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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hybrid quantum simulations with qubits and qumodes on trapped-ion platforms

We explore the feasibility of gate-based hybrid quantum computing using both discrete (qubit) and continuous (qumode) variables on trapped-ion platforms. Trapped-ion systems have demonstrated record one- and two-qubit gate fidelities and long qubit coherence times, while qumodes, which can be represented by the collective vibrational modes of the ion chain, have remained relatively unex- plored for their use in computing. Using numerical simulations, we show that high-fidelity hybrid gates and measurement operations can be achieved for existing trapped-ion quantum platforms. As an exemplary application, we consider quantum simulations of the Jaynes-Cummings-Hubbard model, which is given by a one-dimensional chain of interacting spin and boson degrees of free- dom. Using classical simulations, we study its real-time evolution and develop a suitable variational quantum algorithm for ground state preparation. Furthermore, our results motivate further studies of hybrid quantum computing in this context, which may lead to direct applications in condensed matter and fundamental particle and nuclear physics.

Lower-dimensional field theories↗
DOE OSTI2026

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma↗
DOE OSTI2025

Temperature Measurements in Hypersonic Wind Tunnels via Femtosecond Coherent Anti-Stokes Raman Scattering

A femtosecond coherent anti-Stokes Raman scattering (fs CARS) instrument is developed to perform gas-phase thermometry in cold-flow hypersonic wind tunnels. Measurements are reported for Mach 8 and 14 pure-nitrogen flows. The fs CARS instrument includes a 100 fs pump/Stokes pulse and a spectrally narrow probe pulse from a second harmonic bandwidth compressor. Important experimental considerations such as limits on the pump/Stokes pulse energy are discussed. The fs CARS focusing and collimating optics are mounted on a two-axis translation stage system to scan the measurement location during a 30 second wind tunnel run. Single-laser-shot rotational CARS spectra are recorded at the laser repetition rate of 1 kHz in the wind tunnel freestream and near simple cone models. Spectral fitting is used to determine quantitative gas temperatures. Freestream temperatures at Mach 8 and 14 spanned ranges of 40–75 and 35–50 K, respectively, depending on tunnel operating conditions. Temperature variations across the central 100 mm span of the wind tunnel were quantified. Measured temperature jumps across conical bow shocks from various models varied by less than 1% from predicted values. Hypersonic boundary layer measurements were demonstrated. In conclusion, these measurements illustrate the utility and robustness of this instrument for the study of complex fluid flow phenomena in challenging ground test facilities.

Aerodynamics↗
DOE OSTI2024

Search for Heavy Neutral Leptons at the MINER$\nu$A detector

Heavy Neutral Leptons (HNL) are particles hypothesised to provide a mass generation mechanism for the active (observed) neutrino species, which are known to have nonzero mass from the definitive observation of neutrino oscillations. HNL are eigenstates of mass of the order $\mathcal{O}(0.1 − 1\,\,\mathrm{GeV}/c^{2})$, which mix into the active flavour eigenstates through the extended leptonic mixing matrix. Apart from neutrino mass, they could provide a natural dark matter candidate and a mechanism for matter-antimatter asymmetry in the early Universe, giving rise to today’s matter-dominated cosmos. Searches for HNL typically attempt to either confirm the existence of HNL through an excess in data that is most compatible with an HNL hypothesis, or by setting limits on the HNL parameter space $\left(M_{N4}, \left|U_{\alpha 4}\right|^{2}\right)$ in the case of statistically insignificant excess. Such searches are intensifying as part of a global research programme at both colliders and accelerator / atmospheric neutrino experiments. One such setting is the MINER$\nu$A experiment, located in the NuMI beamline at Fermilab. MINER$\nu$A has collected a large amount of data over seven years of operation to measure the cross-sections of neutrino-nucleus interactions necessary to drive systematic uncertainties down, in order for neutrino oscillation experiments to achieve sensitivity to CP violation in the neutrino sector. With the high-energy, high-intensity NuMI beam, and with good timing, position, and angular resolution leading to sensitivity to HNL decays, MINER$\nu$A is fertile ground for an HNL search, which is performed in this thesis. Specifically, a novel, experiment-agnostic and general simulation of HNL production and decay is presented and deployed; this simulation has been incorporated in the ubiquitous GENIE neutrino event generator for use with neutrino experiments in the future. The event selection and background characterisation is discussed in detail, including the primary background coming from charged-current coherent and diffractive pion production from neutrino-nucleus interactions, and constraints on the background using control regions from MINER$\nu$A data are derived. Finally, by means of a fake-data study given a background of $\mathcal{O}(500)$ events, the discovery potential and limit-setting capacity of MINER$\nu$A is demonstrated, and ways to improve this capacity are expounded upon.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Determining the N -Representability of a Reduced Density Matrix via Unitary Evolution and Stochastic Sampling

