scholarly journals The Maximum Entropy of a Metric Space

2021 ◽  
Author(s):  
Tom Leinster ◽  
Emily Roff
Keyword(s):  
Probability Measure ◽  
Maximum Entropy ◽  
Metric Space ◽  
Large Scale ◽  
Hausdorff Space ◽  
Geometric Information ◽  
Finite Case ◽  
Maximum Value ◽  
Maximizing Measure ◽  
Scale Limit

Abstract We define a one-parameter family of entropies, each assigning a real number to any probability measure on a compact metric space (or, more generally, a compact Hausdorff space with a notion of similarity between points). These generalize the Shannon and Rényi entropies of information theory. We prove that on any space X, there is a single probability measure maximizing all these entropies simultaneously. Moreover, all the entropies have the same maximum value: the maximum entropy of X. As X is scaled up, the maximum entropy grows, and its asymptotics determine geometric information about X, including the volume and dimension. And the large-scale limit of the maximizing measure itself provides an answer to the question: what is the canonical measure on a metric space? Primarily, we work not with entropy itself but its exponential, which in its finite form is already in use as a measure of biodiversity. Our main theorem was first proved in the finite case by Leinster and Meckes.

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

scholarly journals Geometrical properties of the space of idempotent probability measures

2021 ◽  
Vol 22 (2) ◽  
pp. 399
Author(s):  
Kholsaid Fayzullayevich Kholturayev
Keyword(s):  
Metric Space ◽  
Category Theory ◽  
Compact Hausdorff Space ◽  
Hausdorff Space ◽  
Probability Measures ◽  
Compact Metric Space ◽  
Geometrical Properties ◽  
Idempotent Mathematics

Although traditional and idempotent mathematics are "parallel'', by an application of the category theory we show that objects obtained the similar rules over traditional and idempotent mathematics must not be "parallel''. At first we establish for a compact metric space X the spaces P(X) of probability measures and I(X) idempotent probability measures are homeomorphic ("parallelism''). Then we construct an example which shows that the constructions P and I form distinguished functors from each other ("parallelism'' negation). Further for a compact Hausdorff space X we establish that the hereditary normality of I<sub>3</sub>(X)\ X implies the metrizability of X.

Study on space absorbing of multilayer MWCNTs/Fe3O4/NBR composites

2021 ◽  
pp. 2150112
Author(s):  
Song Xinhua ◽  
Zhou Haiyang ◽  
Zhao Tiejun ◽  
Li Xiaojie ◽  
Yan Honghao
Keyword(s):  
Reflection Loss ◽  
Free Space ◽  
Large Scale ◽  
Comsol Multiphysics ◽  
Maximum Value ◽  
The Matrix ◽  
Attenuation Loss ◽  
Stealth Materials ◽  
Free Space Method ◽  
Space Method

In order to meet the requirements of “wide, thin, strong and light” for military stealth materials, it is of great practical value to study the absorbing characteristics of multi-layer MWCNTs/Fe3O4/NBR absorbing materials in space. First, we use the large-scale software COMSOL Multiphysics to simulate the absorbing characteristics of the composite thin plate in space. Then the four-port network matrix is used to calculate the absorbing characteristics of the composite plate in space. Finally, the Free-Space method is used to measure the reflection attenuation loss, and the results of the three methods are compared and analyzed. The results show that when the frequency is 10 GHz, the reflection loss of multi-layer MWCNTs/Fe3O4/NBR reaches the maximum value of −27.91, −27.01 and −22.56 dB by COMOSL numerical simulation, four-port network the matrix and Free-Space experimental measurement. The results of the three methods show that the reflection loss is less than −10 dB in the frequency band of 6–14 GHz.

