IA Scholar Query: Reversible Cellular Automata: From Fundamental Classical Results to Recent Developments.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgWed, 31 Aug 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Information Leakage Games: Exploring Information as a Utility Function
https://scholar.archive.org/work/v524jzty5bdfhgy6fa3xy3pjam
A common goal in the areas of secure information flow and privacy is to build effective defenses against unwanted leakage of information. To this end, one must be able to reason about potential attacks and their interplay with possible defenses. In this article, we propose a game-theoretic framework to formalize strategies of attacker and defender in the context of information leakage, and provide a basis for developing optimal defense methods. A novelty of our games is that their utility is given by information leakage, which in some cases may behave in a non-linear way. This causes a significant deviation from classic game theory, in which utility functions are linear with respect to players' strategies. Hence, a key contribution of this work is the establishment of the foundations of information leakage games. We consider two kinds of games, depending on the notion of leakage considered. The first kind, the QIF -games , is tailored for the theory of quantitative information flow. The second one, the DP -games , corresponds to differential privacy.Mário S. Alvim, Konstantinos Chatzikokolakis, Yusuke Kawamoto, Catuscia Palamidessiwork_v524jzty5bdfhgy6fa3xy3pjamWed, 31 Aug 2022 00:00:00 GMTDecomposing neural circuit function into information processing primitives
https://scholar.archive.org/work/jee5zuehivex7pfp6lks74wagq
ABSTRACTCognitive functions arise from the coordinated activity of neural populations distributed over large-scale brain networks. However, it is challenging to understand and measure how specific aspects of neural dynamics translate into operations of information processing, and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms–such as self-sustained or propagating activity and nonlinear summation of inputs–do not directly give rise to high-level functions. Nevertheless, they already implement simple transformations of the information carried by neural activity.Here, we propose that distinct neural circuit functions, such as stimulus representation, working memory, or selective attention stem from different combinations and types of low-level manipulations of information, or information processing primitives. To test this hypothesis, we combine approaches from information theory with computational simulations of canonical neural circuits involving one or more interacting brain regions that emulate well-defined cognitive functions. More specifically, we track the dynamics of information emergent from dynamic patterns of neural activity, using suitable quantitative metrics to detect where and when information is actively buffered ("active information storage"), transferred ("information transfer") or non-linearly merged ("information modification"), as possible modes of low-level processing. We find that neuronal subsets maintaining representations in working memory or performing attention-related gain modulation are signaled by their boosted involvement in operations of active information storage or information modification, respectively.Thus, information dynamics metrics, beyond detecting which network units participate in cognitive processing, also promise to specify how and when they do it, i.e., through which type of primitive computation, a capability that may be exploited for the parsing of actual experimental recordings.Nicole Voges, Johannes Hausmann, Andrea Brovelli, Demian Battagliawork_jee5zuehivex7pfp6lks74wagqThu, 04 Aug 2022 00:00:00 GMTLIPIcs, Volume 238, DNA 28, Complete Volume
https://scholar.archive.org/work/627o3xn4vbbgpdox5dwolgcuny
LIPIcs, Volume 238, DNA 28, Complete VolumeThomas E. Ouldridge, Shelley F. J. Wickhamwork_627o3xn4vbbgpdox5dwolgcunyThu, 04 Aug 2022 00:00:00 GMTUniversal anomalous fluctuations in charged single-file systems
https://scholar.archive.org/work/cimec6uoj5dobdna3cbyc6xami
Conventional classification of dynamical phenomena is based on universal hydrodynamic relaxation characterized by algebraic dynamical exponents and asymptotic scaling of the dynamical structure factor. This work uncovers a novel type of dynamical universality reflected in statistical properties of macroscopic fluctuating observables such as the transmitted charge. By considering a general class of one-dimensional single-file systems (meaning that particle crossings are prohibited) of interacting hardcore charged particles, we demonstrate that stringent dynamical constraints give rise to universal anomalous statistics of cumulative charge currents manifested both on the timescale characteristic of typical fluctuations and also in the rate function describing rare events. By computing the full counting statistics of net transferred charge between two extended subsystems, we establish a number