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Results for “quantum mechanics and quantum computing”

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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electrically tuned hyperfine spectrum in neutral Tb( II )(Cp iPr5 ) 2 single-molecule magnet

Molecular spin qubits with long spin coherence time as well as non-invasive operation methods on such qubits are in high demand. It was shown that both molecular electronic and nuclear spin levels can be used as qubits. In solid state systems with dopants, an electric field was shown to effectively change the spacing between the nuclear spin qubit levels when the electron spin density is high at the nucleus of the dopant. Inspired by such solid-state systems, we propose that divalent lanthanide (Ln) complexes with an unusual electronic configuration of Ln 2+ have a strong interaction between the Ln nuclear spin and the electronic degrees of freedom, which renders electrical tuning of the interaction. Furthermore, as an example, we study electronic structure and hyperfine interaction of the 159 Tb nucleus in a neutral Tb(II)(Cp iPr5 ) 2 single-molecule magnet (SMM), which exhibits unusually long magnetization relaxation time, using the complete active space self-consistent field (CASSCF) method with spin–orbit interaction included within the restricted active space state interaction (RASSI). Our calculations show that the low-energy states arise from 4f 8 (6s,5d z 2 ) 1 , 4f 8 (5d x 2 -y 2 ) 1 , and 4f 8 (5d xy ) 1 configurations. We compute the hyperfine interaction parameters and the electronic–nuclear spectrum within our multiconfigurational approach. We find that the hyperfine interaction is about one order of magnitude greater than that for Tb(III)Pc 2 SMMs. This stems from the strong Fermi contact interaction between the Tb nuclear spin and the electron spin density at the nucleus that originates from the occupation of the (6s,5d) orbitals. We also uncover that the response of the Fermi contact term to electric field results in electrical tuning of the electronic–nuclear level separations. This hyperfine Stark effect may be useful for applications of molecular nuclear spins for quantum computing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine learning framework for quantum sampling of highly constrained, continuous optimization problems

In recent years, there is growing interest in using quantum computers for solving combinatorial optimization problems. In this work, we developed a generic, machine learning-based framework for mapping continuous-space inverse design problems into surrogate quadratic unconstrained binary optimization (QUBO) problems by employing a binary variational autoencoder and a factorization machine. The factorization machine is trained as a low-dimensional, binary surrogate model for the continuous design space and sampled using various QUBO samplers. Using the D-Wave Advantage hybrid sampler and simulated annealing, we demonstrate that by repeated resampling and retraining of the factorization machine, our framework finds designs that exhibit figures of merit exceeding those of its training set. We showcase the framework’s performance on two inverse design problems by optimizing (i) thermal emitter topologies for thermophotovoltaic applications and (ii) diffractive meta-gratings for highly efficient beam steering. This technique can be further scaled to leverage future developments in quantum optimization to solve advanced inverse design problems for science and engineering applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Modern quantum chemistry with [Open]Molcas

MOLCAS/OpenMolcas is an ab initio electronic structure program providing a large set of computational methods from Hartree–Fock and density functional theory to various implementations of multiconfigurational theory. This article provides a comprehensive overview of the main features of the code, specifically reviewing the use of the code in previously reported chemical applications as well as more recent applications including the calculation of magnetic properties from optimized density matrix renormalization group wave functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Performance of an atomic mean-field spin–orbit approach within exact two-component theory for perturbative treatment of spin–orbit coupling

The paper reports development of an atomic mean-field (AMF) spin–orbit approach within the spin-free exact two-component theory in its one-electron variant (SFX2C-1e), a new relativistic quantum-chemical method for treating spin-orbit coupling in molecules. The effective one-electron spin–orbit integral matrix in the four-component representation is assembled as a direct sum of one-centre spin–orbit integral matrices with the mean-field two-electron contributions evaluated using atomic SFX2C-1e Hartree–Fock density matrices. It is then transformed into two-component representation using analytic SFX2C-1e energy derivative formulation. The resulting two-component spin–orbit integral matrix is by design suitable for use in perturbative calculations of spin–orbit coupling, treating SFX2C-1e wavefunctions as unperturbed states. The accuracy of the present AMF approach has been demonstrated using benchmark calculations of spin–orbit splittings for representative diatomic radicals at the equation-of-motion coupled-cluster singles and doubles level. In conclusion, to demonstrate the applicability and accuracy of the present perturbative spin–orbit scheme in calculations of challenging heavy-element containing systems, a thorough computational investigation of six low-lying electronic states of ThO+ is reported.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Laser-free trapped-ion entangling gates with simultaneous insensitivity to qubit and motional decoherence

