Beyond the Qubit

What if one of the most important companies in quantum is not the one building the qubits, but the one helping the industry see what is going wrong around them?

In this episode, I break down my key learnings from the QuantaMap interview and why I think diagnostics could become one of the most strategic layers in quantum computing. One of the biggest bottlenecks may not be qubit count itself. It may be the invisible defects around it: tiny magnetic fluctuations, microscopic heat leakage, material imperfections, and unwanted current paths that disturb the quantum system.

This episode is for investors, founders, and anyone trying to understand how value could build around the quantum stack. In semiconductors, companies like KLA became essential because advanced chips could not scale without metrology and inspection. Quantum may face the same reality, possibly even more strongly, because these systems are so sensitive and because invasive measurements can disturb the system itself.

That is what makes this discussion so interesting. Scaling quantum is no longer just about building a hero experiment in a lab. It is about repeatability, yield, reliability, and eventually semiconductor-style manufacturing. If that shift happens, the diagnostic layer around quantum could become far more important than many people expect.

💡 In this episode, we cover:

• Why diagnostics may become a strategic layer in quantum computing

• Why invisible defects around qubits matter so much

• How QuantaMap’s SQUID-based approach helps reveal hidden physical disturbances

• Why quantum inspection is harder than classical chip inspection

• Why repeatability, yield, and reliability will matter more as quantum scales

• Why QuantaMap could become part of a KLA-like infrastructure layer for quantum

• The biggest risks, including technology exposure and customer adoption

• Why measurement may become more valuable as computing gets more complex

Chapters

00:00 Why quantum diagnostics matters

01:27 Why quantum is more complex than classical chips

02:50 What QuantaMap actually does

04:01 What a SQUID is

04:42 Why traditional tools miss the real problem

06:55 Why this matters for investors

08:17 Could QuantaMap become the KLA of quantum?

09:34 The biggest risks for QuantaMap

11:25 What would increase conviction

13:23 The one line investors should remember

Share this episode with someone investing in or building in quantum, and subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimers: This is not investment advice. I do this under my personal name and do not represent any company.

What if the real bottleneck in quantum is not building the chip, but learning why it fails?

In this episode, I unpack the key learnings from Part 2 of my deep dive with Johannes Jobst, CEO of QuantaMap. One of my biggest takeaways is that quantum may need its own process control and diagnostics layer before the industry can truly scale. Building a few quantum chips in a lab is one thing. Building thousands of high quality chips with repeatable performance and acceptable yield is something very different.

This episode is for investors, founders, and anyone trying to understand what it will take for quantum to move from lab to fab. In semiconductors, scaling did not happen through transistor innovation alone. It also required decades of progress in inspection, metrology, yield learning, process control, and manufacturing feedback loops. Quantum is only beginning that journey.

That is what makes this conversation so important. If yield remains low and failure analysis stays slow, scaling becomes much harder. Without a real diagnostics layer, every failed chip stays a mystery instead of becoming a learning cycle. The companies that help the industry learn, improve, and manufacture quantum chips reliably at scale may end up becoming one of the most important layers in the value chain.

💡 In this episode, we cover:

• Why diagnostics may be a critical missing layer in quantum manufacturing

• Why quantum scaling needs more than better qubits

• How cryogenic inspection changes what chipmakers can actually learn

• Why room-temperature measurements often miss the real problem

• How process control, yield learning, and feedback loops could shape quantum manufacturing

• Why “business as usual” is still one of the biggest bottlenecks in the market

• How QuantaMap thinks about becoming a deeply embedded diagnostics layer

• What investors should watch as quantum moves from lab to fab

  
  

Chapters

00:00 Why chip diagnostics matters in quantum

00:44 How QuantaMap’s cryogenic measurement works

04:27 Why multimodal imaging matters

06:15 Why process control comes later

08:09 Why cryogenic scanning matters

15:29 Business as usual is the real competition

20:42 Barriers to entry and customer lock-in

23:44 The ASML-style ambition

28:57 Diagnostics as a service and tool sales

34:44 Why timing from lab to fab matters

46:53 What would increase conviction

51:13 Why QuantaMap matters in the value chain

🔗 Resources / Links 🎧 Listen to all episodes →

https://open.spotify.com/show/7HZpSCz1w7a782e1B26MYA?si=JjJ7gTAfRGaZwnYwMa65mQ

Share this episode with someone investing in or building in quantum, and make sure to subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimers: This is not investment advice. I do this under my personal name and do not represent any company.

