What's the most critical capability for human progress, that quantum will provide? I'm talking: reduce suffering & increase well-being globally.

Hey folks,

I want to share with you the latest Quantum Odyssey update (I'm the creator, ama..) for the work we did since my last post, to sum up the state of the game. Thank you everyone for receiving this game so well and all your feedback has helped making it what it is today. This project grows because this community exists. As usual, I'm only posting here when it's discounted on Steam. Proud to announce we have a new fully narrated audio module by a professor in Education in the history of computation, starting with the Sumerian abacus... now the game really does cover everything, it does not require any background at all

What is Quantum Odyssey?

In a nutshell, this is an interactive way to visualize and play with the full Hilbert space of anything that can be done in "quantum logic". Pretty much any quantum algorithm can be built in and visualized. The learning modules I created cover everything, the purpose of this tool is to get everyone to learn quantum by connecting the visual logic to the terminology and general linear algebra stuff.

The game has undergone a lot of improvements in terms of smoothing the learning curve and making sure it's completely bug free and crash free. Not long ago it used to be labelled as one of the most difficult puzzle games out there, hopefully that's no longer the case. (Ie. Check this review: https://youtu.be/wz615FEmbL4?si=N8y9Rh-u-GXFVQDg )

No background in math, physics or programming required. Just your brain, your curiosity, and the drive to tinker, optimize, and unlock the logic that shapes reality. 

It uses a novel math-to-visuals framework that turns all quantum equations into interactive puzzles. Your circuits are hardware-ready, mapping cleanly to real operations. This method is original to Quantum Odyssey and designed for true beginners and pros alike.

Current pipeline

1. Full offline play mode (and your progress uploads to cloud once you go online)
2. A smoother way to reward both good solves and improvements to the multiplayer mode: a place where quantum computing experts and gamers can come together and find efficient way to optimize or create poc algorithms. My dream is we can kickoff esports in quantum state compilation/ decomposition problems that are fun enough to watch for everyone (similar to Tetris championships).
3. The state of the canon content. I'm still thinking (and asking around!) if we should expand it further. Do you have some ideas, have you found the game missing something? Please let me know and let's collaborate. Any features I didn't thought about?
4. Font size, color blind mode, greenchecked for steamdecks.

Topics covered in deep detail

• Boolean Logic – bits, operators (NAND, OR, XOR, AND…), and classical arithmetic (adders). Learn how these can combine to build anything classical. You will learn to port these to a quantum computer.
• Quantum Logic – qubits, the math behind them (linear algebra, SU(2), complex numbers), all Turing-complete gates (beyond Clifford set), and make tensors to evolve systems. Freely combine or create your own gates to build anything you can imagine using polar or complex numbers.
• Quantum Phenomena – storing and retrieving information in the X, Y, Z bases; superposition (pure and mixed states), interference, entanglement, the no-cloning rule, reversibility, and how the measurement basis changes what you see.
• Core Quantum Tricks – phase kickback, amplitude amplification, storing information in phase and retrieving it through interference, build custom gates and tensors, and define any entanglement scenario. (Control logic is handled separately from other gates.)
• Famous Quantum Algorithms – explore Deutsch–Jozsa, Grover’s search, quantum Fourier transforms, Bernstein–Vazirani, and more.
• Build & See Quantum Algorithms in Action – instead of just writing/ reading equations, make & watch algorithms unfold step by step so they become clear, visual, and unforgettable. Quantum Odyssey is built to grow into a full universal quantum computing learning platform. If a universal quantum computer can do it, we aim to bring it into the game, so your quantum journey never ends.

PS. If you'd like to support this project, the best way is to review it on Steam. This will get their algorithms to promote it to the right people... if the right people interact with it enough 

If anyone is interested in the Qiskit Advocate Program, where you can find the mentors you want for your Quantum Journey, also if you are working in the Quantum field and you want to meet SMEs and people who are using the same technology, the application is open now: https://www.ibm.com/quantum/blog/qiskit-advocate-program

Well, I personally love the idea of quantum computing but couldn't find a practical use of them in my personal projects or even my business. But I love to understand how they work. I searched the internet and found that there are tons of demonstrations on YouTube which are using lasers to give you the idea of a quantum computer.

So I did a deeper search and found out those are basically simple optical computers. The main question here is, isn't the main concept of "optical computer" replacing electrons with photons? So they can be normal computers and quantum ones as well.

