Probing Quantum Entanglement in $τ^+τ^-$ Pairs via the $ππ$ Channel at STCF
- URL: http://arxiv.org/abs/2605.01233v1
- Date: Sat, 02 May 2026 04:10:09 GMT
- Title: Probing Quantum Entanglement in $τ^+τ^-$ Pairs via the $ππ$ Channel at STCF
- Abstract summary: Quantum entanglement and Bell-inequality violation in $+-$ pairs provide a sensitive probe of quantum correlations in high-energy interactions.<n>Super Tau-Charm Facility can provide a competitive platform for precision studies of quantum correlations in $$-lepton pairs.
- Score: 7.941172053476731
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Quantum entanglement and Bell-inequality violation in $τ^+τ^-$ pairs provide a sensitive probe of quantum correlations in high-energy interactions. We present a feasibility study of $e^+e^- \to τ^+τ^-$ at the proposed Super Tau-Charm Facility based on full Monte Carlo simulation at $\sqrt{s} = 7$ GeV, focusing on the $ππ$ channel ($τ^\pm \to π^\pmν$), which offers the maximal spin-analyzing power $|κ| = 1$ and the simplest final-state topology for validating the quantum-tomography framework. We establish a consistency chain from the tree-level QED prediction through truth-level and detector-level reconstruction, yielding a reconstructed concurrence of $0.279 \pm 0.007$ with the good-solution approach. A complementary full-simulation study of the $ρρ$ channel is also briefly reported. These results demonstrate that the STCF can provide a competitive platform for precision studies of quantum correlations in $τ$-lepton pairs.
Related papers
- Quantum Speedups for Stochastic Optimization with Heavy-Tailed Noise [49.730496294398726]
We develop a novel quantum mean estimator for heavy-tailed random variables.<n>We derive stronger lower bounds for tail index>4/3$, showing that a nontrivial dependence on a dimension is unavoidable.<n>For a convex objective function, we propose a quantum projected gradient descent method.
arXiv Detail & Related papers (2026-07-28T09:29:37Z) - Spectral Anatomy of Quantum Gaussian Process Kernels [38.264196157340216]
We prove a Cauchy-Schwarz tail bound on Nystrm approximation error, a finite-sample variance-contraction identity, and a characterization of the emphtarget-dependent optimal entropy.<n>The diagnostic is kernel-agnostic: hardware-efficient, matchgate, IQP emphand RBF/Matérn/RFF/deep- kernel families all collapse onto identical $S/log n$ curves.
arXiv Detail & Related papers (2026-05-29T07:41:14Z) - Wavelet Variance Equipartition as a Threshold for World-Model Quality and Quantum Kernel TN-Simulability [0.0]
We identify the wavelet scaling exponent $$ as a critical diagnostic.<n>We establish $= 1/2$ as a sharp transition boundary for the classical simulability of amplitude-encoded quantum kernels.<n>We prove this variance scales strictly as $Var[X] = (d-2)$.
arXiv Detail & Related papers (2026-05-12T05:41:12Z) - Characterizing quantum correlations and quantum teleportation in $gg \ o t\ar{t}$ and $q\ar{q} \ o t\ar{t}$ processes under noisy channels [0.08795040582681389]
We analyze quantum correlations in $tbart$ pairs produced in QCD.<n>The dependence on kinematic variables is examined in both the $gg to tbart$ and $qbarq to tbart$ channels.
arXiv Detail & Related papers (2026-05-11T23:20:01Z) - Quantum channel tomography: optimal bounds and a Heisenberg-to-classical phase transition [29.68432646391692]
Quantum channel tomography is a fundamental task in the characterization and validation of quantum hardware.<n>Despite extensive prior work, the optimal query complexity for quantum channel tomography is far from fully understood.<n>We show that in the near-boundary regime, the query complexity exhibits a mixture of Heisenberg and classical scaling behaviors.
arXiv Detail & Related papers (2026-04-19T10:51:10Z) - Amplitude-amplified coherence detection and estimation [0.0]
Coherence has been linked to quantum advantage.<n>Coherence witnesses are only able to detect coherence for some, but not all, possible states of a quantum system.<n>We construct protocols capable of detecting the presence of coherence in an it unknown pure quantum state.
