Content-Style Decomposition: Representation Discovery and Applications

Content-style decompositions, or CSDs, decompose entities into content, defined by the entity's class, and style, defined as the remaining within-class variation. Content is typically defined in terms of some task. For example, in a face recognition task, identity is the content; in an emotion recognition task, expression is the content. CSDs have many applications: they can provide insight into domains where we have little prior knowledge of the sources of within- and between-class variation, and content-style recombinations are interesting as a creative exercise or for data set augmentation. Our approach is to decompose CSD discovery into two sub-problems: (1) to find useful representations of content that capture the class structure of the domain, and (2) to use those content-representations to discover CSDs. We make contributions to both sub-problems. First, we propose the F-statistic loss, a new method for discovering content representations that uses statistics of class separation on isolated embedding dimensions within a minibatch to determine when to terminate training. In addition to state-of-the-art performance on few-shot learning, we find that the method leads to factorial (also known as disentangled) representations of content when applied with a novel form of weak supervision. Previous work on disentangling is either unsupervised or uses a factor-aware oracle, which provides similar/dissimilar judgments with respect to a named attribute/factor. We explore an intermediate form of supervision, an unnamed-factor oracle, which provides similarity judgments with respect to a random unnamed factor. We demonstrate that the F-statistic loss leads to better disentangling when compared with other deep-embeddings losses and β-VAE, a state-of-the-art unsupervised disentangling method. Second, we introduce a new loss for discovering CSDs that can arbitrarily recombine content and style, called leakage filtering. In contrast to previous research which attempts to separate content and style in two different representation vectors, leakage filtering allows for imperfectly disentangled representations but ensures that residual content information will not leak out of the style representation and vice versa. Leakage filtering is also distinguished by its ability to operate on novel content-classes and by its lack of dependency on style labels for training. The recombined images produced are of high quality and can be used to augment datasets for few-shot learning tasks, yielding significant generalization improvements

Measurements of the Temperature and E-Mode Polarization of the CMB from 500 Square Degrees of SPTpol Data

We present measurements of the $E$-mode polarization angular auto-power spectrum ($EE$) and temperature-$E$-mode cross-power spectrum ($TE$) of the cosmic microwave background (CMB) using 150 GHz data from three seasons of SPTpol observations. We report the power spectra over the spherical harmonic multipole range $50 < \ell \leq 8000$, and detect nine acoustic peaks in the $EE$ spectrum with high signal-to-noise ratio. These measurements are the most sensitive to date of the $EE$ and $TE$ power spectra at $\ell > 1050$ and $\ell > 1475$, respectively. The observations cover 500 deg$^2$, a fivefold increase in area compared to previous SPTpol analyses, which increases our sensitivity to the photon diffusion damping tail of the CMB power spectra enabling tighter constraints on \LCDM model extensions. After masking all sources with unpolarized flux $>50$ mJy we place a 95% confidence upper limit on residual polarized point-source power of $D_\ell = \ell(\ell+1)C_\ell/2\pi <0.107\,\mu{\rm K}^2$ at $\ell=3000$, suggesting that the $EE$ damping tail dominates foregrounds to at least $\ell = 4050$ with modest source masking. We find that the SPTpol dataset is in mild tension with the $\Lambda CDM$ model ($2.1\,\sigma$), and different data splits prefer parameter values that differ at the $\sim 1\,\sigma$ level. When fitting SPTpol data at $\ell < 1000$ we find cosmological parameter constraints consistent with those for $Planck$ temperature. Including SPTpol data at $\ell > 1000$ results in a preference for a higher value of the expansion rate (H_0 = 71.3 \pm 2.1\,\mbox{km}\,s^{-1}\mbox{Mpc}^{-1} ) and a lower value for present-day density fluctuations ($\sigma_8 = 0.77 \pm 0.02$).Comment: Updated to match version accepted to ApJ. 34 pages, 17 figures, 6 table

Measurements of the Temperature and E-mode Polarization of the CMB from 500 Square Degrees of SPTpol Data

We present measurements of the E-mode polarization angular auto-power spectrum (EE) and temperature–E-mode cross-power spectrum (TE) of the cosmic microwave background (CMB) using 150 GHz data from three seasons of SPTpol observations. We report the power spectra over the spherical harmonic multipole range 50 1050 and ℓ > 1475, respectively. The observations cover 500 deg^2, a fivefold increase in area compared to previous SPTpol analyses, which increases our sensitivity to the photon diffusion damping tail of the CMB power spectra enabling tighter constraints on ΛCDM model extensions. After masking all sources with unpolarized flux > 50 mJy, we place a 95% confidence upper limit on residual polarized point-source power of D_ℓ = ℓ(ℓ +1 )C_ℓ/2 π 1000 results in a preference for a higher value of the expansion rate (H_0 = 71.3 ± 2.1 km s^-1 Mpc^-1) and a lower value for present-day density fluctuations (σg_8 = 0.77 ± 0.02)

