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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Above room temperature multiferroic and magnetoelectric properties of (1‐Φ) PZTFT‐Φ CZFMO particulate composites

Magnetoelectric (ME) composites of suitable ferroelectric and magnetic materials can display elevated magnetic and ferroelectric operational temperatures, along with substantial ME coupling, compared to conventional single-phase multiferroics. Herein, we describe the synthesis of (1-Φ) PZTFT-Φ CZFMO, Φ = 0.1, 0.2, 0.3 (PZTFT: [0.6(PbZr 0.53 Ti 0.47 O 3 )–0.4(PbFe 0.5 Ta 0.5 )O 3 ] CZFMO: Co 0.6 Zn 0.4 Fe 1.7 Mn 0.3 O 4 )] particulate (0–3) composites and report on the magnetic as well as ferroelectric phase transitions and magnetoelectric coupling. The phase formation and the induced strain in these composites are investigated via Raman spectroscopy. A large bifurcation of the zero-field cooled-field cooled magnetization curves confirms the highly anisotropic behavior of the composites. These curves also identify spin glass behavior in the CZFMO phase at ≈230 K. The magnetic phase transition of the composite (Φ = 0.2) is reported to be ≈532 (± 10) K. The temperature dependent dielectric data displays the ferroelectric phase transitions from the PZTFT phase and the broad relaxation peak from the CZFMO phase. The quadratic relationship between the magneto-capacitance and the magnetization confirms the existence of biquadratic magnetoelectric coupling in the systems. The collective results are consistent with the presence of a direct magneto-electric effect in the composites, i.e., by the application of magnetic field, the magnetic phase is strained, and this induced strain is responsible for changes of ferroelectric order parameter in the piezoelectric phase. As a result, this attribute makes the current composite structure a promising candidate for multiferroic data storage and processing technologies.

Bhoi, Krishnamayee↗
DOE OSTI2025

Beyond-classical computation in quantum simulation

Quantum computers hold the promise of solving certain problems that lie beyond the reach of conventional computers. However, establishing this capability, especially for impactful and meaningful problems, remains a central challenge. Here, we show that superconducting quantum annealing processors can rapidly generate samples in close agreement with solutions of the Schrödinger equation. We demonstrate area-law scaling of entanglement in the model quench dynamics of two-, three-, and infinite-dimensional spin glasses, supporting the observed stretched-exponential scaling of effort for matrix-product-state approaches. We show that several leading approximate methods based on tensor networks and neural networks cannot achieve the same accuracy as the quantum annealer within a reasonable time frame. Thus, quantum annealers can answer questions of practical importance that may remain out of reach for classical computation.

King, Andrew D. [D-Wave Quantum Inc., Burnaby, BC ↗
NASA NTRS1985

ac susceptibility of thermally annealed and neutron irradiated Cu-Ni alloys

Thermal annealing and high-flux neutron irradiation are used to vary the degree of short-range atomic order in Cu-Ni alloys of composition 40, 50, and 60 at. pct Ni. The magnetic state is measured by ac magnetic susceptibility measurements. It is shown that annealing at 350 C causes significant changes in the susceptibility of all the samples. In the 50 and 60 at. pct Ni samples, the transition is broadened and extended to higher temperatures, while the 40 at. pct Ni sample changes from a paramagnetic system to a weakly ferromagnetic system. The neutron irradiation, in contrast to the thermal treatment, causes the development of smaller size cluster formations. The irradiated 60 at. pct Ni sample exhibits no change in the shape of its susceptibility curve from that of the quenched sample, whereas, the 40 pct alloy is changed, by irradiation, from a paramagnetic system to a spin-glass system.

Catchings, R. M., III↗
NASA NTRS1986

Intractable computations without local minima

An NP-complete problem which is not a spin-glass is exhibited. The NP-complete problem 3-satisfiability is also embedded into a continuous analog system with no hills in the energy landscape obstructing solution of the problem. There is, however, a large flat plateau. This shows how sculpting of the energy surfaces of continuous analog systems to remove hills may fail to aid solution of embedded combinatorial optimization problems.

