Tensorleaf Press

Quantum computing and quantum networks, data science, and AI and large language models: the fields the next generation of technology rests on. Our first list is being written and planned now.

We write for readers who want to learn a new field in order, from the ground up — students and working professionals — and for engineers and researchers putting specialist knowledge to use.

A book should not present terms and techniques as isolated fragments. It should show where an idea came from, how it relates to its neighbours, and what it does when it meets a real problem.

Every book starts from a design rather than a draft. We decide where the reader begins, where they should arrive, and in what order understanding has to be built, before a chapter is written.

Terminology, notation and mathematical style stay consistent across a whole book, and the structure makes each chapter’s role — and its relationship to the others — visible. When a new concept is introduced, its prerequisites are stated, and theory, worked examples, diagrams and code are combined as the material demands.

Where a book carries code, we run it in a real environment and check that the prose, the mathematics, the figures and the code agree. Accuracy matters; so does a reader being able to move through the book without getting lost. We treat both as part of publication quality.

Explanatory articles and documentation are a search away. We publish books because some understanding is only reachable by building it up in order, from its premises. Designing that order, keeping notation consistent, and showing how concepts connect within a single volume is work that fragmented material cannot do.

We would rather hand over a subject’s structure and its connections than a set of pieces — so that a reader who finishes a book can see the whole, and choose where to go next themselves.