Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Quadrature”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Disorder-induced local strain distribution in Y-substituted TmVO 4

We report an investigation of the effect of substitution of Y for Tm in Tm 1-x ⁢Y x VO 4 via low-temperature heat capacity measurements, with the yttrium content x varying from 0 to 0.997. Because the Tm ions support a local quadrupolar (nematic) moment, they act as reporters of the local strain state in the material, with the splitting of the ion's non-Kramers crystal field ground state proportional to the quadrature sum of the in-plane tetragonal symmetry-breaking transverse and longitudinal strains experienced by each ion individually. Analysis of the heat capacity, therefore, provides detailed insights into the distribution of local strains that arise as a consequence of the chemical substitution. These local strains suppress long-range quadrupole order for x > 0.22, and result in a broad Schottky-like feature for higher concentrations. Heat capacity data are compared to expectations for a distribution of uncorrelated (random) strains. For dilute Tm concentrations, the heat capacity cannot be accounted for by randomly distributed strains, demonstrating the presence of significant strain correlations between sites. For intermediate Tm concentrations, these correlations must still exist, but the data cannot be distinguished from that which would be obtained from a two-dimensional Gaussian distribution. The crossover between these limits is discussed in terms of the interplay of key lengthscales in the substituted material. Furthermore, the central result of this work, namely that local strains arising from chemical substitution are not uncorrelated, has implications for the range of validity of theoretical models based on random effective fields that are used to describe such chemically substituted materials, particularly when electronic nematic correlations are present.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Calibrating two jets at once

Jet-energy calibration is an important aspect of many measurements and searches at the LHC. Currently, these calibrations are performed on a per-jet basis, i.e., agnostic to the properties of other jets in the same event. In this work, we propose taking advantage of the correlations induced by momentum conservation between jets in order to improve their jet-energy calibration. By fitting the p T asymmetry of dijet events in simulation, while remaining agnostic to the p T spectra themselves, we are able to obtain correlation-improved maximum likelihood estimates. This approach is demonstrated with simulated jets from the CMS detector, yielding a 3%–5% relative improvement in the jet-energy resolution, corresponding to a quadrature improvement of approximately 35%. Published by the American Physical Society 2024

Gambhir, Rikab (ORCID:0000000251080448)↗
DOE OSTI2024

SPT clusters with DES and HST weak lensing. I. Cluster lensing and Bayesian population modeling of multiwavelength cluster datasets

We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1% at z = 0.25 to 10% at z = 0.95 , to which we add 2% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multiobservable likelihood for the Sunyaev-Zel’dovich effect, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol ECS, and SPTpol 500d surveys and the DES Year 3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Steepest-descent algorithm for simulating plasma-wave caustics via metaplectic geometrical optics

The design and optimization of radiofrequency-wave systems for fusion applications is often performed using ray-tracing codes, which rely on the geometrical-optics (GO) approximation. However, GO fails at wave cutoffs and caustics. To accurately model the wave behavior in these regions, more advanced and computationally expensive “full-wave” simulations are typically used, but this is not strictly necessary. A new generalized formulation called metaplectic geometrical optics (MGO) has been proposed that reinstates GO near caustics. The MGO framework yields an integral representation of the wavefield that must be evaluated numerically in general. We present an algorithm for computing these integrals using Gauss-Freud quadrature along the steepest-descent contours. Benchmarking is performed on the standard Airy problem, for which the exact solution is known analytically. Furthermore, the numerical MGO solution provided by the new algorithm agrees remarkably well with the exact solution and significantly improves on previously derived analytical approximations of the MGO integral.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Properties of carbon up to 10 million kelvin from Kohn-Sham density functional theory molecular dynamics

Accurately modeling dense plasmas over wide-ranging conditions of pressure and temperature is a grand challenge critically important to our understanding of stellar and planetary physics as well as inertial confinement fusion. In this work, we employ Kohn-Sham density functional theory (DFT) molecular dynamics (MD) to compute the properties of carbon at warm and hot dense matter conditions in the vicinity of the principal Hugoniot. In particular, we calculate the equation of state (EOS), Hugoniot, pair distribution functions, and diffusion coefficients for carbon at densities spanning 8 g/$\mathrm{cm^3}$ to 16 g/$\mathrm{cm^3}$ and temperatures ranging from 100 kK to 10 MK using the Spectral Quadrature method. Here, we find that the computed EOS and Hugoniot are in good agreement with path integral Monte Carlo results and the sesame database. Additionally, we calculate the ion-ion structure factor and viscosity for selected points. All results presented are at the level of full Kohn-Sham DFT-MD, free of empirical parameters, average-atom, and orbital-free approximations employed previously at such conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Producing entangled photon pairs and quantum squeezed states in plasmas

