EAGER: Electrodynamic modeling of nanophotonic structures with two-level systems
EAGER:两级系统纳米光子结构的电动力学建模
基本信息
- 批准号:1641006
- 负责人:
- 金额:$ 10万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-08-15 至 2019-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Abstract Title: Electrodynamic simulation software for modelling the quantum effects in hybrid optoelectronic devices. Nontechnical Electrodynamic simulation software is indispensable in designing optoelectronic devices. It is used to predict and optimize device performance. Conventional simulation software solves the Maxwell's equations, which govern the propagation of light. It is designed for classical devices, which means that it does not include quantum effects. In recent years, quantum effects have become increasingly important in miniaturized optical devices. For example, a quantum dot, an element that can absorb or emit a single photon, can be used as an extremely energy-efficient switch. Such devices cannot be modelled using existing electrodynamic simulation tools. The project will develop a new simulation tool to incorporate quantum effects into classical electrodynamic simulation. To achieve this goal, the project will research a new quantum scattering theory that can interface with the classical Maxwell's equations. The result of the project includes a general-purpose simulator that allows scientists and engineers to efficiently explore quantum effects for next-generation optoelectronic devices. Preliminary studies show that intriguing quantum effects in this new design space could be used in fast and secure communication, renewable energy sources, and medical imaging. These technological areas are of significant societal benefits. The software development will also bring significant educational benefits, particularly through an online open-source platform. New opportunities will be created for K-12 students to learn light sciences as well as scientific programming through an integrated research and education program.TechnicalThis project will develop a general-purpose, open-source simulation tool for modeling hybrid photonic devices. Hybrid devices integrate complex nanophotonic structures with quantum two-level systems. These quantum elements enable unconventional functionalities, such as low-power optical switching, quantum information processing, and dynamic wave-front generation. However, the numerical modeling of hybrid devices is extremely difficult because both the Maxwell's equations and the Schrodinger equation must be solved simultaneously. Analytical methods do exist today, but they are only suitable for low dimensional problems such as those in cavity and waveguide quantum electrodynamics. The project will develop a numerical tool for generic modelling of hybrid devices. It will first develop a non-perturbative quantum scattering theory to model the transport of Fock-state photons in three dimensional spaces. The theory explicitly includes the spatial degrees of freedom of photons, which makes it possible to be directly integrated into classical electrodynamic simulation. Based on the theory, numerical simulation software will be implemented and will be released as an open-source project.
