Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session UU10: V: Data Science II |
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Sponsoring Units: GDS Chair: Saravana Prakash Thirumuruganandham, Centro de Investigación de Ciencias Humanas y de la Educació Room: Virtual Room 10 |
Wednesday, March 22, 2023 5:00AM - 5:12AM |
UU10.00001: Correcting optical wavefront distortion due to strong atmospheric turbulence using deep neural networks Paramott Bunnjaweht, Poompong Chaiwongkhot, Thiparat Chotibut In both observation astronomy and (quantum) optical communication, one of the methods widely used to correct optical wavefront distortion due to atmospheric turbulence is using phase holograms. This task relies heavily on the ability to decompose the distorted wavefront to find the coefficients of Zernike polynomials, which is resource-intensive and time-consuming. Here, we propose a novel convolutional neural network model to efficiently and accurately perform Zernike decomposition of optical wavefront distortion up to 12 Zernike modes. We demonstrate that this deep learning-based method can provide an efficient computational framework for real-time correction of optical communication in the presence of strong atmospheric turbulence. |
Wednesday, March 22, 2023 5:12AM - 5:24AM |
UU10.00002: Maximum entropy for fine-tuning quantum dot arrays Mick Ramsey, Florian Luthi, Rostyslav Savytskyy, Stephanie A Bojarski, Justyna P Zwolak Quantum dots are a promising platform to realize practical quantum computing. However, before they can be used as qubits, quantum dots must be carefully tuned to the correct regime in the voltage space to trap individual electrons. Moreover, realizable quantum computing requires tuning of large arrays, which translates to a significant increase in the number of parameters that need to be controlled and calibrated. This necessitates the development of robust and automated methods to bring the device into an operational state. Building upon previous ray-based tuning methods, we explore the utility of the ray-based measurements to accurately extract the interdot and dot-to-gate capacitive coupling. Using the geometric information from the quantum dot charge stability diagram, we derive the probability that the quantum dot system is in the (n,m) state. We achieve this by automatically extracting the fisher information to navigate the probability manifold. This, in turn, gives us both the probability of being in the (m,n) state (charge tuning) and a way to measure the probability of going from (n,m) to (n,m+1) as the plunger gates are changed. This method not only enhances ray-based navigation but also provides a measure of uncertainty for transitioning between different charge occupations. Our work is an important step in establishing reliable fine-tuning methods for calibrating quantum dots to work as qubits. |
Wednesday, March 22, 2023 5:24AM - 5:36AM |
UU10.00003: Agile Experiment Management Software Designed for Large Scale Quantum System. Orkesh Nurbolat Programming and maintaining super conducting quantum qubits can be tedious, the present commercial GUI softwares are bloated and even harder to use, the coding method tends to be high effort and not flexible. In this work I present a compromised solution NLab (Not bloated Laboratory), that allows the user to focus on details of experiments and break free some of the human factor barriers. The goal of NLab is to automate the programming and maintaining process of large scale quantum computing system. To demonstrate its ability, in this work we present a few experiments we have conducted with NLab. Including implementation of auto calibration system, various types of crosstalk cancellation system and feedback control, etc. |
Wednesday, March 22, 2023 5:36AM - 5:48AM |
UU10.00004: Computational Study of Mixing Solid Materials for CO2 Capture Technology Yuhua Duan CO2 is one of the major combustion products that, once released into the air, can contribute to global climate change. Solid sorbents have been reported as promising candidates for CO2 sorbent applications due to their high CO2 absorption capacities at moderate working temperatures. By combining thermodynamic database mining with first-principles density functional theory and phonon lattice dynamics calculations, the National Energy Technology Laboratory has proposed and validated a theoretical screening methodology to identify the most promising CO2 sorbent candidates from a vast array of possible solid materials. The advantage of this method is that it identifies the thermodynamic properties of the CO2 capture reaction as a function of temperature and gas pressure without any experimental input beyond crystallographic structural information of the solid phases involved. The calculated thermodynamic properties of solid materials versus temperature and pressure changes were further used to evaluate the equilibrium properties for the CO2 adsorption/desorption cycles. The selected CO2 sorbent candidates were further considered for experimental validations. In this presentation, the results of M2O/Al2O3 (M=Li, Na, K) mixtures (MAlO2 and M5AlO4) capturing CO2 will be demonstrated in detail. |
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