Grant writing for quantum computing

As a leader of a quantum initiative, you likely know how to write grants very well. It would not be useful to repeat here what you already know. Rather, here we will take a few example practices for general grant writing and map them into the space of quantum computing. To be clear, IBM Quantum® cannot tell you how to win grants; each funding agency has its own priorities and each research group has its own strengths. We can, however, share with you what deliverables we think are plausible, useful, and exciting, as well as our perspective on the field.

In this guide, we will examine the following well-known practices in grant writing, from the perspective of quantum computing:

General practices

Finding grants

Start with a thorough overview of grants available to increase chances and optimize fit.
Match agency initiatives (both strategic goals and timelines).

Prior to writing proposal (these are called out in the proposal itself)

Carry out initial work as proof of principle and highlight it in the proposal (preferably work that is successful but that cannot be grown without funding).
Demonstrate initiative in building collaborations (intra-university, regionally through QICs, nationally).
Apply for and win seed funding as a multiplier of later grant outcomes.

In the proposal

Call out the preliminary work above.
Propose realistic work in terms of timelines, in-house expertise, the state of the science, collaborations, and funds.
Outline institutional resources, facilities, and partnerships that increase feasibility.
Demonstrate that the problem you are pursuing is important and is not solved. This also highlights mastery of recent progress in the field.
Describe the expertise and credentials of the research team.
List concrete deliverables that are realistic given the resources requested and time constraints.
Acknowledge risks and provide realistic mitigation strategies.
Provide a clear, coherent approach with concrete methods, datasets, activities, milestones, and decision points.
Address rigor and reproducibility including data quality, controls, analysis and sharing.
Draw connections between academia and industry, and broader impacts generally.

Quantum-specific suggestions

Many of these practices come with special challenges when applied to quantum computing. For example, quantum computing research is often very interdisciplinary, involving researchers from physics, mathematics, and computer science, as well as from application areas like materials science, chemistry, and many more. This could make it difficult to demonstrate requisite expertise on a given research team. Early collaborative work between groups might mitigate this difficulty. In the following paragraphs we outline some key considerations in implementing these practices in quantum computing proposals.

Finding grants

Start with a thorough overview of grants available to increase chances and optimize fit.
- Quantum computing is a very active area of research and is supported by many government funding institutions including NSF, DoE, DoD, DARPA in the United States, EU Horizon/Quantum Flagship in Europe, and many others.
- There are many state-level or regional initiatives focused on the economic effects of quantum computing.
- There has been a lot of emphasis on the need for a quantum-smart workforce; many grants will at least have a requirement (if not a focus) on education and workforce development.
- See the section below on grants specific to quantum computing and successful grant writing.
Match agency initiatives (both strategic goals and timelines).
Many state and national funding opportunities value job upskilling, re-skilling, and training, as well as job creation.
Consider building connections between academia and industry, as well as between educators and institutions with expertise in workforce development.

Prior to writing proposal (these are called out in the proposal itself)

Initial work as proof-of-principle (work that is successful but that cannot be grown without funding).
- Very early work could be done using the IBM Quantum Open Plan. For initial exploration of scaling up, consider the IBM Quantum Flex Plan or Pay-as-you-go Plan. See the IBM Quantum access plans for more information.
Demonstrate initiative in building collaborations (intra-university, regionally through Quantum Innovation Centers, nationally).
Apply for/win seed funding as a multiplier of later grant outcomes.
- The Quantum Credits program from IBM Quantum may be very useful for showing initial proof-of-principle work, and demonstrating a history of successful grant writing. This program is open to principal investigators at universities and national labs. It is not available to students or members of the broader quantum community.

