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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 343 records · Page 19

Chemical Profiles of the Oxides on Tantalum in State of the Art Superconducting Circuits

Abstract Over the past decades, superconducting qubits have emerged as one of the leading hardware platforms for realizing a quantum processor. Consequently, researchers have made significant effort to understand the loss channels that limit the coherence times of superconducting qubits. A major source of loss has been attributed to two level systems that are present at the material interfaces. It is recently shown that replacing the metal in the capacitor of a transmon with tantalum yields record relaxation and coherence times for superconducting qubits, motivating a detailed study of the tantalum surface. In this work, the chemical profile of the surface of tantalum films grown on c‐plane sapphire using variable energy X‐ray photoelectron spectroscopy (VEXPS) is studied. The different oxidation states of tantalum that are present in the native oxide resulting from exposure to air are identified, and their distribution through the depth of the film is measured. Furthermore, it is shown how the volume and depth distribution of these tantalum oxidation states can be altered by various chemical treatments. Correlating these measurements with detailed measurements of quantum devices may elucidate the underlying microscopic sources of loss.

36 MATERIALS SCIENCE↗

Noise Robustness and Experimental Demonstration of a Quantum Generative Adversarial Network for Continuous Distributions

Abstract The potential advantage of machine learning in quantum computers is a topic of intense discussion in the literature. Theoretical, numerical, and experimental explorations will most likely be required to understand its power. There have been different algorithms proposed to exploit the probabilistic nature of variational quantum circuits for generative modeling. In this paper, a hybrid architecture for quantum generative adversarial networks (QGANs) is employed and their robustness in the presence of noise is studied. A simple way of adding different types of noise to the quantum generator circuit is devised, and the noisy hybrid QGANs (HQGANs) are simulated numerically to learn continuous probability distributions, and to show that the performance of HQGANs remains unaffected. The effect of different parameters on the training time is also investigated to reduce the computational scaling of the algorithm and simplify its deployment on a quantum computer. The training on Rigetti's Aspen‐4‐2Q‐A quantum processing unit is then performed, and the results from the training are presented. The authors' results pave the way for experimental exploration of different quantum machine learning algorithms on noisy intermediate‐scale quantum devices.

Anand, Abhinav↗

A model of randomly-coupled Pauli spins

Abstract We construct a model of Pauli spin operators with all-to-all 4-local interactions by replacing Majorana fermions in the SYK model with spin operators. Equivalently, we replace fermions with hard-core bosons. We study this model numerically and compare the properties with those of the SYK model. We observe a striking quantitative coincidence between the spin model and the SYK model, which suggests that this spin model is strongly chaotic and, perhaps, can play some role in holography. We also discuss the path-integral approach with multi-local fields and the possibility of quantum simulations. This model may be an interesting target for quantum simulations because Pauli spins are easier to implement than fermions on qubit-based quantum devices.

Physics↗

Quantum Computing: Advancing Fundamental Physics

The field of Quantum Information Science (QIS) is a rapidly growing field, with an expanding number of potential applications that explore the capabilities of currently available noisy quantum devices and promise to eventually solve problems beyond anything that classical systems can accomplish. In the past few years, this expectation for transformational applications has translated to a lot of attention, both from the media (reaching the scientific community and the general public) and the government funding agencies and technology industry.

97 MATHEMATICS AND COMPUTING↗

The interaction of acetonitrile with H-terminated and depassivated (100) diamond surfaces

Molecular adsorption on reactive semiconductor surfaces may enable novel surface functionalisation and atomically-precise dopant formation. In this work synchrotron-based x-ray photoelectron spectroscopy and near edge x-ray absorption spectroscopy are used to examine the interaction between acetonitrile and diamond (100) surfaces under ultrahigh vacuum (UHV) conditions. We observe two surface-bound nitrogen species on hydrogen terminated surfaces after thermal depassivation or following synchrotron radiation and subsequent exposure to acetonitrile, but find no evidence of nitrogen adsorption on the hydrogen-terminated diamond surface, at room temperature. Subsequent measurements explore the stability of the surface-bound nitrogen under various temperature conditions and with atmospheric exposure. While the nitrogen coverage achieved in this study is low, this study serves as a proof-of-concept demonstration of a UHV molecular dosing approach to selective nitrogen functionalisation of diamond surfaces as an alternative to plasma-based approaches. This development may be critical for proposed surface-based fabrication workflows using atomic placement of nitrogen-vacancy centres to create quantum devices.

