Prospects & Challenges of Colloidal Quantum Dot Laser Diodes [Slides]
Abstract not provided.
36 MATERIALS SCIENCE↗
SEARCH · Engineering Papers
Results for “quantum science”
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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Physical Mechanisms and Electric-Bias Control of Phase Transitions in Quasi-2D Charge-Density-Wave Quantum Materials
The goals of this fundamental science project, aimed at understanding the physical mechanisms and developing methods for electric-bias control of phase transitions in quasi-2D CDW materials, have been achieved. We focused on 1T-TaS2, one of the most interesting materials of this type, and demonstrated electrical gating of the I-V characteristics and hysteresis in this material. The demonstration of electrical gating of CDW phases in quasi-2D material was performed at RT. We have conducted experiments to separate the electric-field CDW switching from Joule heating-induced switching. This was an important development for 2D CDW materials. The project has led to a better understanding of the physical mechanisms behind the phase transitions and CDW depinning in quasi-2D van der Waals materials. We established that the CDW domain depinning in 1T-TaS2 does not lead to a strong increase in the collective current and accompanying narrow-band noise. We developed a technique that utilized the low-frequency noise measurements in such materials for monitoring the CDW phase transitions. In the experiments where 1T-TaS2 flakes were used in polymeric matrices, we verified the robustness of the phase transitions between the nearly commensurate and incommensurate CDW phases.
36 MATERIALS SCIENCE↗
Vortex guidance and transport in channeled pinning arrays
Here, we numerically examine vortices interacting with pinning arrays where a portion of the pinning sites have been removed in order to create coexisting regions of strong and weak pinning. The region without pinning sites acts as an easy-flow channel. For driving in different directions with respect to the channel, we observe distinct types of vortex flow. When the drive is parallel to the channel, the flow first occurs in the pin free region followed by a secondary depinning transition in the pinned region. At high vortex densities there is also an intermediate plastic flow phase due to the coupling between the weak and strong pinning regions. For driving applied perpendicular to the channel, we observe a jammed phase in which vortices accumulate on the boundary of the pinned region due to the vortex-vortex repulsion, while at higher drives the vortices begin to flow through the pinning array. For driving at an angle to the channel, depending on the filling we observe a drive-induced reentrant pinning effect as well as negative differential mobility which occurs when vortices move from the unpinned to the pinned portion of the sample.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Mechanical properties of zeolite-templated carbons from approximate density functional theory calculations
Zeolite-templated carbon (ZTC) is a unique porous carbonaceous material whose structure is ordered at the nanometre scale, enabling a representative periodic description at the atomistic level. Utilizing an existing, well-defined reference model for ZTCs, a structural library of varying compositions was developed by refinement using density-functional tight-binding (DFTB) potentials parameterized for materials science applications. We first determined the quantum chemical-refined structures of models with CH, CHO, CHON, CHOB, and CHOBN compositions with various degrees of heteroatom substitution. These structural models comprise the characteristic morphological features of highly porous carbon materials, such as open-blade surfaces, edges, saddles, and closed-strut formations, spanning a range of curvatures and characteristic sizes. Second, we carried out alternating compression and expansion of the CHO model unit cell to determine the lowest energy structure as well as to obtain its bulk modulus in order to demonstrate a close connection between macroscopic observations and atomic-scale structures. Further, the agreement between experimental measurements and the computational model is remarkable and demonstrates the power of approximate density functional theory as a cost-effective computational tool with chemical accuracy for the investigation of structure/property relationships in real-world carbon-based solids.
03 NATURAL GAS↗
Possibilistic simulation of quantum circuits by classical circuits
In a breakthrough work, Bravyi, Gosset, and König (BGK) [Science 362, 308 (2018)] unconditionally proved that constant-depth quantum circuits are more powerful than their classical counterparts. Here, their result is equivalent to saying that a particular family of constant-depth quantum circuits takes classical circuits at least Ω(logn) depth to “simulate,” in a certain sense. In our paper, we formalize their sense of simulation, which we call “possibilistic simulation” or “p-simulation,” and construct explicit classical circuits that can p-simulate any depth-d quantum circuit with Clifford and t T-gates in depth O(d+t). Our classical circuits use {NOT,AND,OR} gates of fan-in ≤ 2.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Vacancies in graphene: an application of adiabatic quantum optimization
Quantum annealers have grown in complexity to the point that quantum computations involving a few thousand qubits are now possible. In this paper, with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits the ground state as well as the excited states found by the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. Furthermore, this approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical–chemical interest.
