Quantum computing stocks screener Excel - if that is the phrase you typed into Google this weekend you are almost certainly trying to sort out which of the publicly listed quantum names actually give you exposure to the thesis, which are mostly press-release stories, and which mega-caps quietly run the real quantum programs. The list is short, the categories blend into each other, and the data you need is scattered across investor decks, government contract awards, and qubit-milestone tweets. This guide ships a working Excel workbook that pulls the public quantum universe into one screener, scores each ticker on pure-play exposure and qubit progress, calculates a cash-runway estimate for the pre-revenue plays, and lets you compare four very different categories on a single tab.
This is not a generic "best quantum stocks to buy" listicle. It is a screener template, a methodology, and a structured way to keep score as the quantum race compounds quarter by quarter.
Why a Quantum Computing Stocks Screener Excel Now
For most of the 2010s, "quantum computing stocks" was a label that did not really map to anything investible. The serious work sat inside IBM Research, Google Quantum AI, and a handful of national labs. The earliest pure-play public listings, IonQ and Rigetti among them, came to market via SPAC in 2021 and 2022. Then three things happened almost at once that pulled the sector forward.
First, the qubit count finally started to scale. IBM's Condor roadmap hit four-digit qubit counts, Google's Willow demonstrated below-threshold error correction at 105 qubits, and Microsoft's Majorana 1 prototype gave the topological camp a credible hardware path. The hardware story stopped being a slide deck and started being a measurable trajectory.
Second, government money showed up at scale. The US reauthorization of the National Quantum Initiative, the EU Quantum Flagship, and accelerating Chinese investment have pushed multi-year contract awards into pure-play revenue lines. For names like IonQ and Rigetti, government contracts are now a meaningful share of total revenue, which changes how the cash-burn-to-funding picture looks.
Third, the hyperscalers operationalized quantum-as-a-service. AWS Braket, Azure Quantum, and IBM Quantum Network have moved from research demos to enterprise SLAs. That created a second buyer of pure-play quantum capacity (the hyperscalers themselves) on top of the government channel.
The result is that as of June 2026 we have four very different categories all wearing the same "quantum" label:
| Category | What They Sell | Key Lever |
|---|---|---|
| Pure-Play Hardware | Quantum processors, cloud access | Qubit count, error rate, govt contracts |
| Quantum Security | Post-quantum crypto, QKD systems | NIST PQC adoption, enterprise refresh cycles |
| Mega-Cap Platform | Quantum-as-a-service via cloud | Cloud revenue uplift, R&D scale |
| Diversified Adjacent | Subsidiaries, enabling tech | Parent multiple, M&A optionality |
A real screener has to acknowledge that those four buckets do not behave the same way. A pre-revenue pure-play hardware name trades like venture-stage equity with daily mark-to-market. A post-quantum cryptography vendor trades on enterprise software cycles. A hyperscaler with a quantum line item trades on cloud growth and treats quantum as optionality. Bucketing them into one "quantum ETF" blurs the trade you are actually trying to express.
This template does the bucketing for you.
What the Quantum Computing Stocks Screener Excel Ships With
The workbook has six tabs that flow from "what is the universe" to "how do I score each name" to "how long can the pre-revenue names survive."
- How To Use - tutorial, sheet guide, scoring methodology, risk notes, and an educational-use disclaimer. First-read material.
- Main Dashboard - the screener. Yellow input cells for portfolio size, category allocation cap, minimum composite score, and four score-weight inputs. The body of the sheet is a 15-row table with live price, market cap, 52-week distance, P/E, dividend yield, beta, RSI, earnings growth, and the composite Q Score.
- Quantum Readiness Scoring - the engine. Each ticker gets scored on four dimensions: pure-play percentage of revenue, qubit milestone tier, signed government contract flag, and a category multiplier. The weights live on the Main Dashboard so the model is re-weightable from one tab.
- Cash Runway & Financials - total cash, total debt, enterprise value, revenue, and an estimated quarterly burn input. Runway is computed in quarters and is the most important metric for pre-revenue pure plays.
- Quality + Fundamentals - P/E, dividend yield, ROE, debt-to-equity, revenue growth, EPS growth, gross margin, and Altman Z score. A PASS or REVIEW flag is computed off gross margin and bankruptcy proxy.
