1134 papers
This paper proposes a practical quantum feedback cooling strategy that stabilizes target states by approximating complex state-based control laws with simple measurement-record filtering, thereby eliminating the need for computationally expensive real-time quantum state estimation.
This paper introduces a greedy scheduling algorithm for the Active Volume architecture that assigns logical qubit roles to derive novel overhead formulas, significantly improving resource estimate accuracy and runtime predictions to enable larger circuits to run on existing hardware.
This paper introduces a unified framework bridging stabilizer decompositions and tensor network contraction to develop two new, memory-efficient classical simulation algorithms for quantum circuits whose runtimes are governed by the tree-width or rank-width of the associated tensor network, while also proposing refined complexity measures for tighter performance bounds.
This paper introduces BURY, a scalable heuristic algorithm for balanced k-graph partitioning that minimizes the maximum matching sizes between distributed quantum processing units, thereby reducing the Bell pair overhead required for generating large graph states in distributed measurement-based quantum computation.
This paper introduces the first continuous-variable approximate unitary 2-design, constructed via alternating quadrature-based unitaries on a finite-dimensional discretization, and demonstrates its application in achieving the first unclonable-indistinguishable security for continuous-variable encryption.
This paper presents an analytical model for intermolecular Coulombic electron capture (ICEC) that incorporates internal nuclear dynamics, revealing how molecular motion significantly influences electron spectra, cross sections, and can trigger dissociation in systems like H+ LiH.
This paper demonstrates that entanglement alone is insufficient for secure key distribution in practical entanglement-based QKD protocols when even minimal classical side information leaks, revealing a class of entangled states that cannot yield a secure key and highlighting how such leakage drastically limits the scalability of quantum repeater networks.
This paper extends the analysis of Heisenberg dynamics for non-self-adjoint Hamiltonians by investigating the role of brute-force normalized vectors in identifying conserved quantities and conditions under which observables or their mean values remain time-invariant.
This paper compares the entanglement distribution rates of two heralded and one unheralded SPDC-based systems using spectral islands, finding that while unheralded operation generally outperforms heralded approaches under specific memory and efficiency constraints, the optimal choice depends on a trade-off between achievable heralding efficiencies and the differing equipment burdens of each system.
This paper introduces a Correlation-Complexity Map, comprising Quantum Correlation-Likeness and Classical Correlation-Complexity indicators, to identify real-world data distributions suitable for IQP-based quantum generative models, demonstrating that such models can achieve competitive performance with fewer resources on complex turbulence data when guided by this diagnostic framework.
This paper demonstrates that the spin-1 AKLT Hamiltonian can be realized in tunable quantum-dot arrays by deriving an effective bilinear-biquadratic spin model from half-filled Hubbard tripods, where specific hopping parameters and coupling geometries yield the characteristic singlet-triplet degeneracy while suppressing unwanted longer-range interactions.
This paper generalizes the complete CNOT-dihedral equational theory from qubits to prime-dimensional qudits by constructing a phase-affine circuit calculus with unique normal forms and proving its semantic completeness through polynomial-based rewriting rules.
This paper presents a broadband, low-loss microwave switch for superconducting circuits that utilizes a stable persistent current bias and direct current actuation to eliminate static power consumption and crosstalk while achieving high isolation, sufficient power handling, and wide modulation bandwidth suitable for large-scale quantum information processing.
This paper demonstrates that a mixture-of-experts framework incorporating a guided quantum compressor hybrid model can achieve superior average precision in credit card fraud detection compared to XGBoost, offering a practical balance between enhanced performance and acceptable inference latency despite a minor trade-off in recall.
This paper demonstrates that in quantum Gaussian dynamics, reversing a noising process using a fixed-diffusion Wigner-score drift generally violates complete positivity unless specific conditions are met, thereby necessitating the injection of additional diffusion to ensure physical validity and incurring a fundamental cost in fidelity.
This paper introduces a new experimental method using field ion and field electron microscopes to characterize atomic-scale field emission sources, demonstrating that the Murphy and Good theory yields significantly more accurate emission area measurements than simplified Fowler-Nordheim analysis and enabling the deduction of key beam properties.
This paper proposes and benchmarks a hybrid quantum-classical algorithm that iteratively simulates real-time dynamics of quantum fields coupled to classical fields to achieve self-consistent semiclassical backreaction, demonstrating its convergence and robustness in scalar-tensor modified gravity models relevant to cosmology.
This paper demonstrates that leveraging the higher error tolerance of lattice-surgery operations allows distributed quantum computers to bypass the substantial overhead of remote entanglement distillation, thereby reducing resource requirements by up to two orders of magnitude depending on the fidelity regime.
This paper establishes that the Petz and Schumacher-Westmoreland recovery schemes achieve the true optimal threshold for quantum error correction and introduces the mutual trace distance as a necessary and sufficient diagnostic to determine this threshold without explicit optimization.
This paper presents a method using Rydberg atom processors and sample-based quantum diagonalization to calculate the ground state energy of the Fermi-Hubbard model for large U by sampling the Heisenberg model, demonstrating superior convergence and efficiency over random sampling on up to 56 qubits while analyzing the potential for studying emergent superconductivity.