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DTSTART;TZID=America/Denver:20231113T090000
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UID:submissions.supercomputing.org_SC23_sess446@linklings.com
SUMMARY:Fourth International Workshop on Quantum Computing Software
DESCRIPTION:QArchSearch:  A Scalable Quantum Architecture Search Package\n
 \nThe current era of quantum computing has yielded several algorithms that
  promise high computational efficiency. While the algorithms are sound in 
 theory, there is little guidance on how to design proper quantum circuits 
 to realize the appropriate unitary transformation to be applied to the inp
 ut qua...\n\n\nAnkit Kulshrestha (University of Delaware), William Berquis
 t (Argonne National Laboratory (ANL)), Ilya Safro (University of Delaware)
 , and Yuri Alexeev (Argonne National Laboratory (ANL))\n------------------
 ---\nAn Ising-Based Model for Qubit Mapping\n\nA crucial step in compiling
  a quantum algorithm involves addressing a layout problem to meet the devi
 ce's layout constraints. The Qubit Mapping and Routing (QMR) problem aims 
 to minimize the number of SWAP gates added to the circuit to fulfill NISQ 
 hardware's connectivity constraints. Although this ...\n\n\nHayato Ushijim
 a-Mwesigwa and Xiaoyuan Liu (Fujitsu Research of America, Inc)\n----------
 -----------\nFourth International Workshop on Quantum Computing Software\n
 \nQuantum computing is emerging as a remarkable technology that promises t
 o achieve major scientific breakthroughs. This includes solving complex pr
 oblems whose solution lies well beyond contemporary and even future superc
 omputers based on conventional technologies. Interacting with these quantu
 m comp...\n\n\nTravis Humble (Oak Ridge National Laboratory (ORNL)), Dmitr
 y Lyakh (NVIDIA Corporation), Yuri Alexeev (Argonne National Laboratory (A
 NL)), Bert de Jong (Lawrence Berkeley National Laboratory (LBNL)), Hausi M
 uller (University of Victoria), and Ojas Parekh (Sandia National Laborator
 ies)\n---------------------\nUsing Azure Quantum Resource Estimator to Eva
 luate Performance of Quantum Algorithms\n\nThe automatic resource estimati
 on tools provided by Azure Quantum and Microsoft Quantum Development Kit i
 s described and examples are given of obtaining resource estimates for fau
 lt tolerant implementations of several quantum algorithms. The AQ Resource
  Estimator tool uses the planar, quantum Instru...\n\n\nWim van Dam, Marii
 a Mykhailova, and Mathias Soeken (Microsoft Corporation)\n----------------
 -----\nEnabling Quantum Computer Simulations on AMD GPUs:  A HIP Backend f
 or Google's qsim\n\nQuantum computer simulators play an essential role in 
 advancing the field of quantum computing, serving as indispensable tools f
 or quantum computer verification, debugging, and quantum algorithm prototy
 ping. Among these simulators, Google's state vector quantum simulator qsim
  has gained significant ...\n\n\nStefano Markidis (KTH Royal Institute of 
 Technology, Sweden)\n---------------------\nSimuQ: A Domain-Specific Langu
 age for Quantum Simulation with Analog Compilation\n\nQuantum Hamiltonian 
 simulation is one of the most promising applications of quantum computing.
