Hitting time mixing for the random transposition walk
Abstract Consider shuffling a deck of n cards, labeled 1 through n , as follows: at each time step, pick one card uniformly with your right hand and another card, independently and uniformly with your left hand; then swap the cards. How long does it take until the deck is close to random? Diaconis and Shahshahani showed that this process undergoes cutoff in total variation distance at time $$t = \lfloor (n\log {n})/2 \rfloor $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>t</mml:mi> <mml:mo>=</mml:mo> <mml:mo>⌊</mml:mo> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>log</mml:mo> <mml:mi>n</mml:mi> <mml:mo>)</mml:mo> <mml:mo>/</mml:mo> <mml:mn>2</mml:mn> <mml:mo>⌋</mml:mo> </mml:mrow> </mml:math> . Confirming a conjecture of N. Berestycki, we prove the definitive “hitting time” version of this result: let $$\tau $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>τ</mml:mi> </mml:math> denote the first time at which all cards have been touched. The total variation distance between the stopped distribution at $$\tau $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>τ</mml:mi> </mml:math> and the uniform distribution on permutations is o (1); this is best possible, since at time $$\tau -1$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>τ</mml:mi> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> , the total variation distance is at least $$(1+o(1))e^{-1}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>+</mml:mo> <mml:mi>o</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>1</mml:mn> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>)</mml:mo> </mml:mrow> <mml:msup> <mml:mi>e</mml:mi> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> .
Authors
- Vishesh Jain
- Mehtaab Sawhney
Institutions
- University of Illinois Chicago (US)
- University of Chicago (US)
- Columbia University (US)
Publication Details
- Journal
- Probability Theory and Related Fields
- Published
- 2026-03-16
- DOI
- https://doi.org/10.1007/s00440-026-01479-9
- Primary Topic
- Markov Chains and Monte Carlo Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation