arXiv subjects

Hsuan Lo

Publications and source records attributed to Hsuan Lo.

4 recordsLinked to original sources

arXiv2026

Following the Preference, Missing the Optimum: Compliance Without Optimization in AI Housing Recommendation

Large language models are becoming the first point of contact for consumer search in domains where the stakes are material and the law is explicit. Existing audits show that models steer housing seekers by perceived identity, but none can say what a user loses when a recommender overlooks a suitable option, for want of an enumerated inventory to score omissions against. We audit AI housing recommendation against a verifiable ground truth. For each of 150 synthetic renter scenarios in New York City we build a pool of 120 real listings with known rent, bedrooms and GTFS-computed transit commute, compute the exact set satisfying the renter's stated constraints, and derive its Pareto frontier. The primary outcome assumes no utility function: a recommendation is strictly dominated if the same pool holds a listing cheaper, faster to commute from and no smaller in bedrooms. Across 9,945 calls to three models from two vendors, compliance is near-perfect (1.8% violation against a 66.6% random floor), yet 39.0% of recommendations are strictly dominated, and the dominating listing is a median 900 USD/month cheaper and 3.5 minutes closer. A within-scenario manipulation separates two capabilities usually conflated: changing one sentence moves median recommended rent by 646 USD/month in the correct direction, so preferences are honored, yet recommendations still sit 606 USD/month above the five cheapest qualifying listings on the same screen, and an unambiguous lexicographic instruction gives no improvement under equivalence testing against a pre-specified 50 USD/month bound. The gap widens with candidate-set size and replicates across OpenAI and Anthropic models to within 3 USD. We characterize the failure as compliance without optimization, propose dominance-rate instrumentation as a deployable diagnostic, and release all code, prompts and per-call results.

cs.CY↗

arXiv2025

Resolution and Robustness Bounds for Reconstructive Spectrometers

Reconstructive spectrometers are a promising emerging class of devices that combine complex light scattering with inference to enable compact, high-resolution spectrometry. Thus far, the physical determinants of these devices' performance remain under-explored. We show that under a broad range of conditions, the noise-induced error for spectral reconstruction is governed by the Fisher information. We then use random matrix theory to derive a closed-form relation linking the variance bound to a set of key physical parameters: the spectral correlation length, the mean transmittance, and the number of frequency and measurement channels. The analysis reveals certain fundamental trade-offs between these physical parameters, and establishes the conditions for a spectrometer to achieve ``super-resolution'' below the limit set by the spectral correlation length. Our theory is confirmed using numerical validations with a random matrix model as well as full-wave simulations. These results establish a physically-grounded framework for designing and analyzing performant and noise-robust reconstructive spectrometers.

physics.optics↗

arXiv2025

Wavelength-scale noise-resistant on-chip spectrometer

Performant on-chip spectrometers are important for advancing sensing technologies, from environmental monitoring to biomedical diagnostics. As device footprints approach the scale of the operating wavelength, previously strategies, including those relying on multiple scattering in diffusive media, face fundamental accuracy constraints tied to limited optical path lengths. Here, we demonstrate a wavelength-scale, CMOS-compatible on-chip spectrometer that overcomes this challenge by exploiting inverse-designed quasinormal modes in a complex photonic resonator. These modes extend the effective optical path length beyond the physical device dimensions, producing highly de-correlated spectral responses. We show that this strategy is theoretically optimal for minimizing spectral reconstruction error in the presence of measurement noise. The fabricated spectrometer occupies a lateral footprint of only 3.5 times the free-space operating wavelength, with a spectral resolution of 10 nm across the 3.59-3.76 micrometer mid-infrared band, which is suitable for molecular sensing. The design of this miniaturized noise-resistant spectrometer is readily extensible to other portions of the electromagnetic spectrum, paving the way for lab-on-a-chip devices, chemical sensors, and other applications.

physics.optics↗

arXiv2024

Switchable Non-Hermitian Skin Effect in Bogoliubov Modes

Interacting or nonlinear lattices can host emergent particle-like modes, such as Bogoliubov quasiparticles, whose band topology and other properties are potentially highly tunable. Despite originating in the study of superconducting materials, Bogoliubov quasiparticles can also occur in synthetic metamaterials. Here, we implement a nonlinear driven-dissipative circuit whose fluctuations are Bogoliubov modes possessing nontrivial non-Hermitian band topology. We show experimentally that the system exhibits a switchable non-Hermitian skin effect (NHSE), which abruptly appears when the on-site driving voltage amplitude exceeds a threshold. In contrast to earlier realizations of the NHSE and related phenomena in circuit models, the switchable NHSE in our system occurs in Bogoliubov modes, which are strongly affected by how the system is driven. Moreover, unlike other experimental platforms hosting non-Hermitian Bogoliubov modes, our system does not contain unconventional asymmetric hopping nonlinearities, only a local Kerr-type nonlinearity.

cond-mat.mes-hall↗