36 MATERIALS SCIENCE↗
Quantum logic gate synthesis as a Markov decision process
Reinforcement learning has witnessed recent applications to a variety of tasks in quantum programming. The underlying assumption is that those tasks could be modeled as Markov decision processes (MDPs). Here, we investigate the feasibility of this assumption by exploring its consequences for single-qubit quantum state preparation and gate compilation. By forming discrete MDPs, we solve for the optimal policy exactly through policy iteration. We find optimal paths that correspond to the shortest possible sequence of gates to prepare a state or compile a gate, up to some target accuracy. Our method works in both the absence and presence of noise and compares favorably to other quantum compilation methods, such as the Ross–Selinger algorithm. This work provides theoretical insight into why reinforcement learning may be successfully used to find optimally short gate sequences in quantum programming.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Dynamical properties of a driven dissipative dimerized $S$ =1/2 chain
We consider the dynamical properties of a gapped quantum spin system coupled to the electric field of a laser, which drives the resonant excitation of specific phonon modes that modulate the magnetic interactions. Here, we deduce the quantum master equations governing the time-evolution of both the lattice and spin sectors, by developing a Lindblad formalism with bath operators providing an explicit description of their respective phonon-mediated damping terms. We investigate the nonequilibrium steady states (NESS) of the spin system established by a continuous driving, delineating parameter regimes in driving frequency, damping, and spin-phonon coupling for the establishment of physically meaningful NESS and their related nontrivial properties. Focusing on the regime of generic weak spin-phonon coupling, we characterize the NESS by their frequency and wave-vector content, explore their transient and relaxation behavior, and discuss the energy flow, the system temperature, and the critical role of the type of bath adopted. Our study lays a foundation for the quantitative modeling of experiments currently being designed to control coherent many-body spin states in quantum magnetic materials.
1-dimensional spin chains↗
Polariton panorama
Abstract In this brief review, we summarize and elaborate on some of the nomenclature of polaritonic phenomena and systems as they appear in the literature on quantum materials and quantum optics. Our summary includes at least 70 different types of polaritonic light–matter dressing effects. This summary also unravels a broad panorama of the physics and applications of polaritons. A constantly updated version of this review is available at https://infrared.cni.columbia.edu .
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Green's function methods for multiphysics simulations (Final Report)
Green's functions are important tools for analyzing mathematical properties of partial differential equations (PDEs), and for numerically solving PDEs, especially when equations for the same operator but with multiple right hand sides need to be solved simultaneously. This proposal aims at developing efficient and accurate numerical methods for computing Green's functions, which can be used to tackle a challenging question in multiphysics simulation of DOE-mission science problems: how to couple quantum physics with classical physics. The key mathematical difficulty is properly formulate a "boundary condition" for the region described by quantum physics, and conventional approaches often model such boundary conditions in an empirical way. The proposed Green's function methods use the Dirichlet-to-Neumann map to formulate a boundary condition that is non-empirical and can couple the quantum and classical regions in an in principle exact way. The key ingredient of the new methods is to construct the Dirichlet-to-Neumann map in an efficient, accurate and versatile manner. The new methods have provably low complexity and are ideally suited for massively parallel and emerging many-core computational systems.
97 MATHEMATICS AND COMPUTING↗
NEXUS Scalable and Distributed Next-Generation Avionics Bus for Space Missions
A paper discusses NEXUS, a common, next-generation avionics interconnect that is transparently compatible with wired, fiber-optic, and RF physical layers; provides a flexible, scalable, packet switched topology; is fault-tolerant with sub-microsecond detection/recovery latency; has scalable bandwidth from 1 Kbps to 10 Gbps; has guaranteed real-time determinism with sub-microsecond latency/jitter; has built-in testability; features low power consumption (< 100 mW per Gbps); is lightweight with about a 5,000-logic-gate footprint; and is implemented in a small Bus Interface Unit (BIU) with reconfigurable back-end providing interface to legacy subsystems. NEXUS enhances a commercial interconnect standard, Serial RapidIO, to meet avionics interconnect requirements without breaking the standard. This unified interconnect technology can be used to meet performance, power, size, and reliability requirements of all ranges of equipment, sensors, and actuators at chip-to-chip, board-to-board, or box-to-box boundary. Early results from in-house modeling activity of Serial RapidIO using VisualSim indicate that the use of a switched, high-performance avionics network will provide a quantum leap in spacecraft onboard science and autonomy capability for science and exploration missions.
