11 papers
DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems
Seongmin Kim, Abhinav Rijal, Yuri Alexeev +5
While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to exponentially large search spaces.…
Diagonal-Budgeted Trotterization for Efficient Quantum Hamiltonian Simulation
Srikar Chundury, Blake Burgstahler, Jiajia Li +2
Efficient classical simulation of quantum Hamiltonian dynamics is often bottlenecked by exponential state growth and the overhead of generic sparse linear algebra. We introduce dia…
Quantum solver for single-impurity Anderson models with particle-hole symmetry
Mariia Karabin, Tanvir Sohail, Dmytro Bykov +8
Quantum embedding methods, such as dynamical mean-field theory (DMFT), provide a powerful framework for investigating strongly correlated materials. A central computational bottlen…
Distributed Quantum Optimization for Large-Scale Higher-Order Problems with Dense Interactions
Seongmin Kim, Vincent R. Pascuzzi, Travis S. Humble +5
Many real-world problems are naturally formulated as higher-order optimization (HUBO) tasks involving dense, multi-variable interactions, which are challenging to solve with classi…
Harnessing Quantum Computing for Energy Materials: Opportunities and Challenges
Seongmin Kim, In-Saeng Suh, Travis S. Humble +3
Developing high-performance materials is critical for diverse energy applications to increase efficiency, improve sustainability and reduce costs. Classical computational methods h…
Scaling Hybrid Quantum-HPC Applications with the Quantum Framework
Srikar Chundury, Amir Shehata, Seongmin Kim +6
Hybrid quantum-high performance computing (Q-HPC) workflows are emerging as a key strategy for running quantum applications at scale in current noisy intermediate-scale quantum (NI…