Search NASASearch

SEARCH · Search NASA

Results for “Quantum Data”

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 37 records · Page 2

Explicit expressions of the potential and its derivatives at the origin in terms of the scattering data

The quantum mechanical theory of scattering of a particle by a spherically symmetrical potential is presented. As in the inverse scattering problem, the input of the calculation is the scattering and bound-state data, and the output is data on the potential. The results discussed are explicit expressions for the values of the potential and its derivatives at the origin in terms of the scattering and boundstate data. Various methods to obtain these results are outlined. The presentation is aimed at introducing these various approaches. The simplest scattering problem (nonrelativistic S-wave scattering on a holomorphic potential without bound states) is used as the basis for discussion, and technicalities are omitted whenever possible without loss of clarity. A complete compilation is given of the results obtained to date in this field, including the treatment of higher partial waves and the Klein-Gordon and Dirac equations.

Calogero, F.

Unified architecture for quantum lookup tables

Quantum access to arbitrary classical data encoded in unitary black-box oracles underlies interesting data-intensive quantum algorithms, such as machine learning or electronic structure simulation. The feasibility of these applications depends crucially on gate-efficient implementations of these oracles, which are commonly some reversible versions of the Boolean circuit for a classical lookup table. Here, we present a general parametrized architecture for quantum circuits implementing a lookup table that encompasses all prior work in realizing a continuum of optimal trade-offs between qubits, non-Clifford gates, and error resilience, up to logarithmic factors. Our architecture assumes only local 2D connectivity, yet recovers results, with the appropriate parameters, polylogarithmic error scaling. We also identify regimes, such as simultaneous sublinear scaling, in all parameters. These results enable tailoring implementations of the commonly used lookup table primitive to any given quantum device with constrained resources.

quantum circuits

Energy and physical resource impacts of quantum computing merit greater attention

Quantum computing research and development is growing worldwide; yet the energy and physical resource demands of future quantum-accelerated data centres are unknown. Planning for quantum computing requires strong collaboration between research communities across engineering, physics, environmental sciences, economics, policy, and energy systems and scenario modelling.

97 MATHEMATICS AND COMPUTING

Measurement of tropospheric 300 nm solar ultraviolet flux for determination of O/1D/ photoproduction rate

The tropospheric importance of the OH radical, and the reaction scheme that leads to its formation, are now being widely investigated. Ozone photolysis at wavelengths no greater than 318 nm produces O(1D), a small fraction of which then reacts with water vapor to yield OH. Although experimental data are available for the O(1D) quantum yield, as well as the O3 absorption cross section, all previous tropospheric photochemical models have had to use theoretical calculations to determine the UV flux. Discussed in this paper are aircraft spectral measurements of the solar UV flux at two altitudes - 2 and 6 km. These results have been compared with three theoretical approaches. The measured experimental fluxes have been combined here with recent quantum yield data to calculate the O(1D) photoproduction rate for various albedo values. This rate is larger than that used in models by about a factor of 2 for reasonable values of assumed albedo.

Sellers, B.

Absorption and photoluminescence of ultrathin pseudomorphic InAs/GaAs quantum wells

Absorption data are presented for 2-4-monolayer InAs/GaAs single quantum wells obtained at 77 K using a polarization-based measurement technique. The special contribution of the optical loss features arising from bulk GaAs was minimized using the polarization selectivity of absorption in single quantum wells. The double structure observed in the spectra is attributed to transitions involving confined heavy holes and both confined and unconfined electron states.

Ksendzov, A.

Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data

This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.

Quantum Computing

Scaling Properties of Algorithms in Nanotechnology

At the present time, several technologies are pressing the limits of microminiature manufacturing. In semiconductor technology, for example, the Intel Pentium Pro (which is used in the Department of Energy's ASCI 'red' parallel supercomputer system) and the DEC Alpha 21164 (which is used in the CRAY T3E) both are fabricated using 0.35 micron process technology. Recently Texas Instruments (TI) announced the availability of 0.25 micron technology chips by the end of 1996 and plans to have 0.18 micron devices in production within two years. However, some significant challenges lie down the road. These include the skyrocketing cost of manufacturing plants, the 0.1 micron foreseeable limit of the photolithography process, quantum effects, data communication bandwidth limitations, heat dissipation, and others. Some related microminiature technologies include micro-electromechanical systems (MEMS), opto-electronic devices, quantum computing, biological computing, and others. All of these technologies require the fabrication of devices whose sizes are approaching the nanometer level. As such they are often collectively referred to with the name 'nanotechnology'. Clearly nanotechnology in this general sense is destined to be a very important technology of the 21st century. The ultimate dream in this arena is 'molecular nanotechnology', in other words the fabrication of devices and materials with most or all atoms and molecules in a pre-programmed position, possibly placed there by 'nano-robots'. This futuristic capability will probably not be achieved for at least two decades. However, it appears that somewhat less ambitious variations of molecular nanotechnology, such as devices and materials based on 'buckyballs' and 'nanotubes' may be realized significantly sooner, possibly within ten years or so. Even at the present time, semiconductor devices are approaching the regime where quantum chemical effects must be considered in design.

