Superpositions Studio

Practical quantum platform for industry.
Learn: when quantum wins, when classical wins, and how to choose
Benchmarks • tutorials • use cases • insights
Try free

[Superpositions Studio @SuperpositionsS]

Most optimization teams are asking the wrong question.

It’s not “Is quantum better?”

It’s:
Where might it already help — inside the workflow?

We built Superpositions Studio to benchmark quantum vs classical on real industrial tasks.

Follow for practical quantum insights.

[Superpositions Studio @SuperpositionsS]

The World Cup is on. 48 teams, 104 games, and behind every team there's a room full of analysts trying to figure out the right strategy to win.

At first glance, quantum tech and football seem like they're from completely different universes. But right now, clubs and national squads are constantly facing the same optimization challenge: picking a lineup from a squad of 25+ players while accounting for injury risk, opponent patterns, fitness data, and set-piece roles. Already sounds like a quantum-flavored problem.

Classical algorithms handle it fine at small scale. Add contract constraints, suspension rules, travel load, and opponent-specific game plans, and the search space stops looking like a spreadsheet and starts feeling like a combinatorial nightmare.

QAOA (Quantum Approximate Optimization Algorithm) and quantum annealing are built for exactly this. Nobody's running QPUs in a changing room yet. But formulating the problem and running a real experiment feels like a genuinely interesting thing to do while the matches are on.

And you actually can run a small experiment right now, while watching your favorite team, with Superpositions Studio. First month free.

https://t.co/ANwqHk3b0U
#FWC26 #FIFAWorldCup #WeAre26 #QuantumComputing

[Superpositions Studio @SuperpositionsS]

A lot of what circulates about quantum computing is either too optimistic or too dismissive. Here's a quick fact-check. 

MYTH: Quantum computers will replace classical ones.
REALITY: They won't. Every quantum pipeline starts and ends with classical infrastructure. The question is always: does adding a quantum step improve your specific outcome?

MYTH: You need a physics PhD to work with quantum.
REALITY: You need to be able to describe your problem. The tooling has caught up. Most of the complexity — algorithm selection, circuit generation, hardware dispatch — can be automated.

MYTH: Quantum advantage is 10-20 years away.
REALITY: For general-purpose computing, probably. For specific structured problems — certain optimization tasks, some classification regimes, molecular simulation — meaningful results are available today on simulators and near-term QPUs.

MYTH: Bigger qubit count = more powerful computer.
REALITY: Error rates, connectivity, and circuit depth matter as much as qubit count. A 20-qubit low-error system can outperform a 100-qubit high-noise one on practical tasks.
The useful framing: quantum computing is a specialized tool. The question is whether your problem has the right structure for it.

#QuantumComputing #TechMyths #DeepTech #QuantumML

[Superpositions Studio @SuperpositionsS]

The most surprising thing in last week’s Superpositions Studio usage data? Breast cancer classification became the most-run experiment on the platform.

It makes sense in hindsight. Healthcare has exactly the kind of problem where hybrid quantum approaches show real promise: classification tasks with small, noisy datasets where classical models struggle.

We've now built a dedicated page for healthcare use cases, where you can find more information about quantum in medical diagnostics and tumor classification, biomarker prediction, drug response modeling, molecular simulation with VQE. Each one runs against a classical baseline so you can see the actual difference.

If you work in clinical R&D or healthcare AI and have been curious whether any of this is ready to test on real problems, the answer is: some of it is, and it's cheaper to find out than you'd expect.

https://t.co/NyujOLkLl8
first month free, 1,000 credits, no code required

[Superpositions Studio @SuperpositionsS]

Superpositions Studio subscriptions are now open.

You can now sign up, describe your industry problem in plain language, and get a hybrid quantum-classical solution with benchmarks, reproducible code, and a research-grade PDF report.

Your first month is free with 1,000 credits. That's enough for a full end-to-end experiment.

Subscription is €20/month (1,000 credits). Additional credits: €30 for 3,000.

We will raise prices as the platform grows. If you subscribe now, your rate stays the same. Early subscribers keep today's pricing regardless of future increases.

What's available today:
🔹 20+ industry use cases across finance, energy, manufacturing, and healthcare.
🔹 10+ quantum and hybrid algorithms.
🔹 Multi-vendor QPU access (IBM Quantum, IonQ, Rigetti, IQM).
🔹 Classical baselines included with every run.

Learn more https://t.co/ANwqHk3b0U

#QuantumComputing #SaaS #QuantumTechnology

[Superpositions Studio @SuperpositionsS]

@FinTech_Series Thank you for sharing 💙
Excited to see the conversation around quantum software for finance continue

[Superpositions Studio @SuperpositionsS]

today Superpositions Studio appeared in both @QZeitgeist and @FinTech_Series 🎉

If you're trying to figure out whether quantum computing is relevant to your specific problem that's exactly what the platform is for.

