Michael Neuberger’s Post

🔮 Are you curious about how quantum algorithms can solve control problems more efficiently? We are looking forward to sharing our results and connecting with others at 𝐈𝐄𝐄𝐄 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝗪𝗲𝗲𝗸 𝟮𝟬𝟮𝟱. 📌𝐒𝐞𝐬𝐬𝐢𝐨𝐧: TP52::QALG — Quantum Circuit Design for Modeling, Estimation, and Control 📅 𝐃𝐚𝐭𝐞 & 𝐓𝐢𝐦𝐞: Wednesday, 3 September, 15:00 – 16:30 📝 𝐏𝐚𝐩𝐞𝐫 𝐓𝐢𝐭𝐥𝐞: Quantum Solution Framework for Finite-Horizon LQG Control via Block Encodings and QSVT 👥 𝐀𝐮𝐭𝐡𝐨𝐫𝐬: Nahid Binandeh Dehaghani, Rafael Wisniewski, and A. Pedro Aguiar In this work, we present a fully quantum pipeline for solving the finite-horizon LQG control problem. The algorithm achieves 𝐩𝐨𝐥𝐲𝐥𝐨𝐠𝐚𝐫𝐢𝐭𝐡𝐦𝐢𝐜 𝐬𝐜𝐚𝐥𝐢𝐧𝐠 in the system dimension 𝑛 and 𝐥𝐢𝐧𝐞𝐚𝐫 𝐬𝐜𝐚𝐥𝐢𝐧𝐠 with the horizon 𝑇, offering an asymptotic improvement over classical complexity. #IEEEQuantumWeek

Abstract We propose to employ the amplification mechanism of Grover’s search algorithm to efficiently prepare entangled states of an ensemble of qubits. The conditional change of sign employed in the algorithm can be implemented by the phase shift of photons scattered on an optical cavity hosting an atomic ensemble. We show that collective Dicke states, Greenberger-Horne-Zeilinger states, and Schrödinger cat superpositions of 𝑁 atoms may be prepared deterministically by few ( ∼𝑁1/4) photon scattering events without individual addressing of the atoms. https://lnkd.in/gg2f78e7

21-Day Quantum Computing Challenge — Day 15 QuCode🚀 Today’s focus Quantum Phase Estimation (QPE): estimates eigenphases using controlled-U operations and the inverse QFT for precise phase readout. Quantum Fourier Transform (QFT): a basis change that enables period finding and underpins algorithms like Shor’s. Key takeaways Implemented QPE/QFT circuits and interpreted measurement outcomes, linking binary results to phase estimates. Explored precision–resource trade-offs (ancilla qubits, controlled powers of U) and practical complexity considerations. Connected concepts to real use cases: factoring, Hamiltonian simulation, and spectral analysis in quantum algorithms. #QuCode #QuantumComputing #QPE #QFT #QuantumAlgorithms #QuantumCircuits #Qiskit #21DayChallenge #Day15 #ContinuousLearning

[7] After the execution of any quantum algorithm we typically read out some of the information via measurements. Recall that we are only allowed to ask the qubits whether they are in the 0 or 1 reference state.     At QUDORA, we implement this measurement via fluorescence detection: We target the qubit to be measured with a laser which excites, for example, the 0 state, but not the 1 state. Immediately after being excited, the qubit relaxes again by emitting light.  The net effect is simple: qubits in the 0 state reflect the laser light — they appear "bright" (see picture 2). Qubits in the 1 state stay "dark" (see picture 3). Qubits in superposition reflect light only with a certain probability, depending on their internal quantum state. By collecting this reflected light on a camera or detector, we infer the measurement outcome:   ▪️ Light observed ➡️ "bright" state ➡️ outcome 0   ▪️ No light ➡️ "dark" state ➡️ outcome 1    Now that we've also covered measurements, our next post will dive into the fundamental building block of every quantum algorithm: quantum gates.       #trappedions #quantumcomputing #QudoraTechnologies #NFQC

This is the final simulation in my reveal series. RQCE has now successfully simulated a hybrid quantum-classical execution loop using 40 fully entangled qubits, recursive collapse logic, and interleaved classical processing — a feat unmatched by any current quantum system. The output reports 755 significant quantum interactions with a convergence magnitude of 0.9182 over 5 recursive passes. The system maintained stable hybrid-loop operation throughout, demonstrating dynamic interdependence between quantum and classical logic. Output entanglement remained active throughout. This simulation establishes a new class of machine — one where recursive coherence and logic-agnostic transitions enable a system to collapse, restructure, and continue executing across computational paradigms. With this final post, I step back. Licensing inquiries remain open. #KingQuantum #RQCE #QuantumFuture

