Vine codes generalize directional codes to open planar boundaries, delivering up to 28% fewer data/measure qubits at circuit distance 7 and better simulated performance than the surface code at 10^{-3} noise while using fewer total qubits.
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Universal quantum computation with ideal clifford gates and noisy ancillas
21 Pith papers cite this work. Polarity classification is still indexing.
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Proves unique stationary law for Clifford random monitored quantum circuits and computes leading asymptotics of steady magic, linear for odd-prime dimension mana and quadratic for qubit 2-stabilizer Rényi entropy.
Under local amplitude damping the n-qubit GHZ family loses entanglement at damping strength γ_e but regains magic at γ_+ satisfying γ_e + γ_+ = 1 for every n, with the reborn magic residing in a fully separable state.
Equivariant RL agent synthesizes near-optimal Clifford circuits up to 30 qubits with lower two-qubit gate counts than Qiskit baselines.
Hermitian weighted graphs enable universal exact realization of arbitrary complex QL-bits as real-spectrum eigenstates, with discrete {0, ±1, ±i} couplings dense in the state space.
Logical error rates in [[7,1,3]] and [[12,2,4]] codes are suppressed 9.8-800 times below physical rates on trapped-ion hardware, with repeated correction cycles approaching the error rate of two physical CNOTs.
The paper proposes an eigenstate filtering (EF) variant of quantum inverse power iteration (QIPI) that uses symmetric QSVT polynomials to robustly target excited states, showing better convergence than Chebyshev or Fourier approaches on H2, LiH, and BeH2.
k-local quantum Hamiltonians admit system-size-independent spectral gap for Gibbs samplers at high temperature, enabling FPT quantum approximation algorithms for partition functions.
Pure-state BNMR is an intrinsic function of the nonzero Schmidt spectrum via dimension reduction, yielding quadratic perturbation response, Haar-random profiles localized at symmetric cuts, and closed forms for rank-2 states.
O3LS reduces space overhead by up to 46.7% and time overhead by up to 36% in lattice surgery while suppressing logical error rates by up to an order of magnitude compared with prior layout and scheduling approaches.
Randomized sparse-QSVT reduces gate counts by up to 10x for inhomogeneous many-term Hamiltonians at moderate error (around 10^{-3}), but deterministic QSVT becomes cheaper for higher precision.
Ancilla-mediated protocols enable deterministic universal logical gates on any stabilizer code without ancilla consumption or code modification.
Postselection on typical syndromes in the toric code suppresses logical error rates from p_f to p_f^b with b approximately 3.1 via large-deviation arguments.
Introduces permutation-agnostic distance measures to quantify non-stabiliserness consumption and shows structured variational methods use it more efficiently than unstructured ones with greater classical optimisation freedom.
Experimental demonstration of logical |H_L> and |T_L> magic states with fidelities 0.8806 and 0.8665 on IBM superconducting hardware using a qubit-efficient surface code embedding, with reported error thresholds above prior values.
Constructions for universal quantum computation in the [[n,n-2,2]] error-detecting code detect single-gate errors at computation end, providing weak fault tolerance with reduced overhead versus full error correction.
Within a restricted low-energy spin-sector ansatz for n-p scattering, direction-averaged magic is locally minimized at the CP-conserving point heta-bar=0 when the effective phase equals heta/4 or lies in specific windows.
Concatenates Laflamme and Iceberg codes with selective filtering for a partially fault-tolerant quantum computation scheme that simulations indicate performs reliably at realistic noise levels.
Qubit allocation techniques for distributed color-code logical qubits achieve a 10% reduction in nonlocal gates that scales with more qubits, plus evaluations of methods for universal gate sets including a logical-swaps approach.
A topical review unifying statistical mechanics, tensor network, and AI approaches to approximate maximum likelihood decoding for quantum error correction codes.