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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…
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…
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…
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…
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,…
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…
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…