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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High-dimensional discrete Fourier transform gates with a quantum frequency processor

The discrete Fourier transform (DFT) is of fundamental interest in photonic quantum information, yet the ability to scale it to high dimensions depends heavily on the physical encoding, with practical recipes lacking in emerging platforms such as frequency bins. In this article, we show that d -point frequency-bin DFTs can be realized with a fixed three-component quantum frequency processor (QFP), simply by adding to the electro-optic modulation signals one radio-frequency harmonic per each incremental increase in d . We verify gate fidelity F W > 0.9997 and success probability P W > 0.965 up to d = 10 in numerical simulations, and experimentally implement the solution for d = 3, utilizing measurements with parallel DFTs to quantify entanglement and perform tomography of multiple two-photon frequency-bin states. Our results furnish new opportunities for high-dimensional frequency-bin protocols in quantum communications and networking.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Local spectroscopy of a gate-switchable moiré quantum anomalous Hall insulator

Abstract In recent years, correlated insulating states, unconventional superconductivity, and topologically non-trivial phases have all been observed in several moiré heterostructures. However, understanding of the physical mechanisms behind these phenomena is hampered by the lack of local electronic structure data. Here, we use scanning tunnelling microscopy and spectroscopy to demonstrate how the interplay between correlation, topology, and local atomic structure determines the behaviour of electron-doped twisted monolayer–bilayer graphene. Through gate- and magnetic field-dependent measurements, we observe local spectroscopic signatures indicating a quantum anomalous Hall insulating state with a total Chern number of ±2 at a doping level of three electrons per moiré unit cell. We show that the sign of the Chern number and associated magnetism can be electrostatically switched only over a limited range of twist angle and sample hetero-strain values. This results from a competition between the orbital magnetization of filled bulk bands and chiral edge states, which is sensitive to strain-induced distortions in the moiré superlattice.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
DOE OSTI2023

Trapped-ion entangling gates with bichromatic pair of microwave fields and magnetic field gradient

A trapped-ion quantum logic gate and a method of operating the trapped-ion quantum logic gate are provided. The trapped-ion quantum logic gate includes at least one ion having two internal states and forming a qubit having a qubit transition frequency ω 0 0, a magnetic field gradient, and two microwave fields. Each of the two microwave fields has a respective frequency that is detuned from the qubit transition frequency ω 0 by frequency difference δ. The at least one ion has a Rabi frequency Ω μ due to the two microwave fields and a Rabi frequency Ω g due to the magnetic field gradient. The method includes applying the magnetic field gradient and the two microwave fields to the at least one ion such that a quantity Ω g /δ is in a range between zero and 5×10 −2 .

Sutherland, Robert Tyler↗
DOE OSTI2021

Optimal calibration of gates in trapped-ion quantum computers

Abstract To harness the power of quantum computing, it is essential that a quantum computer provide maximal possible fidelity for a quantum circuit. To this end, much work has been done in the context of qubit routing or embedding, i.e., mapping circuit qubits to physical qubits based on gate performance metrics to optimize the fidelity of execution. Here, we take an alternative approach that leverages a unique capability of a trapped-ion quantum computer, i.e., the all-to-all qubit connectivity. We develop a method to determine a fixed number (budget) of quantum gates that, when calibrated, will maximize the fidelity of a batch of input quantum programs. This dynamic allocation of calibration resources on randomly accessible gates, determined using our heuristics, increases, for a wide range of calibration budget, the average fidelity from 70% or lower to 90% or higher for a typical batch of jobs on an 11-qubit device, in which the fidelity of calibrated and uncalibrated gates are taken to be 99% and 90%, respectively. Our heuristics are scalable, more than 2.5 orders of magnitude faster than a randomized method for synthetic benchmark circuits generated based on real-world use cases.

Maksymov, Andrii (ORCID:0000000282442851)↗
DOE OSTI2022

Gate-tunable heavy fermion quantum criticality in a moiré Kondo lattice

We propose a realization of Kondo lattice physics in moiré superlattices at the interface between a WX 2 homobilayer and MoX 2 monolayer (X = S,Se). Under appropriate gating conditions, the interface WX 2 layer forms a triangular lattice of local moments that couple to itinerant electrons in the other WX 2 layer via a gate-tunable Kondo exchange interaction. Using a parton mean-field approach, we identify a range of twist angles which support a gate-tuned quantum phase transition between a heavy Fermi liquid with large anomalous Hall conductance and a chiral spin liquid coexisting with a light Fermi liquid and describe experimental signatures to distinguish among competing theoretical scenarios.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A universal variational quantum eigensolver for non-Hermitian systems

Abstract Many quantum algorithms are developed to evaluate eigenvalues for Hermitian matrices. However, few practical approach exists for the eigenanalysis of non-Hermintian ones, such as arising from modern power systems. The main difficulty lies in the fact that, as the eigenvector matrix of a general matrix can be non-unitary, solving a general eigenvalue problem is inherently incompatible with existing unitary-gate-based quantum methods. To fill this gap, this paper introduces a Variational Quantum Universal Eigensolver (VQUE), which is deployable on noisy intermediate scale quantum computers. Our new contributions include: (1) The first universal variational quantum algorithm capable of evaluating the eigenvalues of non-Hermitian matrices—Inspired by Schur’s triangularization theory, VQUE unitarizes the eigenvalue problem to a procedure of searching unitary transformation matrices via quantum devices; (2) A Quantum Process Snapshot technique is devised to make VQUE maintain the potential quantum advantage inherited from the original variational quantum eigensolver—With additional $$O(log_{2}{N})$$ O ( l o g 2 N ) quantum gates, this method efficiently identifies whether a unitary operator is triangular with respect to a given basis; (3) Successful deployment and validation of VQUE on a real noisy quantum computer, which demonstrates the algorithm’s feasibility. We also undertake a comprehensive parametric study to validate VQUE’s scalability, generality, and performance in realistic applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Quantum-assisted associative adversarial network: applying quantum annealing in deep learning

Abstract Generative models have the capacity to model and generate new examples from a dataset and have an increasingly diverse set of applications driven by commercial and academic interest. In this work, we present an algorithm for learning a latent variable generative model via generative adversarial learning where the canonical uniform noise input is replaced by samples from a graphical model. This graphical model is learned by a Boltzmann machine which learns low-dimensional feature representation of data extracted by the discriminator. A quantum processor can be used to sample from the model to train the Boltzmann machine. This novel hybrid quantum-classical algorithm joins a growing family of algorithms that use a quantum processor sampling subroutine in deep learning, and provides a scalable framework to test the advantages of quantum-assisted learning. For the latent space model, fully connected, symmetric bipartite and Chimera graph topologies are compared on a reduced stochastically binarized MNIST dataset, for both classical and quantum sampling methods. The quantum-assisted associative adversarial network successfully learns a generative model of the MNIST dataset for all topologies. Evaluated using the Fréchet inception distance and inception score, the quantum and classical versions of the algorithm are found to have equivalent performance for learning an implicit generative model of the MNIST dataset. Classical sampling is used to demonstrate the algorithm on the LSUN bedrooms dataset, indicating scalability to larger and color datasets. Though the quantum processor used here is a quantum annealer, the algorithm is general enough such that any quantum processor, such as gate model quantum computers, may be substituted as a sampler.

Wilson, Max (ORCID:0000000207983391)↗
DOE OSTI2022

A QUBO formulation for top-τ eigencentrality nodes

The efficient calculation of the centrality or “hierarchy” of nodes in a network has gained great relevance in recent years due to the generation of large amounts of data. The eigenvector centrality (aka eigencentrality) is quickly becoming a good metric for centrality due to both its simplicity and fidelity. In this work we lay the foundations for solving the eigencentrality problem of ranking the importance of the nodes of a network with scores from the eigenvector of the network, using quantum computational paradigms such as quantum annealing and gate-based quantum computing. The problem is reformulated as a quadratic unconstrained binary optimization (QUBO) that can be solved on both quantum architectures. The results focus on correctly identifying a given number of the most important nodes in numerous networks given by the sparse vector solution of our QUBO formulation of the problem of identifying the top- τ highest eigencentrality nodes in a network on both the D-Wave and IBM quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Diffusive and ballistic transport in thin InSb nanowire devices using a few-layer-graphene-AlO x gate

