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Landing a multirotor unmanned aerial vehicle (UAV) on an uncrewed surface vessel (USV) extends the operational range and offers recharging capabilities for maritime and limnology applications, such as search-and-rescue and environmental monitoring. However, autonomous UAV landings on USVs are challenging due to the unpredictable tilt and motion of the vessel caused by waves. This movement introduces spatial and temporal uncertainties, complicating safe, precise landings. Existing autonomous landing techniques on unmanned ground vehicles (UGVs) rely on shared state information, often causing time delays due to communication limits. This paper introduces a learning-based distributed Model Predictive Control (MPC) framework for autonomous UAV landings on USVs in wave-like conditions. Each vehicle's MPC optimizes for an artificial goal and input, sharing only the goal with the other vehicle. These goals are penalized by coupling and platform tilt costs, learned as a Gaussian Process (GP). We validate our framework in comprehensive indoor experiments using a custom-designed platform attached to a UGV to simulate USV tilting motion. Our approach achieves a 53% increase in landing success compared to an approach that neglects the impact of tilt motion on landing.

Holographic models that consider classical vector fields in a 5-d background provide successful effective descriptions for heavy vector meson spectra. This holds both in the vacuum and in a thermal medium, like the quark gluon plasma. However, it is somehow mysterious the way that these phenomenological models work. In particular, what is the role of the fifth dimension and what is the relation between the holographic 5-d background and the physical (4-d) heavy mesons. Hadrons, in contrast to leptons, are composite particles with some internal structure, that depends on the energy at which they are observed. In this work, a static meson is represented by a heavy quark-antiquark pair with an interaction described by a Nambu Goto string living in the same 5-d background that provides field solutions leading to masses and decay constants of charmonium states. The interaction potential that shows up is linear for large distances with a string tension consistent with the effective Cornell potential. Introducing temperature $T$ in the background it is found, for the $J/\psi$ case, that there is a deconfining transition at some critical value of $T$. The results obtained indicate that the 5-d background is effectively representing the internal structure of the (static) charmonium (quasi) states., Comment: 27 pages, 13 figures

During infectious disease outbreaks, estimates of time-varying pathogen transmissibility, such as the instantaneous reproduction number R(t) or epidemic growth rate r(t), are used to inform decision-making by public health authorities. For directly transmitted infectious diseases, the renewal equation framework is a widely used method for measuring time-varying transmissibility. The framework uses information on the typical time elapsing between an infection and the offspring infections (quantified by the generation time distribution), and R(t), to describe the rate at which currently infected individuals generate new infections. For diseases with transmission cycles involving hosts and vectors, however, renewal equation models have been far less used. This is likely due to difficulties in mechanistically defining generation times that can capture the complexity of multi-stage, human-vector relationships. Here, using dengue as an example, we provide general renewal equations that are derived from first principles using age-structured systems of coupled partial differential equations across human and vector sub-populations. Our framework tracks the multi-stage transmission cycle over calendar time and across stage-specific ages, resulting in governing renewal equations that quantify how the rate at which new infections are generated from existing infections depends on stage-specific processes. The framework provides a foundation on which to base inferential frameworks for estimating R(t) and r(t) for infectious diseases with multiple stages in the transmission cycle, Comment: 14 pages, 3 figures

We develop a theory of the nonlocal conductance $G_{RL}(V)$ for a disordered Majorana wire tuned near the topological transition critical point. We show that the differential conductance is an odd function of bias, $G_{RL}(V) = -G_{RL}(-V)$. We factorize the conductance into terms describing the contacts between the wire and the normal leads, and the term describing quasiparticle propagation along the wire. Topological transition affects only the latter term. At the critical point, the quasiparticle localization length has a logarithmic singularity at the Fermi level, $l(E) \propto \ln(1 / E)$. This singularity directly manifests in the conductance magnitude, as $\ln |G_{RL}(V) / G_Q| \sim L / l(eV)$ for the wire of length $L \gg l(eV)$. Tuning the wire away from the immediate vicinity of the critical point changes the monotonicity of $l(E)$. This change in monotonicty allows us to define the width of the critical region around the transition point., Comment: 26 pages, 9 figues

