Search NASA⌕ Search

SEARCH · Search NASA

Results for “quantum device”

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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electronic structure calculations of twisted multi-layer graphene superlattices

Quantum confinement endows two-dimensional (2D) layered materials with exceptional physics and novel properties compared to their bulk counterparts. Although certain two- and few-layer configurations of graphene have been realized and studied, a systematic investigation of the properties of arbitrarily layered graphene assemblies is still lacking. We introduce theoretical concepts and methods for the processing of materials information, and as a case study, apply them to investigate the electronic structure of multi-layer graphene-based assemblies in a high-throughput fashion. We provide a critical discussion of patterns and trends in tight binding band structures and we identify specific layered assemblies using low-dispersion electronic bands as indicators of potentially interesting physics like strongly correlated behavior. A combination of data-driven models for visualization and prediction is used to intelligently explore the materials space. This work more generally aims to increase confidence in the combined use of physics-based and data-driven modeling for the systematic refinement of knowledge about 2D layered materials, with implications for the development of novel quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quantum Machine Learning in High Energy Physics

Machine learning has been used in high energy physics for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early 1980s as way to perform computations that would not be tractable with a classical computer. With the advent of noisy intermediate-scale quantum computing devices, more quantum algorithms are being developed with the aim at exploiting the capacity of the hardware for machine learning applications. An interesting question is whether there are ways to apply quantum machine learning to High Energy Physics. This paper reviews the first generation of ideas that use quantum machine learning on problems in high energy physics and provide an outlook on future applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Negative string tension of a higher-charge Schwinger model via digital quantum simulation

We study some properties of generalized global symmetry for the charge- q Schwinger model in the Hamiltonian formalism, which is the (1 + 1)D quantum electrodynamics with a charge- q Dirac fermion. This model has the |$\mathbb {Z}_q\, 1$| -form symmetry, which is a remnant of the electric |$U(1)\, 1$| -form symmetry in the pure Maxwell theory. It is known that, if we put the theory on closed space, then the Hilbert space is decomposed into q distinct sectors, called universes, and some states with higher energy density do not decay to the ground state due to the selection rule of the 1-form symmetry. Even with open boundaries, we can observe the stability of such states by seeing a negative string tension behavior, meaning that opposite charges repel each other. In order to see negative string tensions, the vacuum angle θ has to be large enough and the standard path-integral Monte Carlo method suffers from the sign problem. We develop a method based on the adiabatic state preparation to see this feature with digital quantum simulation and confirm it using a classical simulator of quantum devices. In particular, we measure the local energy density and see how it jumps between the inside and outside of the insertion of the probe charges. We explicitly see that the energy density inside is lower than that outside. This is a clear signature of the negative string tension.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

High magnetic field response of superconductivity dome in quantum artificial high−⁢𝑇 𝐶 superlattices with variable geometry

It is known that cuprate artificial high-𝑇 𝐶 superlattices (AHTS) with period 𝑑, composed of quantum wells confining interface space charge in stoichiometric Mott insulator layers (𝑆), with thickness 𝐿, at the interface with overdoped normal metallic cuprate layers (𝑁) show a superconducting dome by tuning the geometric 𝐿 over 𝑑 ratio of the SNSN superlattice with the top predicted by quantum material design engineering quantum size effects. Here we report high-field magnetotransport measurements up to 41 Tesla of AHTS across the entire superconducting dome. The results show the universal upward-concave behavior of the temperature-dependent upper critical magnetic field in low-𝑇 𝐶 samples at the rising edge and drop edge of the dome, providing strong evidence consistent with two-band superconductivity in agreement with multigap theory used for quantum design of the SNSN superlattices. The measured superconducting coherence length demonstrates that atomic-scale engineering controls not only the critical temperature but also the intrinsic pair size at Fano-Feshbach resonances physics paving the way toward next-generation quantum devices and shedding light on unconventional superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Minimally entangled state preparation of localized wave functions on quantum computers

