiment-runs, results, and lab notebooks.
Entropy is a free and open-source solution with a modern web interface and modular architecture. It is built with the best open-source industry-standard stack, giving a performant out-of-box experience and innumerable options for customization and extensions. In this, we will show a live demonstration of how a researcher can use Entropy to improve their workflow.
Fullstack Quantum Compilation: Mind the Pulse Gap
Abstract: The quantum computing ecosystem has grown substantially in terms of accessible cloud solutions, quantum programming languages, and different open source and proprietary tools. The physical and engineering effort is also rapidly advancing with new technologies and ideas being put forth on a daily basis, e.g. new qubit types, error correction algorithms, qRAM, and many more. Hence, it becomes increasingly important to bridge the gap between the various end-user interfaces and the many different types of QPUs.
In this talk, we discuss quantum compilation, the process in which the high-level quantum programming language is optimized and transformed into low-level instructions that control Quantum Machines’ comprehensive control system, the Quantum Orchestration Platform (QOP). The compilation is composed of several layers and algorithms, and we focus on the compilation from the logic gate level (e.g., OpenQASM) into QUA, QOP’s pulse-level language.
Quantum Intermediate Representation – Why, What and How
Abstract: As the quantum computing stack evolves, it becomes increasingly important to create standard interfaces in order to create larger communities and develop a rich ecosystem. In particular, intermediate representations (IRs), which allow the standard description of quantum programs that serve as a compilation target for high-level programming languages and as a source for execution by quantum machines, will play a critical role in the growth of the field. Here we discuss the various considerations in designing such IRs for quantum computing and how different choices may affect performance as well as ecosystem development.
Variational Quantum Algorithms With the Quantum Orchestration Platform
Abstract: Among the candidates that would showcase a near-term potential advantage over classical computing, Variational Quantum Algorithms (VQAs) do find a large interest in the research community, for they share in common the idea to exploit quantum information processing as a tool for computing difficult functions in the frame of a wider classical computation. Therefore, there is a dire need to build a unified framework for controlling quantum processors and running heavy classical processing. The simultaneous realization of those two features constitutes an essential requirement for running efficient hybrid classical-quantum algorithms.
We shall demonstrate that the Quantum Orchestration Platform (QOP), Quantum Machines’ quantum control stack, can constitute this central component, efficiently connecting classical and quantum resources. Moreover, the enabling of pulse control and tunability of the circuit scheduling could further extend the performance offered by NISQ hardware through a combination of Quantum Optimal Control (QOC) theory and VQAs, which can be seamlessly implemented through the use of the QOP specifically designed pulse-level programming language QUA.
Adaptive Real-Time Protocols for Improved Sensing with NV Centers
Abstract: The Quantum Machines’ Quantum Orchestration Platform (QOP) has advanced real-time capabilities that can be used for various applications. Here we will present several results from groups working with the QOP that utilize its unique capabilities. We will show how real-time feedback and adaptive thresholding can improve the single-shot readout (SSRO) of a three-level nuclear spin next to an NV center.
Adaptive Bayesian estimation has been proven to improve the sensitivity of SSRO sensors. However, in the absence of SSRO, adaptive Bayesian estimation requires complex real-time calculations that were not experimentally demonstrated. We report the first real-time adaptive bayesian estimation with binomial distribution demonstrated using the QOP and an NV center. We calculate the binomial distribution, extract both the optimal phase and duration for the next sensing step.