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At least 1,315 records · Page 73

Optimization of global model composed of radial basis functions using the term-ranking approach

A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Investigating the Chinese postman problem on a quantum annealer

The recent availability of quantum annealers has fueled a new area of information technology where such devices are applied to address practically motivated and computationally difficult problems with hardware that exploits quantum mechanical phenomena. D-Wave annealers are promising platforms to solve these problems in the form of quadratic unconstrained binary optimization. Here we provide a formulation of the Chinese postman problem that can be used as a tool for probing the local connectivity of graphs and networks. We treat the problem classically with a tabu algorithm and simulated annealing, and using a D-Wave device. The efficiency of quantum annealing with respect to the simulated annealing has been demonstrated using the optimal time to solution metric. We systematically analyze computational parameters associated with the specific hardware. Our results clarify how the interplay between the embedding due to limited connectivity of the Chimera graph, the definition of logical qubits, and the role of spin-reversal controls the probability of reaching the expected solution

36 MATERIALS SCIENCE↗

Spin-transfer-torque efficiency enhanced by edge-damage of perpendicular magnetic random access memories

We numerically investigate the effect of magnetic and electrical damages at the edge of a perpendicular magnetic random access memory (MRAM) cell on the spin-transfer-torque (STT) efficiency that is defined by the ratio of thermal stability factor to switching current. We find that the switching mode of an edge-damaged cell is different from that of an undamaged cell, which results in a sizable reduction in the switching current. Together with a marginal reduction of the thermal stability factor of an edge-damaged cell, this feature makes the STT efficiency large. Our results suggest that a precise edge control is viable for the optimization of STT-MRAM.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

"Genetically Engineered" Nanoelectronics

The quantum mechanical functionality of nanoelectronic devices such as resonant tunneling diodes (RTDs), quantum well infrared-photodetectors (QWIPs), quantum well lasers, and heterostructure field effect transistors (HFETs) is enabled by material variations on an atomic scale. The design and optimization of such devices requires a fundamental understanding of electron transport in such dimensions. The Nanoelectronic Modeling Tool (NEMO) is a general-purpose quantum device design and analysis tool based on a fundamental non-equilibrium electron transport theory. NEW was combined with a parallelized genetic algorithm package (PGAPACK) to evolve structural and material parameters to match a desired set of experimental data. A numerical experiment that evolves structural variations such as layer widths and doping concentrations is performed to analyze an experimental current voltage characteristic. The genetic algorithm is found to drive the NEMO simulation parameters close to the experimentally prescribed layer thicknesses and doping profiles. With such a quantitative agreement between theory and experiment design synthesis can be performed.

Klimeck, Gerhard↗

Experimental demonstration of energy harvesting from the sky using the negative illumination effect of a semiconductor photodiode

We experimentally demonstrate electric power generation from the coldness of the universe directly, using the negative illumination effect when an infrared semiconductor diode faces the sky. Our theoretical model, accounting for the experimental results, indicates that the performance of such a power generation scheme is strongly influenced by the degree of matching between the responsivity spectrum and the atmospheric transparency window, as well as the quantum efficiency of the diode. A Shockley-Queisser analysis of an ideal optimized diode, taking into consideration the realistic transmissivity spectrum of the atmosphere, indicates the theoretical maximum power density of 3.99 W/m2 with the diode temperature at 293 K. The results here point to a pathway towards night-time power generation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum oscillations from the reconstructed Fermi surface in electron-doped cuprate superconductors

We have studied the electronic structure of electron-doped cuprate superconductors via measurements of high-field Shubnikov–de Haas oscillations in thin films. In optimally doped Pr 2-x Ce x CuO 4±δ and La 2-x Ce x CuO 4±δ , quantum oscillations indicate the presence of a small Fermi surface, demonstrating that electronic reconstruction is a general feature of the electron-doped cuprates, despite the location of the superconducting dome at very different doping levels. Negative high-field magnetoresistance is correlated with an anomalous low-temperature change in scattering that modifies the amplitude of quantum oscillations. This behavior is consistent with effects attributed to spin fluctuations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Achieving the Holevo bound via a bisection decoding protocol

