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Overview of NASA QuAIL Team Research

NASA is constantly confronting massively challenging computational problems. These problems have the potential to limit mission scope and aim. NASA's Quantum Artificial Intelligence Laboratory (QuAIL) Group was formed to determine the potential for quantum computation to enable more ambitious NASA missions in the future. This presentation highlights recent work by the QuAIL team that is focused on physics insights and applications associated with the D-Wave 2000Q quantum annealing hardware that is located at NASA Ames Research Center.

Shon Grabbe

Boundary and Initial Condition Issues for Computational Fluid Dynamics (CFD) and Modeling and Simulation (Mod-Sim)

For many important classes of Mod-Sim problems, even quantum computing will not enable accurate predictions/computation vis-à-vis the real world due to boundary/initial condition shortfalls in terms of both range of parameters and requisite amplitudes/coverage. The Mod-Sim community needs to consider going forward the knowability of initial and boundary conditions.

Dennis M. Bushnell

High dimensional similarity search with quantum assisted variational autoencoder

Recent progress in quantum algorithms and hardware is indicator of the potential importance of quantum computing in the next future. However, finding suitable application areas remains an active area of research. Quantum machine learning [1] is touted as a potential approach to demonstrate quantum advantage within both the gate-model [2,3] and the adiabatic [4,5] schemes. For instance, the Quantum-assisted Variational Autoencoder (QVAE) [6] has been proposed as a quantum enhancement to the discrete VAE [7]. We extend on previous work and study the real-world applicability of a QVAE, specifically, for similarity search in large-scale high dimensional datasets. While similarity search algorithms are available for low dimensional datasets, scaling to billion-scale datasets with thousands of dimensions is non-trivial. We show how the latent-space representation of a QVAE can be used to construct a space-efficient search index. We back up our claims by experimental results which show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset. Further, we show real-world speedups compared to linear search and demonstrate memory efficient scaling to large-scale datasets.

Nicholas D Gao

High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder

Recent progress in quantum algorithms and hardware indicates the potential importance of quantum computing in the near future. However, finding suitable application areas remains an active area of research. Quantum machine learning is touted as a potential approach to demonstrate quantum advantage within both the gate-model and the adiabatic schemes. For instance, the QVAE has been proposed as a quantum enhancement to the discrete VAE. We extend on previous work and study the real-world applicability of a QVAE by presenting a proof-of-concept for similarity search in large-scale high-dimensional datasets. While exact and fast similarity search algorithms are available for low dimensional datasets, scaling to high-dimensional data is non-trivial. We show how to construct a space-efficient search index based on the latent space representation of a QVAE. Our experiments show a correlation between the Hamming distance in the embedded space and the Euclidean distance in the original space on the MODIS dataset. Further, we find real-world speedups compared to linear search and demonstrate memory-efficient scaling to half a billion data points.

Data mining, similarity search, quantum machine le

Simulation of Non-Markovian Dynamics on IBM QX

Currently available quantum computers allow us to run proof of principle algorithms that are unitary in their nature. Therefore, this architecture is unoptimized for simulation of an open quantum system. Here we present a method that helps us to overcome unitarity. We show how to run a non-Markovian evolution of a qubit system. We discuss all the discrepancies from theoretical predictions.

Wudarski, Filip A.

Dynamical Simulation of Probabilities

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices(such as random number generators). Self-orgainizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed. Special attention was focused upon coupled stochastic processes, defined in terms of conditional probabilities, for which joint probability does not exist. Simulations of quantum probabilities are also discussed.

number generators quantum probabilities

Modeling Entanglement-Based Quantum Key Distribution for the NASA Quantum Communications Analysis Suite

One of the most practical, and sought after, applications of quantum mechanics in the field of information science is the use of entanglement distribution to communicate quantum information effectively. Similar to the continued improvements of functional quantum computers over the past decade, advances in demonstrations of entanglement distribution over long distances may enable new applications in aeronautics and space communications. The existing NASA Quantum Communications Analysis Suite (NQCAS) software models such applications, but limited experimental data exists to verify the model’s theoretical results. There is, however, a large body of experimental data in the relevant literature for entanglement-based quantum key distribution (QKD). This paper details a Monte Carlo based QKD model that uses NQCAS input parameters to generate an estimated QKD link budget for verification of NQCAS. The model generates link budget statistics like key rates, error rates, and S values that can then be compared to the experimental values in the literature. Preliminary comparisons show many similarities between the simulated and experimental data, supporting the model’s validity. A verified NQCAS model will inform experimental work conducted in Glenn Research Center’s (GRC) NASA Quantum Metrology Laboratory (NQML), supporting the United States Quantum Initiative and potential NASA missions.

