The Trilinear Hamiltonian: A Zero Dimensional Model of Hawking Radiation from a Quantized Source

We investigate a quantum parametric amplifier with dynamical pump mode, viewed as a zero-dimensional model of Hawking radiation from an evaporating black hole. The conditions are derived under which the spectrum of particles generated from vacuum fluctuations deviates from the thermal spectrum predicted for the conventional parametric amplifier. We find that significant deviations arise when the pump mode (black hole) has emitted nearly half of its initial energy into the signal (Hawking radiation) and idler (in-falling particle) modes. As a model of black hole dynamics, this finding lends support to the view that late-time Hawking radiation contains information about the quantum state of the black hole and is entangled with the black hole's quantum gravitational degrees of freedom.Comment: 18 pages, 6 figures, Submitted to New Journal of Physics focus issue: "Classical and Quantum Analogues for Gravitational Phenomena and Related Effects

Suppressing quantum circuit errors due to system variability

We present a post-compilation quantum circuit optimization technique that takes into account the variability in error rates that is inherent across present day noisy quantum computing platforms. This method consists of computing isomorphic subgraphs to input circuits and scoring each using heuristic cost functions derived from system calibration data. Using standard algorithmic test circuits we show that it is possible to recover on average nearly 40% of missing fidelity using better qubit selection via efficient to compute cost functions. We demonstrate additional performance gains by considering qubit placement over multiple quantum processors. The overhead from these tools is minimal with respect to other compilation steps such as qubit routing as the number of qubits increases. As such, our method can be used to find qubit mappings for problems at the scale of quantum advantage and beyond.Comment: 8 pages, 6 figure

A combined quantum-classical method applied to material design: optimization and discovery of photochromic materials for photopharmacology applications

Integration of quantum chemistry simulations, machine learning techniques, and optimization calculations is expected to accelerate material discovery by making large chemical spaces amenable to computational study; a challenging task for classical computers. In this work, we develop a combined quantum-classical computing scheme involving the computational-basis Variational Quantum Deflation (cVQD) method for calculating excited states of a general classical Hamiltonian, such as Ising Hamiltonian. We apply this scheme to the practical use case of generating photochromic diarylethene (DAE) derivatives for photopharmacology applications. Using a data set of 384 DAE derivatives quantum chemistry calculation results, we show that a factorization-machine-based model can construct an Ising Hamiltonian to accurately predict the wavelength of maximum absorbance of the derivatives, $\lambda_{\rm max}$, for a larger set of 4096 DAE derivatives. A 12-qubit cVQD calculation for the constructed Ising Hamiltonian provides the ground and first four excited states corresponding to five DAE candidates possessing large $\lambda_{\rm max}$. On a quantum simulator, results are found to be in excellent agreement with those obtained by an exact eigensolver. Utilizing error suppression and mitigation techniques, cVQD on a real quantum device produces results with accuracy comparable to the ideal calculations on a simulator. Finally, we show that quantum chemistry calculations for the five DAE candidates provides a path to achieving large $\lambda_{\rm max}$ and oscillator strengths by molecular engineering of DAE derivatives. These findings pave the way for future work on applying hybrid quantum-classical approaches to large system optimization and the discovery of novel materials.Comment: 13pages, 9 figure

Quantum computing with Qiskit

We describe Qiskit, a software development kit for quantum information science. We discuss the key design decisions that have shaped its development, and examine the software architecture and its core components. We demonstrate an end-to-end workflow for solving a problem in condensed matter physics on a quantum computer that serves to highlight some of Qiskit's capabilities, for example the representation and optimization of circuits at various abstraction levels, its scalability and retargetability to new gates, and the use of quantum-classical computations via dynamic circuits. Lastly, we discuss some of the ecosystem of tools and plugins that extend Qiskit for various tasks, and the future ahead

Real Person Interaction in Visual Attention Research

Abstract. An important development in cognitive psychology in the past decade has been the examination of visual attention during real social interaction. This contrasts traditional laboratory studies of attention, including "social attention" in which observers perform tasks alone. In this review, we show that although the lone-observer method has been central to attention research, real person interaction paradigms have not only uncovered the processes that occur during "joint attention" but have also revealed attentional processes previously thought not to occur. Furthermore, the examination of some visual attention processes almost invariably requires the use of real person paradigms. While we do not argue for an increase in "ecological validity" for its own sake, we do suggest that research using real person interaction has greatly benefited the development of visual attention theories

Pneumococcal density and respiratory co-detection in severe pediatric pneumonia in Laos

There is growing evidence on the importance of bacterial/viral interaction in the course of pneumonia. In Laos, no study has investigated respiratory pathogen co-detection. We conducted a study at Mahosot Hospital in Vientiane to determine whether bacterial/viral co-detection and pneumococcal density are associated with severe pneumonia. Between December 2013 and December 2016, 934 under 5 years old hospitalized children with ARI were enrolled. Swabs from the upper respiratory tract were collected and analyzed by real-time PCR. The most common co-detected microorganisms were Streptococcus pneumoniae/Haemophilus influenzae (24%), Respiratory Syncytial Virus (RSV)/S. pneumoniae (12%) and RSV/H. influenzae (16%). Pneumococcal density was 4.52 times higher in influenza virus positive participants. RSV/S. pneumoniae and RSV/H. influenzae co-detections were positively associated with severe pneumonia in univariate analysis (OR 1.86, 95%CI:1.22–2.81, p = 0.003 and OR 2.09, 95%CI:1.46-3.00), but not confirmed in adjusted analysis (aOR 0.72, 95%CI:0.38–1.6, p = 0.309 and aOR 1.37, 95%CI:0.73–2.58). In RSV positive patients, there was no association between pneumococcal density and severe pneumonia. Our findings confirmed an association between pneumococcal density and influenza but not RSV severe pneumonia in young children. Results highlight the complexity of the interaction of viral/bacterial pathogens, which might not have a simple synergistic action in the evolution of pneumonia

Constructing “Packages” of Evidence-Based Programs to Prevent Youth Violence: Processes and Illustrative Examples From the CDC’s Youth Violence Prevention Centers

This paper describes the strategic efforts of six National Centers of Excellence in Youth Violence Prevention (YVPC), funded by the U.S. Centers for Disease Control and Prevention, to work in partnership with local communities to create comprehensive evidence-based program packages to prevent youth violence. Key components of a comprehensive evidence-based approach are defined and examples are provided from a variety of community settings (rural and urban) across the nation that illustrate attempts to respond to the unique needs of the communities while maintaining a focus on evidence-based programming and practices. At each YVPC site, the process of selecting prevention and intervention programs addressed the following factors: (1) community capacity, (2) researcher and community roles in selecting programs, (3) use of data in decision-making related to program selection, and (4) reach, resources, and dosage. We describe systemic barriers to these efforts, lessons learned, and opportunities for policy and practice. Although adopting an evidence-based comprehensive approach requires significant upfront resources and investment, it offers great potential for preventing youth violence and promoting the successful development of children, families and communities