🎄 All I want for Christmas is a universal fault-tolerant quantum computer: Photonics could make that wish come true

Happy Monday! Here’s what’s inside this week’s newsletter:

• Deep dive: Photonic quantum computing as a path toward fault-tolerance, explaining why photons are strong qubit candidates, how linear-optical and measurement-based approaches evolved, and recent progress.

• Spotlights: Cloudberry launches Europe’s first semiconductor venture fund, and a clear technical overview explains where 2.5D packaging stands today as interposers, bridges, and cost pressures reshape advanced integration.

• Headlines: Semiconductor manufacturing and edge AI updates, steady progress in quantum error correction and scaling, new momentum in photonics and silicon photonics testing, and major data center expansions.

• Readings: Shifting reliability risks in semiconductors, quantum advances in simulation and scaling, new photonic materials and markets, neuromorphic memory and security systems, and Europe’s data center and cloud constraints.

• Funding news: A small set of rounds dominated by public grants under Canada’s Quantum Champions Program, with very limited venture activity and only two disclosed venture rounds across photonics and analog computing.

• Bonus: QuantumDiamonds brings quantum sensing into semiconductor production, showing how diamond-based magnetic field imaging can enable non-destructive testing of advanced 2.5D and 3D chip packages at scale.

We wish you wonderful holidays and you’ll hear from us in January! 🎄❤️

This week’s deep dive is written by Florian Burger, our first guest writer. Florian worked on single-photon sources in silicon during his PhD at the Max Planck Institute of Quantum Optics and TU Munich. He is now exploring new professional avenues in quantum technologies.

If you would like to contribute as a guest writer, feel free to message Emily Eisenblätter.

Photonic Quantum Computing

Among the physical implementations of quantum computing, photonics is the sleeping giant. Sleeping because most well-known players have zeroed in on superconducting qubits (e.g. IBM, Google and Rigetti) or trapped ions (e.g. IonQ and Quantinuum). A giant nevertheless, given that photonic quantum computing startup PsiQuantum has raised over $2.3 billion, more than any other quantum computing startup and clear evidence of the great hopes placed in the technology.

Photons are ideal qubits – almost

All-optical quantum computers encode quantum information in photons and perform operations directly on these photons. Photons are practically noise-free as they do not interact strongly with each other or with most matter. They have several degrees of freedom such as polarization, frequency, path and time-bin available to physically encode a qubit.

Single photons can be reliably created in a variety of ways and efficiently manipulated using so-called linear optics components such as phase plates and (polarizing) beam splitters–standard components that are found in any optics lab. Single-photon detectors with detection efficiencies >80 % and negligible dark count rates have been commercially available for some years. Photonic integrated circuits (PICs), which can be fabricated using the same mature tools as electronic ICs, enable straightforward scaling of optical quantum computers.

A new paradigm paved the way, but it came with a (photon) price tag

The central difficulty of all-optical quantum computing is to realize entangling gates, e.g. a controlled-NOT (CNOT) gate, as they require two photonic qubits to interact–something photons normally do not do. This is the flip side of the photon’s weak interaction with the environment and a trade-off faced by all physical qubits. In principle, non-linear materials can be used to manipulate one photon conditional on the presence of another photon. However, there is another tradeoff: The stronger the non-linearity, the higher the absorption in the material, leading to photon loss.

Two seminal proposals in 2001 offered a clever workaround:

1. A CNOT gate that only uses linear optics components but requires two additional photons, which are destroyed in the process, and is fundamentally nondeterministic (Knill, Laflamme and Milburn; KLM). This means that the gate only works on average 1/16^th of the time. However, a measurement on the additional two photons makes it possible to determine in which instances it has worked. 

2. A paradigm for quantum computation in which only single-qubit measurements are performed on a so-called cluster state of many entangled qubits, that is prepared beforehand (Raussendorf and Briegel).

These two innovations paved the way for linear optical quantum computing and measurement-based quantum computing (MBQC), respectively. Since 2001 a tremendous amount of work has been done to reduce the photon overhead from roughly 10,000 photons per CNOT gate in initial concepts to around 100 photons today. In 2021, scientists at PsiQuantum proposed another update to the paradigm, called fusion-based quantum computation (FBQC), that increases the threshold of tolerable photon loss to 2.7 %.

Theorists have lowered the hurdles, startups are racing to jump them

These theoretical improvements on the one side and advances in PIC fabrication, packaging as well as single-photon detection on the other have made photonics a serious contender to other quantum computing platforms. Startups such as PsiQuantum and Xanadu keep pushing the envelope by creating CMOS-compatible processes for fabricating photonic quantum processors together with commercial foundries. New players with significant expertise in deterministic single-photon generation such as Quandela and Sparrow Quantum are pushing into the market as efficient sources of indistinguishable photons have been recognized as a key differentiator to achieving fault-tolerance.

These strong players as well as the fundamental advantages of photonic quantum computing such as straightforward scalability, moderate cryogenic requirements and inherent modularization and networking capabilities make photonic quantum computing a technology worth watching in 2026.

