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NA Digest, V. 20, # 11

NA Digest Sunday, March 15, 2020 Volume 20 : Issue 11


Today's Editor:

Daniel M. Dunlavy
Sandia National Labs
dmdunla@sandia.gov

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http://icl.utk.edu/na-digest/


From: Pavel Solin solin@unr.edu
Date: March 14, 2020
Subject: Free Self-Paced Online Linear Algebra Course


If you happen to teach Linear Algebra, and if your school is switching
to online instruction, you are very welcome to take advantage of
NCLab's free pioneering selfa-paced Linear Algebra course:

https://docs.google.com/presentation/d/1as1scdJckv2Mbzw1X1VvqEpdeC94ZYR9smNSXPGyAUE

Contact me directly and I'll help you get started.

The course is extremely easy to use for both the students and the
instructor. Students work at their own pace through tutorials,
autograded exercises and quizzes. They love it. For illustration, here
is a recent testimonial:

Dr Solin, I have a number of things to say about how great an idea
this Linear Algebra course has been regarding the use of NCLab. The
program is great, continues to get better, and I cannot compliment
enough any course that involves students actually working on the
problems rather than just listening. I have really enjoyed it so far,
and based on my test score this is the most successful I have been in
a math course since high school. I would not call other classes I
have had difficult but simply unengaging, and this class has turned
that around. Please extend my compliments to the NCLab devs if you
can, and keep advocating for this type of learning, if at the very
least as an option for people like me who learn well this way.
Regards, Andrew S.


From: Siegfried Rump rump@tuhh.de
Date: March 08, 2020
Subject: INTLAB Version 12 - The Matlab/Octave toolbox for Reliable Computing


Version 12 of INTLAB, the Matlab/Octave toolbox for Reliable
Computing, is now available at http://www.ti3.tuhh.de/intlab .

Given a numerical problem, INTLAB delivers rigorously verified bounds
for the solution together with a proof of existence and possibly
uniqueness. Correctness includes all procedural, possible
discretization and rounding errors as well as I/O. The input data may
be afflicted with tolerances. INTLAB comprises of several separate
toolboxes including ODEs, nonlinear systems, global optimization,
automatic differentiation (gradients, Hessians, Taylor expansion,
slopes), affine arithmetic, multivariate polynomials, rigorous
standard functions, error-free transformations, floating-point
arithmetic in specified precision etc. together with problem solving
routines for linear/nonlinear dense/sparse systems, (generalized)
eigenvalue problems, integration, range of nonlinear functions etc.

Compared to the previous version there are more than half of the
INTLAB files have been adapted, changed, and improved, and there are
more than 250 new out of 1669 m-files.

In particular, the
- Taylor model toolbox is extended (thanks to Florian Buenger) to
- Lie-derivative method as an alternative to Picard iteration
- adjustability of individual maximum degrees of Taylor model
variables
- identity and curvilinear preconditioning
- enhancement and adjustability of blunting for parallelepiped
preconditioning (allows verified integration of the asteroid
example up to 23 years)
- Bernstein polynomials for tighter Taylor model range enclosures
(see reference [TG] below)
- new toolbox GFP for Galois field computations,
- various new verification routines including
. all eigenvalues and singular values
. null space and range of a matrix
. pseudoinverse
. sharp range of a nonlinear function
- the long toolbox is extended to long matrices
- Octave-bug fixed that operator preferences are not respected (thanks
to Kai Torben Ohlhus),
- Very fast computation of Bernstein coefficients based on

[TG] J. Titi, J. Garloff, Matrix methods for the tensorial Bernstein
form, Applied Mathematics and Computation 346, p.254-271, 2019.


From: Tzanio Kolev tzanio@llnl.gov
Date: March 11, 2020
Subject: MFEM Version 4.1


Version 4.1 of MFEM, a lightweight, general, scalable C++ library for
finite element methods, is now available at: http://mfem.org

The goal of MFEM is to enable high-performance scalable finite element
discretization research and application development on a wide variety
of platforms, ranging from laptops to exascale supercomputers.

Some of the new additions in version 4.1 are:
- New BSD license.
- Improved GPU capabilities including support for HIP, libCEED,
Umpire, debugging and faster multi-GPU MPI communications.
- GPU acceleration in many additional examples, finite element and
linear algebra kernels.
- Partial assembly and matrix-free algorithm support for DG, H(curl)
and many other existing and new integrators.
- Support for non-conforming AMR on prisms and tetrahedra.
- Mesh optimization algorithms extended to support r-adaptivity.
- Complex-valued finite element operators and fields.
- ParaView, GSLIB-FindPoints, HiOp and Ginkgo support.
- 18 new examples and miniapps.

The MFEM library has many more features, including:
- 2D and 3D, arbitrary order H1, H(curl), H(div), L2, NURBS elements.
- Parallel version scalable to hundreds of thousands of MPI cores.
- Conforming/nonconforming adaptive mesh refinement (AMR), including
anisotropic refinement, derefenement and parallel load balancing.
- Galerkin, mixed, isogeometric, discontinuous Galerkin, hybridized,
and DPG discretizations.
- Support for triangular, quadrilateral, tetrahedral and hexahedral
elements, including arbitrary order curvilinear meshes.
- Scalable algebraic multigrid, time integrators, and eigensolvers.
- Lightweight interactive OpenGL visualization with the MFEM-based
GLVis tool.

MFEM is being developed in CASC, LLNL and is freely available under a
BSD license. For more details, see the interactive documentation and
the full CHANGELOG.


From: Kris ONeill oneill@siam.org
Date: March 11, 2020
Subject: New Book, Foundations of Applied Mathematics, Volume 2

Subject: New Book, Foundations of Applied Mathematics, Volume 2: Algorithms, Approximation, Optimization


Geared toward advanced undergraduate and beginning graduate students
in mathematics, data science, or machine learning, this textbook
presents the foundations of algorithms, approximation, and
optimization-essential topics in modern applied and computational
mathematics.

The authors provide a unified treatment of several topics that do not
usually appear together, and when used in concert with the free
supplemental lab materials, this book teaches not only the theory but
also the computational practice of modern mathematical methods. By
Jeffrey Humpherys and Tyler J. Jarvis

2020 / xx + 820 pages / Hardcover / 978-1-611976-05-2 / List $94.00 / SIAM Member $65.80 / OT166

Book details:

https://my.siam.org/Store/Product/viewproduct/?ProductId=31503574


From: Bernard Beauzamy bernard.beauzamy@scmsa.com
Date: March 09, 2020
Subject: New Book, Simple Random Walks in the Plane


New book: Simple Random Walks in the Plane, by Bernard Beauzamy

ISBN : 979-10-95773-01-6, ISSN : 1767-1175, hard cover, 208 pages.

Please see: http://www.scmsa.eu/livres/SCM_SRW_order.htm


From: Vu Thai Luan luan@math.msstate.edu
Date: March 10, 2020
Subject: Extended Deadline, ICCMAE 2020, USA, May 2020


I would like to let you know the following deadlines extensions for
the conference ICCMAE 2020 https://www.iccmae2020.math.msstate.edu,
May 7-9, MSU:

- Abstract Submission: Extended to March 25, 2020
- Travel Support Submission: Extended to March 20, 2020

Proceedings of this conference will be published in a special issue of
the Journal of Computational and Applied Mathematics (JCAM).

Travel Support: We expect to be able to offer partial travel support
to junior participants (graduate students or recent Ph.D.s) who will
give a talk in a contributed or mini-symposium session. Plus, the
registration fee for graduate students who received the support will
be waived. Please click on

https://www.iccmae2020.math.msstate.edu/registration for more details.


From: Thomas P. Wihler wihler@math.unibe.ch
Date: March 09, 2020
Subject: Swiss Numerics Day 2020, Switzerland, Jun 2020


The Swiss Numerics Day 2020 will be held on:

Thursday, June 4, 2020
University of Bern, Switzerland

Plenary speakers:
- Prof. Paola Antonietti, Politecnico di Milano, Italy
- Prof. Soren Bartels, Albert-Ludwigs-Universitat Freiburg, Germany

The conference webpage with further information (including deadlines
and registration) can found at: https://mathsites.unibe.ch/snd2020/


From: Pamela Bye pam.bye@ima.org.uk
Date: March 13, 2020
Subject: IMA Mathematics of Robotics, UK, Sep 2020


