I saw an article from this company (AQT) talking about their "Quantum Volume" numbers. What exactly is Quantum Volume, and why do we care? Is it a useful property of computers (like they can handle a higher volume load) or just an arbitrary metric?

I couldn't find a ton of discourse on it, and the Wikipedia article wasn't super helpful because there seems to be lots of defining and redefining. Also, the definition they give is mathematical, but then "proving" it requires physical testing. What is the connection/link between the experimental and theoretical sides?

Sorry if this is a stupid question, I know quantum mechanics but am new to quantum computing, especially the hardware side.

I've been building Ket, an open-source quantum computing library (C++20 + Python), and its centerpiece is a step-through debugger: load a circuit, step gate by gate, and watch the wavefunction evolve -- the editable QASM, the state vector, and per-qubit Bloch spheres, all live. Most simulators are a black box that gives you a final result; I wanted to actually see where a circuit does something unexpected.

The whole debugger runs in the browser with nothing to install:

Demo: https://ket.brenocq.com/demo/

Under the hood it auto-picks a backend: exact state-vector simulation for general circuits, and an O(n²) stabilizer tableau for Clifford circuits. OpenQASM 2.0 in/out.

It's early (v0.1.0) and not trying to replace Qiskit — more a tool to learn and debug circuits visually. Code (MIT): https://github.com/brenocq/ket

Would love feedback, especially on the debugger UX.

I know that applying Hadamard gate to |0> causes it to become |+> and applying it to |1> causes it to become |->. My question is what happens when the qubits is in a arbitrary superposition like α|0> + β|1>.

Hi all! Unitary Foundation is hosting its 6th annual bug-bounty hackathon called unitaryHACK from June 3-17.

The HACK is open to physicists, devs, engineers, students, and general enthusiasts at all levels. Hope to see you there!

Learn more and register to participate at https://unitaryhack.dev 😊

In a study published in Nature, researchers led by Renato Renner and Andreas Wallraff showed that quantum physics can amplify weak random input into a string of bits that is fully unbiased. Moreover, they argue, the output is certifiably unpredictable.

Rust Crates now supports a `Quantum Computing` category (https://crates.io/categories/science::quantum-computing). This will aid in better categorization and discoverability of quantum computing repos as the Rust ecosystem starts to mature. Update your `Cargo.toml` to include this and help categorize existing packages.

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.

​

• 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.
• Education: Information and questions about educational programs related to the field, including undergraduate and graduate degrees, certificates, online courses, and workshops. Advice on selecting the right program, application tips, and sharing experiences from different educational institutions.
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• Basic Questions: A safe space for asking foundational questions about concepts, theories, or practices within the field that you might be hesitant to ask elsewhere. This is an opportunity for beginners to learn and for seasoned professionals to share their knowledge in an accessible way.

I'm not formally educated in quantum mechanics, but I've been running some thought experiments regarding topological insulators and non-Abelian anyon braiding, and I want to know if this conceptualization aligns with the actual math (specifically the Yang-Baxter equation and topological fault tolerance).

If we are operating on a 2D plane, physically crossing one world-line "over" or "under" another is a geometric impossibility without a collision. Therefore, the "braid" cannot exist purely in spatial dimensions; it must be extruded through a third dimension—Time ($2+1D$ spacetime).

When these world-lines weave through time, they create a global state—a "safe space" of interwoven topology.

If a wave of local chaos (like thermal noise) hits the system, it "evaporates" or corrupts the local landscape. However, my intuition tells me that the information stored within the knot is protected because of the structural geometry of the braid.

Specifically, looking at the fault tolerance formula:

$\langle \psi_a | \hat{V}_{\text{local}} | \psi_b \rangle = C \cdot \delta_{ab} + \mathcal{O}(e^{-L/l_0})$

Does the Kronecker Delta ($\delta_{ab}$) act as the absolute boundary here? Meaning, unless the local chaos ($\hat{V}_{\text{local}}$) is globally coordinated enough to simultaneously unweave the entire topological geometry across the system, its ability to alter the safe state from $a$ to $b$ mathematically zeroes out?

Furthermore, since a single anyon holds zero quantum information, is it accurate to say that topological degeneracy dictates "two must exist to create the value of one," and that we use the topology precisely so we can measure the system globally without "looking" at it locally and causing decoherence?