^{_{References and further reading: M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information: 10th Anniversary Edition. New York: Cambridge University Press, 2011; J. L. O’Brien, “Optical quantum computing,” Science, vol. 318, no. 5856, pp. 1567–1570, Dec. 2007; E. Knill, R. Laflamme, and G. J. Milburn, “A scheme for efficient quantum computation with linear optics,” Nature, vol. 409, pp. 46–52, Jan. 2001; R. Raussendorf and H. J. Briegel, “A one‑way quantum computer,” Phys. Rev. Lett., vol. 86, no. 22, pp. 5188–5191, May 2001; T. Rudolph, “Why I am optimistic about the silicon‑photonic route to quantum computing,” APL Photonics, vol. 2, no. 030901, Mar. 2017; S. Bartolucci et al., “Fusion‑based quantum computation,” Nat. Commun., vol. 14, Art. no. 912, Feb. 2023; PsiQuantum team, “A manufacturable platform for photonic quantum computing,” Nature, vol. 641, pp. 876–883, May 2025; H. Aghaee Rad et al., “Scaling and networking a modular photonic quantum computer,” Nature, vol. 638, pp. 912–919, Feb. 2025.}}

⚛️ Cloudberry launches Europe’s first semiconductor venture fund (Cloudberry)

“Cloudberry, a venture capital firm based in Helsinki and London, today announced the launch of Europe’s first semiconductor venture fund with an initial close of €30 million. The fund invests in companies advancing the technological frontier with semiconductors, photonics and advanced materials to advance compute, connectivity, sensing and power.”

🦾 What’s Next for 2.5D Packaging? (SemiEngineering)

2.5D packaging is evolving across several paths: more capable silicon interposers and lower-cost alternatives.

• Silicon interposers are getting thicker and more complex, driven by AI, HBM, and wider interfaces. More metal layers improve routing and power delivery but raise cost, warpage, and yield challenges.

• Active interposers are emerging, integrating power management, signal conditioning, memory, or even photonics. They enable tighter integration but significantly increase cost, test complexity, and yield risk.

• Organic and glass interposers aim to reduce cost. Organic options are advancing but struggle with fine pitches and HBM integration. Glass is promising but likely post-2027.

• Silicon bridges are intended to reduce cost by replacing full silicon interposers, but assembly alignment and yield challenges have so far prevented these savings from materializing.

Bottom line: Silicon interposers still dominate today. Cost pressure is pushing the ecosystem toward organic materials and bridges, but yield and integration challenges must be solved before they can scale.

We recommend this reading for a clear, technical overview of where 2.5D packaging stands today and which constraints will matter most going forward.

Last week’s headlines featured semiconductor manufacturing tools and edge AI updates, steady progress in quantum error correction and scaling, new activity in photonics and silicon photonics testing, major data center expansions and strategy shifts, sovereign cloud debates in Europe, and fresh moves in AI models and funding.

🦾 Semiconductors

Nvidia is reportedly weighs ramping up H200 production to meet surging demand in China (TechCrunch)

Toshiba to accelerate semiconductor design innovation with Siemens’ EDA software (Siemens)

Vishay Intertechnology Introduces Thin Film Chip Fuses With Fast and Very Fast Acting Performance (Vishay Intertechnology)

Lattice enhances sensAI solution stack with edge AI performance, efficiency, and ease of use (Lattice Semiconductor)

Rigaku launches ONYX 3200 for Semiconductor Manufacturing (Rigaku)

Rapidus announced new AI-agentic design tools optimized for its 2nm manufacturing process (Rapidus)

⚛️ Quantum

Riverlane hardware decoder enables real-time quantum error correction (The Quantum Insider)

IonQ study finds linked quantum computers can beat bigger single systems (The Quantum Insider)

SQC study shows silicon-based quantum processor can scale without loss of fidelity (The Quantum Insider)

Xanadu Fault Tolerant Quantum Algorithms For Cancer Therapy (Quantum Zeitgeist)

Quantum technology signals new frontier for the gaming industry (The Quantum Insider)

⚡️ Photonic

LLNL researchers break speed-scale barriers in 3D nanofabrication with new meta-optics platform (Lawrence Livermore National Laboratory)

AOI Introduces New Ultra High-Power Semiconductor Laser to Support Silicon Photonics and CPO (AOI)

NTT Tests Optical Switching to Manage Data Center Loads (IEEE Spectrum)

Quantum Computing Inc. CEO Huang to Lead $40M-Funded Photonics Roadmap (Quantum Zeitgeist)

FormFactor acquires Keystone Photonics to boost silicon photonics testing (Investing.com)

💥 Data Centers

NTT gains council approval for 482 MW data center campus in Nierstein, Germany (Data Center Dynamics)

Oracle says it might let customers bring their own hardware into its data centers (Data Center Dynamics)

PIMCO closes record-breaking European data center fund (PERE News)

