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Beta Pictoris (Beta Pic)'s well-studied debris disk and two known giant planets, in combination with the stability of HST/STIS (and now also JWST), offers a unique opportunity to test planet-disk interaction models and to observe recent planetesimal collisions. We present HST/STIS coronagraphic imaging from two new epochs of data taken between 2021 and 2023, complementing earlier data taken in 1997 and 2012. This dataset enables the longest baseline and highest precision temporal comparison of any debris disk to date, with sensitivity to temporal surface brightness variations of sub-percentage levels in the midplane of the disk. While no localized surface brightness changes are detected, which would be indicative of a recent planetesimal collision, there is a tentative brightening of the SE side of the disk over the past decade. We link the constraints on surface brightness variations to dynamical models of the planetary system's evolution and to the collisional history of planetesimals. Using a coupled collisional model and injection/recovery framework, we estimate sensitivity to expanding collisional debris down to a Ceres-mass per progenitor in the most sensitive regions of the disk midplane. These results demonstrate the capabilities of long-baseline, temporal studies with HST (and also soon with JWST) for constraining the physical processes occurring within debris disks., Comment: 16 pages, 7 figures, 1 table. Accepted for publication in ApJ

Correlation Plenoptic Imaging (CPI) is a novel technological imaging modality enabling to overcome drawbacks of standard plenoptic devices, while preserving their advantages. However, a major challenge in view of real-time application of CPI is related with the relevant amount of required frames and the consequent computational-intensive processing algorithm. In this work, we describe the design and implementation of an optimized processing algorithm that is portable to an efficient computational environment and exploits the highly parallel algorithm offered by GPUs. Improvements by a factor ranging from 20x, for correlation measurement, to 500x, for refocusing, are demonstrated. Exploration of the relation between the improvement in performance achieved and actual GPU capabilities, also indicates the feasibility of near-real time processing capability, opening up to the potential use of CPI for practical real-time application., Comment: 17 pages, 13 figures

Differential privacy has become the preeminent technique to protect the privacy of individuals in a database while allowing useful results from data analysis to be shared. Notably, it guarantees the amount of privacy loss in the worst-case scenario. Although many theoretical research papers have been published, practical real-life application of differential privacy demands estimating several important parameters without any clear solutions or guidelines. In the first part of the paper, we provide an overview of key concepts in differential privacy, followed by a literature review and discussion of its application to ECG analysis. In the second part of the paper, we explore how to implement differentially private query release on an arrhythmia database using a six-step process. We provide guidelines and discuss the related literature for all the steps involved, such as selection of the $\epsilon$ value, distribution of the total $\epsilon$ budget across the queries, and estimation of the sensitivity for the query functions. At the end, we discuss the shortcomings and challenges of applying differential privacy to ECG datasets.

Recent advancements in quality control across various industries have increasingly utilized the integration of video cameras and image processing for effective defect detection. A critical barrier to progress is the scarcity of comprehensive datasets featuring annotated defects, which are essential for developing and refining automated defect detection models. This systematic review, spanning from 2015 to 2023, identifies 15 publicly available datasets and critically examines them to assess their effectiveness and applicability for benchmarking and model development. Our findings reveal a diverse landscape of datasets, such as NEU-CLS, NEU-DET, DAGM, KolektorSDD, PCB Defect Dataset, and the Hollow Cylindrical Defect Detection Dataset, each with unique strengths and limitations in terms of image quality, defect type representation, and real-world applicability. The goal of this systematic review is to consolidate these datasets in a single location, providing researchers who seek such publicly available resources with a comprehensive reference., Comment: One figure and one table

