The following application has motivated us to develop new Computational Geometry and Topology methods, involving Brillouin zones and periodic k-fold persistent homology: We model crystals by (infinite) periodic point sets, i.e. by the union of several translates of a lattice, where every point represents an atom. Two periodic point sets are equivalent if there is a rigid transformation from one to the other. A periodic point set can be represented by a finite cutout s.t. copying this cutout infinitely often in all directions yields the periodic point set. The fact that these cutouts are not unique creates problems when working with them. Therefore, material scientists would like to work with a complete, continuous invariant instead.
In this talk, I will present two continuous invariants that are at least generically complete: Firstly, the density fingerprint, computing the probability that a random ball of radius r contains exactly k points of the periodic point set, for all positive integers k and positive reals r. And secondly, the persistence fingerprint, which is the sequence of order k persistence diagrams, newly defined for infinite periodic point sets, for all positive integers k.
Joint work with Herbert Edelsbrunner, Alexey Garber, Vitaliy Kurlin, Georg Osang, Janos Pach, Morteza Saghafian, Philip Smith, and Mathijs Wintraecken.
A Topological Fingerprint for Periodic Crystals 2021-04-09TeresaHeiss
As the atoms in periodic crystals are arranged periodically, such a crystal can be modeled by a periodic point set, i.e. by the union of several translates of a lattice. Two periodic point sets are considered equivalent if there is a rigid motion from one to the other. A periodic point set can be represented by a finite cutout s.t. copying this cutout infinitely often in all directions yields the periodic point set. The fact that these cutouts are not unique creates problems when working with them. Therefore, material scientists would like to work with a complete, continuous invariant instead. We conjecture that a tool from topological data analysis, namely the sequence of order k persistence diagrams for all positive integers k, is such a complete, continuous invariant of equivalence classes of periodic point sets.
Topological Fingerprint for Periodic CrystalsTeresaHeiss
As the atoms in periodic crystals are arranged periodically, such a crystal can be modeled by a periodic point set, i.e. by the union of several translates of a lattice. Two periodic point sets are considered equivalent if there is a rigid motion from one to the other. A periodic point set can be represented by a finite cutout s.t. copying this cutout infinitely often in all directions yields the periodic point set. The fact that these cutouts are not unique creates problems when working with them. Therefore, material scientists would like to work with a complete, continuous invariant instead. We conjecture that a tool from topological data analysis, namely the sequence of k-fold persistence diagrams for all positive integers k, is such a complete, continuous invariant of periodic crystals.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
This article is all about what AI trends will emerge in the field of creative operations in 2024. All the marketers and brand builders should be aware of these trends for their further use and save themselves some time!
A Topological Fingerprint for Periodic Crystals 2021-04-09TeresaHeiss
As the atoms in periodic crystals are arranged periodically, such a crystal can be modeled by a periodic point set, i.e. by the union of several translates of a lattice. Two periodic point sets are considered equivalent if there is a rigid motion from one to the other. A periodic point set can be represented by a finite cutout s.t. copying this cutout infinitely often in all directions yields the periodic point set. The fact that these cutouts are not unique creates problems when working with them. Therefore, material scientists would like to work with a complete, continuous invariant instead. We conjecture that a tool from topological data analysis, namely the sequence of order k persistence diagrams for all positive integers k, is such a complete, continuous invariant of equivalence classes of periodic point sets.
Topological Fingerprint for Periodic CrystalsTeresaHeiss
As the atoms in periodic crystals are arranged periodically, such a crystal can be modeled by a periodic point set, i.e. by the union of several translates of a lattice. Two periodic point sets are considered equivalent if there is a rigid motion from one to the other. A periodic point set can be represented by a finite cutout s.t. copying this cutout infinitely often in all directions yields the periodic point set. The fact that these cutouts are not unique creates problems when working with them. Therefore, material scientists would like to work with a complete, continuous invariant instead. We conjecture that a tool from topological data analysis, namely the sequence of k-fold persistence diagrams for all positive integers k, is such a complete, continuous invariant of periodic crystals.