Using coarse-grained molecular dynamics simulations and a united-monomer model of PE, single well-aligned multi-lamella PE crystals grown in previous work [ACS Macro Letters 12, 808 (2023)] are deformed uniaxially to mimic tensile testing. During deformation, the crystallinity, tie-chain segments, entanglements and folds are monitored and correlated with the stress-strain behaviour and mechanical properties. At small strains, the single well-aligned PE crystals reveal a larger Young modulus when the deformation direction is perpendicular to the global stem direction. At large strains, the memory of the initial topology plays little role in the mechanical response and is observed to be completely destroyed. Short chain branching appears to suppress disentanglement and shear induced alignment of the chains during deformation. As a result, tie-chains and entanglements persist in branched systems and the peak stress at failure is found to be proportional to the change in number of tie-chains from the beginning of the brittle break to its end. Our findings suggest the remarkable mechanical properties of bimodal branched PE result directly from tie-chains, with entanglements playing a secondary role in the mechanical response.

To take full advantage of a specific hardware target, performance engineers need to gain control on compilers in order to leverage their domain knowledge about the program and hardware. Yet, modern compilers are poorly controlled, usually by configuring a sequence of coarse-grained monolithic black-box passes, or by means of predefined compiler annotations/pragmas. These can be effective, but often do not let users precisely optimize their varying compute loads. As a consequence, performance engineers have to resort to implementing custom passes for a specific optimization heuristic, requiring compiler engineering expert knowledge. In this paper, we present a technique that provides fine-grained control of general-purpose compilers by introducing the Transform dialect, a controllable IR-based transformation system implemented in MLIR. The Transform dialect empowers performance engineers to optimize their various compute loads by composing and reusing existing - but currently hidden - compiler features without the need to implement new passes or even rebuilding the compiler. We demonstrate in five case studies that the Transform dialect enables precise, safe composition of compiler transformations and allows for straightforward integration with state-of-the-art search methods.

Electron-electron interactions in high-mobility conductors can give rise to transport signatures resembling those described by classical hydrodynamics. Using a nanoscale scanning magnetometer, we imaged a distinctive hydrodynamic transport pattern - stationary current vortices - in a monolayer graphene device at room temperature. By measuring devices with increasing characteristic size, we observed the disappearance of the current vortex and thus verify a prediction of the hydrodynamic model. We further observed that vortex flow is present for both hole- and electron-dominated transport regimes, while disappearing in the ambipolar regime. We attribute this effect to a reduction of the vorticity diffusion length near charge neutrality. Our work showcases the power of local imaging techniques for unveiling exotic mesoscopic transport phenomena., Comment: Main text and supplementary materials: 16 + 28 pages, 4 + 15 figures. This is the author's version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 25 April 2024, DOI: 10.1126/science.adj2167

Polyethylene (PE) chains, with CH2 groups replaced by CBr2 at regular intervals ("precision PE"), have been observed to exhibit competing polymorphs driven by a preference for quantized fold lengths by Tasaki et al. Motivated by this recent discovery, the crystallisation behaviour of such precision PE chains, 400 carbons long with CBr2 groups placed regularly at every 21st carbon, is investigated using molecular dynamics simulations. The united-monomer model of PE is extended to include dibromo groups, with steric clashes at the bromines reflected in a triple-well bending potential, demonstrating its function as a preferred fold site. Different crystallisation protocols, continuous-cooling and self-seeding, reveal remarkably different crystals. Using self-seeding, the crystalline lamellar thickness increases monotonically with temperature, in quantized multiples of the distance between dibromo units. Polymer chains are observed to fold preferentially at the dibromo groups and such groups appear to be tolerated within the crystal lamellae. On quenching the bromos assemble to form registered layers, not unlike Smectic phases observed in liquid crystals, which confirms the experimental observation of competing Form I and Form I' polymorphs.