Nowhere Dense Subsets of Metric Spaces with Applications to Stone-Cech Compactifications

1972 ◽  
Vol 24 (4) ◽  
pp. 622-630 ◽  
Author(s):  
Jack R. Porter ◽  
R. Grant Woods
Keyword(s):  
Metric Space ◽  
Hausdorff Space ◽  
Metric Spaces ◽  
Dense Subset ◽  
Locally Compact ◽  
Completely Regular ◽  
Isolated Points ◽  
Remote Points ◽  
Topological Boundary ◽  
Regular Closed

Let X be a metric space. Assume either that X is locally compact or that X has no more than countably many isolated points. It is proved that if F is a nowhere dense subset of X, then it is regularly nowhere dense (in the sense of Katětov) and hence is contained in the topological boundary of some regular-closed subset of X. This result is used to obtain new properties of the remote points of the Stone-Čech compactification of a metric space without isolated points.Let βX denote the Stone-Čech compactification of the completely regular Hausdorff space X. Fine and Gillman [3] define a point p of βX to be remote if p is not in the βX-closure of a discrete subset of X.

scholarly journals Coarse quotients by group actions and the maximal Roe algebra

2019 ◽  
Vol 11 (04) ◽  
pp. 875-907
Author(s):  
Logan Higginbotham ◽  
Thomas Weighill
Keyword(s):  
Automorphism Group ◽  
Metric Space ◽  
Large Scale ◽  
Countable Group ◽  
Crossed Product ◽  
Property A ◽  
Bounded Geometry ◽  
Roe Algebra ◽  
Scale Spaces ◽  
The Ideal

For a finitely generated group [Formula: see text] acting on a metric space [Formula: see text], Roe defined the warped space [Formula: see text], which one can view as a kind of large scale quotient of [Formula: see text] by the action of [Formula: see text]. In this paper, we generalize this notion to the setting of actions of arbitrary groups on large scale spaces. We then restrict our attention to what we call coarsely discontinuous actions by coarse equivalences and show that for such actions the group [Formula: see text] can be recovered as an appropriately defined automorphism group [Formula: see text] when [Formula: see text] satisfies a large scale connectedness condition. We show that for a coarsely discontinuous action of a countable group [Formula: see text] on a discrete bounded geometry metric space [Formula: see text] there is a relation between the maximal Roe algebras of [Formula: see text] and [Formula: see text], namely that there is a ∗-isomorphism [Formula: see text], where [Formula: see text] is the ideal of compact operators. If [Formula: see text] has Property A and [Formula: see text] is amenable, then [Formula: see text] has Property A, and thus the maximal Roe algebra and full crossed product can be replaced by the usual Roe algebra and reduced crossed product respectively in the above equation.

scholarly journals On the existence of maximizing measures for irreducible countable Markov shifts: a dynamical proof

2013 ◽  
Vol 34 (4) ◽  
pp. 1103-1115 ◽  
Author(s):  
RODRIGO BISSACOT ◽  
RICARDO DOS SANTOS FREIRE
Keyword(s):  
Probability Measure ◽  
Bounded Variation ◽  
Finite Alphabet ◽  
Markov Shift ◽  
Positive Real ◽  
Shift Space ◽  
Markov Shifts ◽  
Maximizing Measure ◽  
Full Shift ◽  
Countable Markov Shifts

AbstractWe prove that if ${\Sigma }_{\mathbf{A} } ( \mathbb{N} )$ is an irreducible Markov shift space over $ \mathbb{N} $ and $f: {\Sigma }_{\mathbf{A} } ( \mathbb{N} )\rightarrow \mathbb{R} $ is coercive with bounded variation then there exists a maximizing probability measure for $f$, whose support lies on a Markov subshift over a finite alphabet. Furthermore, the support of any maximizing measure is contained in this same compact subshift. To the best of our knowledge, this is the first proof beyond the finitely primitive case in the general irreducible non-compact setting. It is also noteworthy that our technique works for the full shift over positive real sequences.

scholarly journals Joint Geosequential Preference and Distance Metric Factorization for Point-of-Interest Recommendation

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Chunyang Liu ◽  
Chao Liu ◽  
Haiqiang Xin ◽  
Jian Wang ◽  
Jiping Liu ◽  
...  
Keyword(s):  
Metric Space ◽  
Matrix Factorization ◽  
Euclidean Distance ◽  
Large Scale ◽  
Inner Product ◽  
Interaction Matrix ◽  
Distance Metric ◽  
Point Of Interest ◽  
Poi Recommendation ◽  
Real World Datasets

