Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “quantum distributed optimization”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Globally optimal interferometry with lossy twin Fock probes

Parity or quadratic spin (e.g., J z 2 ) readouts of a Mach–Zehnder (MZ) interferometer probed with a twin Fock (TF) input state allow saturating the optimal sensitivity attainable among all mode-separable states with a fixed total number of particles but only when the interferometer phase θ is near zero. When more general Dicke state probes are used, the parity readout saturates the quantum Fisher information (QFI) at θ = 0, whereas better-than-standard quantum limit performance of the J z 2 readout is restricted to an o ( N ) occupation imbalance. We show that a method of moments readout of two quadratic spin observables J z 2 and J + 2 + J − 2 is globally optimal for Dicke state probes; i.e., the error saturates the QFI for all θ . In the lossy setting, we derive the time-inhomogeneous Markov process describing the effect of particle loss on TF states, showing that the method of moments readout of four at-most-quadratic spin observables is sufficient for globally optimal estimation of θ when two or more particles are lost. The analysis culminates in a numerical calculation of the QFI matrix for distributed MZ interferometry on the four-mode state | N 4 , N 4 , N 4 , N 4 〉 and its lossy counterparts, showing that an advantage for the estimation of any linear function of the local MZ phases θ 1 and θ 2 (compared to independent probing of the MZ phases by two copies of | N 4 , N 4 〉 ) appears when more than one particle is lost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Quantum metrology timing limits of the Hong-Ou-Mandel interferometer and of general two-photon measurements

We examine the precision limits of Hong-Ou-Mandel (HOM) timing measurements, as well as precision limits applying to generalized two-photon measurements. As a special case, we consider the use of two-photon measurements using photons with variable bandwidths and frequency correlations. When the photon bandwidths are not equal, maximizing the measurement precision involves a trade-off between high interference visibility and strong frequency anticorrelations, with the optimal precision occurring when the photons share non-maximal frequency anticorrelations. We show that a generalized measurement has precision limits that are qualitatively similar to those of the HOM measurement whenever the generalized measurement is insensitive to the net delay of both photons. Finally, by examining the performance of states with more general frequency distributions, our analysis allows for engineering of the joint spectral amplitude for use in realistic situations, in which both photons may not have ideal spectral properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

CRADA Number NFE-24-10110 with Qubit Engineering Inc. (CRADA Final Report)

Over the past year, the Qubit Engineering team has pushed the frontiers of power‑grid optimization, working in close collaboration with Oak Ridge National Laboratory (ORNL) and the Tennessee Valley Authority (TVA). Their progress is reflected in three newly submitted conference papers, “Unified Relational GNN Architecture for AC Optimal Power Flow Calculations in Electric Grids,” “Graph‑Based Attention Mechanisms for Solving the AC Optimal Power Flow Problem in Electrical‑Power Networks,” and “Enhanced Power‑Grid Maintenance Planning and Quantum‑Inspired Combinatorial Prospects.” These publications showcase state‑of‑the‑art graph‑neural‑network methods for AC‑OPF and novel quantum‑inspired heuristics for maintenance scheduling. Beyond the academic results, the Qubit team has converted the research into two production‑grade tools built on TVA data: Neuro‑Grid, an AI‑driven power‑flow simulator that provides instant, interactive full‑grid load‑flow visualizations, and Quanta‑Grid, a quantum‑inspired maintenance‑scheduling engine to support logistics optimization for power utilities. Together, these advances demonstrate how Qubit’s partnership with ORNL and TVA is delivering practical, physics‑grounded analytics for next‑generation grid management.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

High-intensity polarized electron gun featuring distributed Bragg reflector GaAs photocathode

