13 citations · 26 across the 3 of their papers we have counts for
7 papers
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…
SupermarQ: A Scalable Quantum Benchmark Suite
Teague Tomesh, Pranav Gokhale, Victory Omole +7
The emergence of quantum computers as a new computational paradigm has been accompanied by speculation concerning the scope and timeline of their anticipated revolutionary changes.…
TILT: Achieving Higher Fidelity on a Trapped-Ion Linear-Tape Quantum Computing Architecture
Xin-Chuan Wu, Dripto M. Debroy, Yongshan Ding +4
Trapped-ion qubits are a leading technology for practical quantum computing. In this work, we present an architectural analysis of a linear-tape architecture for trapped ions. In o…
SQUARE: Strategic Quantum Ancilla Reuse for Modular Quantum Programs via Cost-Effective Uncomputation
Yongshan Ding, Xin-Chuan Wu, Adam Holmes +4
Compiling high-level quantum programs to machines that are size constrained (i.e. limited number of quantum bits) and time constrained (i.e. limited number of quantum operations) i…
Full-State Quantum Circuit Simulation by Using Data Compression
Xin-Chuan Wu, Sheng Di, Emma Maitreyee Dasgupta +4
Quantum circuit simulations are critical for evaluating quantum algorithms and machines. However, the number of state amplitudes required for full simulation increases exponentiall…
Memory-Efficient Quantum Circuit Simulation by Using Lossy Data Compression
Xin-Chuan Wu, Sheng Di, Franck Cappello +3
In order to evaluate, validate, and refine the design of new quantum algorithms or quantum computers, researchers and developers need methods to assess their correctness and fideli…