Given a holomorphic family of Bridgeland stability conditions over a surface, we define a notion of spectral network which is an object in a Fukaya category of the surface with coefficients in a triangulated DG-category. These spectral networks are analogs of special Lagrangian submanifolds, combining a graph with additional algebraic data, and conjecturally correspond to semistable objects of a suitable stability condition on the Fukaya category with coefficients. They are closely related to the spectral networks of Gaiotto-Moore-Neitzke. One novelty of our approach is that we establish a general uniqueness results for spectral network representatives. We also verify the conjecture in the case when the surface is disk with six marked points on the boundary and the coefficients category is the derived category of representations of an quiver. This example is related, via homological mirror symmetry, to the stacky quotient of an elliptic curve by the cyclic group of order six.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470886PMC
http://dx.doi.org/10.1007/s00220-024-05138-9DOI Listing

Publication Analysis

Top Keywords

spectral networks
12
stability conditions
8
spectral network
8
fukaya category
8
spectral
5
networks stability
4
conditions fukaya
4
fukaya categories
4
coefficients
4
categories coefficients
4

Similar Publications

Probing Surface Reactions on Multicomponent Glass Using Reflection-Absorption Infrared Spectroscopy.

Langmuir

January 2025

Department of Chemical Engineering and Materials Research Institute, Pennsylvania State University, University Park, Pennsylvania 16802, United States.

The chemical reactivity of glass surfaces is often studied with elemental analysis techniques, and although such characterization methods provide insights on compositional changes from exposure to specific chemical conditions, molecule-specific chemical reactions are not determined unambiguously. This study demonstrates the use of reflection-absorption infrared spectroscopy (RAIRS) to detect molecular species on alkali-free boroaluminosilicate and alkali aluminosilicate glasses, using acetic acid vapor as a model reactant to probe reaction sites at the surface with or without pretreatment by aqueous solutions of varied pH. With the assistance of the theoretical calculation of spectral changes based on refractive indices of bulk materials, it was possible to identify the molecular species being removed and produced at the glass surface.

View Article and Find Full Text PDF

Purpose: To develop and evaluate a physics-driven, saturation contrast-aware, deep-learning-based framework for motion artifact correction in CEST MRI.

Methods: A neural network was designed to correct motion artifacts directly from a Z-spectrum frequency (Ω) domain rather than an image spatial domain. Motion artifacts were simulated by modeling 3D rigid-body motion and readout-related motion during k-space sampling.

View Article and Find Full Text PDF

Bruises can affect the appearance and nutritional value of apples and cause economic losses. Therefore, the accurate detection of bruise levels and bruise time of apples is crucial. In this paper, we proposed a method that combines a self-designed multispectral imaging system with deep learning to accurately detect the level and time of bruising on apples.

View Article and Find Full Text PDF

Speech Enhancement for Cochlear Implant Recipients using Deep Complex Convolution Transformer with Frequency Transformation.

IEEE/ACM Trans Audio Speech Lang Process

February 2024

CRSS: Center for Robust Speech Systems; Cochlear Implant Processing Laboratory (CILab), Department of Electrical and Computer Engineering, University of Texas at Dallas, USA.

The presence of background noise or competing talkers is one of the main communication challenges for cochlear implant (CI) users in speech understanding in naturalistic spaces. These external factors distort the time-frequency (T-F) content including magnitude spectrum and phase of speech signals. While most existing speech enhancement (SE) solutions focus solely on enhancing the magnitude response, recent research highlights the importance of phase in perceptual speech quality.

View Article and Find Full Text PDF

Single-Cell Identification and Characterization of Viable but Nonculturable Using Raman Optical Tweezers and Machine Learning.

Anal Chem

January 2025

Department of Food Science and Agricultural Chemistry, Faculty of Agricultural and Environmental Sciences, McGill University, Sainte-Anne-de-Bellevue, Quebec H9X 3 V9, Canada.

is a leading foodborne pathogen that may enter a viable but nonculturable (VBNC) state to survive under environmental stresses, posing a significant health concern. VBNC cells can evade conventional culture-based detection methods, while viability-based assays are usually hindered by low sensitivity, insufficient specificity, or technical challenges. There are limited studies analyzing VBNC cells at the single-cell level for accurate detection and an understanding of their unique behavior.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!