The polarized electron source is a critical component in accelerator facilities such as the electron–ion collider, which requires a polarized electron gun with higher voltage and higher bunch charge than existing sources. One challenge we faced was the surface charge limit of the distributed Bragg reflector GaAs/GaAsP superlattice (DBR-SL-GaAs) photocathode. We suppressed this effect by optimizing the surface doping and heat cleaning procedures. We achieved up to 11.6 nC bunch charge of polarized electron beam. In this report, we discuss the performance of tests of a DBR-SL-GaAs photocathode in the high voltage direct current gun. Possible reasons for the observed peak quantum efficiency wavelength shift are analyzed, and we addressed it by using a wavelength tunable laser. In addition, the impact of the DBR layer and laser on the lifetime is investigated in this paper. The optimal DBR-SL-GaAs operating zone has been proposed, which gave us a long lifetime and high polarization at 30 μA operation. Finally, the success of this polarized gun will be key to the future of the nuclear sciences.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Enhanced quantum state transfer by circumventing quantum chaotic behavior

The ability to realize high-fidelity quantum communication is one of the many facets required to build generic quantum computing devices. In addition to quantum processing, sensing, and storage, transferring the resulting quantum states demands a careful design that finds no parallel in classical communication. Existing experimental demonstrations of quantum information transfer in solid-state quantum systems are largely confined to small chains with few qubits, often relying upon non-generic schemes. Here, by using a superconducting quantum circuit featuring thirty-six tunable qubits, accompanied by general optimization procedures deeply rooted in overcoming quantum chaotic behavior, we demonstrate a scalable protocol for transferring few-particle quantum states in a two-dimensional quantum network. These include single-qubit excitation, two-qubit entangled states, and two excitations for which many-body effects are present. Our approach, combined with the quantum circuit’s versatility, paves the way to short-distance quantum communication for connecting distributed quantum processors or registers, even if hampered by inherent imperfections in actual quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Active learning enables generation of molecules that advance the known Pareto front

Although generative models hold promise for discovering molecules with optimized desired properties, they often fail to suggest synthesizable molecules that improve upon the properties of the structures represented in the training distribution. We find that this limitation arises not only from the molecule generation process itself, but also from the poor generalization capabilities of molecular property predictors. We address this challenge by creating a closed-loop molecule generation pipeline with iterative retraining on new quantum chemical simulation data. Compared against static, single-pass generative modeling approaches, only our closed-loop iterative workflow generates molecules with properties extending beyond the training distribution (up to 0.44 standard deviations beyond the original range) and achieves a 79% improvement in out-of-distribution molecule classification accuracy. Furthermore, by conditioning molecular generation on thermodynamic stability data obtained during the iterative loop, the proportion of stable and hence potentially synthesizable molecules generated is 3.5x higher than the next-best model.

Chemistry↗
DOE OSTI2020

Virtualized Logical Qubits: A 2.5D Architecture for Error-Corrected Quantum Computing

Current, near-term quantum devices have shown great progress in the last several years culminating recently with a demonstration of quantum supremacy. In the medium-term, however, quantum machines will need to transition to greater reliability through error correction, likely through promising techniques like surface codes which are well suited for near-term devices with limited qubit connectivity. We discover quantum memory, particularly resonant cavities with transmon qubits arranged in a 2.5D architecture, can efficiently implement surface codes with substantial hardware savings and performance/fidelity gains. Specifically, we virtualize logical qubits by storing them in layers of qubit memories connected to each transmon. Surprisingly, distributing each logical qubit across many memories has a minimal impact on fault tolerance and results in substantially more efficient operations. Our design permits fast transversal application of CNOT operations between logical qubits sharing the same physical address (same set of cavities) which are 6x faster than standard lattice surgery CNOTs. We develop a novel embedding which saves approximately 10x in transmons with another 2x savings from an additional optimization for compactness. Although qubit virtualization pays a 10x penalty in serialization, advantages in the transversal CNOT and in area efficiency result in fault-tolerance and performance comparable to conventional 2D transmon-only architectures. Our simulations show our system can achieve fault tolerance comparable to conventional two-dimensional grids while saving substantial hardware. Furthermore, our architecture can produce magic states at 1.22x the baseline rate given a fixed number of transmon qubits. Here, this is a critical benchmark for future fault-tolerant quantum computers as magic states are essential and machines will spend the majority of their resources continuously producing them. This architecture substantially reduces the hardware requirements for fault-tolerant quantum computing and puts within reach a proof-of-concept experimental demonstration of around 10 logical qubits, requiring only 11 transmons and 9 attached cavities in total.

