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Results for “quantum resource estimation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

Surrogate Optimization for Quantum Circuits

Variational quantum Eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has yet to be realized with few claims of quantum advantage and high resource estimates mainly due to the need for optimization in the presence of noise. Finding algorithms and methods to improve the convergence is essential to accelerate the capabilities of near-term hardware for VQE or more broad applications of hybrid methods in which optimization is required. To this goal we look to use modern approaches recently developed in circuit simulations and stochastic classical optimization that can be combined in a surrogate optimization approach to classical circuits. Using an approximate state vector simulator, we efficiently calculate an approximate Hessian, fed as an input for a detailed quantum circuit simulator. We demonstrate the capabilities of such an approach with and without sampling noise. We also show that this method outperforms Powell in the presence of quantum circuit shot noise by a factor of 2-4

quantum computing↗
NASA NTRSDate not supplied

Incorporating ADAPT-VQE with a Sparse Wavefunction Circuit Simulator to Find Compact Quantum Circuits for Chemical Applications

We implemented the ADAPT-VQE algorithm into our recent classical sparse wavefunction circuit simulator to demonstrate that classical resources can (1) efficiently find a physically motivated compact wavefunction ansatz for further refinement on near-term quantum hardware and (2) benchmark expected results of VQE-based algorithms once the quantum hardware is available to study large-scale applications. In particular, we study the role of the ADAPT-VQE operator pool, molecular basis set selection, and variations such as TETRIS-ADAPT-VQE on the performance of our classical circuit simulator. This work demonstrates the promise of using classical resources to generate highly accurate wavefunctions that can be prepared on quantum hardware to initiate other quantum algorithms such as phase estimation. Our approach harnesses the power of high-performance computing resources with the more limited available quantum computers to map a path toward quantum advantage for electronic structure calculations in chemistry and materials science.

Quantum Computing↗
NASA NTRS2021

Quantum Computing to Accelerate High Fidelity Computational Materials Modeling

In this CIF we worked to develop quantum algorithms for material science simulations based on new ideas recently proposed on plane wave basis sets. Many body simulations are not generally performed in plane wave basis sets on classical hardware, but with newly proposed quantum algorithms, it is possible this will be a highly efficient basis set to run quantum simulations on quantum hardware. Using state of the art classical simulations we ran small test simulations to estimate the resources that will be needed to run such plane wave algorithms on quantum hardware. We demonstrate our approach for a series of atoms and molecular systems.

Norman Tubman↗
NASA NTRSDate not supplied

Simulating a Low-Weight Encoding of the Fermi-Hubbard Model Feedback and Support with QAOA

Recent work [1] has proposed a compact fermion-to-qubit mapping for the Fermi-Hubbard model (FHM), potentially lowering the overhead needed to simulate such a system on quantum hardware. In prior work [2], we numerically investigated how well a quantum annealer could prepare ground states of the FHM encoded using the resource-efficient mapping. In order to compare these results to gate-model systems, we turn to a QAOA-style approach and replace the annealing schedule with both Trotterizations thereof and also more general Hamiltonian-variational ansatze based on the terms of the mapped FH Hamiltonian. We investigate the achievable ground state fidelities of these gate sequences, consider various optimizations of the ansatze structure, and offer resource estimations of the optimized QAOA protocols for near-term hardware.

quantum computing↗
NASA NTRSDate not supplied

Logical Shadow Tomography: Efficient Estimation of Error-mitigated Observables

In near-term quantum applications, reducing errors and improving device reliability is an essential task. Towards these ends, various techniques have been introduced in recent literature, collectively referred to as quantum error mitigation techniques, for reducing errors in pre-fault-tolerant devices. Here, we introduce logical shadow tomography as a versatile error mitigation method. Our technique uses a stabilizer code to encode information in a logical state. Instead of doing active error correction, quantum states will be measured at the end of computation via shadow tomography and non-logical errors are projected out in the classical post-processing. Relative to quantum subspace expansion which requires O(2(M-1)L) experiments to estimate an logical Pauli observable encoded by an [[M, L, d]] code, our technique only requires 2L experiments, an important practical reduction in resources.

Hong-Ye Hu↗