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No quantum advantage (yet) in the world of tensor networks
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No quantum advantage (yet) in the world of tensor networks

Tensor networks pictographic scheme Each tensor is represented by an array of dimension N, that matches its number of indices. By joining the legs (indices) of each tensor, it is possible to encode the Hamiltonian or the state of a many-particle system. (Courtesy: Lucy Reading-Ikkanda/Simons Foundation)"> Tensor networks pictographic scheme Each tensor is represented by an array of dimension N, that matches its number of indices. By joining the legs (indices) of each tensor, it is possible to encode the Hamiltonian or the state of a many-particle system. (Courtesy: Lucy Reading-Ikkanda/Simons Foundation) Researchers at the Flatiron Institute in New York City have used a new tensor network (TN) scheme to simulate how Ising spin glasses evolve in time. In many cases, their classical method is more accurate than the latest quantum annealers running the same problem. The results scale in two and three dimensions and raise the bar in the ongoing competition between classical and quantum computers for simulating many-particle quantum systems. Classical versus quantum Quantum many-particle systems provide a good way of comparing computational techniques because their complexity grows exponentially with the number of particles. In theory, quantum computers hold an advantage rooted in entanglement and superposition. In a classical computer, the spin of a particle (up or down) is encoded in bit that is either zero (down) or one (up), but never both. In a quantum computer, the spin can be encoded in a qubit holding a quantum superposition of up and down. This is a much more natural way to represent what the simulated system is actually doing. Recently, a team of quantum computing researchers used the D-Wave’s Advantage2 quantum annealer to simulate Ising spin glass dynamics and claimed that classical computers could not match their results. But now, Joseph Tindall and colleagues at the Flatiron Institute have shown that a classical scheme can do just as well -and sometimes bet

Aug 21, 2026

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The HALO Engine: $\mathcal{O}(1)$-Step Compilation and Localized String Rupture for Lattice Gauge Theories on Quantum Hardwarequantum-computing

The HALO Engine: $\mathcal{O}(1)$-Step Compilation and Localized String Rupture for Lattice Gauge Theories on Quantum Hardware

--> Quantum Physics arXiv:2608.19243 (quant-ph) [Submitted on 14 Aug 2026] Title:The HALO Engine: $\mathcal{O}(1)$-Step Compilation and Localized String Rupture for Lattice Gauge Theories on Quantum Hardware Authors:Abhiroop Gohar View a PDF of the paper titled The HALO Engine: $\mathcal{O}(1)$-Step Compilation and Localized String Rupture for Lattice Gauge Theories on Quantum Hardware, by Abhiroop Gohar View PDF HTML (experimental) Abstract:Simulating the real-time dynamics of lattice gauge theories (LGTs) represents a challenge for near-term quantum computing. Standard digital simulations rely on Trotterization schemes where circuit depth scales proportionally with lattice size, inevitably colliding with the coherence limits of noisy intermediate-scale quantum (NISQ) hardware. To deal with this depth-scaling bottleneck, we introduce the Hardware-Aware Lattice Optimization (HALO) compiler, an architecture that executes global time-evolution steps in an immutable $\mathcal{O}(1)$ circuit depth per Trotter step. Leveraging this framework, we elevate the digital simulation of the Quantum Link Model (QLM) truncation of the Schwinger model to the mesoscopic scale, utilizing a composite multi-qubit gauge link representation to support non-trivial electric field dynamics. We initialize and execute the non-perturbative dynamics of a heavily stretched $L=15$ meson string on a 16-qubit superconducting transmon processor. By coupling the $\mathcal{O}(1)$ compilation with Zero-Noise Extrapolation (ZNE), we suppress physical hardware decoherence to extract the precise dynamical crossover of localized pair creation, identifying the topological transition at $t \approx 0.790$ lattice units with an $18.3 \pm 2.2\%$ rupture probability. Furthermore, we empirically map the dynamical phase diagram of the mesoscopic lattice, pinpointing the effective confinement phase boundary at precisely $g_c = 1.0$. Finally, we extend the mathematical principles of the HALO engine to higher dimensi

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Phase information beyond entanglement sudden death in coherence-to-entanglement conversion under post-gate noisequantum-computing

Phase information beyond entanglement sudden death in coherence-to-entanglement conversion under post-gate noise

--> Quantum Physics arXiv:2608.19247 (quant-ph) [Submitted on 15 Aug 2026] Title:Phase information beyond entanglement sudden death in coherence-to-entanglement conversion under post-gate noise Authors:Asad Ali, Hashir Kuniyil, M.T Rahim, Saif Al-kuwari View a PDF of the paper titled Phase information beyond entanglement sudden death in coherence-to-entanglement conversion under post-gate noise, by Asad Ali and 3 other authors View PDF HTML (experimental) Abstract:An ideal CNOT maps the phase of a coherent qubit onto the coherence between $\ket{00}$ and $\ket{11}$ of a two-qubit state, producing an output that carries both entanglement and estimable phase information. We ask how post-gate noise degrades these two quantities, and find that they are not lost together. For the phase-encoded X states generated by the protocol, the negativity is a thresholded difference of the surviving coherence $z=f\kappa$ and a population penalty $g$, vanishing once $f\kappa\le g$, while the phase quantum Fisher information (QFI) is the smooth ratio $F_\phi=4z^2/(a+b)$, which stays positive for any nonzero coherence. As a result there is an exact region of state space in which the output is separable but still phase-sensitive. We characterize this region, give the residual QFI $F_\phi^\star=4g_\star^2/(1-2g_\star)$ at entanglement death, and show that channels reaching death at the same coordinate share this residual, with global and independent local depolarization forming one such class and $F_\phi^\star=1/6$ at maximal input coherence. Four standard channels appear as trajectories through this common geometry, and asymmetric population transfer adds a third coordinate that changes the entanglement but leaves the QFI unchanged, which marks where the two-coordinate description applies. We identify a measurement that attains the bound and compare with a direct single-qubit probe, which is more precise under matched exposure; the results are therefore reference benchmarks for phase-inf

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