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X-WR-CALDESC:Events for Claremont Center for the Mathematical Sciences
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DTSTART;TZID=America/Los_Angeles:20230417T161500
DTEND;TZID=America/Los_Angeles:20230417T171500
DTSTAMP:20260622T024008
CREATED:20221207T193543Z
LAST-MODIFIED:20230816T023354Z
UID:3015-1681748100-1681751700@colleges.claremont.edu
SUMMARY:Applied Math Seminar: Emily de Jong (Caltech)
DESCRIPTION:Title: Modeling size distributions and collisions in cloud microphysics \nAbstract:\nFeedbacks between a warming atmosphere\, emission of aerosols\, and clouds and precipitation are one of the most difficult aspects for climate models to accurately capture. While these models operate at resolutions of tens or hundreds of kilometers\, many of the physics that determine how and where clouds form or precipitate function at the micron droplet scale. This separation of scales means that most of these “microphysics” must be modeled with only a few approximate quantities and physical equations. These simplifications lead to large uncertainties about the future climate\, such as the sensitivity of global warming to human-emitted aerosols.   \nThis talk presents two promising techniques for mathematically representing droplet size distributions and the microphysics that govern how droplets within the distribution evolve. The first method attempts to span a gap in complexity between a simple method of moments and expensive “bin” or spectral representations by collocating smooth basis functions over the droplet size domain. With intelligently selected basis functions\, this approach can represent the process of cloud droplets coalescing to form rain with bin-like accuracy\, but with a degree of complexity that is attainable for global simulations. Next\, we present a high-complexity high-fidelity Lagrangian approach known as the superdroplet method. This approach shows promise as a research tool to verify and train future microphysics models\, but it is currently incomplete in its purview of droplet physics. We describe a probabilistic approach to representing collisional breakup\, an often-overlooked process that can impact precipitation rates\, cloud lifetime\, and aerosol processing.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-emily-de-jong-caltech/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230410T161500
DTEND;TZID=America/Los_Angeles:20230410T171500
DTSTAMP:20260622T024008
CREATED:20230131T010146Z
LAST-MODIFIED:20230816T023147Z
UID:3058-1681143300-1681146900@colleges.claremont.edu
SUMMARY:Applied Math Seminar: Johannes Brust (UCSD)
DESCRIPTION:Title: PLSS: A Projected Linear Systems Solver (joint work with Michael Saunders) \nAbstract:\nIteratively solving linear systems has proven to be useful for many large applications. Projection methods use sketching matrices (possibly randomized) to generate a sequence of small projected subproblems\, but even the smaller systems can be costly. We develop a method in which one column is added to the sketching matrix each iteration. By choosing the sequence of all previous residuals for a sketch\, we derive an iterative process with orthogonal residuals that leads to a simple recursive update to approximate the solution. In exact arithmetic\, our method (PLSS) converges in at most \(n\) iterations\, where \(n\) is the column rank of matrix \(A\). In experiments on large sparse systems\, PLSS compares favorably with deterministic and state-of-the-art randomized methods.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-johannes-brust-ucsd/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230403T161500
DTEND;TZID=America/Los_Angeles:20230403T171500
DTSTAMP:20260622T024008
CREATED:20221020T204917Z
LAST-MODIFIED:20230320T152627Z
UID:2965-1680538500-1680542100@colleges.claremont.edu
SUMMARY:Applied Math Seminar: Ivy Xiong (USC)
DESCRIPTION:Title: A common pathway to cancer: oncogenic mutations abolish p53 oscillations. \nAbstract:\nThe tumor suppressor p53 oscillates in response to DNA double-strand breaks\, a behavior that has been suggested to be essential to its anti-cancer function. Nearly all human cancers have genetic alterations in the p53 pathway; a number of these alterations have been shown to be oncogenic by experiment. These alterations include somatic mutations and copy number variations as well as germline polymorphisms. Intriguingly\, they exhibit a mixed pattern of interactions in tumors\, such as co-occurrence\, mutual exclusivity\, and paradoxically\, mutual antagonism. Using a differential equation model of p53-Mdm2 dynamics\, I employ Hopf bifurcation analysis to show that these alterations have a common mode of action\, to abolish the oscillatory competence of p53\, thereby impairing its tumor suppressive function. In this analysis\, diverse genetic alterations\, widely associated with human cancers clinically\, have a unified mechanistic explanation of their role in oncogenesis. In this talk\, I will also discuss the role of physiological oscillations in health and disease broadly. \nReferences: \nXiong\, L.\, and Garfinkel\, A. (2022). A common pathway to cancer: Oncogenic mutations abolish p53 oscillations. Progress in Biophysics and Molecular Biology. DOI: 10.1016/j.pbiomolbio.2022.06.002 \nXiong\, L.\, and Garfinkel\, A. (2023). Are physiological oscillations “physiological”? arXiv. DOI: 10.48550/arXiv.2301.08996
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-ivy-xiong-usc/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230327T161500
DTEND;TZID=America/Los_Angeles:20230327T171500
DTSTAMP:20260622T024008
CREATED:20221026T182923Z
LAST-MODIFIED:20230816T040538Z
UID:2971-1679933700-1679937300@colleges.claremont.edu
SUMMARY:Applied Math Seminar:  Linh Huynh (University of Utah)
DESCRIPTION:Title:Inferring birth and death rates from population size time series data   \nAbstract:\nModels of population dynamics are usually formulated and analyzed with net growth rates. However\, separately identifying birth and death rates is significant in various biological applications such as disambiguating (1) exploitation vs. interference competition in ecology\, (2) bacteriostatic vs. bactericidal antibiotics in clinical treatments\, and (3) enhanced-fecundity vs. reduced-mortality mechanisms in drug resistance. In each of these three contexts\, the mechanisms are different\, but could be manifest in the same mean-field population size. \nIn this talk\, I will discuss a nonparametric method that utilizes stochastic fluctuations to extract birth and death rates from population size time series data. I will demonstrate the method on logistic growth to study density dependence\, but the method can be applied to general birth-death processes and does not require a priori assumptions on the rates. I will also discuss how to implement the theory on sample data and our estimation error analysis. This is based on published work joint with Peter Thomas (Case Western Reserve University) and Jacob Scott (Cleveland Clinic) and can be found here: Inferring density-dependent population dynamics mechanisms through rate disambiguation for logistic birth-death processes.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-linh-huynh-university-of-utah/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230320T150000
DTEND;TZID=America/Los_Angeles:20230320T160000
DTSTAMP:20260622T024008
CREATED:20230320T175619Z
LAST-MODIFIED:20230320T175619Z
UID:3105-1679324400-1679328000@colleges.claremont.edu
SUMMARY:Deniz Sarikaya on Narratives of Mathematical Practice (and why they matter!)
