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Publication	Type	Year
Application of the Level-2 Quantum Lasserre Hierarchy in Quantum Approximation Algorithms Quantum Information Processing 2022 Ojas D. Parekh, Kevin Thompson	Conference Presentation – 2022 Conference Presentation	2022
Neuromorphic scaling advantages for energy-efficient random walk computations Nature Electronics John Darby Smith, Aaron Jamison Hill, Reeder Leah, Brian C. Franke, Richard B. Lehoucq, Ojas D. Parekh, William Mark Severa, James Bradley Aimone https://www.osti.gov/search/identifier:1845387	Journal Article – 2022 Journal Article	2022
Neuromorphic Graph Algorithms Ojas D. Parekh, Yipu Wang, Yang Ho, Cynthia Ann Phillips, Ali Pinar, James Bradley Aimone, William Mark Severa https://www.osti.gov/search/identifier:1829422	SAND Report – 2021 SAND Report	2021
Beating Random Assignment for Approximating Quantum 2-Local Hamiltonian Problems European Symposium no Algorithms (ESA 2021) Ojas D. Parekh, Kevin Thompson	Conference Presentation – 2021 Conference Presentation	2021
Outperforming QAOA on MaxCut with Fast Classical Hyperplane Rounding Algorithms SIAM Optimization Conference Ojas D. Parekh, Jessica Kelley Thompson	Conference Presentation – 2021 Conference Presentation	2021
Application of the Level-2 Quantum Lasserre Hierarchy in Quantum Approximation Algorithms International Colloquium on Automata, Languages and Programming Ojas D. Parekh, Kevin Thompson	Conference Presentation – 2021 Conference Presentation	2021
Provable Advantages for Graph Algorithms in Spiking Neural Networks ACM Symposium on Parallelism in Algorithms and Architectures James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang	Conference Presentation – 2021 Conference Presentation	2021
Provable advantages for graph algorithms in spiking neural networks 33rd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2021) James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang https://www.osti.gov/search/identifier:1871422	Conference Paper – 2021 Conference Paper	2021
CIS External Review Lightning Presentation: Neuromorphic Graph Algorithms CIS External Review Lightning Presentation Ojas D. Parekh https://www.osti.gov/search/identifier:1856083	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
An approximation algorithm for the MAX-2-Local Hamiltonian problem arXiv publication Sean Hallgren, Eunou Lee, Ojas D. Parekh https://www.osti.gov/search/identifier:1847599	Conference Paper – 2021 Conference Paper	2021
Novel Geometric Operations for Linear Programming Mohamed Salah Ebeida, Ahmed Abdelkader, Nina Amenta, Drew Philip Kouri, Ojas D. Parekh, Cynthia Ann Phillips, Nickolas Winovich https://www.osti.gov/search/identifier:1813669	SAND Report – 2020 SAND Report	2020
Neuromorphic scaling advantages for energy-efficient random walk computations John Darby Smith, Aaron Jamison Hill, Leah Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas D. Parekh, William Mark Severa, James Bradley Aimone https://www.osti.gov/search/identifier:1671377	SAND Report – 2020 SAND Report	2020
Brief Announcement: Provable neuromorphic advantages for computing constrained shortest paths 32nd ACM Symposium on Parallelism in Algorithms and Architectures James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang https://www.osti.gov/search/identifier:1814114	Conference Paper – 2020 Conference Paper	2020
Solving a steady-state pde using spiking networks and neuromorphic hardware International Conference on Neuromorphic Systems John Darby Smith, William Mark Severa, Aaron Jamison Hill, Leah Reeder, Ojas D. Parekh, Brian C. Franke, Richard B. Lehoucq, James Bradley Aimone https://www.osti.gov/search/identifier:1813714	Conference Paper – 2020 Conference Paper	2020
Solving a steady-state pde using spiking networks and neuromorphic hardware International Conference on Neuromorphic Systems John Darby Smith, William Mark Severa, Aaron Jamison Hill, Leah Evelyn Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas D. Parekh, James Bradley Aimone https://www.osti.gov/search/identifier:1808426	Conference Paper – 2020 Conference Paper	2020
Brief Announcement: Provable neuromorphic advantages for computing constrained shortest paths 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020) James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang https://www.osti.gov/search/identifier:1808434	Conference Paper – 2020 Conference Paper	2020
Probing a set of trajectories to maximize captured information 18th Symposium on Experimental Algorithms Sandor P. Fekete, Alexander Hill, Dominik Krupke, Tyler Mayer, Joseph S.B. Mitchell, Ojas D. Parekh, Cynthia Ann Phillips https://www.osti.gov/search/identifier:1778662	Conference Paper – 2020 Conference Paper	2020
Probing a set of trajectories to maximize captured movement EuroCG Sandor P. Fekete, Alexander Hill, Dominik Krupke, Tyler Mayer, Joseph S. B. Mitchell, Ojas D. Parekh, Cynthia Ann Phillips	Abstract – 2020 Abstract	2020
Fundamental Algorithmic Research for Quantum Computing (FAR-QC): Project Overview DOE/ASCR ARQC Kickoff meeting Ojas D. Parekh	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
Quantum Optimization and Learning and Simulation (QOALAS): Project Overview DOE/ASCR ARQC kickoff meeting Ojas D. Parekh	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
A Hybrid Quantum Optimization Algorithm Incorporating Classical Heuristics Annual update talk for UNM PhD requirments Jaimie Suzette Stephens, Ojas D. Parekh, William Bolden https://www.osti.gov/search/identifier:1761890	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
Solving IPDEs on Spiking Neuromorphic Hardware Joint Math Meetings John Darby Smith, James Bradley Aimone, Brian C. Franke, Aaron Jamison Hill, Richard B. Lehoucq, Ojas D. Parekh, Leah Evelyn Reeder, William Mark Severa https://www.osti.gov/search/identifier:1761032	Conference Paper – 2020 Conference Paper	2020
Almost optimal classical algorithms for a quantum generalization of Max Cut Quantum Information Processing 2020 Ojas D. Parekh https://www.osti.gov/search/identifier:1643365	Conference Paper – 2019 Conference Paper	2019
A Hybrid Quantum Approximate Optimization Algorithm Incorporating Classical Heuristics 22nd Annual Southwest Quantum Information and Technology Workshop Jaimie Suzette Stephens, Ojas D. Parekh, William Bolden	Abstract – 2019 Abstract	2019
Almost optimal classical approximation algorithms for a quantum generalization of Max-Cut ArXiv version of a paper Sevag Gharibian, Ojas D. Parekh https://www.osti.gov/search/identifier:1642618	Conference Paper – 2019 Conference Paper	2019
Document Title	Type	Year