Baum, Eric B.↗
NASA NTRS1990

Magnetic susceptibility of Inconel alloys 718, 625, and 600 at cryogenic temperatures

After a hydrogen fuel bleed valve problem on the Discovery Space Shuttle was traced to the strong magnetization of Inconel 718 in the armature of the linear variable differential transformer near liquid hydrogen temperatures, the ac magnetic susceptibility of three samples of Inconel 718 of slightly different compositions, one sample of Inconel 625, and on sample of Inconel 600 were measured as a function of temperature. Inconel 718 alloys are found to exhibit a spin glass state below 16 K. Inconel 600 exhibits three different magnetic phases, the lowest-temperature state (below 6 K) being somewhat similar to that of Inconel 718. The magnetic states of the Inconel alloys and their magnetic susceptibilities appear to be strongly dependent on the exact composition of the alloy.

Goldberg, Ira B.↗
NASA NTRS1993

Random interactions in higher order neural networks

Recurrent networks of polynomial threshold elements with random symmetric interactions are studied. Precise asymptotic estimates are derived for the expected number of fixed points as a function of the margin of stability. In particular, it is shown that there is a critical range of margins of stability (depending on the degree of polynomial interaction) such that the expected number of fixed points with margins below the critical range grows exponentially with the number of nodes in the network, while the expected number of fixed points with margins above the critical range decreases exponentially with the number of nodes in the network. The random energy model is also briefly examined and links with higher order neural networks and higher order spin glass models made explicit.

Baldi, Pierre↗
NASA NTRS2001

Improving Simulated Annealing by Recasting it as a Non-Cooperative Game

The game-theoretic field of COllective INtelligence (COIN) concerns the design of computer-based players engaged in a non-cooperative game so that as those players pursue their self-interests, a pre-specified global goal for the collective computational system is achieved "as a side-effect". Previous implementations of COIN algorithms have outperformed conventional techniques by up to several orders of magnitude, on domains ranging from telecommunications control to optimization in congestion problems. Recent mathematical developments have revealed that these previously developed game-theory-motivated algorithms were based on only two of the three factors determining performance. Consideration of only the third factor would instead lead to conventional optimization techniques like simulated annealing that have little to do with non-cooperative games. In this paper we present an algorithm based on all three terms at once. This algorithm can be viewed as a way to modify simulated annealing by recasting it as a non-cooperative game, with each variable replaced by a player. This recasting allows us to leverage the intelligent behavior of the individual players to substantially improve the exploration step of the simulated annealing. Experiments are presented demonstrating that this recasting improves simulated annealing by several orders of magnitude for spin glass relaxation and bin-packing.

Wolpert, David↗
NASA NTRS2017

Exponentially-Biased Ground-State Sampling of Quantum Annealing Machines with Transverse-Field Driving Hamiltonians

We study the performance of the D-Wave 2X quantum annealing machine on systems with well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass benchmark instance represents a difficult task, the gold standard for any optimization algorithm or machine is to sample all solutions that minimize the Hamiltonian with more or less equal probability. Our results show that while naive transverse-field quantum annealing on the D-Wave 2X device can find the ground-state energy of the problems, it is not well suited in identifying all degenerate ground-state configurations associated to a particular instance. Even worse, some states are exponentially suppressed, in agreement with previous studies on toy model problems [New J. Phys. 11, 073021 (2009)]. These results suggest that more complex driving Hamiltonians are needed in future quantum annealing machines to ensure a fair sampling of the ground-state manifold.

Quantum Annealing↗
NASA NTRS2017

QSPIN: A High Level Java API for Quantum Computing Experimentation

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Quantu↗
NASA NTRS2019

Size and Structure of the Sequence Space of Repeat Proteins

The coding space of protein sequences is shaped by evolutionary constraints set by requirements of function and stability. We show that the coding space of a given protein family— the total number of sequences in that family—can be estimated using models of maximum entropy trained on multiple sequence alignments of naturally occurring amino acid sequences. We analyzed and calculated the size of three abundant repeat proteins families, whose members are large proteins made of many repetitions of conserved portions of *30 amino acids. While amino acid conservation at each position of the alignment explains most of the reduction of diversity relative to completely random sequences, we found that correlations between amino acid usage at different positions significantly impact that diversity. We quantified the impact of different types of correlations, functional and evolutionary, on sequence diversity. Analysis of the detailed structure of the coding space of the families revealed a rugged landscape, with many local energy minima of varying sizes with a hierarchical structure, reminiscent of frustrated energy landscapes of spin glass in physics. This clustered structure indicates a multiplicity of subtypes within each family and suggests new strategies for protein design.