The dominant error sources for state-of-the-art laser-free trapped-ion entangling gates are decoherence of the qubit state and the ion motion. The effect of these decoherence mechanisms can be suppressed with additional control fields or with techniques that have the disadvantage of reducing gate speed. In this study, we propose using a near-motional-frequency magnetic field gradient to implement a laser-free gate that is simultaneously resilient to both types of decoherence, does not require additional control fields, and has a relatively small cost in gate speed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Enhancing the Q-Factor of a Practical Qubit Niobium Three-Dimensional λ/4-Resonator Through Surface Treatment

Quantum computing stands as a revolutionary frontier in information technology, with the potential to solve complex problems far beyond the capacity of classical computers. At the heart of this disruptive innovation are qubits, forming the fundamental backbone of quantum computing. A leading-edge solution for constructing robust, enduring qubits involves embedding a Josephson junction within a high Q-factor, superconducting three-dimensional cavity. Further, our recent innovation lies in developing a uniquely optimized, quarter-wave resonator-based superconducting cavity, functioning at 6 GHz, specifically tailored for quantum computers. In this work, we elucidate our advancement towards elevating the Q-factor tenfold, an achievement made possible through the enhancement of machining precision, the application of rigorous postprocessing techniques—including mechanical, chemical, and surface treatments—as well as the refinement of our testing methods.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Quantum Circuit Cutting for Classical Shadows

Classical shadow tomography is a sample-efficient technique for characterizing quantum systems and predicting many of their properties. Circuit cutting is a technique for dividing large quantum circuits into smaller fragments that can be executed more robustly using fewer quantum resources. We introduce a divide-and-conquer circuit cutting method for estimating the expectation values of observables using classical shadows. We derive a general formula for making predictions using the classical shadows of circuit fragments from arbitrarily cut circuits and provide the sample complexity analysis for the case when observables factorize across fragments. Then, we numerically show that our divide-and-conquer method outperforms traditional uncut shadow tomography when estimating high-weight observables that act non-trivially on many qubits and discuss the mechanisms for this advantage.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Predicting Phonon-Induced Spin Decoherence from First Principles: Colossal Spin Renormalization in Condensed Matter

Developing a microscopic understanding of spin decoherence is essential to advancing quantum technologies. Electron spin decoherence due to atomic vibrations (phonons) plays a special role as it sets an intrinsic limit to the performance of spin-based quantum devices. Two main sources of phonon-induced spin decoherence—the Elliott-Yafet and Dyakonov-Perel mechanisms—have distinct physical origins and theoretical treatments. Here, we show calculations that unify their modeling and enable accurate predictions of spin relaxation and precession in semiconductors. We compute the phonon-dressed vertex of the spin-spin correlation function with a treatment analogous to the calculation of the anomalous electron magnetic moment in QED. We find that the vertex correction provides a giant renormalization of the electron spin dynamics in solids, greater by many orders of magnitude than the corresponding correction from photons in vacuum. Finally, our Letter demonstrates a general approach for quantitative analysis of spin decoherence in materials, advancing the quest for spin-based quantum technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Linear resistivity and Sachdev-Ye-Kitaev (SYK) spin liquid behavior in a quantum critical metal with spin-1/2 fermions

Significance In “Planckian metals,” electrons dissipate energy at the fastest possible rate allowed by the fundamental laws of quantum mechanics, resulting in a linear temperature dependence of their electrical resistivity. Although observed for a number of quantum materials, this phenomenon lacks a general theoretical understanding and is often considered as one of the prominent fundamental questions in condensed matter physics. Here, we show that Planckian dissipation and a behavior consistent with the “marginal Fermi liquid” phenomenology emerge in the quantum critical regime separating a Mott insulating spin glass and a Fermi liquid. By establishing this behavior in an explicit model solvable by state-of-the-art computational methods, our theory paves the way toward a deeper understanding of Planckian or “strange” metals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Identification of Solid-Electrolyte Interphase Species by Joint Characterization of Li-Ion Battery Chemistry by Mass Spectrometry and Electrochemical Reaction Networks