Results 1–25 of 116

Publications

Application of the Level-2 Quantum Lasserre Hierarchy in Quantum Approximation Algorithms

Neuromorphic scaling advantages for energy-efficient random walk computations

Neuromorphic Graph Algorithms

Beating Random Assignment for Approximating Quantum 2-Local Hamiltonian Problems

Outperforming QAOA on MaxCut with Fast Classical Hyperplane Rounding Algorithms

Application of the Level-2 Quantum Lasserre Hierarchy in Quantum Approximation Algorithms

Provable Advantages for Graph Algorithms in Spiking Neural Networks

Provable advantages for graph algorithms in spiking neural networks

CIS External Review Lightning Presentation: Neuromorphic Graph Algorithms

An approximation algorithm for the MAX-2-Local Hamiltonian problem

Novel Geometric Operations for Linear Programming

Neuromorphic scaling advantages for energy-efficient random walk computations

Brief Announcement: Provable neuromorphic advantages for computing constrained shortest paths

Solving a steady-state pde using spiking networks and neuromorphic hardware

Solving a steady-state pde using spiking networks and neuromorphic hardware

Brief Announcement: Provable neuromorphic advantages for computing constrained shortest paths

Probing a set of trajectories to maximize captured information

Probing a set of trajectories to maximize captured movement

Fundamental Algorithmic Research for Quantum Computing (FAR-QC): Project Overview

Quantum Optimization and Learning and Simulation (QOALAS): Project Overview

A Hybrid Quantum Optimization Algorithm Incorporating Classical Heuristics

Solving IPDEs on Spiking Neuromorphic Hardware

Almost optimal classical algorithms for a quantum generalization of Max Cut

A Hybrid Quantum Approximate Optimization Algorithm Incorporating Classical Heuristics

Almost optimal classical approximation algorithms for a quantum generalization of Max-Cut