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At least 37 records · Page 2

Motional Squeezing for Trapped Ion Transport and Separation

Transport, separation, and merging of trapped ion crystals are essential operations for most large-scale quantum computing architectures. In this Letter, we develop a theoretical framework that describes the dynamics of ions in time-varying potentials with a motional squeeze operator, followed by a motional displacement operator. Using this framework, we develop a new, general protocol for trapped ion transport, separation, and merging. We show that motional squeezing can prepare an ion wave packet to enable transfer from the ground state of one trapping potential to another. Here, the framework and protocol are applicable if the potential is harmonic over the extent of the ion wave packets at all times. As illustrations, we discuss two specific operations: changing the strength of the confining potential for a single ion and separating same-species ions with their mutual Coulomb force. Both of these operations are, ideally, free of residual motional excitation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sparse non-Markovian Noise Modeling of Transmon-Based Multi-Qubit Operations

The influence of noise on quantum dynamics is one of the main factors preventing current quantum processors from performing accurate quantum computations. Sufficient noise characterization and modeling can provide key insights into the effect of noise on quantum algorithms and inform the design of targeted error protection protocols. However, constructing effective noise models that are sparse in model parameters, yet predictive can be challenging. In this work, we present an approach for effective noise modeling of multi-qubit operations on transmon-based devices. Through a comprehensive characterization of seven devices offered by the IBM Quantum Platform, we show that the model can capture and predict a wide range of single- and two-qubit behaviors, including non-Markovian effects resulting from spatiotemporally correlated noise sources. The model’s predictive power is further highlighted through multi-qubit dynamical decoupling demonstrations and an implementation of the variational quantum eigensolver. As a training proxy for the hardware, we show that the model can predict expectation values within a relative error of 0.5%; this is a sevenfold improvement over default hardware noise models. Through these demonstrations, we highlight key error sources in superconducting qubits and illustrate the utility of reduced noise models for predicting hardware dynamics.

open quantum systems & decoherence↗

Characterization of dot-specific and tunable effective g factors in a GaAs/AlGaAs double quantum dot single-hole device

Difference in g factors in multidot structures can form the basis of dot-selective spin manipulation under global microwave irradiation. Here employing electric dipole spin resonance facilitated by strong spin-orbit interaction (SOI), we observe differences in the extracted values of the single-hole effective g factors of the constituent quantum dots of a GaAs/AlGaAs double quantum dot device at the level of ~ 5 %–10%. We examine the continuous change in the hole g factor with electrical detuning over a wide range of interdot tunnel couplings and for different out-of-plane magnetic fields. The observed tendency of the quantum dot effective g factors to steadily increase on decreasing the interdot coupling or on increasing the magnetic field is attributed to the impact on the SOI of changing the dot confinement potential and heavy-hole light-hole mixing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Robust qubit interactions mediated by photonic topological edge states

Here, we investigate the coupling of two spatially separated qubits via topologically protected edge states in a two-dimensional Hofstadter lattice. In this hybrid platform, the qubits are coupled to distinct edge sites of the lattice, enabling long-range interactions mediated by topological edge modes. We solve the full system Hamiltonian and analyze the resulting eigenstate structure to uncover the conditions under which coherent qubit interactions emerge. Our analysis reveals that the effective coupling is highly sensitive to the qubit placement, energy detuning, and the topological character of the edge spectrum. We obtain an analytical solution that goes beyond the perturbative regime, capturing the full interplay between the qubits and edge modes. These results provide a foundation for exploring information transport and many-body effects in engineered quantum systems where interactions are mediated by topological edge modes.

Chern insulators↗

Neural-Network Inverse Design of SRF Cavities and Transmons for Bosonic Quantum Computation

Three-dimensional superconducting radio-frequency (SRF) cavities provide exceptionally long-lived electromagnetic modes and, when coupled to nonlinear elements such as transmon qubits, become promising architectures for bosonic quantum information processing. The inverse design of such systems, i.e., recovering device geometries that produce specified electromagnetic and coupling targets, is generally a one-to-many problem. The qubit-cavity coupling strength depends sensitively on both the transmon geometry and its position within the cavity's electromagnetic field. As these systems scale up and their design parameter spaces grow, the cost of conventional iterative simulation becomes prohibitive. We present two deep neural network (DNN) approaches that address this inverse-design problem at complementary levels of the design stack. The first proposes SRF cavity geometries that produce target cavity observables. The second proposes transmon qubit designs that produce target qubit-cavity parameters - the coupling rate, qubit frequency, and anharmonicity $(g, ν_q, α)$. The recovered candidate designs match the targets to within ~5% (cavity) and ~2% (transmon), confirmed by end-to-end re-simulation. Both approaches map desired device behavior directly to candidate designs, a fast alternative to the iterative simulation studies usually required.