Scanning probe microscopy with multi-qubit sensors offers the potential to improve imaging speed and measure previously inaccessible quantities, such as two-point correlations. We develop a multiplexed quantum sensing approach with scanning probes containing two nitrogen-vacancy (NV) centers at the tip apex. A shared optical channel is used for simultaneous qubit initialization and readout, while phase- and frequency-dependent microwave spin manipulations are leveraged for de-multiplexing the optical readout signal. Scanning dual-NV magnetometry is first demonstrated by simultaneously imaging multiple field projections of a ferrimagnetic racetrack device. Then, we record the two-point covariance of spatially correlated field fluctuations across a current-carrying wire. Our multiplex framework establishes a method to investigate a variety of spatio-temporal correlations, including phase transitions and electronic noise, with nanoscale resolution., Comment: 7 pages, 4 figures

Magnetic skyrmions are chiral spin textures which have attracted intense research for their fundamentally novel physics and potential applications as spintronic information carriers. The stability which makes them so potentially useful is a result of their underlying non-trivial topology. While skyrmions were originally predicted and observed in crystalline materials lacking inversion symmetry, some of the most promising host systems for skyrmions are multilayer thin films, where skyrmions have been stabilized at ambient conditions, which is critical for their use in real world devices. The skyrmions found in multilayer thin films have additional three-dimensional structure, with their domain wall helicities twisting through the thickness of the film to create a hybrid skyrmion composed of a Bloch-type core with N\'eel-type caps of opposite chiralities at the surfaces. In this work, we show that this three-dimensional variation creates additional knotted topological structure, providing an explanation for their exceptional stability in ambient conditions. We show that hybrid skyrmions can be described as half-integer Hopfions, and that their field lines have the knotted structure of the Hopf fibration. Furthermore, we show that the topological charge of partially twisted hybrid skyrmions can be related to the domain wall helicity at the surfaces, providing a straightforward way to connect experimental measurements to underlying topology., Comment: 8 pages, 6 figures, 1 table

The effect of short chain grafting on the liquid crystalline (LC) ordering of nano-crystals is investigated using molecular dynamics simulations of a coarse-grained grafted nano-rod model. Monodisperse nano-rods, with aspect ratios typical of cellulose nano-crystals (CNCs) are grafted randomly with oligomers at different grafting densities. LC ordering depends non-trivially on grafting density as the effective nano-rod shape and softness is modified. Ungrafted rods exhibit Nematic and tilted Smectic-C phases. At 25\% grafting, the addition of a few side chains entirely suppresses Smectic order and instead a persistent Nematic phase is favoured. Intermediary grafting, around 50\%, results in a Nematic and the reappearance of tilted Smectic-F phases. Heavier grafting facilitates direct transitions to either Smectic-I with extreme tilt (75\%) or an un-tilted Smectic-B (100\%). Such behaviour falls outside of current hard or soft-rod descriptions of phase-transitions in rod-like LC systems and points to undiscovered LC behaviour in both shape-purified grafted/un-grafted CNCs., Comment: 17 pages, 11 figures

The size and complexity of software applications is increasing at an accelerating pace. Source code repositories (along with their dependencies) require vast amounts of labor to keep them tested, maintained, and up to date. As the discipline now begins to also incorporate automatically generated programs, automation in testing and tuning is required to keep up with the pace - let alone reduce the present level of complexity. While machine learning has been used to understand and generate code in various contexts, machine learning models themselves are trained almost exclusively on static code without inputs, traces, or other execution time information. This lack of training data limits the ability of these models to understand real-world problems in software. In this work we show that inputs, like code, can be generated automatically at scale. Our generated inputs are stateful, and appear to faithfully reproduce the arbitrary data structures and system calls required to rerun a program function. By building our tool within the compiler, it both can be applied to arbitrary programming languages and architectures and can leverage static analysis and transformations for improved performance. Our approach is able to produce valid inputs, including initial memory states, for 90% of the ComPile dataset modules we explored, for a total of 21.4 million executable functions. Further, we find that a single generated input results in an average block coverage of 37%, whereas guided generation of five inputs improves it to 45%.