- Category Heatmap - the four buckets aggregated to median market cap, P/E, dividend yield, ROE, debt-to-equity, and EPS growth. This is the tab you screenshot when you brief a client.
Every sheet ends with a "MarketXLS Functions Used in This Sheet" reference block so the reader always knows which function powers which cell.
The sample workbook ships with illustrative static values plus the formula reference next to each cell. The template workbook ships with live MarketXLS formulas only and refreshes on every Ctrl+Alt+F9. Both files use the same six-sheet structure.
The Composite Quantum Readiness Score Explained
The composite score on the Main Dashboard is the most opinionated part of the workbook, so it gets the most explanation.
Q Score = (Pure-Play % x W1) + (Qubit Milestone Tier x W2)
+ (Government Contract Bonus x W3) + (Category Multiplier x W4)
The default weights are 35 / 25 / 20 / 20 and they sit in editable yellow cells on the Main Dashboard. Every other sheet references those cells, so if you decide pure-play exposure should weigh more than qubit milestones you change one cell and the screener re-ranks instantly.
A higher Q Score does not mean "buy this." It means the ticker is more leveraged to the quantum-thesis playbook. If quantum re-rates higher, the high-Q-Score names should respond more violently to the upside. If quantum disappoints, the same names should respond more violently to the downside. That is the structural trade-off the score is trying to expose.
Here is the intuition behind each input.
Pure-Play %. This is the share of revenue (or, for pre-revenue names, the share of operating activity) that is quantum-specific. A pure-play hardware name like IonQ or Rigetti scores 1.00. A hyperscaler like Microsoft scores under 0.05. The point is that a 10% move in the quantum addressable market means very different things for the two names.
Qubit Milestone Tier. This is a four-tier scale capturing how mature the company's hardware (or hardware partnership) is. Tier 4 is production-grade with error correction (IBM's Heron and Quantinuum's H2 sit here). Tier 3 is over 100 stable qubits (IonQ's Tempo roadmap, Rigetti's Ankaa-3, Google Willow). Tier 2 is 50 to 100 qubits or specialized hardware (D-Wave's Advantage2 annealer). Tier 1 is below 50 qubits or pre-commercial.
Government Contract Bonus. A binary flag that flips to 100 if the company has a publicly disclosed contract with a national lab, defense agency, or sovereign quantum program. The bonus is binary because the lumpy nature of government revenue does not lend itself to fine-grained scoring.
Category Multiplier. A constant per category. Pure-Play Hardware gets 100 (highest leverage). Quantum Security gets 85. Mega-Cap Platform gets 50 (quantum is a rounding error in revenue). Diversified Adjacent gets 60.
The math is intentionally simple. The point of the score is to make the trade-offs explicit, not to manufacture a hidden alpha factor. If you disagree with any of the inputs, the workbook lets you change them in one cell.
Pure-Play Hardware: The High-Beta Bucket
The four pure-play hardware names in the universe are IonQ (IONQ), Rigetti Computing (RGTI), D-Wave Quantum (QBTS), and Quantum Computing Inc (QUBT). Each runs a different qubit modality.
IonQ runs trapped-ion hardware. The trapped-ion approach delivers very high-fidelity gates at low qubit counts and is the modality favored by Quantinuum (which is privately held inside Honeywell). The 2026 roadmap centers on the 64-qubit Tempo system. IonQ has been the most consistent commercial-revenue story among the pure plays, with multi-year contracts from the Air Force Research Lab and the Department of Energy.
Rigetti runs superconducting qubits. The 84-qubit Ankaa-3 system has been the most-cited reference machine for benchmarking, and Rigetti has a long-running collaboration with the UK National Quantum Computing Centre. The challenge for Rigetti has always been moving from research-grade systems to commercially recurring revenue.
D-Wave Quantum runs quantum annealing hardware. Annealers solve a narrower class of optimization problems but solve them faster than gate-based machines at similar qubit counts. The Advantage2 system is targeted at logistics, finance, and materials-science applications. D-Wave's commercial pipeline is more diverse than the gate-based pure plays, but the addressable market is smaller.
Quantum Computing Inc runs photonic-based hardware (the Dirac series). Photonic quantum can in principle scale at room temperature, which is the structural argument for the modality. The 2026 roadmap is the earliest stage of the four pure plays.
