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Chiral exceptional point enhanced active tuning and nonreciprocity in micro-resonators

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arXiv 2024年

作者： Lee, Hwaseob Chang, Lorry Kecebas, Ali Mao, Dun Xiao, Yahui Li, Tiantian Alù, Andrea Özdemir, Sahin K. Gu, Tingyi Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Engineering Science and Mechanics Pennsylvania State University University ParkPA16802 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical and Computer Engineering Saint Louis University Saint LouisMO63103 United States

Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity. A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs, but also helped reduce losses originating from nanofabrication imperfections, facilitating the insitu study of chiral EPs and their contribution to the dynamics and tunability of resonators. Here, we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator, to demonstrate deterministic thermal tuning across a chiral EP, and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic tuning. Our results indicate asymmetric electro-optic modulation with up to 17dB contrast at GHz and CMOS-compatible voltage levels. Such wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing, electromagnetic wave control, and optical interconnects. © 2024, CC BY.

关键词： Microresonators

engineering Moiré Meta-crystals with Conventional Photonic and Phononic Structures

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arXiv 2023年

作者： Oudich, Mourad Kong, Xianghong Zhang, Tan Qiu, Chengwei Jing, Yun Graduate Program in Acoustics Penn State University University ParkPA16802 United States Université de Lorraine CNRS Institut Jean Lamour NancyF-54000 France Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

Recent discoveries on Mott insulating and unconventional superconducting states in twisted bilayer graphene with Moiré superlattices have reshaped the landscape of "twistronics" and paved the way for developing high-temperature superconductors and new devices for quantum computing and sensing. Meanwhile, artificially structured photonic and phononic metamaterials/crystals (or meta-crystals) have become a fertile playground for emulating quantum-mechanical features of condensed matter systems, revealing new routes for robust control of classical waves. Drawing inspiration from the success of twisted bilayer graphene, this perspective casts an overarching framework of the emerging Moiré photonic and phononic meta-crystals that promise novel classical-wave devices. We begin with the fundamentals of Moiré superlattices, before highlighting recent works that exploit twist angle and interlayer coupling as new ingredients to engineer and tailor the band structures and effective material properties of photonic and phononic meta-crystals. We finally discuss future directions and promises of this emerging area in materials science and wave physics. © 2023, CC BY-NC-SA.

关键词： Graphene

Ramsey envelope modulation in NV diamond magnetometry

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Physical Review B 2022年第5期106卷 054110-054110页

作者： Jner Tzern Oon Jiashen Tang Connor A. Hart Kevin S. Olsson Matthew J. Turner Jennifer M. Schloss Ronald L. Walsworth Department of Physics University of Maryland College Park Maryland 20742 USA Quantum Technology Center University of Maryland College Park Maryland 20742 USA Department of Electrical Engineering and Computer Science University of Maryland College Park Maryland 20742 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Lincoln Laboratory Massachusetts Institute of Technology Lexington Massachusetts 02421 USA

Nitrogen-vacancy (NV) spin ensembles in diamond provide an advanced magnetic sensing platform, with applications in both the physical and life sciences. The development of isotopically engineered NV15 diamond offers advantages over naturally occurring NV14 for magnetometry, due to its simpler hyperfine structure. However, for sensing modalities requiring a bias magnetic field not aligned with the sensing NV axis, the absence of a quadrupole moment in the N15 nuclear spin leads to pronounced envelope modulation effects in time-dependent measurements of NV15 spin evolution. While such behavior in spin echo experiments are well studied, analogous effects in Ramsey measurements and the implications for magnetometry remain underexplored. Here, we derive the modulated NV15 Ramsey response to a misaligned bias field, using a simple vector description of the effective magnetic field on the nuclear spin. The predicted modulation properties are then compared to experimental results, revealing significant magnetic sensitivity loss if unaddressed. We demonstrate that double-quantum coherences of the NV S=1 electronic spin states dramatically suppress these envelope modulations, while additionally proving resilient to other parasitic effects such as strain heterogeneity and temperature shifts.

