A mixed Dicke state ansatz is introduced that encodes Hamming weight equality and inequality constraints directly into the VQE circuit to preserve feasibility without penalty terms.
Extending the computational reach of a noisy superconducting quantum processor
4 Pith papers cite this work. Polarity classification is still indexing.
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abstract
Quantum computation, a completely different paradigm of computing, benefits from theoretically proven speed-ups for certain problems and opens up the possibility of exactly studying the properties of quantum systems. Yet, because of the inherent fragile nature of the physical computing elements, qubits, achieving quantum advantages over classical computation requires extremely low error rates for qubit operations as well as a significant overhead of physical qubits, in order to realize fault-tolerance via quantum error correction. However, recent theoretical work has shown that the accuracy of computation based off expectation values of quantum observables can be enhanced through an extrapolation of results from a collection of varying noisy experiments. Here, we demonstrate this error mitigation protocol on a superconducting quantum processor, enhancing its computational capability, with no additional hardware modifications. We apply the protocol to mitigate errors on canonical single- and two-qubit experiments and then extend its application to the variational optimization of Hamiltonians for quantum chemistry and magnetism. We effectively demonstrate that the suppression of incoherent errors helps unearth otherwise inaccessible accuracies to the variational solutions using our noisy processor. These results demonstrate that error mitigation techniques will be critical to significantly enhance the capabilities of near-term quantum computing hardware.
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A quantum simulation framework is developed and demonstrated for energy loss and hadronization of a heavy quark in 1+1D SU(2) lattice gauge theory on 18 qubits of IBM hardware, with results matching classical simulations.
VQE with Dicke state ansatz encodes diversification constraints for multiclass portfolio optimization and outperforms other optimizers when paired with CMA-ES on convergence and approximation metrics.
A full-system energy model shows NISQ quantum simulations dominated by error mitigation sampling overhead while FTQC costs are driven by physical qubit overhead from code distance and magic states.
citing papers explorer
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Pure and mixed Dicke state ansatz for equality and inequality constraints in variational quantum eigensolver
A mixed Dicke state ansatz is introduced that encodes Hamming weight equality and inequality constraints directly into the VQE circuit to preserve feasibility without penalty terms.
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A Framework for Quantum Simulations of Energy-Loss and Hadronization in Non-Abelian Gauge Theories: SU(2) Lattice Gauge Theory in 1+1D
A quantum simulation framework is developed and demonstrated for energy loss and hadronization of a heavy quark in 1+1D SU(2) lattice gauge theory on 18 qubits of IBM hardware, with results matching classical simulations.
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Multiclass Portfolio Optimization via Variational Quantum Eigensolver with Dicke State Ansatz
VQE with Dicke state ansatz encodes diversification constraints for multiclass portfolio optimization and outperforms other optimizers when paired with CMA-ES on convergence and approximation metrics.
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Estimating The Energy Consumption of Quantum Computing from A Full System Aspect
A full-system energy model shows NISQ quantum simulations dominated by error mitigation sampling overhead while FTQC costs are driven by physical qubit overhead from code distance and magic states.