Summary of Ongoing and Accomplished Projects:
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Microwave Quantum Memory based on rare-earth materials
A solution for practical quantum information processing is to develop quantum memories that store microwave photons. Today, most quantum memories work on optical modes while many quantum information systems operate in the microwave regime and are limited by relatively short coherence times. Rare-earth atoms in solids are a promising platform for both optical quantum memory and microwave to optical quantum transduction due to their extremely long coherence times, high densities of emitters, and more. In particular, certain isotopes with GHz-scale hyperfine splittings (including 167Er3+, 145Nd3+, and 171Yb3+) in yttrium-oxide crystalline hosts are well-suited for microwave quantum memory due to their minimal inhomogeneous broadening and optical addressability for spectroscopic investigations. For most microwave-regime quantum memory protocols, minimizing the inhomogeneous broadening of the spin transition is vital. In this project I am presenting spectroscopic investigations of the hyperfine states of rare-earth ensembles at cryogenic temperatures to determine the dependence of the inhomogeneous broadening on temperature, magnetic field, doping concentration, and host material. The goal is to discuss the implications on future microwave quantum memories with rare-earth doped crystals.
Figure: Right is a view of our experimental setup and the place of Erbiub doped crystal inside the 1.7K Cryostate. Left is the transmission spectrum measured from the Crystal at 305652.709 GHz.
LIGO DQ shift data analysis
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Below is a summary of data science and data analysis projects I was involved with the Laser Interferometer Gravitational-Wave Observatory (LIGO) astrophysics groups. I had actively collaborated with the LIGO group during run O2 and O3. One of my responsibility was to analyze the enormous amount of data we receive from the sensors and detectors each day from Hanford and Livingston sites. These data included all the environmental noises such as glitches, different motions such as earthquakes, and acoustic noises, in addition to the signals we receive from the galaxy. The goal was to optimize the algorithm in order to analyze the data with higher accuracy and better functionality to eliminate noise from the targeted signal. My collaboration during this time leads to several important discoveries, such as the coalescence of neutron stars,gand calculating the mass of a huge black hole.
Figure: Sample of data collected and analyized from LIGO sensors
Design and implement microsphere resonators to increase light-matter interaction using rare-earth materials.
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The current challenges of long-distance quantum communication are the lack of efficiency, scalability, short coherent time, and optical losses. In fact, quantum communications are limited by the distance photons traveling over fiber-optic cable, generally no more than 100km. This project aims to develop efficient quantum light-matter interfaces using atom-like emitters with excellent coherence properties that are compatible with integrated photonics platforms. Furthermore, we are designing and implementing microsphere resonators to increase light-matter interaction using rare-earth materials. Moreover, we want to extract light efficiently from the nanoscale cavity to a microscale propagating mode in an optical fiber by using whispering gallery mode (WGM) resonators to achieve the high-quality factors in low-loss optical materials. We are using different methods to build our microspheres and tapered optical fibers, such as etching the fiber optic and pulling by a Hydrogen flame. We are also simulating the microsphere to visualize the modes. For the simulations I am using numerical analysis, data analysis and high-performance computing. The final goal is to make quantum memory and quantum repeater based on microsphere resonator and WGM.
Figure: Right is a view of our experimental setup, left is the picture of microsphere using Scanning Electron Microscopy (SEM), the top is the initial transmission from two different microresonators built with etch method and pulled method.
Introducing Opto-plasmonic amplifier operating in visible range and generating Raman signal internally with injection seeding
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Resonant propagation of light is important for building novel light sources and chip-scale optical interconnects. This project aims to introduce new optoplasmonic amplifiers in visible light (670-680 nm), which generate Raman signals internally with injection seeding. To achieve a high-quality cavity, I use computational analysis and whispering gallery mode to analyze the effect of excitation and polarization with respect to different spheres and positions of excitation. In addition, the effect of different kinds of underlying substrates such as silicon nanopillar, polymer nanopillar, pyramid polymer, and nanohole polymer was studied. The results show that modes' place and intensity change depend on which sphere gets excited in the chains. The type of modes was also dictated by the individual shape of resonators and the type of polarization. The level of splitting can be controlled with different numbers of microspheres. The results offer a great deal of flexibility to create a desired spectral response from the photonic molecule for various applications such as single biological cells, quantum dots, nanoparticles, optical oscillators, and amplifiers. All the simulations were done using numerical analysis, data analysis and high-performance computing.
