# TRAILBLAZER: Quantum Computing and Machine Learning for Fluid Dynamics Research

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · New York University (NY) · $2,999,456

## Abstract

Computational fluid dynamics is an area of engineering that predicts complicated flows, such as air flow around supersonic aircraft, hurricanes, and fuel combustion processes inside an automobile engine. Accurate and rapid prediction of these complicated flows, particularly their chaotic or turbulent patterns which are collectively called nonlinear processes, is an ongoing challenge for engineering. Quantum computers, which rely on the principles of quantum mechanics, can perform calculations at much greater speed than traditional supercomputers. Currently however, quantum computers cannot be used to predict complicated flows. The central problem is to make quantum data processing, which is based on linear processes, work with nonlinear processes associated with complex flows. To address this problem, this project will combine quantum computing with classical supercomputing, using artificial intelligence to accelerate connection between these two computing methods. If successful, this project will enable rapid prediction of complicated flows associated with natural systems such as wind gusts and engineered systems such as supersonic transport. To help disseminate these new methods, the project will host workshops at national scientific meetings, and work with private companies, both large and small, to test out the computer code. Additionally, students will be trained in a collaborative environment that includes engineers, computer scientists, and physicists to build a quantu

## Key facts

- **NSF award ID:** 2534977
- **Awardee organization:** New York University (NY)
- **SAM.gov UEI:** NX9PXMKW5KW8
- **PI:** Katepalli R Sreenivasan
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** —
- **Estimated total:** $2,999,456
- **Funds obligated:** $2,999,456
- **Transaction type:** Standard Grant
- **Period:** 09/01/2025 → 08/31/2028

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2534977

## Citation

> US National Science Foundation, Award 2534977, TRAILBLAZER: Quantum Computing and Machine Learning for Fluid Dynamics Research. Retrieved via AI Analytics 2026-06-07 from https://api.ai-analytics.org/grant/nsf/2534977. Licensed CC0.

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