950 research outputs found
Classical and quantum algorithms for scaling problems
This thesis is concerned with scaling problems, which have a plethora of connections to different areas of mathematics, physics and computer science. Although many structural aspects of these problems are understood by now, we only know how to solve them efficiently in special cases.We give new algorithms for non-commutative scaling problems with complexity guarantees that match the prior state of the art. To this end, we extend the well-known (self-concordance based) interior-point method (IPM) framework to Riemannian manifolds, motivated by its success in the commutative setting. Moreover, the IPM framework does not obviously suffer from the same obstructions to efficiency as previous methods. It also yields the first high-precision algorithms for other natural geometric problems in non-positive curvature.For the (commutative) problems of matrix scaling and balancing, we show that quantum algorithms can outperform the (already very efficient) state-of-the-art classical algorithms. Their time complexity can be sublinear in the input size; in certain parameter regimes they are also optimal, whereas in others we show no quantum speedup over the classical methods is possible. Along the way, we provide improvements over the long-standing state of the art for searching for all marked elements in a list, and computing the sum of a list of numbers.We identify a new application in the context of tensor networks for quantum many-body physics. We define a computable canonical form for uniform projected entangled pair states (as the solution to a scaling problem), circumventing previously known undecidability results. We also show, by characterizing the invariant polynomials, that the canonical form is determined by evaluating the tensor network contractions on networks of bounded size
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This ďŹfth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ďŹelds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiďŹed Proportional ConďŹict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiďŹers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiďŹcation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiďŹcation.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiďŹcation, and hybrid techniques mixing deep learning with belief functions as well
Metadynamics Calculations of Magnetic Skyrmion Stabilities
Interfacial magnetic skyrmions are topological spin textures that have been proposed for use as information carriers in spintronic devices. Hence, it is vital that their creation, annihilation, and motion can be accurately controlled. Still, their thermal stability and interactions are not fully understood. Currently, athermal methods such as the geodesic nudged elastic band method (GNEBM) are used to quantify the skyrmion creation and annihilation energy barriers, including only the skyrmionâs internal energy. Furthermore, GNEBM is a low-temperature formalism that samples only saddle points along the energy landscape without providing any information about the transition from a skyrmionic to a ferromagnetic (FM) state and vice versa. Similarly, the skyrmion lifetimes are often estimated using energy barrier calculations and an arbitrary attempt frequency.
In contrast with GNEBM calculations, this thesis successfully demonstrated a novel use of metadynamics combined with atomic-scale magnetic simulations performed to reconstruct the free energy landscape (FEL) of macroscopic skyrmion observables. The reconstructed FELs are then used to quantify the skyrmions creation and annihilation energy barriers as a function of temperature, including both the effects of the internal energy and entropy, which is a major factor in skyrmion stability. The reconstructed FEL shows every possible transition path from a skyrmionic to a ferromagnetic path. Additionally, it is demonstrated that the skyrmionsâ attempt frequency in finite temperature can be estimated with metadynamics and not assumed. Nonetheless, with the use of metadynamics, the effects of magnetisation reversal in thin films with DMI are explored, revealing the generation of a chiral domain that expands to reverse the magnetisation. Finally, the procedures to explore the effect of lattice defects and exploration of all possible topological spin textures in any thin film heterostructure in finite temperatures with metadynamics are reported. Ultimately, the results of this thesis demonstrate new procedures which can be used to design and realise future skyrmionic devices by identifying possible spin textures and assessing their thermal stability and lifetimes accurately while fully accounting for temperature effects
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Sonic heritage: listening to the past
History is so often told through objects, images and photographs, but the potential of sounds to reveal place and space is often neglected. Our research project âSonic Palimpsestâ1 explores the potential of sound to evoke impressions and new understandings of the past, to embrace the sonic as a tool to understand what was, in a way that can complement and add to our predominant visual understandings. Our work includes the expansion of the Oral History archives held at Chatham Dockyard to include womenâs voices and experiences, and the creation of sonic works to engage the public with their heritage. Our research highlights the social and cultural value of oral history and field recordings in the transmission of knowledge to both researchers and the public. Together these recordings document how buildings and spaces within the dockyard were used and experienced by those who worked there. We can begin to understand the social and cultural roles of these buildings within the community, both past and present
