activity
20192022
most citedAnalysis of Quantum Approximate Optimization Algorithm under Realistic Noise in Superconducting Qubits

35 citations · 58 across the 6 of their papers we have counts for

collaborators

8 papers

quant-ph2022★ 1 cited

Optimization of Quantum Read-Only Memory Circuits

Koustubh Phalak, Mahabubul Alam, Abdullah Ash-Saki +2

Quantum computing is a rapidly expanding field with applications ranging from optimization all the way to complex machine learning tasks. Quantum memories, while lacking in practic…

quant-ph2021

A Survey and Tutorial on Security and Resilience of Quantum Computing

Abdullah Ash Saki, Mahabubul Alam, Koustubh Phalak +3

Present-day quantum computers suffer from various noises or errors such as gate error, relaxation, dephasing, readout error, and crosstalk. Besides, they offer a limited number of…

quant-ph2021★ 3 cited

A Quantum Circuit Obfuscation Methodology for Security and Privacy

Aakarshitha Suresh, Abdullah Ash Saki, Mahabubul Alam +2

Optimization of quantum circuits using an efficient compiler is key to its success for NISQ computers. Several 3rd party compilers are evolving to offer improved performance for la…

cs.ET2020

Resiliency Analysis and Improvement of Variational Quantum Factoring in Superconducting Qubit

Ling Qiu, Mahabubul Alam, Abdullah Ash-Saki +1

Variational algorithm using Quantum Approximate Optimization Algorithm (QAOA) can solve the prime factorization problem in near-term noisy quantum computers. Conventional Variation…

cs.ET2020

Accelerating Quantum Approximate Optimization Algorithm using Machine Learning

Mahabubul Alam, Abdullah Ash-Saki, Swaroop Ghosh

We propose a machine learning based approach to accelerate quantum approximate optimization algorithm (QAOA) implementation which is a promising quantum-classical hybrid algorithm…

quant-ph2019★ 35 cited

Analysis of Quantum Approximate Optimization Algorithm under Realistic Noise in Superconducting Qubits

Mahabubul Alam, Abdullah Ash-Saki, Swaroop Ghosh

The quantum approximate optimization algorithm (QAOA) is a promising quantum-classical hybrid technique to solve combinatorial optimization problems in near-term gate-based noisy q…

cs.ET2019★ 19 cited

Study of Decoherence in Quantum Computers: A Circuit-Design Perspective

Abdullah Ash Saki, Mahabubul Alam, Swaroop Ghosh

Decoherence of quantum states is a major hurdle towards scalable and reliable quantum computing. Lower decoherence (i.e., higher fidelity) can alleviate the error correction overhe…

cs.ET2019

Addressing Temporal Variations in Qubit Quality Metrics for Parameterized Quantum Circuits

Mahabubul Alam, Abdullah Ash-Saki, Swaroop Ghosh

The public access to noisy intermediate-scale quantum (NISQ) computers facilitated by IBM, Rigetti, D-Wave, etc., has propelled the development of quantum applications that may off…