NSF award 2639616 · University of Maine

Exact Formulas for the KPZ Fixed Point and the Directed Landscape

Final report due

28 October 2027

in 375 days · The award ends on 30 June 2027.

GrantClerk is a private service. We are not NSF or any government agency.

Dates this award owes

NSF emails you about this too.

Decide about an extension2 Mar 2027in 135 days
award ending 2027-06-30 · Research.gov
This one is ours, not NSF’s.
Extension request16 May 2027in 210 days
award ending 2027-06-30 · Research.gov
PAPPG 24-1: “at least 45 days prior to the end date”
No-cost extension notice20 Jun 2027in 245 days
award ending 2027-06-30 · Research.gov
PAPPG 24-1: “at least ten calendar days prior to the end date”
Final report due28 Oct 2027in 375 days
award ending 2027-06-30 · Research.gov
PAPPG 24-1: “no later than 120-days following the end date of the award”
Project outcomes report due28 Oct 2027in 375 days
award ending 2027-06-30 · Research.gov
PAPPG 24-1: “no later than 120 days following the end date”
Award is closed out28 Oct 2027in 375 days
award ending 2027-06-30 · Research.gov
PAPPG 24-1: “financially closed out 120 days after their expiration date”

Annual report dates come from the budget period on your award notice. That date is not public, so it is not shown here.

How we got this date

NSF lists this award's end date as 30 June 2027.
NSF rules say the final report is due no later than 120 days after that.
So the final report is due by 28 October 2027.

Read the rule on Research.gov

Get a note before each report date

Add this award to your desk. We email you before each date and keep the dates in one place.

Renews each year until you cancel. Cancel any time from your account.

Already a member? Sign in

Award card

Award number: 2639616
Period of support: 15 Sep 2026 – 30 Jun 2027
Amount: $296,885
Awardee: University of Maine, Orono, ME
Program: PROBABILITY
Directorate: MPS

Abstract

The project aims to study the properties of limiting random fields arising from a broad class of physical and probabilistic models, including random growing interfaces, interacting particle systems, and polymers in random environments. This class is called the Kardar-Parisi-Zhang universality class, and it models many real-world phenomena, such as fire propagation, traffic flow, or disordered polymer chains. It has…

Is this right?

We copy this from the public NSF award record. Your award notice and NSF always win. If a date looks wrong, check Research.gov.