quantum computing↗
DOE OSTI2025

Design and Optimization of a Hybrid Design for Quantum Transduction

This study presents the mechanical design and analysis of a quantum electro-optical transducer engineered to operate at millikelvin temperatures within a dilution refrigerator. The transducer enables bidirectional microwave-optical frequency conversion through a hybrid architecture that integrates a superconducting radiofrequency (SRF) cavity with an electro-optic optical cavity. Among several design options investigated, the configuration offering the best thermal and mechanical performance was selected, yielding a robust solution with reduced sensitivity to fabrication tolerances, improved heat dissipation, as well as alignment precision. The design ensures uniform temperature distribution, enabling higher laser pump powers and, thus, increased conversion efficiency, while maintaining mechanical stresses safely below the material yield strength. Electromagnetic simulations further validate the design, demonstrating enhanced coupling between the optical and microwave modes, as well as a broader tuning range achieved with smaller tuner displacements.

quantum computing↗
DOE OSTI2022

ExaTN: Scalable GPU-Accelerated High-Performance Processing of General Tensor Networks at Exascale

We present ExaTN (Exascale Tensor Networks), a scalable GPU-accelerated C++ library which can express and process tensor networks on shared- as well as distributed-memory high-performance computing platforms, including those equipped with GPU accelerators. Specifically, ExaTN provides the ability to build, transform, and numerically evaluate tensor networks with arbitrary graph structures and complexity. It also provides algorithmic primitives for the optimization of tensor factors inside a given tensor network in order to find an extremum of a chosen tensor network functional, which is one of the key numerical procedures in quantum many-body theory and quantum-inspired machine learning. Numerical primitives exposed by ExaTN provide the foundation for composing rather complex tensor network algorithms. We enumerate multiple application domains which can benefit from the capabilities of our library, including condensed matter physics, quantum chemistry, quantum circuit simulations, as well as quantum and classical machine learning, for some of which we provide preliminary demonstrations and performance benchmarks just to emphasize a broad utility of our library.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Optimizing spectral phase transfer in four-wave mixing with gas-filled capillaries

Four-wave mixing (FWM) in gas-filled hollow-core capillaries, a nonlinear optical process that mixes signal and pump photon frequencies to generate idler frequency photons, offers a method for precise spectral phase transfer from signal to idler at ultrashort timescales and extreme powers. However, this regime is challenged by competing linear and nonlinear dynamics, leading to significant trade-offs between spectral phase transfer and conversion efficiency. Our computational investigation focuses on the upconversion of femtosecond pulses from the infrared (IR) to the ultraviolet (UV), a range notoriously difficult to manipulate. We explore an intermediate energy regime that strikes an optimal balance between FWM-mediated phase-transfer fidelity and nonlinear conversion efficiency. By adjusting the energy ratios and spectral phase profiles of the input signal, we achieve conversion efficiencies of approximately 5-15% while maintaining an effective quasi-linear spectral phase transfer. These findings will contribute to establishing first-principles and scaling laws essential for applications such as high-precision imaging, spectroscopy, quantum transduction, and distributed entangled interconnects, facilitating advanced control of ultrafast photonic and electronic wavepackets in quantum materials with unprecedented spatial and temporal precision.

