9 papers
InterQ: Communication-Aware Scheduling Across Modular QPUs with Classical and Quantum Links
Vinooth Kulkarni, Jaehyun Lee, Lauren Li +5
As quantum computing scales toward practical workloads, future systems are expected to move beyond single monolithic processors toward modular architectures that connect multiple Q…
QuMod: Parallel Quantum Job Scheduling on Modular QPUs using Circuit Cutting
Vinooth Kulkarni, Aaron Orenstein, Xinpeng Li +3
The quantum computing community is increasingly positioning quantum processors as accelerators within classical HPC workflows, analogous to GPUs and TPUs. However, many real-world…
hdlib 2.0: Extending Machine Learning Capabilities of Vector-Symbolic Architectures
Fabio Cumbo, Kabir Dhillon, Daniel Blankenberg
Following the initial publication of hdlib, a Python library for designing Vector-Symbolic Architectures (VSA), we introduce a major extension that significantly enhances its machi…
An Automatic Pipeline for the Integration of Python-Based Tools into the Galaxy Platform: Application to the anvi'o Framework
Fabio Cumbo, Jayadev Joshi, Daniel Blankenberg
The integration of command-line tools into the Galaxy platform is crucial for making complex computational methods accessible to a broader audience and ensuring reproducible resear…
Quantum Hyperdimensional Computing: a foundational paradigm for quantum neuromorphic architectures
Fabio Cumbo, Rui-Hao Li, Bryan Raubenolt +4
A significant challenge in quantum computing (QC) is developing learning models that truly align with quantum principles, as many current approaches are complex adaptations of clas…
Efficient Quantum Protein Structure Prediction with Problem-Agnostic Ansatzes
Hanna Linn, Rui-Hao Li, Alexander Holden +6
Accurately predicting protein structures from amino acid sequences remains a fundamental challenge in computational biology, with profound implications for understanding biological…