6 citations · 16 across the 10 of their papers we have counts for
10 papers · 1 filter
One Coordinate at a Time: Convergence Guarantees for Rotosolve in Variational Quantum Algorithms
Sayantan Pramanik, M Girish Chandra
In this paper, we resolve an open question in the field of optimization algorithms for training parametrized quantum circuits: Does the popular Rotosolve algorithm converge? Until…
Stochastic Shadow Descent: Training Parametrized Quantum Circuits with Shadows of Gradients
Sayantan Pramanik, M Girish Chandra
In this paper, we focus on the task of optimizing the parameters in Parametrized Quantum Circuits (PQCs). While popular algorithms, such as Simultaneous Perturbation Stochastic App…
Parsimonious Optimisation of Parameters in Variational Quantum Circuits
Sayantan Pramanik, Chaitanya Murti, M Girish Chandra
Variational quantum circuits characterise the state of a quantum system through the use of parameters that are optimised using classical optimisation procedures that typically rely…
Exploring the synergistic potential of quantum annealing and gate model computing for portfolio optimization
Naman Jain, M Girish Chandra
Portfolio optimization is one of the most studied problems for demonstrating the near-term applications of quantum computing. However, large-scale problems cannot be solved on toda…
Quantum-Enhanced Topological Data Analysis: A Peep from an Implementation Perspective
Ankit Khandelwal, M Girish Chandra
There is heightened interest in quantum algorithms for Topological Data Analysis (TDA) as it is a powerful tool for data analysis, but it can get highly computationally expensive.…
On Quantum-Enhanced LDPC Decoding for Rayleigh Fading Channels
Utso Majumder, Aditya Das Sarma, Vishnu Vaidya +1
Quantum and Classical computers continue to work together in tight cooperation to solve difficult problems. The combination is thus suggested in recent times for decoding the Low D…
One-Step Time Series Forecasting Using Variational Quantum Circuits
Payal Kaushik, Sayantan Pramanik, M Girish Chandra +1
Time series forecasting has always been a thought-provoking topic in the field of machine learning. Machine learning scientists define a time series as a set of observations record…
Quantum Image Representation Methods Using Qutrits
Ankit Khandelwal, M Girish Chandra
Quantum Image Processing is a recent highlight in the quantum computing field. All previous methods for representing the images as quantum states were defined using qubits. One Qua…
On Classifying Images using Quantum Image Representation
Ankit Khandelwal, M Girish Chandra, Sayantan Pramanik
In this paper, we consider different Quantum Image Representation Methods to encode images into quantum states and then use a Quantum Machine Learning pipeline to classify the imag…
A Quantum-Classical Hybrid Method for Image Classification and Segmentation
Sayantan Pramanik, M Girish Chandra, C V Sridhar +9
Enormous activity in the Quantum Computing area has resulted in considering them to solve different difficult problems, including those of applied nature, together with classical c…