Yaker, Joseph [Fermilab; Northwestern U.]↗

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗

A Compact Monolithic Electro-Optic Package for Quantum Microwave-to-Optical Transduction

We present a novel quantum transduction package that integrates a macroscopic electro-optic crystal into a compact, monolithic assembly designed for superconducting quantum processors. The device provides an efficient and scalable interface between microwave and optical domains while preserving cryogenic compatibility. We performed full-wave and quantum dynamical simulations to assess the performance of the hybrid system, focusing on the interaction between a transmon-based microwave cavity and the crystal’s and cavity low-frequency microwave mode. The transmon operates both as an ancilla for the QPU and as a nonlinear element enabling four-wave mixing between cavity and electro-optic crystal microwave fields. Our results indicate that this architecture can coherently mediate quantum information transfer from the cavity to the electro-optic mode, offering a promising platform for on-chip quantum transduction within superconducting quantum networks.

Reineri, Alessandro [Fermilab] (ORCID:000000016175↗

A Compact Monolithic Electro-Optic Package for Quantum Microwave-to-Optical Transduction

We present a novel quantum transduction package that integrates a macroscopic electro-optic crystal into a compact, monolithic assembly designed for superconducting quantum processors. The device provides an efficient and scalable interface between microwave and optical domains while preserving cryogenic compatibility. We performed full-wave and quantum dynamical simulations to assess the performance of the hybrid system, focusing on the interaction between a transmon-based microwave cavity and the crystal’s and cavity low-frequency microwave mode. The transmon operates both as an ancilla for the QPU and as a nonlinear element enabling four-wave mixing between cavity and electro-optic crystal microwave fields. Our results indicate that this architecture can coherently mediate quantum information transfer from the cavity to the electro-optic mode, offering a promising platform for on-chip quantum transduction within superconducting quantum networks.

Reineri, Alessandro [Fermilab] (ORCID:000000016175↗

SWAP Gate between a Majorana Qubit and a Parity-Protected Superconducting Qubit

High fidelity quantum information processing requires a combination of fast gates and long-lived quantum memories. Here, in this Letter, we propose a hybrid architecture, where a parity-protected superconducting qubit is directly coupled to a Majorana qubit, which plays the role of a quantum memory. The superconducting qubit is based upon a π-periodic Josephson junction realized with gate-tunable semiconducting wires, where the tunneling of individual Cooper pairs is suppressed. One of the wires additionally contains four Majorana zero modes that define a qubit. We demonstrate that this enables the implementation of a SWAP gate, allowing for the transduction of quantum information between the topological and conventional qubit. This architecture combines fast gates, which can be realized with the superconducting qubit, with a topologically protected Majorana memory.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Coherence-mediated quantum thermometry in a hybrid circuit quantum electrodynamics architecture

Quantum thermometry plays a critical role in the development of low-temperature sensors and quantum information platforms. Here, in this work, we propose and analyze a hybrid circuit quantum electrodynamics architecture in which a superconducting qubit is dispersively coupled to two distinct bosonic modes: one initialized in a weak coherent state as a phase reference and information buffer and the other coupled to a thermal environment. We show that the qubit serves as a sensitive readout of the probe mode, mapping the interplay between thermal and coherent photon-number fluctuations onto measurable dephasing. This coherence-mediated mechanism enables improved sensitivity to thermal energy fluctuations in the sub-millikelvin regime through Ramsey interferometry. We derive analytic expressions for the probe coherence envelope, compute the quantum Fisher information for temperature estimation, and demonstrate numerically that the presence of a coherent reference enhances the qubit's sensitivity to small changes in thermal photon occupancy. Our results establish a coherence-enabled approach to thermometry and provide a scalable platform for future calorimetric sensing in high-energy physics and quantum metrology.

Zhu, Shaojiang [Fermi National Accelerator Laborat↗

Coherent manipulation of graph states composed of finite-energy Gottesman-Kitaev-Preskill-encoded qubits

Graph states are a central resource in measurement-based quantum information processing. In the photonic qubit architecture based on Gottesman-Kitaev-Preskill (GKP) encoding, the generation of high-fidelity graph states composed of realistic, finite-energy approximate GKP-encoded qubits thus constitutes a key task. We consider the finite-energy approximation of GKP-qubit states given by a coherent superposition of shifted finite-squeezed vacuum states, where the displacements are Gaussian distributed. We present an exact description of graph states composed of such approximate GKP qubits as a coherent superposition of a Gaussian ensemble of randomly displaced ideal GKP-qubit graph states. Using standard Gaussian dynamics, we track the transformation of the covariance matrix and the mean-displacement vector elements of the Gaussian distribution of the ensemble under tools such as GKP-Steane error-correction and fusion operations that can be used to grow large high-fidelity GKP-qubit graph states. The covariance matrix elements capture the noise in the graph state due to the finite-energy approximation of GKP qubits, while the mean displacements relate to the possible absolute shift errors on the individual qubits arising conditionally from the homodyne measurements that are a part of these tools. Our work thus pins down an exact coherent error model for graph states generated from truly finite-energy GKP qubits, which can shed light on their error-correction properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-fidelity entanglement and coherent multi-qubit mapping in an atom array

