I have the idea of a quantum computing education tool that has simulations to make understanding of the concepts easier. Would you think it is a good idea?

https://docs.google.com/forms/d/e/1FAIpQLSfQA_nYefSMIJb-XXjCaerQzNetj2pgl5EnzZkuWwnTsOuzTw/viewform?usp=dialog

Hi everyone,

I'm an undergraduate studying the foundations of quantum technology. For one of my assignments, I have to present a quantum communication protocol (BB84, E91, BBM92, etc.), and instead of making a regular presentation, I want to build a small game around one of them.

The part I'm struggling with is teaching the concept through gameplay. The target audience is college students with little background in quantum mechanics, so the game needs to be simple while still conveying the core idea of the protocol.

Has anyone come across good examples or have ideas on how to design the gameplay? I'd really appreciate any suggestions on mechanics, analogies, or ways to make the learning feel intuitive.

Just wondering what the full story is on these guys. Anyone have more info?

"Finally, quantum computing is no longer decades away, it is upon us, and we are investing aggressively. (...) we disclosed plans to invest more than $10 billion in quantum over the next five years, spanning R&D, capex, manufacturing scaling, M&A and ecosystem expansion. We remain on track to deliver the first large-scale fault-tolerant quantum computer by 2029."

https://newsroom.ibm.com/2026-07-14-Arvind-Krishnas-Letter-to-IBM-Investors

"IBM is delivering the tools to achieve near-term quantum advantage by the end of 2026, and the first large-scale, fault-tolerant quantum computer by 2029"

https://www.ibm.com/quantum/hardware#roadmap

I understand that a Toffoli gate only acts on three qubits, so in my head its "size" should always stay the same regardless of how many logical qubits a quantum computer has.

But then I see papers discussing Toffoli counts alongside logical qubit counts, and it sometimes sounds like the number of Toffolis scales with the number of logical qubits.

Can someone explain this like I'm five?

Right now, in the NISQ era, algorithm design/implementation is dominated by circuit depth, qubit count, and noise accumulation, so a lot of effort goes into keeping circuits shallow, minimizing gate count, and working around noise with mitigation techniques.

Once we actually have the fault-tolerant quantum computers up and running, where do we expect the bottlenecks to be?

I've been developing and testing a theory and body of work pertaining to gravity and quantum computation. I have tested and verified my theory on multiple IBM backends via an open instance including Ibm_Kingston, IBM_Fez, and IBM_Marrakesh.

After getting enough results to really warrant me bringing this up to someone, I started hitting up relevant researchers and professors in those fields. I've been trying to get an endorsement so I can post this on arXiv. My cold outreach hasn't gotten any bites though.

I just want to get this out so people can start working with it themselves. Where can an unaffiliated researcher like myself "get the word out" and still "get credit" for the work? Where are the best places to do that?

I have a website for the company who will be using embodiments based on the theory test results. The siteplan for that is simple, its just a home page, an about page, and a contact page. I plan to create a new "theory/body of work" page, and dump all of the public parts on there . I'll attach the URL to the body of work I post anywhere else to point people to the site.

Other than that, though, i'm like.. ok, I'll post it on here for ya'll to look at?

Long story long me brain hurty. I taught myself a lot in a very short time to do what I needed to do to prove what I needed to prove so I could build what I needed to build. And now I just need a little help figuring out where to put all this for everyone.

Qblex.com is saying they have quantum blockchains with a new proof of coherence validation method. It validates quantum through bell inequality. Validates in less than a second??? Anyone see this?

Could this thing be achievable for IONQ or its just marketing?

At this moment Quantinuum's Helios system has 50 logical qubits and IONQ's Tempo system has only 12 logical qubits. (see their roadmaps)

I'm a little bit skeptical that IONQ from 12 logical qubits atm could jump to 1000's of them in a few years.