This study evaluates $n = 300$ short-form physics essay submissions, equally divided between student work submitted before the introduction of ChatGPT and those generated by OpenAI's GPT-4. In blinded evaluations conducted by five independent markers who were unaware of the origin of the essays, we observed no statistically significant differences in scores between essays authored by humans and those produced by AI (p-value $= 0.107$, $\alpha$ = 0.05). Additionally, when the markers subsequently attempted to identify the authorship of the essays on a 4-point Likert scale - from `Definitely AI' to `Definitely Human' - their performance was only marginally better than random chance. This outcome not only underscores the convergence of AI and human authorship quality but also highlights the difficulty of discerning AI-generated content solely through human judgment. Furthermore, the effectiveness of five commercially available software tools for identifying essay authorship was evaluated. Among these, ZeroGPT was the most accurate, achieving a 98% accuracy rate and a precision score of 1.0 when its classifications were reduced to binary outcomes. This result is a source of potential optimism for maintaining assessment integrity. Finally, we propose that texts with $\leq 50\%$ AI-generated content should be considered the upper limit for classification as human-authored, a boundary inclusive of a future with ubiquitous AI assistance whilst also respecting human-authorship., Comment: 18 pages, 5 figures

Many biological systems can form strong adhesion to various materials with complex shapes. The adhesion is further switchable between strongly adhering and completely non-adhering in a simple and fast manner. By contrast, no engineering system has yet achieved the same robust adherence and switching. This limitation severely hinders the advancement of several emerging technologies including biomimetic robots, assembly-based manufacturing, precision medicine, wearable and implantable devices, as well as on-demand material dismantling and recycling for sustainability. Here we present a design approach for strong and highly switchable adhesion by synergizing the surface stickiness, bulk energy dissipation, and stimuli-responsive polymer chains in a thermo-switchable soft sticky adhesive. The adhesive has a high adhesion strength of about 80 kPa with diverse materials at room temperature. The adhesion is highly switchable to near-vanishing (about 0.6 kPa) at an elevated temperature due to the thermo-responsive surface polymer chain retraction. This adhesion switching is reversible and repeatable for many cycles, enabling selective pick-and-release of objects with various materials, shapes, sizes, and weights. The switching time is around 10 s with an adhesive layer of 1 mm, governed by thermal conduction through the adhesive, faster than or comparable to most state-of-the-art methods. The adhesive is self-healing, and can be recycled, dried, stored, reswollen, and reused with nearly intact adhesion and switching properties. The synergistic design combining strong adhesion and stimuli-responsive switching can be potentially extended to various polymer systems, and further enhanced by optimized surface architectures., Comment: Submitted manuscript

To address many of the deficiencies in optical neuroimaging technologies such as poor spatial resolution, time-consuming reconstruction, low penetration depth, and contact-based measurement, a novel, noncontact, time-resolved laser speckle contrast imaging (TR-LSCI) technique has been developed for continuous, fast, and high-resolution 2D mapping of cerebral blood flow (CBF) at different depths of the head. TR-LSCI illuminates the head with picosecond-pulsed, coherent, widefield near-infrared light and synchronizes a newly developed, high-resolution, gated single-photon avalanche diode camera (SwissSPAD2) to capture CBF maps at different depths. By selectively collecting diffuse photons with longer pathlengths through the head, TR-LSCI reduces partial volume artifacts from the overlying tissues, thus improving the accuracy of CBF measurement in the deep brain. CBF map reconstruction was dramatically expedited by incorporating highly parallelized computation. The performance of TR-LSCI was evaluated using head-simulating phantoms with known properties and in-vivo rodents with varied hemodynamic challenges to the brain. Results from these pilot studies demonstrated that TR-LSCI enabled mapping CBF variations at different depths with a sampling rate of up to 1 Hz and spatial resolutions ranging from tens of micrometers on the head surface to 1-2 millimeters in the deep brain. With additional improvements and validation in larger populations against established methods, we anticipate offering a noncontact, fast, high-resolution, portable, and affordable brain imager for fundamental neuroscience research in animals and for translational studies in humans., Comment: 22 pages, 7 figures, 4 tables