Neutral atoms in optical tweezer arrays possess broad applicability for quantum technologies, such as computing, analogue simulation and metrology. The atomic species ytterbium-171 is able to host multiple types of qubits, making it a strong candidate for bridging various applications of tweezer arrays. Realizing this potential requires high-fidelity generation and transfer of many-body entanglement between these distinct qubit degrees of freedom. Here, in this study, we demonstrate the creation and coherent mapping of entangled quantum states across multiple qubits in ytterbium-171 tweezer arrays. We map entangled states onto the optical clock qubit from the nuclear spin qubit or the Rydberg qubit. We coherently transfer Z 2 -ordered Greenberger–Horne–Zeilinger states of up to 20 atoms from the interacting Rydberg manifold to the metastable nuclear spin manifold. Furthermore, we find that clock-qubit-based spin detection, when applied to Rydberg and nuclear spin qubits, facilitates atom-loss-detectable qubit measurements and Rydberg decay detection. This enables delayed-erasure detection, yielding an error-detected two-qubit gate fidelity of 99.78(4)% in metastable qubits. These results establish a versatile architecture that advances multiple fields of quantum information science while also establishing bridges between them.

Senoo, Aruku [University of Colorado, Boulder, CO ↗

Epitaxial integration of superconducting nitrides with cubic GaN

Epitaxial combination of transition metal nitrides and group III-nitrides holds significant potential for novel device architectures, given their wide array of properties and similar lattice constants. However, the mixture of hexagonal and cubic crystals limits structural quality and has stymied development. This work will discuss the molecular beam epitaxy synthesis of metastable cubic GaN on 3C-SiC templates and its integration with cubic ZrN and NbN superconductors in single and multilayer heterostructures. The fully cubic nature of GaN and the epitaxial nature of all layers are confirmed via in situ and ex situ techniques. The electrical transport properties of transition metal nitrides on cubic GaN (001) are compared to those grown directly on 3C-SiC (001) and c-plane hexagonal GaN templates. The determination of a similar growth window for cubic wide-bandgap and superconducting metal nitrides creates a platform for new epitaxial device architectures and potential applications in metamaterials, quantum information science, and condensed matter physics.

Condensed matter physics↗

Hybrid Quantum Networks with Discrete Polarizations and Continuous Quadrature Variables

Final Scientific/Technical Report for DOE Project DE-SC0022069. Quantum communication and computation systems have evolved along two largely independent paradigms: discrete-variable (DV) systems that encode information in qubits such as photon polarizations or photon-number states, and continuous-variable (CV) systems that encode information in optical field quadratures. Each approach offers distinct advantages—DVs provide low error rates and compatibility with single-photon platforms, while CVs support deterministic operations and efficient quantum state manipulation. A fundamental challenge for building a scalable Quantum Internet lies in interfacing these two regimes into a unified hybrid architecture that can coherently distribute and process quantum information across heterogeneous quantum nodes. This project aims to develop and demonstrate a hybrid optical quantum network that seamlessly integrates DV and CV systems. Specifically, we investigate a new class of hybrid entanglement between the discrete polarizations of single photons and the continuous quadrature variables of optical cat states, overcoming incompatibilities in existing DV–CV demonstrations. Using this new entanglement resource, the team investigates a multi-node hybrid quantum local area network (Q-LAN) testbed capable of DV–CV entanglement generation, swapping, and distribution across fiber links.

74 ATOMIC AND MOLECULAR PHYSICS↗

Soft syndrome iterative decoding of quantum LDPC codes and hardware architectures

In practical quantum error correction implementations, the measurement of syndrome information is an unreliable step—typically modeled as a binary measurement outcome flipped with some probability. However, the measured syndrome is in fact a discretized value of the continuous voltage or current values obtained in the physical implementation of the syndrome extraction. In this paper, we use this “soft” or analog information to benefit iterative decoders for decoding quantum low-density parity-check (QLDPC) codes. Syndrome-based iterative belief propagation decoders are modified to utilize the soft syndrome to correct both data and syndrome errors simultaneously. We demonstrate the advantages of the proposed scheme not only in terms of comparison of thresholds and logical error rates for quasi-cyclic lifted-product QLDPC code families but also with faster convergence of iterative decoders. Additionally, we derive hardware (FPGA) architectures of these soft syndrome decoders and obtain similar performance in terms of error correction to the ideal models even with reduced precision in the soft information. The total latency of the hardware architectures is about 600 ns (for the QLDPC codes considered) in a 20 nm CMOS process FPGA device, and the area overhead is almost constant—less than 50% compared to min-sum decoders with noisy syndromes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