Jacopo Marchi↗
DOE OSTI2026

Self-consistent mean-field quantum approximate optimization

We introduce a self-consistent mean-field quantum optimization algorithm that approximates the ground state of classical Ising Hamiltonians. The algorithm decomposes the problem into independent subproblems and treats the interactions between them in a mean-field manner. These interactions are captured by a common environment, constructed self-consistently through a variational quantum circuit, and which modifies the subproblems to account for mutual influence while maintaining computational independence. Consequently, subproblems can be solved individually, avoiding the computational cost of the full problem. We explore the properties of the generated environment and assess the algorithm's performance through extensive numerical simulations on Sherrington-Kirkpatrick spin glasses. Furthermore, we apply it experimentally to a weighted maximum clique problem applied to molecular docking. This framework enables the solution of problems that would otherwise exceed the qubit and gate counts of current quantum hardware.

Dupont, Maxime [Rigetti Computing] (ORCID:00000001↗
DOE OSTI2026

Self-consistent mean-field quantum approximate optimization

We introduce a self-consistent mean-field quantum optimization algorithm that approximates the ground state of classical Ising Hamiltonians. The algorithm decomposes the problem into independent subproblems and treats the interactions between them in a mean-field manner. These interactions are captured by a common environment, constructed self-consistently through a variational quantum circuit, and which modifies the subproblems to account for mutual influence while maintaining computational independence. Consequently, subproblems can be solved individually, avoiding the computational cost of the full problem. We explore the properties of the generated environment and assess the algorithm's performance through extensive numerical simulations on Sherrington-Kirkpatrick spin glasses. Furthermore, we apply it experimentally to a weighted maximum clique problem applied to molecular docking. This framework enables the solution of problems that would otherwise exceed the qubit and gate counts of current quantum hardware.

Dupont, Maxime [Rigetti Computing] (ORCID:00000001↗
DOE OSTI2026

Self-consistent mean-field quantum approximate optimization

We introduce a self-consistent mean-field quantum optimization algorithm that approximates the ground state of classical Ising Hamiltonians. The algorithm decomposes the problem into independent subproblems and treats the interactions between them in a mean-field manner. These interactions are captured by a common environment, constructed self-consistently through a variational quantum circuit, and which modifies the subproblems to account for mutual influence while maintaining computational independence. Consequently, subproblems can be solved individually, avoiding the computational cost of the full problem. We explore the properties of the generated environment and assess the algorithm's performance through extensive numerical simulations on Sherrington-Kirkpatrick spin glasses. Furthermore, we apply it experimentally to a weighted maximum clique problem applied to molecular docking. This framework enables the solution of problems that would otherwise exceed the qubit and gate counts of current quantum hardware.

Dupont, Maxime [Rigetti Computing] (ORCID:00000001↗
DOE OSTI2026

Thermoelectric Behavior of Structurally Disordered Lanthanide and Actinide Silicides

Lanthanide and actinide intermetallic materials exhibit intriguing electronic, structural, and magnetic properties arising from their partially filled f orbitals. Strong f-electron correlations can significantly modify the electronic density of states, carrier scattering, and transport behavior, making these systems promising candidates for unconventional thermoelectric materials. In previous studies, single crystals of A1.33T4Al8Si2 (A = Ce, Th, U, Np; T = Co, Ni) were synthesized. This structure consists of ordered TAl2 corrugated double layers separated by disordered An–Si monolayers. The inherent disorder within the An–Si layers has been linked to unusual magnetic behavior, such as spin-glass phenomena, and is expected to strongly influence phonon scattering and charge-carrier transport relevant to thermoelectric performance. However, the thermoelectric properties of this material family have not previously been explored. In this work, DFT calculations were performed to evaluate the electronic density of states, band structures, and thermoelectric properties, including the effects of doping. To validate these predictions, Ce1.33Co4Al8Si2 single crystals were grown and experimentally characterized. Additionally, a new Yb1.33Co4Al8Si2 phase was synthesized and characterized using single-crystal XRD, SEM-EDS, magnetization measurements, and thermoelectric measurements. These results provide insight into structure–property relationships governing thermoelectric behavior in f-electron intermetallics and offer guidance for future thermoelectric materials.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
NASA NTRS1999

Innovative, Inexpensive Etching Technique Developed for Polymer Electro- Optical Structures

