arXiv subjects

Kevin L. Moore

Publications and source records attributed to Kevin L. Moore.

At least 19 recordsLinked to original sources

arXiv2024

Composition Rules for Strong Structural Controllability and Minimum Input Problem in Diffusively-Coupled Networks

This paper presents new results and reinterpretation of existing conditions for strong structural controllability in a structured network determined by the zero/non-zero patterns of edges. For diffusively-coupled networks with self-loops, we first establish a necessary and sufficient condition for strong structural controllability, based on the concepts of dedicated and sharing nodes. Subsequently, we define several conditions for strong structural controllability across various graph types by decomposing them into disjoint path graphs. We further extend our findings by introducing a composition rule, facilitating the analysis of strong structural controllability in larger networks. This rule allows us to determine the strong structural controllability of connected graphs called pactus graphs (a generalization of the well-known cactus graph) by consideration of the strong structural controllability of its disjoint component graphs. In this process, we introduce the notion of a component input node, which is a state node that functions identically to an external input node. Based on this concept, we present an algorithm with approximate polynomial complexity to determine the minimum number of external input nodes required to maintain strong structural controllability in a diffusively-coupled network with self-loops.

math.GN↗

arXiv2023

Topological Clusters in Multi-Agent Networks: Analysis and Algorithm

We study clustering properties of networks of single integrator nodes over a directed graph, in which the nodes converge to steady-state values. These values define clustering groups of nodes, which depend on interaction topology, edge weights, and initial values. Focusing on the interaction topology of the network, we introduce the notion of topological clusters, which are sets of nodes that converge to an identical value due to the topological characteristics of the network, independent of the value of the edge weights. We then investigate properties of topological clusters and present a necessary and sufficient condition for a set of nodes to form a topological cluster. We also provide an algorithm for finding topological clusters. Examples show the validity of the analysis and algorithm.

eess.SY↗

arXiv2022

Forecasting per-patient dosimetric benefit from daily online adaptive radiotherapy for cervical cancer

Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, requiring extra human and machine time compared to standard treatment methods. In this analysis, we sought to predict the subset of node-negative cervical cancer patients who benefit the most from ART. CT images, initial plan data, and on-treatment Cone-Beam CT (CBCT) images for 20 retrospective cervical cancer patients were used to simulate doses from daily non-adaptive and adaptive techniques. We evaluated the correlation (R$^2$) between dose and volume metrics from initial treatment plans and the dosimetric benefits to the Bowel V$_{40Gy}$, Bowel V$_{45Gy}$, Bladder D$_{mean}$, and Rectum D$_{mean}$ from adaptive radiotherapy using reduced 3mm or 5mm CTV-to-PTV margins. The LASSO technique was used to identify the most predictive metrics for Bowel V$_{40Gy}$. The three highest performing metrics were used to build multivariate models with leave-one-out validation for Bowel V$_{40Gy}$. Patients with higher initial bowel doses were correlated with the largest decreases in Bowel V$_{40Gy}$ from daily adaptation (linear best fit R$^2$=0.77 for a 3mm PTV margin and R$^2$=0.8 for a 5mm PTV margin). Other metrics had intermediate or no correlation. Selected covariates for the multivariate model were differences in the initial Bowel V$_{40Gy}$. and Bladder D$_{mean}$ using standard versus reduced margins and the initial bladder volume. Leave-one-out validation had an R$^2$ of 0.66 between the predicted and true adaptive Bowel V$_{40Gy}$ benefits for both margins. This work could be used to prospectively triage cervical cancer patients, and presents a critical foundation for predicting benefits from daily adaptation that can be extended to other patient cohorts.

physics.med-ph↗

arXiv2022

Strong Sign Controllability of Diffusively-Coupled Networks

This paper presents several conditions to determine strong sign controllability for diffusively-coupled undirected networks. The strong sign controllability is determined by the sign patterns (positive, negative, zero) of the edges. We first provide the necessary and sufficient conditions for strong sign controllability of basic components, such as path, cycle, and tree. Next, we propose a merging process to extend the basic componenets to a larger graph based on the conditions of the strong sign controllability. Furthermore, we develop an algorithm of polynomial complexity to find the minimum number of external input nodes while maintaining the strong sign controllability of a network.

