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DOE OSTI2024

SQMS science advances impact on Rigetti commercial processors

The collaboration between the Superconducting Quantum Materials and Systems Center (SQMS) and Rigetti Computing produced several advancements in our understanding of the role of materials characteristics in quantum processor performance. This partnership leverages SQMS's extensive characterization infrastructure and cutting-edge research in materials, and Rigetti's expertise in quantum hardware and robust nanofabrication to improve precision and performance of Rigetti's test QPUs. Qubit frequency is determined in large part by the properties of Josephson junctions (JJs) made of amorphous oxide tunnel barriers; the Alternating-Bias Assisted Annealing (ABAA) process allows us to tune JJs to their desired frequency [1]. Work by SQMS researchers in characterizing high-precision JJs post-processed (using ABAA) have yielded crucial information on the nature of the structure and chemical bonding uniformity of the ABAA processed amorphous oxides. Performance has also been improved through a comprehensive series of experiments that tested encapsulation and surface treatment. Encapsulation of the niobium metal layer with tantalum resulted in an T1 improvement of 80%, experimentally confirming the role of Nb surface losses in qubit performance [2]. Pre-treatment of the underlying silicon surface prior to JJ fabrication by replacing a buffered oxide etch (BOE) with hydrofluoric acid (HF) followed by aqueous ammonium fluoride (NH4F) has shown a statistically significant improvement of T1 by 22%, and reduction in the number of strongly-coupled TLS [3]. These examples, as well as many other published and ongoing investigations, demonstrate the mutual benefits that come from Rigetti's involvement in the SQMS collaboration. [1] - Pappas, D.P., et al. (2024). https://doi.org/10.1038/s43246-024-00596-z [2] - Bal, M., et al. (2024). https://doi.org/10.1038/s41534-024-00840-x [3] Kopas, C. J. et al. Preprint at https://doi.org/10.48550/arXiv.2408.02863 (2024).

Lachman, Ella↗
DOE OSTI2021

Using Grover's search algorithm to characterize the Rigetti Quantum Computing Platform

Performance of the Rigetti quantum computing platform was tested during the period of time from 12/16/2019 to 05/18/2020. The Grover's search (GS) algorithm was used as a testing tool, in particular, 3- and 4-level versions of the algorithm. As a result, a number of hardware issues were revealed, so the algorithm was split to smaller blocks and individual gates, and all of them were tested separately. The fidelity decay was found to be due to both decoherent processes and coherent errors of the native hardware gates. These errors were estimated from RX gate benchmarks and were in a form of extra rotation of the quantum state. As a consequence of that, performance of the algorithm was shown to be strongly dependent on the native gate decomposition of the program. Suggestions and possible improvements of the future Rigetti runs are made based on the obtained observations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum Information for Fusion Energy Sciences (Final Technical Report)

The simulation of plasma dynamics is a critical area of Fusion Energy Sciences (FES) due to it’s usefulness in predicting, controlling, and confining plasmas in the context of potential fusion reactors. The simulation of plasmas is a computationally difficult problem in both classical and quantum physics, motivating investigation into the potential of quantum computers to simulate these systems. This project took several concrete steps towards this goal by developing tools for improving the control, characterization, and calibration of quantum gates on a superconducting quantum computer, developing error suppression and mitigation tools to reduce errors on the quantum computer, and utilizing these advancements to simulate reduced models of plasma dynamics on the quantum computer. In order to efficiently simulate plasma physics, an optimal control method which synthesizes, directly at the pulse level, any quantum gate on qubit and qutrit systems was developed. Using four superconducting transmon quantum processors at Rigetti and LLNL, it was demonstrated that any arbitrary quantum gate on qubits and qutrits could be implemented with high fidelity, leading to a significantly reduced length of a gate sequence. A problem of interest in FES is the nonlinear optical process of laser pulse compression within a plasma. Since quantum physics is linear, simulating nonlinear operations is not naturally feasible on a quantum computer, however it is possible to simulated a quantized version of the nonlinear process. A quantization approach to convert nonlinear wave-wave interaction problems to Hamiltonian simulation problems was developed and demonstrated using two qubits on a Rigetti device. In this experiment, a number of error suppression and mitigation techniques were investigated to determine how best to utilize the finite quantum resources. This study provides an example of how plasma problems may be solved on near-term, noisy quantum computing platforms and identified a promising set of techniques. Building on the insights of these experiments, the investigation turned to linear electron-plasma wave physics. A connection was identified between a local one-dimensional lattice spin model and linear wave phenomena, allowing a plasma physics problem to be efficiently mapped to the quantum computer. In this framework, reflection and transmission of plasma waves at a sharp boundary was studied, as well as the propagation of waves through an inhomogeneous plasma medium. In addition to the suite of error suppression and mitigation techniques developed, this experiment introduced the use of a digital-analog gate scheme designed to efficiently simulate the plasma Hamiltonian. With hardware available at the conclusion of the project, simulation at the scale of 9 qubits and 15 timesteps (60 entangling layers) was achieved.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Dual-map framework for noise characterization of quantum computers

