Landscape Theory Research Articles

Large landscape of 4d superconformal field theories from small gauge theories

We systematically explore the space of renormalization group flows of four-dimensional N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 1 superconformal field theories (SCFTs) triggered by relevant deformations, as well as by coupling to free chiral multiplets with relevant operators. In this way, we classify all possible fixed point SCFTs that can be obtained from certain rank 1 and 2 supersymmetric gauge theories with small amount of matter multiplets, identifying 7,346 inequivalent fixed points which pass a series of non-trivial consistency checks. This set of fixed points exhibits interesting statistical behaviors, including a narrow distribution of central charges (a, c), a correlation between the number of relevant operators and the ratio a/c, and trends in the lightest operator dimension versus a/c. The ratio a/c of this set is distributed between 0.7228 and 1.2100, where the upper bound is larger than that of previously known interacting SCFTs. Moreover, we find a plethora of highly non-perturbative phenomena, such as (super)symmetry enhancements, operator decoupling, non-commuting renormalization group flows, and dualities. We especially identify amongst these fixed points a new SCFT that has smaller central charges ac=63320006832000\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\left(a,c\\right)=\\left(\\frac{633}{2000},\\frac{683}{2000}\\right) $$\\end{document} than that of the deformed minimal Argyres-Douglas theory, as well as novel Lagrangian duals for certain N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 1 deformed Argyres-Douglas theories. We provide a website https://qft.kaist.ac.kr/landscape to navigate through our set of fixed points.

Analysis of Multi-Dimensional Layers in Historic Districts Based on Theory of the Historic Urban Landscape: Taking Shenyang Fangcheng as an Example

The accelerated process of urbanisation in China is resulting in a decline in and threat to the historic landscape of historic districts. This study is based on the theory of historic urban landscapes and employs a multi-dimensional layers research framework for historic districts. It adopts a single case study and a research method that combines quantitative and qualitative methods. The stratification elements of Fangcheng in Shenyang are identified and summarised, the process of stratification is analysed, and the stratification patterns and laws are summarised through the acquisition and collection of multivariate data. The findings of this study indicate that the stratification elements of the Fangcheng Historic District have undergone five distinct phases of stratification evolution. The resulting stratification pattern can be summarised as follows: newborn, preserve, override, juxtaposition and decession. The spatial elements are layered in the following pattern: The historic landscape can be conceptualised as comprising four layers: (1) the layering of the historic landscape with large public buildings as the anchor point; (2) the layering of the historic landscape with the spatial pattern as the skeleton; (3) the layering of the historic landscape with the iconic buildings as the nodes; and (4) the layering of the historic landscape with the correlative elements as the substrate. The law of value element layering primarily reflects the principles of concentration, diversity and adaptation. In light of the urban historic landscape theory, the reconstruction and restoration strategies, integration of old and new and adaptive conservation of historic landscapes are proposed to offer novel insights and guidance for the conservation of the historic landscape in the Fangcheng Historic District.

Geometric Landscape Annealing as an Optimization Principle Underlying the Coherent Ising Machine

Given the fundamental importance of combinatorial optimization across many diverse domains, there has been widespread interest in the development of unconventional physical computing architectures that can deliver better solutions with lower resource costs. However, a theoretical understanding of their performance remains elusive. We develop such understanding for the case of the coherent Ising machine (CIM), a network of optical parametric oscillators that can be applied to any quadratic unconstrained binary optimization problem. We focus on how the CIM finds low-energy solutions of the Sherrington-Kirkpatrick spin glass. As the laser gain of this system is annealed, the CIM interpolates between gradient descent on coupled soft spins to descent on coupled binary spins. By combining the Kac-Rice formula, the replica method, and supersymmetry breaking, we develop a detailed understanding of the evolving geometry of the high-dimensional energy landscape of the CIM as the laser gain increases, finding several phase transitions in the landscape, from flat to rough to rigid. Additionally, we develop a novel cavity method that provides a geometric interpretation of supersymmetry breaking in terms of the reactivity of a rough landscape to specific external perturbations. Our energy landscape theory successfully matches numerical experiments, provides geometric insights into the principles of CIM operation, and yields optimal annealing schedules. Published by the American Physical Society 2024

