15 citations · 34 across the 13 of their papers we have counts for
14 papers · 1 filter
Off-line quantum-advantage feature extraction for industrial production
Carlos Flores-Garrigos, Gabriel D. Alvarado Barrios, Qi Zhang +2
Quantum computing is no longer a lab curiosity for academic research. Industrial processors exceeding 100 qubits are commercially accessible and, for the first time, can extract in…
Quantum Feature Selection with Higher-Order Binary Optimization on Trapped-Ion Hardware
Carlos Flores-Garrigós, Anton Simen, Qi Zhang +6
We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorporates multivariate dependencies…
Quantum-enhanced satellite image classification
Qi Zhang, Anton Simen, Carlos Flores-Garrigós +7
We demonstrate the application of a quantum feature extraction method to enhance multi-class image classification for space applications. By harnessing the dynamics of many-body sp…
Digitized Counterdiabatic Quantum Sampling
Narendra N. Hegade, Nachiket L. Kortikar, Balaganchi A. Bhargava +9
We propose digitized counterdiabatic quantum sampling (DCQS), a hybrid quantum-classical algorithm for efficient sampling from energy-based models, such as low-temperature Boltzman…
Quantum Combinatorial Reasoning for Large Language Models
Carlos Flores-Garrigos, Gaurav Dev, Michael Falkenthal +5
We design and implement a quantum combinatorial reasoning framework for large language models (QCR-LLM), integrating a real quantum computer in the hybrid workflow. QCR-LLM reformu…
Analog Quantum Feature Selection with Neutral-Atom Quantum Processors
Jose J. Orquin-Marques, Carlos Flores-Garrigos, Alejandro Gomez Cadavid +5
We present a quantum-native approach to quantum feature selection (QFS) based on analog quantum simulation with neutral atom arrays, adaptable to a variety of academic and industri…
Digitized Counterdiabatic Quantum Feature Extraction
Anton Simen, Carlos Flores-Garrigós, Murilo Henrique De Oliveira +6
We introduce a Hamiltonian-based quantum feature extraction method that generates complex features via the dynamics of -local many-body spins Hamiltonians, enhancing machine lea…
Hybrid Sequential Quantum Computing
Pranav Chandarana, Sebastián V. Romero, Alejandro Gomez Cadavid +3
We introduce hybrid sequential quantum computing (HSQC), a paradigm for combinatorial optimization that systematically integrates classical and quantum methods within a structured,…
Quenched Quantum Feature Maps
Anton Simen, Carlos Flores-Garrigos, Murilo Henrique De Oliveira +9
We propose a quantum feature mapping technique that leverages the quench dynamics of a quantum spin glass to extract complex data patterns at the quantum-advantage level for academ…
Runtime Quantum Advantage with Digital Quantum Optimization
Pranav Chandarana, Alejandro Gomez Cadavid, Sebastián V. Romero +3
We demonstrate experimentally that the bias-field digitized counterdiabatic quantum optimization (BF-DCQO) algorithm on IBM's 156-qubit devices can outperform simulated annealing (…
Branch-and-bound digitized counterdiabatic quantum optimization
Anton Simen, Sebastián V. Romero, Alejandro Gomez Cadavid +2
Branch-and-bound algorithms effectively solve combinatorial optimization problems, relying on the relaxation of the objective function to obtain tight lower bounds. While this is s…
Bias-Field Digitized Counterdiabatic Quantum Algorithm for Higher-Order Binary Optimization
Sebastián V. Romero, Anne-Maria Visuri, Alejandro Gomez Cadavid +3
Combinatorial optimization plays a crucial role in many industrial applications. While classical computing often struggles with complex instances, quantum optimization emerges as a…
Bias-field digitized counterdiabatic quantum optimization
Alejandro Gomez Cadavid, Archismita Dalal, Anton Simen +2
We introduce a method for solving combinatorial optimization problems on digital quantum computers, where we incorporate auxiliary counterdiabatic (CD) terms into the adiabatic Ham…
Digital-analog quantum convolutional neural networks for image classification
Anton Simen, Carlos Flores-Garrigos, Narendra N. Hegade +6
We propose digital-analog quantum kernels for enhancing the detection of complex features in the classification of images. We consider multipartite-entangled analog blocks, stemmin…