6 papers
Learning to Prepare Molecular Ground States with Transformer Models
Alex Koziell-Pipe, Jasmine Brewer, Jem Guhit +14
Quantum state preparation is a key component of many quantum algorithms. Performing this step efficiently is essential for realizing practical quantum advantage in quantum chemistr…
Artificial Intelligence for Quantum Computing
Yuri Alexeev, Marwa H. Farag, Taylor L. Patti +25
Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extend…
Quantum simulation of CO chemisorption in an amine-functionalized metal-organic framework
Jonathan R. Owens, Marwa H. Farag, Pooja Rao +1
We perform a series of calculations using simulated QPUs, accelerated by the NVIDIA CUDA-Q platform, focusing on a molecular analog of an amine-functionalized metal-organic framewo…
A Hybrid Transformer Architecture with a Quantized Self-Attention Mechanism Applied to Molecular Generation
Anthony M. Smaldone, Yu Shee, Gregory W. Kyro +4
The success of the self-attention mechanism in classical machine learning models has inspired the development of quantum analogs aimed at reducing computational overhead. Self-atte…
QAOA-GPT: Efficient Generation of Adaptive and Regular Quantum Approximate Optimization Algorithm Circuits
Ilya Tyagin, Marwa H. Farag, Kyle Sherbert +3
Quantum computing has the potential to improve our ability to solve certain optimization problems that are computationally difficult for classical computers, by offering new algori…
Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries
Anthony M. Smaldone, Yu Shee, Gregory W. Kyro +8
The nexus of quantum computing and machine learning - quantum machine learning - offers the potential for significant advancements in chemistry. This review specifically explores t…