Quantum Operations on Sequence and Image with EHands and QCrank: Implementations for NISQ Device
ORAL
Abstract
We report practical implementations of quantum algorithms on noisy intermediate-scale quantum (NISQ) hardware for core signal and image processing tasks, including convolution of real-valued functions, discrete-time Fourier transform (DTFT) of time series, squared gradient computation, and edge detection in grayscale images. Input data are encoded using QCrank, a protocol that enables efficient quantum representation of sequences of classical real values through parallel, uniformly controlled rotation gates. Quantum transformations are performed via the EHands protocol, which offers a universal framework for elementary quantum arithmetic operations—multiplication, addition, and negation—facilitating the construction of multivariate polynomial transformations required by these algorithms.
Experimental evaluations on IBM quantum processors demonstrate that accurate and interpretable results can be achieved for several target operations despite inherent hardware noise. These results establish the viability of specialized quantum circuit architectures for nontrivial real-world data processing on NISQ devices and underscore the potential of polynomial-based quantum transformations in bridging the gap between current quantum capabilities and practical computational applications.
Experimental evaluations on IBM quantum processors demonstrate that accurate and interpretable results can be achieved for several target operations despite inherent hardware noise. These results establish the viability of specialized quantum circuit architectures for nontrivial real-world data processing on NISQ devices and underscore the potential of polynomial-based quantum transformations in bridging the gap between current quantum capabilities and practical computational applications.
*This research was supported by the U.S. Department of Energy (DOE) under Contract No.~DE-AC02-05CH11231, through the Office of Science, Office of Advanced Scientific Computing Research (ASCR) Exploratory Research for Extreme-Scale Science and Accelerated Research in Quantum Computing. This research used resources of two DOE user facilities: the National Energy Research Scientific Computing Center (NERSC) located at Lawrence Berkeley National Laboratory, operated under Contract No.~DE-AC02-05CH11231, and the Oak Ridge Leadership Computing Facility, operated under Contract No.~DE-AC05-00OR22725.
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Presenters
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Jan Balewski
- Lawrence Berkeley National Laboratory
- Lawrance Berkeley National Laboratory