NASA Quantum Communications Analysis Suite

Quantum Speedup for Aeroscience and Engineering

Algorithms and hardware for quantum computing (QC) are reaching a critical stage in their development and have the potential to generate a paradigm shift in computing capability across a range of fields. Opportunities are growing for genuine impact of these systems over a timescale of 10-15 years, and there has been significant investment both from government agencies and private industry in its development. However, utilization of quantum phenomena is extraordinarily challenging due to its delicate nature and difficulties in measurement and control. A clear path exists toward demonstrating the advantages of QC over existing high-performance computing for some physics and materials science problems but addressing practical computational challenges in other fields, though promising, is at an early stage of development. Reaching the next level of development will require strategic coordination between physicists, computer & information scientists, mathematicians, and engineers, in order to transition this technology from the laboratory to robust and scalable computations for practical problems, especially those of interest to the aeroscience and engineering community. This community has been relying on high-performance computing heavily and will surely want to be informed of the developments in QC. This survey introduces the background and current state of the art in QC, as well as its perceived opportunities and challenges.

Peyman Givi

Electron-impact vibrational relaxation in high-temperature nitrogen

Vibrational relaxation process of N2 molecules by electron-impact is examined for the future planetary entry environments. Multiple-quantum transitions from excited states to higher/lower states are considered for the electronic ground state of the nitrogen molecule N2 (X 1Sigma-g(+)). Vibrational excitation and deexcitation rate coefficients obtained by computational quantum chemistry are incorporated into the 'diffusion model' to evaluate the time variations of vibrational number densities of each energy state and total vibrational energy. Results show a non-Boltzmann distribution of number densities at the earlier stage of relaxation, which in turn suppresses the equilibrium process but affects little the time variation of total vibrational energy. An approximate rate equation and a corresponding relaxation time from the excited states, compatible with the system of flow conservation equations, are derived. The relaxation time from the excited states indicates the weak dependency of the initial vibrational temperature. The empirical curve-fit formula for the improved e-V relaxation time is obtained.

Lee, Jong-Hun

Using Quasiparticle Poisoning To Detect Photons

According to a proposal, a phenomenon associated with excitation of quasiparticles in certain superconducting quantum devices would be exploited as a means of detecting photons with exquisite sensitivity. The phenomenon could also be exploited to perform medium-resolution spectroscopy. The proposal was inspired by the observation that Coulomb blockade devices upon which some quantum logic gates are based are extremely sensitive to quasiparticles excited above the superconducting gaps in their leads. The presence of quasiparticles in the leads can be easily detected via the charge states. If quasiparticles could be generated in the leads by absorption of photons, then the devices could be used as very sensitive detectors of electromagnetic radiation over the spectral range from x-rays to submillimeter waves. The devices in question are single-Cooper-pair boxes (SCBs), which are mesoscopic superconducting devices developed for quantum computing. An SCB consists of a small superconducting island connected to a reservoir via a small tunnel junction and connected to a voltage source through a gate capacitor. An SCB is an artificial two-level quantum system, the Hamiltonian of which can be controlled by the gate voltage. One measures the expected value of the charge of the eigenvectors of this quantum system by use of a radio-frequency single-electron transistor. A plot of this expected value of charge as a function of gate voltage resembles a staircase that, in the ideal case, consists of steps of height 2 e (where e is the charge of one electron). Experiments have shown that depending on the parameters of the device, quasiparticles in the form of "broken" Cooper pairs present in the reservoir can tunnel to the island, giving rise to steps of 1 e. This effect is sometimes called "poisoning." Simulations have shown that an extremely small average number of quasiparticles can generate a 1-e periodic signal. In a device according to the proposal, this poisoning would be turned to advantage. Depending on the wavelength, an antenna or other component would be used to couple radiation into the reservoir, wherein the absorption of photons would break Cooper pairs, thereby creating quasiparticles that, in turn, would tunnel to the island, creating a 1-e signal. On the basis of conservative estimates of device parameters derived from experimental data and computational simulations that fit the data, it has been estimated that the noise equivalent power of a device according to the proposal could be as low as 6 10(exp -22) W/Hz(exp 1/2). It has also been estimated that the spectroscopic resolution (photon energy divided by increment of photon energy) of such a device in visible light would exceed 100.