arXiv Detail & Related papers (2025-12-17T11:50:32Z) - Shallow IQP circuit and graph generation [37.067444579637076]
We introduce shallow instantaneous quantum-time circuits as generative graph models.<n>We study bipartite and ErdHos-R'enyi distributions through simulations and large-scale experiments.
arXiv Detail & Related papers (2025-11-07T14:28:56Z) - Distributed Quantum Inner Product Estimation with Low-Depth Circuits [14.494830101269677]
This work explores DIPE with low-depth quantum circuits.<n>We first establish that DIPE with an arbitrary unitary $2$-design ensemble achieves an average sample complexity of $Theta(sqrt2n)$.<n>We then analyze ensembles below unitary $2$-designs showing average sample complexities of $O(sqrt2.18n)$ and $O(sqrt2.5n)$.
arXiv Detail & Related papers (2025-06-24T12:37:26Z) - Inertial Confinement Fusion Forecasting via Large Language Models [48.76222320245404]
In this study, we introduce $textbfLPI-LLM$, a novel integration of Large Language Models (LLMs) with classical reservoir computing paradigms.
We propose the $textitLLM-anchored Reservoir$, augmented with a $textitFusion-specific Prompt$, enabling accurate forecasting of $textttLPI$-generated-hot electron dynamics during implosion.
We also present $textbfLPI4AI$, the first $textttLPI$ benchmark based
arXiv Detail & Related papers (2024-07-15T05:46:44Z) - Calculating response functions of coupled oscillators using quantum phase estimation [40.31060267062305]
We study the problem of estimating frequency response functions of systems of coupled, classical harmonic oscillators using a quantum computer.<n>Our proposed quantum algorithm operates in the standard $s-sparse, oracle-based query access model.<n>We show that a simple adaptation of our algorithm solves the random glued-trees problem in time.
arXiv Detail & Related papers (2024-05-14T15:28:37Z) - Towards large-scale quantum optimization solvers with few qubits [59.63282173947468]
We introduce a variational quantum solver for optimizations over $m=mathcalO(nk)$ binary variables using only $n$ qubits, with tunable $k>1$.
We analytically prove that the specific qubit-efficient encoding brings in a super-polynomial mitigation of barren plateaus as a built-in feature.
arXiv Detail & Related papers (2024-01-17T18:59:38Z) - A Quantum Algorithm Framework for Discrete Probability Distributions with Applications to Rényi Entropy Estimation [13.810917492304565]
We propose a unified quantum algorithm framework for estimating properties of discrete probability distributions.
Our framework estimates $alpha$-R'enyi entropy $H_alpha(p)$ to within additive error $epsilon$ with probability at least $2/3$.
arXiv Detail & Related papers (2022-12-03T08:01:55Z) - Laboratory-frame tests of quantum entanglement in $H \to WW$ [0.0]
Quantum entanglement between the two $W$ bosons resulting from the decay of a Higgs boson may be investigated in the dilepton channel $H to WW to ell nu ell nu$
The dilepton invariant mass distribution, already measured by the ATLAS and CMS Collaborations at the LHC, can be used to observe the quantum entanglement of the $WW$ pair.
arXiv Detail & Related papers (2022-09-28T12:22:12Z) - Determination of Chain Strength induced by Embedding in D-Wave Quantum
Annealer [0.0]
D-wave quantum annealer requires embedding with ferromagnetic (FM) chains connected by several qubits.
determination of the chain strength $J_c$ required to sustain FM order of qubits in the chains is crucial for the accuracy of quantum annealing.
arXiv Detail & Related papers (2022-09-25T06:59:10Z) - Speeding up Learning Quantum States through Group Equivariant
Convolutional Quantum Ans\"atze [13.651587339535961]
We develop a framework for convolutional quantum circuits with SU$(d)$symmetry.
We prove Harrow's statement on equivalence between $nameSU(d)$ and $S_n$ irrep bases.
arXiv Detail & Related papers (2021-12-14T18:03:43Z) - Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and
Variance Reduction [63.41789556777387]
Asynchronous Q-learning aims to learn the optimal action-value function (or Q-function) of a Markov decision process (MDP)
We show that the number of samples needed to yield an entrywise $varepsilon$-accurate estimate of the Q-function is at most on the order of $frac1mu_min (1-gamma)5varepsilon2+ fract_mixmu_min (1-gamma)$ up to some logarithmic factor.
arXiv Detail & Related papers (2020-06-04T17:51:00Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.