Gettysburg, Pennsylvania, United States
Hi, I am Adib Kabir, currently a senior at Gettysburg College, and looking forward to apply for a doctoral study in quantum physics. I am very interested in learning about the physics and mathematics behind quantum science and technologies. In particular, I am very passionate about understanding exotic quantum materials like spin liquid materials, topological materials and utilizing these materials to build fault tolerant qubits which will enhance the performance of quantum hardwares and quantum computing.
This summer I am contributing to the ongoing research efforts on the quantum computing applications in the field of Computational Fluid Dynamics (CFD) by ORNL Computational Division. In specific, I am applying quantum linear solvers to solve classical Hele-Shaw Fluid dynamics problem and investigating error-mitigation correction strategies to get better quantum fidelity and quasi-probability in real superconducting devices developed by IBM.
This is the further continuation of my last summer project that I started in collaboration with department of Physics and Astronomy in Purdue University. As a Visiting Research Scholar at Purdue University, I focused on the development of next-generation ultra-sensitive heat capacity measurement pucks. These advanced tools are designed to facilitate the study of Quantum Spin Liquid materials at cryogenic temperatures, specifically below 1.8 K, under varying magnetic field conditions. This work aims to deepen our understanding of the unique properties of these materials and their potential quantum states.
As part of the prestigious Purdue University Summer Research Fellowship, I collaborated with Dr. Arnab Banerjee in the Quantum Spintronics Lab to advance the understanding of Quantum Spin Liquid (QSL) materials. The primary motivation for this research was to develop an ultra-sensitive heat capacity measurement puck to explore the unique thermal properties and exotic quantum states of α-RuCl3 at cryogenic temperature typically below 1.8 K. The key features of this impactful experience are as follows: • Designed an ultra-sensitive heat capacity measurement puck with cryogenic sensors for studying Quantum Spin Liquid (QSL) materials at temperatures below 1.8 K under high magnetic fields. • Calibrated sensors using PPMS electron transport measurement mode across a temperature range of 1.8 K to 300 K in zero magnetic fields. • Investigated quasiparticle contributions to α-RuCl3 heat capacity under zero magnetic field, identifying spin gap signatures and fractionalized excitations.
As part of a semester-long research endeavor with Dr. Yoshihiro Sato, I conducted computational simulations of the time-dependent Schrödinger equation to model the behavior of an electron within a 10 nm potential well using the Crank-Nicolson method. This work aimed to explore and visualize quantum mechanical phenomena in a controlled environment. • Simulated time-dependent Schr ̈odinger equation for an electron within a 10 nm potential well using Crank-Nicolson method. • Generated 2D/3D visualizations to illustrate wavefunction interference patterns and probability densities. • Developed 2D/3D Python animations to showcase the evolution of real, imaginary, and probability density of wavefunction. • Produced a comprehensive 3D model capturing the temporal behavior of electron wavefunctions • Published the research findings in the arXiv journal
Over the span of one year, I conducted an independent one-to-one mentored research project focused on exploring quantum optimization algorithms with Dr. Sheakha Aldaihan. The primary goal was to study and analyze the performance of various quantum algorithms in solving combinatorial graph optimization problems, with a particular emphasis on the Quantum Approximate Optimization Algorithm (QAOA). Key responsibilities are as follows: • Studied variations of the QAOA algorithm to solve Max Cut and Traveling Salesman Problems with quantum simulations. • Analyzed the space and time complexities of quantum optimization algorithms and differentiated their performance with that of classical optimization algorithms to solve the Maxcut problem. • Developed and optimized Qiskit scripts to enhance algorithmic efficiency for solving Max Cut problem. • Implemented quantum algorithms to improve problem-solving efficiency of various combinatorial graph optimization tasks.
During the X-SIG Summer Research Program, I explored the energy loss mechanisms of protons through thin gold films using a Van de Graaff proton accelerator under the guidance of Dr. Bret E. Crawford. This research focused on characterizing materials at the nanoscale to enhance proton detection methodologies. Key contributions include: • Investigating proton energy loss through thin gold films using a Van de Graaff proton accelerator. • Fabricating thin gold films (10-50 nm) using a low-pressure evaporator and measuring the film thickness as a function of wavelength with UV-VIS spectrometry. • Characterizing surface roughness of gold films using Atomic Force Microscopy (AFM). • Developing Python scripts to identify discrepancies between experimental accelerator data and SRIM simulations data for improved proton detection.