The reading room · October 2026

Ideas worth
spending time with.

Ideas from quantum physics, machine learning, and the wider world of science. Magazine stories, interviews, and explainers, alongside resources for learning linear algebra.

October 2026 selection

Quantum, physics & machine learning.

10 reads from 5 publications, published between 18 September and 18 October 2026. Each recommendation includes a source, date, and a short note on why I suggest it.

Showing all 10 articles

Light & measurement

Synopsis

Imaging with Zero Photons (opens in a new tab)

A counterintuitive imaging protocol built around correlations and the choice of which detection events to keep.

Why I recommend itRead past the headline and ask what the experiment actually measures.

APS Physics

Quantum foundations

Viewpoint

Quantum Probability Requires Probability (opens in a new tab)

A discussion of the assumptions behind attempts to derive the Born rule, particularly the role of probability additivity.

Why I recommend itA useful exercise in separating a derivation from its starting assumptions.

APS Physics

Neural networks & attention

Essay

Is ‘Attention’ the Essence of Intelligence? (opens in a new tab)

An accessible account of attention, from early machine translation to transformer models, and the importance of context.

Why I recommend itConnect the vectors and matrix operations from linear algebra to a central mechanism in modern AI.

Quanta Magazine

Precision physics

Research news

First Nuclear Clocks Kick Off a Precision Race (opens in a new tab)

Two operating nuclear clocks mark a step toward new precision measurements, while still trailing the best atomic clocks in stability.

Why I recommend itSee how a new measurement tool can open questions in fundamental physics.

APS Physics

Sources and publication dates checked on 18 October 2026. Links open the original publisher; some publishers may require a subscription. This is a dated selection, updated by hand.

Recommended for students

Build understanding.
Then practise.

Choose a resource for the question you are working on. The course syllabus and class material remain your guide to what is assessed.

01

Start here

18.06 Linear Algebra (opens in a new tab)

Gilbert Strang · MIT OpenCourseWare

A second explanation of the core ideas, with lectures and exercises. Use it alongside your TAU notes, then solve problems yourself.

Free course

Electrical & Electronics Engineering · 05091724

Your English course syllabus.

Topics, assessment rules, exam format, and bibliography for Semester A, 2026–2027.

Read the syllabus ↗