2nd IMA Conference on Mathematics of Robotics

Manchester Metropolitan University, 9-11 September 2020

https://ima.org.uk/11468/ima-conference-on-mathematics-of-robotics/

The IMA Conference on the Mathematics of Robotics aims to bring
together researchers working on all areas of robotics which have a
significant Mathematical content. The idea is to highlight the
Mathematical depth and sophistication of techniques applicable to
Robotics and to foster cooperation between researchers working in
different areas of Robotics. This Conference has been organised in
cooperation with the Society for Industrial and Applied Mathematics
(SIAM). Areas of interest include, but are not limited to:
Topology. Kinematics. Algebraic topology of configuration spaces of
robot mechanisms. Topological aspects of path planning and sensor
networks. Differential topology and singularity theory of robot
mechanism and moduli spaces. Algebraic Geometry. Varieties generated
by linkages and constraints. Geometry of stiffness and inertia
matrices. Rigid-body motions. Computational approaches to algebraic
geometry. Dynamical Systems and Control. Dynamics of robots and
mechanisms. Simulation of multi-body systems, e.g. swarm
robots. Geometric control of robots. Optimal control and other
optimisation problems. Combinatorial and Stochastic Methods. Rigidity
of structures. Path planning algorithms. Modular robots.
Statistics. Stochastic control. Localisation. Navigation with
uncertainty. Statistical learning theory. Cognitive
Robotics. Mathematical aspects of Artificial Intelligence,
Developmental Robotics and other Neuroscience based approaches.

Papers will be accepted on the basis of a 300 word abstract which
should be submitted by 3 April 2020 via https://my.ima.org.uk/.
Authors will be advised of acceptance shortly after and then asked to
submit a compulsory full paper of at most 8 pages by 17 April
2020. All contributions will be peer reviewed and acceptance will be
based on the results of the review process. If you do not wish to
submit an abstract, full papers of at most 8 pages should be submitted
by 17 April 2020. All contributions will be peer reviewed and
acceptance will be based on the results of the review process.

For technical queries please contact Professor W. Holderbaum

(w.holderbaum@reading.ac.uk)


From: Sanmukh Rao Kuppannagari sanmukh@hipc.org
Date: March 11, 2020
Subject: IEEE High Performance Computing, Data, and Analytics, India, Dec 2020


HiPC 2020 CALL FOR PAPERS - 27th IEEE International Conference on High
Performance Computing, Data, and Analytics
16--19 December, 2020 in Pune India

HiPC 2020 will be the 27th edition of the IEEE International
Conference on High Performance Computing, Data, Analytics and Data
Science. HiPC serves as a forum to present current work by researchers
from around the world as well as highlight activities in Asia in the
areas of high performance computing and data science. The meeting
focuses on all aspects of high performance computing systems, and data
science and analytics, and their scientific, engineering, and
commercial applications.

Authors are invited to submit original unpublished research
manuscripts that demonstrate current research in all areas of high
performance computing, and data science and analytics, covering all
traditional areas and emerging topics including from machine learning,
big data analytics and blockchain. Each submission should be
submitted to one of the tracks listed under the two broad themes of
High Performance Computing and Data Science.

Abstract Submissions : June 8, 2020

Paper Submissions : June 15, 2020

Submit your paper: https://easychair.org/conferences/?conf=hipc2020


From: Heike Fassbender h.fassbender@tu-braunschweig.de
Date: March 15, 2020
Subject: CFP, Organize 2023 Householder Symposium, 2023


The Householder Committee seeks a team to organize the 2023
Householder Symposium on Numerical Linear Algebra. The deadline for
submitting a proposal is 1 April 2020.

Guidelines for preparing a proposal and a link for uploding the
proposal can be found at:

https://users.ba.cnr.it//iac/irmanm21/HHXXI/Application_HH_symposium.html

Additional questions can be sent to: Heike Fassbender
(h.fassbender@tu-bs.de) Chair, Householder Committee

Please note: Proposals by professional congress and convention bureaus
will not be considered. No contact information about local members of
our community will be provided.