In order to understand the capabilities and limitations of quantum computers, it is necessary to develop methods that efficiently characterize and benchmark error channels present on these devices. In this paper, we present a method that faithfully reconstructs a marginal (local) approximation of the effective noise (MATEN) channel, that acts as a single layer at the end of the circuit. We first introduce a dual-map framework that allows us to analytically derive expectation values of observables with respect to noisy circuits. These findings are supported by numerical simulations of the quantum approximate optimization algorithm (QAOA) that also justify the MATEN, even in the presence of nonlocal errors that occur during a circuit. Finally, we demonstrate the performance of the method on Rigetti's Aspen-11 quantum computer for QAOA circuits up to six qubits, successfully predicting the observed measurements on a majority of the qubits.

Sud, James↗
DOE OSTI2024

Direct pulse-level compilation of arbitrary quantum logic gates on superconducting qutrits

Advanced simulations and calculations on quantum computers require high-fidelity implementations of quantum operations. The universal gateset approach builds complex unitaries from a small set of primitive gates, often resulting in a long gate sequence, which is typically a leading factor in the total accumulated error. Compiling a complex unitary for processors with higher-dimensional logical elements, such as qutrits, exacerbates the accumulated error per unitary, since an even longer gate sequence is required. Optimal control methods promise time- and resource-efficient compact gate sequences and, therefore, higher fidelity. These methods generate pulses that can directly implement any complex unitary on a quantum device. In this work, we demonstrate that any arbitrary qubit and qutrit gate can be realized with high fidelity, which can significantly reduce the length of a gate sequence. We generate and test pulses for a large set of randomly selected arbitrary unitaries on several quantum processing units (QPUs): the Lawrence Livermore National Laboratory Quantum Device and Integration Testbed’s (QuDIT’s) standard QPU and three of Rigetti’s QPUs: Ankaa-2, Ankaa-9Q-1, and Aspen-M-3. On the QuDIT platform’s standard QPU, the average fidelity of random qutrit gates is 97.9 ± 0.5% measured with conventional QPT and 98.8 ± 0.6% from QPT with gate folding. Rigetti’s Ankaa-2 achieves random qubit gates with an average fidelity of 98.4 ± 0.5% (conventional QPT) and 99.7 ± 0.1% (QPT with gate folding). On Ankaa-9Q-1 and Aspen-M-3, the average fidelities with conventional qubit QPT measurements were higher than 99% (see Appendix). Here we show that optimal control gates are robust to drift for at least 3 h and that the same calibration parameters can be used for all implemented gates. Our work promises that the calibration overheads for optimal control gates can be made small enough to enable efficient quantum circuits based on this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

QASMBench: A Low-Level Quantum Benchmark Suite for NISQ Evaluation and Simulation