Mating Burrows in the Fiddler Crab \u3cem\u3eLeptuca pugilator\u3c/em\u3e: How a Key Resource is Contested, Constructed, and Shared
The Atlantic sand fiddler crab, Leptuca pugilator, is found on sandy, vegetated beach across a large portion of the United Statesâ Atlantic and Gulf of Mexico coasts and is iconic in regions where dense populations of the species occur for its charismatic courtship, competitive, and foraging behaviors. The social dynamics of the species are complex. Reproductively active males maintain mating territories in the dangerous heat of the intertidal zone, away from their food source at the waterâs edge, where they inhabit specialized mating burrows. These mating burrows are essential to successful female reproductive success, and when it is time to mate, females will move to the high intertidal to find a burrow-owning male to mate with. Males attract females with a species-specific waving display using their sexually dimorphic major claw to signal their availability. Following attraction, a female may approach a courting male and, provided the maleâs burrow is of adequate quality, the two will mate within. The female will then stay below ground in the safety of the terminal chamber of the burrow throughout the oviposition and incubation process until the time comes to release her larvae. The necessity of burrow ownership in mating for males creates a high demand for territory, and males interact with one another, sometime fighting, as each mating burrow is pass down from one owner to the next. In the following pages, I address several unanswered questions concerning the nature of L. pugilator social dynamics and behavior surrounding their most important resource: the mating burrow. In Chapter II, I attempt to discern what factors differentiate territory-owning males from others who do not or cannot own territory. Chapter III is an investigation of mating burrow structure and how it changes across time and space. In Chapter IV, I address the construction of new mating burrows which is a topic that has been left largely uninvestigated at the time of this writing. Finally, Chapter V attempts to unveil the social dynamics within burrow through paternity analysis of cohabitating males and females
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Specificity of the innate immune responses to different classes of non-tuberculous mycobacteria
Mycobacterium avium is the most common nontuberculous mycobacterium (NTM) species causing infectious disease. Here, we characterized a M. avium infection model in zebrafish larvae, and compared it to M. marinum infection, a model of tuberculosis. M. avium bacteria are efficiently phagocytosed and frequently induce granuloma-like structures in zebrafish larvae. Although macrophages can respond to both mycobacterial infections, their migration speed is faster in infections caused by M. marinum. Tlr2 is conservatively involved in most aspects of the defense against both mycobacterial infections. However, Tlr2 has a function in the migration speed of macrophages and neutrophils to infection sites with M. marinum that is not observed with M. avium. Using RNAseq analysis, we found a distinct transcriptome response in cytokine-cytokine receptor interaction for M. avium and M. marinum infection. In addition, we found differences in gene expression in metabolic pathways, phagosome formation, matrix remodeling, and apoptosis in response to these mycobacterial infections. In conclusion, we characterized a new M. avium infection model in zebrafish that can be further used in studying pathological mechanisms for NTM-caused diseases
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Drivers and Mechanisms of Historical Sahel Precipitation Variability
The semiarid region between the North African Savanna and Sahara Desert, known as the Sahel, experienced dramatic multidecadal precipitation variability in the 20th century that was unparalleled in the rest of the world, including devastating droughts and famine in the early 1970s and 80s. Accurate predictions of this regionâs hydroclimate future are essential to avoid future disasters of this kind, yet simulations from state of the art general circulation models (GCMs) do a poor job of simulating past Sahel rainfall variability, and donât even agree on whether future precipitation will increase or decrease under global warming. Furthermore, climate scientists are still not in agreement about whether anthropogenic emissions played an important role relative to natural variability in dictating past Sahel rainfall change.
Because the climate system is complex and coupled, it is difficult to determine which processes should be considered causal drivers of circulation changes and which should be considered part of the climate response, and therefore many theories for monsoon rainfall variability coexist in the literature. It is difficult to evaluate these competing theories because observational studies generally cannot be interpreted causally, but simulated experiments may not represent the dynamics of the real world. The Coupled Model Intercomparison Project (CMIP) provides a wealth of data in which GCMs maintained at research institutions worldwide perform similar experiments, allowing the researcher to reach conclusions that are robust to differences in parameterization between GCMs. The scientific community has been using a wide range of statistical techniques to analyze this data, and each has notable limitations. This dissertation explores two statistical techniques for leveraging CMIP to explore the drivers and mechanisms of historical Sahel rainfall variability: analysis of ensemble-mean responses to prescribed variables, and causal inference.
In âChapter 1, we give an overview of the climatology and variability of Sahel rainfall and present relevant physical theory.