From: Mingchao Cai Mingchao.Cai@morgan.edu
Date: March 13, 2020
Subject: Postdoc Position, Computational Math, Morgan State Univ


A postdoctoral position in the area of numerical analysis, scientific
computation, and PDE analysis is available in the research group of
Professor Mingchao Cai in the Department of Mathematics at Morgan
State University. The position involves Finite element methods and
numerical analysis for problems arising from fluid mechanics and
structural mechanics. Candidates should have a Ph.D degree in
Computational Mathematics or in Engineering with a background in
Finite Element methods, high-performance computing, fluid mechanics,
and/or structural mechanics. Candidates who have a strong background
in PDE analysis (for example, asymptotic analysis, homogenization,
analysis of fluid mechanical problems) are also very welcome. The
candidate will also be required to teach one math course per semester.
The benefit includes regular salary (very competitive) plus insurance
for your whole family members ($1,000/m charged by Morgan State
University). The regular salary part is negotiable based on the
expertise of the candidates. Postdoctoral appointments are full-time
training programs of advanced academic preparation and research
training under the mentorship of a faculty member.

Basic Qualifications: PhD Degree in Mathematics, Scientific Computing,
Numerical Analysis, PDE analysis, Computational Mechanical Engineering
or a related discipline at the time of application. 1-2 years of
research experience or training related to mathematics and scientific
computation. Preferred Qualifications: Prior experience would be
viewed especially favorably in the areas of large-scale scientific
computation, numerical analysis, CFD and elasticity, and/or mechanical
engineering, but are not strictly required. The individual would like
to interact with the faculty members and the students in the
department

The initial appointment will be for two (2) year appointment, although
the contract is going to be initialized as 1 year. Please send an
email to Dr. Mingchao Cai: Mingchao.Cai@morgan.edu directly then
apply to the HR website by April 20, 2020 for primary
consideration. The position will remain open until filled.

The anticipated start date is Aug. 1/Sept. 1, 2020. Curriculum vitae,
cover letter, statement of research and 2 letters of reference are
required for a completed application.

The Department is especially interested in candidates who can
contribute to the diversity and excellence of the academic community
through research, teaching, and service. Morgan State University is an
Equal Opportunity/Affirmative Action Employer and all qualified
applicants will receive consideration for employment without regard to
race, color, religion, sex, sexual orientation, gender identity,
national origin, disability status, protected veteran status, or any
other characteristic protected by law. This employer is not accepting
applications for this position through Mathjobs.Org. Please send an
email and then apply it on the website of HR at Morgan State
University.


From: Loic Cappanera lmcappan@Central.UH.EDU
Date: March 11, 2020
Subject: Postdoc Position, Computational Mathematics, Univ of Houston


The Department of Mathematics at the University of Houston invites
applications for a research associate (postdoc) position in
computational mathematics. The position is for 2 years and may involve
teaching of up to one course per semester. We are especially
interested in candidates that have a strong track record in Scientific
Computing with experience in one or more of the following fields:
numerical analysis, finite element method, parallel computing, fluid
dynamics, thermodynamics and/or magnetohydrodynamics.

Please follow the link below to see more detail and apply to the

position: https://www.mathjobs.org/jobs/jobs/15344

Review of applications will begin immediately and will continue until
the position is filled.

Inquiries about the position may be directed to Loic Cappanera
(lcappan@math.uh.edu).


From: Bernhard Müller bernhard.muller@ntnu.no
Date: March 10, 2020
Subject: PhD Position, Numerical Modeling of Fluid-Structure Interaction, NTNU


At the Norwegian University of Science and Technology (NTNU), we have
a vacancy for a PhD candidate at the Department of Energy and Process
Engineering.

In the PhD project "Numerical Modeling of Fluid-Structure
Interaction," the PhD candidate will develop, implement and apply
numerical models for simulating fluid-structure interaction (FSI) in
the upper airways of obstructive sleep apnea (OSA) patients to predict
the outcome of surgery to cure OSA.

Details about the position, duties, selection criteria, salary and
conditions, application via https://www.jobbnorge.no/search/en, and
general information are available at the official job advertisement

https://www.jobbnorge.no/en/available-jobs/job/184493/phd-position-in-numerical-modeling-of-fluid-structure-interaction.

The application deadline is March 30, 2020.