In the screener, all four are tagged Pure-Play Hardware with a category multiplier of 100. The differentiation comes from the Qubit Milestone Tier (IonQ and Rigetti at Tier 3, D-Wave at Tier 2, QUBT at Tier 1) and the government contract flag (IonQ, Rigetti, D-Wave: Yes, QUBT: No).
Quantum Security: Software-Adjacent and Earlier Revenue
The second category is post-quantum cryptography and quantum-key distribution. The thesis here is different. You do not need a fault-tolerant quantum computer for these names to monetize. You need NIST PQC standards adoption (which has already happened), TPM and HSM vendor refresh cycles, and government mandates to rotate to quantum-resistant cryptography. Revenue can show up before the first commercially useful quantum computer ever ships.
Arqit Quantum (ARQQ) sells QuantumCloud, a symmetric-key distribution service. SEALSQ (LAES) sells post-quantum cryptography chips for IoT and TPM applications. The financial profile is closer to a small-cap cybersecurity name than to a hardware pure-play, but the screener still tags them as quantum-thesis exposure because the demand signal is structurally tied to quantum risk.
Both names score high on Pure-Play % (above 0.85) but only Tier 2 on Qubit Milestone (the milestone here is a cryptographic product release, not a qubit count). The category multiplier is 85.
Mega-Cap Platform: Survivability, Not Leverage
IBM, Alphabet, Microsoft, Amazon, and NVIDIA all have meaningful quantum programs, but none of them is a quantum stock. Quantum is single-digit percent of R&D, and well below 1% of revenue, at every one of these names. They are in the screener because they are how serious-money allocators express quantum exposure without venture-stage risk.
IBM operates the largest installed quantum fleet through IBM Quantum Network and has the most ambitious public qubit roadmap (Condor, Flamingo, Kookaburra). Google demonstrated below-threshold error correction with Willow at 105 qubits, which is the most important quantum-error-correction milestone of the cycle. Microsoft's Majorana 1 represents the most ambitious topological qubit bet in the public market. AWS Braket aggregates third-party hardware (including from IonQ and Rigetti) into a quantum-cloud service. NVIDIA's CUDA-Q and DGX Quantum stack supply the classical orchestration layer that every quantum workload needs.
For a quantum investor, the mega-caps are the place you go when you want survivability without the binary outcomes of a pure play. The screener gives them a category multiplier of 50 to reflect that. Pure-Play % is under 0.06 for all of them. The Qubit Milestone Tier is high (4 for IBM and GOOGL), but the equity does not respond to qubit news the way a pure play does, which is exactly the point.
Diversified Adjacent: The Parent-Company Play
The last category is the messiest. Honeywell (HON) is in the screener because Quantinuum, arguably the strongest trapped-ion company in the world, is a subsidiary. Atomera (ATOM) is in because its MST silicon technology is one of several enabling-tech bets that could matter for both classical and quantum semiconductors. Broadcom (AVGO) is in for QKD-capable Tomahawk switches and Cisco (CSCO) is in for quantum network switching research.
These are not quantum stocks in any meaningful direct-revenue sense. They are quantum-adjacent option positions. Category multiplier is 60. Pure-Play % is under 0.30 for all of them.
The screener flags this category exactly because most investors miss it. The Quantinuum-inside-HON setup, in particular, is one of the few ways to get trapped-ion exposure in the public market today.
How to Build the Quantum Computing Stocks Screener Excel from Scratch
If you want to construct the screener yourself rather than download the template, the build is straightforward once you know the MarketXLS function set. Every cell in the template is one of these formulas.
