SearcharxivSearch

arXiv subjects

Kenneth M. Rudinger

Publications and source records attributed to Kenneth M. Rudinger.

13 recordsLinked to original sources

Detailed, interpretable characterization of mid-circuit measurement on a transmon qubit

Mid-circuit measurements (MCMs) are critical components of the quantum error correction protocols expected to enable utility-scale quantum computing. MCMs can be modeled by quantum instruments (a type of quantum operation or process), which can be characterized self-consistently using gate set tomography. However, experimentally estimated quantum instruments are often hard to interpret or relate to device physics. We address this challenge by adapting the error generator formalism -- previously used to interpret noisy quantum gates by decomposing their error processes into physically meaningful sums of "elementary errors" -- to MCMs. We deploy our new analysis on a transmon qubit device to tease out and quantify error mechanisms including amplitude damping, readout error, and imperfect collapse. We examine in detail how the magnitudes of these errors vary with the readout pulse amplitude, recover the key features of dispersive readout predicted by theory, and show that these features can be modeled parsimoniously using a reduced model with just a few parameters.

quant-ph

Mid-circuit logic executed in the qubit layer of a quantum processor

Practical quantum computers need to continuously exchange data between classical and quantum subsystems during a computation. Mid-circuit measurements of a qubits state are transferred to the classical electronics layer, and their outcome can inform feedforward operations that close the loop back to the quantum layer. These operations are crucial for fault-tolerant quantum computers, but the quantum-classical loop must be completed before the qubits decohere, presenting a substantial engineering challenge for full-scale systems comprising millions of qubits. Here we perform the first mid-circuit measurements in a system of silicon spin qubits, and show that feedforward operations can be performed without needing to route information to the classical layer. This in-layer approach leverages a backaction-driven control technique that has previously been considered a source of error. We benchmark our in-layer strategy, together with the standard FPGA-enabled approach, and analyse the performance of both methods using gate set tomography. Our results provide the first step towards moving resource-intensive classical processing into the quantum layer, an advance that could solve key engineering challenges, and drastically reduce the power budget of future quantum computers.

quant-ph

Benchmarking quantum computers with any quantum algorithm

Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale computations, these benchmarks currently test this hardware's performance on ``small'' problem instances that are not necessarily representative of utility-scale problems. Furthermore, these benchmarks often employ methods that are unscalable, limiting their ability to track progress towards utility-scale applications. In this work, we present a method for creating scalable and efficient benchmarks from any quantum algorithm or application. Our subcircuit volumetric benchmarking (SVB) method runs subcircuits of varied shape that are ``snipped out'' from some target circuit, which could implement a utility-scale algorithm. SVB is scalable and it enables estimating a capability coefficient that concisely summarizes progress towards implementing the target circuit. We demonstrate SVB with experiments on IBM Q systems using a Hamiltonian block-encoding subroutine from quantum chemistry algorithms.

quant-ph

Tomography of entangling two-qubit logic operations in exchange-coupled donor electron spin qubits

Scalable quantum processors require high-fidelity universal quantum logic operations in a manufacturable physical platform. Donors in silicon provide atomic size, excellent quantum coherence and compatibility with standard semiconductor processing, but no entanglement between donor-bound electron spins has been demonstrated to date. Here we present the experimental demonstration and tomography of universal 1- and 2-qubit gates in a system of two weakly exchange-coupled electrons, bound to single phosphorus donors introduced in silicon by ion implantation. We surprisingly observe that the exchange interaction has no effect on the qubit coherence. We quantify the fidelity of the quantum operations using gate set tomography (GST), and we use the universal gate set to create entangled Bell states of the electrons spins, with fidelity ~ 93%, and concurrence 0.91 +/- 0.08. These results form the necessary basis for scaling up donor-based quantum computers.

