‘Quantum computers’ do not work in the sense that the electronics does not operate as it is supposed to, but in some other fashion that is not anywhere near as fast as advertised.
It is a complete waste of everyone’s lives who is working in the field. Anyone working on ‘quantum logic’ included. You are wasting your life. You should change subject.
I know this because I can derive the correlation function of the Aspect experiment WITHOUT quantum mechanics or ‘entanglement’.
Quantum computers are unlikely to replace traditional ones any time soon
// Article in French //
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Les ordinateurs quantiques sont peu susceptibles de remplacer les ordinateurs traditionnels de sitôt
#Quantum #QuantumComputing #Quantique #OrdinateursQuantiques #IT #TI #InformationTechnologies #Technologies
Les progrès des ordinateurs quantiques ont été tels que certains se demandent s’ils deviendront la prochaine génération d’ordinateurs personnels dans nos foyers. Ce serait étonnant, résume le Détecteur de rumeurs.
To answer my own question, it is somewhere between 25 kW and 60 kW.
For comparison, the NVIDIA DGX-A100 consumes 6.5kW.
Moreover, this requires Helium-3 which is only 20 ppm in natural Helium (most is Helium-4). I have not yet found the amount of energy required per liter of Helium-3, my guess is that it will be very large.
Bits, qubits, and quantum rules
https://negativepid.blog/bits-qubits-and-quantum-rules/
#Internet #tech #IT #science #STEM #computing #AI #quantumComputing #quantumPhysics #inventions #innovation #negativepid
Cryptography: from paper to silicon
https://negativepid.blog/cryptography-from-paper-to-silicon/
#cryptography #tech #IT #science #STEM #computing #AI #quantumComputing #inventions #innovation #Cybersecurity #onlineSecurity #negativepid
A new study proposes “quantum telepathy,” using entanglement to coordinate decisions between systems without real-time communication. It could enable near-term quantum computers to improve trading, networks, and robotics—though real-world use still needs testing.
Scientists demonstrated controlled memory in a photonic quantum system, boosting how quantum reservoir computers process time-based data. Using entangled light states, the system improves memory capacity and scalability for quantum machine learning tasks.
Researchers demonstrate a photonic quantum reservoir computing platform that uses spectral and temporal multiplexing in a continuous-variable setting. Real-time memory is implemented, and nonlinear temporal tasks are enabled.
Good read to start the week. They calculate logical error bounds using symbolic polynomials instead of mindless sampling.
Even with complexity limits, it’s a perfect example of why formal methods are non-negotiable.
Quantum error correction (QEC) enables reliable computation on noisy hardware by encoding logical information across many physical qubits and periodically measuring parities to detect errors. A decoder is the classical algorithm that uses these measurements to infer which error most likely occurred, so that the system can correct it. The decoder's accuracy-how rarely it makes the wrong guess-directly determines the scale of quantum computation that can be reliably executed. With a wealth of competing decoding algorithms, a QEC system designer needs reliable methods to evaluate them. Today, the dominant approach is to evaluate decoders using Monte Carlo simulation. However, simulation has several drawbacks such as requiring many samples to produce low variance estimates. In this work, we develop a new systematic analysis for evaluating decoders. We introduce a novel formal semantics of a core language for QEC programs that captures the de facto standard Stim circuit format, providing a principled theoretical foundation for the emerging space of fault-tolerant quantum systems design. Given a QEC program and a decoder, our verifier can quantify both the decoder accuracy and the decoder robustness to drift in physical error rate. Our approach has two key components: (i) a structured search over the space of possible errors; and (ii) a constrained polynomial optimization kernel. A thorough empirical evaluation of our approach suggests that it can outperform simulation, especially in low error rate regimes, and that it can be deployed to quantify decoder robustness over an interval of physical error rates.
Does anyone know/have a link to the power consumption of the IBM Marrakesh (156-qubit Heron superconducting QPU)?
Barry Schwartz 🫖
Edwin G. 
Wim🧮
Negative PID SL
Diletta Fileni
Quantum_magazine
Mayckon Giovani