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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Quantification of Organ Motion During Chemoradiotherapy of Rectal Cancer Using Cone-Beam Computed Tomography

Purpose: There has been no previously published data related to the quantification of rectal motion using cone-beam computed tomography (CBCT) during standard conformal long-course chemoradiotherapy. The purpose of the present study was to quantify the interfractional changes in rectal movement and dimensions and rectal and bladder volume using CBCT and to quantify the bony anatomy displacements to calculate the margins required to account for systematic ({Sigma}) and random ({sigma}) setup errors. Methods and Materials: CBCT images were acquired from 16 patients on the first 3 days of treatment and weekly thereafter. The rectum and bladder were outlined on all CBCT images. The interfraction movement was measured using fixed bony landmarks as references to define the rectal location (upper, mid, and low), The maximal rectal diameter at the three rectal locations was also measured. The bony anatomy displacements were quantified, allowing the calculation of systematic ({Sigma}) and random ({sigma}) setup errors. Results: A total of 123 CBCT data sets were analyzed. Analysis of variance for standard deviation from planning scans showed that rectal anterior and lateral wall movement differed significantly by rectal location. Anterior and lateral rectal wall movements were larger in the mid and upper rectum compared with the low rectum. The posterior rectal wall movement did not change significantly with the rectal location. The rectal diameter changed more in the mid and upper than in the low rectum. No consistent relationship was found between the rectal and bladder volume and time, nor was a significant relationship found between the rectal volume and bladder volume. Conclusions: In the present study, the anterior and lateral rectal movement and rectal diameter were found to change most in the upper rectum, followed by the mid rectum, with the smallest changes seen in the low rectum. Asymmetric margins are warranted to ensure phase 2 coverage.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Estimating uncertainties in statistics computed from direct numerical simulation

Rigorous assessment of uncertainty is crucial to the utility of direct numerical simulation (DNS) results. Uncertainties in the computed statistics arise from two sources: finite statistical sampling and the discretization of the Navier–Stokes equations. Due to the presence of non-trivial sampling error, standard techniques for estimating discretization error (such as Richardson extrapolation) fail or are unreliable. This work provides a systematic and unified approach for estimating these errors. First, a sampling error estimator that accounts for correlation in the input data is developed. Then, this sampling error estimate is used as part of a Bayesian extension of Richardson extrapolation in order to characterize the discretization error. These methods are tested using the Lorenz equations and are shown to perform well. These techniques are then used to investigate the sampling and discretization errors in the DNS of a wall-bounded turbulent flow at Reτ ≈ 180. Both small (Lx/δ × Lz/δ = 4π × 2π) and large (Lx/δ × Lz/δ = 12π × 4π) domain sizes are investigated. For each case, a sequence of meshes was generated by first designing a “nominal” mesh using standard heuristics for wall-bounded simulations. These nominal meshes were then coarsened to generate a sequence of grid resolutions appropriate for the Bayesian Richardson extrapolation method. In addition, the small box case is computationally inexpensive enough to allow simulation on a finer mesh, enabling the results of the extrapolation to be validated in a weak sense. For both cases, it is found that while the sampling uncertainty is large enough to make the order of accuracy difficult to determine, the estimated discretization errors are quite small. This indicates that the commonly used heuristics provide adequate resolution for this class of problems. However, it is also found that, for some quantities, the discretization error is not small relative to sampling error, indicating that the conventional wisdom that sampling error dominates discretization error for this class of simulations needs to be reevaluated.

