activity
20072026
most citedDrug design on quantum computers

127 citations · 726 across the 31 of their papers we have counts for

collaborators

31 papers

quant-ph2026

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…

quant-ph2026

Performance Model for Hybrid Quantum-Classical Workflows

Pooja Rao, Dimitar Trenev, Jerome Gonthier +13

Hybrid quantum-classical workflows are expected to underpin practical quantum computing applications, yet the quantum and HPC communities lack a shared framework for reasoning abou…

quant-ph2025★ 1 cited

Quantum-Classical Auxiliary Field Quantum Monte Carlo with Matchgate Shadows on Trapped Ion Quantum Computers

Luning Zhao, Joshua J. Goings, Willie Aboumrad +38

We demonstrate an end-to-end workflow to model chemical reaction barriers with the quantum-classical auxiliary field quantum Monte Carlo (QC-AFQMC) algorithm with quantum tomograph…

quant-ph2025

Constructive interference at the edge of quantum ergodic dynamics

Dmitry A. Abanin, Rajeev Acharya, Laleh Aghababaie-Beni +262

Quantum observables in the form of few-point correlators are the key to characterizing the dynamics of quantum many-body systems. In dynamics with fast entanglement generation, qua…

quant-ph2025

Quantum circuits as a game: A reinforcement learning agent for quantum compilation and its application to reconfigurable neutral atom arrays

Kouhei Nakaji, Jonathan Wurtz, Haozhe Huang +4

We introduce the "quantum circuit daemon" (QC-Daemon), a reinforcement learning agent for compiling quantum device operations aimed at efficient quantum hardware execution. We appl…

quant-ph2025★ 1 cited

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…