Efficient Quantum Circuit Compilation for Near-Term Quantum Advantage

Abstract

Quantum noise in real-world devices poses a significant challenge in achieving practical quantum advantage, since accurately compiled and executed circuits are typically deep and highly susceptible to decoherence. To facilitate the implementation of complex quantum algorithms on noisy hardware, we propose an approximate method for compiling target quantum circuits into brick-wall layouts. This new circuit design consists of two-qubit CNOT gates that can be directly implemented on real quantum computers, in conjunction with optimized one-qubit gates, to approximate the essential dynamics of the original circuit while significantly reducing its depth. Our approach is evaluated through numerical simulations of time-evolution circuits for the critical Ising model, quantum Fourier transformation, and Haar-random quantum circuits, as well as experiments on IBM quantum platforms. By accounting for compilation error and circuit noise, we demonstrate that time evolution and quantum Fourier transformation circuits achieve high compression rates, while random quantum circuits are less compressible. The degree of compression is related to the rate of entanglement accumulation in the target circuit. In particular, experiments on IBM platforms achieve a compression rate of $12.5$ for $N=12$, significantly extending the application of current quantum devices. Furthermore, large-scale numerical simulations for system sizes up to $N=30$ reveal that the optimal depth $d_{\max }$ to achieve maximal overall fidelity is independent of system size $N$, suggesting the scalability of our method for large quantum devices in terms of quantum resources.

13 pages, 9 figures

References in corpus (37)

• Quantum Computing in the NISQ era and beyond
• Supplementary information for "Quantum supremacy using a programmable superconducting processor"
• Variational Quantum Algorithms
• Quantum computational advantage using photons
• A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States
• Matrix Product States, Projected Entangled Pair States, and variational renormalization group methods for quantum spin systems
• Error mitigation for short-depth quantum circuits
• Logical quantum processor based on reconfigurable atom arrays
• Matrix Product States and Projected Entangled Pair States: Concepts, Symmetries, and Theorems
• Quantum Error Mitigation
• Noise tailoring for scalable quantum computation via randomized compiling
• Hybrid quantum-classical algorithms and quantum error mitigation
• High-fidelity parallel entangling gates on a neutral atom quantum computer
• Random Quantum Circuits
• Barren Plateaus in Variational Quantum Computing
• Noise Resilience of Variational Quantum Compiling
• Model-free readout-error mitigation for quantum expectation values
• Solving the sampling problem of the Sycamore quantum circuits
• Efficient tensor network simulation of IBM's Eagle kicked Ising experiment
• Riemannian Adaptive Optimization Methods
• IBM Quantum Computers: Evolution, Performance, and Future Directions
• Phase transition in Random Circuit Sampling
• Efficient classical simulation of noisy random quantum circuits in one dimension
• A Site-Resolved 2D Quantum Simulator with Hundreds of Trapped Ions
• Classically optimized Hamiltonian simulation
• NISQ Computers: A Path to Quantum Supremacy
• Towards adiabatic quantum computing using compressed quantum circuits
• Riemannian optimization of isometric tensor networks
• Quantum Fourier Transform Has Small Entanglement
• Variational circuit compiler for quantum error correction
• Optimizing quantum circuits with Riemannian gradient flow
• Comprehensive characterization of three-qubit Grover search algorithm on IBM's 127-qubit superconducting quantum computers
• QGOpt: Riemannian optimization for quantum technologies
• Noise effects on purity and quantum entanglement in terms of physical implementability
• Optimization Techniques on Riemannian Manifolds
• Locally purified density operators for noisy quantum circuits
• Simulating the quantum Fourier transform, Grover's algorithm, and the quantum counting algorithm with limited entanglement using tensor-networks

Cited by in corpus (1)

• Riemannian quantum circuit optimization based on matrix product operators