Light Curve Patterns and Seismology of a White Dwarf with Complex Pulsation

The ZZ Ceti star KUV 02464+3239 was observed over a whole season at the mountain station of Konkoly Observatory. A rigorous frequency analysis revealed 6 certain periods between 619 and 1250 seconds, with no shorter period modes present. We use the observed periods, published effective temperature and surface gravity, along with the model grid code of Bischoff-Kim, Montgomery and Winget (2008) to perform a seismological analysis. We find acceptable model fits with masses between 0.60 and 0.70 M_Sun. The hydrogen layer mass of the acceptable models are almost always between 10^-4 and 10^-6 M_*. In addition to our seismological results, we also show our analysis of individual light curve segments. Considering the non-sinusoidal shape of the light curve and the Fourier spectra of segments showing large amplitude variations, the importance of non-linear effects in the pulsation is clearly seen.Comment: 5 pages, 6 figures, in "Stellar Pulsation: Challenges for Theory and Observation", Eds. J. Guzik and P. A. Bradley, AIP

Quantum Process Estimation via Generic Two-Body Correlations

Performance of quantum process estimation is naturally limited to fundamental, random, and systematic imperfections in preparations and measurements. These imperfections may lead to considerable errors in the process reconstruction due to the fact that standard data analysis techniques presume ideal devices. Here, by utilizing generic auxiliary quantum or classical correlations, we provide a framework for estimation of quantum dynamics via a single measurement apparatus. By construction, this approach can be applied to quantum tomography schemes with calibrated faulty state generators and analyzers. Specifically, we present a generalization of "Direct Characterization of Quantum Dynamics" [M. Mohseni and D. A. Lidar, Phys. Rev. Lett. 97, 170501 (2006)] with an imperfect Bell-state analyzer. We demonstrate that, for several physically relevant noisy preparations and measurements, only classical correlations and small data processing overhead are sufficient to accomplish the full system identification. Furthermore, we provide the optimal input states for which the error amplification due to inversion on the measurement data is minimal.Comment: 7 pages, 2 figure

Charge-coupled devices with fast timing for astrophysics and space physics research

A charge coupled device is under development with fast timing capability (15 millisecond full frame readout, 30 microsecond resolution for measuring the time of individual pixel hits). The fast timing CCD will be used in conjunction with a CsI microfiber array or segmented scintillator matrix detector to detect x rays and gamma rays with submillimeter position resolution. The initial application will be in conjunction with a coded aperture hard x ray/gamma ray astronomy instrument. We describe the concept and the readout architecture of the device

Scientific intuition inspired by machine learning-generated hypotheses

Machine learning with application to questions in the physical sciences has become a widely used tool, successfully applied to classification, regression and optimization tasks in many areas. Research focus mostly lies in improving the accuracy of the machine learning models in numerical predictions, while scientific understanding is still almost exclusively generated by human researchers analysing numerical results and drawing conclusions. In this work, we shift the focus on the insights and the knowledge obtained by the machine learning models themselves. In particular, we study how it can be extracted and used to inspire human scientists to increase their intuitions and understanding of natural systems. We apply gradient boosting in decision trees to extract human-interpretable insights from big data sets from chemistry and physics. In chemistry, we not only rediscover widely know rules of thumb but also find new interesting motifs that tell us how to control solubility and energy levels of organic molecules. At the same time, in quantum physics, we gain new understanding on experiments for quantum entanglement. The ability to go beyond numerics and to enter the realm of scientific insight and hypothesis generation opens the door to use machine learning to accelerate the discovery of conceptual understanding in some of the most challenging domains of science

Broad Area Cooler Concepts for Cryogenic Propellant Tanks

Numerous studies and ground tests have shown that broad area cooling (also known as distributed cooling) can reduce or eliminate cryogenic propellant boil-off and enable long duration storage in space. Various combinations of cryocoolers, circulators, heat exchangers and other hardware could be used to build the system. In this study, several configurations of broad area cooling systems were compared by weighing hardware combinations, input power requirements, component availability, and Technical Readiness Level (TRL). The preferred system has a high TRL and can be scaled up to provide cooling capacities on the order of 150W at 90

Discrete single-photon quantum walks with tunable decoherence

Quantum walks have a host of applications, ranging from quantum computing to the simulation of biological systems. We present an intrinsically stable, deterministic implementation of discrete quantum walks with single photons in space. The number of optical elements required scales linearly with the number of steps. We measure walks with up to 6 steps and explore the quantum-to-classical transition by introducing tunable decoherence. Finally, we also investigate the effect of absorbing boundaries and show that decoherence significantly affects the probability of absorption.Comment: Published version, 5 pages, 4 figure

Implications of new measurements of O-16 + p + C-12,13, N-14,15 for the abundances of C, N isotopes at the cosmic ray source

The fragmentation of a 225 MeV/n O-16 beam was investigated at the Bevalac. Preliminary cross sections for mass = 13, 14, 15 fragments are used to constrain the nuclear excitation functions employed in galactic propagation calculations. Comparison to cosmic ray isotonic data at low energies shows that in the cosmic ray source C-13/C approximately 2% and N-14/0=3-6%. No source abundance of N-15 is required with the current experimental results

Quantum Algorithm for Molecular Properties and Geometry Optimization

It is known that quantum computers, if available, would allow an exponential decrease in the computational cost of quantum simulations. We extend this result to show that the computation of molecular properties (energy derivatives) could also be sped up using quantum computers. We provide a quantum algorithm for the numerical evaluation of molecular properties, whose time cost is a constant multiple of the time needed to compute the molecular energy, regardless of the size of the system. Molecular properties computed with the proposed approach could also be used for the optimization of molecular geometries or other properties. For that purpose, we discuss the benefits of quantum techniques for Newton's method and Householder methods. Finally, global minima for the proposed optimizations can be found using the quantum basin hopper algorithm, which offers an additional quadratic reduction in cost over classical multi-start techniques.Comment: 6 page