309,133 research outputs found
ISTA Thesis
No full textQuantitative properties offer a framework for specifying and verifying system behaviors beyond the traditional boolean perspective. For example, while a boolean property may specify whether a server eventually grants every request it receives, a quantitative one may map each server execution to its average response time. This quantitative view is relatively well-studied in the context of static verification. However, although such properties often appear in practice as performance or robustness measures in a dynamic verification context, a general theoretical framework for their analysis and classification from a monitoring perspective is still missing.
In this thesis, we aim to develop such a framework that takes resource-precision tradeoffs of monitors as a central consideration. We present the first theory of monitorability for quantitative properties where monitors can be naturally approximate and compared regarding their precision and resource use. In particular, we show that additional monitor resources such as registers or states lead to strictly better approximations for some properties. To enable such analyses in a machine-model independent way, we describe an abstract notion of monitors that can be instantiated with concrete models of monitors. Within this framework, we study how abstract monitors behave and identify classes of properties amenable to approximate monitoring with resource-precision considerations. We then extend the boolean safety-liveness dichotomy and safety-progress hierarchy to the quantitative setting with a monitoring perspective. In particular, we prove that every property is the pointwise minimum of a safety property and a liveness property, and properties that are both safe and co-safe can be approximately monitored arbitrarily precisely using only finitely many states. We also study the classes of quantitative properties definable by finite-state quantitative automata and provide algorithms for deciding their safety or liveness as well as their safety-liveness decompositions. Finally, we present the first general-purpose tool for automating the analysis, verification, and monitoring of quantitative automata.
-------------------------------------------------------------------------------------------------------------------------------------------------------------- In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not
endorse any of ISTA's products or services. Internal or personal use of this
material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional
purposes or for creating new collective works for resale or redistribution, please go to
http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from
RightsLink
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural Networks
No full textIt is promising to solve linear inverse problems by unfolding iterative
algorithms (e.g., iterative shrinkage thresholding algorithm (ISTA)) as deep
neural networks (DNNs) with learnable parameters. However, existing ISTA-based
unfolded algorithms restrict the network architectures for iterative updates
with the partial weight coupling structure to guarantee convergence. In this
paper, we propose hybrid ISTA to unfold ISTA with both pre-computed and learned
parameters by incorporating free-form DNNs (i.e., DNNs with arbitrary feasible
and reasonable network architectures), while ensuring theoretical convergence.
We first develop HCISTA to improve the efficiency and flexibility of classical
ISTA (with pre-computed parameters) without compromising the convergence rate
in theory. Furthermore, the DNN-based hybrid algorithm is generalized to
popular variants of learned ISTA, dubbed HLISTA, to enable a free architecture
of learned parameters with a guarantee of linear convergence. To our best
knowledge, this paper is the first to provide a convergence-provable framework
that enables free-form DNNs in ISTA-based unfolded algorithms. This framework
is general to endow arbitrary DNNs for solving linear inverse problems with
convergence guarantees. Extensive experiments demonstrate that hybrid ISTA can
reduce the reconstruction error with an improved convergence rate in the tasks
of sparse recovery and compressive sensing.Comment: 109 pages, 16 figures; this is a draft and the final version has been
accepted by TPAMI (DOI: 10.1109/TPAMI.2022.3172214
ISTA Thesis
No full textRotations constitute one of the fundamental symmetries in physics, characterized by their intricate group structure and infinite dimensional representations. In contrast to classical rotations, quantum mechanics unveils the SO(3) symmetry group structure, manifesting in phenomena without classical counterparts, from angular momentum quantization to non-trivial addition of angular momenta.
While most studies of topological physics have focused on two-band systems, the SO(3) symmetry group of quantum rotors offers an inherently more complex platform with unprecedented possibilities for exploring topological phenomena. Despite their ubiquity in nature– from molecules to nanorotors– their potential for hosting topological phases has remained largely unexamined.
In this thesis, we mainly focus on periodically driven linear molecules as a prototype for studying topological phenomena in quantum rotors. Recent technological advances in coherent control of molecules, particularly through precisely shaped laser pulses, have made it possible to investigate linear rotors in the context of topology. While planar rotors have received some attention in recent years, threedimensional rotors–particularly linear molecules–harbor substantially richer topological phenomena due to their non-abelian nature and their additional angular degrees of freedom. We demonstrate that these systems can host novel edge states and topological features fundamentally impossible in planar systems.
We begin by establishing a theoretical bridge between periodically kicked rotors and "crystalline" lattices in angular momentum space. Using non-interacting linear molecules as our primary example, we show how quantum interference and revival patterns lead to the possibility to simulate band models with arbitrary number of bands N. While our framework applies to various quantum rotors, including nanorotors and kicked Bose-Einstein condensates, linear
molecules provide an ideal experimental platform due to their abovementioned precise controllability.
The core of this work examines adiabatic dynamics of 3D quantum rotors, establishing a geometric framework based on the Euler class to characterize its non-abelian topology. The non-Hermitian nature of the system enables novel braiding behaviors and topological transitions impossible in static systems, leading to an anomalous Dirac string phase with edge states in each gap, even though the Berry phases are all zero. These features can be directly observed through
molecular alignment and rotational level populations.
These findings establish quantum rotors as an alternative platform for studying multi-band topological physics, while suggesting practical implementations for quantum computation where topological protection could offer natural resilience against decoherence. The rich structure of three-dimensional rotation groups, combined with the tunability of topological features through driving parameters, makes this platform particularly valuable for exploring fundamental
physics and developing quantum technologies
ISTA Thesis
No full textPlant growth and development rely significantly on phytohormones, with auxin serving as a master regulator, orchestrating processes from embryogenesis to organogenesis, vascular patterning, and environmental adaptation. Since its conceptual proposition by Charles Darwin in 1880 as an endogenous chemical signal influencing phototropism in grass, auxin has captivated scientists seeking to understand how such a small molecule exerts a profound influence on plant development.
One particularly fascinating aspect of auxin function is its ability to self-organize its transport. Through a feedback mechanism between auxin perception and directional transport—primarily mediated by PIN auxin transporters—auxin establishes narrow transport channels. This phenomenon, known as auxin canalization, is fundamental to vascular formation, regeneration, and other key developmental processes. Despite advances in our understanding, driven by experimental studies and computational models, auxin canalization remains an enigma, with many unanswered questions.
Like other hormones, auxin functions through intricate signaling pathways. It operates through at least two distinct signaling mechanisms: the well-characterized canonical pathway and the less understood non-canonical pathway. While significant progress has been made in elucidating the canonical pathway, the non-canonical mechanisms remain less defined and require further investigation.
In this study, we revisit the non-canonical auxin signaling pathway mediated by the cell-surface complex Auxin Binding Protein 1-Transmembrane Kinase 1 (ABP1-TMK1), with a particular focus on its downstream phosphorylation events. We reveal that this auxin-mediated phosphorylation is conserved across the green lineage, underscoring its fundamental role in plant development. We explore key phosphorylation targets, particularly PIN2, which is essential for root gravitropism. To further understand TMK1’s role in diverse developmental processes, we identified and investigated its interactors as potential co-receptors or regulatory components within its signaling network.
Given the previously established role of ABP1-TMK1 in auxin canalization, we sought to further investigate this process and identified several TMK1 interactors also involved in this intricate mechanism.
These findings provide new insights into the complex regulation of auxin canalization, highlighting a broader and more interconnected signaling framework than previously understood
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
- …
