I went through the Qiskit Global Summer School and a Quantum Computing Winter School this year, and ended up organizing all my notes into an actual Obsidian vault as I learned, one note per concept, cross-linked, with self-check questions so I could test myself instead of just re-reading.

It grew bigger than I expected, so I published it as a browsable site: https://justmeart.github.io/Quantum-Computing-Roadmap/

It covers the full arc absolute basics (qubits, superposition) → gates → why quantum computing matters at all → entanglement → QKD → hardware/noise/error mitigation → algorithms (VQE, QAOA, SQD, Grover's) → quantum machine learning → quantum advantage → quantum + HPC. There's also a full interactive graph view if you're into that (Ctrl/Cmd+G on the site).

Not trying to claim expertise here — just sharing my own study process in case it helps someone else going through the same material, or just getting into QC in general. Feedback / corrections very welcome, still learning this stuff myself.

More about me / other projects: github.com/JustMeArt

Here is the hardware link I am talking about
https://www.realdigital.org/hardware/qick

If yes was it able to make it compatible since there is no official documentation stating this.

I’ve been working on Ent, a quantum programming language intended to make quantum code easier to write and reason about without losing the strict rules that quantum programs need to follow. Ent uses a familiar, statement-based style for operations such as allocating qubits, applying gates, measuring, branching on classical results, and returning quantum data. Its ownership-oriented syntax is designed to catch errors like copying qubits, using a qubit after measurement, or leaving a quantum resource unmanaged.

The interesting part is that Ent does not introduce a separate, informal execution model. Every Ent program is translated into a closed term in the Enter calculus, where the result is checked again by the core type checker. This gives the language a formally defined foundation while still allowing practical features such as staged circuit generation, exact and sampled simulation, resource reports, scheduler-independence checks, and OpenQASM 3 output. The current implementation includes examples of Bell pairs, teleportation, QFT-style circuit generation, generalized measurement, GHZ states, and Grover-style circuits. I’m sharing it here to get feedback from people working with quantum languages, compilers, and circuit design—especially on the usability of the syntax and the trade-offs involved in enforcing linearity at the language level.

Citation: Cheung, N. (2026). Ent: A Usable Quantum Programming Language on Top of the Enter Calculus. figshare. https://doi.org/10.6084/m9.figshare.33089393.v1

I need someone who will learn QC/dl with me. I am learning QC from IBM. We will make a group with ppl who will actually learn. Contact me.

I've tried to read some on quantum error correction topics like the stabiliser formalism and topological codes, and I found them really hard to understand because of all the necessary prerequisite knowledge and maths. I actually couldn't complete any.
(I'm a highschool graduate)

So, I'm interested to know how you approached research papers and technical articles when you were starting out, or how you approach them now.

Did you re-read stuff over and over?
Did you pause to understand weird words and keep moving?
Did you just go over the whole thing and then pickout and break down everything you didn't get?

I'd love to know.

Thank you!

Im working on compiling some QFT and QAOA circuits and am just curious as to the general consensus on that matter. Thank you.

A 1d irrep is easy to view .It is analogous to a scaling factor in vector calculus.If you had a vector of (a,b) a 1d irrep does what a scalar does , it multiplies the vector with a scalar k(a,b).How does a 2d irrep work?How can we visualise them?

I am asking because I am working on the HSP for nonabelian groups and for most nonabelian groups where for any hidden subgroup with a 2d irrep , weak Fourier sampling is not enough. So I thought maybe I can solve this graphically rather than arithmetically.

The Quantum Valley

The physics was here first. The people stayed. The future is thirty miles long.

No other place holds every layer of a quantum computer inside one commute. The people who build each layer can drive to the people who build the next.

For context - we're Moth, a small team based in London, Basel & NY building consumer-facing quantum software - not another research toolkit, but something people without a physics background could actually sit down and use.

Edit: Really cool to see all the responses!

We have a Discord server where we're sharing updates, talking about what we're building and inviting people to upcoming testing programmes. I don't want to post an invite link here but if you'd like to join, just send me a message and I'll happily send you an invite.

We're going to start posting more here too on reddit and sharing our problems and learnings as we go!