摘要标题:电动力学模拟软件模拟混合光电器件中的量子效应。非技术性的电动力学仿真软件在光电子器件的设计中是必不可少的。它用于预测和优化器件性能。传统的模拟软件求解控制光传播的麦克斯韦方程组。它是为经典设备设计的,这意味着它不包括量子效应。近年来,量子效应在小型化光学器件中变得越来越重要。例如,量子点,一种可以吸收或发射单个光子的元素,可以用作极其节能的开关。这样的设备不能使用现有的电动模拟工具建模。该项目将开发一种新的模拟工具,将量子效应纳入经典电动力学模拟。为了实现这一目标,该项目将研究一种新的量子散射理论,该理论可以与经典的麦克斯韦方程相结合。该项目的成果包括一个通用模拟器,使科学家和工程师能够有效地探索下一代光电器件的量子效应。初步研究表明,这个新设计空间中有趣的量子效应可用于快速安全的通信、可再生能源和医学成像。这些技术领域具有重大的社会效益。软件开发还将带来重大的教育效益,特别是通过在线开源平台。通过一个综合的研究和教育项目,将为K-12学生学习光科学和科学编程创造新的机会。TechnicalThis项目将开发一个通用的开源模拟工具,用于模拟混合光子器件。混合器件将复杂的纳米光子结构与量子二能级系统集成在一起。这些量子元件实现了非常规功能,例如低功率光开关、量子信息处理和动态波前生成。然而,混合器件的数值模拟是非常困难的,因为麦克斯韦方程和薛定谔方程必须同时求解。解析方法今天确实存在,但它们只适用于低维问题,如腔和波导量子电动力学。该项目将开发一种数字工具,用于混合装置的通用建模。它将首先发展一个非微扰量子散射理论来模拟Fock态光子在三维空间中的输运。该理论明确地包括光子的空间自由度,这使得它可以直接集成到经典电动力学模拟。基于该理论,将实施数值模拟软件,并将作为开源项目发布。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Zongfu Yu其他文献
Optimization of Nonlinear Nanophotonic Media for Artificial Neural Inference
用于人工神经推理的非线性纳米光子介质的优化
- DOI:
10.23919/cleo.2019.8750328 - 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
Erfan Khoram;A. Chen;Dianjing Liu;Qiqi Wang;Ming Yuan;Zongfu Yu - 通讯作者:
Zongfu Yu
The Babar Collaboration
巴巴尔合作
- DOI:
- 发表时间:
2000 - 期刊:
- 影响因子:0
- 作者:
B. Aubert;D. Boutigny;J. Gaillard;A. Hicheur;Y. Karyotakis;J. Lees;P. Robbe;V. Tisserand;A. Zghiche;A. Palano;A. Pompili;Jc Chen;N. Qi;G. Rong;Ping Wang;Y. Zhu;G. Eigen;I. Ofte;B. Stugu;G. Abrams;A. Borgland;A. Breon;D. Brown;J. Button‐Shafer;R. Cahn;E. Charles;M. Gill;A. Gritsan;Y. Groysman;R. Jacobsen;R. Kadel;J. Kadyk;L. Kerth;Y. Kolomensky;J. Kral;C. Leclerc;M. Levi;G. Lynch;L. Mir;P. Oddone;T. Orimoto;M. Pripstein;N. Roe;A. Romosan;M. Ronan;V. Shelkov;A. Telnov;W. Wenzel;T. Harrison;C. Hawkes;D. Knowles;S. O’Neale;R. Penny;A. Watson;N. Watson;T. Deppermann;K. Goetzen;H. Koch;B. Lewandowski;K. Peters;H. Schmuecker;M. Steinke;N. Barlow;W. Bhimji;J. Boyd;N. Chevalier;P. Clark;W. Cottingham;C. Mackay;F. Wilson;K. Abe;C. Hearty;T. Mattison;J. McKenna;D. Thiessen;S. Jolly;A. Mckemey;V. Blinov;A. Bukin;A. Buzykaev;V. Golubev;V. Ivanchenko;A. Korol;E. Kravchenko;A. Onuchin;S. Serednyakov;Y. Skovpen;A. Yushkov;D. Best;M. Chao;D. Kirkby;A. Lankford;M. Mandelkern;S. McMahon;D. Stoker;C. Buchanan;S. Chun;H. Hadavand;E. Hill;D. MacFarlane;H. Paar;S. Prell;S. Rahatlou;G. Raven;V. Sharma;J. Berryhill;C. Campagnari;B. Dahmes;P. Hart;N. Kuznetsova;S. Levy;O. Long;M. Mazur;J. Richman;W. Verkerke;J. Beringer;A. Eisner;M. Grothe;C. Heusch;W. Lockman;T. Pulliam;T. Schalk;R. Schmitz;B. Schumm;A. Seiden;M. Turri;W. Walkowiak;David C Williams;M. Wilson;E. Chen;G. Dubois;A. Dvoretskii;D. Hitlin;F. Porter;A. Ryd;A. Samuel;Shengxiang