Seems like many discussions on PQ security hung up speculating about the time frame in which a viable quantum computer comes into play. And to me it doesn’t seem to be the optimal indicator to track. Wouldn’t it make more sense to establish a priority ranking of systems by data shelf life? For instance if information will need to remain secret for more than ten years there is a greater importance attached to harvest now decrypt later regardless of the timing of the quantum event. Conversely if data becomes useless within days or weeks then the need for urgency is much reduced. Thus the priority list would begin with defense, health care record keeping systems, identity management systems, legal record keeping, banking/financial systems, M&A transactions, telecommunications and any other systems involving long lasting highvalue info. Is this the thought process taking place in the minds of decision makers today in the industry? Or are most organizations still operating from the centuries-old inment mindset?ventory manage

I am looking for a little bit of support. I need references on material to read for Quantum Computing, not necessarily languages for building programs, because I know each system in question runs its own language used for performing computation. I just need to learn about the specifications of each computing system that exists. Plus if there's anyone who understands the the stack very well, then I need you to inform me about the trade-offs, or at least point me in a direction for learning about the architecture of said Quantum Computers. I genuinely have no clue where to start, because I have been so busy with other things. But if someone has the knowledge and wants to share/nerd out on this stuff I would love to chat, I know a little bit about Quantum Mechanics and a little bit about Classical mechanics, but very little in the realm of Quantum Technology and would love to bridge that gap! Thanks!

Spotted this and thought of this sub :)

Quantum Learning Quantum: Quantum Computers and AI
https://www.imperial.ac.uk/events/211377/quantum-learning-quantum-quantum-computers-and-ai/

Wednesday 22nd July, 6-8pm, free.

Note that the in-person tickets have sold out and it's now Zoom only https://www.eventbrite.co.uk/e/online-public-talk-quantum-learning-quantum-quantum-computers-and-ai-tickets-1993782281475

Professor Gerard Milburn, Quantum Fellow at the UK’s NQCC, willl share his vision of how quantum computers and AI could transform science.

Galileo’s great insight was that we can learn about the world by building devices that reveal simple, reproducible phenomena. We push on the world, and the world pushes back. More than a century ago, scientists discovered that some experiments produced a startling result: the world is quantum.

Quantum theory is famously strange, yet we now understand it well enough to put it to work. Quantum technologies aim to harness and control the quantum world in ways that can make us wealthier, healthier and safer. In this talk, Professor Milburn will describe the quantum technologies that are already beginning to change our lives, including quantum computing. Looking ahead, he will explore how the combination of quantum computing and embedded artificial intelligence could create “self-driving laboratories” that accelerate scientific discovery and open the door to technologies beyond our current imagination.

- - -

I collect examples of 'public engagement with quantum computing' resources here https://peeecs.wordpress.com/quantum/

Jo

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Hey all, I've been reading up on quantum computing lately (still pretty new to this) and I noticed something that confused me, so hoping someone here can explain it.

From what I understand, "fidelity" is basically how accurate a quantum computer is when it runs an operation between two qubits. The closer to 100%, the better. I was comparing a few companies' numbers and noticed something weird:

Google's number (99.88%) was published in a real scientific journal (Nature), and other scientists checked it over before it came out. They even said clearly it's an average across the whole chip, not just picking their best-performing pair of qubits.

Quantinuum's number (99.921%) went even further — an actual outside lab (Sandia National Labs, part of the US government, not connected to Quantinuum at all) tested it themselves and confirmed it, also published in Nature.

IBM's number... doesn't seem to have either of those? Their most recent solid number is from mid-2024 (about 99.5%), and I can't find any outside scientist or lab that double-checked it. And their newest machine (called Nighthawk, announced late 2025) doesn't even have a clear fidelity number published at all — the closest thing I found was some confusing wording about "over 99.9% on more than half the qubit pairs tested," which sounds like it's only talking about some of the qubits, not the whole machine.

And here's the part that really got me curious: apparently a separate company (Q-CTRL) tested IBM's Nighthawk machine on a different measurement (called coherence time) and found the real number was way lower than what IBM had originally advertised — like over 10 times lower. So there's already proof that IBM's own claimed numbers don't always match what happens when someone else actually tests it.

So my honest questions are:

Is there some technical reason why it's harder to independently check IBM's fidelity specifically, compared to Google or Quantinuum? Or is this just a choice IBM is making not to have it checked?

Does anyone know of an outside test of IBM's fidelity numbers that I'm just not finding?

IBM seems to talk a lot now about "connectivity" and "circuit complexity" instead of giving a plain fidelity percentage — is that a real, legit engineering reason, or could it also be a convenient way to avoid sharing a number that's currently behind their competitors?

