Hybrid MSRM-Based Deep Learning and Multitemporal Sentinel 2-Based Machine Learning Algorithm Detects Near 10k Archaeological Tumuli in North-Western Iberia

This paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available

Hybrid MSRM-based deep learning and multitemporal Sentinel 2-based machine learning algorithm detects near 10k archaeological tumuli in north-western Iberia

This is the final version. Available on open access from MDPI via the DOI in this record.Data Availability Statement: All relevant material has been made available as Supplementary MaterialsThis paper presents an algorithm for large-scale automatic detection of burial mounds, one of the most common types of archaeological sites globally, using LiDAR and multispectral satellite data. Although previous attempts were able to detect a good proportion of the known mounds in a given area, they still presented high numbers of false positives and low precision values. Our proposed approach combines random forest for soil classification using multitemporal multispectral Sentinel-2 data and a deep learning model using YOLOv3 on LiDAR data previously pre-processed using a multi–scale relief model. The resulting algorithm significantly improves previous attempts with a detection rate of 89.5%, an average precision of 66.75%, a recall value of 0.64 and a precision of 0.97, which allowed, with a small set of training data, the detection of 10,527 burial mounds over an area of near 30,000 km2, the largest in which such an approach has ever been applied. The open code and platforms employed to develop the algorithm allow this method to be applied anywhere LiDAR data or high-resolution digital terrain models are available.European Union Horizon 2020Spanish Ministry of Science, Innovation and UniversitiesFundación BBV

Universal Vectorial and Ultrasensitive Nanomechanical Force Field Sensor

Miniaturization of force probes into nanomechanical oscillators enables ultrasensitive investigations of forces on dimensions smaller than their characteristic length scale. Meanwhile it also unravels the force field vectorial character and how its topology impacts the measurement. Here we expose an ultrasensitive method to image 2D vectorial force fields by optomechanically following the bidimensional Brownian motion of a singly clamped nanowire. This novel approach relies on angular and spectral tomography of its quasi frequency-degenerated transverse mechanical polarizations: immersing the nanoresonator in a vectorial force field does not only shift its eigenfrequencies but also rotate eigenmodes orientation as a nano-compass. This universal method is employed to map a tunable electrostatic force field whose spatial gradients can even take precedence over the intrinsic nanowire properties. Enabling vectorial force fields imaging with demonstrated sensitivities of attonewton variations over the nanoprobe Brownian trajectory will have strong impact on scientific exploration at the nanoscale

Signatures of a dissipative phase transition in photon correlation measurements

This work was supported by the Swiss National Science Foundation (SNSF) through the National Centre of Competence in Research - Quantum Science and Technology (NCCR QSIT). A.S., C.S., and S.H. acknowledge support by the State of Bavaria and the DFG within the Project Schn1376/3-1.Understanding and characterizing phase transitions in driven-dissipative systems constitutes a new frontier for many-body physics[1-8]. A generic feature of dissipative phase transitions is a vanishing gap in the Liouvillian spectrum [9], which leads to long-lived deviations from the steady state as the system is driven towards the transition. Here, we show that photon correlation measurements can be used to characterize the corresponding critical slowing down of non-equilibrium dynamics. We focus on the extensively studied phenomenon of optical bistability in GaAs cavity polaritons [10,11], which can be described as a first-order dissipative phase transition [12-14]. Increasing the excitation strength towards the bistable range results in an increasing photon-bunching signal along with a decay time that is prolonged by more than nine orders of magnitude as compared with that of single polaritons. In the limit of strong polariton interactions leading to pronounced quantum fluctuations, the mean-field bistability threshold is washed out. Nevertheless, the functional form with which the Liouvillian gap closes as the thermodynamic limit is approached provides a signature of the emerging dissipative phase transition. Our results establish photon correlation measurements as an invaluable tool for studying dynamical properties of dissipative phase transitions without requiring phase-sensitive interferometric measurements.PostprintPeer reviewe

Fermi polaron-polaritons in charge-tunable atomically thin semiconductors

The dynamics of a mobile quantum impurity in a degenerate Fermi system is a fundamental problem in many-body physics. The interest in this field has been renewed due to recent ground-breaking experiments with ultracold Fermi gases. Optical creation of an exciton or a polariton in a two-dimensional electron system embedded in a microcavity constitutes a new frontier for this field due to an interplay between cavity coupling favouring ultralow-mass polariton formation6 and exciton–electron interactions leading to polaron or trion formation. Here, we present cavity spectroscopy of gate-tunable monolayer MoSe2 exhibiting strongly bound trion and polaron resonances, as well as non-perturbative coupling to a single microcavity mode. As the electron density is increased, the oscillator strength determined from the polariton splitting is gradually transferred from the higher-energy repulsive exciton-polaron resonance to the lower-energy attractive exciton-polaron state. Simultaneous observation of polariton formation in both attractive and repulsive branches indicates a new regime of polaron physics where the polariton impurity mass can be much smaller than that of the electrons. Our findings shed new light on optical response of semiconductors in the presence of free carriers by identifying the Fermi polaron nature of excitonic resonances and constitute a first step in investigation of a new class of degenerate Bose–Fermi mixtures.Physic

Multiparametric computer-aided differential diagnosis of Alzheimer's disease and frontotemporal dementia using structural and advanced MRI

textabstractObjectives: To investigate the added diagnostic value of arterial spin labelling (ASL) and diffusion tensor imaging (DTI) to structural MRI for computer-aided classificat

Cooperatively-enhanced atomic dipole forces in optically trapped nanodiamonds containing NV centres, in liquid

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