Yang;S. Jayatilleke;G. Mancinelli;B. Meadows;M. Sokoloff;T. Barillari;P. Bloom;W. Ford;U. Nauenberg;A. Olivas;P. Rankin;J. Roy;J. Smith;W. V. Hoek;L. Zhang;J. Harton;T. Hu;M. Krishnamurthy;A. Soffer;W. Toki;R. Wilson;J. Zhang;D. Altenburg;T. Brandt;J. Brose;T. Colberg;M. Dickopp;R. Dubitzky;A. Hauke;E. Mały;R. Müller;S. Otto;K. Schubert;R. Schwierz;B. Spaan;L. Wilden;D. Bernard;G. Bonneaud;F. Brochard;J. Cohen;S. Ferrag;S. T’Jampens;C. Thiebaux;G. Vasileiadis;M. Verderi;A. Anjomshoaa;R. Bernet;A. Khan;D. Lavin;F. Muheim;S. Playfer;J. Swain;J. Tinslay;M. Falbo;C. Borean;C. Bozzi;L. Piemontese;A. Sarti;E. Treadwell;F. Anulli;R. Baldini;A. Calcaterra;R. Sangro;D. Falciai;G. Finocchiaro;P. Patteri;I. Peruzzi;M. Piccolo;A. Zallo;S. Bagnasco;A. Buzzo;R. Contri;G. Crosetti;M. Vetere;M. Macrì;M. Monge;F. Pastore;C. Patrignani;E. Robutti;A. Santroni;S. Tosi;S. Bailey;M. Morii;R. Bartoldus;G. Grenier;U. Mallik;J. Cochran;H. Crawley;J. Lamsa;W. Meyer;E. Rosenberg;J. Yi;M. Davier;G. Grosdidier;A. Hocker;H. Lacker;S. Laplace;F. Diberder;V. Lepeltier;A. Lutz;T. Petersen;S. Plaszczynski;M. Schune;L. Tantôt;S. Trincaz;G. Wormser;R. Bionta;V. Brigljevic;D. Lange;K. Bibber;D. Wright;A. Bevan;J. Fry;E. Gabathuler;R. Gamet;M. George;M. Kay;D. Payne;R. Sloane;C. Touramanis;M. Aspinwall;D. Bowerman;P. Dauncey;U. Egede;I. Eschrich;G. Morton;J. Nash;P. Sanders;D. Smith;G. Taylor;J. Back;G. Bellodi;P. Dixon;P. Harrison;R. Potter;H. Shorthouse;P. Strother;P. Vidal;G. Cowan;H. Flaecher;S. George;M. Green;A. Kurup;C. Marker;T. Mcmahon;S. Ricciardi;F. Salvatore;G. Vaitsas;M. Winter;Deborah M. Brown;C. Davis;J. Allison;R. Barlow;A. Forti;F. Jackson;G. Lafferty;A. Lyon;N. Savvas;J. Weatherall;J. Williams;A. Farbin;A. Jawahery;V. Lillard;D. Roberts;J. Schieck;G. Blaylock;C. Dallapiccola;K. Flood;S. Hertzbach;R. Kofler;V. Koptchev;T. Moore;H. Staengle;S. Willocq;B. Brau;R. Cowan;G. Sciolla;F. Taylor;R. Yamamoto;M. Milek;P. Patel;F. Palombo;J. Bauer;L. Cremaldi;V. Eschenburg;R. Kroeger;J. Reidy;D. Sanders;D. Summers;C. Hast;P. Taras;H. Nicholson;N. Cavallo;G. Nardo;F. Fabozzi;C. Gatto;L. Lista;P. Paolucci;D. Piccolo;C. Sciacca;J. LoSecco;J. Alsmiller;T. Gabriel;J. Brau;R. Frey;M. Iwasaki;C. Potter;N. Sinev;D. Strom;E. Torrence;F. Colecchia;A. Dorigo;F. Galeazzi;M. Margoni;M. Morandin;M. Posocco;M. Rotondo;F. Simonetto;R. Stroili;C. Voci;M. Benayoun;H. Briand;J. Chauveau;P. David;C. D. Vaissière;L. Buono;O. Hamon;P. Leruste;J. Ocariz;M. Pivk;L. Roos;J. Stark;P. Manfredi;V. Re;V. Speziali;L. Gladney;Q. Guo;J. Panetta;C. Angelini;G. Batignani;S. Bettarini;M. Bondioli;F. Bucci;G. Calderini;E. Campagna;M. Carpinelli;F. Forti;M. Giorgi;A. Lusiani;G. Marchiori;F. Martinez;M. Morganti;N. Neri;E. Paoloni;M. Rama;G. Rizzo;F. Sandrelli;G. Triggiani;J. Walsh;M. Haire;D. Judd;K. Paick;L. Turnbull;D. Wagoner;J. Albert;N. Danielson;P. Elmer;C. Lu;V. Miftakov;J. Olsen;S. Schaffner;A. Smith;A. Tumanov;E. Varnes;F. Bellini;G. Cavoto;D. Re;R. Faccini;F. Ferrarotto;F. Ferroni;Emilio