arXiv subjects

Daniel Grass

Publications and source records attributed to Daniel Grass.

5 recordsLinked to original sources

arXiv2026

High-Frequency Thermal Noise in Michelson Interferometers

Thermal noise in optics constrains the precision of optical experiments, including Michelson interferometers, optical clocks, and optomechanical sensors. While high-power optical experiments such as gravitational-wave detectors are currently limited mainly by quantum noise, new experiments incorporating recent insights from quantum metrology are being developed that evade the quantum shot noise background. In particular, Michelson interferometers that use photon-counting readout will look for weak, high-frequency signals. Since shot noise is no longer the dominant noise source with these readout schemes, it is important to accurately model thermal noise to characterize signals and design more sensitive experiments. However, previous modeling uses approximations that are no longer valid in these frequency regimes. In the MHz band, the quasistatic approximation does not apply. We therefore develop more general models of substrate and coating mechanical (Brownian) noise, substrate and coating thermoelastic noise, and coating thermorefractive noise. We validate the models with comparisons to previous low-frequency modeling and high-frequency spectra from an experiment that has already taken data, the Holometer. We then apply the new models to GQuEST, an experiment under construction.

physics.ins-det↗

arXiv2026

Clinical Reasoning AI for Oncology Treatment Planning: A Multi-Specialty Case-Based Evaluation

Background: More than 80% of U.S. cancer care is delivered in community settings, where survival remains worse than at academic centers. Clinicians must integrate genomics, staging, radiology, pathology, and changing guidelines, creating cognitive burden. We evaluated OncoBrain, an AI clinical reasoning platform for oncology treatment-plan generation, as an early step toward OGI. Methods: OncoBrain combines general-purpose LLMs with a cancer-specific graph retrieval-augmented generation layer, a gold-standard treatment-plan corpus as long-term memory, and a model-agnostic safety layer (CHECK) for hallucination detection and suppression. We evaluated clinician-enriched case summaries across gynecologic, genitourinary, neuro-oncology, gastrointestinal/hepatobiliary, and hematologic malignancies. Three clinician groups completed structured evaluations of 173 cases using a common 16-item instrument: subspecialist oncologists reviewed 50 cases, physician reviewers 78, and advanced practice providers 45. Results: Ratings were highest for scientific accuracy, evidence support, and safety, with lower but favorable scores for workflow integration and time savings. On a 5-point scale, mean alignment with evidence and guidelines was 4.60, 4.56, and 4.70 across subspecialists, physician reviewers, and advanced practice providers. Mean scores for absence of safety or misinformation concerns were 4.80, 4.40, and 4.60. Workflow integration averaged 4.50, 3.94, and 4.00; perceived time savings averaged 5.00, 3.89, and 3.60. Conclusions: In this multi-specialty vignette-based evaluation, OncoBrain generated oncology treatment plans judged guideline-concordant, clinically acceptable, and easy to supervise. These findings support the potential of a carefully engineered AI reasoning platform to assist oncology treatment planning and justify prospective real-world evaluation in community settings.

cs.CY↗

arXiv2024

Photon Counting Interferometry to Detect Geontropic Space-Time Fluctuations with GQuEST

The GQuEST (Gravity from the Quantum Entanglement of Space-Time) experiment uses tabletop-scale Michelson laser interferometers to probe for fluctuations in space-time. We present a practicable interferometer design featuring a novel photon counting readout method that provides unprecedented sensitivity, as it is not subject to the interferometric standard quantum limit. We evaluate the potential of this design to measure space-time fluctuations motivated by recent `geontropic' quantum gravity models. The accelerated accrual of Fisher information offered by the photon counting readout enables GQuEST to detect the predicted quantum gravity phenomena within measurement times at least 100 times shorter than equivalent conventional interferometers. The GQuEST design thus enables a fast and sensitive search for signatures of quantum gravity in a laboratory-scale experiment.

gr-qc↗

arXiv2022

Optical trapping of high-aspect-ratio NaYF hexagonal prisms for kHz-MHz gravitational wave detectors

We present experimental results on optical trapping of Yb-doped $\beta-$NaYF sub-wavelength-thickness high-aspect-ratio hexagonal prisms with a micron-scale radius. The prisms are trapped in vacuum using an optical standing wave, oriented with the normal vector to their face along the beam propagation direction, and exhibit characteristic modes of three translational and two torsional degrees of freedom. The measured motional spectra are compared with numerical simulations. This plate-like geometry simultaneously enables trapping with low photon-recoil-heating, high mass, and high trap frequency, potentially leading to advances in high frequency gravitational wave searches in the Levitated Sensor Detector (LSD), currently under construction. The material used here has previously been shown to exhibit internal cooling via laser refrigeration when optically trapped and illuminated with light of suitable wavelength. Employing such laser refrigeration methods in the context of our work may enable higher trapping intensity thus and higher trap frequencies for gravitational wave searches approaching the several hundred kHz range.

physics.optics↗

arXiv2021

Scanning force sensing at $\mu$m-distances from a conductive surface with nanospheres in an optical lattice

The center-of-mass motion of optically trapped dielectric nanoparticles in vacuum is extremely well-decoupled from its environment, making a powerful tool for measurements of feeble sub-attonewton forces. We demonstrate a method to trap and manuever nanoparticles in an optical standing wave potential formed by retro-reflecting a laser beam from a metallic mirror surface. We can reliably position a $\sim 170$ nm diameter silica nanoparticle at distances of a few hundred nanometers to tens of microns from the surface of a gold-coated silicon mirror by transferring it from a single-beam tweezer trap into the standing wave potential. We can further scan the two dimensional space parallel to the mirror surface by using a piezo-driven mirror. This method enables three-dimensional scanning force sensing near surfaces using optically trapped nanoparticles, promising for high-sensitivity scanning force microscopy, tests of the Casimir effect, and tests of the gravitational inverse square law at micron scales.

physics.optics↗