3,823 research outputs found
Supersymmetric Localization in GLSMs for Supermanifolds
In this paper we apply supersymmetric localization to study gauged linear
sigma models (GLSMs) describing supermanifold target spaces. We use the
localization method to show that A-twisted GLSM correlation functions for
certain supermanifolds are equivalent to A-twisted GLSM correlation functions
for hypersurfaces in ordinary spaces under certain conditions. We also argue
that physical two-sphere partition functions are the same for these two types
of target spaces. Therefore, we reproduce the claim of arXiv:hep-th/9404186,
arXiv:hep-th/9506070. Furthermore, we explore elliptic genera and (0,2)
deformations and find similar phenomena.Comment: 31 pages, no figure
Quantum K theory of Grassmannians, Wilson line operators, and Schur bundles
We prove a `Whitney' presentation, and a `Coulomb branch' presentation, for
the torus equivariant quantum K theory of the Grassmann manifold
, inspired from physics, and stated in an earlier paper. The
first presentation is obtained by quantum deforming the product of the
Hirzebruch classes of the tautological bundles. In physics, the
classes appeared as certain Wilson line operators. The second
presentation is obtained from the Coulomb branch equations involving the
partial derivatives of a twisted superpotential from supersymmetric gauge
theory. This is closest to a presentation obtained by Gorbounov and Korff,
utilizing integrable systems techniques. Algebraically, we relate the Coulomb
and Whitney presentations utilizing transition matrices from the (equivariant)
Grothendieck polynomials to the (equivariant) complete homogeneous symmetric
polynomials. The calculations of K-theoretic Gromov-Witten invariants of wedge
powers of the tautological subbundles on the Grassmannian utilize the
`quantum=classical' statement.Comment: 39 page
Quantum K Whitney relations for partial flag varieties
In a recent paper, we stated conjectural presentations for the equivariant
quantum K ring of partial flag varieties, motivated by physics considerations.
In this companion paper, we analyze these presentations mathematically. We
prove that if the conjectured relations hold, then they must form a complete
set of relations. Our main result is a proof of the conjectured presentation in
the case of the incidence varieties. We also show that if a quantum K divisor
axiom holds (as conjectured by Buch and Mihalcea), then the conjectured
presentation also holds for the complete flag variety.Comment: 25 pages; revised Remark 5.9 and added Example 5.1
One-off and Repeating Fast Radio Bursts: A Statistical Analysis
According to the number of detected bursts, fast radio bursts (FRBs) can be
classified into two categories, i.e., one-off FRBs and repeating ones. We make
a statistical comparison of these two categories based on the first FRB catalog
of the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst Project.
Using the Anderson-Darling, Kolmogrov-Smirnov, and Energy statistic tests, we
find significant statistical differences (-value 0.001) of the burst
properties between the one-off FRBs and the repeating ones. More specifically,
after controlling for distance, we find that the peak luminosities of one-off
FRBs are, on average, higher than the repeating ones; the pulse temporal widths
of repeating FRBs are, on average, longer than the one-off ones. The
differences indicate that these two categories could have distinct physical
origins. Moreover, we discuss the sub-populations of FRBs and provide
statistical evidence to support the existence of sub-populations in one-off
FRBs and in repeating ones.Comment: 10 pages, 6 figures, accepted for publication in Ap
Color Prompting for Data-Free Continual Unsupervised Domain Adaptive Person Re-Identification
Unsupervised domain adaptive person re-identification (Re-ID) methods
alleviate the burden of data annotation through generating pseudo supervision
messages. However, real-world Re-ID systems, with continuously accumulating
data streams, simultaneously demand more robust adaptation and anti-forgetting
capabilities. Methods based on image rehearsal addresses the forgetting issue
with limited extra storage but carry the risk of privacy leakage. In this work,
we propose a Color Prompting (CoP) method for data-free continual unsupervised
domain adaptive person Re-ID. Specifically, we employ a light-weighted prompter
network to fit the color distribution of the current task together with Re-ID
training. Then for the incoming new tasks, the learned color distribution
serves as color style transfer guidance to transfer the images into past
styles. CoP achieves accurate color style recovery for past tasks with adequate
data diversity, leading to superior anti-forgetting effects compared with image
rehearsal methods. Moreover, CoP demonstrates strong generalization performance
for fast adaptation into new domains, given only a small amount of unlabeled
images. Extensive experiments demonstrate that after the continual training
pipeline the proposed CoP achieves 6.7% and 8.1% average rank-1 improvements
over the replay method on seen and unseen domains, respectively. The source
code for this work is publicly available in
https://github.com/vimar-gu/ColorPromptReID
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