Quantum Computation of Hydrogen Bond Dynamics and Vibrational Spectra

Calculating the observable properties of chemical systems is often classically intractable, and is widely viewed as a promising application of quantum information processing. This is because a full description of chemical behavior relies upon the complex interplay of quantum-mechanical electrons and nuclei, demanding an exponential scaling of computational resources with system size. While considerable progress has been made in mapping electronic-structure calculations to quantum hardware, these approaches are unsuitable for describing the quantum dynamics of nuclei, proton- and hydrogen-transfer processes, or the vibrational spectra of molecules. Here, we use the QSCOUT ion-trap quantum computer to determine the quantum dynamics and vibrational properties of a shared proton within a short-strong hydrogen-bonded system. For a range of initial states, we experimentally drive the ion-trap system to emulate the quantum trajectory of the shared proton wavepacket as it evolves along the potential surface generated by the nuclear frameworks and electronic structure. We then extract the characteristic vibrational frequencies for the shared proton motion to spectroscopic accuracy and determine all energy eigenvalues of the system Hamiltonian to > 99.9% fidelity. Our approach offers a new paradigm for studying the quantum chemical dynamics and vibrational spectra of molecules, and when combined with quantum algorithms for electronic structure, opens the possibility to describe the complete behavior of molecules using exclusively quantum computation techniques.Comment: 10 pages, 4 figure

Error mitigation, optimization, and extrapolation on a trapped ion testbed

Current noisy intermediate-scale quantum (NISQ) trapped-ion devices are subject to errors around 1% per gate for two-qubit gates. These errors significantly impact the accuracy of calculations if left unchecked. A form of error mitigation called Richardson extrapolation can reduce these errors without incurring a qubit overhead. We demonstrate and optimize this method on the Quantum Scientific Computing Open User Testbed (QSCOUT) trapped-ion device to solve an electronic structure problem. We explore different methods for integrating this error mitigation technique into the Variational Quantum Eigensolver (VQE) optimization algorithm for calculating the ground state of the HeH+ molecule at 0.8 Angstrom. We test two methods of scaling noise for extrapolation: time-stretching the two-qubit gates and inserting two-qubit gate identity operations into the ansatz circuit. We find the former fails to scale the noise on our particular hardware. Scaling our noise with global gate identity insertions and extrapolating only after a variational optimization routine, we achieve an absolute relative error of 0.363% +- 1.06 compared to the true ground state energy of HeH+. This corresponds to an absolute error of 0.01 +- 0.02 Hartree; outside chemical accuracy, but greatly improved over our non error mitigated estimate. We ultimately find that the efficacy of this error mitigation technique depends on choosing the right implementation for a given device architecture and sampling budget.Comment: 16 pages, 11 figure

Sample-efficient verification of continuously-parameterized quantum gates for small quantum processors

Most near-term quantum information processing devices will not be capable of implementing quantum error correction and the associated logical quantum gate set. Instead, quantum circuits will be implemented directly using the physical native gate set of the device. These native gates often have a parameterization (e.g., rotation angles) which provide the ability to perform a continuous range of operations. Verification of the correct operation of these gates across the allowable range of parameters is important for gaining confidence in the reliability of these devices. In this work, we demonstrate a procedure for sample-efficient verification of continuously-parameterized quantum gates for small quantum processors of up to approximately 10 qubits. This procedure involves generating random sequences of randomly-parameterized layers of gates chosen from the native gate set of the device, and then stochastically compiling an approximate inverse to this sequence such that executing the full sequence on the device should leave the system near its initial state. We show that fidelity estimates made via this technique have a lower variance than fidelity estimates made via cross-entropy benchmarking. This provides an experimentally-relevant advantage in sample efficiency when estimating the fidelity loss to some desired precision. We describe the experimental realization of this technique using continuously-parameterized quantum gate sets on a trapped-ion quantum processor from Sandia QSCOUT and a superconducting quantum processor from IBM Q, and we demonstrate the sample efficiency advantage of this technique both numerically and experimentally

Characterizing and mitigating coherent errors in a trapped ion quantum processor using hidden inverses

Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits, enabling performance of precise, repeatable operations followed by measurements. Currently, these noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence such that small algorithms can be performed reliably. While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development. Demonstrations of these small algorithms over the past few years, coupled with the idea that imperfect algorithm performance can be caused by several dominant noise sources in the quantum processor, which can be measured and calibrated during algorithm execution or in post-processing, has led to the use of noise mitigation to improve typical computational results. Conversely, small benchmark algorithms coupled with noise mitigation can help diagnose the nature of the noise, whether systematic or purely random. Here, we outline the use of coherent noise mitigation techniques as a characterization tool in trapped-ion testbeds. We perform model-fitting of the noisy data to determine the noise source based on realistic physics focused noise models and demonstrate that systematic noise amplification coupled with error mitigation schemes provides useful data for noise model deduction. Further, in order to connect lower level noise model details with application specific performance of near term algorithms, we experimentally construct the loss landscape of a variational algorithm under various injected noise sources coupled with error mitigation techniques. This type of connection enables application-aware hardware codesign, in which the most important noise sources in specific applications, like quantum chemistry, become foci of improvement in subsequent hardware generations.Comment: 9 pages, 5 figure

Broadband Ultrafast Terahertz Spectroscopy in the 25 T Split Florida-Helix

We describe the development of a broadband (0.3–10 THz) optical pump-terahertz probe spectrometer with an unprecedented combination of temporal resolution (≤200 fs) operating in external magnetic fields as high as 25 T using the new Split Florida-Helix magnet system. Using this new instrument, we measure the transient dynamics in a gallium arsenide four-quantum well sample after photoexcitation at 800 nm