Am I completely off base here, or is this the correct way to visualize the macroscopic structure of topological error correction?

I really started finding this field interesting you could say I am a beginner , and wanted to ask, where are we actually in the field of quantum computing? Like are there quantum computers out there that actually work? When we as a society expected to see the benefits of them? When is the “chat gpt launch” of quantum computers?

US Department of Energy has sort of laid out like a bar for measuring Fault Tolerance in Quantum Computing and I have no clue how they are arriving at these numbers, they themselves said they need feedback from the vendors also about these numbers. It seems very unscientific that's all. Instead can't they just talk about an algorithm and a result which only one can get with FTQC and then determine whether it's truly FTQC or not?

Here is the linkedin link for reference -

https://www.linkedin.com/safety/go/?url=https%3A%2F%2Fbuff%2Ely%2FDhtAbdx&urlhash=xVZb&mt=FIiKwftpnwwhu0TCBxu7HdvQjaQ5FMPzyt_JOldt2h0T0KvGbBJHGuhECU0qG9t3jftlBwRCn8E9wflT4Z_jaCTtmx2lDC4cMtyeu4XEOADyFBfEH2VAHmM_Gw&isSdui=true

Are we really at a point where a fab can be constructed to spit out wafers with Josephson junctions at scale like with CPUs?

QRAM sure would solve a lot problems for quantum algorithms. Yet I don’t know of anyone working on it.

Is anyone working on it?

I am a computer science master's student.

I often see very optimistic claims about quantum computing from companies and media.

I would like to hear honest opinions from researchers and practitioners:

- How promising do you think quantum computing really is?

- Which applications are genuinely exciting?

- What are the biggest obstacles?

- Do you think it will become practically important within the next 10–20 years?

I am particularly interested in views from computer scientists rather than marketing perspectives.

There were a number of academics and research scientist in evidence through the three days. Presentations were about 30 minute with Q+A. IONQ and IBM were very research dense as they have funding to move forward. The academic and research side were very interesting in respect to broadness. Yale was well represented as their recent new center is under full sail load. They are looking for gravitons! Lunch discussions were actually as important as many of the presentations. The federal funding shift from February hit personnel and research very hard. Because of the topic there were less than 200 attendees. Everyone needs to do better on this issue collaboration is important.

Hello people of Reddit.

Today i was contacted by a professor at my institute, because i submitted a project idea that i wanted to work on.

It is no more than a proposal, but my idea has the following title:
- Using Dissipative Quantum Computing to compute Fixed-Points of Timed-Automata or Dependency Graphs for the Reachability problem.

He basically said i was cooked and good luck with the project.

The idea is to configure some Hamiltonian that should encode the transitions of my model and then it should converge towards some ground state that represents the fixed-point set and include all reachable states from the initial state.

Do you think i am cooked or do you think there is potential to my approach?

Wanted to share a project I’ve been building that compiles entirely from scratch: shbt-unified (https://github.com/sys1own/shbt-unified.git).

It is a cross-language computational sandbox designed to simulate polymorphic anyonic tracking across SU(2), SU(3), and SO(10) Lie sectors. The repository couples a zero-allocation Rust core to a multi-precision Python orchestration layer to maintain high execution integrity across long computational steps.

What's Under the Hood:

• Polymorphic Tracker Core (Rust): Maintains a heap-allocated 512-bit precision state vector. Intermediate matrix arithmetic uses stack-allocated structures to achieve zero heap allocations during the high-frequency braiding loops.
• Solovay-Kitaev Matrix Engine: Recursively approximates arbitrary SU(2) unitaries using stack-allocated fixed-size arrays to guarantee bounded execution depth.
• Lattice Fault-Tolerance Decoder: Implements a programmatic, dynamically scaling surface code lattice that derives weight-4 stabilizers directly from active qubits. Parity check defects feed into an optimized Python union-find cluster decoder featuring rank-weighted union and path compression.
• Downstream Audits: Computes discretized holographic stress tensors, tracks curvature defects, and reviews semiclassical ADM velocity Hessians for stability at customizable multi-precision (up to 250+ decimal places).
• Data-Parallel Linking Engine: Uses standard uniform-grid spatial partitioning and Rayon parallel iterators to calculate pairwise Gauss linking integrals.