Full articles
https://t.co/pv4v1GLF71
https://t.co/63wCJlOuXi

[Superpositions Studio @SuperpositionsS]

Quantum is landing in Luxembourg 🇱🇺
Tomorrow and Thursday, our team will be at Nexus Luxembourg 2026 | AI & Tech Summit (June 10–11).
There's a dedicated quantum panel at the summit and we'll be right there, talking to people who are serious about what quantum can actually do for their business today.
If you're exploring quantum for finance, energy, or manufacturing — or just want to understand where the technology really stands — come find us.

📍 Luxembourg 🗓️ June 10–11
#QuantumComputing #NexusLuxembourg

[Superpositions Studio @SuperpositionsS]

We're live on @ProductHunt today 🎉

Superpositions Studio: describe a business problem → get quantum code + benchmarks vs classical + a research-grade PDF.

No quantum PhD. No vendor lock-in. Just a honest answer to "is quantum worth it for my use case?"

👉 https://t.co/rJ90dnF0ja

Would love your support 🙏

[Superpositions Studio @SuperpositionsS]

Superposition gives a qubit a state richer than a single 0 or 1. Quantum algorithms reshape that state so the right answer becomes the most probable one when you measure.

The foundation of quantum computing. Full post ↓

https://t.co/jZR04Xkyll

[Superpositions Studio @SuperpositionsS]

We're closing Early Access to Superpositions Studio.

When we launched the platform, we gave everyone who signed up 3 months of free access — full platform, quantum hardware, 1,000 credits.

That window is closing. Once we turn on subscriptions, new users get 30 days free instead of 90.
What the platform does, briefly: you describe an industrial problem in plain language — portfolio optimization, predictive maintenance, fraud detection — and get a quantum vs. classical comparison with working code and a PDF report. Real QPU runs on IBM, IonQ, and others.

If you've been curious about where quantum computing actually helps and where it doesn't, this is probably the cheapest experiment you'll ever run.

Register at https://t.co/fJj925Rv5n while the 3-month window is still open.

[Superpositions Studio @SuperpositionsS]

Most quantum tooling starts too low in the stack.
We’re about to share SPS Kit: a developer-facing toolkit with sklearn-like APIs, built-in datasets, and honest quantum vs classical benchmarking for applied QML and optimization
#QuantumComputing #SPSQuantum

[Superpositions Studio @SuperpositionsS]

"AI + Quantum" usually gets framed as one story: quantum will supercharge AI. In practice, there are two directions, and they're at very different stages.

The one that's actually delivering results today is AI for quantum: using machine learning to calibrate hardware, correct errors in real time, and optimize circuits. NVIDIA's recently launched Ising models for autonomous quantum calibration are a good example. What used to take researchers days of manual tuning can now happen in hours.

The second direction, quantum for AI, is earlier but producing interesting signals. Hybrid quantum-classical models are showing promise in specific settings: combinatorial optimization inside ML pipelines, classification on small and structured datasets, and memory-efficient data processing on problems that would overwhelm classical approaches.

Where the evidence gets thin: general LLM training, production ML at scale, and any claim that quantum "replaces" classical AI. The pattern is consistent — the more specific and constrained the problem, the more likely quantum adds real value.

We wrote a longer breakdown covering what's working, what's promising, and what remains hype in 2026, with references to recent research from Google Quantum AI, NVIDIA, and others.
Full article 👉 https://t.co/SFmk7pkYaI
#QuantumComputing #MachineLearning #QuantumML #DeepTech #PracticalQuantum

[Superpositions Studio @SuperpositionsS]

We're growing.

Superpositions Studio sits at the intersection of quantum algorithms and real industry problems. That means we need people who are rigorous and practical, who care as much about whether a result holds up under scrutiny as about whether it reaches a customer.

Right now, we're looking for:
🔹 Senior Quantum Research Lead: someone who can bridge theory and application. Design experiments, evaluate results honestly, and push the platform's scientific depth.
🔹 Business Developer: someone who can talk to R&D teams in finance, energy, pharma, and manufacturing, understand what they're actually trying to solve, and connect it to what we've built.

Both roles are remote across the EU, UK, and Switzerland.

If neither role fits but you're drawn to what we're doing, reach out anyway. The right person with the right mix of skills is always more interesting than a perfect job description match.

All details here: https://t.co/MMMOiEOVpZ
DMs open. Or write to [email protected].

Know someone who'd be a good fit? Tag them below 👇
#QuantumComputing #Hiring #DeepTech #RemoteWork #Careers

[Superpositions Studio @SuperpositionsS]

Are we heading into a quantum winter?

Quantum winter keeps coming up in conversations, and every time we hear it, we think the metaphor misses the point.

AI winters happened because the field hit real theoretical walls. The algorithms outran the hardware, the data wasn't there, and nobody was sure the math would eventually work.

🔹Quantum computing is in a fundamentally different place. The theory has been solid for decades. The engineering challenges are massive, but they're well-defined: reduce noise, improve error correction, scale qubit counts. And progress on all three fronts is steady and measurable.