Serial and palimpsest: landscape in Vietnamese cinema

This essay is a study of how landscapes are represented and what they signify in the work of three cutting-edge Vietnamese filmmakers: Siu Pham (1946-); Nguyễn Trinh Thi (1973-)’ and Phan Đăng Di (1976-). Although diverse in their methods and foci, their works share a thematic and politico-aesthetic concern for the Vietnamese landscape as an interface between historical trauma and expressive resistance. Through close readings of these experimental films, I distil a theory from their respective radical practices. Conversely, because of the significant interest in Japanese landscape theory (fūkeiron) among both Vietnamese filmmakers and scholars, I briefly review the major Japanese advocates of fūkeiron, not to ‘apply’ it to the Vietnamese case, but to expose fūkeiron’s internal inconsistencies and thereby further illuminate what the Vietnamese filmmakers have accomplished.

Unraveling the Complexity of Parkinson's Disease: Insights into Pathogenesis and Precision Interventions.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss, leading to motor and non-motor symptoms. Early detection before symptom onset is crucial but challenging. This study presents a framework integrating circuit modeling, non-equilibrium dynamics, and optimization to understand PD pathogenesis and enable precision interventions. Neuronal firing patterns, particularly oscillatory activity, play a critical role in PD pathology. The basal ganglia network, specifically the subthalamic nucleus-external globus pallidus (STN-GPe) circuitry, exhibits abnormal activity associated with motor dysfunction. The framework leverages the non-equilibrium landscape and flux theory to identify key connections generating pathological activity, providing insights into disease progression and potential intervention points. The intricate STN-GPe interplay is highlighted, shedding light on compensatory mechanisms within this circuitry may initially counteract changes but later contribute to pathological alterations as disease progresses. The framework addresses the need for comprehensive evaluation methods to assess intervention outcomes. Cross-correlations between state variables provide superior early warning signals compared to traditional indicators relying on critical slowing down. By elucidating compensatory mechanisms and circuit dynamics, the framework contributes to improved management, early detection, risk assessment, and potential prevention/delay of PD development. This pioneering research paves the way for precision medicine in neurodegenerativedisorders.

Analysis of Linguistic Landscape: Holy Child College of Education Campus

The aim of the paper is to analyze the linguistic landscape of Holy Child College of Education. Drawing of data from first-hand fieldwork, this paper explores the display of language and multimodal on signage on the College campus. In all, it was found out that English language is prevalent on all types of surfaces (walls, doorpost, buildings, cenotaph, billboard) to aid in the identity of occupants as well as associate identity to the properties of the institution. There were also a few private shops which have names on them. The study employs qualitative and quantitative content analysis of a data of about 74 signages from the College. It looked into issues such as top-down, bottom-up approach as well as symbolic and informational function. It also examined if there are instances of the use of only one language or more than a language on a signage. The theory that supported this investigation was Linguistic Landscape Theory foundered by Landry and Bourhis (1997). This theory has it that the study of linguistic landscapes refers to the visibility and salience of languages on public and commercial signs in a given territory or region. Landry and Bourhis argue that the linguistic landscape of an area can serve as an indicator of the relative power and status of different linguistic communities within that area. This theory suggests that the languages displayed in public spaces can reflect broader social, cultural, and political dynamics, such as the dominance of one language over another, and it can affect the perception of language status and identity among community members.

A Taxonomy for Set-Theoretic Potentialism

Abstract Set-theoretic potentialism is one of the most lively trends in the philosophy of mathematics. Modal accounts of sets have been developed in two different ways. The first, initiated by Charles Parsons, focuses on sets as objects. The second, dating back to Hilary Putnam and Geoffrey Hellman, investigates set-theoretic structures. The paper identifies two strands of open issues, technical and conceptual, to clarify these two different, yet often conflated, views and categorize the potentialist approaches that have emerged in the contemporary debate. The final outcome is a taxonomy that should help researchers navigate the rich landscape of modal set theories.

Langevin Dynamics Study on the Driven Translocation of Polymer Chains with a Hairpin Structure.