He, Yutao↗
Simultaneous prediction of structural properties in epitaxially–grown GaN with quantum and conventional multi–output learning algorithms
Hundreds of GaN thin film crystal plasma–assisted molecular beam epitaxy synthesis experiment records spanning two decades were organized into a dataset correlating the growth experiment design parameters with discrete, binary determinations of crystallinity and surface morphology. Conventional data science techniques as well as both quantum and classical multi–output supervised machine learning algorithms were implemented to investigate the relationships between the operating parameter data and the structural figures of merit. Correlation coefficients, decision tree nodes, p–values, and SHAP values all support substrate temperature and gallium effusion cell conditions as being statistically significant for simultaneously influencing GaN crystallinity and surface morphology. Here, a conventional deep neural network learned best from the data, followed by a quantum–classical hybrid gradient boosting algorithm. When combined with calculations of uncertainty intervals based on VennAbers predictors, machine learning predictions of both structural properties show good agreement with results reported in published experimental literature.
36 MATERIALS SCIENCE↗
Anomalous ultrafast all-optical Hall effect in gapped graphene
We propose an ultrafast all-optical anomalous Hall effect in two-dimensional (2D) semiconductors of hexagonal symmetry such as gapped graphene (GG), transition metal dichalcogenides (TMDCs), and hexagonal boron nitride (h-BN). To induce such an effect, the material is subjected to a sequence of two strong-field single-optical-cycle pulses: A chiral pump pulse followed within a few femtoseconds by a probe pulse linearly polarized in the armchair direction of the 2D lattice. Due to the effect of topological resonance, the first (pump) pulse induces a large chirality (valley polarization) in the system, while the second pulse generates a femtosecond pulse of the anomalous Hall current. The proposed effect is fundamentally the fastest all-optical anomalous Hall effect possible in nature. It can be applied to ultrafast all-optical storage and processing of information, both classical and quantum.
36 MATERIALS SCIENCE↗
HamPerf: A Hamiltonian-Oriented Approach to Quantum Benchmarking
Quantum computing technologies are undergoing rapid development. The different qubit modalities being considered for quantum computing each have their strengths and weaknesses, making it challenging to compare their performance relative to each other and the state-of-the-art in classical high-performance computing. To better understand the utility of a given quantum processor and to assess when and how it will be able to advance the frontiers of computational science, researchers need a robust approach to quantum benchmarking. A variety of approaches have been proposed, many of which characterize the presence of noise in current quantum devices. These efforts include component-level performance metrics, such as randomized benchmarking and gate set tomography; high-level application-dependent metrics; and devicelevel metrics, such as the Quantum Volume. However, it remains unclear how low-level metrics, such as fidelities and decoherence times, and global device metrics, such as Quantum Volume, relate to the computational utility and practical limitations of quantum processors to solve useful problems. In this paper, we describe our Hamiltonian-oriented approach to quantum benchmarking called HamPerf. Where previous application-dependent approaches specify a suite of benchmarking circuits inspired by applications, we place the problem Hamiltonian at the center. Our strategy allows us to probe the computational performance of a quantum processor on standardized and relevant problem sets, agnostic of the algorithms and hardware used to solve them; it also provides fundamental insights into how device characteristics correlate with computational utility.