Plasma is capable of mediating the conversion of two pump photons into two different photons through a relativistic four-wave mixing nonlinearity. Spontaneously created photon pairs are emitted at symmetric angles with respect to the colinear pump direction, and the emission rate is largest if they have identical frequency. Thus, two orthogonally polarized pumps can produce polarization-entangled photon pairs through a millimeter-long homogeneous plasma. Here, the noise from Raman scattering can be avoided if the pump detuning differs from twice the plasma frequency. However, pump detuning exactly equal to twice the plasma frequency can significantly enhance the interaction rate, which allows for the production of strong two-mode squeezed states. Remarkably, the amplified noise from Raman scattering are correlated and hence can be suppressed in one of the output quadratures, thereby maintaining the squeezing magnitude.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Encoding an Oscillator into Many Oscillators

An outstanding challenge for quantum information processing using bosonic systems is Gaussian errors such as excitation loss and added thermal noise errors. Thus, bosonic quantum error correction is essential. Most bosonic quantum error correction schemes encode a finite-dimensional logical qubit or qudit into noisy bosonic oscillator modes. In this case, however, the infinite-dimensional bosonic nature of the physical system is lost at the error-corrected logical level. On the other hand, there are several proposals for encoding an oscillator mode into many noisy oscillator modes. However, these oscillator-into-oscillators encoding schemes are in the class of Gaussian quantum error correction. Therefore, these codes cannot correct practically relevant Gaussian errors due to the established no-go theorems that state that Gaussian errors cannot be corrected by using only Gaussian resources. Here, we circumvent these no-go results and show that it is possible to correct Gaussian errors by using Gottesman-Kitaev-Preskill (GKP) states as non-Gaussian resources. In particular, we propose a non-Gaussian oscillator-into-oscillators code, namely the GKP two-mode squeezing code, and demonstrate that it can quadratically suppress additive Gaussian noise errors in both the position and momentum quadratures except for a small sublogarithmic correction. Furthermore, we demonstrate that our GKP two-mode squeezing code is near optimal in the weak noise limit by proving via quantum information theoretic tools that quadratic noise suppression is optimal when we use two physical oscillator modes. Lastly, in this work we show that our non-Gaussian oscillator encoding scheme can also be used to correct excitation loss and thermal noise errors, which are dominant error sources in many realistic bosonic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Bosonic Pair Production and Squeezing for Optical Phase Measurements in Long-Lived Dipoles Coupled to a Cavity

Here, we propose to simulate bosonic pair creation using large arrays of long-lived dipoles with multilevel internal structure coupled to an undriven optical cavity. Entanglement between the atoms, generated by the exchange of virtual photons through a common cavity mode, grows exponentially fast and is described by two-mode squeezing of effective bosonic quadratures. The mapping between an effective bosonic model and the natural spin description of the dipoles allows us to realize the analog of optical homodyne measurements via straightforward global rotations and population measurements of the electronic states, and we propose to exploit this for quantum-enhanced sensing of an optical phase (common and differential between two ensembles). We discuss a specific implementation based on Sr atoms and show that our sensing protocol is robust to sources of decoherence intrinsic to cavity platforms. Our proposal can open unique opportunities for next-generation optical atomic clocks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Gate-Based Quantum Simulation of Gaussian Bosonic Circuits on Exponentially Many Modes

We introduce a framework for simulating, on an ( n + 1 )-qubit quantum computer, the action of a Gaussian bosonic (GB) circuit on a state over 2 n modes. Specifically, we encode the initial bosonic state’s expectation values over quadrature operators (and their covariance matrix) as an input qubit state. This is then evolved by a quantum circuit that effectively implements the symplectic propagators induced by the GB gates. We find families of GB circuits and initial states leading to efficient quantum simulations. For this purpose, we introduce a dictionary that maps between GB and qubit gates such that particle- (non-particle-) preserving GB gates lead to real- (imaginary-) time evolutions at the qubit level. For the special case of particle-preserving circuits, we present a bounded-error-quantum-polynomial time (BQP)-complete GB decision problem, indicating that GB evolutions of Gaussian states on exponentially many modes are as powerful as universal quantum computers. We also perform numerical simulations of an interferometer on ∼ 8 × 10 9 modes, illustrating the power of our framework. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Qubit-Oscillator Concatenated Codes: Decoding Formalism and Code Comparison