Point-of-interest (POI) recommendation is a valuable service to help users discover attractive locations in location-based social networks (LBSNs). It focuses on capturing users’ movement patterns and location preferences by using massive historical check-in data. In the past decade, matrix factorization has become a mature and widely used technology in POI recommendation. However, the inner product of latent vectors adopted in matrix factorization methods does not satisfy the triangle inequality property, which may limit the expressiveness and lead to suboptimal solutions. Besides, the extreme sparsity of check-in data makes it challenging to capture users’ movement preferences accurately. In this paper, we propose a joint geosequential preference and distance metric factorization framework, called GeoSeDMF, for POI recommendation. First, we introduce a distance metric factorization method that is capable of learning users’ personalized preferences from a position and distance perspective in the metric space. Specifically, we convert the user-POI interaction matrix into a distance matrix and factorize it into user and POI dense embeddings. Additionally, we measure users’ personalized preference for the POI by using the Euclidean distance metric instead of the inner product. Then, we model the users’ geospatial preference by applying a geographic weight coefficient and model the users’ sequential preference by using the Euclidean distance of continuous check-in locations. Moreover, a pointwise loss strategy and AdaGrad algorithm are adopted to optimize the positions and relationships of users and POIs in a metric space. Finally, experimental results on three large-scale real-world datasets demonstrate the effectiveness and superiority of the proposed method.

scholarly journals The Infinite limit of random permutations avoiding patterns of length three

2019 ◽  
Vol 29 (1) ◽  
pp. 137-152 ◽  
Author(s):  
Ross G. Pinsky
Keyword(s):  
Probability Measure ◽  
Metric Space ◽  
The Other ◽  
Random Permutations ◽  
Compact Metric Space ◽  
Sigma 1 ◽  
Limiting Behaviour ◽  
Random Probability

AbstractFor $$\tau \in {S_3}$$, let $$\mu _n^\tau $$ denote the uniformly random probability measure on the set of $$\tau $$-avoiding permutations in $${S_n}$$. Let $${\mathbb {N}^*} = {\mathbb {N}} \cup \{ \infty \} $$ with an appropriate metric and denote by $$S({\mathbb{N}},{\mathbb{N}^*})$$ the compact metric space consisting of functions $$\sigma {\rm{ = }}\{ {\sigma _i}\} _{i = 1}^\infty {\rm{ }}$$ from $$\mathbb {N}$$ to $${\mathbb {N}^ * }$$ which are injections when restricted to $${\sigma ^{ - 1}}(\mathbb {N})$$; that is, if $${\sigma _i}{\rm{ = }}{\sigma _j}$$, $$i \ne j$$, then $${\sigma _i} = \infty $$. Extending permutations $$\sigma \in {S_n}$$ by defining $${\sigma _j} = j$$, for $$j \gt n$$, we have $${S_n} \subset S({\mathbb{N}},{{\mathbb{N}}^*})$$. For each $$\tau \in {S_3}$$, we study the limiting behaviour of the measures $$\{ \mu _n^\tau \} _{n = 1}^\infty $$ on $$S({\mathbb{N}},{\mathbb{N}^*})$$. We obtain partial results for the permutation $$\tau = 321$$ and complete results for the other five permutations $$\tau \in {S_3}$$.

The Measure Spectrum of a Uniform Algebra and Subharmonicity

1982 ◽  
Vol 34 (3) ◽  
pp. 673-685
Author(s):  
Donna Kumagai
Keyword(s):  
Probability Measure ◽  
Maximal Ideal ◽  
Compact Hausdorff Space ◽  
Hausdorff Space ◽  
Uniform Algebra ◽  
Ideal Space ◽  
Representing Measure ◽  
Uniform Algebras ◽  
The Subject ◽  
Image Position

Let A be a uniform algebra on a compact Hausdorff space X. The spectrum, or the maximal ideal space, MA, of A is given byWe define the measure spectrum, SA, of A bySA is the set of all representing measures on X for all Φ ∈ MA. (A representing measure for Φ ∈ MA is a probability measure μ on X satisfyingThe concept of representing measure continues to be an effective tool in the study of uniform algebras. See for example [12, Chapters 2 and 3], [5, pp. 15-22] and [3]. Most of the known results on the subject of representing measures, however, concern measures associated with a single homomorphism.

Sign in / Sign up

Export Citation Format

Share Document