=QM_Last("IONQ") Live price
=MarketCapitalization("IBM") Market cap in dollars
=FiftyTwoWeekHigh("RGTI") 52-week high
=FiftyTwoWeekLow("QBTS") 52-week low
=PERatio("MSFT") Trailing P/E
=DividendYield("CSCO") Annual dividend yield
=Beta("QUBT") Beta vs S&P 500
=RSI("ARQQ") Relative Strength Index
=Sector("LAES") GICS sector
=Industry("AVGO") GICS industry
=ReturnOnEquity("NVDA") Trailing ROE
=TotalDebtToEquity("IBM") Debt-to-equity ratio
=QuarterlyRevenueGrowthYOY("IONQ") YoY quarterly revenue growth
=QuarterlyEarningsGrowthYOY("NVDA") YoY quarterly EPS growth
=GrossMargin("MSFT") Gross profit margin
=AltmanZScore("RGTI") Altman Z bankruptcy proxy
=TotalCash("IONQ") Cash and short-term investments
=TotalDebt("IBM") Total debt outstanding
=EnterpriseValue("GOOGL") Market cap + debt - cash
=Revenue("AMZN") Trailing twelve months revenue
=PayoutRatio("CSCO") Dividend payout ratio
=OneYrTargetPrice("IONQ") Consensus 1-year analyst target
Drop the ticker universe in column A of a fresh sheet, paste these formulas in the surrounding columns referencing column A, and you have the core of the Main Dashboard. The Quantum Readiness Scoring tab adds the four manual inputs (Pure-Play %, Qubit Milestone, Qubit Tier, Government Contract flag) and references the weight cells on the Main Dashboard.
The Cash Runway sheet is the one place you have to provide a manual input: the estimated quarterly burn rate. For pure plays this number lives in the 10-Q cash flow statement and changes meaningfully every quarter, so the template leaves the cell editable rather than trying to derive it from a stale screen.
You can find the full MarketXLS function library on the MarketXLS features page, and the live screener is one of about a dozen built-in templates shown on the same page.
Position Sizing Inside the Quantum Computing Stocks Screener Excel
The Main Dashboard has three input cells that drive position sizing:
- Portfolio Size: total dollars allocated to the quantum sleeve of your book.
- Max Category Allocation %: the cap on any single category (default 30%). A 30% cap on Pure-Play Hardware against a $100,000 portfolio means $30,000 of total pure-play exposure regardless of how many tickers pass the screen.
- Min Composite Score: any ticker with a Q Score below this threshold is excluded from sizing.
If you scale this up to a multi-million-dollar allocation, the cap matters more than the score. Two pure-play hardware names that both score above the threshold should share the 30% bucket, not double up to 60%. The category multiplier already pushes pure plays to the top of the Q Score ranking, so a hard cap is the right second-stage control.
A simple Excel implementation looks like this:
=IF(QScore < MinScore, 0,
MIN(MaxCategoryPct * PortfolioSize / CountByCategory,
TickerSizingTargetUSD))
The template ships with a static portfolio size and category cap in the yellow input cells. Re-allocating across the full portfolio is then a matter of updating two cells.
Cash Runway Is the Pure-Play Risk Metric
For Mega-Cap Platform names the runway question is meaningless. They self-fund quantum R&D from operating cash flow and would do so even if quantum revenue went to zero. The screener marks them N/A on the Runway tab.
For Pure-Play Hardware and Quantum Security names the runway question is the most important number in the workbook. The arithmetic is simple. Take the company's total cash, divide by an estimated quarterly burn rate (set by you on the Runway sheet), and the result is the number of quarters of self-funded operations remaining before the company has to raise capital again.
Runway (Quarters) = Total Cash / Estimated Quarterly Burn
A 4-quarter runway is a red flag. The company will have to come to market within 12 months and will almost certainly have to issue equity. A 12-quarter runway is a green light. The company can fund through at least one full hyperscaler design-cycle without dilution. Most of the pure plays in mid-2026 sit between those two numbers.
The runway tab also surfaces enterprise value, debt, and revenue from MarketXLS so you can see at a glance which names trade at the highest multiple of run-rate revenue and which are closest to break-even on cash terms.
Risks the Quantum Computing Stocks Screener Excel Cannot Solve For
Three risks the workbook deliberately does not try to score.
Commercial timeline uncertainty. Fault-tolerant quantum advantage at scale is still believed by most credible researchers to be years rather than months away. The screener does not bet on a specific arrival date. It only ranks names on relative exposure to the upside if and when that day arrives.
Modality risk. Superconducting, trapped ion, photonic, neutral atom, and topological qubits each have very different scaling paths. If one modality wins, the others lose. Picking the right pure play means picking the right modality, which is a research question, not a screening question.
Hyperscaler in-housing. Microsoft built Majorana 1 in-house. Google built Willow in-house. AWS Braket aggregates third-party hardware but could in principle build its own. If the hyperscalers decide to in-house the entire stack, the pure plays lose their largest non-government customer channel.
Read the risk-factors section of every pure-play 10-K before sizing anything. The screener orders the names. Diligence still belongs to you.
