Akshay Vishwanathan

Research Scientist

Education

2023 PhD in Computer Science, Skolkovo Institute of Science and Technology, Moscow
Thesis Title: On the Performance of Quantum Approximate Optimization
Advisor: Jacob Biamonte

2018 BSc and MSc in Photonics, Cochin University of Science and Technology, India
Thesis Title: Building a Spectroscopy Cell for Strontium and Frequency Stabilization of Primary 461nm Cooling Laser by the DAVLL Technique
Supervisor: Kai Bongs
2018 C.V. Raman Thesis Award

Visiting Researcher, Center for Quantum Technologies, National University of Singapore, Singapore (May 2016 – July 2016)
Supervisor: Mile Gu

Biography

Hi there! I’m a researcher in quantum computing with a background in computer science and physics. In 2023, I earned my PhD in Computer Science from the Skolkovo Institute of Science and Technology in Moscow under the supervision of Jacob Biamonte. Before that, I completed my BSc and MSc in Photonics at Cochin University of Science and Technology in India, where I was honored with the 2018 C.V. Raman Thesis Award. During my academic journey, I had the opportunity to be a Visiting Researcher at the Center for Quantum Technologies at the National University of Singapore in 2016, working under the guidance of Mile Gu.

During my PhD, I played a significant role in discovering and quantifying various limiting factors in quantum approximate optimization, including reachability deficits. My research also revealed that training on smaller problem instances in quantum approximate search yielded effective approximations of optimal parameters for larger problems, a phenomenon we termed ‘parameter concentrations.’

Feel free to explore my work and get in touch if you’re interested in discussing quantum computing or collaborating on a project!

Research Interests

Quantum approximate optimisation
Variational quantum algorithms
Entanglement in photonics-based systems
Tensor networks

Publications

Reachability Deficits in Quantum Approximate Optimization
V. Akshay, H. Philathong, M.E.S. Morales, J. Biamonte
Physical Review Letters 124, 090504 (2020) DOI: 10.1103/PhysRevLett.124.090504

Computational Phase Transitions: Benchmarking Ising Machines and Quantum Optimisers
H. Philathong, V. Akshay, K. Samburskaya, J. Biamonte
Journal of Physics: Complexity 2:011002 (2021) DOI: 10.1088/2632-072X/abdadc

Parameter Concentrations in Quantum Approximate Optimization
V. Akshay, D. Rabinovich, E. Campos, J. Biamonte
(Letter) Physical Review A,104, L010401 (2021) DOI: 10.1103/PhysRevA.104.L010401

Reachability Deficits in Quantum Approximate Optimization of Graph Problems
V. Akshay, H. Philathong, I. Zacharov, J. Biamonte
Quantum 5, 532 (2021) DOI: 10.22331/q-2021-08-30-532

Training Saturation in Layerwise Quantum Approximate Optimisation
E Campos, D. Rabinovich, V. Akshay, J. Biamonte
(Letter) Physical Review A 104, L030401 (2021) DOI: 10.1103/PhysRevA.104.L030401

Progress towards analytically optimal angles in quantum approximate optimisation
D. Rabinovich, R. Sengupta,E. Campos, V. Akshay, J. Biamonte
Mathematics, 10(15):2601 (2022) DOI: 10.3390/math10152601

Ion-Native Variational Ansatz for Quantum Approximate Optimization
D. Rabinovich, S. Adhikary, E. Campos, V. Akshay, E. Anikin, R. Sengupta, O. Lakhmanskaya, K. Lakhmanskiy, J. Biamonte
Physical Review A, 106:032418 (2022) DOI: 10.1103/PhysRevA.106.032418

Circuit Depth Scaling for Quantum Approximate Optimization
V. Akshay, H. Philathong, E. Campos, D. Rabinovich, I. Zacharov, Xiao-Ming Zhang, J.D. Biamonte
Physical Review A, 106:042438 (2022) DOI: 10.1103/PhysRevA.106.042438