Oliver, Todd A.↗
DOE OSTI2012

Image-Guided Radiotherapy for Left-Sided Breast Cancer Patients: Geometrical Uncertainty of the Heart

Purpose: To quantify the geometrical uncertainties for the heart during radiotherapy treatment of left-sided breast cancer patients and to determine and validate planning organ at risk volume (PRV) margins. Methods and Materials: Twenty-two patients treated in supine position in 28 fractions with regularly acquired cone-beam computed tomography (CBCT) scans for offline setup correction were included. Retrospectively, the CBCT scans were reconstructed into 10-phase respiration correlated four-dimensional scans. The heart was registered in each breathing phase to the planning CT scan to establish the respiratory heart motion during the CBCT scan ({sigma}{sub resp}). The average of the respiratory motion was calculated as the heart displacement error for a fraction. Subsequently, the systematic ({Sigma}), random ({sigma}), and total random ({sigma}{sub tot}={radical}({sigma}{sup 2}+{sigma}{sub resp}{sup 2})) errors of the heart position were calculated. Based on the errors a PRV margin for the heart was calculated to ensure that the maximum heart dose (D{sub max}) is not underestimated in at least 90% of the cases (M{sub heart} = 1.3{Sigma}-0.5{sigma}{sub tot}). All analysis were performed in left-right (LR), craniocaudal (CC), and anteroposterior (AP) directions with respect to both online and offline bony anatomy setup corrections. The PRV margin was validated by accumulating the dose to the heart based on the heart registrations and comparing the planned PRV D{sub max} to the accumulated heart D{sub max}. Results: For online setup correction, the cardiac geometrical uncertainties and PRV margins were N-Ary-Summation = 2.2/3.2/2.1 mm, {sigma} = 2.1/2.9/1.4 mm, and M{sub heart} = 1.6/2.3/1.3 mm for LR/CC/AP, respectively. For offline setup correction these were N-Ary-Summation = 2.4/3.7/2.2 mm, {sigma} = 2.9/4.1/2.7 mm, and M{sub heart} = 1.6/2.1/1.4 mm. Cardiac motion induced by breathing was {sigma}{sub resp} = 1.4/2.9/1.4 mm for LR/CC/AP. The PRV D{sub max} underestimated the accumulated heart D{sub max} for 9.1% patients using online and 13.6% patients using offline bony anatomy setup correction, which validated that PRV margin size was adequate. Conclusion: Considerable cardiac position variability relative to the bony anatomy was observed in breast cancer patients. A PRV margin can be used during treatment planning to take these uncertainties into account.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Robustness Recipes for Minimax Robust Optimization in Intensity Modulated Proton Therapy for Oropharyngeal Cancer Patients

Purpose: We aimed to derive a “robustness recipe” giving the range robustness (RR) and setup robustness (SR) settings (ie, the error values) that ensure adequate clinical target volume (CTV) coverage in oropharyngeal cancer patients for given gaussian distributions of systematic setup, random setup, and range errors (characterized by standard deviations of Σ, σ, and ρ, respectively) when used in minimax worst-case robust intensity modulated proton therapy (IMPT) optimization. Methods and Materials: For the analysis, contoured computed tomography (CT) scans of 9 unilateral and 9 bilateral patients were used. An IMPT plan was considered robust if, for at least 98% of the simulated fractionated treatments, 98% of the CTV received 95% or more of the prescribed dose. For fast assessment of the CTV coverage for given error distributions (ie, different values of Σ, σ, and ρ), polynomial chaos methods were used. Separate recipes were derived for the unilateral and bilateral cases using one patient from each group, and all 18 patients were included in the validation of the recipes. Results: Treatment plans for bilateral cases are intrinsically more robust than those for unilateral cases. The required RR only depends on the ρ, and SR can be fitted by second-order polynomials in Σ and σ. The formulas for the derived robustness recipes are as follows: Unilateral patients need SR = −0.15Σ{sup 2} + 0.27σ{sup 2} + 1.85Σ − 0.06σ + 1.22 and RR=3% for ρ = 1% and ρ = 2%; bilateral patients need SR = −0.07Σ{sup 2} + 0.19σ{sup 2} + 1.34Σ − 0.07σ + 1.17 and RR=3% and 4% for ρ = 1% and 2%, respectively. For the recipe validation, 2 plans were generated for each of the 18 patients corresponding to Σ = σ = 1.5 mm and ρ = 0% and 2%. Thirty-four plans had adequate CTV coverage in 98% or more of the simulated fractionated treatments; the remaining 2 had adequate coverage in 97.8% and 97.9%. Conclusions: Robustness recipes were derived that can be used in minimax robust optimization of IMPT treatment plans to ensure adequate CTV coverage for oropharyngeal cancer patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Ground state properties of 3d metals from self-consistent GW approach

