7 citations · 13 across the 6 of their papers we have counts for
6 papers
Predicting Ising Model Performance on Quantum Annealers
Salvatore Certo, Georgios Korpas, Andrew Vlasic +1
By analyzing the characteristics of hardware-native Ising Models and their performance on current and next generation quantum annealers, we provide a framework for determining the…
Conditional Generative Models for Learning Stochastic Processes
Salvatore Certo, Anh Pham, Nicolas Robles +1
A framework to learn a multi-modal distribution is proposed, denoted as the Conditional Quantum Generative Adversarial Network (C-qGAN). The neural network structure is strictly wi…
An Advantage Using Feature Selection with a Quantum Annealer
Andrew Vlasic, Hunter Grant, Salvatore Certo
Feature selection is a technique in statistical prediction modeling that identifies features in a record with a strong statistical connection to the target variable. Excluding feat…
Complement Grover's Search Algorithm: An Amplitude Suppression Implementation
Andrew Vlasic, Salvatore Certo, Anh Pham
Grover's search algorithm was a groundbreaking advancement in quantum algorithms, displaying a quadratic speed-up of querying for items. Since the creation of this algorithm it has…
Comparing Classical-Quantum Portfolio Optimization with Enhanced Constraints
Salvatore Certo, Anh Dung Pham, Daniel Beaulieu
One of the problems frequently mentioned as a candidate for quantum advantage is that of selecting a portfolio of financial assets to maximize returns while minimizing risk. In thi…
Benchmarking Amplitude Estimation on a Superconducting Quantum Computer
Salvatore Certo, Anh Dung Pham, Daniel Beaulieu
Amplitude Estimation (AE) is a critical subroutine in many quantum algorithms, allowing for a quadratic speedup in various applications like those involving estimating statistics o…