Two qubits in one transmon -- QEC without ancilla hardware

We show that it is theoretically possible to use higher energy levels for storing and controlling two qubits within a superconducting transmon. This is done by identifying energy levels as product states between multiple effecitve qubits. As a proof of concept we realise a complete set of gates necessary for universal computing by numerically optimising control pulses for single qubit gates on each of the qubits, entangling gates between the two qubits in one transmon, and an entangling gate between two qubits from two coupled transmons. The optimisation considers parameters which could make it possible to validate this experimentally. With these control pulses it is in principle possible to double the number of available qubits without any overhead in hardware. The additional qubits could be used in algorithms which need many short-living qubits such as syndrom qubits in error correction or by embedding effecitve higher connectivity in qubit networks.Comment: 14 pages, 12 figure

Modeling Variable Emission Lines in AGNs: Method and Application to NGC 5548

We present a new scheme for modeling the broad line region in active galactic nuclei (AGNs). It involves photoionization calculations of a large number of clouds, in several pre-determined geometries, and a comparison of the calculated line intensities with observed emission line light curves. Fitting several observed light curves simultaneously provides strong constraints on model parameters such as the run of density and column density across the nucleus, the shape of the ionizing continuum, and the radial distribution of the emission line clouds. When applying the model to the Seyfert 1 galaxy NGC 5548, we were able to reconstruct the light curves of four ultraviolet emission-lines, in time and in absolute flux. This has not been achieved by any previous work. We argue that the Balmer lines light curves, and possibly also the MgII2798 light curve, cannot be tested in this scheme because of the limitations of present-day photoionization codes. Our fit procedure can be used to rule out models where the particle density scales as r^{-2}, where r is the distance from the central source. The best models are those where the density scales as r^{-1} or r^{-1.5}. We can place a lower limit on the column density at a distance of 1 ld, of N_{col}(r=1) >~ 10^{23} cm^{-2} and limit the particle density to be in the range of 10^{12.5}>N(r=1)>10^{11} cm^{-3}. We have also tested the idea that the spectral energy distribution (SED) of the ionizing continuum is changing with continuum luminosity. None of the variable-shape SED tried resulted in real improvement over a constant SED case although models with harder continuum during phases of higher luminosity seem to fit better the observed spectrum. Reddening and/or different composition seem to play a minor role, at least to the extent tested in this work.Comment: 12 pages, including 9 embedded EPS figures, accepted for publication in Ap

An introduction into optimal control for quantum technologies

In this series of lectures, we would like to introduce the audience to quantum optimal control. The first lecture will cover basic ideas and principles of optimal control with the goal of demystifying its jargon. The second lecture will describe computational tools (for computations both on paper and in a computer) for its implementation as well as their conceptual background. The third chapter will go through a series of popular examples from different applications of quantum technology.Comment: Lecture notes for the 51st IFF Spring Schoo

The Relationship Between Luminosity and Broad-Line Region Size in Active Galactic Nuclei

We reinvestigate the relationship between the characteristic broad-line region size (R_blr) and the Balmer emission-line, X-ray, UV, and optical continuum luminosities. Our study makes use of the best available determinations of R_blr for a large number of active galactic nuclei (AGNs) from Peterson et al. Using their determinations of R_blr for a large sample of AGNs and two different regression methods, we investigate the robustness of our correlation results as a function of data sub-sample and regression technique. Though small systematic differences were found depending on the method of analysis, our results are generally consistent. Assuming a power-law relation R_blr \propto L^\alpha, we find the mean best-fitting \alpha is about 0.67+/-0.05 for the optical continuum and the broad H\beta luminosity, about 0.56+/-0.05 for the UV continuum luminosity, and about 0.70+/-0.14 for the X-ray luminosity. We also find an intrinsic scatter of about 40% in these relations. The disagreement of our results with the theoretical expected slope of 0.5 indicates that the simple assumption of all AGNs having on average same ionization parameter, BLR density, column density, and ionizing spectral energy distribution, is not valid and there is likely some evolution of a few of these characteristics along the luminosity scale.Comment: 11 pages, 2 figures, emulateapj, accepted for publication in The Astrophysical Journa

Matching and Predicting Street Level Images

The paradigm of matching images to a very large dataset has been used for numerous vision tasks and is a powerful one. If the image dataset is large enough, one can expect to nd good matches of almost any image to the database, allowing label transfer [3, 15], and image editing or enhancement [6, 11]. Users of this approach will want to know how many images are required, and what features to use for nding semantic relevant matches. Furthermore, for navigation tasks or to exploit context, users will want to know the predictive quality of the dataset: can we predict the image that would be seen under changes in camera position? We address these questions in detail for one category of images: street level views. We have a dataset of images taken from an enumeration of positions and viewpoints within Pittsburgh.We evaluate how well we can match those images, using images from non-Pittsburgh cities, and how well we can predict the images that would be seen under changes in cam- era position. We compare performance for these tasks for eight di erent feature sets, nding a feature set that outperforms the others (HOG). A combination of all the features performs better in the prediction task than any individual feature. We used Amazon Mechanical Turk workers to rank the matches and predictions of di erent algorithm conditions by comparing each one to the selection of a random image. This approach can evaluate the e cacy of di erent feature sets and parameter settings for the matching paradigm with other image categories.United States. Dept. of Defense (ARDA VACE)United States. National Geospatial-Intelligence Agency (NEGI-1582-04- 0004)United States. National Geospatial-Intelligence Agency (MURI Grant N00014-06-1-0734)France. Agence nationale de la recherche (project HFIBMR (ANR-07-BLAN- 0331-01))Institut national de recherche en informatique et en automatique (France)Xerox Fellowship Progra

CG2Real: Improving the Realism of Computer Generated Images using a Large Collection of Photographs

Computer Graphics (CG) has achieved a high level of realism, producing strikingly vivid images. This realism, however, comes at the cost of long and often expensive manual modeling, and most often humans can still distinguish between CG images and real images. We present a novel method to make CG images look more realistic that is simple and accessible to novice users. Our system uses a large collection of photographs gathered from online repositories. Given a CG image, we retrieve a small number of real images with similar global structure. We identify corresponding regions between the CG and real images using a novel mean-shift cosegmentation algorithm. The user can then automatically transfer color, tone, and texture from matching regions to the CG image. Our system only uses image processing operations and does not require a 3D model of the scene, making it fast and easy to integrate into digital content creation workflows. Results of a user study show that our improved CG images appear more realistic than the originals