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20242026
most citedDemonstration of Scalability and Accuracy of Variational Quantum Linear Solver for Computational Fluid Dynamics

1 citations · 1 across the 7 of their papers we have counts for

collaborators

11 papers

cs.NE2026

Landscape Limits of Quantum-Inspired Evolutionary Optimization across 256 continuous functions

Rishi Govind, Ferdin Sagai Don Bosco, Kasturi Venkata Srikanth +4

Quantum-inspired evolutionary optimization (QIEO) represents design variables as a set of qubits and searches a continuous, multi-dimensional landscape through rotation of the qubi…

cs.DC2026

Cross-Backend QIEO: Universal Runtime Portability across OpenMP5, CUDA, HIP, and Multi-Language Interfaces

Aman Mittal, Ferdin Sagai Don Bosco, Kasturi Venkata Srikanth +3

Quantum-inspired algorithms emulate quantum mechanical principles, such as, superposition, interference, and probabilistic amplitude evolution, on classical hardware by representin…

cs.PF2026

Evaluation of portability and performance of an OpenMP5 offloaded Quantum-Inspired Evolutionary Optimization Across the GPU Ecosystem

Kasturi Venkata Srikanth, Ashish Singh, Ferdin Sagai Don Bosco +4

Quantum-inspired evolutionary optimization (QIEO) is a new class of population-based metaheuristic optimization algorithms which represents design variables as a set of qubits and…

quant-ph2026

Maximum-Likelihood Amplitude Estimation for Quantum Monte Carlo Integration on Trapped-Ion Hardware: Convergence, Noise-Floor Saturation, Depth-Dependent Bias

Aditi Lal, Alex Khan, Rut Lineswala +1

Quantum Amplitude Estimation promises to accelerate Monte Carlo integration by replacing the classical sampling law with the Heisenberg-limited $\var…

quant-ph2026

Measurement and reload costs in direct quantum simulation of nonlinear waves

Ziqing Guo, Viraj Dsouza, Alex Khan +3

Quantum processors encode an N-point field in log_2(N) qubits, which renders nonlinear wave equations an important application for quantum simulation. Nonlinear evolution, however,…

quant-ph2026

Variational Quantum Linear Solver via Block Encoding for the Poisson Equation

Viraj Dsouza, Ayush Singhal, Alex Khan +2

We present a variational quantum linear solver (VQLS) for the Poisson equation built on an exact block encoding of the discrete Laplacian, and demonstrate its performance on physic…

cs.CE2026

Exploring the non-convexity in machine learning using quantum-inspired optimization

Kandula Eswara Sai Kumar, Parth Dhananjay Danve, Abhishek Chopra +1

The escalating complexity of modern machine learning necessitates solving challenging non-convex optimization problems, particularly in high-dimensional regimes and scenarios conta…

cs.CE2025

Investigation of Performance and Scalability of a Quantum-Inspired Evolutionary Optimizer (QIEO) on NVIDIA GPU

Aman Mittal, Kasturi Venkata Sai Srikanth, Ferdin Sagai Don Bosco +3

Quantum inspired evolutionary optimization leverages quantum computing principles like superposition, interference, and probabilistic representation to enhance classical evolutiona…

physics.comp-ph2025

Design of Magnetic Lattices with a Quantum-Inspired Evolutionary Optimization Algorithm

Zekeriya Ender Eğer, Waris Khan, Priyabrata Maharana +5

This article investigates the identification of magnetic spin distributions in ferromagnetic materials by minimizing the system's free energy. Magnetic lattices of varying sizes ar…

cs.CE2024

Benchmarking of GPU-optimized Quantum-Inspired Evolutionary Optimization Algorithm using Functional Analysis

Kandula Eswara Sai Kumar, Supreeth B S, Rajas Dalvi +5

This article presents a comparative analysis of GPU-parallelized implementations of the quantum-inspired evolutionary optimization (QIEO) approach and one of the well-known classic…

physics.flu-dyn2024★ 1 cited

Demonstration of Scalability and Accuracy of Variational Quantum Linear Solver for Computational Fluid Dynamics

Ferdin Sagai Don Bosco, Dhamotharan S, Rut Lineswala +1

The solution for non-linear, complex partial differential Equations (PDEs) is achieved through numerical approximations, which yield a linear system of equations. This approach is…