Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 1112.6232

In Square Circle: Geometric Knowledge of the Indus Civilization

Sitabhra Sinha·Nisha Yadav·Mayank N. Vahia
View original source ↗Read source document ↗Export metadata ↓

Abstract

The earliest origins of mathematics in the Indian subcontinent is generally dated around 800-500 BCE when the {\em Sulbasutras} are thought to have been written. In this article we suggest that mathematical thinking in South Asia, in particular, geometry, may have had an even earlier beginning - in the third millenium BCE. We base our hypothesis on the analysis of design patterns, such as complex space-filling tiling, seen on artifacts of the Indus Valley Civilization (also referred to as the Mature Harappan Civilization, 2500-1900 BCE) which speaks of a deep understanding of sophisticated geometric principles.

Explore related subjects

math.HO

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sitabhra Sinha, Nisha Yadav, Mayank N. Vahia. 2011-12-29. In Square Circle: Geometric Knowledge of the Indus Civilization. https://arxiv.org/abs/1112.6232

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Come for the vibe, stay for the math

This article describes our experiences in mathematical outreach over the past decade. We talk about specific activities, but also general principles that we've learned along the way.

math.HO↗
arXiv2026

Graduate Mathematics in the Age of AI: Forming Mathematicians for Original, Independent, and Responsible Inquiry

Artificial intelligence can increasingly produce plausible, sophisticated mathematical material faster than a developing graduate student can understand or verify it. A sophisticated result or paper draft therefore becomes weaker evidence of the student's own mathematical development. This creates a formation gap between output and personal capacity, and a trust gap between a convincing argument and warranted acceptance. The formation gap can persist even when the student understands the output: understanding a supplied argument does not by itself establish the capacity to initiate and direct inquiry. These gaps are not the whole story. AI can also help students explore examples, compare approaches, enter unfamiliar areas, and undertake ambitious research. The task is to design an apprenticeship that realizes these possibilities while developing substantive mathematical command. The central purpose of a mathematics PhD is to form mathematicians capable of original, independent, and responsible inquiry, including inquiry conducted with AI. This document develops that objective through four connected capacities: competence, judgment, independence, and responsibility. It distinguishes a work's contribution to mathematics from the evidence it provides of a student's formation; explains how a known answer can initiate rather than end creative inquiry; and proposes changes in learning activities, assessment, doctoral originality, advising, and institutional support. Purposeful independent work and ambitious AI-assisted research are complementary parts of the model. Its recommendations include proportionate contribution statements, recognition of advising costs, and staged pilots evaluating both mathematical ability and effective human--AI collaboration. The aim is not to preserve an inherited sequence of training, but to improve mathematical formation as mathematical practice changes.

math.HO↗