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In modern cell-less wireless networks, mobility management is undergoing a significant transformation, transitioning from single-link handover management to a more adaptable multi-connectivity cluster reconfiguration approach, including often conflicting objectives like energy-efficient power allocation and satisfying varying reliability requirements. In this work, we address the challenge of dynamic clustering and power allocation for unmanned aerial vehicle (UAV) communication in wireless interference networks. Our objective encompasses meeting varying reliability demands, minimizing power consumption, and reducing the frequency of cluster reconfiguration. To achieve these objectives, we introduce a novel approach based on reinforcement learning using a masked soft actor-critic algorithm, specifically tailored for dynamic clustering and power allocation., Comment: 6 pages, 4 figures

Multi-Agent Path Finding (MAPF) involves determining paths for multiple agents to travel simultaneously and collision-free through a shared area toward given goal locations. This problem is computationally complex, especially when dealing with large numbers of agents, as is common in realistic applications like autonomous vehicle coordination. Finding an optimal solution is often computationally infeasible, making the use of approximate, suboptimal algorithms essential. Adding to the complexity, agents might act in a self-interested and strategic way, possibly misrepresenting their goals to the MAPF algorithm if it benefits them. Although the field of mechanism design offers tools to align incentives, using these tools without careful consideration can fail when only having access to approximately optimal outcomes. In this work, we introduce the problem of scalable mechanism design for MAPF and propose three strategyproof mechanisms, two of which even use approximate MAPF algorithms. We test our mechanisms on realistic MAPF domains with problem sizes ranging from dozens to hundreds of agents. We find that they improve welfare beyond a simple baseline., Comment: 12 pages, 5 figures. IJCAI'24 camera-ready version

Detecting cosmic gamma rays at high rates is the key to time-resolve the acceleration of particles within some of the most powerful events in the universe. Time-resolving the emission of gamma rays from merging celestial bodies, apparently random bursts of gamma rays, recurring novas in binary systems, flaring jets from active galactic nuclei, clocking pulsars, and many more became a critical contribution to astronomy. For good timing on account of high rates, we would ideally collect the naturally more abundant, low energetic gamma rays in the domain of one giga electronvolt in large areas. Satellites detect low energetic gamma rays but only in small collecting areas. Cherenkov telescopes have large collecting areas but can only detect the rare, high energetic gamma rays. To detect gamma rays with lower energies, Cherenkov-telescopes need to increase in precision and size. But when we push the concept of the -- far/tele -- seeing Cherenkov telescope accordingly, the telescope's physical limits show more clearly. The narrower depth-of-field of larger mirrors, the aberrations of mirrors, and the deformations of mirrors and mechanics all blur the telescope's image. To overcome these limits, we propose to record the -- full/plenum -- Cherenkov-light field of an atmospheric shower, i.e. recording the directions and impacts of each individual Cherenkov photon simultaneously, with a novel class of instrument. This novel Cherenkov plenoscope can turn a narrow depth-of-field into the perception of depth, can compensate aberrations, and can tolerate deformations. We design a Cherenkov plenoscope to explore timing by detecting low energetic gamma rays in large areas., Comment: An interdisciplinary effort investigated by physicists and civil engineers. For simulations, see https://github.com/cherenkov-plenoscope. 28 pages, 25 figures, 50 references, 100% motivation. Log:(2024 February 09) Add journal reference, update email and affiliations