The formation and stability of the solid-electrolyte interphase (SEI) play central roles in determining the long-term performance and safety of modern electrochemical energy storage systems. Despite decades of research, the SEI’s heterogeneous, dynamic, and multiphase nature has defied comprehensive molecular-level characterization, creating a critical knowledge gap that limits rational battery design. In this work, we introduce a computational−experimental framework that integrates high-throughput quantum chemistry calculations, data-driven electrochemical reaction networks (eCRNs), stochastic algorithms, and laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry (LDI-FTICR-MS) to unravel SEI formation in carbonatebased electrolytes without imposing predefined mechanisms. We constructed the most comprehensive eCRN to date, spanning over 10,000 species and 209 million reactions. Through stochastic network analysis, we successfully recovered 27 species that were previously reported in the literature and predicted 28 novel SEI species nearly doubling our scientific knowledge in this area. Each new species was rigorously confirmed through advanced mass spectral analysis of its distinct molecular and isotopic signatures. We kinetically refined the formation pathways for a select set of both previously reported and novel SEI products, revealing kinetically feasible elementary reaction mechanisms with activation barriers below 1 eV. This computational−experimental approach deepens our molecular-level understanding of SEI chemistry by resolving which species form and through which decomposition mechanisms they emerge. Such knowledge provides the foundation necessary to connect electrolyte composition to the resulting SEI components, a critical step toward a more informed electrolyte development in next-generation lithium-based batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

MB-Fit: Software infrastructure for data-driven many-body potential energy functions

Many-body potential energy functions (MB-PEFs), which integrate data-driven representations of many-body short-range quantum mechanical interactions with physics-based representations of many-body polarization and long-range interactions, have recently been shown to provide high accuracy in the description of molecular interactions from the gas to the condensed phase. Here, we present MB-Fit, a software infrastructure for the automated development of MB-PEFs for generic molecules within the TTM-nrg (Thole-type model energy) and MB-nrg (many-body energy) theoretical frameworks. Besides providing all the necessary computational tools for generating TTM-nrg and MB-nrg PEFs, MB-Fit provides a seamless interface with the MBX software, a many-body energy and force calculator for computer simulations. Given the demonstrated accuracy of the MB-PEFs, particularly within the MB-nrg framework, we believe that MB-Fit will enable routine predictive computer simulations of generic (small) molecules in the gas, liquid, and solid phases, including, but not limited to, the modeling of quantum isomeric equilibria in molecular clusters, solvation processes, molecular crystals, and phase diagrams.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗
DOE OSTI2025

Plumbene: a comprehensive review of theoretical and experimental advances

Plumbene, a two-dimensional (2D) material consisting of a single layer of lead (Pb) atoms in a honeycomb lattice, stands as a pioneering addition to the elemental 2D material family. Here, this comprehensive review encapsulates the theoretical predictions and experimental advancements that underscore its potential. With properties shaped by significant spin-orbit coupling and structural buckling, plumbene offers a playground for phenomena like the quantum spin Hall effect, superconductivity, and topological phase transitions. Despite promising theoretical insights, experimental realization has encountered challenges, primarily due to high reactivity of Pb and the need for precise fabrication conditions. This paper critically examines the electronic, thermal, mechanical, and topological attributes of plumbene, alongside synthesis methods, functionalization techniques, and substrate effects. It further proposes directions for addressing synthesis challenges and integrating plumbene into advanced technologies, particularly in electronic, spintronic, and quantum computing applications. This review aims to bridge the gap between theoretical potential and experimental progress, fostering a deeper understanding of this intriguing material.

2D materials↗
DOE OSTI2026

Harnessing the Spin-Flip Radiative Lifetimes of Optically Addressable Molecular Qubits

Optically addressable molecular qubits based on spin-flip (SF) emissive transitions are promising candidates for quantum technologies due to their sharp luminescence lines and tunable optical-spin interfaces. Yet, the microscopic mechanisms controlling the spin-flip radiative lifetime of SF emitters, a key property for efficient spin readout, remain largely unexplored. Here, we present a computational study of several Cr 4+ and Mo 4+ pseudotetrahedral molecular qubits, and we identify chemical and structural features that influence the transition dipole moment associated with the SF emission, which, in turn, governs the SF radiative lifetime. We find that the magnitude of the dipole moment is governed by the multireference character of the spin-flip excited-state wave function, which can be modulated by tuning the energy separation between the d orbitals of the metal and the spin-pairing energy. Both parameters are sensitive to molecular symmetry, metal–ligand bond covalency, and bond anisotropy and leave room for modulation via ligand and metal design, as well as applied strain, which is relevant for sensing applications. Our findings provide a mechanistic framework for understanding and tuning the spin-flip radiative behavior of molecular qubits and SF emitters that may guide future advances in quantum information science.

molecular qubits↗
DOE OSTI2024

First-principles calculation of lattice distortion, electronic structure, and bonding properties of GeTe-based and PbSe-based high-entropy chalcogenides