The N-representability problem consists in determining whether, for a given p-body matrix, there exists at least one N-body density matrix from which the p-body matrix can be obtained by contraction, that is, if the given matrix is a p-body reduced density matrix (p-RDM). The knowledge of all necessary and sufficient conditions for a p-body matrix to be N-representable allows the constrained minimization of a many-body Hamiltonian expectation value with respect to the p-body density matrix and, thus, the determination of its exact ground state. However, the number of constraints that complete the N-representability conditions grows exponentially with system size, and hence, the procedure quickly becomes intractable for practical applications. This work introduces a hybrid quantum-stochastic algorithm to effectively replace the N-representability conditions. The algorithm consists of applying to an initial N-body density matrix a sequence of unitary evolution operators constructed from a stochastic process that successively approaches the reduced state of the density matrix on a p-body subsystem, represented by a p-RDM, to a target p-body matrix, potentially a p-RDM. The generators of the evolution operators follow the well-known adaptive derivative-assembled pseudo-Trotter method (ADAPT), while the stochastic component is implemented by using a simulated annealing process. The resulting algorithm is independent of any underlying Hamiltonian, and it can be used to decide whether a given p-body matrix is N-representable, establishing a criterion to determine its quality and correcting it. We apply the proposed hybrid ADAPT algorithm to alleged reduced density matrices from a quantum chemistry electronic Hamiltonian, from the reduced Bardeen–Cooper–Schrieffer model with constant pairing, and from the Heisenberg XXZ spin model. In all cases, the proposed method behaves as expected for 1-RDMs and 2-RDMs, evolving the initial matrices toward different targets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

ThunderDOEME: A Seismoacoustic Deployment at Langmuir Observatory

This report documents a two-month deployment of seismoacoustic instrumentation at the Langmuir Observatory, located outside Socorro, New Mexico. A total of eleven Fairfield Nodal Seismometers and fifteen GEM infrasound loggers were deployed from June 2 to August 5, 2025. The nodal seismometers recorded data for an average of 34 days, while the GEMs had variable operational durations throughout the deployment period. The primary objective was to capture thunder signals using seismoacoustic instrumentation, contributing to a better understanding of the acoustic and seismic phenomena associated with thunder. Coinciding with this deployment, optical and electric field sensors were present, providing information regarding the timing and location of lightning strikes in the region. Additionally, triggered lightning strikes were conducted, serving as a ground truth for validating the captured thunder signals. Preliminary analysis of the data reveals clear thunder signals in both the seismic and infrasound recordings, with peak frequencies observed across a range of 4 to 40 Hz, depending on the event.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗
DOE OSTI2026

ORCHID: Orchestrated Retrieval-Augmented Classification of High-Risk Property with Intelligent Decision-Making

High-Risk Property (HRP) classification is critical at U.S. Department of Energy (DOE) sites, where inventories include sensitive and often dual-use equipment. Compliance must track evolving rules designated by various export control policies to make transparent and auditable decisions. Traditional expert-only workflows are time-consuming, backlog-prone, and struggle to keep pace with shifting regulatory boundaries. We propose ORCHID, a modular agentic framework for HRP classification that pairs retrieval-augmented generation (RAG) with human oversight to produce policy based outputs that can be audited. Small cooperating agents—retrieval, description refiner, classifier, validator, and feedback logger—coordinate via agent-to-agent messaging and invoke tools through the Model Context Protocol (MCP) for model-agnostic on-premise operation. The interface follows an "Item to Evidence to Decision" loop with step-by-step reasoning, on-policy citations, and append-only audit bundles (run-cards, prompts, evidence). In preliminary tests on real HRP cases, ORCHID improves accuracy and traceability over a non-agentic baseline while deferring uncertain items to Subject Matter Experts (SMEs). The demonstration shows single item submission, grounded citations, SME feedback capture, and exportable audit artifacts—illustrating a practical path to trustworthy LLM assistance in sensitive DOE compliance workflows.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗
DOE OSTI2026

First operation of superconducting quantum bits as particle detectors

Transmon qubits are among the leading technologies for the development of future quantum computers. However these superconducting devices are sensitive to ionizing radiation, which reduces their coherence time and leads to correlated errors. This study represents the first quantitative estimation of cosmic rays and ambient radiation impact on transmon qubits. In the shielded underground facility at the Laboratori Nazionali del Gran Sasso (LNGS), errors induced by the interaction of a radioactive source were reconstructed with an efficiency of about 10%. In contrast, in the unshielded above-ground facility at the Fermi National Accelerator Laboratory (FNAL), cosmic and ambient radiation impacts were detected with an efficiency ranging from 10% to 20% by modifying the acquisition protocol. Lastly, the simultaneous readout of three transmons in coincidence was demonstrated, achieving an event reconstruction efficiency of 90% when the devices were illuminated with an LED.