Figure: Analyze the effect of excitation and polarization for different arrangements of chain microspheres such as a single sphere, two spheres, and multi spheres with different sizes and study over magnetic field distribution in different directions for different spheres.
Design of a new graphene-based aperiodic multilayer structures as selective, tunable, and switchable thermal emitters at infrared frequencies.
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Graphene attracts enormous interest for photonic applications as it provides a degree of freedom to manipulate electromagnetic waves. I used a genetic optimization algorithm to find the optimal aperiodic thermal emitters and investigate the effect of the chemical potential and number of graphene layers on the range of selectivity, tunability, and switchability of thermal emittance. The electrically dynamic control of the proposed graphene-based aperiodic multilayer structures can pave the way for a new class of in situ wavelength selective, tunable, and switchable thermal sources. The structures are promising design to cover the thermal radiation of objects within a wide range of infrared in friend-or-foe (FOF) applications, but I expect that the design has a broad impact on various applications including infrared sensing, thermal imaging, and thermophotovoltaics.
Figure: Normalized thermal power emitted μ(λ) per unit area and unit wavelength in the normal direction from bulk tungsten versus wavelength and chemical potential at T = 873 K for the five optimized structures with 8, 13,23, 28, and 32 layers of graphene. Inset shows the structure of the proposed thermal emitter composed of alternating layers of graphene and hBN insulator, which are sandwiched between two thick silicon carbide (SiC) layers.
Design of Microresonators to Minimize Thermal Noise Below the Standard Quantum Limit.
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Microresonators are a crucial component of the Michelson interferometers playing a critical role for the quantum measurement. I used a micro-genetic algorithm and a finite element method to design a new microresonator whose geometry is optimized to maximize sub-Standard Quantum Limit (SQL) performance, including lower thermal noise (TN) below the SQL, a broader sub-SQL region, and a sub-SQL region at lower frequencies. I found that the maximum ratio of TN to SQL is increased, its frequency is decreased, and the sub-SQL range is increased by increasing the length of the microresonator cantilever, increasing the radius of the mirror pad, decreasing the width of the microresonator cantilever and shifting the laser beam location from the mirror center. Also, I found that there exists a trade-off in finding the optimum values of the maximum ratio of TN to SQL and the sub-SQL bandwidth. The new microresonators will enable broadband, off-resonance sub-SQL experiments and serve as a testbed for quantum non-demolition measurements and back action evasion techniques. The design can open new regimes of precision measurement that are relevant for many practical sensing applications, including advanced gravitational wave detectors.
Figure: (a) Experimental arrangement of our optomechanical system and the optomechanical cavity consists of a macroscopic end mirror and a microresonator. (b) Thermal noise and standard quantum limit as a function of frequency for the microresonators, and the SQL/TN ratio for the microresonators, as well as the definition of the parameters. (c) RMAX and (d) BWE as a function of the lengths and widths of the optimized microresonators.
Enabling an Automated Detection of Orbital Angular Momentum of Light in Quantum Optical Experiments using Convolutional Neural Networks.
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Laser beam profiling is necessary for most laser applications, and enabling automated detection of orbital angular momentum (OAM) can tremendously contribute to such quantum optical experiments. I used the convolutional neural networks (CNNs) to automatically identify and classify the noisy images of LG modes collected from two different experimental setups. The classification performance measures of the predictive classification models are studied for generalizing and adapting to experimental conditions. The results demonstrate both accuracy and specificity reach above 90% in classifying the 16 Laguerre-Gaussian (LG) modes for both experimental setups. However, the F-score, sensitivity, and precision of the classification depending on the intensity of experimental imperfections such as non-uniform intensity, mode loss, mode crosstalk, and spatial displacement of OAM modes ranging these performance measures from 57% to 92%. The research contributes towards enabling OAM light with increased degrees of freedom and, thereby, its various applications in telecommunications, sensing, and high-resolution imaging systems.