Echternach, Pierre

Quantum Search in Hilbert Space

A proposed quantum-computing algorithm would perform a search for an item of information in a database stored in a Hilbert-space memory structure. The algorithm is intended to make it possible to search relatively quickly through a large database under conditions in which available computing resources would otherwise be considered inadequate to perform such a task. The algorithm would apply, more specifically, to a relational database in which information would be stored in a set of N complex orthonormal vectors, each of N dimensions (where N can be exponentially large). Each vector would constitute one row of a unitary matrix, from which one would derive the Hamiltonian operator (and hence the evolutionary operator) of a quantum system. In other words, all the stored information would be mapped onto a unitary operator acting on a quantum state that would represent the item of information to be retrieved. Then one could exploit quantum parallelism: one could pose all search queries simultaneously by performing a quantum measurement on the system. In so doing, one would effectively solve the search problem in one computational step. One could exploit the direct- and inner-product decomposability of the unitary matrix to make the dimensionality of the memory space exponentially large by use of only linear resources. However, inasmuch as the necessary preprocessing (the mapping of the stored information into a Hilbert space) could be exponentially expensive, the proposed algorithm would likely be most beneficial in applications in which the resources available for preprocessing were much greater than those available for searching.

Zak, Michail

Computational Nanotechnology Molecular Electronics, Materials and Machines

This presentation covers research being performed on computational nanotechnology, carbon nanotubes and fullerenes at the NASA Ames Research Center. Topics cover include: nanomechanics of nanomaterials, nanotubes and composite materials, molecular electronics with nanotube junctions, kinky chemistry, and nanotechnology for solid-state quantum computers using fullerenes.

Srivastava, Deepak

Improved Fermion Hamiltonians for Quantum Simulations

Constructing improved hamiltonians for gauge theories coupled to fermonic matter will be important for improving continuum limit extrapolations of quantum computations. In this talk we will present a formulation for simulating ASQTAD fermions for lattice computation and provide fault tolerant resource costs in terms of primitive group operations. We additionally show that the scaling of energies with respect to the lattice spacing are better than for the unimproved Hamiltonian for toy models.

Quantum Algorithms

Dynamical Decoupling of Crosstalk on Superconducting Qubit Devices

Current NISQ devices are prone to errors. In order to be used for practical applications or achieve fault-tolerant thresholds, strategies to suppress error rates will be needed to maximize the potential of noisy devices. Dynamical decoupling (DD) is one such strategy for suppressing — or at least alleviating — the effects of decoherence, in which sequences of pulses are applied to qubits to decouple their interaction with the environment. Through experimental runs performed on several Rigetti quantum computing units (QPUs), we first demonstrate that DD is capable of improving coherence times for isolated qubits, as well as suppressing errors caused by the ZZ coupling between pairs of qubits. Extending this framework to cycles containing2-qubit gates, we show that DD can be inserted to decouple qubits from crosstalk occurring during neighboring 2-qubit gates, and demonstrate the efficacy of this procedure on quantum approximate optimization algorithm (QAOA) circuits. We also explore the usage of tailored DD sequences for the suppression of characterized error channels. We are grateful for support from the NASA Ames Research Center and from the DARPA ONISQ program under interagency agreement IAA 8839,Annex 114. HYH is supported by the USRA Feynman QuantumAcademy funded by the NAMS R&D Student Program and a UCHellman Fellowship. JS, ZGI and ZW are supported by USRA NASAAcademic Mission Service (NNA16BD14C).

Dynamical decoupling

Self-consistent Quantum Iteratively Sparsified Hamiltonian Algorithm (SQuISH)

Due to coherence time limitations, reducing the resources required to run quantum algorithms and simulate physical systems on a quantum computer is crucial. With regards to Hamiltonian simulation, a significant effort has focused on building efficient algorithms using various factorizations and truncations, typically derived from the Hamiltonian alone. We introduce a new paradigm for improving Hamiltonian simulation and reducing the cost of ground state problems based on ideas recently developed for classical chemistry simulations. The key idea is that one can find efficient ways to reduce resources needed by quantum algorithms by making use of two key pieces of information: the Hamiltonian operator and an approximate ground state wavefunction. We refer to our algorithm as the self-consistent quantum iteratively sparsified Hamiltonian (SQuISH). By performing our scheme iteratively, one can drive SQuISH to create an accurate wavefunction using a truncated, resource-efficient Hamiltonian. By utilizing this more compact Hamiltonian, our algorithm provides an approach to reduce the gate complexity of ground state calculations on quantum hardware. As proof of principle, we implement SQuISH using configuration interaction for small molecules and coupled cluster for larger systems. Through our combination of approaches, we demonstrate how it performs on a range of systems, the largest of which would require more than 200 qubits to run on quantum hardware.

