Heron R2 entanglement test

I encoded 2 logical qubits in one of the (1+x²)(1+y²) code on ibm_fez and created a logical Bell state |Φ⁺⟩ + |Φ⁻⟩ via a single-ancilla circuit: H → CX(anc, col 0) → CX(anc, row 0) → H → M. At 0 rounds (just state prep + measurement), the Bell fidelity was 73% in Z and 66% in X. Entanglement witness ⟨Z₁Z₂⟩ + ⟨X₁X₂⟩ > 1 in both Bell subspaces, exceeding the separable bound. This is the first demonstration of logical entanglement of this code family on superconducting hardware in general, that I'm aware of.. At 1 round CX pushed the circuit to ~4 errors/shot, killing the correlation. On Heron R2, the distance of the code I used can correct ~1 errors, but ibm_fez's ~2% CX error + 14 Bell CX + 192 round CX = too much noise. Create your account and connect with a world of communities. Quantum algorithms have seen recent developments primarily in the dequantization of quantum machine learning algorithms, benchmarking against physical systems, and educational accessibility. Classical Speedup: Ewin Tang's work has demonstrated that classical computers can solve certain problems, such as the recommendation problem, nearly as fast as quantum computers, challenging previous assumptions about quantum speedup. "At 18, Ewin Tang proved that classical computers can solve the recommendation problem nearly as fast as quantum computers, eliminating one of the best examples of quantum speedup." Efficient Classical Analogs: Tang's research indicates that several prominent Quantum Machine Learning (QML) algorithms, once thought to offer exponential speedups, can be "dequantized" into efficient classical algorithms. "She's shown that classical computers are better than we thought - demonstrating that several of the most prominent QML (quantum machine learning) algorithms, once thought to provide exponential speedup over classical methods, could be 'dequantized' by transforming them into efficient classical algorithms." Real-World Validation: IBM has made progress in benchmarking quantum simulations against real physical systems, specifically by reproducing neutron-scattering measurements of a magnetic crystal on their quantum computer. "Basically, they took a real magnetic crystal (KCuF_3), measured its quantum behaviour using neutron beams, and then reproduced those same measurements on IBM's quantum computer." Material Science Simulation: This breakthrough suggests potential for quantum computers in simulating molecular interactions and material properties, with implications for drug discovery and materials science. "My best guess would be simulating molecular interactions and trying out different protein formations for pharmaceuticals." Cybersecurity Risks: The rapid development of quantum computing capabilities, potentially accelerated by AI, raises concerns about imminent risks to current cybersecurity encryption methods. "The world could be caught off guard by quantum hackers before the end of this decade — much sooner than expected." Accessible Learning Platforms: Efforts are underway to make quantum computing more accessible through visual programming tools and educational games, aiming to simplify the learning process for a broader audience. "I am the Dev behind Quantum Odyssey (AMA! I love taking qs) - worked on it for about 10 years (3.5 in phd), the goal was to make a super immersive space for anyone to learn quantum computing through zachlike (open-ended) logic puzzles and compete on leaderboards and lots of community made content on finding the most optimal quantum algorithms." Do you want to know more about the specific algorithms mentioned, like Shor's or Grover's? Anyone can view, post, and comment to this community