Advanced Physics Research最新文献_第7页

Toward Solution-Time Advantage With Error-Mitigated Quantum Annealing for Combinatorial Optimization 收敛误差的量子退火在组合优化中的求解时间优势

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 Epub Date: 2026-03-14 DOI: 10.1002/apxr.202500216

Yushuang Sam Yang, Peter Tyson, Clement Chu, Anthony Bruce Murphy

{"title":"Toward Solution-Time Advantage With Error-Mitigated Quantum Annealing for Combinatorial Optimization","authors":"Yushuang Sam Yang, Peter Tyson, Clement Chu, Anthony Bruce Murphy","doi":"10.1002/apxr.202500216","DOIUrl":"https://doi.org/10.1002/apxr.202500216","url":null,"abstract":"Quantum annealing (QA) has the potential to solve complex optimization problems, but its broad adoption is hindered by qubit errors, which cause an exponential slowdown in computing the global optimal solution as problem size increases. To address this limitation, we present a novel post-processing error mitigation for optimization technique, known as SEMO (spin-error mitigation for optimization), designed to improve QA computational efficiency. Its effectiveness is demonstrated through a correlated 3D image segmentation model for material microstructures, formulated as a quadratic unconstrained binary optimization (QUBO) problem. The technique significantly reduces the computing time required to reach the global optimum solution, demonstrating a time-to-solution advantage over the standard D-Wave Systems Advantage QA, simulated annealing (SA), and other post-processing techniques. Because it operates at the fundamental QUBO level, this approach is applicable to a wide range of discrete combinatorial optimization problems that can be expressed in QUBO format. As the number of qubits in quantum computers continues to increase, this method will become increasingly impactful.","PeriodicalId":100035,"journal":{"name":"Advanced Physics Research","volume":"5 6","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.202500216","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches 推进手性光子超表面的机器学习优化：神经网络与遗传算法的比较研究

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 Epub Date: 2026-05-04 DOI: 10.1002/apxr.202500223

Davide Filippozzi, Alexandre Mayer, Nicolas Roy, Wei Fang, Arash Rahimi-Iman

{"title":"Advancing Machine Learning Optimization of Chiral Photonic Metasurface: Comparative Study of Neural Network and Genetic Algorithm Approaches","authors":"Davide Filippozzi, Alexandre Mayer, Nicolas Roy, Wei Fang, Arash Rahimi-Iman","doi":"10.1002/apxr.202500223","DOIUrl":"https://doi.org/10.1002/apxr.202500223","url":null,"abstract":"Chiral photonic metasurfaces provide unique capabilities for tailoring light–matter interactions, which are essential for next-generation photonic devices. Here, we report an advanced optimization framework that combines deep learning and evolutionary algorithms to significantly improve both the design and performance of chiral photonic nanostructures. Building on previous work utilizing a three-layer perceptron, reinforced learning, and a stochastic evolutionary algorithm with decaying changes and mass extinction for chiral photonic optimization, our study introduces a refined pipeline featuring a two-output neural network architecture to reduce the trade-off between high chiral dichroism (CD) and reflectivity. Additionally, we use an improved fitness function and efficient data augmentation techniques. A comparative analysis between a neural network (NN)-based approach and a genetic algorithm (GA) is presented for structures of different interface pattern depth, material combinations, and geometric complexity. We demonstrate a twice-higher CD and the impact of both the corner number and the refractive index contrast in the example of a GaP/air and PMMA/air metasurface as a result of superior optimization performance. Additionally, a substantial increase in the number of structures explored within limited computational resources is highlighted, with tailored spectral reflectivity suggested by our electromagnetic simulations, paving the way for chiral mirrors applicable to polarization-selective light–matter interaction studies.","PeriodicalId":100035,"journal":{"name":"Advanced Physics Research","volume":"5 6","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.202500223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Selective Sequestration of Toxic NOx Gases by P-Doped Graphene: A Density Functional Theory Study p掺杂石墨烯选择性封存有毒氮氧化物：密度泛函理论研究

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 Epub Date: 2026-03-02 DOI: 10.1002/apxr.202500236

Anwar Ali, Adnan Ali Khan, Iqtidar Ahmad, Yu-Jia Zeng

{"title":"Selective Sequestration of Toxic NOx Gases by P-Doped Graphene: A Density Functional Theory Study","authors":"Anwar Ali, Adnan Ali Khan, Iqtidar Ahmad, Yu-Jia Zeng","doi":"10.1002/apxr.202500236","DOIUrl":"https://doi.org/10.1002/apxr.202500236","url":null,"abstract":"Using DFT simulations, this study investigates the selective adsorption and sensing mechanism of phosphorus-doped graphene (P-grap) toward NOx (NO and NO2) molecules. The findings reveal that P doping introduces a significant spin density on the graphene surface, which enhances the interaction strength and increases the adsorption energy of NOx species compared to pristine graphene. The electronic structure analysis confirms that NOx adsorption markedly alters hybridization near the Fermi level, indicating a strong interaction and substantial modification of surface properties. The P-graph demonstrates exceptional selectivity for NOx, maintaining strong adsorption and electronic response while other common environmental gases (CO, CO2, NH3, SO2, and H2O) show negligible interaction, confirming its selective robust sensing capability. Furthermore, recovery time calculations suggest that the desorption of NOx molecules from the P-grap surface is feasible and rapid under temperature variation, ensuring reusability of the sensor material. Overall, the findings highlight that P-grap exhibits strong affinity, high sensitivity, and remarkable selectivity for NOx molecules while retaining fast recovery at room temperature. These properties suggest that P-grap is a promising candidate for next-generation gas sensors capable of operating efficiently under real atmospheric conditions.","PeriodicalId":100035,"journal":{"name":"Advanced Physics Research","volume":"5 6","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.202500236","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Hybrid Semi-Inverse Variational and Machine Learning Approach for the Schrödinger Equation 求解Schrödinger方程的半逆变分与机器学习混合方法

