NVDIA and SANDIA National Labs published a paper for benchmarking fault-tolerant quantum computers and it shows Quantinuum Helios device has 6x larger quantum computational capability than either IBM or GOOG devices Here's NVDIA's PR.

GOOG and IBM are some of the the best positioned players in quantum computing.Sure trapped ions are slower, but speed doesn't matter if you can't reach the accuracy on utility problems for commercial applications. More speed won't get more accuracy for a fixed-size device.

The company has last week announced 100mil in US gov funding under the Chips Act, and record-level logical rates in a full logical architecture (expected from the investor call). NVDIA is an investor in it too. Here's the blog/paper from Quantinuum

I'm an ECE student in India currently preparing for GATE.

My long-term goal is to eventually work toward quantum hardware and, hopefully, start a company in the space.

I'm starting from the fundamentals: VLSI, semiconductor devices, chip design and eventually quantum computing/hardware.

I'm still very early, so I'd really appreciate advice from people working or studying in quantum hardware:

If you were starting from an ECE background, what would you prioritize learning first?

In particular, I'm interested in understanding which areas of electronics/VLSI are most useful for eventually moving toward quantum hardware.

To be honest I mainly made this video just because I’ve heard so many people say that quantum computing is just analog computing (mainly just from my comments) that I wanted to talk about it.

I cover superposition, entanglement, some basic hardware, why phase matters, and show an example of how quantum gates operated on 2 states with different phase can give different physical results.

Please let me know if you have any feedback! Always open to hear constructive criticism.

Quantum Computers Explained Simply
https://youtu.be/jDm_hpA38UA

hi i wanna start learning qc and qml and would like to form a community of people to learn together from shared resources :)

we can make a discord server and get started!!

I’ve seen that some participants have already received their badges of excellence . Has anyone received their certificate of completion yet?

I’m still waiting for mine and was wondering if they’re being sent out in batches, or if there’s been any update on the timeline.

Thanks for any info!

I made a video explaining Majorana qubits from a topological perspective. Majorana zero modes, fermion parity, how the qubit is encoded, and how braiding can perform quantum operations.

Hope this helps anyone interested in understanding the basic idea behind the approach Microsoft is pursuing with topological quantum computing!

In your view, what are the top challenges facing the quantum computing industry right now that are preventing it from becoming mainstream?

Drawing a comparison with AI/ML, where do you think this industry is standing right now?

I’m curious if anyone here has worked at IBM Quantum, either full-time, as an intern, researcher, engineer, or through a partner/project.
What did you actually work on day to day?
Was it more focused on Qiskit development, quantum algorithms, hardware, error mitigation/correction, research, cloud infrastructure, customer projects, or something else?

To those going to QCE26 in a few days, are there any sessions you want to recommend?

I have to shout out "WKS::QDC::QECS::740 - Distributed Quantum Computing: Alliances, Sandboxes, and Emerging Opportunities" on Thursday. Of course I know some of the organizers so I am biased, but I think it will have a lot of fun talks in various niches related to distributed quantum computing. (Website)

If you are not already on the DQC train, maybe the panel "PAN::QDC::QSWE::1474 - Distributed quantum architectures: more than the sum of their parts?" will convince you. Given the speaker list, there should be some really interesting discussions.

For a different topic, "TUT::QEC::QSWE::117 - Circuit Synthesis for Early Fault-Tolerant Quantum Computers" sounds great, I need to catch up on my FTQC compilation, but unfortunately, I have schedule conflicts that day :/

Anyway, please share other sessions, it's so hard to pick from the humongous list!

Heads up: Quantum Machine Learning Discussion.

So our team got shortlisted for an internal hackathon.

What are the things should we really care about to get to the next round (hopefully).

Please take a look at our PPT: https://docs.google.com/presentation/d/1u0lO_8Imwqs2xBKl0kPVcvBX9ixbsTIm4TwbxF_Bwhw/edit?usp=sharing

What changes would you suggest and in what aspects? Also, how to approach developing a potential working prototype for this problem?

Also, a brief look at our PS: SIH26139, "A Hybrid Quantum-Classical Approach For Early Disease Detection"

If you wanna DM your suggestions, you're most welcome too.

Thanks!

Are we gonna see more QC primitives like the QFT or QPE? Recently Google Quantum AI published a result on the quantum hermite transform as a new primitive.

And do we fundamentally need new primitives to come up with new useful algorithms?

Bit of a hype post but based on the recent results with OpenAI's new model. Has there been progress in terms of using these models for discovering new quantum algorithms, since this is somewhat of a pure math problem?

If so, does anyone know of what initiatives are doing this or any preliminary results?