Leonardi;S. Morganti;G. Piredda;F. Tehrani;M. Serra;C. Voena;S. Christ;G. Wagner;R. Waldi;T. Adye;N. Groot;B. Franek;N. Geddes;G. Gopal;S. Xella;R. Aleksan;S. Emery;A. Gaidot;P. Giraud;G. D. Monchenault;W. Kozanecki;M. Langer;G. London;B. Mayer;G. Schott;B. Serfass;G. Vasseur;C. Yéche;M. Zito;M. Purohit;A. Weidemann;F. Yumiceva;I. Adam;D. Aston;N. Berger;A. Boyarski;M. Convery;D. Coupal;D. Dong;J. Dorfan;W. Dunwoodie;R. Field;T. Glanzman;S. Gowdy;E. Grauges;T. Haas;T. Hadig;V. Halyo;T. Himel;T. Hryn'ova;M. Huffer;W. Innes;C. Jessop;M. Kelsey;P. Kim;M. Kocian;U. Langenegger;D. Leith;S. Luitz;V. Luth;H. Lynch;H. Marsiske;S. Menke;R. Messner;D. Muller;C. O'grady;V. Ozcan;A. Perazzo;M. Perl;S. Petrak;H. Quinn;B. Ratcliff;S. Robertson;A. Roodman;A. Salnikov;T. Schietinger;R. Schindler;J. Schwiening;G. Simi;A. Snyder;A. Soha;S. Spanier;J. Stelzer;D. Su;M. Sullivan;H. Tanaka;J. Va’vra;S. Wagner;M. Weaver;A. Weinstein;W. Wisniewski;D. Wright;C. Young;P. Burchat;C. Cheng;T. Meyer;C. Roat;R. Henderson;W. Bugg;H. Cohn;J. Izen;I. Kitayama;X. Lou;F. Bianchi;M. Bona;D. Gamb;L. Bosisio;G. Ricca;S. Dittongo;L. Lanceri;P. Poropat;L. Vitale;G. Vuagnin;R. Panvini;S. Banerjee;C. Brown;D. Fortin;P. Jackson;R. Kowalewski;J. Roney;H. Band;S. Dasu;M. Datta;A. Eichenbaum;H. Hu;J. Johnson;R. Liu;F. Lodovico;A. Mohapatra;Y. Pan;R. Prepost;I. Scott;S. Sekula;J. V. Wimmersperg;Jie Wu;S. L. Wu;Zongfu Yu;H. Neal - 通讯作者:
H. Neal
Controlling light with dynamic photonic structures
用动态光子结构控制光
- DOI:
10.1109/leos.2008.4688650 - 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
S. Fan;Zongfu Yu;C. Otey;M. Povinelli - 通讯作者:
M. Povinelli
Nonreciprocal Thermal Emitters Using Metasurfaces with Multiple Diffraction Channels
使用具有多个衍射通道的超表面的不可逆热发射器
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:4.6
- 作者:
B. Zhao;Jiahui Wang;Zhexin Zhao;Cheng Guo;Zongfu Yu;S. Fan - 通讯作者:
S. Fan
SAFT: Shotgun advancing front technique for massively parallel mesh generation on graphics processing unit
SAFT:Shotgun 先进的图形处理单元大规模并行网格生成前端技术
- DOI:
10.1002/nme.7038 - 发表时间:
2022 - 期刊:
- 影响因子:2.9
- 作者:
Qingyi Zhou;Qiqi Wang;Zongfu Yu - 通讯作者:
Zongfu Yu
Zongfu Yu的其他文献
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{{ truncateString('Zongfu Yu', 18)}}的其他基金
EAGER: Collaborative Research: Cold vapor generation beyond the input solar energy limit and its condensation using thermal radiation
EAGER:合作研究:超出输入太阳能限制的冷蒸汽生成及其利用热辐射的冷凝
- 批准号:
1932843 - 财政年份:2019
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
Improving the voltage of solar cells using photon management
利用光子管理提高太阳能电池的电压
- 批准号:
1405201 - 财政年份:2014
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
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Collaborative Research: WOU-MMA: Extreme Quantum-Electrodynamic and General-Relativistic Plasma Physics
合作研究:WOU-MMA:极端量子电动和广义相对论等离子体物理
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The new intensity frontier: exploring quantum electrodynamic plasmas
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Electrodynamic Sampling of Water Ice on the Moon
月球水冰的电动采样
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