The self consistent GW approach (scGW) has been applied to calculate the ground state properties (equilibrium Wigner–Seitz radius S WZ and bulk modulus B) of 3d transition metals Sc, Ti, V, Fe, Co, Ni, and Cu. The approach systematically underestimates S WZ with average relative deviation from the experimental data of about 1% and it overestimates the calculated bulk modulus with relative error of about 25%. We show that scGW is superior in accuracy as compared to the local density approximation but it is less accurate than the generalized gradient approach for the materials studied. If compared to the random phase approximation, scGW is slightly less accurate, but its error for 3d metals looks more systematic. Lastly, the systematic nature of the deviation from the experimental data suggests that the next order of the perturbation theory should allow one to reduce the error.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Automated quantum error mitigation based on probabilistic error reduction

Current quantum computers suffer from a level of noise that prohibits extracting useful results directly from longer computations. The figure of merit in many near-term quantum algorithms is an expectation value measured at the end of the computation, which experiences a bias in the presence of hardware noise. A systematic way to remove such bias is probabilistic error cancellation (PEC). PEC requires a full characterization of the noise and introduces a sampling overhead that increases exponentially with circuit depth, prohibiting high-depth circuits at realistic noise levels. Probabilistic error reduction (PER) is a related quantum error mitigation method that systematically reduces the sampling overhead at the cost of reintroducing bias. In combination with zero-noise extrapolation, PER can yield expectation values with an accuracy comparable to PEC.Noise reduction through PER is broadly applicable to near-term algorithms, and the automated implementation of PER is thus desirable for facilitating its widespread use. To this end, we present an automated quantum error mitigation software framework that includes noise tomography and application of PER to user-specified circuits. We provide a multi-platform Python package that implements a recently developed Pauli noise tomography (PNT) technique for learning a sparse Pauli noise model and exploits a Pauli noise scaling method to carry out PER.We also provide software tools that leverage a previously developed toolchain, employing PyGSTi for gate set tomography and providing a functionality to use the software Mitiq for PER and zero-noise extrapolation to obtain error-mitigated expectation values on a user-defined circuit.

McDonough, Benjamin↗
DOE OSTI2022

Comprehensive Basis-Set Testing of Extended Symmetry-Adapted Perturbation Theory and Assessment of Mixed-Basis Combinations to Reduce Cost

Hybrid or “extended” symmetry-adapted perturbation theory (XSAPT) replaces traditional SAPT’s treatment of dispersion with better performing alternatives while at the same time extending two-body (dimer) SAPT to a many-body treatment of polarization using a self-consistent charge embedding procedure. The present work presents a systematic study of how XSAPT interaction energies and energy components converge with respect to the choice of Gaussian basis set. Errors can be reduced in a systematic way using correlation-consistent basis sets, with aug-cc-pVTZ results converged within <0.1 kcal/mol. Similar (if slightly less systematic) behavior is obtained using Karlsruhe basis sets at much lower cost, and we introduce new versions with limited augmentation that are even more efficient. Pople-style basis sets, which are more efficient still, often afford good results if a large number of polarization functions are included. The dispersion models used in XSAPT afford much faster basis-set convergence as compared to the perturbative description of dispersion in conventional SAPT, meaning that “compromise” basis sets (such as jun-cc-pVDZ) are no longer required and benchmark-quality results can be obtained using triple-ζ basis sets. The use of diffuse functions proves to be essential, especially for the description of hydrogen bonds. As a result, the “δ(Hartree–Fock)” correction for high-order induction can be performed in double-ζ basis sets without significant loss of accuracy, leading to a mixed-basis approach that offers 4× speedup over the existing (cubic scaling) XSAPT approach.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Optimized Auxiliary Functions for Robust Mitigation of Finite-Size Errors in Periodic Hybrid Density Functional Theory

When calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a slowly converging quadrature error when approximating an integral in the reciprocal space by a finite sum. The singularity subtraction (SS) method offers a systematic approach for reducing this quadrature error and thus the FSE. Here, in this work, we first investigate the performance of the SS method in the simplest setting, aiming at reducing the FSE in exact exchange calculations by subtracting the Coulomb contribution with a single, adjustable Gaussian auxiliary function. We demonstrate that a simple fitting method can robustly estimate the optimal Gaussian width and leads to rapid convergence toward the TDL. Furthermore, we suggest new forms of the auxiliary function, whose optimal parameters could also be determined through least-squares fitting. For a range of semiconductors and insulators, the proposed auxiliary functions achieve robust, millihartree-level accuracy in hybrid density functional theory calculations, including cases with sparse k-meshes and large basis sets.

Quiton, Stephen Jon [University of California, Ber↗
DOE OSTI2017

Characterizing the impact of model error in hydrologic time series recovery inverse problems

Hydrologic models are commonly over-smoothed relative to reality, owing to computational limitations and to the difficulty of obtaining accurate high-resolution information. When used in an inversion context, such models may introduce systematic biases which cannot be encapsulated by an unbiased “observation noise” term of the type assumed by standard regularization theory and typical Bayesian formulations. Despite its importance, model error is difficult to encapsulate systematically and is often neglected. In this paper, model error is considered for an important class of inverse problems that includes interpretation of hydraulic transients and contaminant source history inference: reconstruction of a time series that has been convolved against a transfer function (i.e., impulse response) that is only approximately known. Using established harmonic theory along with two results established here regarding triangular Toeplitz matrices, upper and lower error bounds are derived for the effect of systematic model error on time series recovery for both well-determined and over-determined inverse problems. It is seen that use of additional measurement locations does not improve expected performance in the face of model error. A Monte Carlo study of a realistic hydraulic reconstruction problem is presented, and the lower error bound is seen informative about expected behavior. Finally, a possible diagnostic criterion for blind transfer function characterization is also uncovered.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Biological consequences of MLC calibration errors in IMRT delivery and QA

Purpose: The purpose of this work is threefold: (1) to explore biological consequences of the multileaf collimator (MLC) calibration errors in intensity modulated radiotherapy (IMRT) of prostate and head and neck cancers, (2) to determine levels of planning target volume (PTV) and normal tissue under- or overdose flagged with clinically used QA action limits, and (3) to provide biologically based input for MLC QA and IMRT QA action limits. Methods: Ten consecutive prostate IMRT cases and ten consecutive head and neck IMRT cases were used. Systematic MLC offsets (i.e., calibration error) were introduced for each control point of the plan separately for X1 and X2 leaf banks. Offsets were from - 2 to 2 mm with a 0.5 mm increment. The modified files were imported into the planning system for forward dose recalculation. The original plan served as the reference. The generalized equivalent uniform dose (gEUD) was used as the biological index for the targets, rectum, parotid glands, brainstem, and spinal cord. Each plan was recalculated on a CT scan of a 27 cm diameter cylindrical phantom with a contoured 0.6 cc ion chamber. Dose to ion chamber and 3D gamma analysis were compared to the reference plan. QA pass criteria: (1) at least 95% of voxels with a dose cutoff of 50% of maximum dose have to pass at 3 mm/3% and (2) dose to chamber within 2% of the reference dose. Results: For prostate cases, differences in PTV and rectum gEUD greater than 2% were identified. However, a larger proportion of plans leading to greater than 2% difference in prostate PTV gEUD passed the ion chamber QA but not 3D gamma QA. A similar trend was found for the rectum gEUD. For head and neck IMRT, the QA pass criteria flagged plans leading to greater than 4% differences in PTV gEUD and greater than 5% differences in the maximum dose to brainstem. If pass criteria were relaxed to 90% for gamma and 3% for ion chamber QA, plans leading to a 5% difference in PTV gEUD and a 5%-8% difference in brainstem maximum dose would likely pass IMRT QA. A larger proportion of head and neck plans with greater than 2% PTV gEUD difference passed 3D gamma QA compared to ion chamber QA. Conclusions: For low modulation plans, there is a better chance to catch MLC calibration errors with 3D gamma QA rather than ion chamber QA. Conversely, for high modulation plans, there is a better chance to catch MLC calibration errors with ion chamber QA rather than with 3D gamma QA. Ion chamber and 3D gamma analysis IMRT QA can detect greater than 2% change in gEUD for PTVs and critical structures for low modulation treatment plans. For high modulation treatment plans, ion chamber and 3D gamma analysis can detect greater than 2% change in gEUD for PTVs and a 5% change in critical structure gEUD since either QA methods passes the QA criteria. For gEUD changes less than those listed above, either QA method has the same proportion of passing rate.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

