Doubly-Attentive Decoder for Multi-modal Neural Machine Translation

We introduce a Multi-modal Neural Machine Translation model in which a doubly-attentive decoder naturally incorporates spatial visual features obtained using pre-trained convolutional neural networks, bridging the gap between image description and translation. Our decoder learns to attend to source-language words and parts of an image independently by means of two separate attention mechanisms as it generates words in the target language. We find that our model can efficiently exploit not just back-translated in-domain multi-modal data but also large general-domain text-only MT corpora. We also report state-of-the-art results on the Multi30k data set.Comment: 8 pages (11 including references), 2 figure

A new SOLT calibration method for leaky on-wafer measurements using a 10-term error model

We present a new Short-Open-Load-Thru (SOLT) calibration method for on-wafer S-parameter measurements. The new calibration method is based on a 10-term error model which is a simplified version of the 16-term error model. Compared with the latter, the former ignores all signal leakages except the ones between the probes. Experimental results show that this is valid for modern vector network analyzers (VNA). The advantage of using this 10-term error model is that the exact values of all error terms can be obtained by using the same calibration standards as the conventional SOLT method. This avoids not only the singularity problem with approximate methods, such as least squares, but also the usage of additional calibration standards. In this paper, we first demonstrate how the 10-term error model is developed and then the experimental verification of the theory is given. Finally, a practical application of the error model using a 10 dB attenuator from 140 GHz to 220 GHz is presented. Compared with the conventional SOLT calibration method without crosstalk corrections, the new method shows approximately 1 dB improvement in the transmission coefficients of the attenuator at 220 GHz

The Kinematic Sunyaev-Zel'dovich Effect with Projected Fields II: prospects, challenges, and comparison with simulations

The kinematic Sunyaev-Zel'dovich (kSZ) signal is a powerful probe of the cosmic baryon distribution. The kSZ signal is proportional to the integrated free electron momentum rather than the electron pressure (which sources the thermal SZ signal). Since velocities should be unbiased on large scales, the kSZ signal is an unbiased tracer of the large-scale electron distribution, and thus can be used to detect the "missing baryon" that evade most observational techniques. While most current methods for kSZ extraction rely on the availability of very accurate redshifts, we revisit a method that allows measurements even in the absence of redshift information for individual objects. It involves cross-correlating the square of an appropriately filtered cosmic microwave background (CMB) temperature map with a projected density map constructed from a sample of large-scale structure tracers. We show that this method will achieve high signal-to-noise when applied to the next generation of high-resolution CMB experiments, provided that component separation is sufficiently effective at removing foreground contamination. Considering statistical errors only, we forecast that this estimator can yield $S/N \approx$ 3, 120 and over 150 for Planck, Advanced ACTPol, and hypothetical Stage-IV CMB experiments, respectively, in combination with a galaxy catalog from WISE, and about 20% larger $S/N$ for a galaxy catalog from the proposed SPHEREx experiment. This work serves as a companion paper to the first kSZ measurement with this method, where we used CMB temperature maps constructed from Planck and WMAP data, together with galaxies from the WISE survey, to obtain a 3.8 - 4.5$\sigma$ detection of the kSZ$^2$ amplitude.Comment: 14 pages, 10 figures. Comments welcom

The Kinematic Sunyaev-Zel'dovich Effect with Projected Fields: A Novel Probe of the Baryon Distribution with Planck, WMAP, and WISE Data