Abstract Quantum devices based on InSb nanowires (NWs) are a prime candidate system for realizing and exploring topologically-protected quantum states and for electrically-controlled spin-based qubits. The influence of disorder on achieving reliable quantum transport regimes has been studied theoretically, highlighting the importance of optimizing both growth and nanofabrication. In this work, we consider both aspects. We developed InSb NW with thin diameters, as well as a novel gating approach, involving few-layer graphene and atomic layer deposition-grown AlO x . Low-temperature electronic transport measurements of these devices reveal conductance plateaus and Fabry–Pérot interference, evidencing phase-coherent transport in the regime of few quantum modes. The approaches developed in this work could help mitigate the role of material and fabrication-induced disorder in semiconductor-based quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Enabling Pulse-level Programming, Compilation, and Execution in XACC

Noisy gate-model quantum processing units (QPUs) are currently available from vendors over the cloud, and digital quantum programming approaches exist to run low-depth circuits on physical hardware. These digital representations are ultimately lowered to pulse-level instructions by vendor quantum control systems to affect unitary evolution representative of the submitted digital circuit. Vendors are beginning to open this pulse-level control system to the public via specified interfaces. Robust programming methodologies, software frameworks, and backend simulation technologies for this analog model of quantum computation will prove critical to advancing pulse-level control research and development. Prototypical use cases for this include error mitigation, optimal pulse control, and physics-inspired pulse construction. Here we present an extension to the XACC quantum-classical software framework that enables pulse-level programming for superconducting, gate-model quantum computers, and a novel, general, and extensible pulse-level simulation backend for XACC that scales on classical compute clusters via MPI. Our work enables custom backend Hamiltonian definitions and gate-level compilation to available pulses with a focus on performance and scalability. We end with a demonstration of this capability, and show how to use XACC for pertinent pulse-level programming tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Dancing the Quantum Waltz: Compiling Three-Qubit Gates on Four Level Architectures

Superconducting quantum devices are a leading technology for quantum computation, but they face several challenges. Gate errors, coherence errors and a lack of connectivity all contribute to low fidelity results. In particular, connectivity restrictions enforce a gate set that requires three-qubit gates to be decomposed into one- or two-qubit gates. This substantially increases the number of two-qubit gates that need to be executed. However, many quantum devices have access to higher energy levels. We can expand the qubit abstraction of |0〉 and |1〉 to a ququart which has access to the |2〉 and |3〉 state, but with shorter coherence times. This allows for two qubits to be encoded in one ququart, enabling increased virtual connectivity between physical units from two adjacent qubits to four fully connected qubits. This connectivity scheme allows us to more efficiently execute three-qubit gates natively between two physical devices.We present direct-to-pulse implementations of several three-qubit gates, synthesized via optimal control, for compilation of three-qubit gates onto a superconducting-based architecture with access to four-level devices with the first experimental demonstration of four-level ququart gates designed through optimal control. We demonstrate strategies that temporarily use higher level states to perform Toffoli gates and always use higher level states to improve fidelities for quantum circuits. We find that these methods improve expected fidelities with increases of 2x across circuit sizes using intermediate encoding, and increases of 3x for fully-encoded ququart compilation.

Litteken, Andrew↗
DOE OSTI2025

Realization and Calibration of Continuously Parameterized Two-Qubit Gates on a Trapped-Ion Quantum Processor

Continuously parameterized two-qubit gates are a key feature of state-of-the-art trapped-ion quantum processors, as they have favorable error scalings and show distinct improvements in circuit performance over more restricted maximally entangling gatesets. In this work, we provide a comprehensive and pedagogical discussion on how to practically implement these continuously parameterized Mølmer–Sørensen gates on the Quantum Scientific Computing Open User Testbed, a low-level trapped-ion processor. To generate the arbitrary entangling angles, θ, we simply scale the amplitude of light used to generate the entanglement. However, doing so requires careful consideration of amplifier saturation as well as the variable light shifts that result. As such, we describe a method to calibrate and cancel the dominant fourth-order effects, followed by a dynamic virtual phase advance during the gate to cancel any residual light shifts, and find a linear scaling between θ and the residual light shift. Once we have considered and calibrated these effects, we demonstrate performance improvement with decreasing θ. Finally, we describe nuances of hardware control to transform the XX-type interaction of the arbitrary-angle Mølmer–Sørensen gate into a phase-agnostic and crosstalk-mitigating ZZ interaction.