of unorthodox dynamical properties in an analytic fashion. Most prominently, typical fluctuations in equilibrium are governed by a universal distribution that markedly deviates from the expected Gaussian statistics, whereas large fluctuations are described by an exotic large-deviation rate function featuring an exceptional triple critical point. Far from equilibrium, competition between dynamical phases leads to dynamical phase transitions of first and second order. Despite dynamical criticality, we find the large-deviation rate function of the joint particle-charge transfer obeys the fluctuation relation. Curiously, the univariate charge-current rate function experiences a spontaneous breaking of fluctuation symmetry upon varying the particle and charge densities in a nonequilibrium initial state. The rich phenomenology of the outlined dynamical universality is exemplified on an exactly solvable classical cellular automaton of charged hardcore particles.Žiga Krajnik, Johannes Schmidt, Vincent Pasquier, Tomaž Prosen, Enej Ilievskiwork_cimec6uoj5dobdna3cbyc6xamiTue, 02 Aug 2022 00:00:00 GMTRandom Quantum Circuits
https://scholar.archive.org/work/57bh7e2hhbawvbw6cngsbn555e
Quantum circuits -- built from local unitary gates and local measurements -- are a new playground for quantum many-body physics and a tractable setting to explore universal collective phenomena far-from-equilibrium. These models have shed light on longstanding questions about thermalization and chaos, and on the underlying universal dynamics of quantum information and entanglement. In addition, such models generate new sets of questions and give rise to phenomena with no traditional analog, such as new dynamical phases in quantum systems that are monitored by an external observer. Quantum circuit dynamics is also topical in view of experimental progress in building digital quantum simulators that allow control of precisely these ingredients. Randomness in the circuit elements allows a high level of theoretical control, with a key theme being mappings between real-time quantum dynamics and effective classical lattice models or dynamical processes. Many of the universal phenomena that can be identified in this tractable setting apply to much wider classes of more structured many-body dynamics.Matthew P. A. Fisher, Vedika Khemani, Adam Nahum, Sagar Vijaywork_57bh7e2hhbawvbw6cngsbn555eThu, 28 Jul 2022 00:00:00 GMTA Review of Mathematical and Computational Methods in Cancer Dynamics
https://scholar.archive.org/work/etafy2omf5dupmlgn7tdh23pfy
Cancers are complex adaptive diseases regulated by the nonlinear feedback systems between genetic instabilities, environmental signals, cellular protein flows, and gene regulatory networks. Understanding the cybernetics of cancer requires the integration of information dynamics across multidimensional spatiotemporal scales, including genetic, transcriptional, metabolic, proteomic, epigenetic, and multi-cellular networks. However, the time-series analysis of these complex networks remains vastly absent in cancer research. With longitudinal screening and time-series analysis of cellular dynamics, universally observed causal patterns pertaining to dynamical systems, may self-organize in the signaling or gene expression state-space of cancer triggering processes. A class of these patterns, strange attractors, may be mathematical biomarkers of cancer progression. The emergence of intracellular chaos and chaotic cell population dynamics remains a new paradigm in systems medicine. As such, chaotic and complex dynamics are discussed as mathematical hallmarks of cancer cell fate dynamics herein. Given the assumption that time-resolved single-cell datasets are made available, a survey of interdisciplinary tools and algorithms from complexity theory, are hereby reviewed to investigate critical phenomena and chaotic dynamics in cancer ecosystems. To conclude, the perspective cultivates an intuition for computational systems oncology in terms of nonlinear dynamics, information theory, inverse problems, and complexity. We highlight the limitations we see in the area of statistical machine learning but the opportunity at combining it with the symbolic computational power offered by the mathematical tools explored.Abicumaran Uthamacumaran, Hector Zenilwork_etafy2omf5dupmlgn7tdh23pfyMon, 25 Jul 2022 00:00:00 GMTUsing (1 + 1)D Quantum Cellular Automata for Exploring Collective Effects in Large Scale Quantum Neural Networks
https://scholar.archive.org/work/2mlttsljkbd4hmjcufs3uwvn3a