Qualcomm’s Strategic Pivot: Data Center Ambitions Take Center Stage (ad-hoc-news)

☁️ Cloud

Airbus is looking for a sovereign EU cloud (heise)

SAP Leads the Way in Sovereign Cloud (SAP)

🤖 AI

Amazon reportedly in talks to invest $10B in OpenAI as circular deals stay popular (TechCrunch)

Nvidia bulks up open source offerings with an acquisition and new open AI models (TechCrunch)

NVIDIA debuts Nemotron 3 family of open models (NVIDIA)

OpenAI is reportedly trying to raise $100B at an $830B valuation (TechCrunch)

This reading list covers shifting reliability risks in semiconductors, quantum breakthroughs in simulation and scaling, new materials in photonics, neuromorphic memory and security systems, Europe’s data center constraints, and cloud and AI market projections.

🦾 Semiconductors

Reliability risks shift to the materials stack (SemiEngineering) (21 mins)

Global Semiconductor Equipment Sales Projected a Record of $156 Billion in 2027 (SEMI) (13 mins)

Global Pure Foundry Market Share: Quarterly (Q3 2025) (Counterpoint Research) (5 mins)

⚛️ Quantum

Inside SQC’s research on a key quantum scaling problem (The Quantum Insider) (9 mins)

NISQ Computers Achieve Excited-State Calculations for Challenging Condensed Matter Problems (Quantum Zeitgeist) (12 mins)

Quantum Monte Carlo Library Achieves Highly Accurate Electronic Structure (Quantum Zeitgeist) (7 mins)

⚡️ Photonic

PI’s latest 6-axis alignment system, PICs, and photonics wafer probing (EngineerLive) (3 mins)

New material on the block: Barium titanate for silicon photonics (Laser Focus World) (9 mins)

Silicon Photonics Market Size – By Product, By Component, and By Application, Growth Forecast, 2026 – 2035 (Global Market Insights) (3 mins)

🧠 Neuromorphic

Hybrid GNN–LSTM defense with differential privacy and secure multi-party computation for edge-optimized neuromorphic autonomous systems (Nature Scientific Reports) (57 mins)

Accelerated Training Enables Neuromorphic Photonic Computing for Arbitrary Memory Pattern Classification (Quantum Zeitgeist) (12 mins)

Ion-doped organic transistors power neuromorphic memory systems (Bioengineer.org) (5 mins)

Neuromorphic computing meminductor achieves replicating amoeba behaviour with charge-dependent inductance (Quantum Zeitgeist) (12 mins)

💥 Data Centers

What Ireland’s Data Center Crisis Means for the EU’s AI Sovereignty Plans (AlgorithmWatch) (24 mins)

Amazon data centers aren’t raising your electricity bills—Here’s the data (About Amazon) (12 mins)

☁️ Cloud

Cloud market: Gartner forecasts trillion US dollars by 2027 (heise) (10 mins)

🤖 AI

From experiment to infrastructure: what’s next for AI? (Sifted) (5 mins)

The AI Kill Switch: Dangerous Chinese Open Source (CEPA) (8 mins)

Last week included a small set of rounds, with most activity coming from grants under Canada’s Quantum Champions Program. Venture activity was limited, with only two disclosed venture rounds, one in photonics and one larger round in analog computing.

QuantumDiamonds develops quantum-sensing-based semiconductor inspection systems for advanced chip testing and is now scaling this technology through a planned €152M production facility in Munich.

Technology

Its QDM systems use nitrogen-vacancy (NV) centers in diamond, atomic-scale defects that act as quantum sensors for magnetic fields, to detect magnetic fields created by electrical currents flowing inside semiconductor devices and advanced chip packages. Because electrical currents generate magnetic fields, this allows the systems to trace where current flows inside a chip non-destructively, meaning the package does not need to be opened. The measurements are performed with micrometer-scale spatial precision and within seconds, even in complex 2.5D and 3D architectures such as through-silicon vias (TSVs), microbumps, and chiplets. This provides layer-specific insight into current paths in advanced packages that are difficult to access with conventional testing approaches.

Traction

QuantumDiamonds has completed proof-of-concept projects with 9 of the 10 largest chip manufacturers globally, with initial deployments in Europe and further installations planned for Q1 2026 in the United States and Taiwan.

Production Facility

The company announced a €152M investment plan to establish the world’s first production facility for advanced quantum-based chip testing systems in eastern Munich. The site is expected to receive tens of millions of euros in public support from the German federal and Bavarian governments under the European Chips Act. The facility supports the transition from research and pilot deployments to global production and is positioned as a strategic asset within Europe’s semiconductor ecosystem.

Last week, we highlighted a paper from QuantumDiamonds presenting their first real-world demonstration of quantum diamond microscopy on an advanced InFO-PoP chip failure, which may also be of interest in this context.

Sources: QuantumDiamonds – About Us (QuantumDiamonds), QD Plans €152 Million Investment in Next-Gen Quantum-Based Chip Inspection Facility in Munich, Germany (The Quantum Insider)

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