  Recent experimental results suggest that Hamiltonian-oriented analog quan
 tum simulation would be advantageous over circuit-oriented digital quantum
  simulation in the NISQ era. We design and implement SimuQ...\n\n\nYuxiang
  Peng and Jacob Young (University of Maryland); Pengyu Liu (Tsinghua Unive
 rsity, China); and Xiaodi Wu (University of Maryland)\n-------------------
 --\nDistributing Circuits Over Heterogeneous, Modular Quantum Computing Ne
 twork Architectures\n\nWe consider the automated compilation of quantum ci
 rcuits to heterogeneous networks of quantum computing modules, sparsely co
 nnected via Bell states. A circuit too large to be implemented on any one 
 module alone requires the insertion of operations, typically gate teleport
 ation or qubit teleportatio...\n\n\nDaniel Mills (Quantinuum)\n-----------
 ----------\nOpen Q&A Session\n\nThe last session of the workshop will be a
 n open session for discussion about all presentations during the event.\n\
 n---------------------\nBGLS:  A Python Package for the Gate-by-Gate Sampl
 ing Algorithm to Simulate Quantum Circuits\n\nThe classical simulation of 
 quantum computers is in general a computationally hard problem. To emulate
  the behavior of realistic devices, it is sufficient to sample bitstrings 
 from circuits. Recently, Ref. [ 5] introduced the so-called gate-by-gate s
 ampling algorithm to sample bitstrings and showed ...\n\n\nAlex Shapiro (S
 wiss Federal Institute of Technology Lausanne (EPFL)) and Ryan LaRose (Mic
 higan State University)\n---------------------\nPrototype of a Batched Qua
 ntum Circuit Simulator for the Vector Engine\n\nState-of-the-art quantum c
 ircuit simulators have mostly focused on scaling the number of qubits. How
 ever, we argue that studying current noisy quantum computers and variation
 al quantum algorithms benefits from high-throughput simulation of intermed
 iate-scale quantum circuits. We present the first im...\n\n\nKeichi Takaha
 shi (Tohoku University); Toshio Mori (Osaka University, RIKEN); and Hiroyu
 ki Takizawa (Tohoku University)\n---------------------\nMaking QIR Executa
 ble\n\nWe present a work-in-progress to create a software toolchain that l
 inks the Quantum Intermediate Representation (QIR) to the hardware-agnosti
 c execution framework XACC. The novelty of this work is an implementation 
 of the QIR specification for use in the XACC framework by translating the 
 QIR to an X...\n\n\nElaine Wong and Sharmin Afrose (Oak Ridge National Lab
 oratory (ORNL)); Meenambika Gowrishankar (University of Tennessee); and Da
 niel Claudino, Vicente Leyton-Ortega, Seth Johnson, and Travis Humble (Oak
  Ridge National Laboratory (ORNL))\n---------------------\nQuantum Computi
 ng Software – Lunch Break\n---------------------\nTowards an Expressive Py
 thon-Native Interface for Quantum Program Development\n\nIn quantum progra
 mming, there is a natural conflict between high-level expression and low-l
 evel control. Existing quantum programming solutions optimize for either t
 he expressiveness of quantum programs or ease of composing quantum program
 s, but not both. In this work, we describe a quantum programm...\n\n\nLaur
 en Capelluto, Yi-Ting Chen, Ryan Shaffer, Aaron Berdy, Kshitij Chhabra, Je
 an-Christophe Jaskula, Eric Kessler, and Yunong Shi (Amazon Web Services)\
 n---------------------\nQuantum Computing Software – Afternoon Break\n----
 -----------------\nJuliQAOA:  Fast, Flexible QAOA Simulation\n\nWe introdu
 ce JuliQAOA, a simulation package specifically built for the Quantum Alter
 nating Operator Ansatz (QAOA). JuliQAOA does not require a circuit-level d
 escription of QAOA problems, or another package to simulate such circuits,
  instead relying on a more direct linear algebra implementation. Thi...\n\
 n\nJohn Golden, Andreas Baertschi, Dan O'Malley, Elijah Pelofske, and Step
 han Eidenbenz (Los Alamos National Laboratory (LANL))\n-------------------
 --\nQASMTrans: A QASM Quantum Transpiler Framework for NISQ Devices\n\nIn 
 the field of Quantum Computing, transpilation plays a crucial role in conv
 erting high-level quantum circuits into versions that are specific to the 
 underlying quantum devices. This process necessitates a consideration of a
  range of factors, such as the basis gate set, device topology, error prof
 i...\n\n\nFei Hua (Rutgers University, Pacific Northwest National Laborato
 ry (PNNL)); meng wang (University of British Columbia, Pacific Northwest N
 ational Laboratory (PNNL)); Gushu Li (University of Pennsylvania); Bo Peng
  and Chenxu Liu (Pacific Northwest National Laboratory (PNNL)); Muqing Zhe
 ng (Lehigh University, Pacific Northwest National Laboratory (PNNL)); Samu
 el Stein (Pacific Northwest National Laboratory (PNNL)); Yufei Ding (Unive
 rsity of California San Diego); Eddy Z. Zhang (Rutgers University); Travis
  Humble (Oak Ridge National Laboratory (ORNL)); and Ang Li (Pacific Northw
 est National Laboratory (PNNL))\n---------------------\nMEMQSim:  Highly M
 emory-Efficient and Modularized Quantum State-Vector Simulation\n\nWe intr
 oduce a highly memory-efficient state vector simulation of quantum circuit
 s premised on data compression, harnessing the capabilities of both CPUs a
 nd GPUs. We have elucidated the inherent challenges in architecting this s
 ystem, while concurrently proposing our tailored solutions. Moreover, w...
