May 2023 – Page 12 – Kavli Institute Pre-Print Publications

Detecting Exoplanets Closer to Stars with Moderate Spectral Resolution Integral-Field Spectroscopy

Posted by klaurent May 17, 2023Stanford

Kavli Affiliate: Bruce Macintosh | First 5 Authors: Shubh Agrawal, Jean-Baptiste Ruffio, Quinn M. Konopacky, Bruce Macintosh, Dimitri Mawet | Summary: While radial velocity surveys have demonstrated that the population of gas giants peaks around $3~text{au}$, the most recent high-contrast imaging surveys have only been sensitive to planets beyond $sim~10~text{au}$. Sensitivity at small angular separations […]

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Duality Origami: Emergent Ensemble Symmetries in Holography and Swampland

Posted by dbos May 17, 2023Tokyo

Kavli Affiliate: Masahito Yamazaki | First 5 Authors: Meer Ashwinkumar, Jacob M. Leedom, Masahito Yamazaki, , | Summary: We discuss the interrelations between several ideas in quantum gravity — holography, the Swampland, and the concept of ensemble averaging. To do so, we study ensemble averages of Narain-type theories associated with general even quadratic forms and […]

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Duality Origami: Emergent Ensemble Symmetries in Holography and Swampland

Posted by klaurent May 17, 2023Tokyo

Kavli Affiliate: Masahito Yamazaki | First 5 Authors: Meer Ashwinkumar, Jacob M. Leedom, Masahito Yamazaki, , | Summary: We discuss interrelations between several ideas in quantum gravity. One is the Swampland program, which states that a low-energy effective field theory should satisfy non-trivial constraints to have an ultraviolet (UV) completion in quantum gravity. Another is […]

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Gravitational Positivity for Phenomenologists: Dark Gauge Boson in the Swampland

Posted by dbos May 17, 2023Tokyo

Kavli Affiliate: Satoshi Shirai | First 5 Authors: Katsuki Aoki, Toshifumi Noumi, Ryo Saito, Sota Sato, Satoshi Shirai | Summary: The gravitational positivity bound gives quantitative "swampland” constraints on low-energy effective theories inside theories of quantum gravity. We give a comprehensive discussion of this bound for those interested in applications to phenomenological model building. We […]

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Gravitational Positivity for Phenomenologists: Dark Gauge Boson in the Swampland

Posted by dbos May 17, 2023Tokyo

Kavli Affiliate: Satoshi Shirai | First 5 Authors: Katsuki Aoki, Toshifumi Noumi, Ryo Saito, Sota Sato, Satoshi Shirai | Summary: The gravitational positivity bound gives quantitative “swampland” constraints on low-energy effective theories inside theories of quantum gravity. We give a comprehensive discussion of this bound for those interested in applications to phenomenological model building. We […]

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DualVector: Unsupervised Vector Font Synthesis with Dual-Part Representation

Posted by klaurent May 17, 2023UCSB

Kavli Affiliate: Matthew Fisher | First 5 Authors: Ying-Tian Liu, Zhifei Zhang, Yuan-Chen Guo, Matthew Fisher, Zhaowen Wang | Summary: Automatic generation of fonts can be an important aid to typeface design. Many current approaches regard glyphs as pixelated images, which present artifacts when scaling and inevitable quality losses after vectorization. On the other hand, […]

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Super-Resolution Imaging via Angular Magnification

Posted by klaurent May 17, 2023May 30, 2023UCAS

Kavli Affiliate: Yi Zhou | First 5 Authors: Yi Zhou, Dingpeng Liao, Kun Zhang, Zijie Ma, Shikai Wu | Summary: The far-field resolution of optical imaging systems is restricted by the Abbe diffraction limit, a direct result of the wave nature of light. One successful technological approach to circumventing this limit is to reduce the […]

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Improved Bounds for Single-Nomination Impartial Selection

Posted by klaurent May 17, 2023Berkeley

Kavli Affiliate: Felix Fischer | First 5 Authors: Javier Cembrano, Felix Fischer, Max Klimm, , | Summary: We give new bounds for the single-nomination model of impartial selection, a problem proposed by Holzman and Moulin (Econometrica, 2013). A selection mechanism, which may be randomized, selects one individual from a group of $n$ based on nominations […]

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Improved Bounds for Single-Nomination Impartial Selection

Posted by klaurent May 17, 2023Berkeley

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Unconfounded Propensity Estimation for Unbiased Ranking

Posted by klaurent May 17, 2023Cornell

Kavli Affiliate: Dan Luo | First 5 Authors: Dan Luo, Lixin Zou, Qingyao Ai, Zhiyu Chen, Chenliang Li | Summary: The goal of unbiased learning to rank (ULTR) is to leverage implicit user feedback for optimizing learning-to-rank systems. Among existing solutions, automatic ULTR algorithms that jointly learn user bias models (i.e., propensity models) with unbiased […]

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