The hairpin structure is a common and fundamental secondary structure in macromolecules. In this work, the process of the translocation of a model polymer chain with a hairpin structure is studied using Langevin dynamics simulations. The simulation results show that the dynamics of hairpin polymer translocation through a nanopore are influenced by the hairpin structure. Hairpin polymers can be classified into three categories, namely, linear-like, unsteady hairpin, and steady hairpin, according to the interaction with the stem structure. The translocation behavior of linear-like polymers is similar to that of a linear polymer chain. The time taken for the translocation of unsteady hairpin polymers is longer than that for a linear chain because it takes a long time to unfold the hairpin structure, and this time increases with stem interaction and decreases with the driving force. The translocation of steady hairpin polymers is distinct, especially under a weak driving force; the difficulty of unfolding the hairpin structure leads to a low translocation probability and a short translocation time. The translocation behavior of hairpin polymers can be explained by the theory of the free-energy landscape.

Application of artificial intelligence sensor and visual image technology in the analysis of hydrophilic space landscape characteristics

With the continuous development of intelligent sensor technology and artificial intelligence, the application of artificial intelligence feature recognition at the level of intelligent sensor information acquisition to urban landscape analysis has become a current research trend and hot spot, but also brings us new research directions and challenges. In this paper, the multi-sensor collaborative filtering algorithm is optimized, and a method based on evidence theory is proposed to deal with the fuzzy and unclear information generated in the process of multi-sensor collaboration. Then, the analysis and recognition of multi-sensor fusion information using AI technology are analyzed in detail. This paper discusses the problems in multi-sensor information fusion and related solutions. Combined with the key nodes of 3D object AI feature recognition, multi-sensor collaborative Dempster Shafer evidence theory and 3D convolutional neural network waterfront space landscape feature recognition sub-model are constructed, and the waterfront space landscape recognition analysis model is tested and analyzed. The results show that the multi-sensor information collection Kalman filtering fusion algorithm effectively realizes the recognition of landscape feature information and the filtering of irrelevant interference information combined with an artificial intelligence algorithm to build a landscape feature recognition model. Among all kinds of landscape recognition, the recognition effect of beach inflow is the best, and the recognition accuracy, recall, and F1 value are all above 95. However, the identification effect of hydrophilic plank roads and underwater breakwater is relatively poor. The recognition accuracy of the hydrophilic platform is the lowest at 83.16 % among the eight landscape types, and the recall rate of underwater breakwater is the lowest at 79.96 % among the eight landscape types. In general, the multi-sensor Kalman filtering algorithm information fusion model designed in this paper has higher recognition accuracy and better classification performance for the collection and classification of the entire landscape dataset. The work of this paper provides a new idea and direction for the design and application of waterfront landscape identification and analysis systems based on intelligent sensors and artificial intelligence technology and lays a certain foundation for the intelligent design of urban waterfront landscapes.

Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics

Recent advances in single-cell sequencing technology have revolutionized our ability to acquire whole transcriptome data. However, uncovering the underlying transcriptional drivers and nonequilibrium driving forces of cell function directly from these data remains challenging. We address this by learning cell state vector fields from discrete single-cell RNA velocity to quantify the single-cell global nonequilibrium driving forces as landscape and flux. From single-cell data, we quantified the Waddington landscape, showing that optimal paths for differentiation and reprogramming deviate from the naively expected landscape gradient paths and may not pass through landscape saddles at finite fluctuations, challenging conventional transition state estimation of kinetic rate for cell fate decisions due to the presence of the flux. A key insight from our study is that stem/progenitor cells necessitate greater energy dissipation for rapid cell cycles and self-renewal, maintaining pluripotency. We predict optimal developmental pathways and elucidate the nucleation mechanism of cell fate decisions, with transition states as nucleation sites and pioneer genes as nucleation seeds. The concept of loop flux quantifies the contributions of each cycle flux to cell state transitions, facilitating the understanding of cell dynamics and thermodynamic cost, and providing insights into optimizing biological functions. We also infer cell-cell interactions and cell-type-specific gene regulatory networks, encompassing feedback mechanisms and interaction intensities, predicting genetic perturbation effects on cell fate decisions from single-cell omics data. Essentially, our methodology validates the landscape and flux theory, along with its associated quantifications, offering a framework for exploring the physical principles underlying cellular differentiation and reprogramming and broader biological processes through high-throughput single-cell sequencing experiments.