2024 State of Marketing Report – by HubspotMarius Sescu
https://www.hubspot.com/state-of-marketing
· Scaling relationships and proving ROI
· Social media is the place for search, sales, and service
· Authentic influencer partnerships fuel brand growth
· The strongest connections happen via call, click, chat, and camera.
· Time saved with AI leads to more creative work
· Seeking: A single source of truth
· TLDR; Get on social, try AI, and align your systems.
· More human marketing, powered by robots
ChatGPT is a revolutionary addition to the world since its introduction in 2022. A big shift in the sector of information gathering and processing happened because of this chatbot. What is the story of ChatGPT? How is the bot responding to prompts and generating contents? Swipe through these slides prepared by Expeed Software, a web development company regarding the development and technical intricacies of ChatGPT!
Product Design Trends in 2024 | Teenage EngineeringsPixeldarts
The realm of product design is a constantly changing environment where technology and style intersect. Every year introduces fresh challenges and exciting trends that mold the future of this captivating art form. In this piece, we delve into the significant trends set to influence the look and functionality of product design in the year 2024.
How Race, Age and Gender Shape Attitudes Towards Mental HealthThinkNow
Mental health has been in the news quite a bit lately. Dozens of U.S. states are currently suing Meta for contributing to the youth mental health crisis by inserting addictive features into their products, while the U.S. Surgeon General is touring the nation to bring awareness to the growing epidemic of loneliness and isolation. The country has endured periods of low national morale, such as in the 1970s when high inflation and the energy crisis worsened public sentiment following the Vietnam War. The current mood, however, feels different. Gallup recently reported that national mental health is at an all-time low, with few bright spots to lift spirits.
To better understand how Americans are feeling and their attitudes towards mental health in general, ThinkNow conducted a nationally representative quantitative survey of 1,500 respondents and found some interesting differences among ethnic, age and gender groups.
Technology
For example, 52% agree that technology and social media have a negative impact on mental health, but when broken out by race, 61% of Whites felt technology had a negative effect, and only 48% of Hispanics thought it did.
While technology has helped us keep in touch with friends and family in faraway places, it appears to have degraded our ability to connect in person. Staying connected online is a double-edged sword since the same news feed that brings us pictures of the grandkids and fluffy kittens also feeds us news about the wars in Israel and Ukraine, the dysfunction in Washington, the latest mass shooting and the climate crisis.
Hispanics may have a built-in defense against the isolation technology breeds, owing to their large, multigenerational households, strong social support systems, and tendency to use social media to stay connected with relatives abroad.
Age and Gender
When asked how individuals rate their mental health, men rate it higher than women by 11 percentage points, and Baby Boomers rank it highest at 83%, saying it’s good or excellent vs. 57% of Gen Z saying the same.
Gen Z spends the most amount of time on social media, so the notion that social media negatively affects mental health appears to be correlated. Unfortunately, Gen Z is also the generation that’s least comfortable discussing mental health concerns with healthcare professionals. Only 40% of them state they’re comfortable discussing their issues with a professional compared to 60% of Millennials and 65% of Boomers.
Race Affects Attitudes
As seen in previous research conducted by ThinkNow, Asian Americans lag other groups when it comes to awareness of mental health issues. Twenty-four percent of Asian Americans believe that having a mental health issue is a sign of weakness compared to the 16% average for all groups. Asians are also considerably less likely to be aware of mental health services in their communities (42% vs. 55%) and most likely to seek out information on social media (51% vs. 35%).
AI Trends in Creative Operations 2024 by Artwork Flow.pdfmarketingartwork
This article is all about what AI trends will emerge in the field of creative operations in 2024. All the marketers and brand builders should be aware of these trends for their further use and save themselves some time!
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
A report by thenetworkone and Kurio.