74 ATOMIC AND MOLECULAR PHYSICS↗

Topological band gap in intercalated epitaxial graphene

The study of functional manipulation of graphene is a critical subject, both for fundamental research and practical applications. In this study, we present that the intercalation of 5d transition metals into epitaxial graphene on SiC is a promising strategy for the realization of topologically nontrivial phases with a finite band gap in graphene. Employing first-principles calculations, grounded in density functional theory, we demonstrate that Re- and Ta-intercalated graphene evolve into two-dimensional topological insulators. These exhibit linear Dirac cones and quadratic bands with topological band gaps, respectively. The emergence of these topological states is attributed to the strong spin–orbit coupling strength of the intercalants. We show that the corresponding topological edge states persist within the finite bulk band gap, aligning with the bulk-boundary correspondence. Furthermore, we explore the spin splitting of the band structure, brought about by the inversion symmetry breaking and the spin–orbit coupling. Finally, our study underscores that the intercalation of graphene is an effective and a feasible approach for manipulating the band gap and the topological nature of graphene. Such intercalated graphene systems hold potential utility for spintronics and low-dimensional quantum device applications.

36 MATERIALS SCIENCE↗

Efficient Step-Merged Quantum Imaginary Time Evolution Algorithm for Quantum Chemistry

In this work, we develop a resource-efficient step-merged quantum imaginary time evolution approach (smQITE) to solve for the ground state of a Hamiltonian on quantum computers. This heuristic method features a fixed shallow quantum circuit depth along the state evolution path. We use this algorithm to determine the binding energy curves of a set of molecules, including H 2 , H 4 , H 6 , LiH, HF, H 2 O, and BeH 2 , and find highly accurate results. The required quantum resources of smQITE calculations can be further reduced by adopting the circuit form of the variational quantum eigensolver (VQE) technique, such as the unitary coupled cluster ansatz. We demonstrate that smQITE achieves a similar computational accuracy as VQE at the same fixed-circuit ansatz, without requiring a generally complicated high-dimensional nonconvex optimization. Finally, smQITE calculations are carried out on Rigetti quantum processing units, demonstrating that the approach is readily applicable on current noisy intermediate-scale quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning Electronic Properties of 2D Materials Using Metal Adsorbates: Cu at WTe 2 Edges

Two-dimensional materials exhibit properties promising for novel applications. Topologically protected states at their edges can be harnessed for use in quantum devices. We use ab initio simulations to examine properties of edges in 1T'-WTe 2 monolayers, known to exhibit topological order, and their interactions with Cu atoms. Comparison of (010)-oriented edges that have the same composition but different terminations shows that, as the number of Cu atoms increases, their thermodynamically-preferred arrangement depends on the details of the edge structure. Cu atoms aggregate into a cluster at the most stable edge; while the cluster is non-magnetic, it spin-polarizes the W atoms along the edge, which removes the topological protection. At the metastable edge, Cu atoms form a chain incorporated into the WTe 2 lattice; the topological state is preserved in spite of the dramatic edge restructuring. This suggests that exploiting interactions of metal species with metastable edge terminations can provide a path towards non-invasive interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Raman Fingerprints of Phase Transitions and Ferroic Couplings in van der Waals Multiferroic CuCrP 2 S 6

CuCrP 2 S 6 (CCPS), a type-II multiferroic material, exhibits unique phase transitions involving ferroelectric, antiferroelectric, and antiferromagnetic ordering. Here, in this study, we conduct a comprehensive investigation on the intricate phase transitions and their multiferroic couplings in CCPS across a wide temperature range from 4 to 345 K through Raman spectroscopic measurements down to 5 cm –1 . We first assign the observed Raman modes with the support of theoretical calculations and angle-resolved polarized Raman measurements. We further present clear signatures of phase transitions from the analyses of temperature-dependent Raman spectral parameters. Particularly, two low-frequency soft modes are observed at 36.1 cm –1 and 70.5 cm –1 below 145 K, indicating the antiferroelectric to quasi-antiferroelectric transition. Moreover, phonon mode hardening is observed when the temperature increases from 4 to 65 K, suggesting negative thermal expansion (NTE) and strong magnetoelastic coupling below 65 K. These findings advance the understanding of vdW multiferroic CCPS, paving the way for future design and engineering of multiferroicity in cutting-edge technologies, such as spintronics and quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of Tunable SnS-TaS 2 Nanoscale Superlattices

