IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-06-08 DOI: 10.1142/s2010324723400155

Tsung-Hsuan Tsai, YiChing Chen, Chin-Fu Nien

引用次数: 0

Dielectric properties of a phenanthrene-like nanoisland B14A10: Monte Carlo study 类菲纳米岛B14A10介电性能的蒙特卡罗研究

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-06-06 DOI: 10.1142/s2010324723500170

Z. Fadil, Chaitany Jayprakash Raorane, R. El Fdil, Seong Cheol Kim

引用次数: 0

Guest Editorial 客座编辑

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-06-01 DOI: 10.1142/s2010324723020010

G. Kurlyandskaya

引用次数: 0

The Prospects of Quantum Secure Direct Communication: An Overview 量子安全直接通信展望

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-30 DOI: 10.1142/s2010324723400143

Yao-Hsin Chou, Kuo-Chun Tseng, Shu-Yu Kuo

引用次数: 0

A theoretical analysis of spin-dependent tunneling in ZnO-based heterostructures zno基异质结构中自旋相关隧穿的理论分析

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-30 DOI: 10.1142/s2010324723500169

L. B. Chandrasekar, M. Karunakaran

引用次数: 0

Intelligent Hybrid Trading Strategies based on Quantum-inspired Algorithm 基于量子启发算法的智能混合交易策略

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-19 DOI: 10.1142/s2010324723400131

Shu-Yu Kuo, Yu-Chi Jiang, Yao-Hsin Chou

引用次数: 0

A Quantum States Preparation Method Based on Difference-Driven Reinforcement Learning 基于差分驱动强化学习的量子态制备方法

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-19 DOI: 10.1142/s2010324723500133

Wenjie Liu, Jing Xu, Bosi Wang

{"title":"A Quantum States Preparation Method Based on Difference-Driven Reinforcement Learning","authors":"Wenjie Liu, Jing Xu, Bosi Wang","doi":"10.1142/s2010324723500133","DOIUrl":"https://doi.org/10.1142/s2010324723500133","url":null,"abstract":"Due to the large state space of the two-qubit system, and the adoption of ladder reward function in the existing quantum state preparation methods, the convergence speed is slow and it is difficult to prepare the desired target quantum state with high fidelity under limited conditions. To solve the above problems, a difference-driven reinforcement learning (RL) algorithm for quantum state preparation of two-qubit system is proposed by improving the reward function and action selection strategy. Firstly, a model is constructed for the problem of preparing quantum states of a two-qubit system, with restrictions on the type of quantum gates and the time for quantum state evolution. In the preparation process, a weighted differential dynamic reward function is designed to assist the algorithm quickly obtain the maximum expected cumulative reward. Then, an adaptive [Formula: see text]-greedy action selection strategy is adopted to achieve a balance between exploration and utilization to a certain extent, thereby improving the fidelity of the final quantum state. The simulation results show that the proposed algorithm can prepare quantum state with high fidelity under limited conditions. Compared with other algorithms, it has different degrees of improvement in convergence speed and fidelity of the final quantum state.","PeriodicalId":54319,"journal":{"name":"Spin","volume":"abs/2309.16972 1","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"63845344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative study of spin pumping in epitaxial- and polycrystalline-NiO/Ni80Fe20 外延和多晶NiO/Ni80Fe20自旋泵浦的比较研究

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-12 DOI: 10.1142/s201032472340012x

Kacho Imtiyaz Ali Khan, Pankhuri Gupta, R. Agarwal, N. Chowdhury, P. Muduli

引用次数: 0

Oblivious algorithms for the Max-kAND Problem Max-kAND问题的遗忘算法

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-08 DOI: 10.48550/arXiv.2305.04438

Noah G. Singer

{"title":"Oblivious algorithms for the Max-kAND Problem","authors":"Noah G. Singer","doi":"10.48550/arXiv.2305.04438","DOIUrl":"https://doi.org/10.48550/arXiv.2305.04438","url":null,"abstract":"Motivated by recent works on streaming algorithms for constraint satisfaction problems (CSPs), we define and analyze oblivious algorithms for the Max-$k$AND problem. This generalizes the definition by Feige and Jozeph (Algorithmica '15) of oblivious algorithms for Max-DICUT, a special case of Max-$2$AND. Oblivious algorithms round each variable with probability depending only on a quantity called the variable's bias. For each oblivious algorithm, we design a so-called\"factor-revealing linear program\"(LP) which captures its worst-case instance, generalizing one of Feige and Jozeph for Max-DICUT. Then, departing from their work, we perform a fully explicit analysis of these (infinitely many!) LPs. In particular, we show that for all $k$, oblivious algorithms for Max-$k$AND provably outperform a special subclass of algorithms we call\"superoblivious\"algorithms. Our result has implications for streaming algorithms: Generalizing the result for Max-DICUT of Saxena, Singer, Sudan, and Velusamy (SODA'23), we prove that certain separation results hold between streaming models for infinitely many CSPs: for every $k$, $O(log n)$-space sketching algorithms for Max-$k$AND known to be optimal in $o(sqrt n)$-space can be beaten in (a) $O(log n)$-space under a random-ordering assumption, and (b) $O(n^{1-1/k} D^{1/k})$ space under a maximum-degree-$D$ assumption. Even in the previously-known case of Max-DICUT, our analytic proof gives a fuller, computer-free picture of these separation results.","PeriodicalId":54319,"journal":{"name":"Spin","volume":"24 1","pages":"15:1-15:19"},"PeriodicalIF":1.8,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83499538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Structural and Magnetic properties of Ni Nanoparticles Embedded Vinyl Polymer Nanocomposite Films Ni纳米粒子嵌入乙烯基聚合物纳米复合膜的结构和磁性能

IF 1.8 4区物理与天体物理

Spin Pub Date : 2023-05-05 DOI: 10.1142/s2010324723400118

S. Nagar, G. S. Mukherjee, M. Banerjee

引用次数: 0

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