Electro-optic, polymer-based integrated optic devices for high-speed communication and computing applications offer potentially significant advantages over conventional inorganic electro-optic crystals. One key area of integrated optical technology--primary processing and fabrication--may particularly benefit from the use of polymer materials. However, as efforts concentrate on the miniaturization of electro-integrated circuit pattern geometries, the ability to etch fine features and smoothly sloped sidewalls is essential to make polymers useful for electro-integrated circuit applications. There are many existing processes available to etch polymer materials, but they all yield nearly vertical sidewalls. Vertical sidewalls are too difficult to reliably cover with a metal layer, and incomplete metalization degrades microwave performance, particularly at high frequency. However, obtaining a very sloped sidewall greatly improves the deposition of metal on the sidewall, leading to low-loss characteristics, which are essential to integrating these devices in highspeed electro-optic modulators. The NASA Lewis Research Center has developed in-house an inexpensive etching technique that uses a photolithography method followed by a simple, wet chemical etching process to etch through polymer layers. In addition to being simpler and inexpensive, this process can be used to fabricate smoothly sloped sidewalls by using a commercial none rodible mask: Spin-On-Glass. A commercial transparent material, Spin-On-Glass, uses processes and equipment similar to that for photoresist techniques.

Nguyen, Hung D.↗
DOE OSTI2024

Spin-orbit entanglement in the Color Glass Condensate

We compute the spin-orbit correlations of quarks and gluons at small-x and show that the helicity and the orbital angular momentum of individual partons are strongly anti-aligned even in unpolarized or spinless hadrons and nuclei. Combined with the fact that gluons in the Color Glass Condensate are linearly polarized, our finding indicates that the helicity and the orbital angular momentum of single gluons are maximally entangled in a quantum mechanical sense.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Classical combinatorial optimization scaling for random Ising models on 2D heavy-hex graphs

Motivated by near term quantum computing hardware limitations, combinatorial optimization problems that can be addressed by current quantum algorithms and noisy hardware with little or no overhead are used to probe capabilities of quantum algorithms such as the quantum approximate optimization algorithm. In this study, a specific class of near term quantum computing hardware defined combinatorial optimization problems, Ising models on heavy-hex graphs both with and without geometrically local cubic terms, are examined for their classical computational hardness via empirical computation time scaling quantification. Specifically the time-to-solution (TTS) metric using the classical heuristic simulated annealing is measured for finding optimal variable assignments (ground states), as well as the time required for the optimization software Gurobi to find an optimal variable assignment. Because of the sparsity of these Ising models, the classical algorithms are able to find optimal solutions efficiently even for large instances (i.e. 100 000 spin variables). The Ising models both with and without geometrically local cubic terms exhibit average-case linear-time or weakly quadratic scaling when solved exactly using Gurobi, and the Ising models with no cubic terms show evidence of exponential-time TTS scaling when sampled using simulated annealing. These findings point to the necessity of developing and testing more complex, namely more densely connected, optimization problems in order for quantum computing to ever have a practical advantage over classical computing. Our results are another illustration that different classical algorithms can indeed have exponentially different running times, thus making the identification of the best practical classical technique important in any quantum computing vs. classical computing comparison.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Nontrivial critical behavior at magnetic transitions: A case study of Sm 7 ⁢Pd 3

We present a comprehensive analysis of the critical behavior of Sm 7 ⁢Pd 3 in the vicinity of its second-order magnetoelastic transition at 𝑇 c =173 K. The critical exponents (CEs) 𝛽 and 𝛾, determined using both the standard convergence procedure and the average normalized slope (ANS) method, diverge at 𝑇 c –-a characteristic typically associated with first-order transitions. Notably, none of the established universality classes satisfactorily describe the critical behavior of Sm 7 ⁢Pd 3 , and we discuss the possible origins of this deviation in the context of the strong spin-lattice coupling intrinsic to the sample. We emphasize the importance of accurately selecting the critical temperature and magnetic field ranges to ensure robust critical behavior analysis, and propose a quantitative approach to assess the reliability of the extracted CEs. Additionally, we demonstrate that in the ANS method, the critical exponents 𝛽 and 𝛾 should be calculated separately using data for 𝑇 ⩽ 𝑇 c and 𝑇 ⩾ 𝑇 c , respectively. In conclusion, our findings underscore the need for a revised theoretical framework to accurately describe second-order magnetoelastic transitions.

Ferrimagnets↗