activity
20172026
most citedA priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence

48 citations · 108 across the 18 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

quant-ph2025

A Modular, Adaptive, and Scalable Quantum Factoring Algorithm

Alok Shukla, Prakash Vedula

Shor's algorithm for integer factorization offers an exponential speedup over classical methods but remains impractical on Noisy Intermediate Scale Quantum (NISQ) hardware due to t…

quant-ph2025

Modular Quantum Amplitude Estimation: A Scalable and Adaptive Framework

Alok Shukla, Prakash Vedula

Quantum Amplitude Estimation (QAE) is a key primitive in quantum computing, but its standard implementation using Quantum Phase Estimation is resource-intensive, requiring a large…

quant-ph2025

Generalized tensor transforms and their applications in classical and quantum computing

Alok Shukla, Prakash Vedula

We introduce a novel framework for Generalized Tensor Transforms (GTTs), constructed through an -fold tensor product of an arbitrary unitary matrix . This constr…

quant-ph2025

Quantum algorithm for edge detection in digital grayscale images

Mohit Rohida, Alok Shukla, Prakash Vedula

In this work, we propose a novel quantum algorithm for edge detection in digital grayscale images, based on the sequency-ordered Walsh-Hadamard transform. The proposed method signi…

quant-ph2025★ 1 cited

Towards Practical Quantum Phase Estimation: A Modular, Scalable, and Adaptive Approach

Alok Shukla, Prakash Vedula

Quantum Phase Estimation (QPE) is a cornerstone algorithm in quantum computing, with applications ranging from integer factorization to quantum chemistry simulations. However, the…