Central to the field of quantum machine learning is the design of quantum perceptrons and neural network architectures. A key question in this regard is the impact of quantum effects on the way in which such models process information. Here, we approach this question by establishing a connection between (1+1)D quantum cellular automata, which implement a discrete nonequilibrium quantum many-body dynamics through the successive application of local quantum gates, and recurrent quantum neural networks, which process information by feeding it through perceptrons interconnecting adjacent layers. This relation allows the processing of information in quantum neural networks to be studied in terms of the properties of their equivalent cellular automaton dynamics. We exploit this by constructing a class of quantum gates (perceptrons) that allow for the introduction of quantum effects, such as those associated with a coherent Hamiltonian evolution, and establish a rigorous link to continuous-time Lindblad dynamics. We further analyse the universal properties of a specific quantum cellular automaton, and identify a change of critical behavior when quantum effects are varied, demonstrating that they can indeed affect the collective dynamical behavior underlying the processing of information in large-scale neural networks.Edward Gillman, Federico Carollo, Igor Lesanovskywork_2mlttsljkbd4hmjcufs3uwvn3aSun, 24 Jul 2022 00:00:00 GMTQuantum machine learning for chemistry and physics
https://scholar.archive.org/work/ts35ancqmvay5fhyqya6degva4
Machine learning (ML) has emerged as a formidable force for identifying hidden but pertinent patterns within a given data set with the objective of subsequent generation of automated predictive behavior. In recent years, it is safe to conclude that ML and its close cousin, deep learning (DL), have ushered in unprecedented developments in all areas of physical sciences, especially chemistry. Not only classical variants of ML, even those trainable on near-term quantum hardwares have been developed with promising outcomes. Such algorithms have revolutionized materials design and performance of photovoltaics, electronic structure calculations of ground and excited states of correlated matter, computation of force-fields and potential energy surfaces informing chemical reaction dynamics, reactivity inspired rational strategies of drug designing and even classification of phases of matter with accurate identification of emergent criticality. In this review we shall explicate a subset of such topics and delineate the contributions made by both classical and quantum computing enhanced machine learning algorithms over the past few years. We shall not only present a brief overview of the well-known techniques but also highlight their learning strategies using statistical physical insight. The objective of the review is not only to foster exposition of the aforesaid techniques but also to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.Manas Sajjan, Junxu Li, Raja Selvarajan, Shree Hari Sureshbabu, Sumit Suresh Kale, Rishabh Gupta, Vinit Singh, Sabre Kaiswork_ts35ancqmvay5fhyqya6degva4Mon, 18 Jul 2022 00:00:00 GMTMicromechanical study of recrystallization in aluminium alloys
https://scholar.archive.org/work/dixdpx367zf47abhsx2rckwlja
An in-depth understanding of the recrystallization (RX) process in alloys to achieve an optimised microstructure is critical to manufacturing metal parts with superior properties. However, the prediction of the RX process under various processing conditions is still in its early research stage and becoming an urgent demand for both the manufacturing industry and scientific research. Regarding this long-standing microstructure formation problem, deformation bands (DBs) formed in metals are known to contribute to the unsolved problems in the RX process by giving rise to the microstructural heterogeneities. Previous experimental transmission electron microscope (TEM) work has identified the type of DBs at the microscopic scale, showing the importance of understanding the slip activation for DBs. However, the exact mechanisms of how DBs are formed and lead the RX during the subsequent annealing still remain unclear. Firstly, to clarify the mechanism of DBs formation, single crystal, multi-crystal, polycrystalline pure aluminium (Al) and commercial Al alloys, as well as their corresponding crystal plasticity finite element (CPFE) models, were deformed to explore the effect of grain orientation, strain level and neighbouring grains on the formation of DBs regarding the orientations formed in DBs and the distribution of DBs. It is demonstrated that slip band intersection of primary and secondary slip can constrain the lattice sliding but facilitate the lattice rotation for the formation of DBs including the boundary of DBs and its orientation. It is found that the impact of the above factors on the formation of DBs is caused by the slip field of primary slip. The activation of a sufficient amount of primary slip in grains would be crucial to the formation of a large amount of distinct DBs. Next, to explore the effects of DBs on the grain nucleation and the subsequent grain growth, specimens were annealed to observe the RX process. Regarding the recrystallized (RXed) texture, it is noticeable that the orientations of nuc [...]Qinmeng Luan, Jun Jiang, Jianguo Lin, Imperial College Londonwork_dixdpx367zf47abhsx2rckwljaTue, 12 Jul 2022 00:00:00 GMTA computational study of the high-pressure high-temperature liquid phase sintering of polycrystalline diamond