The rapid development of quantum computing (QC) in the NISQ era urgently demands a low-level benchmark suite and insightful evaluation metrics for characterizing the properties of prototype NISQ devices, the efficiency of QC programming compilers, schedulers and assemblers, and the capability of quantum system simulators in a classical computer. In this work, we fill this gap by proposing a low-level, easy-to-use benchmark suite called QASMBench based on the OpenQASM assembly representation. It consolidates commonly used quantum routines and kernels from a variety of domains including chemistry, simulation, linear algebra, searching, optimization, arithmetic, machine learning, fault tolerance, cryptography, and so on, trading-off between generality and usability. To analyze these kernels in terms of NISQ device execution, in addition to circuit width and depth, we propose four circuit metrics including gate density, retention lifespan, measurement density, and entanglement variance, to extract more insights about the execution efficiency, the susceptibility to NISQ error, and the potential gain from machine-specific optimizations. Applications in QASMBench can be launched and verified on several NISQ platforms, including IBM-Q, Rigetti, IonQ and Quantinuum. For evaluation, we measure the execution fidelity of a subset of QASMBench applications on 12 IBM-Q machines through density matrix state tomography, comprising 25K circuit evaluations. In addition we also compare the fidelity of executions among the IBM-Q machines, the IonQ QPU and the Rigetti Aspen M-1 system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Efficient, Predictive Tomography of Multi-Qubit Quantum Processors

After decades of R&D, quantum computers comprising more than 2 qubits are appearing. If this progress is to continue, the research community requires a capability for precise characterization (“tomography”) of these enlarged devices, which will enable benchmarking, improvement, and finally certification as mission-ready. As world leaders in characterization -- our gate set tomography (GST) method is the current state of the art – the project team is keenly aware that every existing protocol is either (1) catastrophically inefficient for more than 2 qubits, or (2) not rich enough to predict device behavior. GST scales poorly, while the popular randomized benchmarking technique only measures a single aggregated error probability. This project explored a new insight: that the combinatorial explosion plaguing standard GST could be avoided by using an ansatz of few-qubit interactions to build a complete, efficient model for multi-qubit errors. We developed this approach, prototyped it, and tested it on a cutting-edge quantum processor developed by Rigetti Quantum Computing (RQC), a US-based startup. We implemented our new models within Sandia’s PyGSTi open-source code, and tested them experimentally on the RQC device by probing crosstalk. We found two major results: first, our schema worked and is viable for further development; second, while the Rigetti device is indeed a “real” 8-qubit quantum processor, its behavior fluctuated significantly over time while we were experimenting with it and this drift made it difficult to fit our models of crosstalk to the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Discovery of Nb hydride precipitates in superconducting qubits

We report the first evidence of the formation of niobium hydrides within niobium films on silicon substrates in superconducting qubits fabricated at Rigetti Computing. We combine complementary techniques including room and cryogenic temperature atomic scale high-resolution and scanning transmission electron microscopy (HR-TEM and STEM), atomic force microscopy (AFM), and the time-of-flight secondary ion mass spectroscopy (TOF-SIMS) to reveal the existence of the niobium hydride precipitates directly in the Rigetti chip areas. Electron diffraction and high-resolution transmission electron microscopy (HR-TEM) analyses are performed at room and cryogenic temperatures (~106 K) on superconducting qubit niobium film areas, and reveal the formation of three types of Nb hydride domains with different crystalline orientations and atomic structures. There is also variation in their size and morphology from small (~5 nm) irregular shape domains within the Nb grains to large (~10-100 nm) Nb grains fully converted to niobium hydride. As niobium hydrides are non-superconducting and can easily change in size and location upon different cooldowns to cryogenic temperatures, our findings highlight a new previously unknown source of decoherence in superconducting qubits, contributing to both quasiparticle and two-level system (TLS) losses, and offering a potential explanation for qubit performance changes upon cooldowns. A pathway to mitigate the formation of the Nb hydrides for superconducting qubit applications is also discussed.

Lee, Jaeyel↗
DOE OSTI2025

Robust resonator-assisted ZZ cancellation in superconducting quantum processors

Strong qubit interactions are essential for faster two-qubit gates, but they often come with undesirable ZZ interactions that limit gate fidelity. Existing methods to mitigate these interactions, such as flux-tunable couplers, can introduce additional noise and complexity. In contrast, our work presents a simpler, more robust approach using a driven resonator to cancel the static ZZ interaction between qubits [1]. The experiment was performed on a revised 9-qubit quantum processing unit from Rigetti, developed in collaboration with SQMS scientists. We validate the resonator-induced-phase (RIP) interaction, where an off-resonant drive on the resonator dynamically cancels ZZ coupling. This marks an important step toward high gate fidelities. We also explore the entangling gates enabled by this coupling scheme, focusing on minimizing gate duration and qubit decoherence while maintaining effective ZZ cancellation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Demonstration of Cross-Resonance Gates with Resonator-Assisted ZZ Cancellation