An Error Analysis Toolkit for Binned Counting Experiments

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Charmed and light pseudoscalar meson decay constants from HISQ simulations

We compute the leptonic decay constants $f_{D^+}$, $f_{D_s}$, and $f_{K^+}$, and the quark-mass ratios $m_c/m_s$ and $m_s/m_l$ in unquenched lattice QCD. We use the MILC highly improved staggered quark (HISQ) ensembles with four dynamical quark flavors. Our primary results are $f_{D^+} = 212.6(0.4)({}^{+1.0}_{-1.2})\ \mathrm{MeV}$, $f_{D_s} = 249.0(0.3)({}^{+1.1}_{-1.5})\ \mathrm{MeV}$, and $f_{D_s}/f_{D^+} = 1.1712(10)({}^{+29}_{-32})$, where the errors are statistical and total systematic, respectively. We also obtain $f_{K^+}/f_{\pi^+} = 1.1956(10)({}^{+26}_{-18})$, updating our previous result, and determine the quark-mass ratios $m_s/m_l = 27.35(5)({}^{+10}_{-7})$ and $m_c/m_s = 11.747(19)({}^{+59}_{-43})$. When combined with experimental measurements of the decay rates, our results lead to precise determinations of the CKM matrix elements $|V_{us}| = 0.22487(51) (29)(20)(5)$, $|V_{cd}|=0.217(1) (5)(1)$ and $|V_{cs}|= 1.010(5)(18)(6)$, where the errors are from this calculation of the decay constants, the uncertainty in the experimental decay rates, structure-dependent electromagnetic corrections, and, in the case of $|V_{us}|$, the uncertainty in $|V_{ud}|$, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey – I: Catalogue preparation and systematic mitigation

ABSTRACT We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z < 3.5, covering an effective area of $4699\, {\rm deg}^{2}$. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for non-linear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Correlation-aware binning for small-angle neutron scattering via Gaussian-process inference

Binning in small-angle neutron scattering (SANS) is typically performed empirically, with fixed parameters chosen for convenience rather than statistical optimality. Such practices often fail to balance statistical precision and spatial resolution, leading to inconsistencies across instruments and datasets. Here we establish a correlation-aware framework that determines the optimal bin width from first principles by extending the classical Freedman–Diaconis (FD) rule to account for inter-bin correlations with a Gaussian process. In this formulation, the scattering intensity is treated as a smooth stochastic field whose statistical coherence is described by a covariance matrix. Analytical expressions of errors derived from this model yield closed-form criteria that separate the total deviation into contributions from counting noise, aliasing distortion and curvature-dependent correlation effects. Expressed in reduced variables, the resulting dimensionless error surface reveals a continuous transition from the uncorrelated FD regime to the correlation-dominated limit, providing a unified description of noise suppression and resolution control. Because the formulation depends only on the profile characteristics of scattering intensity I(Q), specifically its average intensity and first- and second-order derivatives, it applies generally to any SANS measurement regardless of sample, instrument or geometry. Experimental validation using small- and ultra-small-angle neutron scattering data confirms the predicted scaling behavior, demonstrating that correlation-aware inference systematically reduces mean-squared error and enables information-efficient reproducible data reduction across materials and instruments.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2023

Measurements and Model Improvement: Insight into NWP Model Error Using Doppler Lidar and Other WFIP2 Measurement Systems

Abstract Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s −1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement. Significance Statement Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.