In âChapter 2, we examine the roles of various types of anthropogenic forcing in observations and coupled simulations, using a 3-tiered multi-model mean (MMM) to extract robust climate signals from CMIP phase 5 (CMIP5). We examine â20th centuryâ historical and single-forcing simulationsâwhich separate the influence of anthropogenic aerosols, greenhouse gases (GHG), and natural radiative forcing on global coupled ocean-atmosphere system, and were specifically designed for attribution studiesâas well as pre-Industrial control simulations, which only contain unforced internal climate variability, to investigate the drivers of simulated Sahel precipitation variability. The comparison of single-forcing and historical simulations highlights the importance of anthropogenic and volcanic aerosols over GHG in generating forced Sahel rainfall variability that reinforces the observed pattern, with anthropogenic aerosols alone responsible for the low-frequency component of simulated variability. However, the forced MMM only accounts for a small fraction of observed variance. A residual consistency test shows that simulated internal variability cannot explain the residual observed multidecadal variability, and points to model deficiency in simulating multidecadal variability in the forced response, internal variability, or both.
In âChapter 3, we investigate the causes for discrepancies in low-frequency Sahel precipitation variability between these ensembles and for model deficiency in reproducing observations. In the most recent version of CMIP â phase 6 of the Coupled Model Intercomparison Project (CMIP6) â the differences between observed and simulated variability are amplified rather than reduced: CMIP6 still grossly underestimates the magnitude of low-frequency variability in Sahel rainfall, but unlike CMIP5, historical mean precipitation in CMIP6 does not even correlate with observed multi-decadal variability. We continue to use a MMM to extract robust climate signals from simulations, but now additionally include sea surface temperature (SST) as a mediating variable in order to test the proposed physical processes. This partitions all influences on Sahel precipitation variability into five components: (1) teleconnections to SST; (2) atmospheric and (3) oceanic variability internal to the climate system; (4) the SST response to external radiative forcing; and (5) the âfastâ (not mediated by SST) precipitation response to forcing.
Though the coupled simulations perform quite poorly, in a vast improvement from previous ensembles, the CMIP6 atmosphere-only ensemble is able to reproduce the full magnitude of observed low-frequency Sahel precipitation variance when observed SST is prescribed. The high performance is due entirely to the atmospheric response to observed global SST â the fast response to forcing has a relatively small impact on Sahel rainfall, and only lowers the performance of the ensemble when it is included. Using the previously-established North Atlantic Relative Index (NARI) to approximate the role of global SST, we estimate that the strength of simulated teleconnections is consistent with observations. Applying the lessons of the atmosphere-only ensemble to coupled settings, we infer that both coupled CMIP ensembles fail to explain low-frequency historical Sahel rainfall variability mostly because they cannot explain the observed combination of forced and internal variability in SST. Though the fast response is small relative to the simulated response to observed SST variability, it is influential relative to simulated SST variability, and differences between CMIP5 and CMIP6 in the simulation of Sahel precipitation and its correlation with observations can be traced to differences in the simulated fast response to forcing or the role of other unexamined SST patterns.
In this chapter, we use NARI to approximate the role of global SST because it is considered by some to be the best single index for estimating teleconnections to the Sahel. However, we show that NARI is only able to explain half of the high-performing simulated low-frequency Sahel precipitation variability in the atmospheric simulations with prescribed global SST. Statistical techniques commonly applied in the literature cannot distinguish between correlation and causality, so we cannot analyze the response of Sahel rainfall to global SST in more depth without atmospheric CMIP simulations targeted at every ocean basin of interest or a new method.
In âChapter 4, we turn to a novel technique called causal inference to qualify the notion that NARI can adequately represent the role of global SST in determining Sahel rainfall. We apply a causal discovery algorithm to CMIP6 pre-Industrial control simulations to determine which ocean basins influence Sahel rainfall in individual GCMs. Though we find that state of the art causal discovery algorithms for time series still struggle with data that isnât generated specifically for algorithm evaluation, we robustly find that NARI does not mediate the full effect of global SST variability on Sahel rainfall in any of the climate simulations. This chapter lays the foundation for future work to fully-characterize the dependence of Sahel precipitation on individual ocean basins using the non-targeted simulations already available in CMIP â an approach which can be validated by comparing the composite results to the interventional historical simulations that are available. Furthermore, we hope this chapter will guide algorithm improvement efforts that are needed to increase the performance and usefulness of time series causal discovery algorithms on climate data
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