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 Epub Date: 2026-04-13 DOI: 10.1002/apxr.70127

Khalid Reggab, Houssam Eddine Hailouf, Kingsley Onyebuchi Obodo, Mireille Megnidio-Tchoukouegno, Mohammed Benali Kanoun, Souraya Goumri-Said

{"title":"A Hybrid Semi-Inverse Variational and Machine Learning Approach for the Schrödinger Equation","authors":"Khalid Reggab, Houssam Eddine Hailouf, Kingsley Onyebuchi Obodo, Mireille Megnidio-Tchoukouegno, Mohammed Benali Kanoun, Souraya Goumri-Said","doi":"10.1002/apxr.70127","DOIUrl":"https://doi.org/10.1002/apxr.70127","url":null,"abstract":"This study introduces a hybrid analytical–machine learning framework for solving the Schrödinger equation with complex potentials. The semi-inverse variational method is first used to generate highly accurate eigenfunctions and eigenenergies for both 1D radial potentials (Yukawa and Cornell) and a 2D coupled anharmonic oscillator. Based on these rigorous, physics-consistent results, we train supervised machine learning models; including Random Forest and Neural Network regressors; to predict energy eigenvalues across wide parameter ranges. Both models achieve near-perfect predictive accuracy (R2 > 0.999) with errors of only a few millielectronvolts, while preserving fundamental quantum-mechanical trends. Feature importance analysis confirms that the quantum number n and potential strength parameters dominate the energy scaling, in agreement with theoretical expectations. By integrating variational physics with data-driven emulation, this hybrid framework reduces computational cost by orders of magnitude; enabling rapid, high-throughput exploration of quantum systems across dimensions. The approach not only accelerates parameter screening but also serves as a discovery tool, uncovering emergent scaling laws and critical confinement behavior in mixed potentials. This synergy between analytical rigor and machine learning efficiency opens new pathways for quantum simulation, materials design, and the discovery of novel quantum phenomena.","PeriodicalId":100035,"journal":{"name":"Advanced Physics Research","volume":"5 6","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.70127","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148221915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Experimental Demonstration of Radio-Frequency Hong-Ou-Mandel Interference With Emulated Single-Photon States 模拟单光子态射频洪鸥-曼德尔干扰的实验论证

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 Epub Date: 2026-04-22 DOI: 10.1002/apxr.202500204

A. Sheleg, D. Vovchuk, K. Boiko, P. Ginzburg, G. Slepyan, A. Boag, A. Mikhalychev, A. Ulyanenkov, T. Salgals, D. Mogilevtsev

引用次数: 0

Issue Information (Adv. Phys. Res. 6/2026) 发行信息（物理广告）研究》6/2026)

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 DOI: 10.1002/apxr.70145

引用次数: 0

Work Versus Force: Simultaneous Processes for Describing Interactions 功与力：描述相互作用的同时过程

IF 2.8

Advanced Physics Research Pub Date : 2026-06-11 Epub Date: 2026-04-22 DOI: 10.1002/apxr.202500198

Grit Kalies, Duong D. Do, Cornelia Breitkopf

引用次数: 0

IF 2.8

Advanced Physics Research Pub Date : 2026-05-08

引用次数: 0

IF 2.8

Advanced Physics Research Pub Date : 2026-05-08

引用次数: 0

Manipulating Ferroelectricity Without Electrical Bias: A Perspective 操纵铁电性而不产生电偏：一个展望

IF 2.8

Advanced Physics Research Pub Date : 2026-04-09 Epub Date: 2026-02-19 DOI: 10.1002/apxr.202500224

Bixin Yan, Valentine Gillioz, Ipek Efe, Morgan Trassin

{"title":"Manipulating Ferroelectricity Without Electrical Bias: A Perspective","authors":"Bixin Yan, Valentine Gillioz, Ipek Efe, Morgan Trassin","doi":"10.1002/apxr.202500224","DOIUrl":"https://doi.org/10.1002/apxr.202500224","url":null,"abstract":"Ferroelectric materials are established candidates for beyond complementary metal-oxide-semiconductor technology, owing to their nonvolatile spontaneous electrical polarization. The recent boom in electric dipole texture engineering and manipulation in such materials has revealed exciting routes for controlling ferroelectric polarization, offering alternatives to the classical, sometimes challenging, application of electrical fields. In this short perspective, we shed light on electrode-free external stimuli enabling control over polar states in thin films. We bring awareness to the polarizing role of chemically engineered surface contributions and provide insights into the combination of chemical substitution and mechanical pressure, complementing the polar state tuning capabilities readily enabled by flexoelectricity. Finally, we describe recent developments in the optical modulation of polarization. Thus, our perspective aims to stimulate the advancement of alternative means to act on polarization states and facilitate the development of ferroelectric-based applications.","PeriodicalId":100035,"journal":{"name":"Advanced Physics Research","volume":"5 4","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://advanced.onlinelibrary.wiley.com/doi/epdf/10.1002/apxr.202500224","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147683762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0