Zhang, Hao↗
DOE OSTI2020

Improving qubit readout with hidden Markov models

We demonstrate the application of pattern recognition algorithms via hidden Markov models (HMM) for qubit readout. This scheme provides a state-path trajectory approach capable of detecting qubit-state transitions and makes for a robust classification scheme with higher starting-state assignment fidelity than when compared to a multivariate Gaussian or a support vector machine scheme. Therefore, the method also eliminates the qubit-dependent readout time optimization requirement in current schemes. Using a HMM state discriminator we estimate fidelities reaching the ideal limit. Unsupervised learning gives access to transition matrix, priors, and IQ distributions, providing a toolbox for studying qubit-state dynamics during strong projective readout.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Development and application of ReaxFF methodology for understanding the chemical dynamics of metal carbonates in aqueous solutions

A new ReaxFF reactive force field has been developed for metal carbonate systems including Na + , Ca 2+ , and Mg 2+ cations and the CO 3 2– anion. This force field is fully transferable with previous ReaxFF water and water/electrolyte descriptions. The Me–O–C (Me = metal) three-body valence angle parameters and Me–C non-reactive parameters of the force field have been optimized against quantum mechanical calculations including equations of state, heats of formation, heats of reaction, angle distortions and vibrational frequencies. The new metal carbonate force field has been validated using molecular dynamics simulations to study the solvation and reactivity of metal and carbonate ions in water at 300 K and 700 K. The coordination radius and self-diffusion coefficient show good consistency with existing experimental and simulation results. The angular distribution analysis explains the structural preference of carbonate ions to form carbonates and bicarbonates, where Na + predominantly forms carbonates due to weaker angular strain, while Ca 2+ and Mg 2+ prefer to form bicarbonate monodentate in nature. Residence time distribution analyses on different systems reveal the role of ions in accelerating and decelerating the dynamics of water and carbonate ions under different thermodynamic conditions. The formation and dissolution of bicarbonates and carbonates in solution were explored on the basis of the protonation capability in different systems. Here, the nucleation phenomenon of metal carbonates at ambient and supercritical conditions is explained from the perspective of cluster formation over time: Ca 2+ ions can form prenucleation clusters at ambient temperature but show saturation with increasing temperature, whereas Na + and Mg 2+ ions show a rapid increase in cluster size and amount upon increasing time and temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Magnetic flux distribution, quasiparticle spectroscopy, and quality factors in Nb films for superconducting qubits

Niobium is a practical material platform for superconducting microwave circuits; however, device-level performance can vary significantly depending on film growth and processing conditions. We compare three epitaxial Nb films grown on $c-$plane sapphire substrates under nominally identical conditions, except for the deposition temperature. To correlate internal quality factors, $Q_{\mathrm {i}}$, with material properties, we combine magneto-optical imaging of magnetic flux distribution with quasiparticle spectroscopy via measurements of the London penetration depth, $λ(T)$. In the low-$Q_{\mathrm i}$ film, there is a lesser ability to screen the magnetic field and an irregular temperature variation of $λ(T)$, implying the existence of localized in-gap states. High $Q_{\mathrm i}$ films show the opposite trend. We conclude that our measurements provide an efficient method for characterizing and optimizing superconducting films for quantum informatics applications.

Datta, Amlan [Ames Lab; Iowa State U.]↗
DOE OSTI2023

Theory of sigma bond resonance in flat boron materials

Abstract In chemistry, theory of aromaticity or π bond resonance plays a central role in intuitively understanding the stability and properties of organic molecules. Here we present an analogue theory for σ bond resonance in flat boron materials, which allows us to determine the distribution of two-center two-electron and three-center two-electron bonds without quantum calculations. Based on this theory, three rules are proposed to draw the Kekulé-like bonding configurations for flat boron materials and to explore their properties intuitively. As an application of the theory, a simple explanation of why neutral borophene with ~1/9 hole has the highest stability and the effect of charge doping on borophene’s optimal hole concentration is provided with the assumption of σ and π orbital occupation balance. Like the aromaticity theory for carbon materials, this theory greatly deepens our understanding on boron materials and paves the way for the rational design of various boron-based materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quandary