What if one of the biggest winners in quantum is not the company building the qubits, but the one helping everyone understand what is going wrong inside them?

In this episode, I unpack the key learnings from my deep dive with Johannes Jobst, CEO of QuantaMap. The deeper I go into quantum computing, the more I think this industry will become obsessed with measurement. Most people focus on the race for better qubits, higher fidelity, and larger systems. But after this conversation, I am no longer sure that is the full story.

This episode is for investors, founders, and anyone trying to understand how the quantum value chain may evolve. One of the biggest bottlenecks may not just be building quantum chips. It may be inspection, metrology, defect detection, process supervision, and understanding the subtle material imperfections and microscopic noise sources that undermine coherence, repeatability, and yield.

That is what makes this conversation so important. In classical semiconductors, advanced manufacturing scaled because an entire ecosystem was built around measurement, validation, and process control. Quantum does not yet have that same mature inspection layer. If that becomes a core bottleneck, the companies that help the industry see, diagnose, and improve quantum systems may become just as important as the companies building the hardware itself.

💡 In this episode, we cover:

• Why measurement may become one of the most important layers in quantum computing

• Why quantum chip inspection is still an underbuilt part of the stack

• How subtle material defects and microscopic noise sources affect performance

• Why coherence, repeatability, and yield depend on better diagnostics

• How the quantum industry may shift from building systems to validating and controlling them

• Why inspection, metrology, and process supervision could become strategically valuable

• What investors should learn from the semiconductor industry’s measurement ecosystem

• Why quantum may become not just a computing revolution, but a measurement revolution

  
  

Chapters

00:00 Why investors should care about QuantaMap

01:48 Johannes Jobst’s background in physics and semiconductors

14:54 What defects really matter in quantum chips

17:58 Why measurement matters more in quantum

25:44 Where chip measurement fits in the quantum stack

33:04 Process control, defects, and root cause analysis

43:32 Yield loss and performance bottlenecks in quantum

44:56 Why volume inspection could become critical

🔗 Resources / Links 🎧 Listen to all episodes → UCibVGKTQwLCsj0hBgrgWDpA

Share this episode with someone investing in or building in quantum, and make sure to subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimers: This is not investment advice. I do this under my personal name and do not represent any company.

Could the real value in quantum sit above the hardware?Because after two hours with quantum founders, the real question is not only what they are building. It is also how that changes the value chain.In this episode, Henny Crauwels interviews me after my deep dive with ParityQC to unpack the biggest lessons from that conversation. One takeaway stood out: the most interesting quantum company may not be the one with the most qubits. It may be the one that helps everyone else get more out of their qubits.This episode is for investors, founders, and anyone trying to understand how quantum computing could evolve as a market. We look at why architecture matters, how ParityQC’s approach could reduce bottlenecks in today’s systems, and why enabling layers may matter so much in a market where it is still unclear which hardware path will win.That is what makes this format valuable. The deep dives explain the technology. The key learnings connect it back to markets, business models, strategy, and where value may actually accrue across the stack.

• Why quantum value may not all sit in hardware
• What ParityQC is actually doing in simple terms
• Why architecture could become a critical layer in the quantum stack
• How enabling companies may have lower single-platform risk
• Why early monetization matters in quantum
• What ParityQC’s IBM benchmark really shows, and what it does not
• Which KPIs matter most for investors following ParityQC
• The biggest risks to watch, including adoption, neutrality, and access to capital

💡 In this episode, we cover:Chapters00:00 Key takeaways and disclaimers

01:23 Why architecture changed my view of quantum

03:58 What ParityQC actually does

06:36 What the IBM benchmark proves, and what it does not

09:39 Could ParityQC become the ARM of quantum?