I want to be clear, I'm not trying to hate on IBM — from what I've read they're actually really good about showing detailed data for every single qubit on their chips, way more than most companies. It just seems odd that specifically the fidelity number is the one thing missing an outside check. Is this something people already talk about, or am I missing some obvious reason? Genuinely just trying to understand this better.

The machine that could change the world will be housed in a room that looks like a data center crossed with an ice cream factory. Inside will be some 100 stainless-steel cabinets, each about six feet tall and connected to a supply of liquid helium that keeps them only a few degrees above absolute zero. Inside those cabinets will be hundreds of chips, and on those, thousands of particles of light flying through a maze of optical switches and beam splitters. Each photon must be accounted for, because precisely measuring where it ends up will help answer questions that current computers might take millions of years to solve.

This computer, as described, does not exist. It’s the brainchild of a company called PsiQuantum, founded in 2016 by four physicists from UK universities. In a crowded field of deep-pocketed competitors with similarly fantastical visions, the company aims to be first to fulfill its promise.

In the years since the physicist Richard Feynman first envisioned them in 1981, quantum computers have promised to speed up everything from medical research to AI by harnessing the qualities of quantum particles. Unlike normal computer bits, which can be either a 1 or 0, quantum bits can exist in multiple states at once. And combining enough of those quantum bits together could produce a computer capable of tasks well beyond the reach of today’s conventional machines. But even today’s best quantum prototypes are too small and error-prone to do anything useful.

That makes PsiQuantum’s promises for what its computers will ultimately do all the more bold. Consider the company’s hopes for predicting the effects of cytochrome P450 enzymes, which often break down drugs in the body. If pharma companies knew more precisely how they would work on a particular molecule, they could design more effective medications faster. Estimating this for a specific drug can take over 10 years with today’s methods, says Philipp Ernst, vice president of quantum applications for PsiQuantum, but “we aim to get it down to four minutes.”

Hello!

We’re a team of two Computer Engineering students (UPC), about to start our second year, currently developing a high-performance standalone quantum simulator with its own visual interface. We’ve registered for the Barcelona Supercomputing Center (BSC) Hackathon and are looking to bring one or two key contributors into the team.

That said, the hackathon is not the reason this project exists—it’s actually the other way around. The project came first, so you can expect this to be a long-term effort (possibly lasting years).

The project is fully remote (you can contribute from anywhere in Spain without ever meeting us in person if that's what you prefer). However, if you're based in Barcelona and would like to join us physically for the hackathon, you'd be more than welcome. If you choose that option, we can register you as well.

An important note about us: We're students and beginners in this field. Even though we take the project very seriously and strive for technical rigor, we see it as both a production and a learning project. We want to build something ambitious, but our main goal is to learn, wrestle with the hardware, and grow as engineers. We're not looking for experts—we're looking for learning partners.

What is the project?

The project follows a modular architecture split into three independent layers:

1. Front-End / UX (Unity): An interactive 3D environment for visualizing quantum registers and Bloch sphere rotations (C#).
2. Backend / Orchestrator (C++): The intermediate layer responsible for managing and routing computation requests from the front-end to the numerical core.
3. Data Engine (C++): A reusable data-processing engine optimized for CPU-intensive workloads through a data-oriented design (DOD). The quantum simulator is simply its first major use case. If the architecture proves successful, we'd like to reuse the engine for other high-performance computing problems in the future.

We should mention that the project is still in its early stages, but it's starting to take shape. In any case, this is the perfect moment to contribute to its foundations and make a meaningful impact.

Main technologies

• C++20
• CMake
• Unity (C#)
• Linux
• Git
• Python (for mathematical prototyping)

Who we're looking for

We're looking to fill one or both of the following roles. We don't expect previous professional experience—only enthusiasm for low-level development, an interest in quantum computing, and a willingness to learn as part of a team.

Position A: Theory (Mathematics / Physics / Data Science)

We're looking for someone with a solid understanding of Linear Algebra and an interest in Quantum Computing. Your work will focus on algorithmic formalization:

• Designing and structuring mathematical operators, complex transformation matrices, and the logic behind quantum state entanglement.
• Translating those ideas into clear algorithms that the rest of the team can later implement in C++.
• Requirement: Basic programming skills (Python, beginner C++, or similar) so you can communicate effectively with the team.