Nanoscale superlattices represent a compelling platform for designed materials as the specific identity and spatial arrangement of constituent layers can lead to tunable properties. A number of kinetically stabilized, nonepitaxial superlattices with almost limitless structural tunability have been reported in telluride and selenide chemistries but have not yet been extended to sulfides. Here, we present SnS-TaS 2 nanoscale superlattices with tunable layer architecture. Layered amorphous precursors are prepared as thin films programmed to mimic the targeted superlattice; subsequent low temperature annealing activates self-assembly into crystalline nanocomposites. We investigate structure and composition of superlattices comprised of monolayers of TaS 2 and 3–7 monolayers of SnS per repeating unit. Furthermore, a graded precursor preparation approach is introduced, allowing stabilization of superlattices with multiple stacking sequences in a single preparation. Controlled synthesis of the architecture of nanoscale superlattices is a critical path toward tuning their exotic properties and enabling integration with electronic, optical, or quantum devices.

36 MATERIALS SCIENCE↗

A General and Modular Approach to Solid-State Integration of Zero-Dimensional Quantum Systems

Here, we present an all-electrical readout mechanism for quasi-0D quantum states (0D-QS), such as point defects, adatoms, and molecules, that is modular and general, providing an approach that is amenable to scaling and integration with other solid-state quantum technologies. Our approach relies on the creation of high-quality tunnel junctions via the mechanical exfoliation and stacking of multilayer graphene (MLG) and hexagonal boron nitride (hBN) to encapsulate the target system in an MLG/hBN/0D-QS/hBN/MLG heterostructure. This structure allows for all-electronic spectroscopy and readout of candidate systems through a combination of coulomb and spin-blockade. As a proof of principle, we demonstrate electronic tunneling spectroscopy of point defects in hBN and the molecular qubit vanadyl phthalocyanine. Our approach demonstrates a new pathway for the incorporation of molecules and atomic defects into solid-state quantum devices and circuits along with a readout scheme that does not rely on highly constrained optical processes for photonic readout.

defects in hexagonal boron nitride↗

Characterizing Defects Inside Hexagonal Boron Nitride Using Random Telegraph Signals in van der Waals 2D Transistors

Single-crystal hexagonal boron nitride (hBN) is used extensively in many two-dimensional electronic and quantum devices, where defects significantly impact performance. Therefore, characterizing and engineering hBN defects are crucial for advancing these technologies. Here, we examine the capture and emission dynamics of defects in hBN by utilizing low-frequency noise (LFN) spectroscopy in hBN-encapsulated and graphene-contacted MoS 2 field-effect transistors (FETs). The low disorder of this heterostructure allows the detection of random telegraph signals (RTS) in large device dimensions of 100 μm 2 at cryogenic temperatures. Analysis of gate bias- and temperature-dependent LFN data indicate that RTS originates from a single trap species within hBN. By performing multi-space density functional theory (MS-DFT) calculations on a gated defective hBN/MoS 2 heterostructure model, we assign substitutional carbon atoms in boron sites as the atomistic origin of RTS. This study demonstrates the utility of LFN spectroscopy combined with MS-DFT analysis on a low-disorder all-vdW FET as a powerful means for characterizing the atomistic defects in single-crystal hBN.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Quantum Machine-Learning for Eigenstate Filtration in Two-Dimensional Materials

Quantum machine-learning algorithms have emerged to be a promising alternative to their classical counterparts as they leverage the power of quantum computers. Such algorithms have been developed to solve problems like electronic structure calculations of molecular systems and spin models in magnetic systems. However, the discussion in all these recipes focuses specifically on targeting the ground state. Herein we demonstrate a quantum algorithm that can filter any energy eigenstate of the system based on either symmetry properties or a predefined choice of the user. The workhorse of our technique is a shallow neural network encoding the desired state of the system with the amplitude computed by sampling the Gibbs–Boltzmann distribution using a quantum circuit and the phase information obtained classically from the nonlinear activation of a separate set of neurons. We show that the resource requirements of our algorithm are strictly quadratic. To demonstrate its efficacy, we use state filtration in monolayer transition metal dichalcogenides which are hitherto unexplored in any flavor of quantum simulations. We implement our algorithm not only on quantum simulators but also on actual IBM-Q quantum devices and show good agreement with the results procured from conventional electronic structure calculations. We thus expect our protocol to provide a new alternative in exploring the band structures of exquisite materials to usual electronic structure methods or machine-learning techniques that are implementable solely on a classical computer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unconventional Superlattice Ordering in Intercalated Transition Metal Dichalcogenide V1/3NbS2