In the proposal

Call out the preliminary work above.
Propose work that is realistic in terms of timelines, in-house expertise, the state of the science, collaborations, and funds.
- We estimate that the minimum access for novel quantum computing research requires 400 minutes, which is the minimum purchase limit for the (Flex offering)[https://www.ibm.com/quantum/products]. Actual needs will vary by project.
- Typically one needs more than 400 minutes, so make sure to allocate a realistic amount for cloud QPU time.
- Familiarize yourself with the current state of job runtime, qubit counts, and so forth.
- Be mindful that the biggest impact applications are likely to leverage both quantum and high-performance computing.
The advantage tracker offers a quick overview of quantum computations that are pushing the limits of what is achievable today. Outline institutional resources, facilities, and partnerships that increase feasibility.
- Collaborations across disciplines - like computer science, physics, mathematics, chemistry, and others - might help.
- Check whether there is a regional Quantum Innovation Center (QIC) in your area. Their technical expertise, access to latest systems, and knowledge of the landscape make them valuable collaborators.
- If your institution has centers related to quantum computing, like in cybersecurity, logistics, or biochemistry, see if they have expertise, interest, or other resources available to you.
Demonstrate that the problem you are pursuing is important and is not solved, showing mastery of recent progress in the field.
Describe the expertise and credentials of the research team.
- Showcase interdisciplinary expertise: quantum physicists, device engineers, algorithm theorists, plus HPC expertise for hybrid runs.
- Expertise in application areas like chemistry, biochemistry, or materials science may help build a case for broad economic impact.
- Highlight IBM Quantum Network membership or cloud credits.
List concrete deliverables that are realistic given the resources requested and time constraints.
- This can be especially tricky given the pace and novelty of quantum computing.
- Make sure to include reliable deliverables include benchmarking, comparisons of methods, scaling studies of new algorithms or new approaches, upskilling, reskilling, and education.
- Proof-of-concept calculations followed by scaling studies are more likely to succeed in a funding period than large-scale, very deep circuits and long-term approaches.
Acknowledge risks and provide realistic mitigation strategies.
- This will be different for every study, but preliminary work using the Flex Plan or through partnership with a QIC will help you identify areas of uncertainty.
- Include mitigation strategies. Here "mitigation" refers to any project difficulties, but do be sure to outline your intended use of literal error mitigation strategies to show that you will be getting the highest possible performance out of modern quantum computers.
Provide a clear, coherent approach with concrete methods, datasets, activities, milestones, and decision points.
Address rigor and reproducibility, including data quality, controls, analysis, and sharing.
- Include open-source commitments (for example, Qiskit extensions) to meet NSF data-sharing mandates and enable broader impacts
Draw connections between academia and industry, and broader impacts generally Potentially important points unique to the quantum computing industry:
State specifically why you want to use the architecture/systems you propose. For example, you might structure your proposal around fixed-frequency transmon qubits like those in IBM® quantum computers for the following reasons:
- They have very fast gate times and can perform many operations within the coherence time
- They have high gate fidelity
- They have a predictable scalability according to the IBM Quantum Roadmap
You might focus on the scale and accessibility of quantum computers for the following reasons:
- IBM quantum computers are the largest QPUs available, unlocking utility-scale work for true innovation.
- Anything smaller than IBM quantum computers can be done on a simulator.
- You might call out the architecture of a specific processor like Nighthawk, and its suitability for quantum error correction.

Technical feasibility of projects

The limits of what is possible in quantum computing are changing every day. But it is important to keep the current constraints in mind in outlining your project. For detailed information on each quantum computer, and even on each qubit, check out the compute resources page on IBM Quantum Platform. The following high-level technical information might be useful. These are not hard limits that apply to all circumstances, but general guidelines to be adapted to your specific case.

Qubit count - IBM Nighthawk processors have 120 qubits. Some systems have slightly more. These systems offer utility-scale research for novel discoveries that are not classically accessible.. Circuit depth - The maximum circuit depth depends on many factors. Be sure you are considering the transpiled depth of two-qubit gates as the primary measure of depth. Transpiled, two-qubit depths around 30 are often manageable with modern error suppression and mitigation techniques. A few niche applications might encounter difficulties at lower depths, and some circuits can certainly go beyond that. This is a good depth at which to explore. QPU time - This is entirely dependent on your application. We estimate that a minimum of 400 minutes is required for novel quantum computing research. You might also check the QPU time required for individual runs of the projects listed on the advantage tracker. Most fall between 30-120 minutes. When we allow for experimentation, benchmarking of your problem, and multiple attempts, this time range is consistent with the aforementioned minimum.