FAQ: Quantum Computing Stocks Screener Excel
What is a quantum computing stocks screener Excel?
A quantum computing stocks screener Excel is a spreadsheet workbook that lists publicly traded quantum-exposed equities, pulls live data on each (price, market cap, fundamentals, cash position), and ranks them on a methodology that captures the things screeners for other sectors miss (pure-play exposure, qubit milestone, government contracts). The MarketXLS template described in this post is a six-tab screener built around that methodology.
Which tickers belong in a quantum computing stocks screener Excel?
The reasonable universe in mid-2026 is about 15 names across four categories: Pure-Play Hardware (IONQ, RGTI, QBTS, QUBT), Quantum Security (ARQQ, LAES), Mega-Cap Platform (IBM, GOOGL, MSFT, AMZN, NVDA), and Diversified Adjacent (HON, ATOM, AVGO, CSCO). The screener lets you add or remove tickers, but those 15 capture most of the investable surface area today.
How is a pure-play quantum stock different from a quantum-exposed mega-cap?
A pure-play quantum stock derives close to 100% of its revenue or operating activity from quantum computing. A 10% move in the quantum addressable market materially repositions the equity. A quantum-exposed mega-cap (like Microsoft or NVIDIA) generates under 1% of revenue from quantum. The same 10% move in the quantum addressable market barely registers in the consolidated income statement. Pure plays carry higher leverage to the quantum thesis and higher binary risk.
Which MarketXLS formulas does a quantum computing stocks screener Excel need?
The screener uses a standard set of MarketXLS formulas: QM_Last for live price, MarketCapitalization for market cap, PERatio, DividendYield, Beta, RSI, FiftyTwoWeekHigh, ReturnOnEquity, TotalDebtToEquity, GrossMargin, AltmanZScore, QuarterlyRevenueGrowthYOY, QuarterlyEarningsGrowthYOY, TotalCash, TotalDebt, EnterpriseValue, Revenue, and OneYrTargetPrice. The full list with examples is on the Quality + Fundamentals tab of the template.
How does cash runway work in a quantum computing stocks screener Excel?
Cash runway is total cash on hand divided by estimated quarterly burn rate, expressed in quarters. The template ships with a default burn estimate per ticker (sourced from the most recent 10-Q at build time). Update the burn cell on the Runway tab as fresh 10-Qs arrive and the runway figure updates automatically. The metric matters most for Pure-Play Hardware and Quantum Security names because those companies depend on capital markets access to keep funding R&D.
Can I use the quantum computing stocks screener Excel without the MarketXLS add-in?
The sample workbook is fully usable as a static reference because the values are pre-filled. The template workbook requires the MarketXLS add-in installed in Excel because every data cell is a live function. If you do not have MarketXLS installed, you can still see the structure and methodology in the sample file, but the prices and ratios will not update.
How often should I refresh the quantum computing stocks screener Excel?
For day-to-day price moves, refresh whenever you open the workbook (Ctrl+Alt+F9 in Excel with MarketXLS installed). For the manual inputs (Pure-Play %, Qubit Milestone, Government Contract flag, Quarterly Burn), update once per quarter or whenever a material disclosure changes the picture. Most users find a weekly review of the Q Score column is plenty.
The Bottom Line
A quantum computing stocks screener Excel is not a prediction engine. It is a structured way to keep the categories straight, surface which names actually carry pure-play exposure, and track cash runway for the pre-revenue cohort. As of June 2026 the quantum story is moving from research demos to commercial milestones, government contract revenue is at the largest scale it has ever been, and hyperscalers are using their cloud platforms to aggregate third-party quantum hardware. That is a more investable backdrop than the sector has had at any point in the previous decade, but it does not change the fact that almost every pure play is still pre-profit and capital-markets dependent. The screener is built to keep both of those truths in view at once.
Download the templates:
- - Pre-filled with illustrative June 2026 data
- - Live-updating formulas
Explore more screeners and the full MarketXLS function library on the MarketXLS website, and if you want a walkthrough of how an Excel-native quant workflow fits into a multi-asset portfolio, book a demo.
This article is for educational purposes only and is not investment advice. The screener, scoring methodology, and risk notes are illustrative. Always do your own research and consult a licensed financial advisor before making any investment decision.