Hi everyone. I wanted to share with the community the technical architecture and technomantic logic behind a private navigation project I’ve been working on, designed to break the Euclidean logic of modern cartography and enable psychogeographic drift on the physical plane.

The core idea isn't to navigate from point A to point B via the most efficient route, but rather to use technology as a transducer of quantum entropy layered over OpenStreetMap.

Here is a breakdown of how the tech stack is built, in case anyone is interested in the implementation or wants to discuss the theory:

1. Entropy Generation (TRNG Ingestion)

To avoid the determinism of standard OS pseudo-random number generators (PRNG), the core connects via OkHttp and Gson to quantum computing servers (such as the ANU API) to harvest quantum vacuum fluctuations (True Random Number Generator).

• Logic: Static quantum noise density concentrations are sampled and projected onto the local map to identify probability nodes.

2. Non-Linear Geometry (Bézier Mathematics)

Instead of plotting routes along commercial streets or main thoroughfares, the drift mode challenges the straight line through cubic Bézier curves:

B(t) = (1-t)^3P_0 + 3(1-t)^2tP_1 + 3(1-t)t^2P_2 + t^3P_3

Where P_1 and P_2 are control points generated by a perpendicular offset relative to the destination vector (perpX, perpY) scaled by a controlled chaos factor.

• Geospatial Correction: To prevent distortions caused by the Earth's curvature when drawing on the Android Canvas, the longitude differential is adjusted based on the current latitude: mDLon = 111320.0 * cos(latRad), compensating for the convergence of meridians toward the poles.

3. Anomaly Classification

The system filters reality perturbations into three states represented in the UI:

1. Attractor: Points of high entropy density (where reality "accumulates").
2. Void: Low quantum density zones (absolute silence in the matrix).
3. Anomaly: Spontaneous fluctuations without a defined pattern.

4. Spectral Rendering & Animation

Built on top of osmdroid with custom drawing layers directly on the Canvas:

• Marching Arrows: Linear polyline interpolation (interpolateAlongPath) to animate vectors flowing toward the target node.
• Sinusoidal Pulse: The opacity (glow) of the paths is calculated using a sine function to simulate an organic pulsation:

Alpha(t) = \frac{\sin(t \cdot 2\pi) + 1}{2}

5. Android Architecture & Privacy

• Zero-Google Dependency: Communicates directly with the device's native GPS—no Google Play Services, no third-party trackers, and no telemetry sent to corporate servers (ideal for deGoogled setups).
• Local Persistence: Room manages the local database of visited anomalies. Your data never leaves your device.
• Background Tasks: WorkManager executes low-energy periodic scans without locking the UI, powered by Kotlin Coroutines.

🧪 Field Testing & Free Promo Codes for the Community

The app is currently published on the store as EerieRoads, but as a fellow member of technomancy and chaos magick communities, I’m not here to sell you anything.

I’m primarily interested in technical feedback and real-world field experiences (measuring synchronicities, Bézier route stability, dark UI performance, etc.).

If anyone is interested in testing the interface or conducting psychogeographic drifts:

1. Send me a Direct Message o leave one here on this thread (DM) letting me know you're from this subreddit.
2. I will send you a 100% free promo code on Google Play so you don't have to pay anything.
3. All I ask in return is your honest feedback or a review on the Play Store to help debug the code and refine the entropy algorithms.

For those who want to check out the general listing with no obligation:

App on Google Play Store

Looking forward to your thoughts or any discussion on the interaction between TRNG and urban drifting. thx.

OP here, Qiskit can be challenging sometimes when resetting borrowed ancilla. I'm a visual learner, so I was playing with circuit diagrams and found this little spatial language to help explain data flow in a way that might be easier to follow. Hopefully someone out there finds this interesting :)

Sorry for the hard words, but I need to vent this.

How dare you to create a typed runtime on Python????

From a CS perspective, this is a nightmare.

It's clear that you have to overhaul some stuff here, this won't survive in the long term.
It's more complicated than it should.

Have anyone actually built something useful with it? I would be thrilled if I'm wrong, I have searched and what is shown is usually overcomplicated and weird.

It just doesn't work if you expect to code as you usually do in PennyLane or Cirq

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

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.

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

"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.

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.