Retrograde inversion, often referred to in the context of astronomy and planetary motion, describes the phenomenon when a planet appears to move backward (or retrograde motion) in its orbit as observed from Earth. This can happen when Earth, on its faster orbit, overtakes another planet that is slower in its orbit around the Sun. In the case of "inversion," the term is not commonly used specifically to describe retrograde motion.
The International Conference on Rewriting Techniques and Applications (RTA) is a prominent academic event focused on the theory and application of rewriting techniques in computer science. Rewriting techniques are used in various fields such as formal methods, programming languages, automated reasoning, and symbolic computation.
The Symposium on Foundations of Computer Science (FOCS) is an annual academic conference that focuses on theoretical computer science. Established in 1960, FOCS is one of the most prestigious conferences in the field, along with its counterpart, the Annual ACM Symposium on Theory of Computing (STOC).
Alexander Razborov is a prominent mathematician and computer scientist, known for his significant contributions to the field of computational complexity theory. He is particularly recognized for his work on proof complexity, combinatorics, and the study of propositional logic. Razborov is known for his collaborations with other researchers and his influential papers that have shaped the understanding of different complexity classes. His work often focuses on the formalization of problems and the development of rigorous methods to analyze the limits of algorithmic approaches.
Andris Ambainis is a prominent researcher in the field of theoretical computer science, known particularly for his contributions to quantum computing and computational complexity. He is a professor at the University of Latvia and has made significant advances in understanding the power and limitations of quantum algorithms. Ambainis is especially noted for his work on quantum walk algorithms, quantum lower bounds, and various problems in the context of quantum information theory. His research has implications for both theoretical foundations of computer science and practical applications in quantum computing.
Angelika Steger is a prominent mathematician known for her work in areas such as computational geometry, discrete mathematics, and graph theory. She has made significant contributions to the field and is recognized for her research and academic activities. In addition to her research, Steger is known for her work in education and mentorship within the mathematical community.
As of my last update in October 2021, Arun Sharma is known as a computer scientist whose research interests may span various domains, including algorithms, machine learning, data mining, or another specialized field within computer science.
Cynthia Dwork is a prominent computer scientist and researcher known for her contributions to various fields, including algorithms, cryptography, distributed systems, and, notably, differential privacy. She has played a significant role in the development of theoretical foundations for privacy-preserving data analysis. Dwork's work on differential privacy provides a framework for ensuring that the privacy of individuals in a dataset is maintained while still allowing for useful statistical analysis.
Dana Ron is a prominent computer scientist, recognized for her contributions to algorithms, data structures, and theoretical computer science. She is particularly known for her work in areas such as approximation algorithms, online algorithms, and games in computation. Dana Ron has authored numerous research papers and made significant contributions to the understanding of algorithmic principles.
Giuseppe F. Italiano is a computer scientist known for his work in algorithms and data structures, particularly in the areas of computational geometry, graph algorithms, and optimization. He has made significant contributions to the understanding and development of efficient algorithms and has published numerous research papers in these fields. Many of his works are influential in both theoretical computer science and practical applications.
I. J. Good, or Irving John Good, was a British mathematician and statistician known for his work in the fields of statistics, machine learning, and artificial intelligence. He is perhaps best known for his contributions to the philosophy of artificial intelligence, particularly his formulation of the "Good's intelligence explosion" concept, which explores the potential for an artificial intelligence system to iteratively improve itself and surpass human intelligence.
Leslie Valiant is a prominent British computer scientist and a professor at Harvard University, best known for his contributions to the fields of theoretical computer science, machine learning, and computational complexity. He is particularly well-known for introducing the concept of probably approximately correct (PAC) learning, a foundational concept in machine learning that provides a framework for understanding how algorithms can learn from and make predictions based on data.
Michael Luby is a notable figure in the fields of computer science and information theory. He is particularly recognized for his work on algorithms, error-correcting codes, and randomized algorithms. Luby is known for co-developing Luby Transform (LT) codes, which are a form of fountain codes used for efficient data transmission and error correction in communication systems. In addition to his research contributions, Luby has held academic positions and has been involved in various projects related to computer science and engineering.
Yossi Matias is a prominent figure in the field of computer science and artificial intelligence, particularly known for his work with Google. He has made significant contributions to various areas, including machine learning and natural language processing. Matias has held leadership roles within Google, overseeing research initiatives and the development of technologies that leverage AI to improve user experiences and enhance product capabilities.
Self-reference is a concept where an expression, statement, or rule refers to itself in some way. This idea can be found in various fields such as mathematics, logic, computer science, linguistics, and philosophy. Here are some key aspects of self-reference: 1. **Linguistics**: In language, self-reference can occur when a term or a phrase refers back to itself.
A Cooper pair is a fundamental concept in the theory of superconductivity, which describes the pairing of two electrons (or other fermions) at very low temperatures. Named after the physicist Leon Cooper, who introduced the idea in 1956, Cooper pairs are essential for the Bardeen-Cooper-Schrieffer (BCS) theory of superconductivity. In a normal conductor, electrons experience repulsive interactions due to their negative charge.
Heusler compounds are a class of intermetallic materials that showcase unique magnetic, electronic, and mechanical properties. They are typically ternary or quaternary alloys composed of three or four elements, frequently featuring combinations of transition metals, main group metals, and sometimes metalloids.
Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 3. Visual Studio Code extension installation.Figure 4. Visual Studio Code extension tree navigation.Figure 5. Web editor. You can also edit articles on the Web editor without installing anything locally.Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.Video 4. OurBigBook Visual Studio Code extension editing and navigation demo. Source. - Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact





