Software-Hardware Co-Optimization for Computational Chemistry on Superconducting Quantum Processors

@article{Li2021SoftwareHardwareCF,
  title={Software-Hardware Co-Optimization for Computational Chemistry on Superconducting Quantum Processors},
  author={Gushu Li and Yunong Shi and Ali Javadi-Abhari},
  journal={2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA)},
  year={2021},
  pages={832-845}
}
Computational chemistry is the leading application to demonstrate the advantage of quantum computing in the near term. However, large-scale simulation of chemical systems on quantum computers is currently hindered due to a mismatch between the computational resource needs of the program and those available in today’s technology. In this paper we argue that significant new optimizations can be discovered by co-designing the application, compiler, and hardware. We show that multiple optimization… 
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14 Citations
Background Citations
10
Methods Citations
3

14 Citations

Paulihedral: a generalized block-wise compiler optimization framework for Quantum simulation kernels

Experimental results show that Paulihedral can outperform state-of-the-art compiler infrastructures in a wide-range of applications on both near-term superconducting quantum processors and future fault-tolerant quantum computers.

On the Co-Design ofQuantum Software and Hardware

In this review, it is pointed out that the quantum software and hardware systems should be designed collaboratively to fully exploit the potential of quantum computing.

On the Co-Design of Quantum Software and Hardware

This review of quantum software and hardware systems should be designed collaboratively to fully exploit the potential of quantum computing and discusses some potential future directions following the co-design principle.

2QAN: a quantum compiler for 2-local qubit hamiltonian simulation algorithms

This work develops a compiler, named 2QAN, to optimize quantum circuits for 2-local qubit Hamiltonian simulation problems, a framework which includes the important quantum approximate optimization algorithm (QAOA).

Full-stack quantum computing systems in the NISQ era: algorithm-driven and hardware-aware compilation techniques

The need for tight co-design among adjacent layers as well as vertical cross-layer design to extract the most from noisy intermediate-scale quantum (NISQ) processors which are both error-prone and severely constrained in resources is emphasized.

Interaction graph-based profiling of quantum benchmarks for improving quantum circuit mapping techniques

This paper characterized a large body of quantum circuits by extracting graph theory-based properties from their corresponding qubit interaction graphs and afterwards clustered them based on those and other commonly used circuit-describing parameters to provide an all-gathering, easy-to-use, categorized and characterized benchmark set available for the quantum computing community.

TQSim: A Case for Reuse-Focused Tree-Based Quantum Circuit Simulation

A noisy simulation technique called Tree-Based Quantum Circuit Simulation (TQSim), which exploits the reusability of the intermediate results during the noisy simulation and reduces computation.

Pulse-Level Optimization of Parameterized Quantum Circuits for Variational Quantum Algorithms

Pulse-level access to quantum machines and understanding of their two-qubit interactions are utilized to optimize the design of two- qubit entanglers in a manner suitable for VQAs, and results show that pulse-optimized ansatze reduce state preparation times by more than half, maintain expressibility relative to standard PQCs, and are more trainable through local cost function analysis.

Evaluation of Parameterized Quantum Circuits with Cross-Resonance Pulse-Driven Entanglers

Pulse-level access to quantum machines, understanding of their two-qubit interactions, and, more importantly, the knowledge of VQAs are utilized, to customize the design of two- qubit entanglers.

Not All SWAPs Have the Same Cost: A Case for Optimization-Aware Qubit Routing

  • Ji LiuPeiyi LiHuiyang Zhou
  • Computer Science
    2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
  • 2022
NASSC (Not All Swaps have the Same Cost) is the first algorithm that considers the subsequent optimizations during the routing step, and optimization-aware qubit routing leads to better routing decisions and benefits subsequent optimizations.

References

SHOWING 1-10 OF 75 REFERENCES

Automated optimization of large quantum circuits with continuous parameters

An automated methods for optimizing quantum circuits of the size and type expected in quantum computations that outperform classical computers are developed and implemented and a collection of fast algorithms capable of optimizing large-scale quantum circuits are reported.

Towards Efficient Superconducting Quantum Processor Architecture Design

This paper proposes an automatic design flow to generate simplified superconducting quantum processor architecture with negligible performance loss for different quantum programs and shows that the design methodology could outperform IBM's general-purpose design schemes with better Pareto-optimal results.

Hartree-Fock on a superconducting qubit quantum computer

Several quantum simulations of chemistry with up to one dozen qubits are performed, including modeling the isomerization mechanism of diazene, and error-mitigation strategies based on N-representability that dramatically improve the effective fidelity of the experiments are demonstrated.

Ground-state energy estimation of the water molecule on a trapped-ion quantum computer

An extensible co-design framework for solving chemistry problems on a trapped-ion quantum computer is described and applied to estimating the ground-state energy of the water molecule using the variational quantum eigensolver (VQE) method.

Co-Designing a Scalable Quantum Computer with Trapped Atomic Ions

This article shows how a modular quantum computer of any size can be engineered from ion crystals, and how the wiring between ion trap qubits can be tailored to a variety of applications and quantum computing protocols.

Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers

It is shown that fine grained spatial and temporal variations in hardware parameters can be exploited to obtain an average 2.9x (and up to 18x) improvement in program success rate over the industry standard IBM Qiskit compiler.

Elucidating reaction mechanisms on quantum computers

This work shows how quantum computers can be used to elucidate the reaction mechanism for biological nitrogen fixation in nitrogenase, by augmenting classical calculation of reaction mechanisms with reliable estimates for relative and activation energies that are beyond the reach of traditional methods.

Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets

The experimental optimization of Hamiltonian problems with up to six qubits and more than one hundred Pauli terms is demonstrated, determining the ground-state energy for molecules of increasing size, up to BeH2.

Quantum Chemistry Calculations on a Trapped-Ion Quantum Simulator

Quantum-classical hybrid algorithms are emerging as promising candidates for near-term practical applications of quantum information processors in a wide variety of fields ranging from chemistry to…

An open-source, industrial-strength optimizing compiler for quantum programs

Many of the principles behind Quilc’s design are described, the compiler is demonstrated, and the authoring quantum software a simpler exercise by making architectural details less burdensome to the author.
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