eess.SY↗

arXiv2022

OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines

We establish an open framework for developing plan optimization models for knowledge-based planning (KBP) in radiotherapy. Our framework includes reference plans for 100 patients with head-and-neck cancer and high-quality dose predictions from 19 KBP models that were developed by different research groups during the OpenKBP Grand Challenge. The dose predictions were input to four optimization models to form 76 unique KBP pipelines that generated 7600 plans. The predictions and plans were compared to the reference plans via: dose score, which is the average mean absolute voxel-by-voxel difference in dose a model achieved; the deviation in dose-volume histogram (DVH) criterion; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models. The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50 to 0.62, which indicates that the quality of the predictions is generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P<0.05; one-sided Wilcoxon test) on 18 of 23 DVH criteria. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for a conventional planning model. This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. In the interest of reproducibility, our data and code is freely available at https://github.com/ababier/open-kbp-opt.

physics.med-ph↗

arXiv2021

Knowledge-Based Three-Dimensional Dose Prediction for Tandem-And-Ovoid Brachytherapy

Purpose: To develop a knowledge-based voxel-wise dose prediction system using a convolution neural network for high-dose-rate brachytherapy cervical cancer treatments with a tandem-and-ovoid (T&O) applicator. Methods: A 3D U-NET was utilized to output dose predictions using organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source locations. A sample of previous T&O treatments comprising 397 cases (273 training:62 validation:62 test), HRCTV and OARs (bladder/rectum/sigmoid) was used. Structures and dose were interpolated to 1x1x2.5mm3 dose planes with two input channels (source positions, voxel identification) and one output channel for dose. We evaluated dose difference (ΔD)(xyz)=D_(actual)(x,y,z)-D_(predicted)(x,y,z) and dice similarity coefficients in all cohorts across the clinically-relevant dose range (20-130% of prescription), mean and standard deviation. We also examined discrete DVH metrics used for T&O plan quality assessment: HRCTV D_90%(dose to hottest 90% volume) and OAR D_2cc, with ΔD_x=D_(x,actual)-D_(x,predicted). Pearson correlation coefficient, standard deviation, and mean quantified model performance on the clinical metrics. Results: Voxel-wise dose difference accuracy for 20-130% dose range for training(test) ranges for mean (ΔD) and standard deviation for all voxels was [-0.3%+/-2.0% to +1.0%+/-12.0%] ([-0.1%+/-4% to +4.0%+/-26%]). Voxel-wise dice similarity coefficients for 20-130% dose ranged from [0.96, 0.91]([0.94, 0.87]). DVH metric prediction in the training (test) set were HRCTV(ΔD_90)=-0.19+/-0.55 Gy (-0.09+/-0.67 Gy), bladder(ΔD_2cc)=-0.06+/-0.54 Gy (-0.17+/-0.67 Gy), rectum(ΔD)_2cc=-0.03+/-0.36 Gy (-0.04+/-0.46 Gy), and sigmoid(ΔD_2cc)=-0.01+/-0.34 Gy (0.00+/-0.44 Gy). Conclusion: 3D knowledge-based dose predictions for T&O brachytherapy provide accurate voxel-level and DVH metric estimates.

physics.med-ph↗

arXiv2021

OpenKBP: The open-access knowledge-based planning grand challenge

The purpose of this work is to advance fair and consistent comparisons of dose prediction methods for knowledge-based planning (KBP) in radiation therapy research. We hosted OpenKBP, a 2020 AAPM Grand Challenge, and challenged participants to develop the best method for predicting the dose of contoured CT images. The models were evaluated according to two separate scores: (1) dose score, which evaluates the full 3D dose distributions, and (2) dose-volume histogram (DVH) score, which evaluates a set DVH metrics. Participants were given the data of 340 patients who were treated for head-and-neck cancer with radiation therapy. The data was partitioned into training (n=200), validation (n=40), and testing (n=100) datasets. All participants performed training and validation with the corresponding datasets during the validation phase of the Challenge, and we ranked the models in the testing phase based on out-of-sample performance. The Challenge attracted 195 participants from 28 countries, and 73 of those participants formed 44 teams in the validation phase, which received a total of 1750 submissions. The testing phase garnered submissions from 28 teams. On average, over the course of the validation phase, participants improved the dose and DVH scores of their models by a factor of 2.7 and 5.7, respectively. In the testing phase one model achieved significantly better dose and DVH score than the runner-up models. Lastly, many of the top performing teams reported using generalizable techniques (e.g., ensembles) to achieve higher performance than their competition. This is the first competition for knowledge-based planning research, and it helped launch the first platform for comparing KBP prediction methods fairly and consistently. The OpenKBP datasets are available publicly to help benchmark future KBP research, which has also democratized KBP research by making it accessible to everyone.