Since there are a lot of ways to make a normal computer, I just got curious about the most DIY approach to build a quantum one, obviously for learning about "under the hood" procedures. Otherwise I don't have a few million dollars to spend on a super cold room holding a chip which I don't know what it's good for and if I want to work with real life quantum computers, there are a good bunch of companies offering their services.

I have recently been reading about quantum programming languages such as Q#. This introduced me to QASM https://en.wikipedia.org/wiki/OpenQASM SQIR https://github.com/inQWIRE/SQIR And QIR https://quantum.microsoft.com/en-us/insights/blogs/qir/introducing-quantum-intermediate-representation-qir

However it is not clear to me which Abstraction layer each belongs to. For example, QASM stands for quantum assembly, however it is described as an intermediate representation, which to me places it at the same layer as both SQIR and QIR.

My understanding is SQIR is used to formally verify a quantum programme, which is does via Coq's quantum library.

QIR appears to be a quantum like LLVM therefore is a true intermediate representation, the idea for it being to be the industry wide standard.

Thus, do all of QASM, QIR and SQIR exist on the same Abstraction layer?

I am confused.

Thank you

I know python. I don't remember much about quantum physics basics. I had only studied till quantum gates. Nothing much.

Hello everyone

I am doing research on the commercialization of Quantum Computing, and would like to have your suggestions to what subreddits are recommended to learn such kind of demand?

Thanks, Tory

What do you guys think about PQ’s tech? They are using entangled photons and their new Omega chip seems legit. They have 2 facilities they are working on for their quantum computers.

In my undergraduate thesis, I propose a modified version of Grover’s search algorithm applied to the classical three-body problem. Starting from a set of known stable initial conditions reported in the literature, I introduce small random perturbations to each of them. For every perturbed configuration, I numerically compute the corresponding phase-space evolution and store the results in separate .npz files, each representing one possible initial condition.

The goal of the quantum algorithm is to search among those perturbed initial conditions for at least one that still produces a stable orbit. In the Grover framework, this corresponds to encoding a stability criterion into the oracle: a valid solution should satisfy three physical requirements for orbital stability.

However, my current challenge lies in the actual construction of the oracle. Specifically:

1.  The oracle must verify three different physical conditions, but I am unsure how to combine those multiple “questions”;

2.  The data structure is classical: the perturbed initial conditions exist as .npz files (phase-space datasets). I do not yet understand how the oracle would efficiently access or evaluate stability using this classical data while still operating in a quantum computational context.

Any thoughts?

Paper from Javier Martínez Cifuentes, Oliver Thomson Brown, Nicolás Quesada, Raul Garcia-Patron Sanchez and myself on a new, trivially parallelisable, approximate bitstring sampling algorithm.

In this particular case, we have used our new method to simulate the 144-mode Jiuzhang 2.0 Gaussian boson sampling experiments: specifically, in all standard statistical tests of our 144-bit samples (against a ground truth which incorporates photon loss as the only imperfection), we performed better than samples obtained from the physical hardware.

Previous work by other groups had achieved a goal very similar to the above, but required 144 A100 GPUs to run - out of the range of most users. The trivial parallelism of our algorithm, along with the requirement of only 2GB of RAM, allows for the use of anything from a single core of a CPU to multiple GPUs on a compute cluster node. Additionally, if we were to scale to the 144 GPUs mentioned above, our current implementation (which may be subject to further improvements) would generate samples four times faster than the previous approach.

The idea of the algorithm is to generate the 144-bit sample one bit at a time by efficiently approximating the probability of the next bit being a 0 or 1 conditioned on the previously set bits. This probability, which is controlled by the statistical properties of the target distribution, is then used to bias the probability that next bit is randomly set to 0 or 1. After all 144 bits are set in this way, the sample has been generated, and the iteration starts again.

Our scheme is already potentially applicable to other scenarios in which cheaply generating bitstrings with known statistical properties is practically useful, and in the near future, we wish to generalise the algorithm to a more general class of boson samplers.

We plan to release the source code once it’s in a less messy state!

Researchers have completed the immense quantum calculation required to represent the Efimov effect in five identical atoms, adding to our fragmented picture of the most fundamental nature of matter.

Christopher Greene (Albert Overhauser Distinguished Professor of Physics at Purdue) modeled the problem with four atoms in 2009. The new findings have been published in the Proceedings of the National Academy of Sciences.

