scholarly journals Essential dimension of representations of algebras

2020 ◽  
Vol 95 (4) ◽  
pp. 661-702
Author(s):  
Federico Scavia
2021 ◽  
Vol 224 (2) ◽  
pp. S200-S201
Author(s):  
Eran Bornstein ◽  
Yael Eliner ◽  
Moti Gulersen ◽  
Amos Grunebaum ◽  
Erez Lenchner ◽  
...  

2018 ◽  
Vol 62 (1) ◽  
pp. 291-304
Author(s):  
Dave Benson ◽  
Zinovy Reichstein

AbstractWe examine situations, where representations of a finite-dimensionalF-algebraAdefined over a separable extension fieldK/F, have a unique minimal field of definition. Here the base fieldFis assumed to be a field of dimension ≼1. In particular,Fcould be a finite field ork(t) ork((t)), wherekis algebraically closed. We show that a unique minimal field of definition exists if (a)K/Fis an algebraic extension or (b)Ais of finite representation type. Moreover, in these situations the minimal field of definition is a finite extension ofF. This is not the case ifAis of infinite representation type orFfails to be of dimension ≼1. As a consequence, we compute the essential dimension of the functor of representations of a finite group, generalizing a theorem of Karpenko, Pevtsova and the second author.


2011 ◽  
Vol 118 (2, Part 1) ◽  
pp. 357 ◽  
Author(s):  
Nicholas S. Fogelson ◽  
Stuart Fischbein

2016 ◽  
Vol 28 (6) ◽  
pp. 1072-1100 ◽  
Author(s):  
Kun Zhan ◽  
Jicai Teng ◽  
Jinhui Shi ◽  
Qiaoqiao Li ◽  
Mingying Wang

Inspired by gamma-band oscillations and other neurobiological discoveries, neural networks research shifts the emphasis toward temporal coding, which uses explicit times at which spikes occur as an essential dimension in neural representations. We present a feature-linking model (FLM) that uses the timing of spikes to encode information. The first spiking time of FLM is applied to image enhancement, and the processing mechanisms are consistent with the human visual system. The enhancement algorithm achieves boosting the details while preserving the information of the input image. Experiments are conducted to demonstrate the effectiveness of the proposed method. Results show that the proposed method is effective.


Author(s):  
Indranil Biswas ◽  
Ajneet Dhillon ◽  
Nicole Lemire

AbstractWe find upper bounds on the essential dimension of the moduli stack of parabolic vector bundles over a curve. When there is no parabolic structure, we improve the known upper bound on the essential dimension of the usual moduli stack. Our calculations also give lower bounds on the essential dimension of the semistable locus inside the moduli stack of vector bundles of rank r and degree d without parabolic structure.


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