Diana Chamaki

Simulation of Laser Cooling and Trapping in Engineering Applications

An advanced computer code is undergoing development for numerically simulating laser cooling and trapping of large numbers of atoms. The code is expected to be useful in practical engineering applications and to contribute to understanding of the roles that light, atomic collisions, background pressure, and numbers of particles play in experiments using laser-cooled and -trapped atoms. The code is based on semiclassical theories of the forces exerted on atoms by magnetic and optical fields. Whereas computer codes developed previously for the same purpose account for only a few physical mechanisms, this code incorporates many more physical mechanisms (including atomic collisions, sub-Doppler cooling mechanisms, Stark and Zeeman energy shifts, gravitation, and evanescent-wave phenomena) that affect laser-matter interactions and the cooling of atoms to submillikelvin temperatures. Moreover, whereas the prior codes can simulate the interactions of at most a few atoms with a resonant light field, the number of atoms that can be included in a simulation by the present code is limited only by computer memory. Hence, the present code represents more nearly completely the complex physics involved when using laser-cooled and -trapped atoms in engineering applications. Another advantage that the code incorporates is the possibility to analyze the interaction between cold atoms of different atomic number. Some properties that cold atoms of different atomic species have, like cross sections and the particular excited states they can occupy when interacting with each other and light fields, play important roles not yet completely understood in the new experiments that are under way in laboratories worldwide to form ultracold molecules. Other research efforts use cold atoms as holders of quantum information, and more recent developments in cavity quantum electrodynamics also use ultracold atoms to explore and expand new information-technology ideas. These experiments give a hint on the wide range of applications and technology developments that can be tackled using cold atoms and light fields. From more precise atomic clocks and gravity sensors to the development of quantum computers, there will be a need to completely understand the whole ensemble of physical mechanisms that play a role in the development of such technologies. The code also permits the study of the dynamic and steady-state operations of technologies that use cold atoms. The physical characteristics of lasers and fields can be time-controlled to give a realistic simulation of the processes involved such that the design process can determine the best control features to use. It is expected that with the features incorporated into the code it will become a tool for the useful application of ultracold atoms in engineering applications. Currently, the software is being used for the analysis and understanding of simple experiments using cold atoms, and for the design of a modular compact source of cold atoms to be used in future research and development projects. The results so far indicate that the code is a useful design instrument that shows good agreement with experimental measurements (see figure), and a Windows-based user-friendly interface is also under development.

Ramirez-Serrano, Jaime

Scaling Properties of Algorithms in Nanotechnology

At the present time, several technologies are pressing the limits of microminiature manufacturing. In semiconductor technology, for example, the Intel Pentium Pro (which is used in the Department of Energy's ASCI 'red' parallel supercomputer system) and the DEC Alpha 21164 (which is used in the CRAY T3E) both are fabricated using 0.35 micron process technology. Recently Texas Instruments (TI) announced the availability of 0.25 micron technology chips by the end of 1996 and plans to have 0.18 micron devices in production within two years. However, some significant challenges lie down the road. These include the skyrocketing cost of manufacturing plants, the 0.1 micron foreseeable limit of the photolithography process, quantum effects, data communication bandwidth limitations, heat dissipation, and others. Some related microminiature technologies include micro-electromechanical systems (MEMS), opto-electronic devices, quantum computing, biological computing, and others. All of these technologies require the fabrication of devices whose sizes are approaching the nanometer level. As such they are often collectively referred to with the name 'nanotechnology'. Clearly nanotechnology in this general sense is destined to be a very important technology of the 21st century. The ultimate dream in this arena is 'molecular nanotechnology', in other words the fabrication of devices and materials with most or all atoms and molecules in a pre-programmed position, possibly placed there by 'nano-robots'. This futuristic capability will probably not be achieved for at least two decades. However, it appears that somewhat less ambitious variations of molecular nanotechnology, such as devices and materials based on 'buckyballs' and 'nanotubes' may be realized significantly sooner, possibly within ten years or so. Even at the present time, semiconductor devices are approaching the regime where quantum chemical effects must be considered in design.

Saini, Subhash