Resources

The following are good candidate organizations for QC funding.

Program family	Typical quantum scope	Region	Example calls/notes
NSF Access Allocations	Access to computing resources	U.S.	NSF Access Allocations
NSF Quantum Information Science	Algorithms, hardware, networking, education	U.S.	Quantum Leap Challenge Institutes, ExpandQISE
DOE NQISRCs & Office of Science	Qubit science, quantum simulation for chemistry/materials	U.S.	Basic Energy Sciences quantum calls
DoD/DARPA Programs	Quantum devices, sensing, utility-scale QC	U.S.	For example: Quantum Benchmarking Initiative
EU Horizon/Quantum Flagship	Processors, communication, simulation	Europe	Work programmes (U.S. collaboration OK w/ licenses)
UK NQCC & National Programme	Compute access, demonstrators, feasibility	UK	NQCC funding opportunities
Eureka Network Quantum Calls	Applied R&D (computing, sensing)	Multi-national	Applied Quantum Technologies
DOE Chemistry/Materials	Quantum algorithms for electronic structure	U.S.	BES novel simulation methods
Regional/State Quantum Hubs	Translational prototypes, ecosystem building	U.S.	State-level seed grants

To search for specific grants, we recommend going directly to funding agency calls or consulting grant funding tracker websites. The following resources may be helpful:

Key Curator Websites

Quantum Computing Report: Dedicated section listing government and non-profit quantum funders worldwide (for example, NSF and DOE centers), with notes on research focus and contacts.
Qureca: Comprehensive tracker of global quantum initiatives, including national missions, budgets, and specific grant programs.
University Research Development Pages (for example, UConn): Curated lists of quantum-specific opportunities from NSF, DOE, DoD, and regional seeds; updated monthly.
Grants.gov: Official U.S. federal portal with advanced filters for "quantum computing" or "quantum information science" - search yields active solicitations like DOE's quantum R&D calls.
NSF SBIR/STTR Site: Tracks small business quantum grants in algorithms, computing, sensing, and more.
Paper Digest: Aggregates recent U.S. government grants tagged to quantum computing, sorted by date and relevance.
Unitary Foundation: Lists micro-grants and ecosystem funding, plus open-source quantum tools.

Examples of successful funding proposals

SBIR/STTR examples

Type	Company/project	Notes
NIST SBIR Phase II	Icarus Quantum (photon sources)	Press release with project summary; tech transfer from NIST
DOE SBIR Phase I	Q-CTRL (quantum automation)	Details AI for hardware control; Sandia collaboration

Federal large-scale examples

NSF Quantum Awards: Search NSF awards search for public abstracts (for example, Quantum Leap Challenge Institutes); full proposals not public but summaries are available.
DOE Quantum Centers: See NQISRC awards on science.osti.gov; for example, Q-NEXT center proposal excerpts in reports.

General Repositories

SBIR.gov Portfolio: Filter for "quantum" to show awards with abstracts.
Grants.gov Success Stories: Archived federal quantum SBIR narratives.

Concise wording on common grant needs

Each grant writer will obviously produce their own original proposal. But there are very common needs across many grants, like a description of why quantum computing is important or the state of modern quantum computers. These are predictable, but it is very important to get the statements correct. Below we provide concise wording on a few common grant components that can serve as inspiration for your own wording, complete with references.

What quantum computing is and what it is not

Quantum computing uses superposition, entanglement, and interference to manipulate information in ways impossible for classical systems, enabling potential advantages in tasks such as quantum simulation and certain structured optimization problems. It is not a faster general‑purpose computer: most workloads gain no quantum benefit, and current NISQ‑era devices remain limited by noise and scale. Quantum computing should therefore be viewed as a distinct, emerging computational model, which is promising for specific high‑impact problems but dependent on continued advances in hardware, algorithms, and error correction.