quant-ph

Two-Qubit Gate Set Tomography with Fewer Circuits

Gate set tomography (GST) is a self-consistent and highly accurate method for the tomographic reconstruction of a quantum information processor's quantum logic operations, including gates, state preparations, and measurements. However, GST's experimental cost grows exponentially with qubit number. For characterizing even just two qubits, a standard GST experiment may have tens of thousands of circuits, making it prohibitively expensive for platforms. We show that, because GST experiments are massively overcomplete, many circuits can be discarded. This dramatically reduces GST's experimental cost while still maintaining GST's Heisenberg-like scaling in accuracy. We show how to exploit the structure of GST circuits to determine which ones are superfluous. We confirm the efficacy of the resulting experiment designs both through numerical simulations and via the Fisher information for said designs. We also explore the impact of these techniques on the prospects of three-qubit GST.

quant-ph

Assessment of error variation in high-fidelity two-qubit gates in silicon

Achieving high-fidelity entangling operations between qubits consistently is essential for the performance of multi-qubit systems and is a crucial factor in achieving fault-tolerant quantum processors. Solid-state platforms are particularly exposed to errors due to materials-induced variability between qubits, which leads to performance inconsistencies. Here we study the errors in a spin qubit processor, tying them to their physical origins. We leverage this knowledge to demonstrate consistent and repeatable operation with above 99% fidelity of two-qubit gates in the technologically important silicon metal-oxide-semiconductor (SiMOS) quantum dot platform. We undertake a detailed study of these operations by analysing the physical errors and fidelities in multiple devices through numerous trials and extended periods to ensure that we capture the variation and the most common error types. Physical error sources include the slow nuclear and electrical noise on single qubits and contextual noise. The identification of the noise sources can be used to maintain performance within tolerance as well as inform future device fabrication. Furthermore, we investigate the impact of qubit design, feedback systems, and robust gates on implementing scalable, high-fidelity control strategies. These results are achieved by using three different characterization methods, we measure entangling gate fidelities ranging from 96.8% to 99.8%. Our analysis tools identify the causes of qubit degradation and offer ways understand their physical mechanisms. These results highlight both the capabilities and challenges for the scaling up of silicon spin-based qubits into full-scale quantum processors.

quant-ph

Lyapunov control-inspired strategies for quantum combinatorial optimization

The prospect of using quantum computers to solve combinatorial optimization problems via the quantum approximate optimization algorithm (QAOA) has attracted considerable interest in recent years. However, a key limitation associated with QAOA is the need to classically optimize over a set of quantum circuit parameters. This classical optimization can have significant associated costs and challenges. Here, we provide an expanded description of Lyapunov control-inspired strategies for quantum optimization, as presented in [Magann et al., Phys. Rev. Lett. 129, 250502 (2022)], that do not require any classical optimization effort. Instead, these strategies utilize feedback from qubit measurements to assign values to the quantum circuit parameters in a deterministic manner, such that the combinatorial optimization problem solution improves monotonically with the quantum circuit depth. Numerical analyses are presented that investigate the utility of these strategies towards MaxCut on weighted and unweighted 3-regular graphs, both in ideal implementations and also in the presence of measurement noise. We also discuss how how these strategies compare with QAOA, how they may be used to seed QAOA optimizations in order to improve performance for near-term applications, and explore connections to quantum annealing.

quant-ph

Feedback-based quantum optimization

It is hoped that quantum computers will offer advantages over classical computers for combinatorial optimization. Here, we introduce a feedback-based strategy for quantum optimization, where the results of qubit measurements are used to constructively assign values to quantum circuit parameters. We show that this procedure results in an estimate of the combinatorial optimization problem solution that improves monotonically with the depth of the quantum circuit. Importantly, the measurement-based feedback enables approximate solutions to the combinatorial optimization problem without the need for any classical optimization effort, as would be required for the quantum approximate optimization algorithm (QAOA). We experimentally demonstrate this feedback-based protocol on a superconducting quantum processor for the graph-partitioning problem MaxCut, and present a series of numerical analyses that further investigate the protocol's performance.