Initializing a single site of a lattice scalar field theory into an arbitrary state with support throughout the quantum register requires $O(2^{nQ})$ entangling gates on a quantum computer with $n_Q$ qubits per site. It is conceivable that instead initializing to functions that are good approximations to states may have utility in reducing the number of required entangling gates. In the case of a single site of a noninteracting scalar field theory, initializing to a symmetric exponential wave function requires $n_Q – 1$ entangling gates, the minimal number necessary to create an entangled state of all $n_Q$ qubits. This is compared with the $2^{nQ – 1} + n_Q – 3 + δ_{nQ, 1}$ required for a symmetric Gaussian wave function. In this work, we explore the initialization of one-site $(n_Q = 4)$, two-site $(n_Q = 3)$, and three-site ( n Q = 3 ) noninteracting scalar field theories with symmetric exponential wave functions using IBM's quantum simulators and quantum devices (Poughkeepsie and Tokyo). With the digitizations attainable with $n_Q = 3,4$, these tensor-product wave functions are found to have large overlap with a Gaussian wave function and provide a suitable low-noise initialization for improvement and Somma inflation. Further, in performing these simulations, we have employed a workflow that interleaves calibrations to mitigate systematic errors in production. The calibrations allow tolerance cuts on gate performance including the fidelity of the symmetrizing Hadamard gate, both in vacuum $(|\textbf{0}\gg^{\bigotimes nQ})$ and in medium ($n_Q –1$ qubits initialized to an exponential function). The results obtained in this work are relevant to systems beyond scalar field theories, such as the deuteron radial wave function, two- and three-dimensional Cartesian-space wave functions, and nonrelativistic multinucleon systems built on a localized eigenbasis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Fixed-angle conjectures for the quantum approximate optimization algorithm on regular MaxCut graphs

The quantum approximate optimization algorithm (QAOA) is a near-term combinatorial optimization algorithm suitable for noisy quantum devices. However, little is known about performance guarantees for p > 2. A recent work computing MaxCut performance guarantees for 3-regular graphs conjectures that any d-regular graph evaluated at particular fixed angles has an approximation ratio greater than some worst-case guarantee. In this work, we provide numerical evidence for this fixed angle conjecture for p < 12. We compute and provide these angles via numerical optimization and tensor networks. These fixed angles serve for an optimization-free version of QAOA and have universally good performance on any 3-regular graph. Heuristic evidence is presented for the fixed angle conjecture on graph ensembles, which suggests that these fixed angles are "close" to global optimum. Under the fixed angle conjecture, QAOA has a larger performance guarantee than the Goemans Williamson algorithm on 3-regular graphs for p >= 11.

Wurtz, Jonathan↗
DOE OSTI2024

Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms

Here, this study investigates the thermal properties of the repulsive Fermi-Hubbard model with chemical potential using variational quantum algorithms, crucial in comprehending particle behaviour within lattices at heightened temperatures in condensed matter systems. Conventional computational methods encounter challenges, especially in managing chemical potential, prompting exploration into Hamiltonian approaches. Despite the promise of quantum algorithms, their efficacy is hampered by coherence limitations when simulating extended imaginary time evolution sequences. To overcome these constraints, this research focuses on optimizing variational quantum algorithms to probe the thermal properties of the Fermi-Hubbard model. Physics-inspired circuit designs are tailored to alleviate coherence constraints, facilitating a more comprehensive exploration of materials at elevated temperatures. Our study demonstrates the potential of variational algorithms in simulating the thermal properties of the Fermi-Hubbard model while acknowledging limitations stemming from error sources in quantum devices and encountering barren plateaus.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Manipulating topological properties in Bi 2 Se 3 / BiSe /transition metal dichalcogenide heterostructures with interface charge transfer