关键词： NV centers Quantum metrology Quantum sensing Nitrogen vacancy centers in diamond Magnetization measurements Numerical approximation & analysis Perturbation theory

Photonic Metacrystal: Design and Experimental Results

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Photonic Metacrystal: Design and Experimental Results

CLEO: Science and Innovations, S and I 2022

作者： Hu, S. Khater, M. Kratschmer, E. Engelmann, S. Arnold, K.P. Green, W.M.J. Weiss, S.M. Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States IBM T J Watson Center 1101 Kitchawan Road Yorktown HeightsNY10598 United States INanoBio Inc 1600 Adams Drive Menlo ParkCA94025 United States Interdisciplinary Materials Science Program Vanderbilt University NashvilleTN37235 United States

ISBN: (纸本)9781557528209

Going beyond the limited design freedoms of traditional photonic crystals, we experimentally show how photonic metacrystals exploit the inclusion of subwavelength dielectric scatterers in the unit cell to deterministically modify k-space and real space profiles. © Optica Publishing Group 2022, © 2022 The Authors.

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Hybrid Stochastic Synapses Enabled by Scaled Ferroelectric Field-effect Transistors

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arXiv 2022年

作者： Islam, A.N.M. Nafiul Saha, Arnob Jiang, Zhouhang Ni, Kai Sengupta, Abhronil School of Electrical Engineering & Computer Science The Pennsylvania State University University ParkPA16802 United States Microsystems Engineering Ph.D. Program Rochester Institute of Technology RochesterNY14623 United States

Achieving brain-like density and performance in neuromorphic computers necessitates scaling down the size of nanodevices emulating neuro-synaptic functionalities. However, scaling nanodevices results in reduction of programming resolution and emergence of stochastic non-idealities. While prior work has mainly focused on binary transitions, in this work we leverage the stochastic switching of a three-state ferroelectric field effect transistor (FeFET) to implement a long-term and short-term 2-tier stochastic synaptic memory with a single device. Experimental measurements are performed on a scaled 28nm high-k metal gate technology-based device to develop a probabilistic model of the hybrid stochastic synapse. In addition to the advantage of ultra-low programming energies afforded by scaling, our hardware-algorithm co-design analysis reveals the efficacy of the 2-tier memory in comparison to binary stochastic synapses in on-chip learning tasks - paving the way for algorithms exploiting multi-state devices with probabilistic transitions beyond deterministic ones. © 2022, CC BY.

关键词： Stochastic models

All-optical Raman-based noise spectroscopy of solid-state spin qubits

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All-optical Raman-based noise spectroscopy of solid-state sp...

Conference on Quantum Information and Measurement, ICQI 2021

作者： Farfurnik, Demitry Singh, Harjot Luo, Zhouchen Bracker, Allan S. Carter, Samuel G. Pettit, Robert M. Waks, Edo Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics Joint Quantum Institute University of Maryland College ParkMD United States Naval Research Laboratory WashingtonDC United States Intelligence Community Postrdoctoral Research Fellowship Program University of Maryland College ParkMD United States

We introduce an all-optical approach for noise spectroscopy of solid-state spin qubits, based on Raman control and the Carr-Purcell-Meiboom-Gill pulse sequences, and use it to extract the noise spectra of self-assembl... 详细信息

ISBN: (纸本)9781957171012

关键词： Semiconductor quantum dots

Transcranial Phase Correction Using Pulse-echo Ultrasound and Deep Learning: A 2D Numerical Study

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TechRxiv

TechRxiv 2023年

作者： Tian, Zixuan Olmstead, Matthew Jing, Yun Han, Aiguo Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign UrbanaIL61801 United States The Graduate Program in Acoustics Penn State University University ParkPA16802 United States The Department of Biomedical Engineering and Mechanics Virginia Polytechnic Institute State University BlacksburgVA24061 United States