quant-ph

Precision tomography of a three-qubit donor quantum processor in silicon

Nuclear spins were among the first physical platforms to be considered for quantum information processing, because of their exceptional quantum coherence and atomic-scale footprint. However, their full potential for quantum computing has not yet been realized, due to the lack of methods to link nuclear qubits within a scalable device combined with multi-qubit operations with sufficient fidelity to sustain fault-tolerant quantum computation. Here we demonstrate universal quantum logic operations using a pair of ion-implanted 31P donor nuclei in a silicon nanoelectronic device. A nuclear two-qubit controlled-Z gate is obtained by imparting a geometric phase to a shared electron spin, and used to prepare entangled Bell states with fidelities up to 94.2(2.7)%. The quantum operations are precisely characterised using gate set tomography (GST), yielding one-qubit average gate fidelities up to 99.95(2)%, two-qubit average gate fidelity of 99.37(11)% and two-qubit preparation/measurement fidelities of 98.95(4)%. These three metrics indicate that nuclear spins in silicon are approaching the performance demanded in fault-tolerant quantum processors. We then demonstrate entanglement between the two nuclei and the shared electron by producing a Greenberger-Horne-Zeilinger three-qubit state with 92.5(1.0)% fidelity. Since electron spin qubits in semiconductors can be further coupled to other electrons or physically shuttled across different locations, these results establish a viable route for scalable quantum information processing using donor nuclear and electron spins.

quant-ph

Consistency testing for robust phase estimation

We present an extension to the robust phase estimation protocol, which can identify incorrect results that would otherwise lie outside the expected statistical range. Robust phase estimation is increasingly a method of choice for applications such as estimating the effective process parameters of noisy hardware, but its robustness is dependent on the noise satisfying certain threshold assumptions. We provide consistency checks that can indicate when those thresholds have been violated, which can be difficult or impossible to test directly. We test these consistency checks for several common noise models, and identify two possible checks with high accuracy in locating the point in a robust phase estimation run at which further estimates should not be trusted. One of these checks may be chosen based on resource availability, or they can be used together in order to provide additional verification.

quant-ph

Just another quantum assembly language (Jaqal)

The Quantum Scientific Computing Open User Testbed (QSCOUT) is a trapped-ion quantum computer testbed realized at Sandia National Laboratories on behalf of the Department of Energy's Office of Science and its Advanced Scientific Computing (ASCR) program. Here we describe Jaqal, for Just another quantum assembly language, the programming language we invented to specify programs executed on QSCOUT. Jaqal is useful beyond QSCOUT---it can support mutliple hardware targets because it offloads gate names and their pulse-sequence definitions to external files. We describe the capabilities of the Jaqal language, our approach in designing it, and the reasons for its creation. To learn more about QSCOUT, Jaqal, or JaqalPaq, the metaprogramming Python package we developed for Jaqal, please visit https://qscout.sandia.gov, https://gitlab.com/jaqal, or send an e-mail to qscout@sandia.gov.

quant-ph

Jaqal, the Quantum Assembly Language for QSCOUT

QSCOUT is the Quantum Scientific Computing Open User Testbed, a trapped-ion quantum computer testbed realized at Sandia National Laboratories on behalf of the Department of Energy's Office of Science and its Advanced Scientific Computing (ASCR) program. Jaqal, for Just Another Quantum Assembly Language, is the programming language used to specify programs executed on QSCOUT. This document contains a specification of Jaqal along with a summary of QSCOUT 1.0 capabilities, example Jaqal programs, and plans for possible future extensions. To learn more about QSCOUT and the Jaqal language developed for it, please visit qscout.sandia.gov or send an e-mail to qscout@sandia.gov.

quant-ph

Optimization of a solid-state electron spin qubit using Gate Set Tomography

State of the art qubit systems are reaching the gate fidelities required for scalable quantum computation architectures. Further improvements in the fidelity of quantum gates demands characterization and benchmarking protocols that are efficient, reliable and extremely accurate. Ideally, a benchmarking protocol should also provide information on how to rectify residual errors. Gate Set Tomography (GST) is one such protocol designed to give detailed characterization of as-built qubits. We implemented GST on a high-fidelity electron-spin qubit confined by a single $^{31}$P atom in $^{28}$Si. The results reveal systematic errors that a randomized benchmarking analysis could measure but not identify, whereas GST indicated the need for improved calibration of the length of the control pulses. After introducing this modification, we measured a new benchmark average gate fidelity of $99.942(8)\%$, an improvement on the previous value of $99.90(2)\%$. Furthermore, GST revealed high levels of non-Markovian noise in the system, which will need to be understood and addressed when the qubit is used within a fault-tolerant quantum computation scheme.

cond-mat.mes-hall