Meteorology & Atmospheric Sciences↗
DOE OSTI2017

Quasiparticle and hybrid density functional methods in defect studies: An application to the nitrogen vacancy in GaN

Defects in semiconductors can play a vital role in the performance of electronic devices, with native defects often dominating the electronic properties of the semiconductor. Understanding the relationship between structural defects and electronic function will be central to the design of new high-performance materials. In particular, it is necessary to quantitatively understand the energy and lifetime of electronic states associated with the defect. In this work, we apply first-principles density functional theory (DFT) and many-body perturbation theory within the GW approximation to understand the nature and energy of the defect states associated with a charged nitrogen vacancy on the electronic properties of gallium nitride (GaN), as a model of a well-studied and important wide gap semiconductor grown with defects. We systematically investigate the sources of error associated with the GW approximation and the role of the underlying atomic structure on the predicted defect state energies. Additionally, analysis of the computed electronic density of states (DOS) reveals that there is one occupied defect state 0.2 eV below the valence band maximum and three unoccupied defect states at energy of 0.2–0.4 eV above the conduction band minimum, suggesting that this defect in the +1 charge state will not behave as a carrier trap. Furthermore, we compare the character and energy of the defect state obtained from GW and DFT using the HSE approximate density functional and find excellent agreement. This systematic study provides a more complete understanding of how to obtain quantitative defect energy states in bulk semiconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that near term algorithms can be performed with proximate accuracy (like chemical accuracy for quantum chemistry problems). While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Systematic calibration of an integrated x-ray and optical tomography system for preclinical radiation research

Purpose: The cone beam computed tomography (CBCT) guided small animal radiation research platform (SARRP) has been developed for focal tumor irradiation, allowing laboratory researchers to test basic biological hypotheses that can modify radiotherapy outcomes in ways that were not feasible previously. CBCT provides excellent bone to soft tissue contrast, but is incapable of differentiating tumors from surrounding soft tissue. Bioluminescence tomography (BLT), in contrast, allows direct visualization of even subpalpable tumors and quantitative evaluation of tumor response. Integration of BLT with CBCT offers complementary image information, with CBCT delineating anatomic structures and BLT differentiating luminescent tumors. This study is to develop a systematic method to calibrate an integrated CBCT and BLT imaging system which can be adopted onboard the SARRP to guide focal tumor irradiation. Methods: The integrated imaging system consists of CBCT, diffuse optical tomography (DOT), and BLT. The anatomy acquired from CBCT and optical properties acquired from DOT serve as a priori information for the subsequent BLT reconstruction. Phantoms were designed and procedures were developed to calibrate the CBCT, DOT/BLT, and the entire integrated system. Geometrical calibration was performed to calibrate the CBCT system. Flat field correction was performed to correct the nonuniform response of the optical imaging system. Absolute emittance calibration was performed to convert the camera readout to the emittance at the phantom or animal surface, which enabled the direct reconstruction of the bioluminescence source strength. Phantom and mouse imaging were performed to validate the calibration. Results: All calibration procedures were successfully performed. Both CBCT of a thin wire and a euthanized mouse revealed no spatial artifact, validating the accuracy of the CBCT calibration. The absolute emittance calibration was validated with a 650 nm laser source, resulting in a 3.0% difference between simulated and measured signal. The calibration of the entire system was confirmed through the CBCT and BLT reconstruction of a bioluminescence source placed inside a tissue-simulating optical phantom. Using a spatial region constraint, the source position was reconstructed with less than 1 mm error and the source strength reconstructed with less than 24% error. Conclusions: A practical and systematic method has been developed to calibrate an integrated x-ray and optical tomography imaging system, including the respective CBCT and optical tomography system calibration and the geometrical calibration of the entire system. The method can be modified and adopted to calibrate CBCT and optical tomography systems that are operated independently or hybrid x-ray and optical tomography imaging systems.

60 APPLIED LIFE SCIENCES↗