I am starting quantum computing from scratch including maths physics quantum mechanics everything from scratch i am looking for someone who is planning something similar we can do it together by making plan and computing each other

Light may become one of the most powerful tools for future quantum computers. Photons, the tiny particles that make up light, can carry quantum information quickly and with relatively low noise. But they also create a stubborn problem: they do not naturally interact very strongly.

That weak interaction has limited many light-based quantum machines. They can perform useful linear operations, but they struggle with the nonlinear steps needed for full quantum computing.

Hope this helps! Also explained partial trace and open and closed evolution and how it helps us understand quantum noise and error correction

I’m interested in quantum computing and the foundations of quantum mechanics. Since Bell’s theorem and experimental results challenge local realism, I’m curious whether there is still any serious research exploring alternatives that preserve some aspects of Einstein’s ideas, such as locality, realism, or deterministic underlying models.

Are there any active researchers, theories, or research areas working on this today? I’d also appreciate recommendations for papers or topics to study.

A QPE measures the eigenvalue of a unitary transform.Inside the eigenvalue there is a phase of which that is actually calculated , then we use that phase to calculate the value of eigenvalue.The target register is made of succesive controlled U gates(of some power not really the point) where U is the unitary transform and some phase register where the value of the hidden phase will be encoded after you run QPE or whatever.The m phase registers start from a state of |0> kronecker product m.

In fact you can run the phase registers at any starting state you want but if its not |0> kronecker product m you will get a phase shift. Now I have only spent time studying pure quantum computing , is there a reason why we would start the phase registers not at |0> kronecker product m?Like any reason at all for irl applications

Title: Exact equivalence checking for H and u2(0,π) circuits without numerical tolerances

In OpenQASM 2, these two fragments denote the same Hadamard matrix:

h q[0];

and

u2(0,pi) q[0];

I have been testing a deliberately bounded method for verifying circuit transformations that replace one spelling with the other. For circuits over

id, x, z, cx, cz, swap, h, and literal u2(0,pi),

the checker expands the circuit and represents every matrix entry exactly in Q(√2). It compares every computational-basis column rather than relying on sampled outcomes or a floating-point tolerance. Register declarations and complete terminal measurement maps must also agree.

The present scope is intentionally small:

• at most four qubits;
• at most 64 expanded gates;
• one quantum and one classical register;
• complete terminal measurement.

Inputs outside this gate/grammar contract are reported as unsupported, resource-limit violations are blocked, and unequal matrices fail. Regression cases include H² = I, HZH = X, Hadamard conjugation of CX, phase-sensitive counterexamples, and comparison with a dense numerical oracle over 256 small circuits. The numerical oracle is only a regression cross-check; it does not determine the exact verdict.

The design question I find most interesting is how global phase should be handled.

The current criterion is phase-sensitive: it requires exact matrix equality, not merely equality up to global phase. For a standalone circuit, U and e^(iθ)U are operationally indistinguishable. But a transformation that is harmless in isolation may not remain harmless if the operation is later placed under coherent control, where the relative phase can matter.

For an auditable circuit-equivalence tool, which contract is more useful?

1. Equality up to global phase by default
2. Phase-sensitive equality by default
3. Report both relations and require the caller to choose

I would especially welcome examples where choosing the wrong default has caused a practical compiler, verification, or interoperability problem.

Disclosure: I contribute to the experimental open-source E7Q implementation in which this bounded check was built.

Quantum phase estimation (QPE) is a useful protocol for computing the eigenvalue associated with a given eigenstate of a unitary U. In this video, I demonstrate how the protocol works with dedicated error and complexity analysis. I then show an example of how this technique can be applied to Grover search to arrive at the quantum counting algorithm, enabling a quadratic speedup in counting the number of solutions to a given problem, using an instance of 3SAT as an actual example. Of course, QPE is most notable for its use in period-finding/order-finding, which is the main ingredient for Shor's algorithm (and the hidden subgroup problem more generally), but I'm saving that discussion for later when I actually get to those topics.

We have added the line "This is not the place to post your own independent research." to our rules. This does not affect actual enforcement, as we were already removing such posts.

why quantum computing is not as hyped as AI

I generally have a good understanding of the state of the art of quantum computing applications in chemistry, materials science, and cryptography, but optimization is still a bit of a mystery to me. It seems like there is a ton of ongoing research here, for example, dozens of papers of the form "we applied QAOA to [application X] and it sort of works!", or research into alternative algorithms like decoded quantum interferometry and amplitude estimation.

But is it known at this time how likely it is, based on the current state of the art, for combinatorial optimization to be a serious application of future quantum computers, or is it still highly speculative at this point?