# Approaches for Noise Robust Quantum Algorithm Design

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · Johns Hopkins University (MD) · $330,000

## Abstract

The research team aims to address the fundamental challenge of designing quantum algorithms with inherent noise robustness. While industry, government, and academia are investing heavily in realizing quantum computing, current devices remain limited by noise, which undermines their potential advantages.  The approach tackles this issue at the algorithmic level, embedding robustness into the structure and execution of the algorithm itself. This helps shift the burden of noise mitigation away from hardware and toward software. The researchers will focus on variational quantum algorithms (VQAs), a widely applicable class of algorithms spanning quantum chemistry, optimization, and machine learning. Success in this effort will advance the field of quantum computing and enable higher-performance quantum applications that drive scientific discovery. Moreover, this effort will aid in developing a quantum workforce that can immediately contribute to the challenges of today’s hardware while gaining knowledge relevant to future hardware.

Focusing specifically on algorithms that possess inherent symmetry, the proposed work leverages concepts from quantum control and quantum error correction. The research team will exploit this symmetry to develop a theoretical framework based on dynamical Lie algebras to characterize the propagation of noise through a VQA. This framework will be leveraged to identify algorithmic motifs inspired by dynamical decoupling and noise-filtering protocols to 

## Key facts

- **NSF award ID:** 2515049
- **Awardee organization:** Johns Hopkins University (MD)
- **SAM.gov UEI:** FTMTDMBR29C7
- **PI:** Gregory D Quiroz
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** QUANTUM INFORMATION SCIENCE
- **Estimated total:** $330,000
- **Funds obligated:** $330,000
- **Transaction type:** Standard Grant
- **Period:** 08/15/2025 → 07/31/2028

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2515049

## Citation

> US National Science Foundation, Award 2515049, Approaches for Noise Robust Quantum Algorithm Design. Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2515049. Licensed CC0.

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