Saini, Subhash

Hidden Statistics Approach to Quantum Simulations

Recent advances in quantum information theory have inspired an explosion of interest in new quantum algorithms for solving hard computational (quantum and non-quantum) problems. The basic principle of quantum computation is that the quantum properties can be used to represent structure data, and that quantum mechanisms can be devised and built to perform operations with this data. Three basic non-classical properties of quantum mechanics superposition, entanglement, and direct-product decomposability were main reasons for optimism about capabilities of quantum computers that promised simultaneous processing of large massifs of highly correlated data. Unfortunately, these advantages of quantum mechanics came with a high price. One major problem is keeping the components of the computer in a coherent state, as the slightest interaction with the external world would cause the system to decohere. That is why the hardware implementation of a quantum computer is still unsolved. The basic idea of this work is to create a new kind of dynamical system that would preserve the main three properties of quantum physics superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. In other words, such a system would reinforce the advantages and minimize limitations of both quantum and classical aspects. Based upon a concept of hidden statistics, a new kind of dynamical system for simulation of Schroedinger equation is proposed. The system represents a modified Madelung version of Schroedinger equation. It preserves superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods. Such an optimal combination of characteristics is a perfect match for simulating quantum systems. The model includes a transitional component of quantum potential (that has been overlooked in previous treatment of the Madelung equation). The role of the transitional potential is to provide a jump from a deterministic state to a random state with prescribed probability density. This jump is triggered by blowup instability due to violation of Lipschitz condition generated by the quantum potential. As a result, the dynamics attains quantum properties on a classical scale. The model can be implemented physically as an analog VLSI-based (very-large-scale integration-based) computer, or numerically on a digital computer. This work opens a way of developing fundamentally new algorithms for quantum simulations of exponentially complex problems that expand NASA capabilities in conducting space activities. It has been illustrated that the complexity of simulations of particle interaction can be reduced from an exponential one to a polynomial one.

Zak, Michail

Laboratory instrumentation and techniques for characterizing multi-junction solar cells for space applications

Multi-junction solar cells are attractive for space applications because they can be designed to convert a larger fraction of AMO into electrical power at a lower cost than single-junction cells. The performance of multi-junction cells is much more sensitive to the spectral irradiance of the illuminating source than single-junction cells. The design of high efficiency multi-junction cells for space applications requires matching the optoelectronic properties of the junctions to AMO spectral irradiance. Unlike single-junction cells, it is not possible to carry out quantum efficiency measurements using only a monochromatic probe beam and determining the cell short-circuit current assuming linearity of the quantum efficiency. Additionally, current-voltage characteristics can not be calculated from measurements under non-AMO light sources using spectral-correction methods. There are reports in the literature on characterizing the performance of multi junction cells by measuring and convoluting the quantum efficiency of each junction with the spectral irradiance; the technique is of limited value for the characterization of cell performance under AMO power-generating conditions. We report the results of research to develop instrumentation and techniques for characterizing multi junction solar cells for space . An integrated system is described which consists of a standard lamp, spectral radiometer, dual-source solar simulator, and personal computer based current-voltage and quantum efficiency equipment. The spectral radiometer is calibrated regularly using the tungsten-halogen standard lamp which has a calibration based on NIST scales. The solar simulator produces the light bias beam for current-voltage and cell quantum efficiency measurements. The calibrated spectral radiometer is used to 'fit' the spectral irradiance of the dual-source solar simulator to WRL AMO data. The quantum efficiency apparatus includes a monochromatic probe beam for measuring the absolute cell quantum efficiency at various voltage biases, including the voltage bias corresponding to the maximum-power point under AMO light bias. The details of the procedures to 'fit' the spectral irradiance to AMO will be discussed. An assessment of the role of the accuracy of the 'fit' of the spectral irradiance and probe beam intensity on measured cell characteristics will be presented. quantum efficiencies were measured with both spectral light bias and AMO light bias; the measurements show striking differences. Spectral irradiances were convoluted with cell quantum efficiencies to calculate cell currents as function of voltage. The calculated currents compare with measured currents at the 1% level. Measurements on a variety of multi-junction cells will be presented. The dependence of defects in junctions on cell quantum efficiencies measured under light and voltage bias conditions will be presented. Comments will be made on issues related to standards for calibration, and limitations of the instrumentation and techniques. Expeditious development of multi-junction solar cell technology for space presents challenges for cell characterization in the laboratory.

