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Past exam of the year 1 of the computer science course of the University of Oxford 2016 Discrete mathematics, continuous mathematics and probability (resit) 6 f Solution by
Codex 0 2026-10-31
For , the same Newton's method formula givesThus the first step overshoots the root to . Part (e) then applies from index : the remaining sequence decreases to . The first step can be very large when is close to , where the derivative vanishes, but every starting value strictly between and still gives convergence to . The entire sequence is not decreasing, since .
Past exam of the year 1 of the computer science course of the University of Oxford 2016 Discrete mathematics, continuous mathematics and probability (resit) 6 e Solution by
Codex 0 2026-10-31
Since , Newton's method becomesFor , subtraction from givesAlso . Hence . Equivalently, the positive excess above is multiplied by the function from part (c): , with .
Thus the iterates form a decreasing sequence bounded below by . By the monotone convergence theorem for sequences they have a limit . Passing to the limit in the continuous update gives , or . Therefore . The exact error formula also shows quadratic convergence near this root.
Past exam of the year 1 of the computer science course of the University of Oxford 2016 Discrete mathematics, continuous mathematics and probability (resit) 6 d Solution by
Codex 0 2026-10-31
The tangent line to at is . Its intersection with the horizontal axis gives Newton's method:Each step requires . Convergence to a zero of a function additionally depends on the starting point and the local behavior of ; the update formula alone is not a convergence guarantee.
Past exam of the year 1 of the computer science course of the University of Oxford 2016 Discrete mathematics, continuous mathematics and probability (resit) 6 c Solution by
Codex 0 2026-10-31
Past exam of the year 1 of the computer science course of the University of Oxford 2016 Discrete mathematics, continuous mathematics and probability (resit) 6 b Solution by
Codex 0 2026-10-31
The constraint is a compact set, so the continuous objective attains both extrema by the extreme value theorem. Use Lagrange multipliers with :Since the second component makes , the two equations give , or . Substitution into the constraint yieldswith matching signs. The objective values are thereforeThe constraint gradient never vanishes on the ellipse, so these are all the possible extrema. As a direct check, set , ; then and the Cauchy-Schwarz inequality gives , with equality at the same points.
Past exam of the year 1 of the computer science course of the University of Oxford 2016 Discrete mathematics, continuous mathematics and probability (resit) 6 a Solution by
Codex 0 2026-10-31
The critical points satisfy both first partial derivatives equal to zero:Substitute into the second equation to get . Thus the candidates are and .
The Hessian matrix and its determinant areAt the determinant is , so the Hessian matrix is indefinite and the point is a saddle point. At the determinant is and , so the Hessian matrix is positive definite and the point is a strict local minimum, with valueThere is no local maximum. Along , is unbounded above and below, so there are no global extrema either.
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 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.Figure 3. Visual Studio Code extension installation.Figure 5. . 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. - 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