Broader impacts of quantum computing

Quantum computing could enable advances in materials, chemistry, secure communication, and complex optimization by directly leveraging quantum‑mechanical structure, opening pathways to more efficient energy systems, novel pharmaceuticals, and high‑performance manufacturing. Its broader impact includes catalyzing new high‑skill industries, strengthening technological competitiveness, and stimulating regional innovation ecosystems as quantum technologies mature into deployable tools for science and industry.

Education and workforce needs

Quantum technology requires interdisciplinary talent pipelines that blend quantum physics with computer science, engineering, and applied math, plus domain know‑how for target industries (chemicals, finance, health) and quantum‑safe cybersecurity skills for migration to post-quantum cryptography. Demand spans researchers, software engineers, control/cryogenic and photonics engineers, technicians, and systems integrators, with current shortages flagged across advanced hardware, algorithms, and manufacturing supply chains. Effective strategies include modular, stack‑wide curricula (from fundamentals to error correction and benchmarking), industry‑embedded training and apprenticeships, and regional hub programs that coordinate universities, national labs, and firms to accelerate experiential learning and job placement. Policymakers should prioritize standards/competency frameworks, mobility and reskilling pathways, and inclusive talent development, to sustain innovation while mitigating commercialization bottlenecks and uneven access.

Strengths of IBM quantum computers

IBM quantum computers use superconducting qubits and stand out through high‑connectivity processor designs—exemplified by the Nighthawk architecture—enabling circuits ~30% more complex than prior generations and supporting more efficient routes to logical qubits than competing layouts. Their modular, upgradeable IBM Quantum System Two® platform, built around Heron processors with ~10× improved error rates and hybrid quantum‑classical integration, accelerates workflows in chemistry, materials, and optimization - and positions IBM as a leader in quantum‑centric supercomputing. IBM's long‑term development roadmap, global cloud‑connected fleet, and the world’s largest industrial–academic Quantum Network provide unmatched accessibility, software maturity (Qiskit), and community‑driven benchmarking frameworks that reinforce IBM's ecosystem advantage over competitors.

References

The following references might be especially useful in crafting a well-informed narrative about a quantum project. They have been sorted first by topic and then by asset type to allow matching to funding agency norms.

What quantum computing is - and is not

Government / Official Reports

U.S. Government Accountability Office (GAO). Quantum Computing and Communications: Status and Prospects (Technology Assessment), Oct 2021.
U.S. DOE Office of Science (ASCR). ASCR Report on Quantum Computing for Science (Workshop Report), 2015.

National Academies / Standards Bodies

National Academies of Sciences, Engineering, and Medicine. Quantum Computing: Progress and Prospects (Consensus Study Report), 2019. (open versions hosted by MIT/Brown)

Intergovernmental / Policy Organizations

OECD. A Quantum Technologies Policy Primer (Digital Economy Papers No. 371), 2025.

Broader impacts of quantum technology

Government / Official Programs

U.S. DOE ARPA‑E. [Quantum Computing for Computational Chemistry (QC3) Program](https://arpa-e.energy.gov/programs-and-initiatives/view-all-programs/qc3 (program overview) and announcement summary at quantum.gov), 2024.
National Quantum Initiative Advisory Committee (NQIAC). Quantum Networking: Findings and Recommendations (Report), Sept. 2024.
U.S. Economic Development Administration (EDA). Regional Technology & Innovation Hubs (Tech Hubs) Program—designations & awards (regional innovation/economic impact), 2023–2026.

Intergovernmental / Policy Organizations

OECD + European Patent Office (EPO). Quantum technologies surge five‑fold...yet market adoption remains slow (press analysis with market projection ≈ €93B by 2035), Dec 17, 2025.

Peer‑Reviewed / Scholarly & Domain Reports