Top Tweets for #Quantumcomputation
Via #OPG_OpEx: Experimental investigation of maximum-confidence measurements and their contextual advantages https://t.co/zZc9CkkcYw #InformationProcessing #QuantumComputation
In detail, topological codes have many desirable properties that allow #faulttolerant #quantumcomputation with relatively low overhead. A core challenge for these codes, however, is to achieve a low-#overhead universal gate set with limited connectivity.
In this work, we explore a #nonPauli stabilizer code that can be used to complete a universal gate set on topological toric and surface codes in strictly two dimensions. Fault-tolerant syndrome extraction for the non-Pauli code requires mid-circuit X corrections, a key difference to conventional Pauli codes.
We construct and benchmark a #justintime (JIT) matching decoder to reliably decide these corrections. Under a phenomenological error model with equally likely physical and measurement errors, we find a high threshold of ≈2.5%, close to the ≈2.9% of a decoder with access to the full syndrome history.
We also perform a finite-size scaling analysis to estimate how the logical error rate scales below threshold and verify an exponential suppression in both physical error rate and in the system size. A second global decoding step for Z errors is required and the non-Clifford gates in the circuit reduce the threshold from ≈2.9% to ≈1.8% with a naive decoder.
We show how Z decoding can be improved using knowledge of the X corrections, pushing the threshold to ≈2.2%. Our results suggest non-Clifford logic in 2D codes could perform comparably to 2D quantum memory. Our formalism for efficient benchmarking and decoding directly generalizes to a broader family of CSS codes whose X stabilizers are twisted by diagonal Clifford operators, and spacetime versions thereof, defined by CSS-like circuits enriched by CCZ, CS, and T gates.
An Editors' Pick via #OPG_OpEx: Generation of 10-dB squeezed light from a broadband waveguide optical parametric amplifier with improved phase locking method\ https://t.co/Jjhe2bqgjr #QuantumComputation #SqueezedStates @UTokyo_News_en @NTTPR
IBM researchers link two quantum processors in real time, creating a 142-qubit system using dynamic circuits and virtual gates for modular quantum computing. - https://t.co/jveh2ZDrbP #quantumcomputation #ibmquantumqpu
Mid-circuit measurements are a powerful tool for state preparation, and they have generated considerable excitement in condensed matter physics due to their rich and surprising effects. In contrast, their usefulness for #quantumcomputation remains comparatively less well understood. In this work, we demonstrate that #midcircuitmeasurementscan enable genuine quantum advantages even in shallow quantum circuits.
https://t.co/zH1JbGjPfd
Concretely, quantum advantage schemes probe the boundary between classically simulatable and classically intractable quantum dynamics. We explore the impact of mid-circuit measurements on the computational power of quantum circuits.
To this effect, we focus on quantum sampling and introduce a constant-depth measurement-driven approach for efficiently sampling from a broad class of commuting diagonal quantum circuits and associated structured phase states, previously requiring polynomial-depth unitary circuits.
By interleaving mid-circuit measurements with feed-forward in randomized "fan-out staircases", our dynamical circuits bypass Lieb-Robinson light-cone constraints, enabling global entanglement with flexible auxiliary qubit usage on bounded-degree lattices (e.g., two-dimensional grids). The generated phase states exhibit random-matrix statistics and anti-concentration comparable to fully random architectures.
We further demonstrate measurement-driven feature maps that distinguish phases of an extended SSH model from random eigenstates in a quantum machine-learning benchmark (reservoir computing). Technologically, our results harness mid-circuit measurements to realize quantum advantages on bounded-degree hardware with a favorable topology. Conceptually, they provide complexity-theoretic support for quantum speedups by mid-circuit measurements.
Warm thanks to Chenfeng Cao for this wonderfully fruitful and inspiring collaboration.
#HarvardPhysicists unveil system to solve barrier to #NewGeneration of #SuperComputers;
“For the first time, we combined all essential elements for:
-#Scalable
-#ErrorCorrected
-#QuantumComputation,
in an
-#IntegratedArchitecture”
Mikhail Lukin
@harvard
https://t.co/7f5rU5uG2K
AI, Quantum Computing And Future Digital Innovations - Dr. #AdnanMasood PhD. - Chief AI Architect, #UST joins me on Progress, Potential, And Possibilities #ArtificialIntelligence #MachineLearning #CognitiveServices #CognitiveRobotics #QuantumComputation
AI, Quantum Computing And Future Digital Innovations - Dr. @adnanmasood - Chief AI Architect, @USTglobal @ProgressPotent1 @irat1onal @MIT_CSAIL @StanfordAILab #ArtificialIntelligence #MachineLearning #CognitiveServices #CognitiveRobotics #QuantumComputation https://t.co/dcnJLtLCk7
#mdpisymmetry Article "From Entanglement to Universality: A Multiparticle Spacetime Algebra Approach to Quantum Computational Gates Revisited" is available at https://t.co/UEao7SllK4
Authors: Carlo Cafaro et al.
#quantumcomputation #quantuminformation
@ualbany
@SUNYPolyInst
#Day19 of #21daychallenge by @Qucodes
QML basics - data encoding and QNN
The flow via - input-> hidden->output layers; lossfunctions; QNN;
the optimizer and optimization --- https://t.co/OKVaYZ6ScL
#learning #quantumcomputation #Qucodes
#callforpapers #mdpisymmetry A new Special Issue opens for submission!
Title: Symmetry/Asymmetry in Superconducting Quantum Computation
Editor: Haozhi Wang and Parameshwar R. Pasnoori
Details: https://t.co/jivpan87GY
#superconductingqubits #quantumcomputation
@UofMaryland
📌June 10 @chalmersuniv : Mini-symposium on quantum computation | Speakers: Fernando Quijandria, David Haviland, Perola Milman, Alessandro Ferraro, David Gross
Moderated by Giulia Ferrini #WACQT
https://t.co/ybRPKyXeqT
#quantumcomputation #IYQ2025
Via #OPG_OpticaQ: Liouvillian skin effect in quantum neural networks https://t.co/nOR2KAcDH9 #MachineLearning #QuantumComputation @UIBuniversitat
Via #OPG_JOSA_B: Programmable color qubit quantum gates https://t.co/HiD9iQQNlu #IntegratedPhotonics #QuantumComputation @GobiernoMX
Theory of Quantum Computation, Communication and Cryptography (TQC) 2025, organized by Indian Institute of Science, Bengaluru, India @iiscbangalore
#QuantumComputation #QuantumCommunication #QuantumCryptography
https://t.co/SoYggCOsbZ
Summer School on Mathematical Aspects of Quantum Information and Computation, June 16-20, 2025, France, organized by Université Paris-Saclay @UnivParisSaclay and Institut Polytechnique de Paris @IP_Paris_
#QuantumInformation #QuantumComputation
https://t.co/xWMLBsrsaG
Via #OPG_JOSA_B: Tailoring the light–matter interaction for high-fidelity holonomic gate operations in multiple systems https://t.co/USk4WuEfYi #QuantumComputation #QuantumGates
Via #OPG_OpticaQ: Quantum interferences and gates with emitter-based coherent photon sources https://t.co/M4JbofEWJO #QuantumComputation #SqueezedStates @UnivParisSaclay
$DNX #DeSci #Ai #DePIN #GPU #Quantum #Computing #future #binance #gateio #okx #mexc
#money #profit #elon_musk
#alan_becker
The people has begun to understand the value of $DNX up 28% in day 🚀❤️🚀
The chips will be insane
#QuantumComputation
#SiliconChip
#DNX
#Depin
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