arXiv subjects

Guillermo Aguilar

Publications and source records attributed to Guillermo Aguilar.

3 recordsLinked to original sources

arXiv2025

Direct Photochemical Patterning of Lithium Niobate Thin Films for Scalable Nonlinear Optical Metasurfaces

Lithium niobate is one of the most sought-after materials for nanophotonic devices, including frequency converters, modulators, and quantum light sources. Integration of lithium niobate into optical devices, however, is hampered by significant top-down fabrication challenges due to its exceptional chemical resistance. Scalable fabrication methods that preserve material quality while reducing fabrication complexity and cost are, therefore, crucial to advancing lithium niobate devices. We present a photochemical metal-organic decomposition technique for the scalable patterning of lithium niobate at ambient conditions, eliminating the need for harsh etching conditions and cleanroom protocols. The method utilizes a solution of a custom-prepared photosensitive organometallic precursor as a negative photoresist. The UV light exposure of the thin films of the precursor through a photomask, followed by rinsing with ethanol, yields amorphous patterns, which transform into crystalline lithium niobate after a calcination step. This method enables a scalable fabrication of a range of complex geometric shapes with a feature resolution down to $30\,μ\mathrm{m}$. The patterned lithium niobate structures exhibit a tunable second harmonic generation activity with an isotropic optical response. This approach offers a scalable and low-cost pathway for manufacturing lithium niobate photonics and the potential to fabricate other materials (e.g., barium titanite and lithium tantalate).

physics.optics↗

arXiv2025

Ordinal Characterization of Similarity Judgments

Characterizing judgments of similarity within a perceptual or semantic domain, and making inferences about the underlying structure of this domain from these judgments, has an increasingly important role in cognitive and systems neuroscience. We present a new framework for this purpose that makes limited assumptions about how perceptual distances are converted into similarity judgments. The approach starts from a dataset of empirical judgments of relative similarities: the fraction of times that a subject chooses one of two comparison stimuli to be more similar to a reference stimulus. These empirical judgments provide Bayesian estimates of underling choice probabilities. From these estimates, we derive indices that characterize the set of judgments in three ways: compatibility with a symmetric dis-similarity, compatibility with an ultrametric space, and compatibility with an additive tree. Each of the indices is derived from rank-order relationships among the choice probabilities that, as we show, are necessary and sufficient for local consistency with the three respective characteristics. We illustrate this approach with simulations and example psychophysical datasets of dis-similarity judgments in several visual domains and provide code that implements the analyses at https://github.com/jvlab/simrank.

q-bio.NC↗

arXiv2024

Estimating the contribution of early and late noise in vision from psychophysical data

In many psychophysical detection and discrimination tasks human performance is thought to be limited by internal or inner noise when neuronal activity is converted into an overt behavioural response. It is unclear, however, to what extent the behaviourally limiting inner noise arises from early noise in the photoreceptors and the retina, or from late noise in cortex at or immediately prior to the decision stage. Presumably, the behaviourally limiting inner noise is a non-trivial combination of both early and late noises. Here we propose a method to quantify the contributions of early and late noise purely from psychophysical data. Our analysis generalizes classical results for linear systems (Burgess and Colborne, 1988) by combining the theory of noise propagation through a nonlinear network (Ahumada, 1987) with the expressions to obtain the perceptual metric along the nonlinear network (Malo and Simoncelli, 2006; Laparra et al., 2010). We show that from threshold-only data the relative contribution of early and late noise can only be determined if the experiments include substantial external noise in some of the stimuli used during experiments. If experimenters collected full psychometric functions, however, then early and late noise sources can be quantified even in the absence of external noise. Our psychophysical estimate of the magnitude of the early noise assuming a standard cascade of linear and nonlinear model stages is substantially lower than the noise in cone photocurrents computed via an accurate model of retinal physiology (Brainard and Wandell, 2020, ISETBIO). This is consistent with the idea that one of the fundamental tasks of early vision is to reduce the comparatively large retinal noise.

q-bio.NC↗