The modeling of convection is a long standing problem in stellar physics. Up-to-now, all ad hoc models rely on a free parameter alpha (among others) which has no real physical justification and is therefore poorly constrained. However, a link exists between this free parameter and the entropy of the stellar adiabat. Prescriptions, derived from 3D stellar atmospheric models, are available that provide entropy as a function of stellar atmospheric parameters (effective temperature, surface gravity, chemical composition). This can provide constraints on alpha through the development of entropy-calibrated models. Several questions arise as these models are increasingly used. Which prescription should be used? How do uncertainties impact entropy-calibrated models? We aim to study the three existing prescriptions and determine which one should be used, and how. We implemented the entropy-calibration method into the stellar evolution code Cesam2k20 and performed comparisons with the Sun and the alpha Cen system. In addition, we used data from the CIFIST grid of 3D atmosphere models to evaluate the accuracy of the prescriptions. Of the three entropy prescriptions available, we determine which one best reproduces the entropies of the 3D models. We also demonstrate that the entropy obtained from this prescription should be corrected for the evolving chemical composition and for an entropy offset different between various EoS tables, following a precise procedure, otherwise classical parameters obtained from the models will be strongly biased. Finally, we also provide table with entropy of the adiabat of the CIFIST grid, as well as fits of these entropies. We performed a precise examination of entropy-calibrated modelling, and gave recommendations on which adiabatic entropy prescription to use, how to correct it and to implement the method into a stellar evolution code., Comment: 18 pages, 11 figures. Submitted to Astronomy and Astrophysics, recommended for publication with minor revisions

For non-reciprocal objects in vacuum, the Casimir interaction can become repulsive. Here, we present a comprehensive study for idealized non-reciprocal materials known as perfect electromagnetic conductors (PEMC). The system consists of two spheres made of different PEMC materials, including the plane-sphere geometry as a particular case. The sign of the Casimir force does not only depend on the distance between the spheres and their geometric parameters but can be controlled by adjusting the temperature. A repulsive Casimir interaction at small distances allows for stable equilibrium configurations of the spheres. A sum rule previously derived for the plane-plane geometry at zero temperature is violated in general, if at least one plane is replaced by a sphere.

Bartholomew's trend test belongs to the broad class of isotonic regression models, specifically with a single qualitative factor, e.g. dose levels. Using the approximation of the ANOVA F-test by the maximum contrast test against grand mean and pool-adjacent-violator estimates under order restriction, an easier to use approximation is proposed., Comment: 1 figure, 5 tables

Acute Kidney Injury (AKI) is a frequent complication in critically ill patients, affecting up to 50% of patients in the intensive care units. The lack of standardized and open-source tools for applying the Kidney Disease Improving Global Outcomes (KDIGO) criteria to time series data has a negative impact on workload and study quality. This project introduces pyAKI, an open-source pipeline addressing this gap by providing a comprehensive solution for consistent KDIGO criteria implementation. The pyAKI pipeline was developed and validated using a subset of the Medical Information Mart for Intensive Care (MIMIC)-IV database, a commonly used database in critical care research. We defined a standardized data model in order to ensure reproducibility. Validation against expert annotations demonstrated pyAKI's robust performance in implementing KDIGO criteria. Comparative analysis revealed its ability to surpass the quality of human labels. This work introduces pyAKI as an open-source solution for implementing the KDIGO criteria for AKI diagnosis using time series data with high accuracy and performance.

When different researchers study the same research question using the same dataset they may obtain different and potentially even conflicting results. This is because there is often substantial flexibility in researchers' analytical choices, an issue also referred to as ''researcher degrees of freedom''. Combined with selective reporting of the smallest p-value or largest effect, researcher degrees of freedom may lead to an increased rate of false positive and overoptimistic results. In this paper, we address this issue by formalizing the multiplicity of analysis strategies as a multiple testing problem. As the test statistics of different analysis strategies are usually highly dependent, a naive approach such as the Bonferroni correction is inappropriate because it leads to an unacceptable loss of power. Instead, we propose using the ''minP'' adjustment method, which takes potential test dependencies into account and approximates the underlying null distribution of the minimal p-value through a permutation-based procedure. This procedure is known to achieve more power than simpler approaches while ensuring a weak control of the family-wise error rate. We illustrate our approach for addressing researcher degrees of freedom by applying it to a study on the impact of perioperative paO2 on post-operative complications after neurosurgery. A total of 48 analysis strategies are considered and adjusted using the minP procedure. This approach allows to selectively report the result of the analysis strategy yielding the most convincing evidence, while controlling the type 1 error -- and thus the risk of publishing false positive results that may not be replicable.