From: Nail Yamaleev nyamalee@odu.edu
Date: March 14, 2020
Subject: PhD Position, Old Dominion Univ


Applications are invited for a PhD student position in the Department
of Mathematics and Statistics at Old Dominion University (Norfolk,
VA). This position will provide a unique opportunity to work on a
cutting-edge project in the group of Prof. N. Yamaleev in close
collaboration with research scientists of NASA Langley Research
Center. Current research in the group focuses on the development of
new entropy stable spectral collocation schemes for the Navier-Stokes
equations, adjoint-based methods for PDE-constrained optimization
problems, and grid adaptation methods based on error minimization. Our
group has a history of producing highly educated, independent,
exceptionally talented PhD scientists and postdocs. More information
about our research can be found at:

https://www.odu.edu/directory/people/n/nyamalee#profiletab=1

A typical PhD study in our group leads to participation in national
and international conferences and meetings, multiple publications in
top journals such as Journal of Computational Physics, Computers &
Fluids, AIAA Journal etc., and ample opportunities for networking with
leading research scientists from NASA, national labs, academia, and
industry.

We are looking for an enthusiastic and highly motivated PhD candidate
with a M.S. or B.S. degree in Mathematics, Computer Science,
Engineering or a closely related field. A solid background in
numerical methods, excellent programming skills (Fortran 90 or C++),
and effective communication skills (written/spoken English) are
required. Interested candidates should apply for a graduate
assistantship in computational and applied mathematics at:

https://www.odu.edu/admission/graduate Further details on how to apply

can be found at:

http://catalog.odu.edu/graduate/collegeofsciences/mathematicsstatistics/#doctorofphilosophy-computationalandappliedmathematics

For more information, please contact Dr. Yamaleev at nyamalee@odu.edu.


From: Kody Law kody.law@manchester.ac.uk
Date: March 11, 2020
Subject: PhD Position, Univ of Manchester


CFD and inverse UQ for investigation of drop/bubble dynamics

Applications are invited for a PhD position in the Department of
Mathematics at University of Manchester funded by EPSRC Industrial
CASE and IBM Research UK. The academic supervisors will be Prof. Kody
Law (kody.law@manchester.ac.uk) and Dr. Alice Thompson
(alice.thompson@manchester.ac.uk), and the industrial supervisor will
be Dr. Carlos Pena-Monferrer (cpena@ibm.com).

The focus of the project is the investigation of specific two-phase
flow problems such as the ones encountered in 3D printing, water
treatment or chemical mixing. A range of forward models are available,
from very detailed direct numerical simulations to various reduced
physics models. The aim of this investigation is to provide
data-driven and data assimilation inference tools for these complex
processes, for example for offline calibration, surrogate modelling,
and real time feedback control.

This PhD studentship offers an opportunity to apply the scientific
method on real-life problems combining CFD physical modelling,
mathematical and statistical modelling, and AI. The successful
candidate will also interact with the latest hardware and software
stacks in HPC and acquire highly desirable transferrable skills in
scientific software quality, reproducible research, and related
productivity tools. The offer also includes a minimum stay of three
months at IBM Research UK within the Hartree Center in Daresbury.

Interested candidates should email all 3 supervisors with CV, cover
letter, transcripts, and contact details for at least 2 referees.


From: Savagya Upadhyay supadhyay@us.fujitsu.com
Date: March 10, 2020
Subject: Internship Position, Quantum algorithms, Fujitsu Labs of America


Fujitsu Laboratories of America (FLA) has an internship opportunity
for a graduate student interested in quantum information
processing. The research will focus on quantum algorithms that are
potentially implementable of noisy intermediate scale quantum (NISQ)
devices. FLA serves as the US based research arm of Fujitsu, the
global information and communications technologies leader
headquartered in Japan.

A qualified candidate should have
i) Research interest and experience in quantum computing, specially in
quantum algorithms
ii) Background in linear algebra, machine learning, and probability
theory
iii) Strong programming skills
iv) Demonstrated ability to publish research papers in peer-reviewed
conference proceedings and/ or journals
v) Ability to work creatively and quickly

Students pursuing Masters and PhD programs with relevant coursework or
research experience are invited to apply. Successful candidate is
expected to have exceptional communication skills, work independently
as well as a part of a team, and grasp information outside her/ his
research expertise when required.

If this sounds like something you'd be interested at, please send a
recent CV to supadhyay@us.fujitsu.com

End of Digest
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