The interplay between symmetry and topology in magnetic materials makes it possible to engineer exotic phases and technologically useful properties. A key requirement for these pursuits is achieving control over local crystallographic and magnetic structure, usually through sample morphology (such as synthesis of bulk crystals versus thin films) and application of magnetic or electric fields. Here we show that V1/3NbS2 can be crystallized in two ordered superlattices, distinguished by the periodicity of out-of-plane magnetic intercalants. Whereas one of these structures is metallic and displays the hallmarks of altermagnetism, the other superlattice, which has not been isolated before in this family of intercalation compounds, is a semimetallic noncollinear antiferromagnet that may enable access to topologically nontrivial properties. This observation of an unconventional superlattice structure establishes a powerful route for tailoring the tremendous array of magnetic and electronic behaviors hosted in related materials and may expand their use in low-power spintronic or topological quantum devices.

Fender, Shannon S↗

Control of electronic topology in a strongly correlated electron system

It is becoming increasingly clear that breakthrough in quantum applications necessitates materials innovation. In high demand are conductors with robust topological states that can be manipulated at will. This is what we demonstrate in the present work. We discover that the pronounced topological response of a strongly correlated “Weyl-Kondo” semimetal can be genuinely manipulated—and ultimately fully suppressed—by magnetic fields. We understand this behavior as a Zeeman-driven motion of Weyl nodes in momentum space, up to the point where the nodes meet and annihilate in a topological quantum phase transition. The topologically trivial but correlated background remains unaffected across this transition, as is shown by our investigations up to much larger fields. Our work lays the ground for systematic explorations of electronic topology, and boosts the prospect for topological quantum devices.

36 MATERIALS SCIENCE↗

The critical role of ultra-low-energy vibrations in the relaxation dynamics of molecular qubits

Improving the performance of molecular qubits is a fundamental milestone towards unleashing the power of molecular magnetism in the second quantum revolution. Taming spin relaxation and decoherence due to vibrations is crucial to reach this milestone, but this is hindered by our lack of understanding on the nature of vibrations and their coupling to spins. Here we propose a synergistic approach to study a prototypical molecular qubit. It combines inelastic X-ray scattering to measure phonon dispersions along the main symmetry directions of the crystal and spin dynamics simulations based on DFT. We show that the canonical Debye picture of lattice dynamics breaks down and that intra-molecular vibrations with very-low energies of 1-2 meV are largely responsible for spin relaxation up to ambient temperature. We identify the origin of these modes, thus providing a rationale for improving spin coherence. The power and flexibility of our approach open new avenues for the investigation of magnetic molecules with the potential of removing roadblocks toward their use in quantum devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep learning at the edge enables real-time streaming ptychographic imaging

Abstract Coherent imaging techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent imaging methods like ptychography are poised to revolutionize nanoscale materials characterization. However, these advancements are accompanied by significant increase in data and compute needs, which precludes real-time imaging, feedback and decision-making capabilities with conventional approaches. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the oversampling constraints, allowing low-dose imaging using orders of magnitude less data than required by traditional methods.

36 MATERIALS SCIENCE↗

Atomic-scale imaging and charge state manipulation of NV centers by scanning tunneling microscopy

Nitrogen-vacancy (NV) centers in diamond are among the most promising solid-state qubit candidates, owing to their exceptionally long spin coherence times, efficient spin-photon coupling, room-temperature operation, and steadily advancing fabrication and integration techniques. Despite significant progress in the field, atomic-scale characterization and control of individual NV centers have remained elusive. In this work, we utilize a conductive graphene capping layer to enable direct imaging and manipulation of NV - defects via scanning tunneling microscopy (STM). By investigating over 40 individual NV - centers, we identify their spectroscopic signatures and spatial configurations. Our dI/dV conductance spectra reveal the ground state resonance approximately 300 meV below the Fermi level and density-of-states maps uncover a two-lobed wavefunction aligned along the [111] crystallographic direction. Remarkably, we demonstrate the ability to manipulate the charge state of the NV centers from NV - to NV 0 through STM tip-induced gating. This work represents a significant advance in the atomic-scale imaging, spectroscopic characterization, and charge-state manipulation of NV centers, potentially paving the way for future quantum device development.

Raghavan, Arjun [Univ. of Illinois at Urbana-Champ↗