Recent work has highlighted the complex influence training hyperparameters, e.g., the number of training epochs, can have on the prunability of machine learning models. Perhaps surprisingly, a systematic approach to predict precisely how adjusting a specific hyperparameter will affect prunability remains elusive. To address this gap, we introduce a phenomenological model grounded in the statistical mechanics of learning. Our approach uses temperature-like and load-like parameters to model the impact of neural network (NN) training hyperparameters on pruning performance. A key empirical result we identify is a sharp transition phenomenon: depending on the value of a load-like parameter in the pruned model, increasing the value of a temperature-like parameter in the pre-pruned model may either enhance or impair subsequent pruning performance. Based on this transition, we build a three-regime model by taxonomizing the global structure of the pruned NN loss landscape. Our model reveals that the dichotomous effect of high temperature is associated with transitions between distinct types of global structures in the post-pruned model. Based on our results, we present three case-studies: 1) determining whether to increase or decrease a hyperparameter for improved pruning; 2) selecting the best model to prune from a family of models; and 3) tuning the hyperparameter of the Sharpness Aware Minimization method for better pruning performance., Comment: ICML 2023

The latest AI language modules can produce original, high quality full short-form ($300$-word) Physics essays within seconds. These technologies such as ChatGPT and davinci-003 are freely available to anyone with an internet connection. In this work, we present evidence of AI generated short-form essays achieving first-class grades on an essay writing assessment from an accredited, current university Physics module. The assessment requires students answer five open-ended questions with a short, $300$-word essay each. Fifty AI answers were generated to create ten submissions that were independently marked by five separate markers. The AI generated submissions achieved an average mark of $71 \pm 2 \%$, in strong agreement with the current module average of $71 \pm 5 %$. A typical AI submission would therefore most-likely be awarded a First Class, the highest classification available at UK universities. Plagiarism detection software returned a plagiarism score between $2 \pm 1$% (Grammarly) and $7 \pm 2$% (TurnitIn). We argue that these results indicate that current AI MLPs represent a significant threat to the fidelity of short-form essays as an assessment method in Physics courses., Comment: 14 pages, 2 figures

The correlation properties of light provide an outstanding tool to overcome the limitations of traditional imaging techniques. A relevant case is represented by correlation plenoptic imaging (CPI), a quantum-inspired volumetric imaging protocol employing spatio-temporally correlated photons from either entangled or chaotic sources to address the main limitations of conventional light-field imaging, namely, the poor spatial resolution and the reduced change of perspective for 3D imaging. However, the application potential of high-resolution imaging modalities relying on photon correlations is limited, in practice, by the need to collect a large number of frames. This creates a gap, unacceptable for many relevant tasks, between the time performance of correlated-light imaging and that of traditional imaging methods. In this article, we address this issue by exploiting the photon number correlations intrinsic in chaotic light, combined with a cutting-edge ultrafast sensor made of a large array of single-photon avalanche diodes (SPADs). This combination of source and sensor is embedded within a novel single-lens CPI scheme enabling to acquire 10 volumetric images per second. Our results place correlated-photon imaging at a competitive edge and prove its potential in practical applications., Comment: 13 pages, 6 figures

More than 5,000 exoplanets have been confirmed and among them almost 4,000 were discovered by the transit method. However, few transiting exoplanets have an orbital period greater than 100 days. Here we report a transit detection of Kepler-167 e, a "Jupiter analog" exoplanet orbiting a K4 star with a period of 1,071 days, using the Unistellar ground-based telescope network. From 2021 November 18 to 20, citizen astronomers located in nine different countries gathered 43 observations, covering the 16 hour long transit. Using a nested sampling approach to combine and fit the observations, we detected the mid-transit time to be UTC 2021 November 19 17:20:51 with a 1$\sigma$ uncertainty of 9.8 minutes, making it the longest-period planet to ever have its transit detected from the ground. This is the fourth transit detection of Kepler-167 e, but the first made from the ground. This timing measurement refines the orbit and keeps the ephemeris up to date without requiring space telescopes. Observations like this demonstrate the capabilities of coordinated networks of small telescopes to identify and characterize planets with long orbital periods., Comment: 11 pages, 3 figures, 2 tables, accepted in ApJL