We present a new decoding protocol to realize transmission of classical information through a quantum channel at asymptotically maximum capacity, achieving the Holevo bound and thus the optimal communication rate. At variance with previous proposals, our scheme recovers the message bit by bit, making use of a series of “yes-no” measurements, organized in bisection fashion, thus determining which codeword was sent in log{sub 2} N steps, N being the number of codewords.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhanced quantum efficiency of photoelectron emission, through surface textured metal electrodes

It is predicted that the quantum efficiency (QE) of photoelectron emission from metals may be enhanced, possibly by an order of magnitude, through optimized surface texture. Through extensive computational simulations, it is shown that the absorption enhancement in select surface groove geometries may be a dominant contributor to enhanced QE and corresponds to localized Fabry–Perot resonances. The inadequacy of extant analytical models in predicting the QE increase, and suggestions for further improvement, are discussed.

42 ENGINEERING↗

Fault tolerant filtering and fault detection for quantum systems driven by fields in single photon states

The purpose of this paper is to solve the fault tolerant filtering and fault detection problem for a class of open quantum systems driven by a continuous-mode bosonic input field in single photon states when the systems are subject to stochastic faults. Optimal estimates of both the system observables and the fault process are simultaneously calculated and characterized by a set of coupled recursive quantum stochastic differential equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimized Lie–Trotter–Suzuki decompositions for two and three non-commuting terms

Lie–Trotter–Suzuki decompositions are an efficient way to approximate operator exponentials exp ( t H ) when H is a sum of n (non-commuting) terms which, individually, can be exponentiated easily. They are employed in time-evolution algorithms for tensor network states, digital quantum simulation protocols, path integral methods like quantum Monte Carlo, and splitting methods for symplectic integrators in classical Hamiltonian systems. Here, we provide optimized decompositions up to order t 6 . The leading error term is expanded in nested commutators (Hall bases) and we minimize the 1-norm of the coefficients. For n = 2 terms, several of the optima we find are close to those in McLachlan (1995). Generally, our results substantially improve over unoptimized decompositions by Forest, Ruth, Yoshida, and Suzuki. We explain why these decompositions are sufficient to efficiently simulate any one- or two-dimensional lattice model with finite-range interactions. This follows by solving a partitioning problem for the interaction graph.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Universal scheme for finite-probability perfect transfer of arbitrary multispin states through spin chains

In combination with the theories of open system and quantum recovering measurement, we propose a quantum state transfer scheme using spin chains by performing two sequential operations: a projective measurement on the spins of ‘environment’ followed by suitably designed quantum recovering measurements on the spins of interest. The scheme allows perfect transfer of arbitrary multispin states through multiple parallel spin chains with finite probability. Our scheme is universal in the sense that it is state-independent and applicable to any model possessing spin–spin interactions. We also present possible methods to implement the required measurements taking into account the current experimental technologies. As applications, we consider two typical models for which the probabilities of perfect state transfer are found to be reasonably high at optimally chosen moments during the time evolution. - Highlights: • Scheme that can achieve perfect quantum state transfer is devised. • The scheme is state-independent and applicable to any spin-interaction models. • The scheme allows perfect transfer of arbitrary multispin states. • Applications to two typical models are considered in detail.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomically dispersed Pb ionic sites in PbCdSe quantum dot gels enhance room-temperature NO2 sensing

Abstract Atmospheric NO 2 is of great concern due to its adverse effects on human health and the environment, motivating research on NO 2 detection and remediation. Existing low-cost room-temperature NO 2 sensors often suffer from low sensitivity at the ppb level or long recovery times, reflecting the trade-off between sensor response and recovery time. Here, we report an atomically dispersed metal ion strategy to address it. We discover that bimetallic PbCdSe quantum dot (QD) gels containing atomically dispersed Pb ionic sites achieve the optimal combination of strong sensor response and fast recovery, leading to a high-performance room-temperature p-type semiconductor NO 2 sensor as characterized by a combination of ultra–low limit of detection, high sensitivity and stability, fast response and recovery. With the help of theoretical calculations, we reveal the high performance of the PbCdSe QD gel arises from the unique tuning effects of Pb ionic sites on NO 2 binding at their neighboring Cd sites.