 \n\n\nBoyuan Zhang (Indiana University), Bo Fang (Pacific Northwest Nation
 al Laboratory (PNNL)), Qiang Guan (Kent State University), Ang Li (Pacific
  Northwest National Laboratory (PNNL)), and Dingwen Tao (Indiana Universit
 y)\n---------------------\nEnabling Scalable VQE Simulation on Leading HPC
  Systems\n\nLarge-scale simulations of quantum circuits pose significant c
 hallenges, especially in the context of quantum chemistry, due to the numb
 er of qubits, circuit depth, and the number of circuits needed per problem
 . High-performance computing (HPC) systems offer massive computational cap
 abilities that c...\n\n\nMeng Wang (University of British Columbia, Pacifi
 c Northwest National Laboratory (PNNL)); Fei Hua (Rutgers University, Paci
 fic Northwest National Laboratory (PNNL)); Chenxu Liu, Nicholas Bauman, an
 d Karol Kowalski (Pacific Northwest National Laboratory (PNNL)); Daniel Cl
 audino and Travis Humble (Oak Ridge National Laboratory (ORNL)); Prashant 
 Nair (University of British Columbia); and Ang Li (Pacific Northwest Natio
 nal Laboratory (PNNL))\n---------------------\nA Reference Implementation 
 for a Quantum Message Passing Interface\n\nPractical applications of quant
 um computing are currently limited by the number of qubits that can be set
  with reasonable fidelities for each system. Therefore, a distributed quan
 tum computing system with multiple quantum computers coherently connected 
 is highly demanding. To realize the internode c...\n\n\nYue Shi and Tommy 
 Nguyen (Pacific Northwest National Laboratory (PNNL), University of Washin
 gton); Samuel Stein, Tim Stavenger, and Marvin Warner (Pacific Northwest N
 ational Laboratory (PNNL)); Martin Roetteler and Torsten Hoefler (Microsof
 t Corporation); and Ang Li (Pacific Northwest National Laboratory (PNNL))\
 n---------------------\nTISCC:   A Surface Code Compiler and Resource Esti
 mator for Trapped-Ion Processors\n\nWe introduce the Trapped-Ion Surface C
 ode Compiler (TISCC), a software tool that generates circuits for a univer
 sal set of surface code patch operations in terms of a native trapped-ion 
 gate set. To accomplish this, TISCC manages an internal representation of 
 a trapped-ion system where a repeating p...\n\n\nTyler LeBlond, Justin Lie
 tz, Christopher Seck, and Ryan Bennink (Oak Ridge National Laboratory (ORN
 L))\n---------------------\nQuantum Computing Software – Morning Break\n--
 -------------------\nFast Simulation of High-Depth QAOA Circuits\n\nUntil 
 high-fidelity quantum computers with a large number of qubits become widel
 y available, classical simulation remains a vital tool for algorithm desig
 n, tuning, and validation. We present a simulator for the Quantum Approxim
 ate Optimization Algorithm (QAOA). Our simulator is designed with the go..
 .\n\n\nDanylo Lykov (JPMorgan Chase, Argonne National Laboratory (ANL)); R
 uslan Shaydulin and Yue Sun (JPMorgan Chase); Yuri Alexeev (Argonne Nation
 al Laboratory (ANL)); and Marco Pistoia (JPMorgan Chase)\n\nTag: Quantum C
 omputing, Software Engineering\n\nRegistration Category: Workshop Reg Pass
 \n\nSession Chairs: Yuri Alexeev (NVIDIA Corporation); Bert de Jong (Lawre
 nce Berkeley National Laboratory (LBNL)); Travis Humble (Oak Ridge Nationa
 l Laboratory (ORNL), Quantum Science Centre); Dmitry Liakh (NVIDIA Corpora
 tion); Hausi Muller (University of Victoria, British Columbia; IEEE Quantu
 m Week); and Ojas Parekh (Sandia National Laboratories)
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