The massive amount of wasted heat energy from industry has pushed the development of thermoelectric (TE) materials that directly convert heat into electricity to a new level of concern. Recently, multicomponent alloys such as GeTe-based and PbSe-based high-entropy (HE) chalcogenides have attracted a great deal of attention due to their potential application as TE materials. The nature of the interatomic bonding, lattice distortion (LD), and the electronic structure in this class of materials is not fully understood. Herein, we report a comprehensive computational investigation of nine GeTe-based HE alloys with eight metallic elements (Ag, Pb, Sb, Bi, Cu, Cd, Mn, and Sn) with large supercells of 1080 atoms each; seven PbSe-based HE solid solutions: Pb0.99−ySb0.012SnySe1−2xTexSx (x = 0.1, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, with y = 0) with supercells of 1000 atoms each; and five Pb0.99−ySb0.012SnySe1−2xTexSx (y = 0.05, 0.1, 0.15, 0.2, 0.25 with x = 0.25) solid solutions with supercells of 1000 atoms each. All these HE models are theoretically investigated for the first time. The electronic structure, interatomic bonding, charge transfer, and lattice distortion (LD) are investigated by first-principles calculations based on density functional theory. Multicomponent HE alloys can cause a significant LD, which affects their mechanical, thermal, and TE properties. The calculations for the GeTe-based HE chalcogenides showed that they are semiconductors with a narrow bandgap, except for m8, which has a semi-metallic characteristic, and this makes them good candidates for TE applications. For most of these models, the Fermi level shifts upward and locates deeply in the conduction bands, resulting in the enhancement of the electrical conductivity (σ). The bonding properties showed that most bonds in m5 are more dispersed, indicating highest LD and lower lattice thermal conductivity. For PbSe-based HE solid solutions, the LD calculations showed that the models Pb0.99Sb0.012Se0.5Te0.25S0.25 and Pb0.89Sb0.012Sn0.1Se0.5Te0.25S0.25 have the higher LD, and thus a lower lattice thermal conductivity. Such investigations are in high demand since it enables us to design new HE chalcogenides for TE applications. We use the novel concept of total bond order density as a single quantum mechanical metric to characterize the internal cohesion of these HE alloys and correlate with calculated properties, especially the mechanical properties. This work provides a solid database for HE chalcogenides and a road map for many potential applications. Moreover, the computational procedure we developed can be used to design new HE chalcogenides for specific TE applications.

Physics↗
DOE OSTI2026

Emergence of vorticity and viscous stress in finite-scale quantum hydrodynamics

The Madelung equations offer a hydrodynamic description of quantum systems, from single particles to quantum fluids. In this formulation, the probability density is mapped onto the fluid density and the phase is treated as a scalar potential generating the velocity field. As examples of potential flows, quantum fluids described in this way are inherently irrotational, but quantum vortices may arise at discrete points where the phase is undefined. In this paper, starting from this irrotational description of a quantum fluid, a coarse-graining procedure is applied to arrive at a macroscopic description of the quantum fluid in terms of a hierarchy of moments in which the role of velocity is played by a Favre average of the microscopic velocity field. This hierarchy is truncated using an explicit closure derived from an expansion in a finite length scale. The resulting coarse-grained fields are shown to allow for finite vorticity at any point in the fluid. Additionally, it is shown that this vorticity obeys a similar equation to the vorticity equation in classical hydrodynamics and includes a vortex-stretching term. The particular closure employed here also gives rise to a novel stress term in the fluid equations, which in the appropriate limit appears analogous to an artificial viscous stress from computational fluid dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Seal Strength Calculations for Low Mass DDT Vessel

Lawrence Livermore National Laboratory (LLNL) is collaborating with Colorado School of Mines (Mines), to field the first dynamic experiments on the 3-ring flash radiography system (3-ring). One set of experiments for 3-ring concerns the deflagration to detonation transition (DDT), within a sealed column of high-explosives. The high-explosive material is ignited at one end with a BK-80, an igniter made from Boron Potassium-Nitrate (BKNO 3 ). The initial deflagration reaction will increase the pressure in the sealed vessel, resulting in the formation of a dense "plug" of material ahead of the deflagration front. The transition to detonation is thought to be related to the plug formation. Previous experiments have been able to resolve the plug geometry, but only in a two dimensional radio-graph. 3-ring offers a novel diagnostic tool which could provide three dimensional density fields via few-view reconstruction algorithms and computed tomography.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