36 MATERIALS SCIENCE↗

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Induced spin-accumulation and spin-polarization in a quantum-dot ring by using magnetic quantum dots and Rashba spin-orbit effect

The effect of magnetic contacts on spin-dependent electron transport and spin-accumulation in a quantum ring, which is threaded by a magnetic flux, is studied. The quantum ring is made up of four quantum dots, where two of them possess magnetic structure and other ones are subjected to the Rashba spin-orbit coupling. The magnetic quantum dots, referred to as magnetic quantum contacts, are connected to two external leads. Two different configurations of magnetic moments of the quantum contacts are considered; the parallel and the anti-parallel ones. When the magnetic moments are parallel, the degeneracy between the transmission coefficients of spin-up and spin-down electrons is lifted and the system can be adjusted to operate as a spin-filter. In addition, the accumulation of spin-up and spin-down electrons in non-magnetic quantum dots are different in the case of parallel magnetic moments. When the intra-dot Coulomb interaction is taken into account, we find that the electron interactions participate in separation between the accumulations of electrons with different spin directions in non-magnetic quantum dots. Furthermore, the spin-accumulation in non-magnetic quantum dots can be tuned in the both parallel and anti-parallel magnetic moments by adjusting the Rashba spin-orbit strength and the magnetic flux. Thus, the quantum ring with magnetic quantum contacts could be utilized to create tunable local magnetic moments which can be used in designing optimized nanodevices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Parameter estimation for chaotic systems using a hybrid adaptive cuckoo search with simulated annealing algorithm

This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Inherent limits on optimization and discovery in physical systems

Topological mapping of a large physical system on a graph, and its decomposition using universal measures are proposed. We find inherent limits to the potential for optimization of a given system and its approximate representations by motifs, and the ability to reconstruct the full system given approximate representations. The approximate representation of the system most suited for optimization may be different from that which most accurately describes the full system. - Highlights: • Graph-based approach to analyze full and partial representations of physical systems. • Direct link between a change in the physical system and complexity of the graph. • Inherent limits to the potential for optimization of a general system. • Inherent limits to the reconstruction of full system from partial representations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Reinforcement Learning for Volt-VAR Control in Power Distribution Systems

Volt-VAR control (VVC) is crucial in active distribution networks for optimizing voltage profiles and minimizing network losses. While traditional deep reinforcement learning (DRL) algorithms exhibit promise for VVC, they often require extensive computational resources to handle such a high-dimensional problem. As a potential solution, quantum reinforcement learning (QRL) algorithms integrate the computational capabilities of quantum computing into the DRL framework. However, existing QRL algorithms struggle with complex VVC problems due to the limitations of current quantum hardware. To bridge this gap, this paper proposes an innovative QRL algorithm featuring an end-to-end architecture that integrates a classical autoencoder, variational quantum circuits (VQCs), and classical post-processing layers. This design efficiently compresses high-dimensional grid states, enabling VQCs to leverage quantum advantages while producing multiple control device outputs tailored for VVC tasks. Numerical studies on three representative distribution systems verify the effectiveness and scalability of the proposed QRL algorithm, and demonstrate its enhanced performance over classical approaches with only approximately 1% of the parameters. Additionally, the robustness of our developed algorithm is validated through noisy quantum environments.

97 MATHEMATICS AND COMPUTING↗

Bandgap Engineering of InP QDs Through Shell Thickness and Composition

Fields as diverse as biological imaging and telecommunications utilize the unique photophysical and electronic properties of nanocrystal quantum dots (NQDs). The development of new NQD compositions promises material properties optimized for specific applications, while addressing material toxicity. Indium phosphide (InP) offers a 'green' alternative to the traditional cadmium-based NQDs, but suffers from extreme susceptibility to oxidation. Coating InP cores with more stable shell materials significantly improves nanocrystal resistance to oxidation and photostability. We have investigated several new InP-based core-shell compositions, correlating our results with theoretical predictions of their optical and electronic properties. Specifically, we can tailor the InP core-shell QDs to a type-I, quasi-type-II, or type-II bandgap structure with emission wavelengths ranging from 500-1300 nm depending on the shell material used (ZnS, ZnSe, CdS, or CdSe) and the thickness of the shell. Single molecule microscopy assessments of photobleaching and blinking are used to correlate NQD properties with shell thickness.

36 MATERIALS SCIENCE↗