5 papers
Role of overparametrization in quantum approximate optimization
Daniil Rabinovich, Andrey Kardashin, Soumik Adhikary
Variational quantum algorithms have emerged as a cornerstone of contemporary quantum algorithms research. While they have demonstrated considerable promise in solving problems of p…
Expressivity Limits in Quantum Walk-based Optimization
Guilherme A. Bridi, Debbie Lim, Lirandë Pira +3
Quantum algorithms have emerged as a promising tool to solve combinatorial optimization problems. The quantum walk optimization algorithm (QWOA) is one such variational approach th…
Online Learning of Pure States is as Hard as Mixed States
Maxime Meyer, Soumik Adhikary, Naixu Guo +1
Quantum state tomography, the task of learning an unknown quantum state, is a fundamental problem in quantum information. In standard settings, the complexity of this problem depen…
Mitigating Quantum Gate Errors for Variational Eigensolvers Using Hardware-Inspired Zero-Noise Extrapolation
Alexey Uvarov, Daniil Rabinovich, Olga Lakhmanskaya +3
Variational quantum algorithms have emerged as a cornerstone of contemporary quantum algorithms research. Practical implementations of these algorithms, despite offering certain le…
Robustness of Variational Quantum Algorithms against stochastic parameter perturbation
Daniil Rabinovich, Ernesto Campos, Soumik Adhikary +3
Variational quantum algorithms are tailored to perform within the constraints of current quantum devices, yet they are limited by performance-degrading errors. In this study, we co…