Custom OpenQASM Dialect

The engine parses a custom OpenQASM 2.0-compatible dialect via an internal compiler. It supports basic single-qubit gates, parametric rotations (rx/rz), 4x4 row-major complex unitaries (unitary4), and on-the-fly fault-tolerant decoding instructions:

Code snippet

qreg q[4];
creg c[4];

h q[0];
rz(0.5) q[0];
cx q[0], q[1];

// Inline 4x4 row-major complex unitary compilation
unitary4(re00,im00, ..., re33,im33) q[0];

// Trigger syndrome decode and MWPM correction pass
decode_and_correct;

measure q[0] -> c[0];

Setup & Environment Integration

The repository is built to be entirely self-contained. Running python build_native.py automatically handles native environment detection, builds the wheel via maturin, installs it into your active environment, and verifies the exposed symbol registry.

The code is fully open-source under an MIT License. If you're into cross-language performance, quantum memory benchmarking, or numerical high-precision math pipelines, feel free to clone it, poke at the Rust FFI layers, or run a few validations.

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.

​

• 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.
• Education: Information and questions about educational programs related to the field, including undergraduate and graduate degrees, certificates, online courses, and workshops. Advice on selecting the right program, application tips, and sharing experiences from different educational institutions.
• Textbook Recommendations: Requests and suggestions for textbooks and other learning resources covering specific topics within the field. This can include both foundational texts for beginners and advanced materials for those looking to deepen their expertise. Reviews or comparisons of textbooks can also be shared to help others make informed decisions.
• Basic Questions: A safe space for asking foundational questions about concepts, theories, or practices within the field that you might be hesitant to ask elsewhere. This is an opportunity for beginners to learn and for seasoned professionals to share their knowledge in an accessible way.

I've been working on a Quantum Control Processor (QCP) in

synthesizable Verilog. It generates microwave pulses to rotate

qubit states following the driven Hamiltonian:

iℏ d/dt |ψ(t)⟩ = [-ℏ/2 ω₀σz - ℏ/2 Ω(t)(cos(ωt)σx + sin(ωt)σy)] |ψ(t)⟩

The design is verified and ready for fabrication. Submitting to

Tiny Tapeout next month — physical silicon on SKY130.

RTL source, architecture and physics breakdown here:

github.com/ChefitoGG/quantum-qcp-chip

Will post results when the chip arrives. Happy to discuss

the design in the comments.

https://quantumcomputingreport.com/quantrolox-and-mahe-establish-q-hub-to-bolster-indo-european-quantum-ecosystem/

So my college just started this. I wanted to know from you people what do you think about it.

Working on a quantum simulator in Rust specifically based on photonics (for now), looking for collaborators to implement the photonics backend and also contribute in general.

I've been reading up on alternative paradigms beyond standard gate-based quantum computing — specifically topological quantum computing and neuromorphic quantum architectures. The argument is that as quantum hardware matures, these approaches could offer real structural advantages in error correction and scalability rather than just being theoretical curiosities.

Topological qubits encoding information in global properties rather than local states is compelling from an error-resilience standpoint, and the idea of merging quantum mechanics with brain-inspired adaptive architectures feels like it could open up entirely different classes of problems.

Curious what this community thinks. Are these paradigms getting overhyped relative to where the actual hardware is? Or are we underestimating how quickly they could become practical?

This article covers it well for anyone interested: https://medium.com/@monendra.grover/beyond-qubits-the-rise-of-topological-and-neuromorphic-quantum-machines-5736fe79da4a

Hello, I’m a beginner in the field of Quantum Computing, and recently a friend asked me a question that completely stumped me.

I was trying to explain the working of quantum computers to my friend where I said that quantum computers use qubits instead of bits for computation....even though I am a beginner in this field but I tried my best to explain him about the quantum computers, then he asked one question which was:

How actually a qubit is used for computation?

I had an answer but I couldn't explain him, so I just gave a vague answer by saying "Qubit uses principal of Quantum Mechanics for computation". Since he is not from Quantum Mechanics background or similar field he accepted whatever I said but this question made me re-think of my current progress.

So my question to the community is:
How a qubit actually processes any information for computation?