Author

Abhishek Chopra

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Preprint Sep 2026

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

Quantum Amplitude Estimation promises to accelerate Monte Carlo integration by replacing the classical $\varepsilon \propto N^{-1/2}$ sampling law with the Heisenberg-limited $\varepsilon \propto N^{-1}$ scaling, but whether any part of that advantage survives on present-day hardware is an empirical question. We report...

Aditi Lal, Alex Khan, Rut Lineswala et al. · 0 citations

Preprint Sep 2026

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

Quantum-inspired evolutionary optimization (QIEO) represents design variables as a set of qubits and searches a continuous, multi-dimensional landscape through rotation of the qubit's amplitude pair. Every generation rotates those amplitudes toward a single elite, which corresponds to that generation's best. The update...

R. Govind, F. Bosco, Kasturi Srikanth et al. · 0 citations

Preprint Sep 2026

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

Results reveal gene-parallel offload achieved geometric-mean speedups of 90% and 155% over a single CPU core on the V100, A100, and MI300X, respectively, and 12$\times$, 17$\times$, and 16.6$\times$ over 72 host threads.

Kasturi Srikanth, Ashish Singh, F. Bosco et al. · 0 citations

#natural language process... Preprint Sep 2026

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

The Cross-Backend Quantum Inspired Evolutionary Optimizer (QIEO) is presented, the runtime core of BQP's BQPhy solver, which addresses the gap between algorithmic performance and hardware portability through a single-source-of-truth architecture.

Aman Mittal, F. Bosco, Kasturi Srikanth et al. · 0 citations

Preprint Aug 2026

Variational Quantum Linear Solver via Block Encoding for the Poisson Equation

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 physically motivated benchmarks. Unlike LCU-based VQLS where the number of distinct circuits required per cost-function evaluation is $\mathcal{O}...

Viraj Dsouza, A. Singhal, Alex Khan et al. · 0 citations

Preprint Aug 2026

Measurement and reload costs in direct quantum simulation of nonlinear waves

A hybrid split-step solver is proposed in which the field is measured, updated classically, and reloaded at every step, with all shots and gates accounted for in a single cost-and-error model.

Zi-Qing Guo, Viraj Dsouza, Alex Khan et al. · 0 citations