From the 2 of 96 papers with an AI index.
38 citations
- University of Tennessee at KnoxvilleUS22 papers
- Lawrence Berkeley National LaboratoryUS11 papers
- University of Illinois Urbana-ChampaignUS11 papers
- Ruhr University BochumDE10 papers
- Texas A&M UniversityUS10 papers
- Brookhaven National LaboratoryUS9 papers
- California Institute of TechnologyUS9 papers
- Centro de Investigaciones Energéticas, Medioambientales y TecnológicasES9 papers
- Fermi National Accelerator LaboratoryUS9 papers
- Institució Catalana de Recerca i Estudis AvançatsES9 papers
- Instituto de Astrofísica de CanariasES9 papers
- Laboratoire de Physique Subatomique et de CosmologieFR9 papers
9 papers · 1 filter
Locally Purified Maximally Mixed States At Scale: Entanglement Pruning and Symmetries
Amit Jamadagni, Eugene Dumitrescu
Locally Purified Density Operators (LPDOs) are state-of-the-art tensor network ansatze candidates that efficiently represent mixed quantum states at scale. However, given their non…
Sampling two-dimensional isometric tensor network states
Alec Dektor, Eugene Dumitrescu, Chao Yang
Sampling a quantum system's underlying probability distributions is an important computational task, e.g., for quantum advantage experiments and quantum Monte Carlo algorithms. Ten…
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…
Robust design under uncertainty in quantum error mitigation
Maksym Prodius, Piotr Czarnik, Michael McKerns +2
Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical post-processing of quantum computation outcomes is a popular approach for error mitigati…
Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations
Jai Moondra, Phillip C. Lotshaw, Philip C. Lotshaw +2
We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut prob…