Vacuum energy sequestering and conformal symmetry

In a series of recent papers Kaloper and Padilla proposed a mechanism to sequester standard model vacuum contributions to the cosmological constant. We study the consequences of embedding their proposal into a fully local quantum theory. In the original work, the bare cosmological constant $\Lambda$ and a scaling parameter $\lambda$ are introduced as global fields. We find that in the local case the resulting Lagrangian is that of a spontaneously broken conformal field theory where $\lambda$ plays the role of the dilaton. A vanishing or a small cosmological constant is thus a consequence of the underlying conformal field theory structure.Comment: Extended discussion on the conformal symmetry. Matches the published versio

Reconnaissance of infrared emission from the lunar nighttime surface

The reconnaissance described in this paper was performed in 1964 and is an extension and refinement of the first observations (1962), in the 8- to 14-μ wavelength region, of the thermal emission from the lunar nighttime surface [Murray and Wildey, 1964]. The present investigation was intended to sample representatively enough of the lunar surface to determine the general character of the lunar nighttime emission and the relative abundance of nighttime infrared anomalies. More complete studies of the infrared emission with higher spatial resolution during eclipse were made at about the same time [Saari and Shorthill, 1965]

Thermal infrared emission of the Jovian disk

The 8–14 micron infrared emission of Jupiter has been observed on six nights in December 1963 using the 200-inch Hale telescope. The new observations possess twice the resolution of those obtained in 1962. The brightness temperature at the center of the disk appears to be nearly constant at 129°K. With some slight ambiguity, the light bands are about 0.5° cooler in appearance than the dark bands. There is some suggestion of morning-evening asymmetry in one of the bands. The Great Red Spot is found to be from 1.5° to 2.0° cooler than the surrounding disk at the newer resolution

The triple quasar Q1115+080A, B, C - A quintuple gravitational lens image

Spectroscopy and direct imaging of Qll 15+080A,B,C with a CCD camera supports the hypothesis that they are gravitational images of a single object. Spectroscopy of the C III] λ1909 emission line shows all the images to have identical spectra and redshifts (to within 100 km s^(-1)), except that Bis slightly redder. The position and brightness of the three images has been accurately measured; the images A, B, and Care magnitudes 16.30,18.64, and 18.17, respectively, in the r band, B is 1". 77 from A in position angle 266°, and C is 2".28 away at position angle 322°. A and C have the same color, but B is redder by 0.23 mag in (g-r). There is no trace of a lens galaxy, which must have a surface brightness of less than 29 mag arcsec^(-2) at a distance of 5" -8" from Q1115+080. Three bright galaxies lie near Q1115+080, apparently forming a small group. Gravitational lens imaging by a massive spiral galaxy is explored, and we find a quintuple image model resembling Q1115+080 A,B,C. In this model, Q1115+080A is a highly magnified close pair of images oriented in position angle 23°. An elongation of Q1115+080A at this angle is seen in the CCD pictures

Hand classification of fMRI ICA noise components

We present a practical "how-to" guide to help determine whether single-subject fMRI independent components (ICs) characterise structured noise or not. Manual identification of signal and noise after ICA decomposition is required for efficient data denoising: to train supervised algorithms, to check the results of unsupervised ones or to manually clean the data. In this paper we describe the main spatial and temporal features of ICs and provide general guidelines on how to evaluate these. Examples of signal and noise components are provided from a wide range of datasets (3T data, including examples from the UK Biobank and the Human Connectome Project, and 7T data), together with practical guidelines for their identification. Finally, we discuss how the data quality, data type and preprocessing can influence the characteristics of the ICs and present examples of particularly challenging datasets