https://scholar.archive.org/work/aqkrvtqqfvb6vkfn4fmlenrsgm
In light of mounting experimental evidence, the mechanism behind polycrystalline diamond (PCD) sintering has come under scrutiny. In this body of work, it was hypothesised that sintering requires the presence of non-diamond carbon in the reaction volume to achieve the level of sintering and the microstructures observed in experiment. Based around this hypothesis, there were two objectives. The primary objective was to use theories and simulation to investigate and challenge the currently accepted mechanisms behind the liquid phase sintering of PCD, and the secondary objective was to develop a usable computational model capable of predicting microstructure evolution. A variety of computational methods ranging from the nano- to the meso-scale were used to investigate the sintering process. At the smallest investigated scale, molecular dynamics was used to perform nano-scale high-pressure high-temperatrue (HPHT) di usion and sintering experiments. The factors in uencing carbon di usion and sintering on the molecular level were explored and the learning was applied to the meso-scale model. Two meso-scale methods were investigated. Due to the limitations encountered with the Monte Carlo approach, a new phase eld model was developed with the novel incorporation of elastic stresses in the inter-granular contact regions. It was found that the externally applied pressure resulted in densi cation rates correlating well with a newly developed theory. Upon validation with experimental work, it was found that elastic energy alone could not account for the discrepancy in diamond density between simulated and experimental microstructures. The subsequent implementation of a super-saturation algorithm to simulate the presence of non-diamond carbon helped bridge the gap. Qualitative and quantitative image analysis of experimental and simulated microstructures suggested that the hypothesis remains valid and thus challenges the long-standing theory that PCD sinters via ordinary liquid phase sintering. This seminal work has shown tha [...]Branislav Dzepina, Daniele Dini, Daniel Balint, James Ewen, Engineering And Physical Sciences Research Councilwork_aqkrvtqqfvb6vkfn4fmlenrsgmFri, 08 Jul 2022 00:00:00 GMTComplex simulation of entrepreneurial opportunity emergence: The case of Nigerian entrepreneurship
https://scholar.archive.org/work/muck2ztl25gwjnhyda3vvom3oi
The current policy and public debate on the overall topic of entrepreneurship pays little attention to a more specific and developing property of entrepreneurship such as the emergence of an entrepreneur. This study examines the emergence of entrepreneurs through their behavioural interaction amongst one another and their environment. As a research methodology, agent based modelling was adopted for this research over system dynamics because, individual interactions (behavioural reactions/responses) between each entity and the immediate universe (environment) is the crucial unit for determination of the research results. In order to correctly capture this concept, interactions in the forms of personality trait attributes, social networking, technological acquaintance, environment (niche) and previous know-how (prior knowledge) were considered as the behaviours of study using agent based model. To achieve this, these entities were broken into their sub attributes in Bayesian probability model to provide statistical data for the behavioural analysis and a NetLogo simulation tool was used to reproduce a visual behavioural pattern of the agents (entrepreneurs) within an artifitial universe. It is this process of using simulation to study entrepreneurial behaviour that is called 'Simuprenuership' within this study. The emergent patterns and behaviours implies that, entrepreneurship is an emergent process that takes form during and within the interactions between the agents and the environment. This suggest that variations in the smallest attributes of the agents could completely result in an unpredictable emergence. Hence, discernment process is not suuficient to explain entrepreneurship as in the literature. therefore, there is a necessity to move from cognition, illumination or insightful way of entrepreneurial thinking, to a more holistic and evolutionary system of thinking, this study adopted an emergent system of thinking. This infers that entrepreneurial ideas and opportunities emerge from a mindset that is [...]Izuchukwu Benedict Okoyework_muck2ztl25gwjnhyda3vvom3oiThu, 07 Jul 2022 00:00:00 GMTNATHENA - D2.1 State Of Art
https://scholar.archive.org/work/tnihvfex7vbonkwgjgk2h5imgq
This deliverable constitutes the state of the art on heat exchangers, their principles of operation, their manufacturing by additive methods, the simulation techniques to characterize their performances as well as the means of testing to validate these performances. Patents and norms related to these subjects are also presented.NATHENAwork_tnihvfex7vbonkwgjgk2h5imgqTue, 05 Jul 2022 00:00:00 GMTA Color Image Encryption Algorithm Based on Double Fractional Order Chaotic Neural Network and Convolution Operation