The contributing experts and agencies are (in an alphabetical order): Sylwia Rytel, Social Media Supervisor, 180heartbeats + JUNG v MATT (PL), Sharlene Jenner, Vice President - Director of Engagement Strategy, Abelson Taylor (USA), Alex Casanovas, Digital Director, Atrevia (ES), Dora Beilin, Senior Social Strategist, Barrett Hoffher (USA), Min Seo, Campaign Director, Brand New Agency (KR), Deshé M. Gully, Associate Strategist, Day One Agency (USA), Francesca Trevisan, Strategist, Different (IT), Trevor Crossman, CX and Digital Transformation Director; Olivia Hussey, Strategic Planner; Simi Srinarula, Social Media Manager, The Hallway (AUS), James Hebbert, Managing Director, Hylink (CN / UK), Mundy Álvarez, Planning Director; Pedro Rojas, Social Media Manager; Pancho González, CCO, Inbrax (CH), Oana Oprea, Head of Digital Planning, Jam Session Agency (RO), Amy Bottrill, Social Account Director, Launch (UK), Gaby Arriaga, Founder, Leonardo1452 (MX), Shantesh S Row, Creative Director, Liwa (UAE), Rajesh Mehta, Chief Strategy Officer; Dhruv Gaur, Digital Planning Lead; Leonie Mergulhao, Account Supervisor - Social Media & PR, Medulla (IN), Aurelija Plioplytė, Head of Digital & Social, Not Perfect (LI), Daiana Khaidargaliyeva, Account Manager, Osaka Labs (UK / USA), Stefanie Söhnchen, Vice President Digital, PIABO Communications (DE), Elisabeth Winiartati, Managing Consultant, Head of Global Integrated Communications; Lydia Aprina, Account Manager, Integrated Marketing and Communications; Nita Prabowo, Account Manager, Integrated Marketing and Communications; Okhi, Web Developer, PNTR Group (ID), Kei Obusan, Insights Director; Daffi Ranandi, Insights Manager, Radarr (SG), Gautam Reghunath, Co-founder & CEO, Talented (IN), Donagh Humphreys, Head of Social and Digital Innovation, THINKHOUSE (IRE), Sarah Yim, Strategy Director, Zulu Alpha Kilo (CA).
Trends In Paid Search: Navigating The Digital Landscape In 2024Search Engine Journal
The search marketing landscape is evolving rapidly with new technologies, and professionals, like you, rely on innovative paid search strategies to meet changing demands.
It’s important that you’re ready to implement new strategies in 2024.
Check this out and learn the top trends in paid search advertising that are expected to gain traction, so you can drive higher ROI more efficiently in 2024.
You’ll learn:
- The latest trends in AI and automation, and what this means for an evolving paid search ecosystem.
- New developments in privacy and data regulation.
- Emerging ad formats that are expected to make an impact next year.
Watch Sreekant Lanka from iQuanti and Irina Klein from OneMain Financial as they dive into the future of paid search and explore the trends, strategies, and technologies that will shape the search marketing landscape.
If you’re looking to assess your paid search strategy and design an industry-aligned plan for 2024, then this webinar is for you.
5 Public speaking tips from TED - Visualized summarySpeakerHub
From their humble beginnings in 1984, TED has grown into the world’s most powerful amplifier for speakers and thought-leaders to share their ideas. They have over 2,400 filmed talks (not including the 30,000+ TEDx videos) freely available online, and have hosted over 17,500 events around the world.
With over one billion views in a year, it’s no wonder that so many speakers are looking to TED for ideas on how to share their message more effectively.
The article “5 Public-Speaking Tips TED Gives Its Speakers”, by Carmine Gallo for Forbes, gives speakers five practical ways to connect with their audience, and effectively share their ideas on stage.
Whether you are gearing up to get on a TED stage yourself, or just want to master the skills that so many of their speakers possess, these tips and quotes from Chris Anderson, the TED Talks Curator, will encourage you to make the most impactful impression on your audience.
See the full article and more summaries like this on SpeakerHub here: https://speakerhub.com/blog/5-presentation-tips-ted-gives-its-speakers
See the original article on Forbes here:
http://www.forbes.com/forbes/welcome/?toURL=http://www.forbes.com/sites/carminegallo/2016/05/06/5-public-speaking-tips-ted-gives-its-speakers/&refURL=&referrer=#5c07a8221d9b
ChatGPT and the Future of Work - Clark Boyd Clark Boyd
Everyone is in agreement that ChatGPT (and other generative AI tools) will shape the future of work. Yet there is little consensus on exactly how, when, and to what extent this technology will change our world.