Woodyard, James R.

Quantum Time Dynamics Mediated by the Yang–Baxter Equation and Artificial Neural Networks

Quantum computing shows great potential, but errors pose a significant challenge. This study explores new strategies for mitigating quantum errors using artificial neural networks (ANNs) and the Yang–Baxter equation (YBE). Unlike traditional error mitigation methods, which are computationally intensive, we investigate artificial error mitigation. We developed a novel method that combines ANNs for noise mitigation combined with the YBE to generate noisy data. This approach effectively reduces noise in quantum simulations, enhancing the accuracy of the results. The YBE rigorously preserves quantum correlations and symmetries in spin chain simulations in certain classes of integrable lattice models, enabling effective compression of quantum circuits while retaining linear scalability with the number of qubits. This compression facilitates both full and partial implementations, allowing the generation of noisy quantum data on hardware alongside noiseless simulations using classical platforms. By introducing controlled noise through the YBE, we enhance the data set for error mitigation. We train an ANN model on partial data from quantum simulations, demonstrating its effectiveness in mitigating errors in time-evolving quantum states, providing a scalable framework to enhance quantum computation fidelity, particularly in noisy intermediate-scale quantum (NISQ) systems. We demonstrate the efficacy of this approach by performing quantum time dynamics simulations using the Heisenberg XY Hamiltonian on real quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Finding the perfect imperfection: Accelerated, computationally driven discovery and design of quantum defects

Optically addressable spin defects have emerged as the leading platforms for quantum sensing and communication in solid-state systems. While traditional efforts have concentrated on a focused set of well-studied defects, recent advances in high-throughput computational methods have shown promise for large-scale exploration of defects across diverse semiconductor hosts. By cataloging key properties of quantum defects in computational databases, high-throughput screening techniques can systematically suggest and design novel candidates. In this article, we highlight recent advances in data-driven quantum defect design aimed at addressing critical materials science challenges such as host materials selection, defect stability, and desirable electronic and optical properties. Here, we emphasize the importance of electronic-structure-guided searches across various materials and illustrate how high-throughput computations contribute to our understanding of design principles for quantum defects. Additionally, we outline ongoing challenges and emerging opportunities in this rapidly developing field.

Xiong, Yihuang [Dartmouth College, Hanover, NH (Un

Low-cost DH and quantum well laser array development

The intial results of a program aimed at developing low-cost diode laser arrays for use as solid-state laser pumps are reported. MOCVD is used to demonstrate excellent run-to-run reproducibility in emission wavelength, threshold current density, and quantum efficiency. For this first experimental series, J(th) values of approximately 1310 Amps/sq cm were obtained for broad-area unthinned devices from the growth runs. Differential quantum efficiencies of between 41 percent and 47 percent were measured on the non-facet-coated devices from all four runs. Single quantum well, separate confinement heterostructure lasers fabricated from wafers grown in the same MOCVD reactor exhibited near single-mode emission, with J(th) values of approximately 300 Amps/sq cm. Photoluminescence data confirm quantum well widths of 80 A and 150 A for two different MOCVD growth runs.

Linden, Kurt J.

The seventh blind test of crystal structure prediction: structure ranking methods

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol −1 at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases.

Chemistry

An Experimental and Theoretical Study of Nitrogen-Broadened Acetylene Lines

We present experimental nitrogen-broadening coefficients derived from Voigt profiles of isotropic Raman Q-lines measured in the 2 band of acetylene (C2H2) at 150 K and 298 K, and compare them to theoretical values obtained through calculations that were carried out specifically for this work. Namely, full classical calculations based on Gordon's approach, two kinds of semi-classical calculations based on Robert Bonamy method as well as full quantum dynamical calculations were performed. All the computations employed exactly the same ab initio potential energy surface for the C2H2N2 system which is, to our knowledge, the most realistic, accurate and up-to-date one. The resulting calculated collisional half-widths are in good agreement with the experimental ones only for the full classical and quantum dynamical methods. In addition, we have performed similar calculations for IR absorption lines and compared the results to bibliographic values. Results obtained with the full classical method are again in good agreement with the available room temperature experimental data. The quantum dynamical close-coupling calculations are too time consuming to provide a complete set of values and therefore have been performed only for the R(0) line of C2H2. The broadening coefficient obtained for this line at 173 K and 297 K also compares quite well with the available experimental data. The traditional Robert Bonamy semi-classical formalism, however, strongly overestimates the values of half-width for both Qand R-lines. The refined semi-classical Robert Bonamy method, first proposed for the calculations of pressure broadening coefficients of isotropic Raman lines, is also used for IR lines. By using this improved model that takes into account effects from line coupling, the calculated semi-classical widths are significantly reduced and closer to the measured ones.