Position B: C++ Developer (Beginner)

If you're interested in C++, Linux, and understanding how hardware works under the hood, but you're still learning and looking for a real project to get your hands dirty:

• You'll help connect the different parts of the project: implementing efficient data loading and management, and helping build the bridge between our C++ code and the Unity environment. In the medium term, you'll also help plan and extend the computation engine alongside us.

• What you'll gain: Hands-on experience managing real memory, understanding cache optimization, and applying Data-Oriented Design (DOD) principles while working as part of a team.

Expected commitment

• Around 8–12 hours per week (flexible).
• Since this is a long-term project, we understand that people may eventually need to step away. If that happens, we only ask that whatever you've been working on is documented or left in a clean state so the rest of the team can continue smoothly.

What we offer

• A collaborative learning environment with no hierarchy or commercial pressure.
• A project with a modular architecture and a strong emphasis on code quality.
• The opportunity to compete in—and receive mentorship from experienced HPC professionals during—the BSC Hackathon.
• Complete flexibility and fully remote work if that's what you prefer.

If you're excited about learning by programming close to the hardware or designing the mathematics behind a real quantum simulator, send us a private message telling us a bit about yourself.

Note: Even if you don't fully master these topics yet, but you're passionate about low-level programming or quantum physics, feel free to contact us anyway. We're not experts either—we're just developers at an early stage of our journey.

Repositories

• Atomix (Data Processing Engine): https://github.com/ElectroX79/Atomix_sandbox

• Entangle (Backend / Orchestrator): https://github.com/Ironduck2/Entangle

  (Still in a very early stage, as its development depends on the evolution of the engine.)

Hackathon

• 8th MareNostrum Hackathon (BSC): https://www.bsc.es/en/news/events/mnhack26-8th-marenostrum-hackathon

"Can you give me a practical example of a simple algorithm where a quantum computer is more efficient? I struggle to understand the usual ones, like the maze-solving example, which aren't very clear to me. They always seem too theoretical. Can someone provide a more concrete and intuitive example, please?"

Hobbyist here, no physics background (30-year metalworker). I spent the weekend on Quantum Inspire's Tuna-17 measuring how GHZ fidelity decays as you add qubits to the chain. 1024 shots each, strict fidelity (% of shots that are all-0 or all-1). Plot attached.

4:84%  5:79%  6:72%  7:67%  8:65%  10:58%  13:46%  17:33% 

 Crosses the 50% line between 10 and 13 — matches a simple ~7%/qubit rule (half-life ~10 links). What got me: even the "dead" GHZ-17 still has 000…0 and 111…1 as its top-2 outcomes out of 131,072 (207 and 127 counts, chance ~0.008 each). The wave fades but doesn't vanish.

 Also consistent at every length: all-zeros beats all-ones — I read that as T1 relaxation, excited states decaying toward ground during the circuit and readout. Sanity-checked with a readout calibration: reading a prepared |1> was only ~79% correct vs ~93% for |0>, so a big chunk of the asymmetry is readout, not decoherence.

Not claiming anything new — just a fun, honest measurement anyone can reproduce for free. Questions and corrections very welcome; I only trust what I can measure.

Weekly Thread dedicated to all your career, job, education, and basic questions related to our field. Whether you're exploring potential career paths, looking for job hunting tips, curious about educational opportunities, or have questions that you felt were too basic to ask elsewhere, this is the perfect place for you.

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• Careers: Discussions on career paths within the field, including insights into various roles, advice for career advancement, transitioning between different sectors or industries, and sharing personal career experiences. Tips on resume building, interview preparation, and how to effectively network can also be part of the conversation.
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PsiQuantum in Australia — PsiQuantum https://www.psiquantum.com/australia

Google scientists optimized Shor’s algorithm to break 256-bit ECC with 1,200 to 1,450 logical qubits. But they revealed their findings in a zero-knowledge proof, so that they could be accepted but not replicated. Until Eigen Labs overcame 256-bit ECC with a circuit 47.5 percent more efficient than Google’s...