DESCRIPTION:Deniz Sarikaya joining us from the Technical University of Denmark and speaking on “Narratives of Mathematical Practice (and why they matter!)” (abstract below).\n \nThe speaker will join via zoom\, but there will be a live audience on the second floor of Pitzer College’s Gold Student Center in the Multipurpose room (in the building marked 3 here: https://www.pitzer.edu/about/maps-directions/quick-reference-map/).\n\nabstract:\nThere are different narratives on mathematics as part of our world\, some of which are more appropriate than others. Such narratives might be of the form ‘Mathematics is useful’\, ‘Mathematics is beautiful’\, or ‘Mathematicians aim at theorem-credit’. These narratives play a crucial role in mathematics education and in society as they are influencing people’s willingness to engage with the subject or the way they interpret mathematical results in relation to real-world questions; the latter yielding important normative considerations.\nIn this talk\, we want to analyze different narratives of mathematics and suggest that mathematizing as a virtuous practice in its own right is a better narrative of mathematics than\, for example\, extrinsic narratives which focus on the results of mathematical activity and the application of mathematics in non-mathematical contexts. By ‘better’ we mean that the mathematizing-narrative describes mathematical practice more adequately and that it allows for a shift in mathematics education that yields beneficial outcomes for our society. This is heavily drawing on Freudenthal’s Realistic Mathematical Education.\n \nThe talk is based on joint work with Deborah Kant (University of Hamburg)
URL:https://colleges.claremont.edu/ccms/event/deniz-sarikaya-on-narratives-of-mathematical-practice-and-why-they-matter/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:History and Philosophy of Mathematics Seminar
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230306T161500
DTEND;TZID=America/Los_Angeles:20230306T171500
DTSTAMP:20260622T024008
CREATED:20230118T184527Z
LAST-MODIFIED:20230208T193952Z
UID:3032-1678119300-1678122900@colleges.claremont.edu
SUMMARY:Applied Math Seminar: Nataliya Vasylyeva (IAMM NAS of Ukraine)
DESCRIPTION:Title: Identification of the order of semilinear subdiffusion with memory \nAbstract: See attached abstract
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-nataliya-vasylyeva-iamm-nas-of-ukraine/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20230227T161500
DTEND;TZID=America/Los_Angeles:20230227T171500
DTSTAMP:20260622T024008
CREATED:20221011T224115Z
LAST-MODIFIED:20230816T040643Z
UID:2958-1677514500-1677518100@colleges.claremont.edu
SUMMARY:Applied Math Seminar: Michael Perlmutter (UCLA)
DESCRIPTION:Title:Geometric Scattering on Measure Spaces \nAbstract:\nGeometric Deep Learning is an emerging field of research that aims to extend the success of convolutional neural networks (CNNs) to data with non-Euclidean geometric structure. Despitebeing in its relative infancy\, this field has already found great success in many applications such as recommender systems\, computer graphics\, and traffic navigation. In order to improve our understanding of the networks used in this new field\, several works have proposed novelversions of the scattering transform\, a wavelet-based model of CNNs for graphs\, manifolds\,and more general measure spaces. In a similar spirit to the original Euclidean scattering transform\, these geometric scattering transforms provide a mathematically rigorous framework for understanding the stability and invariance of the networks used in geometric deep learning.Additionally\, they also have many interesting applications such as drug discovery\, solving combinatorial optimization problems\, and predicting patient outcomes from single-cell data. In particular\, motivated by these applications to single-cell data\, I will also discuss recent work proposing a diffusion maps style algorithm with quantitative convergence guarantees for implementing the manifold scattering transform from finitely many samples of an unknown manifold.
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-michael-perlmutter-ucla/
LOCATION:Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
ORGANIZER;CN="Heather Zinn Brooks":MAILTO:hzinnbrooks@g.hmc.edu
END:VEVENT
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