11:52 Where value may be captured in the quantum stack

14:17 Why enabling companies may be more attractive early

19:40 The investor KPIs I would track

22:15 What would increase my conviction

23:36 The biggest risks for ParityQC

26:48 What this says about the broader quantum market🔗

Resources / Links Listen to all episodes: SpotifyBeyond the QubitShare this episode with someone investing in or building in quantum, and make sure to subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer: This is not an investment advice. This post is shared on a personal basis, and I do not represent any company.

What if the company that captures the most value in quantum is the one that helps everyone else perform better?

In this episode, I go deeper with Magdalena Hauser and Wolfgang Lechner of ParityQC to explore a very different way of thinking about value in quantum computing. A lot of the discussion still centers on hardware alone: more qubits, better fidelity, bigger systems. But ParityQC is making a different bet, one built around architecture, IP, and enabling software.

This conversation is for investors, founders, and anyone trying to understand where value may really build across the quantum stack. We unpack ParityQC’s core idea of representing relative information instead of the information itself, why that could matter for connectivity and error correction, and why their business model looks closer to an architecture company than a full stack hardware player.

That is what makes this episode so interesting. It is not just about physics. It is about business model, defensibility, IP, and what it means to control a critical layer of the stack in a market where not every winner will own the full machine.

💡 In this episode, we cover:

• How ParityQC’s parity transformation changes the way quantum information is represented

• Why relative information could help with connectivity, programmability, and redundancy

• How ParityQC thinks about error correction differently

• Why the company licenses IP and enabling software instead of building full stack hardware

• Why their model looks closer to ARM than a traditional quantum hardware company

• How ParityQC monetizes through licensing and software

• Why profitability matters so much in today’s quantum market

• What investors should watch if they want to track whether the model is working

Chapters00:00 Why ParityQC’s architecture matters

00:48 The parity transformation explained

04:27 How ParityQC thinks about error correction

07:47 Patents, IP, and barriers to entry

13:00 How ParityQC makes money

16:43 Why governments are buying early quantum systems

27:34 Why ParityQC wants to be the ARM of quantum

29:29 Profitable since 2023

33:13 The KPI investors should watch

42:08 Why they are excited about the future

🔗 Resources / Links

• Explore ParityQC and their work in quantum architecture → https://parityqc.com/

• Magdalena Hauser on LinkedIn → https://www.linkedin.com/in/magdalena-hauser42/

• Wolfgang Lechner on LinkedIn → https://www.linkedin.com/in/wolfgang-lechner-2b36b634/

• Listen to all episodes: https://open.spotify.com/show/7HZpSCz1w7a782e1B26MYA

Share this episode with someone investing in or building in quantum and make sure to subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer: This post is shared on a personal basis and I do not represent any company.

What if the real breakthrough in quantum computing is not just better qubits, but a better way to use them?

In this episode, I explore why architecture may be one of the most overlooked layers in quantum computing with Magdalena Hauser and Wolfgang Lechner of ParityQC. Their latest result, implementing a 52-qubit Quantum Fourier Transform on an IBM Quantum Heron processor, suggests that progress may not only come from hardware improvements, but also from smarter architecture and compilation.

This episode is for investors, founders, and anyone trying to understand where value may build across the quantum stack. If ParityQC is right, the winners in quantum may not only be the companies building the machines. They may also be the companies that make those machines more useful, more scalable, and more efficient.

That is what makes this conversation so interesting. It shifts the question from who has the best hardware to who has the best architecture for turning hardware into real performance.

💡 In this episode, we cover:

• Why ParityQC believes architecture is a core layer of value in quantum computing

• Why the Quantum Fourier Transform is such an important benchmark

• How ParityQC and IBM reached a 52-qubit QFT result

• Why this result is about more than hardware alone

• How architecture and compilation can improve real quantum performance

• Why ParityQC’s approach is designed to work across multiple hardware platforms

• Why removing swaps matters in quantum computing

• Why investors may need to look beyond hardware to understand where value will accrue

  
  

Chapters

00:00 ParityQC and why investors should care

01:49 Why Quantum Fourier Transform matters

03:00 The 52-qubit QFT breakthrough explained

06:57 Does this accelerate the quantum timeline?