The kinematic Sunyaev-Zel'dovich (kSZ) effect --- the Doppler boosting of cosmic microwave background (CMB) photons due to Compton-scattering off free electrons with non-zero bulk velocity --- probes the abundance and distribution of baryons in the Universe. All kSZ measurements to date have explicitly required spectroscopic redshifts. Here, we implement a novel estimator for the kSZ -- large-scale structure cross-correlation based on projected fields: it does not require redshift estimates for individual objects, allowing kSZ measurements from large-scale imaging surveys. We apply this estimator to cleaned CMB temperature maps constructed from Planck and Wilkinson Microwave Anisotropy Probe data and a galaxy sample from the Wide-field Infrared Survey Explorer (WISE). We measure the kSZ effect at 3.8-4.5$\sigma$ significance, depending on the use of additional WISE galaxy bias constraints. We verify that our measurements are robust to possible dust emission from the WISE galaxies. Assuming the standard $\Lambda$CDM cosmology, we directly constrain $( {f_{b}}/{0.158} ) ( {f_{\rm free}}/{1.0} ) = 1.48 \pm 0.19$ (statistical error only) at redshift $z \approx 0.4$, where $f_{b}$ is the fraction of matter in baryonic form and $f_{\rm free}$ is the free electron fraction. This is the tightest kSZ-derived constraint reported to date on these parameters. The consistency between the $f_{b}$ value found here and the values inferred from analyses of the primordial CMB and Big Bang nucleosynthesis verifies that baryons approximately trace the dark matter distribution down to $\sim$Mpc scales. While our projected-field estimator is already competitive with other kSZ approaches when applied to current datasets (because we are able to use the full-sky WISE photometric survey), it will yield enormous signal-to-noise when applied to upcoming high-resolution, multi-frequency CMB surveys.Comment: 5 pages + references, 2 figures; v2: matches PRL accepted version, results unchange

Happy times: measuring happiness using response times

Surveys measuring happiness or preferences generate discrete ordinal data. Ordered response models, which are used to analyze such data, suffer from an identification problem. Their conclusions depend on distributional assumptions about a latent variable. We propose using response times to solve that problem. Response times contain information about the distribution of the latent variable through a chronometric effect. Using an online survey experiment, we verify the chronometric effect. We then provide theoretical conditions for testing conventional distributional assumptions. These assumptions are rejected in some cases, but overall our evidence is consistent with the qualitative validity of the conventional models

Using Multimodal LLM for Material Type and Emissivity Determination to Enhance Accuracy of Infrared Temperature Measurement

Smart devices equipped with infrared (IR) sensors offer convenient temperature measurement capabilities. However, the accuracy of temperature measurement using IR sensors is dependent on estimating the emissivity of the target surface. Currently, manual categorization of the object is necessary so that its material properties can be determined. Requiring such manual input is inconvenient and detracts from the user experience. This disclosure describes techniques that utilize a multimodal large language model (LLM) to automatically determine material type of an object whose temperature is to be determined. Per the techniques, an image of the object captured by a camera is provided to the multimodal LLM along with a suitable prompt instructing the LLM to determine the material type for the object. The LLM outputs the material type which is used in determining the temperature of the object based on infrared sensors. Alternatively, the LLM can be prompted to provide an emissivity estimate of the object directly and the emissivity estimate can be used to determine the object temperature. The techniques leverage the capability of a multimodal LLM of analyzing images to provide detailed information regarding an input image without requiring extensive training for various use cases

Phase transition dimensionality crossover from two to three dimensions in a trapped ultracold atomic Bose gas

The equilibrium properties of a weakly interacting atomic Bose gas across the Berezinskii-Kosterlitz-Thouless (BKT) and Bose-Einstein condensation (BEC) phase transitions are numerically investigated through a dimensionality crossover from two to three dimensions. The crossover is realised by confining the gas in an experimentally feasible hybridised trap which provides homogeneity along the planar xy-directions through a box potential in tandem with a harmonic transverse potential along the transverse z-direction. The dimensionality is modified by varying the frequency of the harmonic trap from tight to loose transverse trapping. Our findings, based on a stochastic (projected) Gross-Pitaevskii equation, showcase a continuous shift in the character of the phase transition from BKT to BEC, and a monotonic increase of the identified critical temperature as a function of dimensionality, with the strongest variation exhibited for small chemical potential values up to approximately twice the transverse confining potentialComment: 14 pages, 7 figure