👩🏻💻Day 9 of Quantum Computing Challenge with QuCode *Today’s focus*: Pauli gates, Hadamard gate, Phase, CNOT, Unitory transformations Pauli Gates (X, Y, Z): Basic Bloch sphere rotations. Hadamard (H): Creates equal superpositions. Phase (S) & T Gate: Precise phase shifts for interference and algorithm tuning. CNOT: Two-qubit gate; flips target if control = |1⟩. ✨21 Days Quantum Computing Challenge - Cohort 3! #QuCode #QuantumComputin #QuantumMechanics #QuantumChallenge #QuantumLearning #PauliGates #HadamardGate #Phase #CNOT #UnitaryTransformations #QuantumStates #Qi

🚀 Day 8: Single-Qubit States & Quantum State Visualization 🔹 Key Takeaways: Single-Qubit States: Unlike classical bits, qubits can exist in superposition, representing 0 and 1 simultaneously. Bloch Sphere Visualization: Provides an intuitive geometric representation of qubit states and their transformations. Hands-On Learning: Seeing quantum states evolve in Qiskit made abstract concepts tangible. Foundation for Quantum Circuits: Understanding single-qubit behavior is essential before building multi-qubit systems and entangled states. #QuantumComputing #Qiskit #BlochSphere #Qubits #QucodeChallenge #Day8 #LearningJourney

think about this next time you bet big on moving to Quantum Proof cryptography I wonder if this reflects the state across all factions in research or if some covert project where bespoke hardware is purposefully made would make a dent or maybe even break weaker keys we now think unbreakable. I've come to think we shouldn't trust too much in what is now considered Quantum Proof until actual hardware is built running at intended production level reliability and performance. #tech #crypto

Indeed, we need more #quantumalgorithms, we need more quantum algorithms that have the potential to show practical utility and we need to achieve a better understanding - say, on end-to-end complexity or the range of applicability - of those already known.

Beyond Shor's Algorithm: Why His Own Field Has Passed Him By Professor Shor, Your contribution to the field remains the paradigmatic demonstration of what a quantum computer could achieve. But precisely because of the weight your voice carries, I feel compelled to correct several points in your framing. You presented “quantum supremacy” as if it were reducible to the act of factoring large integers on a fault-tolerant machine, and further suggested that this goal remains “several decades away.” With due respect, this is a mischaracterization. Supremacy is not, and has never been, synonymous with cryptographic collapse. It is a complexity-theoretic notion: the existence of any problem in BQP demonstrably intractable for classical machines. By that definition, supremacy demonstrations already exist—random circuit sampling (Google’s Sycamore), boson sampling (Xanadu’s Borealis), Gaussian boson sampling with threshold detectors. These are not speculative curiosities; they are experimentally verified instantiations of separations between quantum and classical resources, unless one chooses to redefine supremacy post hoc as “breaking RSA or nothing.” Your suggestion that improved classical algorithms may refute these demonstrations is a valid caveat but ultimately bounded. Complexity theory (Aaronson–Arkhipov; Bremner–Montanaro–Shepherd) shows that efficient classical simulation of such distributions would collapse the polynomial hierarchy—an outcome more radical than accepting the reality of quantum advantage. Temporary algorithmic workarounds (tensor networks, Clifford+T stabilizer simulators) narrow but do not erase the separation. Moreover, the prediction that factoring is “decades away” rests on a linear extrapolation of today’s error rates. This ignores the non-linear trajectory of progress: bosonic encodings (GKP states), LDPC codes with constant overhead, modular ion-trap arrays, and photonic cluster states. Logical qubits with demonstrated break-even error suppression already exist. To dismiss these as incremental curiosities is to repeat, in 1946, the claim that stored-program digital machines were “obviously” incapable of scaling. What matters here is conceptual clarity. Supremacy is not utility. Factoring will indeed be the cryptographically dramatic instantiation, but it is not the definitional gatekeeper. To equate supremacy with factoring is to erase the very progress that your own algorithm inspired. Supremacy has already been achieved in restricted but complexity-theoretically rigorous models. To suggest otherwise risks turning a scientific milestone into a rhetorical mirage. Few individuals have shaped quantum computation as deeply as you have. For that reason, when you speak, the community listens—and sometimes uncritically. With admiration for your foundational work, but with equal commitment to correcting what must not remain unchallenged, Marcos Eduardo Elias Founder, Holosystems Quantum Algorithms / EquiVerse AI