Foundation models such as GPT-4 are fine-tuned to avoid unsafe or otherwise problematic behavior, such as helping to commit crimes or producing racist text. One approach to fine-tuning, called reinforcement learning from human feedback, learns from humans' expressed preferences over multiple outputs. Another approach is constitutional AI, in which the input from humans is a list of high-level principles. But how do we deal with potentially diverging input from humans? How can we aggregate the input into consistent data about "collective" preferences or otherwise use it to make collective choices about model behavior? In this paper, we argue that the field of social choice is well positioned to address these questions, and we discuss ways forward for this agenda, drawing on discussions in a recent workshop on Social Choice for AI Ethics and Safety held in Berkeley, CA, USA in December 2023., Comment: 15 pages, 4 figures

Silicone is frequently used as a model system to investigate and tune wetting on soft materials. Silicone is biocompatible and shows excellent thermal, chemical, and UV stability. Moreover, the mechanical properties of the surface can be easily varied by several orders of magnitude in a controlled manner. Polydimethylsiloxane (PDMS) is a popular choice for coating applications such as lubrication, self-cleaning, and drag reduction, facilitated by low surface energy. Aiming to understand the underlying interactions and forces, motivated numerous and detailed investigations of the static and dynamic wetting behavior of drops on PDMS-based surfaces. Here, we recognize the three most prevalent PDMS surface variants, namely liquid-infused (SLIPS/LIS), elastomeric, and liquid-like (SOCAL) surfaces. To understand, optimize, and tune the wetting properties of these PDMS surfaces, we review and compare their similarities and differences by discussing (i) the chemical and molecular structure, and (ii) the static and dynamic wetting behavior. We also provide (iii) an overview of methods and techniques to characterize PDMS-based surfaces and their wetting behavior. The static and dynamic wetting ridge is given particular attention, as it dominates energy dissipation, adhesion, and friction of sliding drops and influences the durability of the surfaces. We also discuss special features such as cloaking and wetting-induced phase separation. Key challenges and opportunities of these three surface variants are outlined.

Many biological studies involve inferring the evolutionary history of a sample of individuals from a large population and interpreting the reconstructed tree. Such an ascertained tree typically represents only a small part of a comprehensive population tree and is distorted by survivorship and sampling biases. Inferring evolutionary parameters from ascertained trees requires modeling both the underlying population dynamics and the ascertainment process. A crucial component of this phylodynamic modeling involves tree simulation, which is used to benchmark probabilistic inference methods. To simulate an ascertained tree, one must first simulate the full population tree and then prune unobserved lineages. Consequently, the computational cost is determined not by the size of the final simulated tree, but by the size of the population tree in which it is embedded. In most biological scenarios, simulations of the entire population are prohibitively expensive due to computational demands placed on lineages without sampled descendants. Here, we address this challenge by proving that, for any partially ascertained process from a general multi-type birth-death-mutation-sampling model, there exists an equivalent process with complete sampling and no death, a property which we leverage to develop a highly efficient algorithm for simulating trees. Our algorithm scales linearly with the size of the final simulated tree and is independent of the population size, enabling simulations from extremely large populations beyond the reach of current methods but essential for various biological applications. We anticipate that this unprecedented speedup will significantly advance the development of novel inference methods that require extensive training data., Comment: 37 pages, 7 figures

Hallucinations and delusions are often grouped together within the positive symptoms of psychosis. However, recent evidence suggests they may be driven by distinct computational and neural mechanisms. Examining the time course of their emergence may provide insights into the relationship between these underlying mechanisms. Participants from the second (N = 719) and third (N = 699) iterations of the North American Prodrome Longitudinal Study (NAPLS 2 and 3) were assessed for timing of CHR-P-level delusion and hallucination onset. Pre-onset symptom patterns in first-episode psychosis patients (FEP) from the Prevention and Early Intervention Program for Psychosis (PEPP-Montreal; N = 694) were also assessed. Symptom onset was determined at baseline assessment and the evolution of symptom patterns examined over 24 months. In all three samples, participants were more likely to report the onset of delusion-spectrum symptoms prior to hallucination-spectrum symptoms (odds ratios (OR): NAPLS 2 = 4.09; NAPLS 3 = 4.14; PEPP, Z = 7.01, P < 0.001) and to present with only delusions compared to only hallucinations (OR: NAPLS 2 = 5.6; NAPLS 3 = 11.11; PEPP = 42.75). Re-emergence of delusions after remission was also more common than re-emergence of hallucinations (Ps < 0.05), and hallucinations more often resolved first (Ps < 0.001). In both CHR-P samples, ratings of delusional ideation fell with the onset of hallucinations (P = 0.007). Delusions tend to emerge before hallucinations and may play a role in their development. Further work should examine the relationship between the mechanisms driving these symptoms and its utility for diagnosis and treatment.

In fair division of a connected graph $G = (V, E)$, each of $n$ agents receives a share of $G$'s vertex set $V$. These shares partition $V$, with each share required to induce a connected subgraph. Agents use their own valuation functions to determine the non-negative numerical values of the shares, which determine whether the allocation is fair in some specified sense. We introduce forbidden substructures called graph cutsets, which block divisions that are fair in the EF1 (envy-free up to one item) sense by cutting the graph into "too many pieces". Two parameters - gap and valence - determine blocked values of $n$. If $G$ guarantees connected EF1 allocations for $n$ agents with valuations that are CA (common and additive), then $G$ contains no elementary cutset of gap $k \ge 2$ and valence in the interval $\[n - k + 1, n - 1\]$. If $G$ guarantees connected EF1 allocations for $n$ agents with valuations in the broader CM (common and monotone) class, then $G$ contains no cutset of gap $k \ge 2$ and valence in the interval $\[n - k + 1, n - 1\]$. These results rule out the existence of connected EF1 allocations in a variety of situations. For some graphs $G$ we can, with help from some new positive results, pin down $G$'s spectrum - the list of exactly which values of $n$ do/do not guarantee connected EF1 allocations. Examples suggest a conjectured common spectral pattern for all graphs. Further, we show that it is NP-hard to determine whether a graph admits a cutset. We also provide an example of a (non-traceable) graph on eight vertices that has no cutsets of gap $\ge 2$ at all, yet fails to guarantee connected EF1 allocations for three agents with CA preferences., Comment: Extended abstract accepted at AAMAS'24

Quantum computing promises transformational gains for solving some problems, but little to none for others. For anyone hoping to use quantum computers now or in the future, it is important to know which problems will benefit. In this paper, we introduce a framework for answering this question both intuitively and quantitatively. The underlying structure of the framework is a race between quantum and classical computers, where their relative strengths determine when each wins. While classical computers operate faster, quantum computers can sometimes run more efficient algorithms. Whether the speed advantage or the algorithmic advantage dominates determines whether a problem will benefit from quantum computing or not. Our analysis reveals that many problems, particularly those of small to moderate size that can be important for typical businesses, will not benefit from quantum computing. Conversely, larger problems or those with particularly big algorithmic gains will benefit from near-term quantum computing. Since very large algorithmic gains are rare in practice and theorized to be rare even in principle, our analysis suggests that the benefits from quantum computing will flow either to users of these rare cases, or practitioners processing very large data.

In many situations, it would be useful to know not just the best phylogenetic tree for a given data set, but the collection of high-quality trees. This goal is typically addressed using Bayesian techniques, however, current Bayesian methods do not scale to large data sets. Furthermore, for large data sets with relatively low signal one cannot even store every good tree individually, especially when the trees are required to be bifurcating. In this paper, we develop a novel object called the "history subpartition directed acyclic graph" (or "history sDAG" for short) that compactly represents an ensemble of trees with labels (e.g. ancestral sequences) mapped onto the internal nodes. The history sDAG can be built efficiently and can also be efficiently trimmed to only represent maximally parsimonious trees. We show that the history sDAG allows us to find many additional equally parsimonious trees, extending combinatorially beyond the ensemble used to construct it. We argue that this object could be useful as the "skeleton" of a more complete uncertainty quantification., Comment: To appear in JMB