We propose a general mechanism for generating limit cycle (LC) oscillations by coupling a linear bosonic mode to a dissipative nonlinear bosonic mode. By analyzing the stability matrix, we show that LCs arise due to a supercritical Hopf bifurcation. We find that the existence of LCs is independent of the sign of the effective nonlinear interaction. The LC phase can be classified as a continuous time crystal (CTC), if it emerges in a many-body system. The bosonic model can be realised in three-level systems interacting with a quantised light mode as realised in atom-cavity systems. Using such a platform, we experimentally observe LCs for the first time in an atom-cavity system with attractive optical pump lattice, thereby confirming our theoretical predictions.

We demonstrate a new method for determining the radius of micron-sized particles trapped by a vortex laser beam. The technique is based on measuring the rotation experienced by the center of mass of a microsphere that is laterally displaced by a Stokes drag force to an off-axis equilibrium position. The rotation results from an optical torque pointing along the direction opposite to the vortex beam angular momentum. We fit the rotation angle data for different Laguerre-Gaussian modes taking the radius as a fitting parameter in the Mie-Debye theory of optical tweezers. We also discuss how micron-sized beads can be used as probes for optical aberrations introduced by the experimental setup., Comment: 11 pages, 5 figures

Parametric resonances and amplification have led to extraordinary photoinduced phenomena in pump-probe experiments. While these phenomena manifest themselves in out-of-equilibrium settings, here, we present the striking result of parametric amplification in equilibrium. In particular, we demonstrate that quantum and thermal fluctuations of a Raman-active mode amplifies light inside a cavity, at equilibrium, when the Raman mode frequency is twice the cavity mode frequency. This noise-driven amplification leads to the creation of an unusual parametric Raman polariton, intertwining the Raman mode with cavity squeezing fluctuations, with smoking gun signatures in Raman spectroscopy. In the resonant regime, we show the emergence of not only quantum light amplification but also localization and static shift of the Raman mode. Apart from the fundamental interest of equilibrium parametric amplification our study suggests a resonant mechanism for controlling Raman modes and thus matter properties by cavity fluctuations. We conclude by outlining how to compute the Raman-cavity coupling, and suggest possible experimental realization, Comment: as accepted in PRL

We present the non-linear DC photoconductivity of graphene under strong infra-red (IR) radiation. The photoconductivity is obtained as the response to a strong DC electric field, with field strengths outside of the linear-response regime, while the IR radiation is described by a strong AC electric field. The conductivity displays two distinct regimes in which either the DC or the AC field dominates. We explore these regimes and associate them with the dynamics of driven Landau-Zener quenches in the case of a large DC field. In the limit of large AC field, we describe the conductivity in a Floquet picture and compare the results to the closely related Tien-Gordon effect. We present analytical calculations for the non-linear differential photoconductivity, for both regimes based on the corresponding mechanisms. As part of this discussion of the non-equilibrium state of graphene, we present analytical estimates of the conductivity of undriven graphene as a function of temperature and DC bias field strength that show very good agreement with our simulations.

Adiabatic processes can keep the quantum system in its instantaneous eigenstate, which is robust to noises and dissipation. However, it is limited by sufficiently slow evolution. Here, we experimentally demonstrate the transitionless quantum driving (TLQD) of the shortcuts to adiabaticity in gate-defined semiconductor quantum dots (QDs) to greatly accelerate the conventional adiabatic passage for the first time. For a given efficiency of quantum state transfer, the acceleration can be more than twofold. The dynamic properties also prove that the TLQD can guarantee fast and high-fidelity quantum state transfer. In order to compensate for the diabatic errors caused by dephasing noises, the modified TLQD is proposed and demonstrated in experiment by enlarging the width of the counter-diabatic drivings. The benchmarking shows that the state transfer fidelity of 97.8% can be achieved. This work will greatly promote researches and applications about quantum simulations and adiabatic quantum computation based on the gate-defined QDs., Comment: 6 pages, 3 figures