Heterostructures of topological insulator Bi 2 Se 3 on transition metal dichalcogenides (TMDCs) offer a new materials platform for studying novel quantum states by exploiting the interplay among topological orders, charge orders and magnetic orders. Here, the diverse interface attributes, such as material combination, charge re-arrangement, defect and strain, can be utilized to manipulate the quantum properties of this class of materials. Recent experiments of Bi 2 Se 3 /NbSe 2 heterostructures show signatures of strong Rashba band splitting due to the presence of a BiSe buffer layer, but the atomic level mechanism is not fully understood. We conduct first-principles studies of the Bi 2 Se3/BiSe/TMDC heterostructures with five different TMDC substrates (1T phase VSe 2 , MoSe 2 , TiSe 2 , and 2H phase NbSe 2 , MoSe 2 ). We find significant charge transfer at both BiSe/TMDC and Bi 2 Se 3 /BiSe interfaces driven by the work function difference, which stabilizes the BiSe layer as an electron donor and creates interface dipole. The electric field of the interface dipole breaks the inversion symmetry in the Bi 2 Se 3 layer, leading to the giant Rashba band splitting in two quintuple layers and the recovery of the Dirac point in three quintuple layers, with the latter otherwise only occurring in thicker samples with at least six Bi 2 Se 3 quintuple layers. Besides, we find that strain can significantly affect the charge transfer at the interfaces. Our study presents a promising avenue for tuning topological properties in heterostructures of two-dimensional materials, with potential applications in quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lattice holography on a quantum computer

We explore the potential application of quantum computers to the examination of lattice holography, which extends to the strongly coupled bulk theory regime. With adiabatic evolution, we compute the ground state of a spin system on a ( 2 + 1 )-dimensional hyperbolic lattice, and measure the spin-spin correlation function on the boundary. Notably, we observe that with achievable resources for coming quantum devices, the correlation function demonstrates an approximate scale-invariant behavior, aligning with the pivotal theoretical predictions of the anti–de Sitter/conformal field theory correspondence. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quantum error mitigation for Fourier moment computation

Hamiltonian moments in Fourier space—expectation values of the unitary evolution operator under a Hamiltonian at different times—provide a convenient framework to understand quantum systems. They offer insights into the energy distribution, higher-order dynamics, response functions, correlation information, and physical properties. This paper focuses on the computation of Fourier moments within the context of a nuclear effective field theory on superconducting quantum hardware. The study integrates echo verification and noise renormalization into Hadamard tests using control reversal gates. These techniques, combined with purification and error suppression methods, effectively address quantum hardware decoherence. The analysis, conducted using noise models, reveals a significant reduction in noise strength by two orders of magnitude. Moreover, quantum circuits involving up to 266 gates over five qubits demonstrate high accuracy under these methodologies when run on IBM superconducting quantum devices. Published by the American Physical Society 2025

Kiss, Oriel (ORCID:0000000174613342)↗
DOE OSTI2022

Classical Simulation of Boson Sampling Based on Graph Structure

Boson sampling is a fundamentally and practically important task that can be used to demonstrate quantum supremacy using noisy intermediate-scale quantum devices. In this Letter, we present classical sampling algorithms for single-photon and Gaussian input states that take advantage of a graph structure of a linear-optical circuit. The algorithms’ complexity grows as so-called treewidth, which is closely related to the connectivity of a given linear-optical circuit. Using the algorithms, we study approximated simulations for local Haar-random linear-optical circuits. For equally spaced initial sources, we show that, when the circuit depth is less than the quadratic in the lattice spacing, the efficient simulation is possible with an exponentially small error. Notably, right after this depth, photons start to interfere each other and the algorithms’ complexity becomes subexponential in the number of sources, implying that there is a sharp transition of its complexity. Finally, when a circuit is sufficiently deep enough for photons to typically propagate to all modes, the complexity becomes exponential as generic sampling algorithms. We numerically implement a likelihood test with a recent Gaussian boson sampling experiment and show that the treewidth-based algorithm with a limited treewidth renders a larger likelihood than the experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Dependence of the electronic structure of the EuS/InAs interface on the bonding configuration