Quandary numerically simulates and optimizes the time-evolution of open quantum systems. The underlying dynamics are modelled by Lindblad's master equation, a linear ordinary differential equation (ODE) describing quantum systems interacting with the environment. Quandary solves this ODE numerically by applying a time-stepping integration scheme, and utilizes a gradient-based optimization approach to determine optimal control pulses that drive the quantum system to a desired target state. Two optimization objectives are considered: (a) Unitary gate optimization that finds controls to realize a unitary gate transformation, and (b) optimal reset that aims to drive the quantum system to the ground states. Gradient-based optimization schemes utilizing Petsc's Tao optimization package are applied to generate control pulses that minimize the respective measure. To evaluate the gradient of the objective function, the discrete adjoint method is used while leveraging techniques from Algorithmic Differentiation to produce exact and consistent gradients. To mitigate excessive execution run times, the software can be build together with the XBraid software library which provides a parallelization strategy to distribute the time-evolution of the underlying dynamics onto multiple processor.

Petersson, NilsA.↗
DOE OSTI2024

pnnl/emp-gnn

Efficient Graph Neural Network for Predicting Molecular Properties software can compare the prediction quality with ab initio DFT results reported by the high-performance state-of-theart NWChem quantum chemistry package [1] through Mean Absolute Error (MAE) obtained by the fitting between DFT and model predictions i.e, MPNN [2]. We also demonstrated the performance benefits by grouping large molecules by atom sizes, and executing GNN models on different types of resources. Since the training times depend on the number of atoms, we demonstrate the impact of distributing the workloads on two GPUs with varying capabilities (e.g., NVIDIA A100 vs. GeForce RTX 2080 Ti) to optimize the efficiency. We are at the precipice of broad adoption of GNNs for molecular property prediction tasks; hence, our work is timely by comparing model prediction against classical approaches with the intent of providing initial screening for specific classes of molecules.

Lee, Hyungro↗
DOE OSTI2022

Spectral Filtering Induced by Non-Hermitian Evolution with Balanced Gain and Loss: Enhancing Quantum Chaos

Here, the dynamical signatures of quantum chaos in an isolated system are captured by the spectral form factor, which exhibits as a function of time a dip, a ramp, and a plateau, with the ramp being governed by the correlations in the level spacing distribution. While decoherence generally suppresses these dynamical signatures, the nonlinear non-Hermitian evolution with balanced gain and loss (BGL) in an energy-dephasing scenario can enhance manifestations of quantum chaos. In the Sachdev-Ye-Kitaev model and random matrix Hamiltonians, BGL increases the span of the ramp, lowering the dip as well as the value of the plateau, providing an experimentally realizable physical mechanism for spectral filtering. The chaos enhancement due to BGL is optimal over a family of filter functions that can be engineered with fluctuating Hamiltonians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Scaling of silicon nanoparticle growth in low temperature flowing plasmas

Low temperature plasmas are an emerging method to synthesize high quality nanoparticles (NPs). An established and successful technique to produce NPs is using a capacitively coupled plasma (CCP) in cylindrical geometry. Although a robust synthesis technique, optimizing or specifying NP properties using CCPs, is challenging. In this paper, results from a computational investigation for the growth of silicon NPs in flowing inductively coupled plasmas (ICPs) using Ar/SiH 4 gas mixtures of up to a few Torr are discussed. ICPs produce more locally constrained and quiescent plasma potentials. These positive plasma potentials produce an electrostatic trap for negatively charged NPs, which can significantly extend the residence time of NPs in the plasma, which in turn provides a controllable period for particle growth. The computational platforms used in this study consist of a two-dimensional plasma hydrodynamics model, a three-dimensional nanoparticle growth and trajectory tracking model, and a molecular dynamics simulation for deriving reactive sticking coefficients of silane radicals on Si NPs. Trends for the nanoparticle growth as a function of SiH 4 inlet fraction, gas residence time, energy deposition per particle, pressure, and reactor diameter are discussed. The general path for particle synthesis is the trapping of small NPs in the positive electrostatic potential, followed by entrainment in the gas flow upon reaching a critical particle size. Optimizing or controlling NP synthesis then depends on the spatial distribution of plasma potential, the density of growth species, and the relative time that particles spend in the electrostatic trap and flowing through higher densities of growth species upon leaving the trap.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