coefficients

MSD CoP Webinar: Quantum Computing Futures through a Multisector Lens

Context: This webinar featured two presentations examining quantum computing and its complex implications across the energy, water, and materials sectors. Olivier Ezratty introduced quantum computing, its anticipated applications and added value, and the hardware required to support these systems. He also discussed their energy demands and the role of the Quantum Energy Initiative in developing an interdisciplinary research field focused on these challenges. David McCollum then explored the opportunities and multisectoral challenges associated with next-generation, quantum-accelerated data centers, including their potential energy and resource impacts and the infrastructure chokepoints that could emerge. Together, the presentations emphasized the need for long-term planning and cross-cutting research collaboration as quantum computing technologies continue to develop. Presenters: Olivier Ezratty (Quantum Energy Initiative); David McCollum (Oak Ridge National Laboratory) Moderator: Patrick M. Reed (MSD CoP Facilitation Team); Gokul Iyer (Pacific Northwest National Laboratory) This webinar was held on: July 9th, 2026 from 1:00–2:30 PM EDT.

Quantum Computing

STEPs-SOL, a Peptoid Force Field Parameterization to Include Solvent Effects

As peptoids (N-substituted glycines) continue to gain popularity as a class of biomimetic polymers, the importance and demand for accurate force fields in molecular simulations also grow. Building on the vacuum-optimized Systematic and Extensible Force Field for Peptoids (STEPs) force field, here we present STEPs-SOL, a novel peptoid force field parametrization that effectively incorporates solvent effects to enhance the accuracy of peptoid simulations. The development of STEPs-SOL is based on the need for precise electrostatic modeling achieved through solvent-specific partial charge optimization. Here, our systematic approach significantly improves agreement with experimental measurements, reducing the mean absolute error in cis/trans ratio predictions (ΔG c/t ) by an average of 38% across multiple peptoid residues and solvent environments. This improved parametrization addresses computational challenges associated with nonbonded energies while maintaining a workflow that relies on high-level quantum mechanical data rather than depending solely on limited experimental equilibrium properties. By evaluating the effects of conformational bias in restrained electrostatic potential (RESP) charge generation and examining their impact on peptoid conformations in various solvents, we enhance our understanding of peptoid structural dynamics while providing a more accurate modeling framework.

force field

Automatic Generation of Chemical Mechanisms for Electrochemical Systems: Solid Electrolyte Interphase Formation in Lithium Batteries

Electrolytes in many lithium ion batteries decompose at the low potentials near the anode. The decomposition products form a layer termed the solid electrolyte interphase (SEI). The composition and growth of the SEI layer significantly affect both the capacity fade and safety of lithium ion batteries. However, SEI formation and growth kinetics are not well understood. In this work, we present an extension of the Reaction Mechanism Generator (RMG) software to automatically generate mechanisms for SEI formation. We extend RMG’s solvation correction framework to account for kinetic solvent effects and demonstrate the accuracy of our technique. We calculate thermochemical parameters for 252 species and rate coefficients for 69 reactions, most with associated solvation corrections. This and additional quantum chemistry data are used to extend RMG’s thermodynamic group additivity and solute parameter estimation schemes to handle lithiated species and add 14 new reaction families to RMG. RMG is additionally extended to simulate electrocatalytic systems. Lastly, we demonstrate RMG on the decomposition of acetonitrile and ethylene carbonate near a battery anode. Furthermore, while this framework does not yet resolve individual ions, as appropriate thermochemistry estimators are not available, and thus, cannot yet resolve more complex electrochemical pathways, RMG is able to generate reasonable pathways for SEI formation that match literature pathways and products. In particular, RMG identifies a new important reaction pathway that is not present in literature.

Chemical reactions

Can ferric-oxyl excited states explain elongated iron-oxygen bonds in heme peroxidase catalytic intermediates?

The use of X-ray structures to determine and interpret the ferryl iron-oxygen bond order in molecular oxygen-activating heme enzymes has, in the past, been controversial. This has mainly stemmed from the susceptibility of ferryl species to X-ray-induced electronic state changes. In this work we establishe using time-resolved serial femtosecond X-ray crystallography (tr-SFX) on a dye-decolourising peroxidase that the ferryl intermediate species (Compounds I and II) captured following in situ mixing of microcrystals with H 2 O 2 have single, rather than the double bond character expected. X-ray emission validated tr-SFX data with quantum refinement, time-dependent-DFT calculations and QM/MM geometry optimizations together support the concept that the single iron-oxygen bond character is not an indication of ferryl reduction or a protonated form (Fe IV -OH) but is instead attributed to the existence of accessible excited states possessing ferric-oxyl (Fe III –O •– ) character. Such states offer insight into the nature of ferryl heme.

Williams, Lewis J. [University of Essex, Colcheste