activity
20182022
most citedAn LLVM-based C++ Compiler Toolchain for Variational Hybrid Quantum-Classical Algorithms and Quantum Accelerators

13 citations · 17 across the 2 of their papers we have counts for

collaborators

8 papers

quant-ph20224 cited

A Scalable Microarchitecture for Efficient Instruction-Driven Signal Synthesis and Coherent Qubit Control

Nader Khammassi, Randy W. Morris, Shavindra Premaratne +7

Execution of quantum algorithms requires a quantum computer architecture with a dedicated quantum instruction set that is capable of supporting translation of workloads into actual…

quant-ph202213 cited

An LLVM-based C++ Compiler Toolchain for Variational Hybrid Quantum-Classical Algorithms and Quantum Accelerators

Pradnya Khalate, Xin-Chuan Wu, Shavindra Premaratne +6

Variational algorithms are a representative class of quantum computing workloads that combine quantum and classical computing. This paper presents an LLVM-based C++ compiler toolch…

quant-ph2020

Designing high-fidelity multi-qubit gates for semiconductor quantum dots through deep reinforcement learning

Sahar Daraeizadeh, Shavindra P. Premaratne, A. Y. Matsuura

In this paper, we present a machine learning framework to design high-fidelity multi-qubit gates for quantum processors based on quantum dots in silicon, with qubits encoded in the…

quant-ph2020

Engineering the Cost Function of a Variational Quantum Algorithm for Implementation on Near-Term Devices

Shavindra P. Premaratne, A. Y. Matsuura

Variational hybrid quantum-classical algorithms are some of the most promising workloads for near-term quantum computers without error correction. The aim of these variational algo…

quant-ph2020

Enhancing a Near-Term Quantum Accelerator's Instruction Set Architecture for Materials Science Applications

Xiang Zou, Shavindra P. Premaratne, M. Adriaan Rol +7

Quantum computers with tens to hundreds of noisy qubits are being developed today. To be useful for real-world applications, we believe that these near-term systems cannot simply b…

quant-ph2019

Machine-learning based three-qubit gate for realization of a Toffoli gate with cQED-based transmon systems

Sahar Daraeizadeh, Shavindra P. Premaratne, Xiaoyu Song +2

We use machine learning techniques to design a 50 ns three-qubit flux-tunable controlled-controlled-phase gate with fidelity of >99.99% for nearest-neighbor coupled transmons in ci…