Advances in Solid State Circuit Technologies

This book brings together contributions from experts in the fields to describe the current status of important topics in solid-state circuit technologies. It consists of 20 chapters which are grouped under the following categories: general information, circuits and devices, materials, and characterization techniques. These chapters have been written by renowned experts in the respective fields making this book valuable to the integrated circuits and materials science communities. It is intended for a diverse readership including electrical engineers and material scientists in the industry and academic institutions. Readers will be able to familiarize themselves with the latest technologies in the various fields

Design and test of readout electronics for medical and astrophysics applications

The applied particle physics has a strong R&D tradition aimed at rising the instrumentation performances to achieve relevant results for the scientific community. The know-how achieved in developing particle detectors can be applied to apparently divergent fields like hadrontherapy and cosmic ray detection. A proof of this fact is presented in this doctoral thesis, where the results coming from three different projects are discussed in likewise macro-chapters. A brief introduction (Chapter 1) reports the basic features characterizing a typical particle detector system. This section is developed following the data transmission path: from the sensor, the data moves through the front-end electronics for being readout and collected, ready for the data manipulation. After this general section, the thesis describes the results achieved in two projects developed by the collaboration between the medical physics group of the University of Turin and the Turin section of the Italian Nuclear Institute for Nuclear Physics. Chapter 2 focuses on the TERA09 project. TERA09 is a 64 channels customized chip that has been realized to equip the front-end readout electronics for the new generation of beam monitor chambers for particle therapy applications. In this field, the trend in the accelerators development is moving toward compact solutions providing high-intensity pulsed-beams. However, such a high intensity will saturate the present readout electronics. In order to overcome this critical issue, the TERA09 chip is able to cope with the expected maximum intensity while keeping high resolution by working on a wide conversion-linearity zone which extends from hundreds of pA to hundreds of μA. The chip gain spread is in the order of 1-3% (r.m.s.), with a 200 fC charge resolution. The thesis author took part in the chip design and fully characterized the device. The same group is currently working on behalf of the MoVeIT collaboration for the development of a new silicon strip detector prototype for particle therapy applications. Chapter 3 presents the technical aspects of this project, focusing on the author’s contribution: the front-end electronics design. The sensor adopted for the MoVeIT project is based on 50 μm thin sensors with internal gain, aiming to detect the single beam particle thus counting their number up to 109 cm2/s fluxes, with a pileup probability < 1%. A similar approach would lead to a drastic step forward if compared to the classical and widely used monitoring system based on gas ionization chambers. For what concerns the front-end electronics, the group strategy has been to design two prototypes of custom front-end: one based on a transimpedance preamplifier with a resistive feedback and the other one based on a charge sensitive amplifier. The challenging tasks for the electronics are represented by the charge and dynamic range which are respectively the 3 - 150 fC and the hundreds of MHz instantaneous rate (100 MHz as the milestone, up to 250 MHz ideally). Chapter 4 is a report on the trigger logic development for the Mini-EUSO detector. Mini-EUSO is a telescope designed by the JEM-EUSO Collaboration to map the Earth in the UV range from the vantage point of the International Space Station (ISS), in low Earth orbit. This approach will lay the groundwork for the detection of Extreme Energy Cosmic Rays (EECRs) from space. Due to its 2.5 μs time resolution, Mini-EUSO is capable of detecting a wide range of UV phenomena in the Earth’s atmosphere. In order to maximize the scientific return of the mission, it is necessary to implement a multi-level trigger logic for data selection over different timescales. This logic is key to the success of the mission and thus must be thoroughly tested and carefully integrated into the data processing system prior to the launch. The author took part in the trigger integration in hardware, laboratory trigger tests and also developed the firmware of the trigger ancillary blocks. Chapter 5 closes this doctoral thesis, with a dedicated summary part for each of the three macro-chapters

Towards an Information Theoretic Framework for Evolutionary Learning

The vital essence of evolutionary learning consists of information flows between the environment and the entities differentially surviving and reproducing therein. Gain or loss of information in individuals and populations due to evolutionary steps should be considered in evolutionary algorithm theory and practice. Information theory has rarely been applied to evolutionary computation - a lacuna that this dissertation addresses, with an emphasis on objectively and explicitly evaluating the ensemble models implicit in evolutionary learning. Information theoretic functionals can provide objective, justifiable, general, computable, commensurate measures of fitness and diversity. We identify information transmission channels implicit in evolutionary learning. We define information distance metrics and indices for ensembles. We extend Price\u27s Theorem to non-random mating, give it an effective fitness interpretation and decompose it to show the key factors influencing heritability and evolvability. We argue that heritability and evolvability of our information theoretic indicators are high. We illustrate use of our indices for reproductive and survival selection. We develop algorithms to estimate information theoretic quantities on mixed continuous and discrete data via the empirical copula and information dimension. We extend statistical resampling. We present experimental and real world application results: chaotic time series prediction; parity; complex continuous functions; industrial process control; and small sample social science data. We formalize conjectures regarding evolutionary learning and information geometry