Phase aberration caused by human skulls severely degrades the quality of transcranial ultrasound images, posing a major challenge in the practical application of transcranial ultrasound techniques in adults. Aberration can be corrected if the skull profile (i.e., thickness distribution) and speed of sound (SOS) are known. However, accurately estimating the skull profile and SOS using ultrasound with a physics-based approach is challenging due to the complexity of the interaction between ultrasound and the skull. A deep learning approach is proposed herein to estimate the skull profile and SOS using ultrasound radiofrequency (RF) signals backscattered from the skull. A (Image Presented) numerical study was performed to test the approach's feasibility. Realistic numerical skull models were constructed from computed tomography (CT) scans of five ex vivo human skulls in this numerical study. Acoustic simulations were performed at various skull locations (N=3,595) to generate array-based ultrasound backscattered signals. A deep learning model was developed and trained to estimate skull thickness and SOS from RF channel data. The trained model was shown to be highly accurate. The mean absolute error was 0.15 mm (2% error) for thickness estimation and 13 m/s (0.5% error) for SOS estimation. The Pearson correlation coefficient between the estimated and ground-truth values was 0.99 for thickness and 0.95 for SOS. Aberration correction performed using deep-learning-estimated skull thickness and SOS values yielded significantly improved beam focusing (e.g., narrower beams) and transcranial imaging quality (e.g., improved spatial resolution and reduced artifacts) compared with no aberration correction. The results demonstrate the feasibility of the proposed approach for transcranial phase aberration correction. © 2023, CC BY.

关键词： Acoustic wave velocity

EllipsoNet: Deep-learning-enabled optical ellipsometry for complex thin films

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arXiv 2022年

作者： Wang, Ziyang Lin, Yuxuan Cosmi Zhang, Kunyan Wu, Wenjing Huang, Shengxi Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Department of Electrical Engineering The Pennsylvania State University University ParkPA16802 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States

Optical spectroscopy is indispensable for research and development in nanoscience and nanotechnology, microelectronics, energy, and advanced manufacturing. Advanced optical spectroscopy tools often require both specifically designed high-end instrumentation and intricate data analysis techniques. Beyond the common analytical tools, deep learning methods are well suited for interpreting high-dimensional and complicated spectroscopy data. They offer great opportunities to extract subtle and deep information about optical properties of materials with simpler optical setups, which would otherwise require sophisticated instrumentation. In this work, we propose a computational ellipsometry approach based on a conventional tabletop optical microscope and a deep learning model called EllipsoNet. Without any prior knowledge about the multilayer substrates, EllipsoNet can predict the complex refractive indices of thin films on top of these nontrivial substrates from experimentally measured optical reflectance spectra with high accuracies. This task was not feasible previously with traditional reflectometry or ellipsometry methods. Fundamental physical principles, such as the Kramers-Kronig relations, are spontaneously learned by the model without any further training. This approach enables in-operando optical characterization of functional materials within complex photonic structures or optoelectronic devices. © 2022, CC BY.

关键词： Refractive index

Investigation of Noise at a Microelectrode during a Faradaic Reaction

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ACS Electrochemistry

ACS Electrochemistry 2025年第4期1卷 552-559页

作者： Kaden Wheeler Joseph Gott Brian Roehrich Julia Chung Kajal Kajal Jaroslaw Syzdek Joao Hespanha Lior Sepunaru Department of Chemistry and Biochemistry University of California at Santa Barbara Santa Barbara California 93106 United States Interdepartmental Program in Biomolecular Science and Engineering University of California at Santa Barbara Santa Barbara California 93106 United States Bio-Logic USA LLC 9050 Executive Park Dr. Ste. 110C Knoxville Tennessee 37923 United States Electrical and Computer Engineering Department University of California at Santa Barbara Santa Barbara California 93106 United States

Measurement of small currents is often impeded by a suboptimal signal-to-noise ratio, largely due to background noise. This background noise significantly constrains the range of catalysts accessible for interrogation via micro- and nanoscale electrochemistry. In response, this work reveals how background noise scales in the presence of induced Faradaic reactions. We measured noise under a series of electrochemical conditions and discovered that the induced noise from a Faradaic reaction scales directly with current. Complementary electrochemical impedance spectroscopy measurements demonstrated that diffusional resistance dictates the noise of Faradaic reactions, independent of the electrochemical mechanism. The noise source is thermal in origin and propagates in a predictable trend, which is inversely proportional to the equivalent diffusional resistance of the analyte. The universality of the observed phenomenon allows for better deconvolution of measured charge from background noise, thus assisting in achieving higher resolution and measurement precision, which is a key in micro- and nanoscale electrochemical measurements.

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