The transiting planet HD80606b undergoes a 1000-fold increase in insolation during its 111-day orbit due to it being highly eccentric (e=0.93). The planet's effective temperature increases from 400K to over 1400K in a few hours as it makes a rapid passage to within 0.03AU of its host star during periapsis. Spectroscopic observations during the eclipse (which is conveniently oriented a few hours before periapsis) of HD80606b with the James Webb Space Telescope (JWST) are poised to exploit this highly variable environment to study a wide variety of atmospheric properties, including composition, chemical and dynamical timescales, and large scale atmospheric motions. Critical to planning and interpreting these observations is an accurate knowledge of the planet's orbit. We report on observations of two full-transit events: 7 February 2020 as observed by the TESS spacecraft and 7--8 December 2021 as observed with a worldwide network of small telescopes. We also report new radial velocity observations which when analyzed with a coupled model to the transits greatly improve the planet's orbital ephemeris. Our new orbit solution reduces the uncertainty in the transit and eclipse timing of the JWST era from tens of minutes to a few minutes. When combined with the planned JWST observations, this new precision may be adequate to look for non-Keplerian effects in the orbit of HD80606b., Comment: Accepted for publication in AJ; in press

The geographical variability, frequency content, and vertical structure of near-surface oceanic kinetic energy (KE) are important for air-sea interaction, marine ecosystems, operational oceanography, pollutant tracking, and interpreting remotely sensed velocity measurements. Here, KE in high-resolution global simulations (HYbrid Coordinate Ocean Model; HYCOM, and Massachusetts Institute of Technology general circulation model; MITgcm), at the sea surface (0 m) and 15 m, are respectively compared with KE from undrogued and drogued surface drifters. Global maps and zonal averages are computed for low-frequency ($<$ 0.5 cpd), near-inertial, diurnal, and semi-diurnal bands. Both models exhibit low-frequency equatorial KE that is low relative to drifter values. HYCOM near-inertial KE is higher than in MITgcm, and closer to drifter values, probably due to more frequently updated atmospheric forcing. HYCOM semi-diurnal KE is lower than in MITgcm, and closer to drifter values, likely due to inclusion of a parameterized topographic internal wave drag. A concurrent tidal harmonic analysis in the diurnal band demonstrates that much of the diurnal flow is non-tidal. We compute a simple proxy of near-surface vertical structure, the ratio of 0 m KE to 0 m KE plus 15 m KE in model outputs, and undrogued KE to undrogued KE plus drogued KE in drifter observations. Over most latitudes and frequency bands, model ratios track the drifter ratios to within error bars. Values of this ratio demonstrate significant vertical structure in all frequency bands except the semidiurnal band. Latitudinal dependence in the ratio is greatest in diurnal and low-frequency bands., Comment: revised for AGU JGR: Oceans

We present spectroscopic measurements of the Rossiter-McLaughlin effect for WASP-148b, the only known hot Jupiter with a nearby warm-Jupiter companion, from the WIYN/NEID and Keck/HIRES instruments. This is one of the first scientific results reported from the newly commissioned NEID spectrograph, as well as the second obliquity constraint for a hot Jupiter system with a close-in companion, after WASP-47. WASP-148b is consistent with being in alignment with the sky-projected spin axis of the host star, with $\lambda=-8^{\circ}.2^{{+8^{\circ}.7}}_{-9^{\circ}.7}$. The low obliquity observed in the WASP-148 system is consistent with the orderly-alignment configuration of most compact multi-planet systems around cool stars with obliquity constraints, including our solar system, and may point to an early history for these well-organized systems in which migration and accretion occurred in isolation, with relatively little disturbance. By contrast, previous results have indicated that high-mass and hot stars appear to more commonly host a wide range of misaligned planets: not only single hot Jupiters, but also compact systems with multiple super-Earths. We suggest that, to account for the high rate of spin-orbit misalignments in both compact multi-planet and isolated-hot-Jupiter systems orbiting high-mass and hot stars, spin-orbit misalignments may be caused by distant giant planet perturbers, which are most common around these stellar types., Comment: 13 pages, 4 figures, accepted for publication in ApJL

Multiply-excited states in semiconductor quantum dots feature intriguing physics and play a crucial role in nanocrystal-based technologies. While photoluminescence provides a natural probe to investigate these states, room temperature single-particle spectroscopy of their emission has so far proved elusive due to the temporal and spectral overlap with emission from the singly-excited and charged states. Here we introduce biexciton heralded spectroscopy, enabled by a single-photon avalanche diode array based spectrometer. This allows us to directly observe biexciton-exciton emission cascades and measure the biexciton binding energy of single quantum dots at room temperature, even though it is well below the scale of thermal broadening and spectral diffusion. Furthermore, we uncover correlations hitherto masked in ensembles, of the biexciton binding energy with both charge-carrier confinement and fluctuations of the local electrostatic potential. Heralded spectroscopy has the potential of greatly extending our understanding of charge-carrier dynamics in multielectron systems and of parallelization of quantum optics protocols., Comment: 9+10 pages, 5+8 figures