The elective clinical target volume (CTV-N) in oropharyngeal squamous cell carcinoma (OPSCC) is currently based mostly on the prevalence of lymph node metastases in different lymph node levels (LNLs) for a given primary tumor location. We present a probabilistic model for ipsilateral lymphatic spread that can quantify the microscopic nodal involvement risk based on an individual patient's T-category and clinical involvement of LNLs at diagnosis. We extend a previously published hidden Markov model (HMM), which models the LNLs (I, II, III, IV, V, and VII) as hidden binary random variables (RVs). Each represents a patient's true state of lymphatic involvement. Clinical involvement at diagnosis represents the observed binary RVs linked to the true state via sensitivity and specificity. The primary tumor and the hidden RVs are connected in a graph. Each edge represents the conditional probability of metastatic spread per abstract time-step, given disease at the edge's starting node. To learn these probabilities, we draw Markov chain Monte Carlo samples from the likelihood of a dataset (686 OPSCC patients) from three institutions. We compute the model evidence using thermodynamic integration for different graphs to determine which describes the data best. The graph maximizing the model evidence connects the tumor to each LNL and the LNLs I through V in order. It predicts the risk of occult disease in level IV is below 5% if level III is clinically negative, and that the risk of occult disease in level V is below 5% except for advanced T-category (T3 and T4) patients with clinical involvement of levels II, III, and IV. The provided statistical model of nodal involvement in OPSCC patients trained on multi-institutional data may guide the design of clinical trials on volume-deescalated treatment of OPSCC and contribute to more personal guidelines on elective nodal treatment., Comment: 17 pages, 12 figures, 7 tables, submitted to Physics in Medicine and Biology

Fusion-based photonic quantum computing architectures rely on two primitives: i) near-deterministic generation and control of constant-size entangled states and ii) probabilistic entangling measurements (photonic fusion gates) between entangled states. Here, we demonstrate these key functionalities by fusing resource states deterministically generated using a solid-state spin-photon interface. Repetitive operation of the source leads to sequential entanglement generation, whereby curiously entanglement is created between the quantum states of the same spin at two different instances in time. Such temporal multiplexing of photonic entanglement provides a resource-efficient route to scaling many-body entangled systems with photons.

Robustness to distribution shift has become a growing concern for text and image models as they transition from research subjects to deployment in the real world. However, high-quality benchmarks for distribution shift in tabular machine learning tasks are still lacking despite the widespread real-world use of tabular data and differences in the models used for tabular data in comparison to text and images. As a consequence, the robustness of tabular models to distribution shift is poorly understood. To address this issue, we introduce TableShift, a distribution shift benchmark for tabular data. TableShift contains 15 binary classification tasks in total, each with an associated shift, and includes a diverse set of data sources, prediction targets, and distribution shifts. The benchmark covers domains including finance, education, public policy, healthcare, and civic participation, and is accessible using only a few lines of Python code via the TableShift API. We conduct a large-scale study comparing several state-of-the-art tabular data models alongside robust learning and domain generalization methods on the benchmark tasks. Our study demonstrates (1) a linear trend between in-distribution (ID) and out-of-distribution (OOD) accuracy; (2) domain robustness methods can reduce shift gaps but at the cost of reduced ID accuracy; (3) a strong relationship between shift gap (difference between ID and OOD performance) and shifts in the label distribution. The benchmark data, Python package, model implementations, and more information about TableShift are available at https://github.com/mlfoundations/tableshift and https://tableshift.org ., Comment: NeurIPS 2023 Dataset and Benchmarks Track accepted version

The increasing importance of recycling makes the recovery of valuable elements from slags interesting, e.g., by the concept of engineered artificial minerals (EnAMs). In this concept, it is aimed for the formation of EnAMs, meaning phase(s) with a high content of the to-be-recovered element(s) from slags of pyrometallurgical recycling processes. For this, understanding the phase constitution of the slag systems is of high importance. The system Mg-Mn-Al-O is a metal oxide slag subsystem from Li-ion battery recycling, that is critical for the formation of spinel phases, which are competing phases to the possible Li-containing EnAM phase LiAlO2. Here, the phase constitution was investigated using a thin film materials library that covers the composition space (Mg14-69Mn11-38Al14-74)Ox. By means of high-throughput energy-dispersive X-ray spectroscopy and X-ray diffraction, the formation of the spinel solid solution phase was confirmed for a wide composition space. Increasing preferential orientation of the spinel solid solution along (400) with increasing Mg content was identified. X-ray photoelectron spectroscopy was used to measure the near-surface composition of selected areas of the materials library, and detailed peak fitting of the Mn 2p3/2 region revealed the Mn oxidation state to be a mixture of Mn2+ and Mn3+. For one measurement area of the materials library containing equal atomic amounts of Mg, Mn and Al, transmission electron microscopy showed that the approximately 420 nm-thick film consists of columnar spinel grains with Mg, Mn and Al being evenly distributed. Based on these results, we suggest that the shown high likelihood of spinel formation in slags might be influenced by controlling the Mn oxidation state to enable the formation of desirable EnAM phases.