https://scholar.archive.org/work/l3jekylcvrebjcjsgcgbnya3sm
A color image encryption algorithm based on double fractional order chaotic neural network (CNN), interlaced dynamic deoxyribonucleic acid (DNA) encoding and decoding, zigzag confusion, bidirectional bit-level diffusion and convolution operation is proposed. Firstly, two fractional order chaotic neural networks (CNNs) are proposed to explore the application of fractional order CNN in image encryption. Meanwhile, spectral entropy (SE) algorithm shows that the sequence generated by the proposed fractional order CNNs has better randomness. Secondly, a DNA encoding and decoding encryption scheme with evolutionary characteristics is adopted. In addition, convolution operation is utilized to improve the key sensitivity. Finally, simulation results and security analysis illustrate that the proposed algorithm has high security performance and can withstand classical cryptanalysis attacks.Nanming Li, Shucui Xie, Jianzhong Zhangwork_l3jekylcvrebjcjsgcgbnya3smTue, 05 Jul 2022 00:00:00 GMTA Self-Controlled and Self-Healing Model of Bacterial Cells
https://scholar.archive.org/work/bovucdx26jgylnclayipiqhyiy
A new kind of self-assembly model, morphogenetic (M) systems, assembles spatial units into larger structures through local interactions of simpler components and enables discovery of new principles for cellular membrane assembly, development, and its interface function. The model is based on interactions among three kinds of constitutive objects such as tiles and protein-like elements in discrete time and continuous 3D space. It was motivated by achieving a balance between three conflicting goals: biological, physical-chemical, and computational realism. A recent example is a unified model of morphogenesis of a single biological cell, its membrane and cytoskeleton formation, and finally, its self-reproduction. Here, a family of dynamic M systems (Mbac) is described with similar characteristics, modeling the process of bacterial cell formation and division that exhibits bacterial behaviors of living cells at the macro-level (including cell growth that is self-controlled and sensitive to the presence/absence of nutrients transported through membranes), as well as self-healing properties. Remarkably, it consists of only 20 or so developmental rules. Furthermore, since the model exhibits membrane formation and septic mitosis, it affords more rigorous definitions of concepts such as injury and self-healing that enable quantitative analyses of these kinds of properties. Mbac shows that self-assembly and interactions of living organisms with their environments and membrane interfaces are critical for self-healing, and that these properties can be defined and quantified more rigorously and precisely, despite their complexity.Max Garzon, Petr Sosik, Jan Drastík, Omar Skalliwork_bovucdx26jgylnclayipiqhyiyThu, 30 Jun 2022 00:00:00 GMTAn Innovative Neutrosophic Combinatorial Approach Towards the Fusion and Edge Detection of MR Brain Medical Images
https://scholar.archive.org/work/5uspmkemgzdxhh6nnjg5wur6p4
This research proposes the idea of implementing an innovative mechanism to detect the edges in distinct MR brain medical images based on the aspect of Neutrosophic sets (NSs). NS-based entropy is one of the emerging tools to procure a neutrosophic image from the crisp image. Followed by the aforementioned procedure, fusion has been done for the neutrosophic image in order to acquire fused neutrosophic images (FNI) then the FNI's are again regenerated to form a fused crisp image. Later, the Bell-Shaped (BS) function and the Sobel operator works on the FNI to obtain a combination of three subsets. After determining the neutrosophic subsets, various entropies such as Norm, Threshold, Sure, and Shannon act on it to provide their threshold values, and the computed subsets along with thresholds are incorporated to produce a new binarized image. Subsequently, morphological operations were implemented to construct the image edges. The resultant images with different entropies are compared by using the performance measurement factors. Based on the measurement factors, the proposed Norm entropy image edge detection innovations have proven to be an efficient tool with reference to other entropies. In addition, the Norm entropy-based proposed method was compared with some of the other existing edge detection methods inclusive of Sobel, Chan, Tian, and Wu. FOM and PSNR factors have been applied to estimate the results of edge detection achieved through five distinct methods. The findings confirmed that the implementation of the proposed object edge detection mechanism is much stronger compared to other existing methods.Premalatha Rathnasabapathy, Dhanalakshmi Palanisamiwork_5uspmkemgzdxhh6nnjg5wur6p4Wed, 29 Jun 2022 00:00:00 GMTWhich arithmetic operations can be performed in constant time in the RAM model with addition?