Figure: (a) The training dataset of the LG modes is used to train the CNN model. (b) Evaluation of the learned network using the random test experimental images. (c) Validation accuracy of the deep CNN predictive model versus iteration. (d) Five statistical metrics: accuracy, specificity, F-score, sensitivity, precision for the model prediction in assigning the test images of 16 classes of LG modes trained by the simulated data and tested by the real experimental data.
Improving the measurement of squeezed states using noise subtraction techniques
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Ponderomotive squeezing produced in an optomechanical cavity with a strong optical spring has some advantages over squeezed light sources that use nonlinear crystals. However, the cavity requires feedback to maintain stability, and excess noise is injected as a result. The excess noise may be removed from the squeezing measurement by time-domain subtraction. The application of this subtraction is difficult because it requires precise knowledge of the optical transfer function, which could change over time. Here, I used a noise subtraction technique that relies on measuring the coherence between the feedback signal and the squeezed state to purify the squeezed state. The experimental setup consists of the optomechanical system and a subsystem used to detect transmitted light from a Fabry-Perot cavity with a 1064 nm Nd: YAG NPRO laser. A beam splitter is used to pick off 15% of the transmitted cavity light to a photodetector for locking the cavity, and the remaining 85% is used for combining with a local oscillator to detect squeezing. The results at different quadratures show that the budgeted noise agrees with the measured subtracted noise and that if this subtraction technique was not applied, no squeezing would be seen in any quadrature.
Figure: (a) Overview of the experimental setup. (b) The average noisy level of both subtracted and unsubtracted measurements, noise budget, and sources of the budget, between 45 and 46 kHz. The subtracted measurement (blue) and budgeted noise (brown) drop below shot noise (green) between 12 and 24 degrees, indicating squeezing.
Investigating the effects of acoustic noises on gravitational waves detection in LIGO infrastructures using unsupervised machine learning
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Acoustic noises such as Thunderstorms are common in Louisiana that might have impacts on the LIGO detector’s sensitivity. I used unsupervised machine learning algorithms (K-mean clustering) to classify the acoustic noises, determine their sources, and study their effects on the detector. The datasets are prepared by recording omicron triggers in the EY microphone and extracting the 39 features. To find the most important features, I used Principle Component Analysis (PCA) that reduces computational time and avoids overfitting of the model. The coherence spectrograms, spectrograms, correlation, and band-limited RMS is used to find relationships between the quiet time segments and environmental noises such as thunder sample segment. Finally, listening to the recorded noise reveals the accuracy and similarity of the noises in the clusters including the thunder sounds and other undetermined sounds that need further investigations to find their sources.
Figure: (a) aLIGO PEM sensor locations (including microphones). (b) Noise Spectrum for thunder and quiet samples that have been classified using the KNN algorithm in classifying 199 of the 1076 triggers as thunders. (c) Applying Principle Component Analysis (PCA) and K-mean clustering to classify the acoustic noises into seven clusters. Listening to the recorded noises of the clusters approves the accuracy of the clustering and the soundness of the number of clusters.
Design broadband, high gain, and low noise photodetectors to use in the LIGO Laboratory
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A low-noise photodetector is a fundamental tool for the research of quantum information processing and quantum optical systems in the LIGO laboratory. I designed a low-noise, high gain photoelectric detector with a bandwidth of ~130 MHz, using a trans-impedance amplification circuit. The designed photodetector has a good linear response to the injected light and outperforms the conventional photodetectors, considering thermal noise, electronic noises, dark current noise, and shot noise. The designed photoelectric detector has a broad impact on various applications, including in an optical cavity locking system in the LIGO laboratory.
Figure: (a) Circuit design and (b) the designed PCB layout of the proposed broadband, high gain, and low noise photodetectors.