5,851 research outputs found
On the Hurewicz homomorphism on the extensions of ideals in and spherical classes in
This is about Curtis conjecture on the image of the Hurewicz map
. First, we show that if
is of Adams filtration at least with then
is not a decomposable element in . Moreover, it is shown if
is the least positive integer that is represented by a cycle in
, then (i) if then
; (ii) if then for some
. Second, for we show that: (i) if the
conjecture holds on , then it holds on \la S\ra; (ii) if then
acts trivially on any extension of obtained by applying homotopy operations
arising from with . We also provide partial results on
the extensions of \la S\ra by taking (possible) Toda brackets of its
elements. We also discuss how the -sequence information maybe applied to
eliminate classes from being spherical
Generalised geometric weak conjecture on spherical classes and non-factorisation of Kervaire invariant one elements
This paper is on the Curtis conjecture. We show that the image of the
Hurewicz homomorhism , when restricted
to product of positive dimensional elements, is determined by
. Localised at , this proves
a geometric version of a result of Hung and Peterson for the Lannes-Zarati
homomorphism. We apply this to show that, for and or any prime
and any compact Lie group with Lie algebra so that
, the composition
where
is the -fold transfer, is
trivial if . Moreover, we show that for , the image of the above
composition vanishes on all elements of Adams filtration at least , i.e.
those elements of
represented by a permanent cycle
with , map trivially under the above composition. The
case of of the above observation proves and generalises a geometric
variant of the weak conjecture on spherical classes due to Hung, later on
verified by Hung and Nam. We also show that, for a compact Lie group ,
Curtis conjecture holds if we restrict to the image of the -fold transfer
with . Finally, we show
that the Kervaire invariant one elements
with do not factorise through the -fold transfer
with for or
any compact Lie group as above.Comment: Comments are welcom
Center conditions: pull back of differential equations
The space of polynomial differential equations of a fixed degree with a
center singularity has many irreducible components. We prove that pull back
differential equations form an irreducible component of such a space. The
method used in this article is inspired by Ilyashenko and Movasati s method.
The main concepts are the Picard Lefschetz theory of a polynomial in two
variables with complex coefficients, the Dynkin diagram of the polynomial and
the iterated integral
Tropicalisation for Topologists
This is an attempt to look at the tropical geometry from topological point of
view.Comment: A set of notes on tropical sets (no claim of originality). Comments
are welcom
Towards a Browder theorem for spherical classes in
According to Browder if then the Kervaire invariant of
the cobordism class of a -dimensional manifold vanishes and
is of Kervaire invariant one if and only if
is a permanent cycle. On the
other hand, according to Madsen if then is
cobordant to a sphere (hence of Kervaire invariant zero) and is
not cobordant to a sphere (hence of Kervaire invariant one) if and only if
certain element is spherical. Moreover, it is known
that is spherical if and only if is a permanent cycle in
the Adams spectral sequence. Moreover, classes with
are easily eliminated from being spherical. Hence, Browder's
theorem admits a presentation and proof in terms of certain square classes
being spherical in (see also work of Akhmetev and Eccles). In this
note, we consider the problem of determining spherical classes
with and . We show
(1) if is given with and
and , then is not spherical.
We refer to this as a generalised Browder theorem. We also present some partial
results on the degenerate cases, corresponding to , when
. (2) For the only spherical classes in
arise from the inclusion of the bottom cell, or the Hopf
invariant one elements. This verifies Eccles conjecture when restricted to
finite loop spaces with .Comment: Comments are welcom
Filtered finiteness of the image of the unstable Hurewicz homomorphism with applications to bordism of immersions
After recent work of Hill, Hopkins, and Ravenel on the Kervaire invariant one
problem, as well as Adams' solution of the Hopf invariant one problem, an
immediate consequence of Curtis conjecture is that the set of spherical classes
in is finite. Similarly, Eccles conjecture, when specialised to
with , together with Adams' Hopf invariant one theorem, implies
that the set of spherical classes in is finite. We prove a filtered
version of the above the finiteness properties. We show that if is an
arbitrary -complex such that is finite dimensional then the image of
the composition is finite; the finiteness remains valid if we formally replace
with . As an immediate and interesting application, we observe that
for any compact Lie group with and for any the
image of the composition
is finite where is a suitably twisted transfer map. Next, we consider work of Koschorke
and Sanderson which using Thom-Pontrjagin construction provides a -
correspondence (a group isomorphism if ) . We apply work of Asadi and Eccles on
computing Stiefel-Whitney numbers of immersions to show that given a framed
immersion and choosing very large with respect to
and , all self-intersection manifolds of an arbitrary element of
are boundary.Comment: This is the submitted version of this work. Comments are welcome! A
mis-statement in Corollary 1.7 is corrected, and the abstract is adopted
accordingl
Estimating Target Signatures with Diverse Density
Hyperspectral target detection algorithms rely on knowing the desired target
signature in advance. However, obtaining an effective target signature can be
difficult; signatures obtained from laboratory measurements or
hand-spectrometers in the field may not transfer to airborne imagery
effectively. One approach to dealing with this difficulty is to learn an
effective target signature from training data. An approach for learning target
signatures from training data is presented. The proposed approach addresses
uncertainty and imprecision in groundtruth in the training data using a
multiple instance learning, diverse density (DD) based objective function.
After learning the target signature given data with uncertain and imprecise
groundtruth, target detection can be applied on test data. Results are shown on
simulated and real data.Comment: Appeared in Proceedings of the 7th IEEE Workshop on Hyperspectral
Image and Signal Processing: Evolution in Remote Sensing, Tokyo, Japan, 201
Splitting Madsen-Tillmann spectra II. The Steinberg idempotents and Whitehead conjecture
We show that, at the prime , the spectrum splits off
the Madsen-Tillmann spectrum which is compatible
with the classic splitting of off . For , together with
our previous splitting result on Madsen-Tillmann spectra, this shows that
is homotopy equivalent to .Comment: Comments are welcome
Multiple Instance Hybrid Estimator for Learning Target Signatures
Signature-based detectors for hyperspectral target detection rely on knowing
the specific target signature in advance. However, target signature are often
difficult or impossible to obtain. Furthermore, common methods for obtaining
target signatures, such as from laboratory measurements or manual selection
from an image scene, usually do not capture the discriminative features of
target class. In this paper, an approach for estimating a discriminative target
signature from imprecise labels is presented. The proposed approach maximizes
the response of the hybrid sub-pixel detector within a multiple instance
learning framework and estimates a set of discriminative target signatures.
After learning target signatures, any signature based detector can then be
applied on test data. Both simulated and real hyperspectral target detection
experiments are shown to illustrate the effectiveness of the method
Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation
The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for
hyperspectral endmember estimation and spectral unmixing is presented. PM-LDA
provides a model for a hyperspectral image analysis that accounts for spectral
variability and incorporates spatial information through the use of
superpixel-based 'documents.' In our application of PM-LDA, we employ the
Normal Compositional Model in which endmembers are represented as Normal
distributions to account for spectral variability and proportion vectors are
modeled as random variables governed by a Dirichlet distribution. The use of
the Dirichlet distribution enforces positivity and sum-to-one constraints on
the proportion values. Algorithm results on real hyperspectral data indicate
that PM-LDA produces endmember distributions that represent the ground truth
classes and their associated variability
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