https://scholar.archive.org/work/d4vm7l2bybez5lre4poemf6vjy
In the literature of algorithms, the specific computation model is often not explicit as it is assumed that the model of computation is the RAM (Random Access Machine) model. However, the RAM model itself is ill-founded in the literature, with disparate definitions and no unified results. The ambition of this paper is to found the RAM model from scratch by exhibiting a RAM model that enjoys interesting algorithmic properties and the robustness of its complexity classes, notably LIN, the class of linear-time computable problems, or the now well-known CONST-DELAY-lin class of enumeration problems computable with constant delay after linear-time preprocessing, The computation model that we define is a RAM whose contents and addresses of registers are O(N), where N is the size (number of registers) of the input, and where the time cost of each instruction is 1 (unit cost criterion). The key to the foundation of our RAM model will be to prove that even if addition is the only primitive operation, such a RAM can still compute all the basic arithmetic operations in constant time after a linear-time preprocessing. Moreover, while the RAM handles only O(N) integers in each register, we will show that our RAM can handle O(N^d) integers, for any fixed d, by storing them on O(d) registers and we will have surprising algorithms that computes many operations acting on these "polynomial" integers – addition, subtraction, multiplication, division, exponential, integer logarithm, integer square root (or c-th root, for any integer c), bitwise logical operations, and, more generally, any operation computable in linear time on a cellular automaton – in constant time after a linear-time preprocessing.Étienne Grandjean, Louis Jachietwork_d4vm7l2bybez5lre4poemf6vjyTue, 28 Jun 2022 00:00:00 GMTSharp threshold for the FA-2f kinetically constrained model
https://scholar.archive.org/work/kdtgztej7fdebpjkqm3pq4as3a
The Fredrickson-Andersen 2-spin facilitated model on ℤ^d (FA-2f) is a paradigmatic interacting particle system with kinetic constraints (KCM) featuring dynamical facilitation, an important mechanism in condensed matter physics. In FA-2f a site may change its state only if at least two of its nearest neighbours are empty. Although the process is reversible w.r.t. a product Bernoulli measure, it is not attractive and features degenerate jump rates and anomalous divergence of characteristic time scales as the density q of empty sites tends to 0. A natural random variable encoding the above features is τ_0, the first time at which the origin becomes empty for the stationary process. Our main result is the sharp threshold τ_0=exp(d·λ(d,2)+o(1)/q^1/(d-1)) w.h.p. with λ(d,2) the sharp threshold constant for 2-neighbour bootstrap percolation on ℤ^d, the monotone deterministic automaton counterpart of FA-2f. This is the first sharp result for a critical KCM and it compares with Holroyd's 2003 result on bootstrap percolation and its subsequent improvements. It also settles various controversies accumulated in the physics literature over the last four decades. Furthermore, our novel techniques enable completing the recent ambitious program on the universality phenomenon for critical KCM and establishing sharp thresholds for other two-dimensional KCM.Ivailo Hartarsky, Fabio Martinelli, Cristina Toninelliwork_kdtgztej7fdebpjkqm3pq4as3aTue, 28 Jun 2022 00:00:00 GMTZMK Zeitschrift für Medien- und Kulturforschung. Focus Producing Places
https://scholar.archive.org/work/k6pikcnpifgrhnvaz7iluioftu
and object-but, as a consequence, also the distinction of object and operation becomes a relative and transient one, very much like the one between place and space, place and non-place. It is quite clear that these two types of place-generating operations are interrelated in their turn. The operation of differentiation is not possible without decoupling of the formerly coherent and without a certain momentum of touch and tactility, as the operation of coupling requires distinct entities or operations, which are subject to the operation of coupling. The example of recent positioning and navigation technologies illustrates the interrelation of the two types very clearly. The question remains, though, as to how we could ascribe a place to such entities and operations, which do not interrelate, positively or negatively, and which do not touch each other, cross each other, affect each other, or attach to each other. Are there places that are being produced not via coupling, be it firm or loose, nor via distinction of identity and difference, but via an otherness, which doesn't even allow for comparison nor for contact? Are there places of and for objects and operations that do not share anything with other entities, which are unable to inhabit the same place? And, if so, would such a