Bonomo, Camilla [Rome U.; INFN, Rome]↗
DOE OSTI2025

Lattice QCD Calculation of the Subtraction Function in Forward Compton Amplitude

The subtraction function plays a pivotal role in calculations involving the forward Compton amplitude, which is crucial for predicting the Lamb shift in muonic atoms, as well as the proton-neutron mass difference. In this Letter, we present a lattice QCD calculation of the subtraction function using two domain wall fermion gauge ensembles near the physical pion mass. We utilize a recently proposed subtraction point, demonstrating its advantage in mitigating statistical and systematic uncertainties by eliminating the need for ground-state subtraction. Our results reveal significant contributions from N⁢π intermediate states to the subtraction function. Incorporating these contributions, we compute the proton, neutron, and nucleon isovector subtraction functions at photon momentum transfer Q 2 ϵ[0,2] GeV 2 . For the proton subtraction function, we compare our lattice results with chiral perturbation theory prediction at low Q 2 and with the results from the perturbative operator-product expansion at high Q 2 . Finally, using these subtraction functions as input, we determine their contribution to two-photon exchange effects in the Lamb shift and isovector nucleon electromagnetic self-energy.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

(SPT-)LSM theorems from projective non-invertible symmetries

Projective symmetries are ubiquitous in quantum lattice models and can be leveraged to constrain their phase diagram and entanglement structure. In this paper, we investigate the consequences of projective algebras formed by non-invertible symmetries and lattice translations in a generalized 1+1 1 + 1 D quantum XY model based on group-valued qudits. This model is specified by a finite group G G and enjoys a projective \mathsf{Rep}(G)× Z(G) 𝖱 𝖾 𝗉 ( G ) × Z ( G ) and translation symmetry, where symmetry operators obey a projective algebra in the presence of symmetry defects. For invertible symmetries, such projective algebras imply Lieb-Schultz-Mattis (LSM) anomalies. However, this is not generally true for non-invertible symmetries, and we derive a condition on G G for the existence of an LSM anomaly. When this condition is not met, we prove an SPT-LSM theorem: any unique and gapped ground state is necessarily a non-invertible weak symmetry protected topological (SPT) state with non-trivial entanglement, for which we construct an example fixed-point Hamiltonian. The projectivity also affects the dual symmetries after gauging \mathsf{Rep}(G)× Z(G) 𝖱 𝖾 𝗉 ( G ) × Z ( G ) sub-symmetries, giving rise to non-Abelian and non-invertible dipole symmetries, as well as non-invertible translations. We complement our analysis with the SymTFT, where the projectivity causes it to be a topological order non-trivially enriched by translations. Throughout the paper, we develop techniques for gauging \mathsf{Rep}(G) 𝖱 𝖾 𝗉 ( G ) symmetry and inserting its symmetry defects on the lattice, which are applicable to other non-invertible symmetries.

Pace, Salvatore D. (ORCID:0000000306093335)↗
DOE OSTI2026

Polynomial-time preparation of low-temperature Gibbs states for two-dimensional toric code

In this work, we propose a polynomial-time algorithm for preparing the Gibbs state of the two-dimensional toric code Hamiltonian at any temperature, starting from any initial state, significantly improving upon prior estimates that suggested exponential scaling with inverse temperature. We prove that fast mixing at low temperature for the two-dimensional toric code can be achieved by augmenting local jump operators with simple global jump operators, which enable efficient transitions between logical sectors. To establish tight lower bounds on the spectral gap, we introduce a new reduction method that eventually maps the problem to estimating the spectral gap of a perturbed graph Laplacian on a stair graph. Our proof also shows that the Lindblad dynamics with a digitally implemented low-temperature local Davies generator is able to efficiently drive the quantum state toward the ground state manifold.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Applications of Solid-State Transformers for Electric Power Grid HEMP/GMD Resilience

A high-altitude electromagnetic pulse (HEMP) or geomagnetic disturbance (GMD) can disrupt power grids by inducing low-frequency common-mode (CM) currents. When these currents flow through grounded transformers, they can bias the magnetic core, driving it into saturation and reducing performance or damaging equipment. This work presents a solid-state transformer (SST) to replace vulnerable assets and improve grid resilience. The paper reviews half-cycle saturation in conventional transformers, then describes an SST architecture that neutralizes and redirects CM currents during HEMP/GMD events. A prototype SST is built and validated, demonstrating stable CM-disturbance operation and protection of nearby transformers. Finally, large-scale simulations show how coordinated SST deployment mitigates CM disturbances and strengthens overall grid resilience.