Businesses that extract maximum value from ChatGPT will use it as a collaborative tool for everything from brainstorming to technical maintenance.
For individuals, now is the time to pinpoint the skills the future professional will need to thrive in the AI age.
Check out this presentation to understand what ChatGPT is, how it will shape the future of work, and how you can prepare to take advantage.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
Time Management & Productivity - Best PracticesVit Horky
Here's my presentation on by proven best practices how to manage your work time effectively and how to improve your productivity. It includes practical tips and how to use tools such as Slack, Google Apps, Hubspot, Google Calendar, Gmail and others.
The six step guide to practical project managementMindGenius
The six step guide to practical project management
If you think managing projects is too difficult, think again.
We’ve stripped back project management processes to the
basics – to make it quicker and easier, without sacrificing
the vital ingredients for success.
“If you’re looking for some real-world guidance, then The Six Step Guide to Practical Project Management will help.”
Dr Andrew Makar, Tactical Project Management
Unlocking the Power of ChatGPT and AI in Testing - A Real-World Look, present...Applitools
During this webinar, Anand Bagmar demonstrates how AI tools such as ChatGPT can be applied to various stages of the software development life cycle (SDLC) using an eCommerce application case study. Find the on-demand recording and more info at https://applitools.info/b59
Key takeaways:
• Learn how to use ChatGPT to add AI power to your testing and test automation
• Understand the limitations of the technology and where human expertise is crucial
• Gain insight into different AI-based tools
• Adopt AI-based tools to stay relevant and optimize work for developers and testers
* ChatGPT and OpenAI belong to OpenAI, L.L.C.
More than Just Lines on a Map: Best Practices for U.S Bike Routes
This session highlights best practices and lessons learned for U.S. Bike Route System designation, as well as how and why these routes should be integrated into bicycle planning at the local and regional level.
Presenters:
Presenter: Kevin Luecke Toole Design Group
Co-Presenter: Virginia Sullivan Adventure Cycling Association
Ride the Storm: Navigating Through Unstable Periods / Katerina Rudko (Belka G...DevGAMM Conference
Has your project been caught in a storm of deadlines, clashing requirements, and the need to change course halfway through? If yes, then check out how the administration team navigated through all of this, relocating 160 people from 3 countries and opening 2 offices during the most turbulent time in the last 20 years. Belka Games’ Chief Administrative Officer, Katerina Rudko, will share universal approaches and life hacks that can help your project survive unstable periods when there seem to be too many tasks and a lack of time and people.
This presentation was designed to provide strategic recommendations for a brand in decline. The deck also incorporates a situational assessment, including a brand identity, positioning, architecture, and portfolio strategy for the Brand.
Presentation originally created for NYU Stern's Brand Strategy course. Design by Erica Santiago & Chris Alexander.
Geometric and Topological Fingerprints for Periodic Crystals
1. Geometric and Topological Fingerprints for Periodic
Crystals
Teresa Heiss (IST Austria), Herbert Edelsbrunner, Alexey Garber,
Vitaliy Kurlin, Georg Osang, János Pach, Morteza Saghafian, Philip
Smith, Mathijs Wintraecken
SIAM MS21, May 26, 2021
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 1 / 27
2. What is a (periodic) crystal?
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 2 / 27
3. What is a (periodic) crystal?
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 2 / 27
4. What is a (periodic) crystal?
“A [periodic] crystal is a solid composed of atoms, ions, or molecules
arranged in a pattern that is periodic in three dimensions.” [ASTM F1241]
i.e. there exist three linearly independent translations, such that each of
them maps the crystal to itself.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 3 / 27
5. What is a (periodic) crystal?
“A [periodic] crystal is a solid composed of atoms, ions, or molecules
arranged in a pattern that is periodic in three dimensions.” [ASTM F1241]
i.e. there exist three linearly independent translations, such that each of
them maps the crystal to itself.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 3 / 27
6. What is a periodic crystal not?
quasi-periodic crystal
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 4 / 27
7. What is our mathematical model for a crystal?
We model a crystal by an infinite periodic point set.