The EuS/InAs interface has recently attracted attention for the possibility of inducing magnetic exchange correlations in a strong spin-orbit semiconductor, which could be useful for topological quantum devices. We use density functional theory with a machine-learned Hubbard U correction [Yu et al., npj Comput. Mater. 6, 180 (2020)] to elucidate the effect of the bonding configuration at the interface on the electronic structure. For all interface configurations considered here, we find that the EuS valence band maximum (VBM) lies below the InAs VBM. In addition, dispersed states emerge at the top of the InAs VBM at the interface, which do not exist in either material separately. These states are contributed mainly by the InAs layer adjacent to the interface. They are localized at the interface and may be attributed to charge transfer from the EuS to the InAs. The interface configuration affects the position of the EuS VBM with respect to the InAs VBM, as well as the dispersion of the interface states. For all interface configurations studied here, the induced magnetic moment in the InAs is small. Our results suggest that this interface, in its coherent form studied here, may not be promising for inducing equilibrium magnetic properties in InAs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Stability and magnetic behavior of exfoliable nanowire one-dimensional materials

Low-dimensional materials can display enhanced electronic, magnetic, and quantum properties. Here we use the topological scaling algorithm to identify all sufficiently metastable materials in the Materials Project database to identify bulk crystals with one-dimensional (1D) structural motifs: Five hundred fifty-one crystals that are within 50 meV atom –1 of the thermodynamic hull display 1D motifs, where 293 of these contain d-valence elements, which we focus on in this work. After exfoliating nanowires from 263 of these materials and calculating their thermodynamic stability using density functional theory, 103 nanowires meet per-atom and per-Ångström thermodynamic stability criteria. We illustrate for three nanowire systems that a variety of local minima can be present in these systems, demonstrating one case of a Peierls distortion. The wires display a broad diversity of electronic and magnetic properties of these nanowires, with 14 metals, 7 half-metals, and 82 semiconductors and insulators, and 41 nanowires displaying magnetic moments ranging from 0.1 to 5μ B per d-valence species when assuming ferromagnetic order. A subset of these chains are investigated for the impact of magnetic ordering, identifying 1D FeCl 3 to be most stable in an antiferromagnetic state. The electronic and magnetic properties of the identified 1D materials could enable applications in spintronic and quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Intricate short-range order in GeSn alloys revealed by atomistic simulations with highly accurate and efficient machine-learning potentials

GeSn alloys hold promise for silicon-compatible integrated applications in electronics, photonics, and topological quantum devices. However, understanding their intricate structures using density functional theory (DFT) calculations is hindered by spatiotemporal constraints. To overcome this limitation, we develop highly accurate and efficient machine-learning interatomic potentials based on a neuroevolution potential approach with farthest point sampling on a comprehensive DFT data set. The application of the developed machine-learning potential in large-scale atomistic simulations bridges the spatiotemporal gap between modeling and advanced characterizations, and facilitates the discovery of structural intricacies in GeSn alloys. Through extensive statistical sampling, we identify a type of short-range order (SRO) that is distinguished by both its structural signature and electronic band gap from the SRO structure previously predicted. Modeling based on a large simulation cell reveals the coexistence of nano SRO domains with various degrees of ordering, demonstrating a complex spatial heterogeneity of SRO structure. Finally, our study not only reinforces the significance of fine-level structural information in alloys, but it also constitutes an effective framework for exploring SRO in a broad range of complex alloys based on highly accurate and effective machine-learning potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Classifying One-Dimensional Quantum States Prepared by a Single Round of Measurements