four-leg inverter↗
DOE OSTI2026

Integration of GOES Data for Solar Resource Assessment of the Contiguous United States

The National Solar Radiation Database (NSRDB), produced by the National Laboratory of the Rockies (NLR), provides high-resolution solar resource data for the contiguous United States (CONUS) using Geostationary Operational Environmental Satellite (GOES) East and West observations. This study evaluates the integration of multi-satellite data within the GOES-East/West overlap regions, where conventional longitude-based selection methods often produce an artificial boundary seam. Our results demonstrate that an advanced blending algorithm, which incorporates sun-satellite scattering angles and satellite viewing zenith angles, improves NSRDB accuracy and creates a spatially continuous dataset. Validation against ground-based irradiance measurements reveals reductions in both percentage error (PE) and normalized Root Mean Square Error (nRMSE), particularly in the central United States. The dynamical integration of multi-satellite data provides a robust foundation for more precise modeling of solar resource and improved spatiotemporal analysis of solar ramp across the CONUS.

14 SOLAR ENERGY↗
DOE OSTI2026

Atomic-scale imaging and charge state manipulation of NV centers by scanning tunneling microscopy

Nitrogen-vacancy (NV) centers in diamond are among the most promising solid-state qubit candidates, owing to their exceptionally long spin coherence times, efficient spin-photon coupling, room-temperature operation, and steadily advancing fabrication and integration techniques. Despite significant progress in the field, atomic-scale characterization and control of individual NV centers have remained elusive. In this work, we utilize a conductive graphene capping layer to enable direct imaging and manipulation of NV - defects via scanning tunneling microscopy (STM). By investigating over 40 individual NV - centers, we identify their spectroscopic signatures and spatial configurations. Our dI/dV conductance spectra reveal the ground state resonance approximately 300 meV below the Fermi level and density-of-states maps uncover a two-lobed wavefunction aligned along the [111] crystallographic direction. Remarkably, we demonstrate the ability to manipulate the charge state of the NV centers from NV - to NV 0 through STM tip-induced gating. This work represents a significant advance in the atomic-scale imaging, spectroscopic characterization, and charge-state manipulation of NV centers, potentially paving the way for future quantum device development.

Raghavan, Arjun [Univ. of Illinois at Urbana-Champ↗
DOE OSTI2026

Trigonometric continuous-variable gates and hybrid quantum simulations of the sine-Gordon model

Hybrid qubit-qumode quantum computing platforms provide a natural setting for simulating interacting bosonic quantum field theories. However, existing continuous-variable gate constructions rely predominantly on polynomial functions of canonical quadratures. In this work, we introduce a complementary universality paradigm based on trigonometric continuous-variable gates, which enable a Fourier-like representation of bosonic operators and are particularly well suited for periodic and non-perturbative interactions. We present an ancilla-based framework for implementing trigonometric gates with arguments given by arbitrary Hermitian functions of qumode quadratures. The protocol yields unitary gates deterministically, and non-unitary gates through probabilistic post-selection. As a concrete application, we develop a hybrid qubit-qumode quantum simulation of the lattice sine-Gordon model. Using these gates, we prepare ground states via quantum imaginary-time evolution, simulate real-time dynamics, compute time-dependent vertex two-point correlation functions, and extract quantum kink profiles under topological boundary conditions. Our results demonstrate that trigonometric continuous-variable gates provide a physically natural framework for simulating interacting field theories on near-term hybrid quantum hardware, while establishing a parallel route to universality beyond polynomial gate constructions. We expect that the trigonometric gates introduced here to find broader applications, including quantum simulations of condensed matter systems, quantum chemistry, and biological models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

In situ midcircuit qubit measurement and reset in a single-species trapped-ion quantum computing system

We implement in situ midcircuit measurement and reset (MCMR) operations on a full-scale trapped-ion quantum computing system by using metastable qubit states in 171 Yb + ions. We compare two methods for isolating data qubits from measured qubits: one shelves the data qubits into the metastable state and the other drives the measured qubit to the metastable state without disturbing the other qubits. We experimentally demonstrate both methods on a crystal of two 171 Yb + ions using both the 𝑆 1/2 ground-state hyperfine clock qubit and the 𝑆 1/2 −𝐷 3/2 optical qubit. These MCMR methods result in errors on the data qubit of about 2% without degrading the measurement fidelity. With straightforward reductions in laser noise, these errors can be suppressed to less than 0.1%. The demonstrated methods allow MCMR to be performed in a single-species ion chain without shuttling or additional qubit-addressing optics, greatly simplifying the system architecture and allowing straightforward integration with existing trapped-ion quantum computers.

coherent control↗