Concatenating bosonic error-correcting codes with qubit codes can substantially boost the errorcorrecting power of the original qubit codes. It is not clear how to concatenate optimally, given that there are several bosonic codes and concatenation schemes to choose from, including the recently discovered Gottesman-Kitaev-Preskill (GKP) – stabilizer codes [Phys. Rev. Lett. 125, 080503 (2020)] that allow protection of a logical bosonic mode from fluctuations of the conjugate variables of the mode. We develop efficient maximum-likelihood decoders for and analyze the performance of three different concatenations of codes taken from the following set: qubit stabilizer codes, analog or Gaussian stabilizer codes, GKP codes, and GKP-stabilizer codes. We benchmark decoder performance against additive Gaussian white noise, corroborating our numerics with analytical calculations. We observe that the concatenation involving GKP-stabilizer codes outperforms the more conventional concatenation of a qubit stabilizer code with a GKP code in some cases. We also propose a GKP-stabilizer code that suppresses fluctuations in both conjugate variables without extra quadrature squeezing and formulate qudit versions of GKP-stabilizer codes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Quantum Sensing of Displacements with Stabilized Gottesman-Kitaev-Preskill States

We demonstrate how recent protocols developed for the stabilization of Gottesman-Kitaev-Preskill states can be used for the estimation of two-quadrature displacement sensing, with sensitivities approaching the multivariate quantum Cramer-Rao bound. Thanks to the stabilization, this sensor is backaction evading and can function continuously without reset, making it well suited for the detection of itinerant signals. Additionally, we provide numerical simulations showing that the protocol can unconditionally surpass the Gaussian limit of displacement sensing with prior information, even in the presence of realistic noise. Our work shows how reservoir engineering in bosonic systems can be leveraged for quantum metrology, with potential applications in force sensing, waveform estimation, and quantum channel learning.

Labarca, Lautaro [Univ. of Sherbrooke, QC (Canada)↗
DOE OSTI2026

Correlated Noise Estimation with Quantum Sensor Networks

We address the metrological problem of estimating collective stochastic properties imprinted on a network of quantum sensors. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins), bosons, or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and reveal the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and “classical” correlations of the noises. Here, we determine optimal entangled probe states and identify a sensing protocol—reminiscent of a many-body echo—that achieves the fundamental limits of measurement sensitivity for a broad class of problems, unveiling a route toward entanglement-enhanced metrology of correlated many-body phenomena.

Quantum metrology↗
DOE OSTI2020

Dynamic Model of Active Front-End Converters with 2DOF-PI Controllers for DC Bus Voltage Control

In most of the research, a conventional one degree-of-freedom type proportional-integral controller (1DOF-PI) is used for the regulation of the dc bus voltage in an Active Front-End Converter (AFEC). This paper proposes a two degree-of-freedom type proportional-integral controller (2DOF-PI) for the regulation of dc bus voltage in an AFEC. Such a controller eliminates the left-half plane (LHP) zero in the command-to-output transfer function for dc bus voltage regulation that is inherent to the conventional 1DOF-PI for this application. The dynamic model of an AFEC in the synchronous reference frame (SRF) is presented. An inner current control and outer dc voltage control loop is built for controlling the AFEC. Vector-control scheme is employed to achieve decoupled control of direct-axis and quadrature-axis currents. The outer dc voltage control loop is designed with a 2DOF-PI to complete the control system. Transfer function (TF) of the controller is derived based on the presented model and used to calculate the controller gains. Transient and steady state performance of the designed controllers are investigated in MATLAB/Simulink and results presented.

