Matrix Product States, Random Matrix Theory and the Principle of Maximum Entropy

Using random matrix techniques and the theory of Matrix Product States we show that reduced density matrices of quantum spin chains have generically maximum entropy.Comment: 11 pages, 4 figure

Superconducting resonators as beam splitters for linear-optics quantum computation

A functioning quantum computer will be a machine that builds up, in a programmable way, nonclassical correlations in a multipartite quantum system. Linear optics quantum computation (LOQC) is an approach for achieving this function that requires only simple, reliable linear optical elements, namely beam splitters and phase shifters. Nonlinear optics is only required in the form of single-photon sources for state initialization, and detectors. However, the latter remain difficult to achieve with high fidelity. A new setting for quantum optics has arisen in circuit quantum electrodynamics (cQED) using superconducting (SC) quantum devices, and opening up the way to LOQC using microwave, rather than visible photons. Much progress is being made in SC qubits and cQED: high-fidelity Fock state generation and qubit measurements provide single photon sources and detection. Here we show that the LOQC toolkit in cQED can be completed with high-fidelity (>99.92%) linear optical elements.Comment: 4 pages, 3 figure

Cross-Modal Health State Estimation

Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geospatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.Comment: Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18/1

Interpolated potential energy surfaces and dynamics for atom exchange between H and H⁺₃, and D and H⁺₃

Two ab initio interpolated potential energy surfaces have been constructed to study the dynamics of atomic hydrogen/deuterium exchange in collisions of H(3)(+) with H (D). One of the surfaces is based on energy calculations using quadratic configuration interaction with single and double excitations. The second includes a perturbative treatment of the triple excitations and an additive correction for basis set deficiency. Results from classical dynamics simulation of the exchange reaction on these surfaces are presented and discussed

Scaling issues in ensemble implementations of the Deutsch-Jozsa algorithm

We discuss the ensemble version of the Deutsch-Jozsa (DJ) algorithm which attempts to provide a "scalable" implementation on an expectation-value NMR quantum computer. We show that this ensemble implementation of the DJ algorithm is at best as efficient as the classical random algorithm. As soon as any attempt is made to classify all possible functions with certainty, the implementation requires an exponentially large number of molecules. The discrepancies arise out of the interpretation of mixed state density matrices.Comment: Minor changes, reference added, replaced with publised versio

Associations among Wine Grape Microbiome, Metabolome, and Fermentation Behavior Suggest Microbial Contribution to Regional Wine Characteristics.

UnlabelledRegionally distinct wine characteristics (terroir) are an important aspect of wine production and consumer appreciation. Microbial activity is an integral part of wine production, and grape and wine microbiota present regionally defined patterns associated with vineyard and climatic conditions, but the degree to which these microbial patterns associate with the chemical composition of wine is unclear. Through a longitudinal survey of over 200 commercial wine fermentations, we demonstrate that both grape microbiota and wine metabolite profiles distinguish viticultural area designations and individual vineyards within Napa and Sonoma Counties, California. Associations among wine microbiota and fermentation characteristics suggest new links between microbiota, fermentation performance, and wine properties. The bacterial and fungal consortia of wine fermentations, composed from vineyard and winery sources, correlate with the chemical composition of the finished wines and predict metabolite abundances in finished wines using machine learning models. The use of postharvest microbiota as an early predictor of wine chemical composition is unprecedented and potentially poses a new paradigm for quality control of agricultural products. These findings add further evidence that microbial activity is associated with wine terroirImportanceWine production is a multi-billion-dollar global industry for which microbial control and wine chemical composition are crucial aspects of quality. Terroir is an important feature of consumer appreciation and wine culture, but the many factors that contribute to terroir are nebulous. We show that grape and wine microbiota exhibit regional patterns that correlate with wine chemical composition, suggesting that the grape microbiome may influence terroir In addition to enriching our understanding of how growing region and wine properties interact, this may provide further economic incentive for agricultural and enological practices that maintain regional microbial biodiversity

Polarization Requirements for Ensemble Implementations of Quantum Algorithms with a Single Bit Output

We compare the failure probabilities of ensemble implementations of quantum algorithms which use pseudo-pure initial states, quantified by their polarization, to those of competing classical probabilistic algorithms. Specifically we consider a class algorithms which require only one bit to output the solution to problems. For large ensemble sizes, we present a general scheme to determine a critical polarization beneath which the quantum algorithm fails with greater probability than its classical competitor. We apply this to the Deutsch-Jozsa algorithm and show that the critical polarization is 86.6%.Comment: 11 pages, 3 figure