233 citations · 397 across the 20 of their papers we have counts for
20 papers
A Hybrid Classical-Quantum Approach for Multi-Constrained Location Optimization Problem
Jorge Saavedra-Benavides, J. Alejandro Montanez-Barrera, Alberto Maldonado-Romo +1
The Maximal Covering Location Problem (MCLP) is an NP-hard Combinatorial Optimization Problem (COP) that aims to determine the optimal facility placements that maximize total cover…
Setting angles in quantum approximate optimization at utility-scale
Maosheng Guo, Joel Jurado Diaz, Anurag Ramesh +16
The quantum approximate optimization algorithm (QAOA) is a powerful heuristic that seeks to solve combinatorial optimization problems using quantum hardware and classical optimizat…
Large-Scale Quantum Circuit Simulation on an Exascale System for QPU Benchmarking
J. A. Montanez-Barrera, Kristel Michielsen
Recent advances in quantum computing have enabled the development of quantum processors with hundreds of qubits. However, noise continues to limit the amount of useful information…
Quantum and classical approaches to the optimization of highway platooning: the two-vehicle matching problem
Chinonso Onah, Agneev Guin, Carsten Othmer +2
Aerodynamic drag reduction on highways through vehicle platooning is a well-known concept, but it has not yet seen systematic uptake, arguably because of significant technological…
Interplay of Confinement and Localization in a Programmable Rydberg Atom Chain
Andrea B. Rava, Jhon A. Montanez-Barrera, Kristel Michielsen +1
Analog quantum simulators promise access to complex many-body dynamics, yet their performance is ultimately set by how device imperfections compete with intrinsic physical mechanis…
Benchmarking neutral atom-based quantum processors at scale
Andrea B. Rava, Kristel Michielsen, J. A. Montanez-Barrera
In recent years, neutral atom-based quantum computation has been established as a competing alternative for the realization of fault-tolerant quantum computation. However, as with…
Optimizing QAOA circuit transpilation with parity twine and SWAP network encodings
J. A. Montanez-Barrera, Yanjun Ji, Michael R. von Spakovsky +2
Mapping quantum approximate optimization algorithm (QAOA) circuits with non-trivial connectivity in fixed-layout quantum platforms, such as superconducting quantum processing units…
Quantum Optimization Benchmarking Library - The Intractable Decathlon
Thorsten Koch, David E. Bernal Neira, Ying Chen +24
Through recent progress in hardware development, quantum computers have advanced to the point where benchmarking of (heuristic) quantum algorithms at scale is within reach. Particu…
Evaluating the performance of quantum processing units at large width and depth
J. A. Montanez-Barrera, Kristel Michielsen, David E. Bernal Neira
Quantum computers have now surpassed classical simulation limits, yet noise continues to limit their practical utility. As the field shifts from proof-of-principle demonstrations t…
Diagnosing crosstalk in large-scale QPUs using zero-entropy classical shadows
J. A. Montañez-Barrera, G. P. Beretta, Kristel Michielsen +1
As quantum processing units (QPUs) scale toward hundreds of qubits, diagnosing noise-induced correlations (crosstalk) becomes critical for reliable quantum computation. In this wor…
Towards a Linear-Ramp QAOA protocol: Evidence of a scaling advantage in solving some combinatorial optimization problems
J. A. Montanez-Barrera, Kristel Michielsen
The Quantum Approximate Optimization Algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational para…
Transfer learning of optimal QAOA parameters in combinatorial optimization
J. A. Montanez-Barrera, Dennis Willsch, Kristel Michielsen
Solving combinatorial optimization problems (COPs) is a promising application of quantum computation, with the Quantum Approximate Optimization Algorithm (QAOA) being one of the mo…
Improving Performance in Combinatorial Optimization Problems with Inequality Constraints: An Evaluation of the Unbalanced Penalization Method on D-Wave Advantage
J. A. Montanez-Barrera, Pim van den Heuvel, Dennis Willsch +1
Combinatorial optimization problems are one of the target applications of current quantum technology, mainly because of their industrial relevance, the difficulty of solving large…
Unbalanced penalization: A new approach to encode inequality constraints of combinatorial problems for quantum optimization algorithms
Alejandro Montanez-Barrera, Dennis Willsch, Alberto Maldonado-Romo +1
Solving combinatorial optimization problems of the kind that can be codified by quadratic unconstrained binary optimization (QUBO) is a promising application of quantum computation…
Decoherence predictions in a superconductive quantum device using the steepest-entropy-ascent quantum thermodynamics framework
J. A. Montanez-Barrera, M. R. von Spakovsky, C. E. Damian-Ascencio +1
The current stage of quantum computing technology, called noisy intermediate-scale quantum (NISQ) technology, is characterized by large errors that prohibit it from being used for…
Method for Generating Randomly Perturbed Density Operators Subject to Different Sets of Constraints
J. A. Montanez-Barrera, R. T. Holladay, G. P. Beretta +1
This paper presents a general method for producing randomly perturbed density operators subject to different sets of constraints. The perturbed density operators are a specified "d…
Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels
J. A. Montanez-Barrera, J. M. Barroso-Maldonado, A. F. Bedoya-Santacruz +1
Accurate pressure drop estimation in forced boiling phenomena is important during the thermal analysis and the geometric design of cryogenic heat exchangers. However, current metho…
Testing Swampland Conjectures with Machine Learning
Nana Cabo Bizet, Cesar Damian, Oscar Loaiza-Brito +2
We consider Type IIB compactifications on an isotropic torus threaded by geometric and non geometric fluxes. For this particular setup we apply supervised machine learning te…
Loss-of-entanglement prediction of a controlled-PHASE gate in the framework of steepest-entropy-ascent quantum thermodynamics
J. A. Montañez-Barrera, Cesar E. Damian-Ascencio, Michael R. von Spakovsky +1
As has been shown elsewhere, a reasonable model of the loss of entanglement or correlation that occurs in quantum computations is one which assumes that they can effectively be pre…
PennyLane: Automatic differentiation of hybrid quantum-classical computations
Ville Bergholm, Josh Izaac, Maria Schuld +65
PennyLane is a Python 3 software framework for differentiable programming of quantum computers. The library provides a unified architecture for near-term quantum computing devices,…