Centers of the atoms = points
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 5 / 27
8. Definition (Periodic point set)
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 6 / 27
9. Definition (Periodic point set)
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 6 / 27
10. Definition (Periodic point set)
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 6 / 27
11. Definition (Periodic point set)
((v1, v2, v3), M)
finite description of S
(CIF file)
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 6 / 27
12. Description not unique
A B
C
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 7 / 27
13. What is our mathematical model for a crystal?
We model a crystal by a periodic point set
.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 8 / 27
14. What is our mathematical model for a crystal?
We model a crystal by a periodic point set
an equivalence class of periodic point sets.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 8 / 27
15. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
16. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
17. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
18. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
19. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
20. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
21. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
22. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
23. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
24. Motivation: Crystal Structure Prediction
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 9 / 27
25. Definition fingerprint
Goal: map every crystal to a point in a nice space
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
26. Definition fingerprint
Goal: map every crystal to a point in a nice space
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
27. Definition fingerprint
Goal: map every crystal to a point in a nice space
A B
C
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
28. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant)
A B
C
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
29. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant)
A B
C
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
30. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant), s.t. the map is
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
31. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant), s.t. the map is injective
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
32. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant), s.t. the map is injective and continuous.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 10 / 27
35. Pair of periodic point sets close in bottleneck distance
Example α:
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 12 / 27
36. Pair of periodic point sets close in bottleneck distance
Example β:
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 13 / 27
37. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant), s.t. the map is injective and continuous.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 14 / 27
38. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant), s.t. the map is injective and continuous. → “fingerprint”
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 14 / 27
39. Definition fingerprint
Goal: map every crystal to a point in a nice space (we call this a crystal
invariant), s.t. the map is injective and continuous. → “fingerprint” [1]
[1] Edelsbrunner, Heiss, Kurlin, Smith, Wintraecken: The density fingerprint of a periodic point set. In: Proceedings of SoCG,
2021
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 14 / 27
40. Caveat
Goal: map every crystal to a point in Rn, s.t. the map is
invariant under isometries, injective, continuous.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 15 / 27
41. Caveat
Goal: map every crystal to a point in Rn, s.t. the map is
invariant under isometries, injective, continuous.
Problem: There are too many equivalence classes of periodic point sets.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 15 / 27
42. Caveat
Goal: map every crystal to a point in Rn, s.t. the map is
invariant under isometries, injective, continuous.
Problem: There are too many equivalence classes of periodic point sets.
Possible Solution: Make n depend on parameter of crystals
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 15 / 27
43. Why do we want a fingerprint function?
• develop understanding for the space of crystals
• compare crystals by comparing fingerprints
• vector representation → machine learning
• . . .
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 16 / 27
44. The density fingerprint and the persistence fingerprint
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 17 / 27
45. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 17 / 27
46. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 17 / 27
47. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 17 / 27
48. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 17 / 27
49. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 18 / 27
50. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 18 / 27
51. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 18 / 27
52. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 18 / 27
53. Persistent homology
What is the “shape” of the point set?