We present the characterization of a CNOT gate realized by combining cross-resonance interaction with resonator-assisted ZZ cancellation in fixed-frequency transmons on a Rigetti–SQMS co-developed quantum processor. Extending earlier work on dynamical ZZ cancellation via off-resonant resonator drives [1], we demonstrate a direct CNOT gate implementation achieved through two microwave drives on the transmons that generate a CX rotation in the |10⟩−|11⟩ subspace while selectively darkening the |00⟩−|01⟩ transition. This tunable-coupler-free approach enables high-fidelity gates and enhances the scalability of superconducting quantum architectures. [1] Z. Huang et al., Phys. Rev. Applied 22, 034007 (2024)

Heidler, Paul [Fermilab]↗
DOE OSTI2026

Formation of niobium hydride precipitates in superconducting qubits

We report evidence for the formation of niobium hydride phase within niobium films on silicon substrates in superconducting qubits fabricated at Rigetti Computing. For this study, we combined complementary techniques—including room-temperature and cryogenic atomic force microscopy (AFM), synchrotron x-ray diffraction, and time-of-flight secondary ion mass spectroscopy (ToF-SIMS)—to directly reveal the existence of niobium hydride precipitates on the surface of superconducting qubits. Upon cryogenic cooling, we observed variation in the size and morphology of the hydrides, ranging from small (∼5 nm) irregular shapes to large (∼10–100 nm) domains within the Nb grains, which were fully converted to niobium hydrides. Since niobium hydrides are nonsuperconducting and can easily change in size and location upon different cooldowns to cryogenic temperature, our finding highlights a previously unknown source of decoherence in superconducting qubits. This contributes to quasiparticle losses, offering a potential explanation for changes in qubit performance upon cooldowns. Finally, by leveraging the RF performance of a 3D bulk Nb resonator, we quantify RF dissipation in a superconducting qubit caused by hydrogen concentration variation, and propose a practical engineering pathway to mitigate the formation of Nb hydrides for superconducting qubit applications.

Sung, Zuhawn [Fermi National Accelerator Laborator↗
DOE OSTI2021

Noise Robustness and Experimental Demonstration of a Quantum Generative Adversarial Network for Continuous Distributions

Abstract The potential advantage of machine learning in quantum computers is a topic of intense discussion in the literature. Theoretical, numerical, and experimental explorations will most likely be required to understand its power. There have been different algorithms proposed to exploit the probabilistic nature of variational quantum circuits for generative modeling. In this paper, a hybrid architecture for quantum generative adversarial networks (QGANs) is employed and their robustness in the presence of noise is studied. A simple way of adding different types of noise to the quantum generator circuit is devised, and the noisy hybrid QGANs (HQGANs) are simulated numerically to learn continuous probability distributions, and to show that the performance of HQGANs remains unaffected. The effect of different parameters on the training time is also investigated to reduce the computational scaling of the algorithm and simplify its deployment on a quantum computer. The training on Rigetti's Aspen‐4‐2Q‐A quantum processing unit is then performed, and the results from the training are presented. The authors' results pave the way for experimental exploration of different quantum machine learning algorithms on noisy intermediate‐scale quantum devices.