Understanding exciton-exciton interaction in multiply-excited nanocrystals is crucial to their utilization as functional materials. Yet, for lead halide perovskite nanocrystals, which are promising candidates for nanocrystal-based technologies, numerous contradicting values have been reported for the strength and sign of their exciton-exciton interaction. In this work we unambiguously determine the biexciton binding energy in single cesium lead halide perovskite nanocrystals at room temperature. This is enabled by the recently introduced SPAD array spectrometer, capable of temporally isolating biexciton-exciton emission cascades while retaining spectral resolution. We demonstrate that CsPbBr$_3$ nanocrystals feature an attractive exciton-exciton interaction, with a mean biexciton binding energy of 10 meV. For CsPbI$_3$ nanocrystals we observe a mean biexciton binding energy that is close to zero, and individual nanocrystals show either weakly attractive or weakly repulsive exciton-exciton interaction. We further show that within ensembles of both materials, single-nanocrystal biexciton binding energies are correlated with the degree of charge-carrier confinement., Comment: 7+7 pages, 4+4 figures

We review the advancement of the research toward the design and implementation of quantum plenoptic cameras, radically novel 3D imaging devices that exploit both momentum-position entanglement and photon-number correlations to provide the typical refocusing and ultra-fast, scanning-free, 3D imaging capability of plenoptic devices, along with dramatically enhanced performances, unattainable in standard plenoptic cameras: diffraction-limited resolution, large depth of focus, and ultra-low noise. To further increase the volumetric resolution beyond the Rayleigh diffraction limit, and achieve the quantum limit, we are also developing dedicated protocols based on quantum Fisher information. However, for the quantum advantages of the proposed devices to be effective and appealing to end-users, two main challenges need to be tackled. First, due to the large number of frames required for correlation measurements to provide an acceptable SNR, quantum plenoptic imaging would require, if implemented with commercially available high-resolution cameras, acquisition times ranging from tens of seconds to a few minutes. Second, the elaboration of this large amount of data, in order to retrieve 3D images or refocusing 2D images, requires high-performance and time-consuming computation. To address these challenges, we are developing high-resolution SPAD arrays and high-performance low-level programming of ultra-fast electronics, combined with compressive sensing and quantum tomography algorithms, with the aim to reduce both the acquisition and the elaboration time by two orders of magnitude. Routes toward exploitation of the QPI devices will also be discussed., Comment: 14 pages, 6 figures

Single-photon light detection and ranging (LiDAR) is a key technology for depth imaging through complex environments. Despite recent advances, an open challenge is the ability to isolate the LiDAR signal from other spurious sources including background light and jamming signals. Here we show that a time-resolved coincidence scheme can address these challenges by exploiting spatiotemporal correlations between entangled photon pairs. We demonstrate that a photon-pair-based LiDAR can distill desired depth information in the presence of both synchronous and asynchronous spurious signals without prior knowledge of the scene and the target object. This result enables the development of robust and secure quantum LiDAR systems and paves the way to time-resolved quantum imaging applications.

The globus pallidus (GPe) of the basal ganglia has been underappreciated for decades due to poor understanding of its cells and circuits. The advent of molecular tools has sparked a resurgence in interest in the GPe. Here, we review a recent flurry of publications that has unveiled the complexity of the molecular landscape and cellular composition within the GPe. These discoveries have revealed that GPe neurons display a number of circuit features that do not conform to the traditional views of the basal ganglia. Consistent with its broad interconnectivity across the brain, emerging evidence suggests that the GPe plays multifaceted roles in both motor and non-motor functions. Altogether, recent data highlight cellular and functional diversity within the GPe and prompt new proposals for computational rules of the basal ganglia.