place still fall under the concept of producing places in the double meaning mentioned initially? Wouldn't it rather, instead of being productive, have no impact and no effect whatsoever, and wouldn't it insofar figure as a mere and pure place residing in itself, a sheer place of being? And if so, wouldn't we have to concede that such a place cannot be produced, but just arrive? The question is very relevant philosophically, but it is also of notable practical relevance as far as media cultures and places of media and in media are concerned. Different media, serving as tools of distinction and coupling, produce different places in diverse manners-but do they cooperate in placing operations, do they share places at all, do they even have places? In McLuhan, we find the metaphor of two galaxies (i.e. media cultures and media universes) crossing each other on their way through outer space without interference, without touching, without even contacting or affecting each other in the slightest way. Does this take place? Do they, and does their non-encounter, inhabit one place at all? How could we conceive of such a place? Do non-interference and disentanglement, and do refraining and abstaining from productivity and operativity have a sitting room?(:Unkn) Unknown, Mediarep.Org, Lorenz Engell, Bernhard Siegertwork_k6pikcnpifgrhnvaz7iluioftuTue, 21 Jun 2022 00:00:00 GMTA stochastic hierarchical model for low grade glioma evolution
https://scholar.archive.org/work/z6i54a2kgfhh7asfft72yjx4ru
A stochastic hierarchical model for the evolution of low grade gliomas is proposed. Starting with the description of cell motion using piecewise diffusion Markov processes (PDifMPs) at the cellular level, we derive an equation for the density of the transition probability of this Markov process using the generalised Fokker-Planck equation. Then a macroscopic model is derived via parabolic limit and Hilbert expansions in the moment equations. After setting up the model, we perform several numerical tests to study the role of the local characteristics and the extended generator of the PDifMP in the process of tumour progression. The main aim focuses on understanding how the variations of the jump rate function of this process at the microscopic scale and the diffusion coefficient at the macroscopic scale are related to the diffusive behaviour of the glioma cells and to the onset of malignancy, i.e., the transition from low-grade to high-grade gliomas.Evelyn Buckwar, Martina Conte, Amira Meddahwork_z6i54a2kgfhh7asfft72yjx4ruMon, 20 Jun 2022 00:00:00 GMTDiscrete time crystals beyond the MBL paradigm
https://scholar.archive.org/work/ucwhtk4wjfeyldq6n7ogk5mp74
Discrete time crystals (DTCs) are systems that, subject to a periodic forcing, respond with a period larger than that of the drive. Breaking the discrete time-translational symmetry of the underlying equations, DTCs maintain an infinite autocorrelation time, avoid ergodicity, and realize a novel nonequilibrium phase of matter. In most previous proposals of DTCs, this peculiar behavior relied on the presence of (strong) disorder. Indeed, according to the celebrated mechanism of many-body localization (MBL), disorder can avert the otherwise generally expected 'heat death' to a featureless infinite temperature state in a driven system. And yet, it has recently been discovered that alternative mechanisms do exist through which thermalization can be avoided or significantly slowed down, such as confinement from long-range interactions, so-called quantum scars, or dynamical localization. This raises a number of natural questions: To what extent is MBL needed to observe nontrivial dynamics? What classifies a dynamics as nontrivial? What mechanisms can stabilize what phenomenologies of time crystallinity? Are DTCs possible in a classical setting and in which sense? In this dissertation, we address these questions proposing and investigating various remarkable notions of DTCs beyond the MBL-paradigm. Our journey across the zoology of time crystallinity embraces both the quantum and the classical realms, and discusses DTCs in their quasi, higher-order, fractional, and classical-stochastic flavours. All these exotic phenomena are encompassed by a unifying framework that we develop. Following this common thread, we justify and emphasise the key elements that, we think, should characterise DTCs, namely their many-body nature and the concept of universality in the nonequilibrium setting. Bringing together problems from different fields such as condensed matter physics, statistical physics, dynamical system theory, and epidemiology, we unveil striking ramifications of these remarkable dynamical phases of matter, advance our cur [...]Andrea Pizzi, Apollo-University Of Cambridge Repository, Andreas Nunnenkamp, Austen Lamacraftwork_ucwhtk4wjfeyldq6n7ogk5mp74Fri, 17 Jun 2022 00:00:00 GMT