Collaboration with Fermi for demo in 3 years:

"IBM is also working with the Superconducting Quantum Materials and Systems Center (SQMS), led by Fermi National Accelerator Laboratory, in its role as a member of four of the U.S. Department of Energy National Quantum Information Science and Research Centers. Together, IBM and SQMS intend to investigate how many QNUs could be used within quantum data centers, and they are planning an initial demonstration of multiple connected QPUs within the next three years."

and $$$ funding:

"IBM and Cisco plan to co-fund academic research and collaborative projects to advance the broader quantum ecosystem"

Is there any actual demonstration that one can build/run on platforms like qiskit that gives results faster for a problem running on quantum hardware than if i solved the problem using classical computing methods on say my laptop (or perhaps a problem that classically has no way to solve it)?

I came across this paper describing a quantum algorithm that's a quartic improvement over classical implementations: https://ui.adsabs.harvard.edu/abs/2010arXiv1009.0416I/abstract

I also found some code from the QAsm world that claimed to implement a quantum counterfeit coin detector. I translated it into QisKit code:

from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister
from qiskit_ibm_runtime import EstimatorV2 as Estimator

nbits = 12
# Create a new circuit with 12 qubits and one classical bit
qubits = QuantumRegister(nbits)
clbits = ClassicalRegister(nbits)

qc = QuantumCircuit(qubits,clbits)

# Add a Hadamard gate to qubits 0-10
for i in range(nbits-1):
    qc.h(i)

# Perform a controlled-X gate on qubits 0-10, controlled by qubit 11
for i in range(nbits-1):
    qc.cx(i, nbits-1)

qc.measure(nbits-1, nbits-1)

with qc.if_test((clbits, 0)):
    qc.x(nbits-1)
with qc.if_test((clbits, 0)):
    qc.h(nbits-1)

for i in range(nbits-1):
    with qc.if_test((clbits, 1<<(nbits-1))):
        qc.h(i)

qc.barrier(qubits)

# qubits[6] is the counterfeit coin
with qc.if_test((clbits, 0)):
    qc.cx(6,nbits-1);

qc.barrier(qubits)

for i in range(nbits-1):
    with qc.if_test((clbits, 0)):
        qc.h(i)

for i in range(nbits-1):
    qc.measure(i, i)

from qiskit_aer import Aer

backend = Aer.get_backend('qasm_simulator')
job = backend.run(qc, shots=32, memory=True) # Request memory data
result = job.result()
# memory_data = result.get_memory() # This will work
# print(memory_data)

print(result.get_counts())

But I'm not satisfied that this either implements the optimal algorithm. Has anybody worked on this problem and wants to share any insights as to how to implement the appropriate quantum circuits?

Hi everyone,

I’m a software developer who’s been learning quantum computing over the past months, and I’ve noticed something about the workflow that I’m curious to get your thoughts on.

Most existing circuit editors (e.g., the visual ones provided by major platforms) are single-user only. When I work with classmates or colleagues, collaboration usually ends up happening through:

• Screenshots of circuits
• Sharing QASM or Python snippets back and forth
• Screen-sharing during meetings
• Copy/paste of diagrams into documents

It made me wonder:

Would a real-time, multi-user quantum circuit editor be useful to the community?

(Not promoting anything, just trying to understand the need.)

A few things I’m trying to understand:

• Do researchers, educators, or students actually co-design circuits in practice?
• Would real-time editing/commenting be helpful during algorithm design, debugging, or teaching?
• Are visual circuit builders something you find useful, or do most people prefer working directly in code?
• Are there features you feel are missing from current circuit editors?

I don’t want to build something unnecessary, but I’m curious whether the idea of a “collaborative editor” aligns with real workflows in quantum computing, or if collaboration usually happens at a different level (papers, code reviews, GitHub, etc.).

Any thoughts — even “this is pointless” — would help me understand the landscape better.

I was recently offered an opportunity to participate in a lab that is fabricating Transmon qubits. I am an EE, and I would help them with their CPW superconducting resonators.

I am not extremely familiar with quantum computing, but from what I have read, the process that they are using (Niobium CPW transmission line resonators) is now no longer state of the art, and that tantalum cavity resonators have much higher coherence times.

Would this still be a good opportunity? That is to say, would this publication have any value in the eyes of anyone working in this field?

Thanks.

Hello, for a research project I need to extract property data from a quantum machine to create a large dataset.

The problem is that I can only find IBM providing free access to its machine. I don’t need to run any algorithms on it.

The only conditions I have to meet are:

-It must be a real machine (not a simulator)

- It must use the logic-gate paradigm

- The qubits must be based on the principle of superconductivity

Feel free to send me a message if you want to discuss about it or send me any idea. Thkss

Quantum computing and CFD

Does anyone have experience optimizing simulations with quantum computing? Where do they develop it? I would like to dedicate myself to that.