activity
20192026
most citedHAMMER: boosting fidelity of noisy Quantum circuits by exploiting Hamming behavior of erroneous outcomes

24 citations · 44 across the 13 of their papers we have counts for

collaborators

18 papers

quant-ph2026

ChainForge: Characterizing Embedding as the Bottleneck in Quantum Annealer Workloads

Kanishka Jayathilake, Cordelia Brumley, Tanner Smith +1

Quantum Annealers (QAs) are among the first commercially scaled quantum computing systems designed for large-scale optimization. Unlike digital systems that execute sequences of co…

quant-ph2026

Stabilizer Code-Generic Universal Fault-Tolerant Quantum Computation

Nicholas J. C. Papadopoulos, Ramin Ayanzadeh

Fault-tolerant quantum computation allows quantum computations to be carried out while resisting unwanted noise. Several error-correcting codes have been developed to achieve this…

cs.CR2026

BloQBench: A Blockchain Benchmarking Framework for Quantum Supremacy

Nicholas J. C. Papadopoulos, Ramin Ayanzadeh

As quantum computing matures, characterizing its practical workloads and verifying quantum supremacy presents a significant challenge. Current benchmarking and claims rely on trust…

quant-ph2025

On the Potential of Quantum Computing in Classical Program Analysis

Yicheng Guang, Pietro Zanotta, Kai Zhou +2

Classical program analysis techniques, such as abstract interpretation and symbolic execution, are essential for ensuring software correctness, optimizing performance, and enabling…

quant-ph2024★ 1 cited

Promatch: Extending the Reach of Real-Time Quantum Error Correction with Adaptive Predecoding

Narges Alavisamani, Suhas Vittal, Ramin Ayanzadeh +2

Fault-tolerant quantum computing relies on Quantum Error Correction, which encodes logical qubits into data and parity qubits. Error decoding is the process of translating the meas…

quant-ph2023

Skipper: Improving the Reach and Fidelity of Quantum Annealers by Skipping Long Chains

Ramin Ayanzadeh, Moinuddin Qureshi

Quantum Annealers (QAs) operate as single-instruction machines, lacking a SWAP operation to overcome limited qubit connectivity. Consequently, multiple physical qubits are chained…

quant-ph2023★ 1 cited

Enigma: Application-Layer Privacy for Quantum Optimization on Untrusted Computers

Ramin Ayanzadeh, Ahmad Mousavi, Amirhossein Basareh +2

The Early Fault-Tolerant (EFT) era is emerging, where modest Quantum Error Correction (QEC) can enable quantum utility before full-scale fault tolerance. Quantum optimization is a…

quant-ph2022★ 3 cited

FrozenQubits: Boosting Fidelity of QAOA by Skipping Hotspot Nodes

Ramin Ayanzadeh, Narges Alavisamani, Poulami Das +1

Quantum Approximate Optimization Algorithm (QAOA) is one of the leading candidates for demonstrating the quantum advantage using near-term quantum computers. Unfortunately, high de…

quant-ph2022★ 24 cited

HAMMER: boosting fidelity of noisy Quantum circuits by exploiting Hamming behavior of erroneous outcomes

Swamit Tannu, Poulami Das, Ramin Ayanzadeh +1

Quantum computers with hundreds of qubits will be available soon. Unfortunately, high device error-rates pose a significant challenge in using these near-term quantum systems to po…

quant-ph2022

Quantum-Assisted Greedy Algorithms

Ramin Ayanzadeh, John E Dorband, Milton Halem +1

We show how to leverage quantum annealers (QAs) to better select candidates in greedy algorithms. Unlike conventional greedy algorithms that employ problem-specific heuristics for…

quant-ph2021

EQUAL: Improving the Fidelity of Quantum Annealers by Injecting Controlled Perturbations

Ramin Ayanzadeh, Poulami Das, Swamit S. Tannu +1

Quantum computing is an information processing paradigm that uses quantum-mechanical properties to speedup computationally hard problems. Although promising, existing gate-based qu…

quant-ph2020

Multi-Qubit Correction for Quantum Annealers

Ramin Ayanzadeh, John Dorband, Milton Halem +1

We present \emph{multi-qubit correction} (MQC) as a novel postprocessing method for quantum annealers that views the evolution in an open-system as a Gibbs sampler and reduces a se…

quant-ph2020

An Ensemble Approach for Compressive Sensing with Quantum

Ramin Ayanzadeh, Milton Halem, Tim Finin

We leverage the idea of a statistical ensemble to improve the quality of quantum annealing based binary compressive sensing. Since executing quantum machine instructions on a quant…

quant-ph2020

Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach

Ramin Ayanzadeh, Milton Halem, Tim Finin

We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning…

quant-ph2019

Quantum-Assisted Greedy Algorithms

Ramin Ayanzadeh, Milton Halem, John Dorband +1

We show how to leverage quantum annealers to better select candidates in greedy algorithms. Unlike conventional greedy algorithms that employ problem-specific heuristics for making…

math.OC2019

A Survey on Compressive Sensing: Classical Results and Recent Advancements

Ahmad Mousavi, Mehdi Rezaee, Ramin Ayanzadeh

Recovering sparse signals from linear measurements has demonstrated outstanding utility in a vast variety of real-world applications. Compressive sensing is the topic that studies…

cs.IT2019★ 2 cited

SAT-based Compressive Sensing

Ramin Ayanzadeh, Milton Halem, Tim Finin

We propose to reduce the original well-posed problem of compressive sensing to weighted-MAX-SAT. Compressive sensing is a novel randomized data acquisition approach that linearly s…

cs.IT2019★ 13 cited

Quantum Annealing Based Binary Compressive Sensing with Matrix Uncertainty

Ramin Ayanzadeh, Seyedahmad Mousavi, Milton Halem +1

Compressive sensing is a novel approach that linearly samples sparse or compressible signals at a rate much below the Nyquist-Shannon sampling rate and outperforms traditional sign…