Yale, Christopher Gordon [Sandia National Laborato↗
DOE OSTI2025

Investigating parameter trainability in the SNAP-displacement protocol of a qudit system

Here, in this study, we explore the universality of Selective Number-dependent Arbitrary Phase (SNAP) and Displacement gates for quantum control in qudit-based systems. However, optimizing the parameters of these gates poses a challenging task. Our main focus is to investigate the sensitivity of training any of the SNAP parameters in the SNAP-Displacement protocol. We analyze conditions that could potentially lead to the Barren Plateau problem in a qudit system and draw comparisons with multi-qubit systems. The parameterized ansatz we consider consists of blocks, where each block is composed of hardware operations, namely SNAP and Displacement gates [Fösel et al 2020 Efficient cavity control with snap gates arXiv:2004.14256]. Applying Variational Quantum algorithm (VQA) with observable and gate cost functions, we utilize techniques similar to those in [McClean et al 2018 Barren plateaus in quantum neural network training landscapes Nat. Commun.9 1–6] and [Cerezo et al 2021 Cost function dependent barren plateaus in shallow parametrized quantum circuits. Nat. Commun.12 1–12] along with the concept of t − design. Through this analysis, we make the following key observations: (a) The trainability of a SNAP-parameter does not exhibit a preference for any particular direction within our cost function landscape, (b) By leveraging the first and second moments properties of Haar measures, we establish new lemmas concerning the expectation of certain polynomial functions, and (c) utilizing these new lemmas, we identify a general condition that indicates an expected trainability advantage in a qudit system when compared to multi-qubit systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Hardware-Efficient Microwave-Activated Tunable Coupling between Superconducting Qubits

Generating high-fidelity, tunable entanglement between qubits is crucial for realizing gate-based quantum computation. In superconducting circuits, tunable interactions are often implemented using flux-tunable qubits or coupling elements, adding control complexity and noise sources. Here, we realize a tunable $ZZ$ interaction between two transmon qubits with fixed frequencies and fixed coupling, induced by driving both transmons off-resonantly. We show tunable coupling over one order of magnitude larger than the static coupling, and change the sign of the interaction, enabling cancellation of the idle coupling. Further, this interaction is amenable to large quantum processors: the drive frequency can be flexibly chosen to avoid spurious transitions, and because both transmons are driven, it is resilient to microwave crosstalk. We apply this interaction to implement a controlled phase (CZ) gate with a gate fidelity of $99.43(1)\%$ as measured by cycle benchmarking, and we observe the fidelity is limited by incoherent errors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Crystalline materials for quantum computing: Semiconductor heterostructures and topological insulators exemplars

Abstract High-purity crystalline solid-state materials play an essential role in various technologies for quantum information processing, from qubits based on spins to topological states. New and improved crystalline materials emerge each year and continue to drive new results in experimental quantum science. This article summarizes the opportunities for a selected class of crystalline materials for qubit technologies based on spins and topological states and the challenges associated with their fabrication. We start by describing semiconductor heterostructures for spin qubits in gate-defined quantum dots and benchmark GaAs, Si, and Ge, the three platforms that demonstrated two-qubit logic. We then examine novel topologically nontrivial materials and structures that might be incorporated into superconducting devices to create topological qubits. We review topological insulator thin films and move onto topological crystalline materials, such as PbSnTe, and its integration with Josephson junctions. We discuss advances in novel and specialized fabrication and characterization techniques to enable these. We conclude by identifying the most promising directions where advances in these material systems will enable progress in qubit technology.

Scappucci, G. (ORCID:0000000325120079)↗
DOE OSTI2022

Engineering, Control, and Longitudinal Readout of Floquet Qubits

We discuss how properties of time-periodic Hamiltonians can be exploited to increase the dephasing time of qubits and to design protected one- and two-qubit gates. Recently, Huang et al. [Phys. Rev. Applied 15, 034065 (2021)] have shown that Floquet states offer a manifold of working points with dynamical protection larger than the few, usual, static sweet spots. Here, we show how Floquet theory, often used on systems with a single drive tone, can be used to describe approaches to robustly control Floquet qubits in the presence of multiple commensurate drive tones. Using this formulation, we introduce a longitudinal readout protocol to measure the Floquet qubit without the need of first adiabatically mapping the Floquet states back to the static qubit states, resulting in a significant speedup in the measurement time of the Floquet qubit. The analytical approach developed here can be applied to any Hamiltonian involving a small number of distinct drive tones, typical in the study of standard parametric gates for qubits outside of the rotating-wave approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