Measurements and feedback have emerged as powerful resources for creating many-body quantum states. However, a detailed understanding has been restricted to fixed-point representatives of phases of matter. Here, we go beyond this and characterize the patterns of many-body entanglement that can be deterministically created from measurement. Focusing on one spatial dimension, a framework is developed for the case where a single round of measurements is the only entangling operation. We show this creates matrix-product states and identify necessary and sufficient tensor conditions for preparability, which uniquely determine the preparation protocol. We use these conditions to both classify preparable quantum states and characterize their physical constraints. In particular, we find a trade-off between the richness of the preparable entanglement spectrum and correlation functions, which leads to a no-go theorem for preparing certain quantum states. More broadly, we connect properties of the preparation protocol to the resulting phase of matter, including trivial, symmetry-breaking, and symmetry-protected topological phases—for both uniform and modulated symmetries. This work offers a resource-theoretic perspective on preparable quantum entanglement and shows how to systematically create states of matter, away from their fixed points, in quantum devices. Published by the American Physical Society 2025

Sahay, Rahul (ORCID:0000000174579826)↗
DOE OSTI2026

Optimal filtering and generation of entangled photons for quantum applications in the presence of noise

Filtering is commonly used in quantum optics to reject noise photons, and also to enable interference between independent photons. However, filtering the joint spectrum of photon pairs can reduce the inherent coincidence probability or loss-independent heralding efficiency. Here we investigate filtering for multiphoton applications based on entanglement and interference (e.g., quantum teleportation). We multiplex C-band entangled photons and C-band classical communications into the same long-distance fibers, which enables scalable low-loss quantum networking but requires filtering of spontaneous Raman scattering noise from classical light. Using tunable-bandwidth filters, low-jitter detectors, and polarization filters, we distribute wavelength-degenerate time-bin entangled photons in the C band (1536.5 nm) over 25 km/25 km standard fibers (50 km) each carrying 10 Gbit/s C-band classical data signals. Narrow filtering enables milliwatt-level C-band power, which exceeds the power achieved by comparable studies by roughly an order of magnitude and could feasibly support terabit per second classical rates. We evaluate how performance depends on pump and filter bandwidths, multipair emission, filter shapes, loss, phase matching, and how quantum information is measured. We find a trade-off between reducing noise impact and increasing single-mode purity, and discuss mitigation methods toward optimal multiphoton applications. Importantly, these results apply to noise in free space and in quantum devices (sources, frequency converters, switches, detectors, etc.) and provide insight into filter-induced degradation of single-photon purity and rates even in noise-free environments.

Thomas, Jordan M. [Fermilab; Northwestern U.]↗
DOE OSTI2022

Benchmarking Quantum Processor Performance through Quantum Distance Metrics Over An Algorithm Suite

Quantum computing is poised to solve computational paradigms that classical computing could never feasibly reach. Tasks such as prime factorization to Quantum Chemistry are examples of classically difficult problems that have analogous algorithms that are sped up on quantum computers. To attain this computational advantage, we must first traverse the noisy intermediate scale quantum (NISQ) era, in which quantum processors suffer from compounding noise factors that can lead to unreliable algorithm induction producing noisy results. We describe QASMBench, a suite of QASM-level (Quantum assembly language) benchmarks that challenge all realisable angles of quantum processor noise. We evaluate a large portion of these algorithms by performing density matrix tomography on 14 IBMQ Quantum devices.

Stein, Samuel A.↗
DOE OSTI2025

Entanglement Benchmarking in Quantum Simulations of Spin Systems

We simulate quantum spin systems and measure entanglement using circuits tailored for near-term quantum computers. Traditional tools like entanglement entropy are limited to pure states and require full state tomography, making them impractical on current hardware. Instead, we employ the novel approach, Positive Partial Transpose (PPT) criterion to efficiently detect pairwise entanglement from two-spin reduced density matrices, applicable to both pure and mixed states. This method enables scalable entanglement detection, providing a practical route to study quantum correlations, phase transitions, and benchmark quantum devices.

Baul, Anshumitra [ORNL] (ORCID:0000000268947191)↗