t$|$ket$\rangle$ : A Retargetable Compiler for NISQ Devices

• URL: http://arxiv.org/abs/2003.10611v3
• Date: Fri, 24 Apr 2020 10:51:22 GMT
• Title: t$|$ket$\rangle$ : A Retargetable Compiler for NISQ Devices
• Authors: Seyon Sivarajah and Silas Dilkes and Alexander Cowtan and Will Simmons and Alec Edgington and Ross Duncan
• Abstract summary: t$|$ket$rangle$ is a language-agnostic optimising compiler designed to generate code for a variety of NISQ devices. The compiler has been extensively benchmarked and outperforms most competitors in terms of circuit optimisation and qubit routing.
• Score: 55.41644538483948
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present t$|$ket$\rangle$, a quantum software development platform produced by Cambridge Quantum Computing Ltd. The heart of t$|$ket$\rangle$ is a language-agnostic optimising compiler designed to generate code for a variety of NISQ devices, which has several features designed to minimise the influence of device error. The compiler has been extensively benchmarked and outperforms most competitors in terms of circuit optimisation and qubit routing.

Related papers

• Weaver: A Retargetable Compiler Framework for FPQA Quantum Architectures [0.5571222258950509]
  New quantum hardware technologies are emerging, such as Trapped Ions, Neutral Atoms (or FPQAs), Silicon Spin Qubits, etc. There is a growing need for a retargetable compiler that can efficiently adapt existing code to these emerging hardware platforms. We present $Weaver$, the first, performant, and verifiable retargetable quantum compiler framework.
  arXiv  Detail & Related papers  (2024-09-12T09:28:30Z)
• Quantum Compiling with Reinforcement Learning on a Superconducting Processor [55.135709564322624]
  We develop a reinforcement learning-based quantum compiler for a superconducting processor. We demonstrate its capability of discovering novel and hardware-amenable circuits with short lengths. Our study exemplifies the codesign of the software with hardware for efficient quantum compilation.
  arXiv  Detail & Related papers  (2024-06-18T01:49:48Z)
• Computational Capabilities and Compiler Development for Neutral Atom Quantum Processors: Connecting Tool Developers and Hardware Experts [3.4115342075432435]
  Neutral Atom Quantum Computing (NAQC) emerges as a promising hardware platform. This work investigates the broad spectrum of capabilities intrinsic to the NAQC platform and its implications on the compilation process.
  arXiv  Detail & Related papers  (2023-09-15T18:00:00Z)
• The Basis of Design Tools for Quantum Computing: Arrays, Decision Diagrams, Tensor Networks, and ZX-Calculus [55.58528469973086]
  Quantum computers promise to efficiently solve important problems classical computers never will. A fully automated quantum software stack needs to be developed. This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.
  arXiv  Detail & Related papers  (2023-01-10T19:00:00Z)
• Compiler Optimization for Quantum Computing Using Reinforcement Learning [3.610459670994051]
  We propose a reinforcement learning framework for developing optimized quantum circuit compilation flows. The proposed framework is set up with a selection of compilation passes from IBM's Qiskit and Quantinuum's TKET. It significantly outperforms both individual compilers in 73% of cases regarding the expected fidelity.
  arXiv  Detail & Related papers  (2022-12-08T19:00:01Z)
• Towards Optimal VPU Compiler Cost Modeling by using Neural Networks to Infer Hardware Performances [58.720142291102135]
  'VPUNN' is a neural network-based cost model trained on low-level task profiling. It consistently outperforms the state-of-the-art cost modeling in Intel's line of VPU processors.
  arXiv  Detail & Related papers  (2022-05-09T22:48:39Z)
• Arline Benchmarks: Automated Benchmarking Platform for Quantum Compilers [0.0]
  Open-source software package, Arline Benchmarks, is designed to perform automated benchmarking of quantum compilers. We compare several quantum compilation frameworks based on a set of important metrics. We propose a concept of composite compilation pipeline that combines compiler-specific circuit optimizations in a single compilation stack.
  arXiv  Detail & Related papers  (2022-02-28T18:48:01Z)
• Enabling Retargetable Optimizing Compilers for Quantum Accelerators via a Multi-Level Intermediate Representation [78.8942067357231]
  We present a multi-level quantum-classical intermediate representation (IR) that enables an optimizing, retargetable, ahead-of-time compiler. We support the entire gate-based OpenQASM 3 language and provide custom extensions for common quantum programming patterns and improved syntax. Our work results in compile times that are 1000x faster than standard Pythonic approaches, and 5-10x faster than comparative standalone quantum language compilers.
  arXiv  Detail & Related papers  (2021-09-01T17:29:47Z)
• Extending C++ for Heterogeneous Quantum-Classical Computing [56.782064931823015]
  qcor is a language extension to C++ and compiler implementation that enables heterogeneous quantum-classical programming, compilation, and execution in a single-source context. Our work provides a first-of-its-kind C++ compiler enabling high-level quantum kernel (function) expression in a quantum-language manner.
  arXiv  Detail & Related papers  (2020-10-08T12:49:07Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.