Butko, Anastasiia↗
Investigation of Exciton Delocalization and Exciton Coherence in Chromophores and Acoustic Nanostructures
Quantum materials have a rich potential for providing transformative energy technologies ranging from new energy efficient computation paradigms to lossless energy transport across the national grid. The field of quantum materials, however, is still in its infancy with many quantum materials systems requiring cyrogenic temperatures to be viable. Few viable, room-temperature quantum materials systems have been identified; therefore, identifying additional such systems is vitally important. This state of the science combined with the low number of potential systems that exhibit room-temperature quantum character make this field of research fertile ground for EPSCoR states (states eligible for funding under the Established Program to Stimulate Competitive Research program) such as Idaho to compete on a national level. As a result, this project proposed and accomplished two main goals in advancing two room-temperature quantum materials systems: (1) advance the science for demonstrating room temperature exciton delocalization in two excitonic systems and (2) build capacity and expertise in developing and understanding quantum materials at both Boise State University and Idaho National Laboratory. The work at Boise State focused mainly on the use of nucleic acid self-assembled chromophore molecule networks that offer a much easier and mature approach to construct aggregates of chromophores that can be tailored to specific two-dimensional and three-dimensional geometries and allow exciton manipulation towards achieving room-temperature quantum computation. A second complementary effort performed at Boise State and INL focused on confining excitons on quantum length scales using coherent surface acoustic phonons
36 MATERIALS SCIENCE↗
Highly Emissive Semi-Ladder-Type Copolymers, Aggregation State, and Solution-Processed Organic Light-Emitting Transistor
An organic light-emitting transistor (OLET) integrates the logic function of a field-effect transistor (FET) with electroluminescence of a light-emitting diode (LED) into a single device. This has the potential to play an important role in smart displays, electrically pumped organic laser, and other flexible electronic devices. For achieving high-performance solution-processed OLET, three semiladder copolymers—TPTI-CC, TPTI-C, and TPTI-F—were developed in this study. It was found that variation in the chemical structure lead to significant differences in energy level, emission color, and intermolecular aggregation. High photoluminescence quantum yields (PLQY) was obtained in these three polymers. Solution-processed trilayered OLET devices were fabricated, which exhibited strong electroluminescence, balanced charge mobility, and external quantum efficiency (EQE) of 2.8%.
36 MATERIALS SCIENCE↗
Evolution of short-range magnetic correlations in ferromagnetic Ni-V alloys
Here we experimentally study how the magnetic correlations develop in a binary alloy close to the ferromagnetic quantum critical point with small-angle neutron scattering (SANS). Upon alloying the itinerant ferromagnet nickel with vanadium, the ferromagnetic order is continuously suppressed. The critical temperature T c vanishes when vanadium concentrations reach the critical value of x c =0.116 indicating a quantum critical point separating the ferromagnetic and paramagnetic phases. Earlier magnetization and μSR data have indicated the presence of magnetic inhomogeneities in Ni 1-x V x and, in particular, recognize the magnetic clusters close to x c , on the paramagnetic and on the ferromagnetic sides with nontrivial dynamical properties [R. Wang et al., Phys. Rev. Lett. 118, 267202 (2017)]. We present the results of SANS study with full polarization analysis of polycrystalline Ni 1-x V x samples with x=0.10 and x=0.11 with low critical temperatures T c <50 K. For both Ni-V samples close to x c we find isotropic magnetic short-range correlations on the nanometer scale persisting at low temperatures. They are suppressed gradually in higher magnetic fields. In addition, signatures of long-range ordered magnetic domains are present below T c . The fraction of these magnetic clusters embedded in the ferromagnetic ordered phase grows toward x c and agrees well with the cluster fraction estimate from the magnetization and μSR data. Our SANS studies provide new insights into the nature of the inhomogeneities in a ferromagnetic alloy close to a quantum critical point.
36 MATERIALS SCIENCE↗
Quantum Memristors in Frequency-Entangled Optical Fields
A quantum memristor is a passive resistive circuit element with memory, engineered in a given quantum platform. It can be represented by a quantum system coupled to a dissipative environment, in which a system–bath coupling is mediated through a weak measurement scheme and classical feedback on the system. In quantum photonics, such a device can be designed from a beam splitter with tunable reflectivity, which is modified depending on the results of measurements in one of the outgoing beams. Here, we show that a similar implementation can be achieved with frequency-entangled optical fields and a frequency mixer that, working similarly to a beam splitter, produces state superpositions. We show that the characteristic hysteretic behavior of memristors can be reproduced when analyzing the response of the system with respect to the control, for different experimentally attainable states. Since memory effects in memristors can be exploited for classical and neuromorphic computation, the results presented in this work could be a building block for constructing quantum neural networks in quantum photonics, when scaling up.
36 MATERIALS SCIENCE↗