output
20102026
most citedAnalysis of numerical methods for spectral fractional elliptic equations based on the best uniform rational approximation

55 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing quant-phShow all

10 papers · 1 filter

quant-ph2024★ 1 cited

Increasing the Hardness of Posiform Planting Using Random QUBOs for Programmable Quantum Annealer Benchmarking

Elijah Pelofske, Georg Hahn, Hristo Djidjev

Posiform planting is a method for constructing QUBO problems with a single unique planted solution that can be tailored to arbitrary connectivity graphs. In this study we investiga…

quant-ph2023★ 3 cited

Posiform Planting: Generating QUBO Instances for Benchmarking

Georg Hahn, Elijah Pelofske, Hristo N. Djidjev

We are interested in benchmarking both quantum annealing and classical algorithms for minimizing Quadratic Unconstrained Binary Optimization (QUBO) problems. Such problems are NP-h…

quant-ph2023★ 12 cited

Initial State Encoding via Reverse Quantum Annealing and h-gain Features

Elijah Pelofske, Georg Hahn, Hristo Djidjev

Quantum annealing is a specialized type of quantum computation that aims to use quantum fluctuations in order to obtain global minimum solutions of combinatorial optimization probl…

quant-ph2022★ 14 cited

Noise Dynamics of Quantum Annealers: Estimating the Effective Noise Using Idle Qubits

Elijah Pelofske, Georg Hahn, Hristo N. Djidjev

Quantum annealing is a type of analog computation that aims to use quantum mechanical fluctuations in search of optimal solutions of QUBO (quadratic unconstrained binary optimizati…

quant-ph2022★ 29 cited

Solving Larger Maximum Clique Problems Using Parallel Quantum Annealing

Elijah Pelofske, Georg Hahn, Hristo N. Djidjev

Quantum annealing has the potential to find low energy solutions of NP-hard problems that can be expressed as quadratic unconstrained binary optimization problems. However, the har…

quant-ph2021★ 54 cited

Parallel Quantum Annealing

Elijah Pelofske, Georg Hahn, Hristo N. Djidjev

Quantum annealers of D-Wave Systems, Inc., offer an efficient way to compute high quality solutions of NP-hard problems. This is done by mapping a problem onto the physical qubits…

quant-ph2021★ 18 cited

Quantum Annealing Algorithms for Boolean Tensor Networks

Elijah Pelofske, Georg Hahn, Daniel O'Malley +2

Quantum annealers manufactured by D-Wave Systems, Inc., are computational devices capable of finding high-quality solutions of NP-hard problems. In this contribution, we explore th…

quant-ph2021★ 1 cited

Using machine learning for quantum annealing accuracy prediction

Aaron Barbosa, Elijah Pelofske, Georg Hahn +1

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or QUBO (quadratic unconstr…

quant-ph2021★ 3 cited

Boolean Hierarchical Tucker Networks on Quantum Annealers

Elijah Pelofske, Georg Hahn, Daniel O'Malley +2

Quantum annealing is an emerging technology with the potential to solve some of the computational challenges that remain unresolved as we approach an era beyond Moore's Law. In thi…

quant-ph2017

On the Hydrogen Atom Beyond the Born-Oppenheimer Approximation

Jean Michel Sellier, K. G. Kapanova

Recently a new formulation of quantum mechanics has been suggested which is based on the concept of signed particles, that is, classical objects provided with a position, a momentu…