physics.med-ph↗

arXiv2019

Topological Controllability of Undirected Networks of Diffusively-Coupled Agents

This paper presents conditions for establishing topological controllability in undirected networks of diffusively coupled agents. Specifically, controllability is considered based on the signs of the edges (negative, positive or zero). Our approach differs from well-known structural controllability conditions for linear systems or consensus networks, where controllability conditions are based on edge connectivity (i.e., zero or nonzero edges). Our results first provide a process for merging controllable graphs into a larger controllable graph. Then, based on this process, we provide a graph decomposition process for evaluating the topological controllability of a given network.

eess.SY↗

arXiv2018

Cooperative opinion dynamics on multiple interdependent topics: Modeling and analysis

To model the interdependent couplings of multiple topics, we develop a set of rules for opinion updates of a group of agents. The rules are used to design or assign values to the elements of interdependent weighting matrices. The cooperative and anti-cooperative couplings are modeled in both the inverse-proportional and proportional feedbacks. The behaviors of cooperative opinion dynamics are analyzed using a null space property of state-dependent matrix-weighted Laplacian matrices and a Lyapunov candidate. Various consensus properties of state-dependent matrix-weighted Laplacian matrices are predicted according to the intra-agent network topology and inter-dependency topical coupling topologies.

eess.SY↗

arXiv2016

Bayesian Evolution Models for Jupiter with Helium Rain and Double-diffusive Convection

Hydrogen and helium demix when sufficiently cool, and this bears on the evolution of all giant planets at large separations at or below roughly a Jupiter mass. We model the thermal evolution of Jupiter, including its evolving helium distribution following results of ab initio simulations for helium immiscibility in metallic hydrogen. After 4 Gyr of homogeneous evolution, differentiation establishes a thin helium gradient below 1 Mbar that dynamically stabilizes the fluid to convection. The region undergoes overstable double-diffusive convection (ODDC), whose weak heat transport maintains a superadiabatic temperature gradient. With a generic parameterization for the ODDC efficiency, the models can reconcile Jupiter's intrinsic flux, atmospheric helium content, and radius at the age of the solar system if the Lorenzen et al. H-He phase diagram is translated to lower temperatures. We cast the evolutionary models in an MCMC framework to explore tens of thousands of evolutionary sequences, retrieving probability distributions for the total heavy element mass, the superadiabaticity of the temperature gradient due to ODDC, and the phase diagram perturbation. The adopted SCvH-I equation of state favors inefficient ODDC such that a thermal boundary layer is formed, allowing the molecular envelope to cool rapidly while the deeper interior actually heats up over time. If the overall cooling time is modulated with an additional free parameter to imitate the effect of a colder or warmer EOS, the models favor those that are colder than SCvH-I. In this case the superadiabaticity is modest and a warming or cooling deep interior are equally likely.

astro-ph.EP↗

arXiv2015

Control of Networked Multiagent Systems with Uncertain Graph Topologies

Multiagent systems consist of agents that locally exchange information through a physical network subject to a graph topology. Current control methods for networked multiagent systems assume the knowledge of graph topologies in order to design distributed control laws for achieving desired global system behaviors. However, this assumption may not be valid for situations where graph topologies are subject to uncertainties either due to changes in the physical network or the presence of modeling errors especially for multiagent systems involving a large number of interacting agents. Motivating from this standpoint, this paper studies distributed control of networked multiagent systems with uncertain graph topologies. The proposed framework involves a controller architecture that has an ability to adapt its feed- back gains in response to system variations. Specifically, we analytically show that the proposed controller drives the trajectories of a networked multiagent system subject to a graph topology with time-varying uncertainties to a close neighborhood of the trajectories of a given reference model having a desired graph topology. As a special case, we also show that a networked multi-agent system subject to a graph topology with constant uncertainties asymptotically converges to the trajectories of a given reference model. Although the main result of this paper is presented in the context of average consensus problem, the proposed framework can be used for many other problems related to networked multiagent systems with uncertain graph topologies.

math.OC↗

arXiv2008

Quantum micro-mechanics with ultracold atoms

In many experiments isolated atoms and ions have been inserted into high-finesse optical resonators for the study of fundamental quantum optics and quantum information. Here, we introduce another application of such a system, as the realization of cavity optomechanics where the collective motion of an atomic ensemble serves the role of a moveable optical element in an optical resonator. Compared with other optomechanical systems, such as those incorporating nanofabricated cantilevers or the large cavity mirrors of gravitational observatories, our cold-atom realization offers direct access to the quantum regime. We describe experimental investigations of optomechanical effects, such as the bistability of collective atomic motion and the first quantification of measurement backaction for a macroscopic object, and discuss future directions for this nascent field.