11:16 Why ParityQC works across hardware platforms

14:02 How ParityQC removes swaps

17:04 Why architecture may capture more value

24:04 The origin of ParityQC’s architecture

30:09 How ParityQC works in simple terms

🔗 Resources / Links

• Explore ParityQC and their work in quantum architecture → https://parityqc.com/

• Magdalena Hauser on LinkedIn → https://www.linkedin.com/in/magdalena-hauser42/

• Wolfgang Lechner on LinkedIn → https://www.linkedin.com/in/wolfgang-lechner-2b36b634/

• Listen to all episodes: https://open.spotify.com/show/7HZpSCz1w7a782e1B26MYA

  
  

Share this episode with someone investing in or building in quantum and make sure to subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer: This post is shared on a personal basis and I do not represent any company.

In Part 3 of this conversation, Frank Dekker reflects on one of the biggest takeaways from his discussion with Olivier Ezratty: great science alone does not create a winning quantum ecosystem. Europe has deep talent, strong research, and serious technical capability, but turning that into globally relevant companies is a different challenge.

This episode is for investors, founders, policymakers, and anyone trying to understand what it will really take for Europe to compete in quantum. The conversation goes beyond technology and looks at the harder questions around energy, coordination, ecosystem building, and long term strategy.

That is what makes Olivier’s perspective so valuable. He is not only trying to understand where quantum is going. He is trying to improve the odds that Europe builds something meaningful around it.

💡 In this episode, we cover:

• Why strong quantum talent does not automatically create strong quantum companies

• Why the Quantum Energy Initiative matters for the future economics of the industry

• Why energy and power costs could shape who scales and who can deploy

• Why ecosystem building takes more than great technology

• How Olivier thinks about strengthening the French and European quantum landscape

• Why Europe needs stronger links between research, capital, policy, and industry

• Why coordination may matter as much as technical progress

• What Europe needs most right now to improve its chances in quantum

Chapters

00:00 Introduction to Olivier Ezratty

00:48 Olivier’s background in software, Microsoft, and startups

04:07 How curiosity led him into science and quantum

05:52 From tech events to explaining quantum publicly

10:25 Building a 1,500-page quantum guide

13:36 Olivier’s goals for the next five years

14:18 Why Europe has talent but not enough quantum companies

35:39 Quantum Energy Initiative and why energy matters early

37:53 The hidden classical costs behind useful quantum computing

39:05 Why quantum needs a system-level engineering mindset

41:31 Quantum matter, new materials, and Europe’s next opportunity

🔗 Resources / LinksFollow Olivier Ezratty on LinkedIn: https://www.linkedin.com/in/ezratty/

Listen to all episodes: https://open.spotify.com/show/7HZpSCz1w7a782e1B26MYA

Share this episode with someone following Europe’s quantum future. Subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer: This post is shared on a personal basis, and I do not represent any company.

Quantum computing has a hype problem. But the real challenge is much harder than most people think.

In Part 2 of this conversation, Frank Dekker continues his deep dive with Olivier Ezratty and gets into what real progress in quantum actually looks like. One of the clearest takeaways is that every step forward can create a new bottleneck. Solve one problem, and another appears right behind it.

This episode is for investors, founders, and anyone trying to understand why scaling quantum computing is so difficult. The challenge is not just adding more qubits. It is building a system that can handle noise, error correction, control complexity, and energy demands, while still producing something useful at a cost the market can bear.

That is what makes this conversation so valuable. Olivier brings a grounded perspective that goes beyond exciting narratives and focuses on what it really takes to make the whole system work.

💡 In this episode, we cover:

• Why quantum computing has a hype problem

• Why solving one problem often creates another

• Why scaling quantum is not just about adding more qubits

• How noise and control complexity slow real progress

• Why error correction creates major system overhead

• Why energy demands matter in the future of quantum computing

• Why quantum is a full stack challenge across physics, engineering, software, control, and economics

• Why the winners in quantum will be the teams that can make the whole system work

  
  

YouTube Chapters

00:00 Introduction and the core question

00:52 Does a quantum computer really work?

05:45 Is a quantum computer really a computer?