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 19 / 27
66. k-fold covers
Cover1(X, r)
Coverk(X, r) := {p ∈ R3 : p ∈ Br (x) for at least k points x ∈ X}
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 20 / 27
67. k-fold covers
Cover2(X, r)
Coverk(X, r) := {p ∈ R3 : p ∈ Br (x) for at least k points x ∈ X}
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 20 / 27
68. k-fold covers
Cover3(X, r)
Coverk(X, r) := {p ∈ R3 : p ∈ Br (x) for at least k points x ∈ X}
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 20 / 27
69. k-fold covers
Cover4(X, r)
Coverk(X, r) := {p ∈ R3 : p ∈ Br (x) for at least k points x ∈ X}
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 20 / 27
70. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
71. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
72. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
73. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
74. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
75. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
76. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
77. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
78. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
79. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
80. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
81. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
82. k-fold persistence
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
83. k-fold persistence
Dgmk(X) :=
Dgm((Coverk(X, r))r∈R)
. . . k-fold persistence [2]
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
[2] Herbert Edelsbrunner and Georg Osang. The Multi-cover Persistence of Euclidean Balls. In 34th International Symposium on
Computational Geometry (SoCG 2018), volume 99 of Leibniz International Proceedings in Informatics (LIPIcs), pages
34:1–34:14, Dagstuhl, Germany, 2018.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
84. k-fold persistence
Dgmk(X) :=
Dgm((Coverk(X, r))r∈R)
. . . k-fold persistence [2]
(Dgmk(X))k∈N ∈ DgmN
. . . persistence fingerprint
where Dgm is the set of persistence
diagrams
Fix k, let r increase:
Coverk(X, r1) ⊆ Coverk(X, r2) ⊆ · · · ⊆ Coverk(X, rn)
In the figures above: k=2
[2] Herbert Edelsbrunner and Georg Osang. The Multi-cover Persistence of Euclidean Balls. In 34th International Symposium on
Computational Geometry (SoCG 2018), volume 99 of Leibniz International Proceedings in Informatics (LIPIcs), pages
34:1–34:14, Dagstuhl, Germany, 2018.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 21 / 27
85. Definition (Persistence fingerprint function ϕ)
P . . . set of equivalence classes of periodic point sets in R3
Definition
Define the persistence fingerprint function as
ϕ : P → DgmN
[S]' 7→ (Dgmk(S))k∈N
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 22 / 27
86. Definition (Persistence fingerprint function ϕ)
P . . . set of equivalence classes of periodic point sets in R3
Definition
Define the persistence fingerprint function as
ϕ : P → DgmN
[S]' 7→ (Dgmk(S))k∈N
To avoid multiplicities = ∞, define
Dgmk(S) := lim
j→∞
Dgmk(S ∩ Uj )
Vol(Uj )
,
where Uj consists of j × j × j copies of the unit cell U and
where the division and the limit is applied to the multiplicity of each
persistence pair individually.
Note, this definition yields non-integer multiplicities.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 22 / 27
87. The density fingerprint and the persistence fingerprint
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
ψ0
A ψ1
A ψ2
A ψ3
A ψ4
A ψ5
A ψ6
A ψ7
A ψ8
A
Radius of Balls
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 23 / 27
88. Future Work
• fine-tune definition of persistence fingerprint
• prove invariance, continuity and generic completeness for persistence
fingerprint (easy)
• prove completeness without genericity conditions?
• generalize to weighted point sets with atomic weights (should be
straight-forward)
• continuity with respect to a different distance instead bottleneck
distance?
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 24 / 27
89. Pairs of periodic point sets that should get a small
distance assigned
Example γ:
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 25 / 27
90. Alternative distance between crystals
An alternative dissimilarity that may be more relevant in practice considers
affine transformations, τ, that minimize the bottleneck distance:
dAT(A, Q) = inf
τ
max{min{dB,2(A, τ(Q)), dB,2(τ(A), Q)}, | log s1|, | log s3|},
in which s1 ≥ s2 ≥ s3 are the three singular values of the matrix of τ.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 26 / 27
91. Herbert Edelsbrunner, Teresa Heiss, Vitaliy Kurlin, Phil Smith, and
Mathijs Wintraecken.
The density fingerprint of a periodic point set.
In Proceedings of SoCG 2021, 2021.
Herbert Edelsbrunner and Georg Osang.
The Multi-cover Persistence of Euclidean Balls.
In 34th International Symposium on Computational Geometry (SoCG
2018), volume 99 of Leibniz International Proceedings in Informatics
(LIPIcs), pages 34:1–34:14, Dagstuhl, Germany, 2018. Schloss
Dagstuhl–Leibniz-Zentrum fuer Informatik.
Teresa Heiss (IST Austria) Fingerprints for Crystals SIAM MS21, May 26, 2021 27 / 27
92. Space of crystals
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