🔹What the industry is actually going through looks more like a calibration. The gap between what was promised and what can be delivered today is narrowing, just more slowly than some roadmaps suggested. Some companies are adjusting timelines. Others are shifting toward hybrid approaches, combining classical and quantum methods where each contributes the most. Both of those are signs of a field maturing, not freezing.

There's also something genuinely new happening at the applied layer. Teams across finance, energy, and manufacturing are running real experiments, comparing quantum and classical approaches side by side, and building an evidence base that didn't exist two years ago. That kind of work doesn't happen in a winter.

The field will earn its credibility through practical results. And from where we sit, there are more teams doing that kind of work today than at any point before.

What's your read: is the industry finding its footing, or still adjusting expectations?

#QuantumComputing #DeepTech #PracticalQuantum #QuantumML

[Superpositions Studio @SuperpositionsS]

3 questions we hear on almost every demo call

"Do I need my own data to try it?"

No. The platform includes a preloaded Demo Run — a full workflow from use case to comparison, ready to explore. No data, no setup. When you're ready, describe your own problem in plain language and the co-pilot helps map it to the right formulation.

"The code imports superpositions_kit. Can I see it? Run it myself?"

Good eye. It's our internal library powering the experiments. Right now it runs within the platform — but we're preparing an open-source release so you can download it and use it locally. Coming soon.

"Can I actually use the PDF report to present results to my lead?"

That's exactly what it's for. Every run produces a publication-style report: abstract, methods, results, discussion, classical comparison. Designed so the person running the experiment and the person making the decision don't need to speak the same technical language.

Try it yourself!
#QuantumComputing #QuantumML #DeepTech #PracticalQuantum

[Superpositions Studio @SuperpositionsS]

Can quantum computing help catch financial crime?
Transaction screening is one of the hardest problems in anti-money laundering and fraud detection and one of the use cases we explore at Superpositions Studio.

The problem is brutal: in real-world transaction data, suspicious activity makes up a fraction of a percent. A model can look 97% accurate and still be operationally useless, burying compliance teams in false alerts.

We tested whether quantum kernels — one of the most mature near-term quantum ML approaches — can compete with classical methods on this kind of rare-event detection. Using an 8-qubit feature map on a credit card fraud benchmark (as an AML proxy), the QSVM achieved a PR-AUC of 0.98 with perfect precision on a balanced evaluation set.

Quantum kernels show real strength in small-sample, low-feature regimes — exactly the situation you face when labeled suspicious activity data is scarce. The open challenges are about scaling: kernel computation grows quadratically, real transaction streams drift over time, and moving from balanced training sets to real-world prevalence requires careful calibration.

What we think matters most right now:
→ Decision-focused metrics over headline accuracy
→ Rigorous calibration when moving between balanced training and real-world prevalence
→ Kernel approximation methods to make quantum approaches scalable

Explore this and other use cases in our Quantum Solutions Library.
🔗 https://t.co/FdYklqfyuD

#QuantumComputing #AML #MachineLearning #FraudDetection #QuantumML #FinancialCrime

[Superpositions Studio @SuperpositionsS]

Happy World Quantum Day!

4.14 — the first digits of Planck's constant.
A good day to celebrate the physics. Also a good day to be honest about where the industry actually is.

At Superpositions Studio, we think the most useful way to work with quantum is to keep it grounded in real problems, real benchmarks, and clear comparison with classical methods.

For us, World Quantum Day is a good moment to celebrate the field and also keep the conversation practical.

What real-world problem would you be most interested to test with quantum today?

#WorldQuantumDay #QuantumComputing #QuantumML #DeepTech #MachineLearning

[Superpositions Studio @SuperpositionsS]

THE JOURNEY: From Excel to Quantum Processor

From business data to problem formulation, from simulation to QPU execution, the real value comes from turning experiments into evidence.

You can try this journey yourself on our platform and if you want to go further, our team is ready to help you explore a deeper, more tailored quantum solution for your problem.

[Superpositions Studio @SuperpositionsS]

Your CEO asks: "When will quantum computers deliver real ROI?"
Until recently, the honest answer was "nobody knows."

Now? Concrete numbers. Crossover graphs. Hardware roadmaps.
Here's what changed:

We built a platform that lets R&D teams answer this question quickly, no need to wait for months
→ Describe your business problem in plain English
→ Get a quantum algorithm recommendation
→ Run benchmarks against classical methods
→ See exactly when (and if) quantum wins

No PhD in physics required. No vendor lock-in. Just evidence.
The quantum hype cycle is ending. The evidence era is beginning.

Try it!

#QuantumComputing #Innovation #EnterpriseAI #ROI

[Superpositions Studio @SuperpositionsS]

More qubits ≠ more value
Physical qubit counts are growing fast. Useful applications are not growing at the same pace.
What matters: error rates, depth limits, overhead, and whether a hybrid workflow actually beats a strong classical baseline
Use case first. Hardware second
#QuantumComputing #QuantumML