10:39 Quantum memory, QRAM, and communication

14:28 How AI helps quantum and where it still does not

19:38 Which quantum technology platform will win?

27:20 Why every scaling solution creates a new problem

40:05 Quantum Energy Initiative and why energy matters

52:49 The three expensive classical costs behind FTQC

56:10 Quantum engineering and the bigger opportunity in quantum

🔗 Resources / Links

Follow Olivier Ezratty on LinkedIn: https://www.linkedin.com/in/ezratty/

Listen to all episodes: https://open.spotify.com/show/7HZpSCz1w7a782e1B26MYA

Share this episode with someone following quantum computing seriously.

Subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

📌 Disclaimer: This post is shared on a personal basis and I do not represent any company.

Why is quantum computing still so hard to explain clearly, even for smart investors?

In this episode of Beyond the Qubit, Frank Dekker sits down with Olivier Ezratty, one of the most respected independent voices in quantum technology. Olivier shares how he went from software engineering and Microsoft to becoming a key educator, researcher, and bridge builder across the quantum ecosystem.

This conversation is for investors, founders, and deep tech professionals who want a clearer view of quantum computing without the hype. They discuss what sparked Olivier’s obsession with the field, why so many people still explain quantum poorly, and what it really takes to understand the space across hardware, software, physics, and market reality.

💡 In this episode, we cover:

• How Olivier Ezratty became one of the most trusted independent researchers in quantum computing

• Why early D-Wave claims pushed him to study quantum more seriously

• How Understanding Quantum Technologies grew into a major free resource

• Why investors need to connect physics, hardware, and software to understand the market

• What Europe gets right in quantum, and where it still struggles commercially

• Why the Quantum Energy Initiative matters for the future of the industry

• How long-form research, public learning, and sharing knowledge can build real influence in deep tech

• What Olivier sees as the biggest bottlenecks over the next five years

Chapters

00:00 Introduction to Olivier Ezratty

04:09 Olivier’s background from software to Microsoft to deep tech

08:13 Why Olivier started creating long-form knowledge resources

33:09 What first sparked his interest in quantum computing

37:20 Olivier’s goals: quantum energy, teaching, and Europe

40:07 Why Europe needs both strong research and strong startups

50:17 The biggest bottlenecks for the next five years

🔗 Resources / Links

Follow Olivier Ezratty on LinkedIn: https://www.linkedin.com/in/ezratty/

Listen to all episodes: https://open.spotify.com/show/7HZpSCz1w7a782e1B26MYA

Share this episode with someone investing in or building in quantum and make sure to subscribe or follow Beyond the Qubit for more conversations on quantum technology, markets, and investing.

DeepMind helped transform AI by using games as a training ground.

Evert van Nieuwenburg wants to build the European DeepMind for quantumcomputing.

In my conversation with Evertvan Nieuwenburg on Beyond the Qubit, one idea stood out:

What if games are not just a way to explain quantum computing, but a way tounlock it?

Thatsounds playful.

Butthe ambition is serious.

DeepMindshowed that games could be much more than entertainment.They became structured environments for learning, experimentation, search, anddiscovery.

Evert’svision is that quantum computing may need something similar.

Notjust better hardware.

Notjust more qubits.

Notjust lower error rates.

It may also need a better playground for building intuition.

Becausethe space of possible quantum circuits and quantum algorithms isenormous.

Mostof it is noise.

Usefulstructure is rare.

Andintuition is hard to build.

Thatis where quantumgames become interesting.

Gamescreate structure. They give people rules, feedback, andgoals. And when a hard problem becomes game-like, it can become easier forhumans to explore and potentially easier for AI systems to learn from too.

Thatis the part of the conversation I keep coming back to.

Evertis not talking about games as a side project for outreach.

He is pointing at a bigger idea:

Europe may have a chance to build its own DeepMind for quantum computing

notby copying AI exactly,

butby creating the structured environments that help peopleand machines discover what matters in quantum.

Thatis a bold vision.

Andbold visions are usually where the interesting companiesbegin.

#QuantumComputing #QuantumTechnology #AI #Gaming #DeepTech@evertvannieuwenburg

📌 Disclaimer:This post is shared on a personal basis and I do not represent any company