BEGIN:VCALENDAR VERSION:2.0 PRODID:-//jEvents 2.0 for Joomla//EN CALSCALE:GREGORIAN METHOD:PUBLISH BEGIN:VTIMEZONE TZID:America/New_York BEGIN:STANDARD DTSTART:20231205T170000 RDATE:20240310T030000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:America/New_York EST END:STANDARD BEGIN:STANDARD DTSTART:20241103T010000 RDATE:20250309T030000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:America/New_York EST END:STANDARD BEGIN:STANDARD DTSTART:20251102T010000 RDATE:20260308T030000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:America/New_York EST END:STANDARD BEGIN:STANDARD DTSTART:20261101T010000 RDATE:20270314T030000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:America/New_York EST END:STANDARD BEGIN:STANDARD DTSTART:20271107T010000 RDATE:20280312T030000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:America/New_York EST END:STANDARD BEGIN:STANDARD DTSTART:20281105T010000 RDATE:20290311T030000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:America/New_York EST END:STANDARD BEGIN:DAYLIGHT DTSTART:20240310T030000 RDATE:20241103T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:America/New_York EDT END:DAYLIGHT BEGIN:DAYLIGHT DTSTART:20250309T030000 RDATE:20251102T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:America/New_York EDT END:DAYLIGHT BEGIN:DAYLIGHT DTSTART:20260308T030000 RDATE:20261101T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:America/New_York EDT END:DAYLIGHT BEGIN:DAYLIGHT DTSTART:20270314T030000 RDATE:20271107T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:America/New_York EDT END:DAYLIGHT BEGIN:DAYLIGHT DTSTART:20280312T030000 RDATE:20281105T010000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:America/New_York EDT END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT UID:e4b2d4e845f9a4224d4ec708837a195e CATEGORIES:Experimental Mathematics Seminar CREATED:20241010T184609 SUMMARY:Combinatorial structure behind Sinkhorn limits LOCATION:https://rutgers.zoom.us/j/91865817691 [password: The 20th Catalan number\, alias (40)!/(20!*21!)\, alias 6564120420 ] DESCRIPTION:Abstract: The Sinkhorn limit of a positive square matrix is obtained by sca ling the rows so each row sum is 1, then scaling the columns so each column sum is 1, then scaling the rows again, then the columns again, and so on. It has been used for almost 90 years in applications ranging from predictin g telephone traffic to machine learning. But until recently, nothing was kn own about the exact values of its entries. In 2020, Nathanson determined th e Sinkhorn limit of a 2 x 2 matrix, and Ekhad and Zeilberger determined the Sinkhorn limit of a symmetric 3 x 3 matrix. We were able to determine the Sinkhorn limit of a general 3 x 3 matrix, and the result suggests the gener al form for n x n matrices. In particular, the coefficients reflect new com binatorial structure on sets of minor specifications. This is joint work wi th Jason Wu; Here is our paper (https://arxiv.org/abs/2409.02789) .\n X-ALT-DESC;FMTTYPE=text/html:

Abstract: The Sinkhorn limit of a positive square matrix is obtained by scaling the rows so each row sum is 1, then scaling the columns so each column sum is 1, then scaling the rows again, then the columns again, and so on. It has been used for almost 90 years in applicati ons ranging from predicting telephone traffic to machine learning. But unti l recently, nothing was known about the exact values of its entries. In 202 0, Nathanson determined the Sinkhorn limit of a 2 x 2 matrix, and Ekhad and Zeilberger determined the Sinkhorn limit of a symmetric 3 x 3 matrix. We w ere able to determine the Sinkhorn limit of a general 3 x 3 matrix, and the result suggests the general form for n x n matrices. In particular, the co efficients reflect new combinatorial structure on sets of minor specificati ons. This is joint work with Jason Wu; Here is our paper .

CONTACT: Eric Rowland, Hofstra University DTSTAMP:20260828T041413 DTSTART;TZID=America/New_York:20241205T170000 DTEND;TZID=America/New_York:20241205T180000 SEQUENCE:0 TRANSP:OPAQUE END:VEVENT END:VCALENDAR