Anand, Abhinav↗
DOE OSTI2021

Robust implementation of generative modeling with parametrized quantum circuits

Although the performance of hybrid quantum-classical algorithms is highly dependent on the selection of the classical optimizer and the circuit ansätze, a robust and thorough assessment on-hardware of such features has been missing to date. From the optimizer perspective, the primary challenge lies in the solver’s stochastic nature, and their significant variance over the random initialization. Therefore, a robust comparison requires one to perform several training curves for each solver before one can reach conclusions about their typical performance. Since each of the training curves requires the execution of thousands of quantum circuits in the quantum computer, such a robust study remained a steep challenge for most hybrid platforms available today. In this work, we leverage on Rigetti’s Quantum Cloud Services (QCS™) to overcome this implementation barrier, and we study the on-hardware performance of the data-driven quantum circuit learning (DDQCL) for three different state-of-the-art classical solvers, and on two-different circuit ansätze associated to different entangling connectivity graphs for the same task. Additionally, we assess the gains in performance from varying circuit depths. To evaluate the typical performance associated with each of these settings in this benchmark study, we use at least five independent runs of DDQCL towards the generation of quantum generative models capable of capturing the patterns of the canonical Bars and Stripes dataset. In this experimental benchmarking, the gradient-free optimization algorithms show an outstanding performance compared to the gradient-based solver. In particular, one of them had better performance when handling the unavoidable noisy objective function to be minimized under experimental conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Efficient Step-Merged Quantum Imaginary Time Evolution Algorithm for Quantum Chemistry

In this work, we develop a resource-efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state evolution path. We use this algorithm to determine the binding energy curves of a set of molecules, including H 2 , H 4 , H 6 , LiH, HF, H 2 O, and BeH 2 , and find highly accurate results. The required quantum resources of smQITE calculations can be further reduced by adopting the circuit form of the variational quantum eigensolver (VQE) technique, such as the unitary coupled cluster ansatz. We demonstrate that smQITE achieves a similar computational accuracy as VQE at the same fixed-circuit ansatz, without requiring a generally complicated high-dimensional nonconvex optimization. Finally, smQITE calculations are carried out on Rigetti quantum processing units, demonstrating that the approach is readily applicable on current noisy intermediate-scale quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Variational fast forwarding for quantum simulation beyond the coherence time

Abstract Trotterization-based, iterative approaches to quantum simulation (QS) are restricted to simulation times less than the coherence time of the quantum computer (QC), which limits their utility in the near term. Here, we present a hybrid quantum-classical algorithm, called variational fast forwarding (VFF), for decreasing the quantum circuit depth of QSs. VFF seeks an approximate diagonalization of a short-time simulation to enable longer-time simulations using a constant number of gates. Our error analysis provides two results: (1) the simulation error of VFF scales at worst linearly in the fast-forwarded simulation time, and (2) our cost function’s operational meaning as an upper bound on average-case simulation error provides a natural termination condition for VFF. We implement VFF for the Hubbard, Ising, and Heisenberg models on a simulator. In addition, we implement VFF on Rigetti’s QC to demonstrate simulation beyond the coherence time. Finally, we show how to estimate energy eigenvalues using VFF.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Long-time simulations for fixed input states on quantum hardware

Publicly accessible quantum computers open the exciting possibility of experimental dynamical quantum simulations. While rapidly improving, current devices have short coherence times, restricting the viable circuit depth. Despite these limitations, we demonstrate long-time, high fidelity simulations on current hardware. Specifically, we simulate an XY-model spin chain on Rigetti and IBM quantum computers, maintaining a fidelity over 0.9 for 150 times longer than is possible using the iterated Trotter method. Our simulations use an algorithm we call fixed state Variational Fast Forwarding (fsVFF). Recent work has shown an approximate diagonalization of a short time evolution unitary allows a fixed-depth simulation. fsVFF substantially reduces the required resources by only diagonalizing the energy subspace spanned by the initial state, rather than over the total Hilbert space. We further demonstrate the viability of fsVFF through large numerical simulations, and provide an analysis of the noise resilience and scaling of simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

QuaSiMo: A composable library to program hybrid workflows for quantum simulation

Abstract A composable design scheme is presented for the development of hybrid quantum/classical algorithms and workflows for applications of quantum simulation. The proposed object‐oriented approach is based on constructing an expressive set of common data structures and methods that enables programming of a broad variety of complex hybrid quantum simulation applications. The abstract core of the scheme is distilled from the analysis of the current quantum simulation algorithms. Subsequently, it allows synthesis of new hybrid algorithms and workflows via the extension, specialisation, and dynamic customisation of the abstract core classes defined by the proposed design. The design scheme is implemented using the hardware‐agnostic programming language QCOR into the QuaSiMo library. To validate the implementation, the authors test and show its utility on commercial quantum processors from IBM and Rigetti, running some prototypical quantum simulations.

97 MATHEMATICS AND COMPUTING↗