Thapa, Anup↗
DOE OSTI2021

Discriminating Quantum States with Quantum Machine Learning

Quantum machine learning (QML) algorithms have obtained great relevance in the machine learning (ML) field due to the promise of quantum speedups when performing basic linear algebra subroutines (BLAS), a fundamental element in most ML algorithms. By making use of BLAS operations, we propose, implement and analyze a quantum k-means (qk-means) algorithm with a low time complexity of O(NKlog(D)I/C) to apply it to the fundamental problem of discriminating quantum states at readout. Discriminating quantum states allows the identification of quantum states |0⟩ and |1⟩ from low-level in-phase and quadrature signal (IQ) data, and can be done using custom ML models. In order to reduce dependency on a classical computer, we use the qk-means to perform state discrimination on the IBMQ Bogota device and managed to find assignment fidelities of up to 98.7% that were only marginally lower than that of the k-means algorithm. We also performed a cross-talk benchmark on the quantum device by applying both algorithms to perform state discrimination on a combination of quantum states and using Pearson Correlation coefficients and assignment fidelities of discrimination results to conclude on the presence of cross-talk on qubits. Evidence shows cross-talk in the (1, 2) and (2, 3) neighboring qubit couples for the analyzed device.

Quiroga, David↗
DOE OSTI2022

Autonomous Wireless Technology Detection in Seamless IoT Applications

The ever-increasing use of Internet of Things (IoT) devices results in the implementation of multiple wireless technologies that would not only cater their data rate requirements but also support various applications. To optimize the energy efficiency and security of the wireless transmission, it is imperative to identify the wireless technologies in various IoT implementations. Many of the existing approaches are based on measuring only the receiving signal strength indicator (RSSI). However, such approaches may not work well because of transmit power control and complex channel variations among different wireless technologies. In this article, we propose an autonomous wireless detection scheme that considers multiple distinguishable physical (PHY)-layer settings for real-time identification of wireless technologies for real-time applications. Specifically, the proposed scheme relies on the PHY-layer measurements of the targeted spectrum. Transmission settings, such as bandwidth, carrier frequency, and RSSI are estimated from the raw in-phase and quadrature-phase (I/Q) measurements. In addition, a symbol-level extraction scheme is implemented to extract unique features of modulation settings. These aforementioned features are applied to a machine learning process to identify the received wireless technologies. Compared with raw I/Q measurements, the extracted features are much simplified and, thus, the machine learning classifier can be designed with a simple structure for fast processing on IoT nodes. Finally, the proposed schemes are primarily evaluated theoretically, followed by implementing them on a USRP software-defined radio (SDR)-based hardware testbed. The evaluation results demonstrate high accuracy in the real-time detection of different wireless technologies for seamless IoT applications.

42 ENGINEERING↗
DOE OSTI2023

Oscillatory Power Control and Consensus in Unbalanced Networks Using Grid Forming Inverters

In this paper, a state-space nonlinear control previously designed for balanced operation of grid-forming (GFM) inverters is extended to unbalanced operations. Unbalanced voltages and currents are analyzed, and their time-varying direct, quadrature, and zero components are parameterized in terms of six constant parameters. These parameters provide primary control design choices for not only an inverter’s terminal voltage but also its injections of both real and oscillatory power. It is shown that the proposed GFM control can precisely achieve a desired balanced terminal voltage under unbalanced loads. It is also shown that, by allowing the terminal voltage to be slightly unbalanced, oscillatory power can be adaptively minimized. Lastly, it is illustrated that oscillatory power can also be shared among multiple GFM inverters. Case studies and their simulations demonstrate that the proposed GFM control is effective in meeting the aforementioned objectives.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

GPU-Accelerated Analytic Simulation of Sparse Ionization Signal Formation in Pixelated Projection Detector

This paper presents a GPU-accelerated simulation package, TRED, for next-generation neutrino detectors with pixelated charge readout, leveraging community-driven software ecosystems to ensure adaptability and extensibility. We introduce two generic contributions: (i) an effective-charge representation based on Gaussian quadrature rules, in which the linear- interpolation factors for the field response inside each voxel are absorbed into the effective charge, and (ii) a sparse, block- binned tensor representation that enables efficient FFT-based computation of induced signals on readout electrodes for sparsely activated detector volumes. The former captures structure inside a voxel without dense sampling, while the latter achieves low memory usage and scalable runtime, as demonstrated in bench- mark studies. The underlying data representation is applicable to large-scale detectors and to other computational problems involving sparse activity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