Architecture-Aware Synthesis of Stabilizer Circuits from Clifford Tableaus
- URL: http://arxiv.org/abs/2309.08972v3
- Date: Wed, 30 Oct 2024 08:51:05 GMT
- Title: Architecture-Aware Synthesis of Stabilizer Circuits from Clifford Tableaus
- Authors: David Winderl, Qunsheng Huang, Arianne Meijer-van de Griend, Richie Yeung,
- Abstract summary: We contribute to the field of compilation or, more precisely, synthesis by reducing the number of CNOTs in the synthesized quantum circuit.
Our method shows to outperform other state-of-the-art synthesis techniques, when executed with respect to a specific hardware.
- Score: 0.0
- License:
- Abstract: Since quantum computing is currently in the NISQ-Era, compilation strategies to reduce the number of gates executed on specific hardware are required. In this work, we utilize the concept of synthesis of a data structure called Clifford tableaus, focusing on applying CNOTs within the respective connectivity graph of the quantum device. We hence contribute to the field of compilation or, more precisely, synthesis by reducing the number of CNOTs in the synthesized quantum circuit. Upon convergence, our method shows to outperform other state-of-the-art synthesis techniques, when executed with respect to a specific hardware. Upon executing the resulting circuits on real hardware, our synthesized circuits tend to increase the final fidelity and reduce the overall execution times.
Related papers
- 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) - Improving Quantum Circuit Synthesis with Machine Learning [0.7894596908025954]
We show how applying machine learning to unitary datasets permits drastic speedups for synthesis algorithms.
This paper presents QSeed, a seeded synthesis algorithm that employs a learned model to quickly propose resource efficient circuit implementations of unitaries.
arXiv Detail & Related papers (2023-06-09T01:53:56Z) - Majorization-based benchmark of the complexity of quantum processors [105.54048699217668]
We numerically simulate and characterize the operation of various quantum processors.
We identify and assess quantum complexity by comparing the performance of each device against benchmark lines.
We find that the majorization-based benchmark holds as long as the circuits' output states have, on average, high purity.
arXiv Detail & Related papers (2023-04-10T23:01:10Z) - 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) - Compilation of algorithm-specific graph states for quantum circuits [55.90903601048249]
We present a quantum circuit compiler that prepares an algorithm-specific graph state from quantum circuits described in high level languages.
The computation can then be implemented using a series of non-Pauli measurements on this graph state.
arXiv Detail & Related papers (2022-09-15T14:52:31Z) - Decomposition of Matrix Product States into Shallow Quantum Circuits [62.5210028594015]
tensor network (TN) algorithms can be mapped to parametrized quantum circuits (PQCs)
We propose a new protocol for approximating TN states using realistic quantum circuits.
Our results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods.
arXiv Detail & Related papers (2022-09-01T17:08:41Z) - Decoding techniques applied to the compilation of CNOT circuits for NISQ
architectures [0.0]
We present a new algorithm for the synthesis of CNOT circuits based on the solution of the syndrome decoding problem.
Our method addresses the case of ideal hardware with an all-to-all qubit connectivity and the case of near-term quantum devices with restricted connectivity.
arXiv Detail & Related papers (2022-01-17T15:11:36Z) - Scaling Quantum Approximate Optimization on Near-term Hardware [49.94954584453379]
We quantify scaling of the expected resource requirements by optimized circuits for hardware architectures with varying levels of connectivity.
We show the number of measurements, and hence total time to synthesizing solution, grows exponentially in problem size and problem graph degree.
These problems may be alleviated by increasing hardware connectivity or by recently proposed modifications to the QAOA that achieve higher performance with fewer circuit layers.
arXiv Detail & Related papers (2022-01-06T21:02:30Z) - Architecture aware compilation of quantum circuits via lazy synthesis [0.0]
We propose a meta-heuristic that couples the iterative approach of SWAP insertion techniques with greedy architecture aware synthesis routines.
We show that our algorithms show significant reduction in the entangling gate overhead due to compilation.
arXiv Detail & Related papers (2020-12-17T15:20:02Z) - Efficient CNOT Synthesis for NISQ Devices [1.0152838128195467]
In the era of noisy intermediate-scale quantum (NISQ), executing quantum algorithms on actual quantum devices faces unique challenges.
We propose a CNOT synthesis method called the token reduction method to solve this problem.
Our algorithm consistently outperforms the best publicly accessible algorithm for all of the tested quantum architectures.
arXiv Detail & Related papers (2020-11-12T15:13:32Z) - Architecture-Aware Synthesis of Phase Polynomials for NISQ Devices [0.0]
We propose a new algorithm toe quantum circuits for connectivitys, which takes into account the qubit of the quantum computer.
Our algorithm generates circuits with a smaller CNOT depth than the algorithms currently used in Staq and tket.
arXiv Detail & Related papers (2020-04-13T16:26:14Z)
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.