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DTSTART;TZID=America/Denver:20231113T153000
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UID:submissions.supercomputing.org_SC23_sess446_ws_qcs124@linklings.com
SUMMARY:QArchSearch:  A Scalable Quantum Architecture Search Package
DESCRIPTION:Ankit Kulshrestha (University of Delaware), William Berquist (
 Argonne National Laboratory (ANL)), Ilya Safro (University of Delaware), a
 nd Yuri Alexeev (Argonne National Laboratory (ANL))\n\nThe current era of 
 quantum computing has yielded several algorithms that promise high computa
 tional efficiency. While the algorithms are sound in theory, there is litt
 le guidance on how to design proper quantum circuits to realize the approp
 riate unitary transformation to be applied to the input quantum state. We 
 present QArchSearch, an AI based quantum architecture search package with 
 the QTensor library as a backend that provides a principled and automated 
 approach to finding the best model given a task and input quantum state. W
 e show that the search package is able to efficiently scale the search to 
 large quantum circuits and enables exploration of more complex models for 
 different quantum applications. QArchSearch runs at scale and high efficie
 ncy on high-performance computing systems using two-level parallelization 
 scheme on both CPUs and GPUs, which has been demonstrated on the Polaris s
 upercomputer .\n\nTag: Quantum Computing, Software Engineering\n\nRegistra
 tion Category: Workshop Reg Pass\n\nSession Chairs: Yuri Alexeev (NVIDIA C
 orporation); Bert de Jong (Lawrence Berkeley National Laboratory (LBNL)); 
 Travis Humble (Oak Ridge National Laboratory (ORNL), Quantum Science Centr
 e); Dmitry Liakh (NVIDIA Corporation); Hausi Muller (University of Victori
 a, British Columbia; IEEE Quantum Week); and Ojas Parekh (Sandia National 
 Laboratories)\n\n
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