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Quantum Sensing and Communications Being Developed for Nanotechnology

An interdisciplinary quantum communications and sensing research effort has been underway at the NASA Glenn Research Center since the summer of 2000. Researchers in the Communications Technology, Instrumentation and Controls, and Propulsion and Turbomachinery Divisions have been working together to study and develop techniques that use the principle of quantum entanglement (QE). This work is supported principally by the Nanotechnology Base R&T program at Glenn. As applied to communications and sensing, QE is an emerging technology that holds promise as a new and innovative way to communicate faster and farther, and to sense, measure, and image environmental properties in ways that are not possible with existing technology. Quantum entangled photons are "inseparable" as described by a wave function formalism. For two entangled photons, the term "inseparable" means that one cannot describe one photon without completely describing the other. This inseparability gives rise to what appears as "spooky," or nonintuitive, behavior because of the quantum nature of the process. For example, two entangled photons of lower energy can be created simultaneously from a single photon of higher energy in a process called spontaneous parametric down-conversion. Our research is focused on the use of polarization-entangled photons generated by passing a high-energy (blue) photon through a nonlinear beta barium borate crystal to generate two red photons that have orthogonal, but entangled, polarization states. Although the actual polarization state of any one photon is not known until it is measured, the act of measuring the polarization of one photon completely determines the polarization state of its twin because of entanglement. This unique relationship between the photons provides extra information about the system. For example, entanglement makes it easy to distinguish entangled photons from other photons impinging on a detector. For many other applications, ranging from quantum computation and information to quantum sensing, the entanglement property is critical.

Nguyen, Quang-Viet↗

Quantum-accelerated Global Constraint Filtering

Motivated by recent advances in quantum algorithms and gate-model quantum computation, we introduce quantum-accelerated filtering algorithms for global constraints in constraint programming. We adapt recent work in quantum algorithms for graph problems and identify quantum subroutines that accelerate the main domain consistency algorithms for the all different constraint and the global cardinality constraint (gcc). The subroutines are based on quantum algorithms for finding maximum matchings and strongly connected components in graphs, and provide speedups over the best classical algorithms. We detail both complete and bounded-probability frameworks for quantum-accelerated global constraint filtering algorithms within backtracking search.

Quantum algorithms↗

Classical Optimizers for Noisy Intermediate-Scale Quantum Devices

We present a collection of optimizers tuned for usage on Noisy Inter-mediate-Scale Quantum (NISQ) devices. Optimizers have a range of applications in quantum computing, including the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization (QAOA) algorithms. They have further uses in calibration, hyperparameter tuning, machine learning, etc. We employ the VQE algorithm as a case study. VQE is a hybrid algorithm, with a classical minimizer step driving the next evaluation on the quantum processor. While most results to date concentrated on tuning the quantum VQE circuit, our study indicates that in the presence of quantum noise the classical minimizer step is a weak link and a careful choice combined with tuning is required for correct results. We explore state-of-the-art gradient-free optimizers capable of handling noisy, black-box, cost functions and stress-test them using a quantum circuit simulation environment with noise injection capabilities on individual gates. Our results indicate that specifically tuned optimizers are crucial to obtaining valid science results on NISQ hardware, as well as projecting forward on fault tolerant circuits.

Lavrijsen, Wim↗