Modern communication systems need to fulfill multiple and often conflicting objectives at the same time. In particular, new applications require high reliability while operating at low transmit powers. Moreover, reliability constraints may vary over time depending on the current state of the system. One solution to address this problem is to use joint transmissions from a number of base stations (BSs) to meet the reliability requirements. However, this approach is inefficient when considering the overall total transmit power. In this work, we propose a reinforcement learning-based power allocation scheme for an unmanned aerial vehicle (UAV) communication system with varying communication reliability requirements. In particular, the proposed scheme aims to minimize the total transmit power of all BSs while achieving an outage probability that is less than a tolerated threshold. This threshold varies over time, e.g., when the UAV enters a critical zone with high-reliability requirements. Our results show that the proposed learning scheme uses dynamic power allocation to meet varying reliability requirements, thus effectively conserving energy., Comment: 5 pages, 3 figures

It is the purpose of this paper to present a computational framework for reliably determining the frequency-dependent intermolecular and intramolecular NMR dipole-dipole relaxation rate of spin $1/2$ nuclei from MD simulations. The approach avoids alterations caused by well-known finite-size effects of the translational diffusion. Moreover, a procedure is derived to control and correct for effects caused by fixed distance-sampling cutoffs and periodic boundary conditions. By construction, this approach is capable of accurately predicting the correct low-frequency scaling behavior of the intermolecular NMR dipole-dipole relaxation rate and thus allows the reliable calculation of the frequency-dependent relaxation rate over many orders of magnitude. Our approach is based on the utilisation of the theory of Hwang and Freed for the intermolecular dipole-dipole correlation function and its corresponding spectral density [J. Chem. Phys. 63, 4017 (1975)] and its combination with data from molecular dynamics (MD) simulations. The deviations from the Hwang and Freed theory caused by periodic boundary conditions and sampling distance cutoffs are quantified by means of random walker Monte Carlo simulations. An expression based on the Hwang and Freed theoryis also suggested for correcting those effects. As a proof of principle, our approach is demonstrated by computing the frequency-dependent inter- and intramolecular dipolar NMR relaxation rate of the $^1$H nuclei in liquid water at $273\,\mbox{K}$ and $298\,\mbox{K}$ based on simulations of the TIP4P/2005 model. Our calculations are suggesting that the intermolecular contribution to the $^1$H NMR relaxation rate of the TIP4P/2005 model in the extreme narrowing limit has previously been substantially underestimated., Comment: 15 pages, 8 figures, removed typos, added an additional Figure 4, corrected mistake in Figure 8 (previously Figure 7)

We report on MoSi-based superconducting nanowire single-photon detectors on a gallium arsenide substrate. MoSi deposited on a passivated GaAs surface has the same critical temperature as MoSi deposited on silicon. The critical temperature decreases slightly on depositing MoSi directly on the native oxide of GaAs. Hence, MoSi works well as a thin-film superconductor on GaAs. We propose that the amorphous structure of MoSi ensures compatibility with the GaAs matrix. Superconducting nanowire single-photon detectors (SNSPDs) are fabricated with MoSi on GaAs using a meander-wire design. The SNSPD metrics are very similar to those of devices fabricated with the same procedure on a silicon substrate. We observe a plateau in the response-versus-bias curve signalling a saturated internal quantum efficiency. The plateau remains even at an elevated temperature, 2.2 K, at a wavelength of 980 nm. We achieve a timing jitter of 50 ps and a recovery time of 29 ns. These results point to the promise of integrating MoSi SNSPDs with GaAs photonic circuits.