Exploring the truth and beauty of theory landscapes with machine learning

Theoretical physicists describe nature by i) building a theory model and ii) determining the model parameters. The latter step involves the dual aspect of both fitting to the existing experimental data and satisfying abstract criteria like beauty, naturalness, etc. We use the Yukawa quark sector as a toy example to demonstrate how both of those tasks can be accomplished with machine learning techniques. We propose loss functions whose minimization results in true models that are also beautiful as measured by three different criteria — uniformity, sparsity, or symmetry.

Il paesaggio tra estetica e geografia: un confronto tra Joachim Ritter e Augustin Berque

In this essay I compare the landscape philosophy proposed by Joachim Ritter in his famous essay Landschaft (1963) and the landscape theory elaborated by French geographer and orientalist Augustin Berque, focussing primarily on the volume La pensée paysagère (2008). The perspective from which the comparison is advanced concerns the problem of aesthetic appraisal and experience and its relation to the geographical reality to which landscape refers. The confrontation between Ritter and Berque brings the tradition of philosophical aesthetics into confrontation with that of human geography, as part of a path aimed progressively at overcoming the separation of the aesthetic (of which the aestheticized concept of landscape typical of the tradition of Western art history would be an expression) from the other spheres of meaning with which space is invested, from the ecological- environmental to the ethical-political.

Paesaggi dell’interstizio. Per un Illuminismo post-coloniale

The landscape of tomorrow can be imagined today starting from events currently emerging from what Michel Foucault called “the interstice”. According to him, the interstice is the gray area that lies between the fundamental choices and exclusion’s strategies that every culture accomplishes to affirm its identity. Some of these interstices have been brought to light precisely in the context of landscape theories, notably by Gilles Clément. Others, however, are now emerging in political fields where landscape is not the object of a theory, but a reference for struggle and contestation. Thus, starting from a visit to the 2024 Venice Art Biennale, this essay outlines the intertwining between some interstitial movements of today - post-colonial studies, migrations, queer identities - and their impact on a possible landscape to come: not identitarian but fluid, inclusive and open towards a new idea of cosmopolitism.

Finiteness theorems and counting conjectures for the flux landscape

In this paper, we explore the string theory landscape obtained from type IIB and F-theory flux compactifications. We first give a comprehensive introduction to a number of mathematical finiteness theorems, indicate how they have been obtained, and clarify their implications for the structure of the locus of flux vacua. Subsequently, in order to address finer details of the locus of flux vacua, we propose three mathematically precise conjectures on the expected number of connected components, geometric complexity, and dimensionality of the vacuum locus. With the recent breakthroughs on the tameness of Hodge theory, we believe that they are attainable to rigorous mathematical tools and can be successfully addressed in the near future. The remainder of the paper is concerned with more technical aspects of the finiteness theorems. In particular, we investigate their local implications and explain how infinite tails of disconnected vacua approaching the boundaries of the moduli space are forbidden. To make this precise, we present new results on asymptotic expansions of Hodge inner products near arbitrary boundaries of the complex structure moduli space.

Uncertainty measures: A critical survey

Classical probability is not the only mathematical theory of uncertainty, or the most general. Many authors have argued that probability theory is ill-equipped to model the ‘epistemic’, reducible uncertainty about the process generating the data. To address this, many alternative theories of uncertainty have been formulated. In this paper, we highlight how uncertainty theories can be seen as forming clusters characterised by a shared rationale, are connected to each other in an intricate but interesting way, and can be ranked according to their degree of generality. Our objective is to propose a structured, critical summary of the research landscape in uncertainty theory, and discuss its potential for wider adoption in artificial intelligence.

