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Welcome aboard!! My name is Atharva Vidwans and I will take you through my life journey. Enjoy the ride!!!
About Me
I am a second year PhD student at UW Madison. My research is in Quantum algorithms and quantum computing. Outside my research and academics, I like solving problems and putting pieces together, sometimes elegantly, sometimes with duct tape. I build, break, and rebuild until something interesting comes out. Outside of that cycle, I write blogs, play soccer and badminton, or buried in an Agatha Christie novel (my personal favourite novel: Murder of Roger Ackroyd).
Undergrad
I completed my undergraduate degree in Mechanical Engineering, with a final year project focused on 3D printing. Studying Mechanical Engineering gave me a unique perspective on problem solving, it was during these 4 years I became fascinated by the strange and elegant laws that govern the quantum world. This was my first introduction to quantum.
Autonomous Robotic Surgery
After my undergraduate degree, I worked as a Research Intern at a startup in autonomous robotic surgery for treating kidney stones under the guidance of Rakesh Sharma. My work focused on image registration of Digitally Rendered Radiographs(DRRs), where I used Python tools of parallel processing such as Numba to accelerate DRR generation. By leveraging parallel computing, I was able to improve registration speed by nearly 300×. A detailed report of this work can be found (here).
Even while working in robotics, my self-study in quantum mechanics and quantum computing never stopped.
Entry into Quantum Computing
After enough studying and tinkering in Quantum Computing, I wanted to put my curiosity to the test, so I threw myself into quantum computing competitions, breaking things, fixing them, and occasionally even solving the problem. Along the way, I earned the IBM Quantum Developer (Associate) certification (here). With all these competitions and hackathons, I discovered that dedication isn’t just about smooth wins, it’s about the nights spent stuck on a bug, the papers re-read three times, and the stubborn joy of refusing to give up until something finally clicks.
Along the way I did few mini projects in quantum computing. Few of the projects code can be found here:
QML using variational Quantum Classifier in Pennylane,
Payoff optimization in Options using Quantum Amplitude Estimation,
QUBO formulation for crop yield problem.
Articles for all these problems can be found on my medium page here.
Research Intern
I began my journey in quantum computing as a research intern under Dr. Pawel Gora at the University of Warsaw, where I worked on layering VQE and FVQE to tackle the Vehicle Routing Problem and its variants. It was an exciting challenge, my first taste of applying quantum ideas to real-world problems. I even had the chance to present this work at the 13th Warsaw IT Days Conference in 2022, which was both nerve-wracking and unforgettable. The slides from that talk can be viewed here.
This experience was a turning point. It convinced me that quantum computing wasn’t just a passing interest but it was the field I wanted to dive deeper into. That realization ultimately led me to pursue a Master’s program in Physics at UW Madison, where I could continue exploring this fascinating world.
Masters
During my Master’s in Physics at UW Madison, I worked under Prof. Micheline Soley and
Prof. Shimon Kolkowitz on multiple research projects spanning quantum algorithm
development and error correction. I investigated molecular resonances and developed a quantum
algorithm called qDRIVE, which incorporated Complex Absorbing Potentials to
identify resonance states (paper). I also contributed to the design and implementation of
Bayesian Iterative Quantum Amplitude Estimation (BIQAE), where Bayesian inference was
used to obtain rigorous interval estimates with far fewer measurements in applications ranging
from finance to quantum chemistry
(paper).
In parallel, I explored ADAPT-VQE, an adaptive ansatz construction method for ground-state
energy estimation, analyzing its efficiency and limitations compared to traditional unitary
coupled-cluster approaches. Additionally, I implemented simulations of surface codes to study
error thresholds, logical qubit lifetimes, and trade-offs between code distance and realistic noise
models
(report).
Collectively, these projects gave me broad experience in algorithm design, performance analysis,
and error mitigation strategies, preparing me to tackle both theoretical and practical challenges
in quantum computing.
PhD
Currently I am in my second year of my PhD in Quantum chemistry. I am working under the mentorship of Prof. Matthew Otten. I am working with Double factorization and tensor hyper contraction along with BIQAE to reduce number of pauli terms scaling thus requiring even less shots than exsiting methods. Working on reducing the depth and T gate count of BIQAE circuit using techniques like local Grover implementation, surrogate quantum circuits and using different quantum compilers. I am also working in estimating resources for BIQAE for FTQC using Fluid Allocation of Surface code qubit mathematical model.
Resume
Click here for resume