quant-ph↗

arXiv2008

Observation of quantum-measurement backaction with an ultracold atomic gas

Current research on micro-mechanical resonators strives for quantum-limited detection of the motion of macroscopic objects. Prerequisite to this goal is the observation of measurement backaction consistent with quantum metrology limits. However, thermal noise presently dominates measurements and precludes ground-state preparation of the resonator. Here we establish the collective motion of an ultracold atomic gas confined tightly within a Fabry-Perot optical cavity as a system for investigating the quantum mechanics of macroscopic bodies. The cavity-mode structure selects a single collective vibrational mode that is measured by the cavity's optical properties, actuated by the cavity optical field, and subject to backaction by the quantum force fluctuations of this field. Experimentally, we quantify such fluctuations by measuring the cavity-light-induced heating of the intracavity atomic ensemble. These measurements represent the first observation of backaction on a macroscopic mechanical resonator at the standard quantum limit.

quant-ph↗

arXiv2007

Cavity Nonlinear Optics at Low Photon Numbers from Collective Atomic Motion

We report on Kerr nonlinearity and dispersive optical bistability of a Fabry-Perot optical resonator due to the displacement of ultracold atoms trapped within. In the driven resonator, such collective motion is induced by optical forces acting upon up to $10^5$ $^{87}$Rb atoms prepared in the lowest band of a one-dimensional intracavity optical lattice. The longevity of atomic motional coherence allows for strongly nonlinear optics at extremely low cavity photon numbers, as demonstrated by the observation of both branches of optical bistability at photon numbers below unity.

quant-ph↗

arXiv2006

Probing the quantum state of a guided atom laser pulse

We describe bichromatic superradiant pump-probe spectroscopy as a tomographic probe of the Wigner function of a dispersing particle beam. We employed this technique to characterize the quantum state of an ultracold atomic beam, derived from a Rb-87 Bose-Einstein condensate, as it propagated in a 2.5 mm diameter circular waveguide. Our measurements place an upper bound on the longitudinal phase-space area occupied by the 300,000 atom beam of 9(1) $\hbar$ and a lower bound on the coherence length (L > 13 microns). These results are consistent with full quantum degeneracy after multiple orbits around the waveguide.

quant-ph↗

arXiv2005

Bose-Einstein condensation in a mm-scale Ioffe-Pritchard trap

We have constructed a mm-scale Ioffe-Pritchard trap capable of providing axial field curvature of 7800 G/cm$^2$ with only 10.5 Amperes of driving current. Our novel fabrication method involving electromagnetic coils formed of hard anodized aluminum strips is compatible with ultra-high vacuum conditions, as demonstrated by our using the trap to produce Bose-Einstein condensates of 10$^6$ $^87$Rb atoms. The strong axial curvature gives access to a number of experimentally interesting configurations such as tightly confining prolate, nearly isotropic, and oblate spheroidal traps, as well as traps with variable tilt angles with respect to the nominal axial direction.

cond-mat.other↗

arXiv2004

Collimated, single-pass atom source from a pulsed alkali metal dispenser for laser-cooling experiments

We have developed an improved scheme for loading atoms into a magneto-optical trap (MOT) from a directed alkali metal dispenser in < 10^-10 torr ultra-high vacuum conditions. A current-driven dispenser was surrounded with a cold absorbing "shroud" held at < 0 C, pumping rubidium atoms not directed into the MOT. This nearly eliminates background alkali atoms and reduces the detrimental rise in pressure normally associated with these devices. The system can be well-described as a current-controlled, rapidly-switched, two-temperature thermal beam, and was used to load a MOT with 3 x 10^8 atoms.

physics.atom-ph↗

arXiv2004

Blind Detection and Compensation of Camera Lens Geometric Distortions

This paper presents a blind detection and compensation technique for camera lens geometric distortions. The lens distortion introduces higher-order correlations in the frequency domain and in turn it can be detected using higher-order spectral analysis tools without assuming any specific calibration target. The existing blind lens distortion removal method only considered a single-coefficient radial distortion model. In this paper, two coefficients are considered to model approximately the geometric distortion. All the models considered have analytical closed-form inverse formulae.

cs.CV↗