Translation of Outdoor Signs in Nusa Dua Beach Area

This research was conducted to have a closer look at Linguistic Landscape in one of coastal areas of Bali, Indonesia. It specifically conducted with the aim of analyzing the translation of outdoor signs, in the form of notice or information boards. This research also examines translation shifts occur within those outdoor signs. This research is a qualitative descriptive study. The method applied for this research is observation method and include image capture and also note-taking technique. The problem formulated in this research applies Linguistic Landscape theory by Landry and Bourhis and also Translation Shift theory by Catford and Simatupang. The result of the research found that the form of translation of the outdoor signs in Nusa Dua beach area can be seen in the form of Notice board, cemented sign, or colored banner which has function to give information or warning to the people who visit the area. It also can be found that the shift occurs in the translation of the outdoor signs consists of structure and meaning shift.

Unveiling and challenging the identity, formation, and evolution of Transformation Theory

In this contribution, we explore established and emerging facets that contribute to shaping the theoretical landscape of transformation theory. Throughout our discussion, we contemplate the multifaceted nature of transformative learning, acknowledging its positive evolution with diverse perspectives that have enriched the field. Despite this progress, we argue that challenges persist, prompting the recognition of transformative learning theory as an ongoing, dynamic paradigm capable of organically responding to the contemporary challenges of adult learning and education. Our discourse advocates for a deeper exploration of the theory's potential for profound change, emphasizing the imperative to move beyond its dominant cognitive dimension.

Neural network learning and Quantum Gravity

The landscape of low-energy effective field theories stemming from string theory is too vast for a systematic exploration. However, the meadows of the string landscape may be fertile ground for the application of machine learning techniques. Employing neural network learning may allow for inferring novel, undiscovered properties that consistent theories in the landscape should possess, or checking conjectural statements about alleged characteristics thereof. The aim of this work is to describe to what extent the string landscape can be explored with neural network-based learning. Our analysis is motivated by recent studies that show that the string landscape is characterized by finiteness properties, emerging from its underlying tame, o-minimal structures. Indeed, employing these results, we illustrate that any low-energy effective theory of string theory is endowed with certain statistical learnability properties. Consequently, several local learning problems therein formulated, including interpolations and multi-class classification problems, can be concretely addressed with machine learning, delivering results with sufficiently high accuracy.

Optical pulse-induced ultrafast antiferrodistortive transition in SrTiO3

The ultrafast dynamics of the antiferrodistortive phase transition in perovskite SrTiO3 is monitored via time-domain Brillouin scattering. Using femtosecond optical pulses, we initiate a thermally driven tetragonal-to-cubic structural transformation and detect the crystal phase through changes in the frequency of Brillouin oscillations (BO) induced by propagating acoustic phonons. Coupling the measured BO frequency with a spatiotemporal heat diffusion model, we demonstrate that, for a sample kept in the tetragonal phase, deposition of sufficient thermal energy induces a rapid transformation of the heat-affected region to the cubic phase. The initial phase change is followed by a slower reverse cubic-to-tetragonal phase transformation occurring on a timescale of hundreds of picoseconds. We attribute this ultrafast phase transformation in the perovskite to a structural resemblance between atomic displacements of the R-point soft optic mode of the cubic phase and the tetragonal phase, both characterized by anti-phase rotation of oxygen octahedra. The structural relaxation time exhibits a strong temperature dependence consistent with the prediction of the equation of motion describing collective oxygen octahedra rotation based on the energy landscape of the phenomenological Landau theory of phase transitions. Evidence of such a fast structural transition in perovskites can open up new avenues in information processing and energy storage sectors.

Mapping the Landscape of the Manosphere within the Analytical Framework of Wave and War

In this paper, I aim to adopt two conceptual frameworks as a latticework of perception to read the complex and multifaceted situations in contemporary Korean society. First, I will explore whether the metaphor of feminism as a fluid wave is a suitable analysis for understanding feminism as a complex of various bodies, forces, energies, materials, desires, and thoughts, and how the anti-feminism backlash counters the fluidity of the fourth wave of feminism with the territoriality and solidity of macho tribalism. Second, I will examine whether the spread of material-discursive practices based on misogyny within the male-centric online ecosystem (manosphere) in the backlash against feminism can be read as a gender war. Considering that war is a network of human and non-human assemblages and an entanglement of material and symbolic elements, I will analyze the technologies of the gender war based on misogyny and female antagonism through Michel Foucault’s war model. Through this analysis, I aim to map the current landscape of feminist movements and theories in Korea confronted with the frontlines of misogyny.