Sdim is the first open-source qudit stabilizer simulator supporting all dimensions, enabling circuit evaluation and sampling for qudit fault-tolerant quantum computing research.
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Quisp: a quantum internet simulation package
19 Pith papers cite this work. Polarity classification is still indexing.
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A randomized linear-time phase-folding algorithm using constant-width bitstring abstraction optimizes T-count in quantum circuits orders of magnitude faster than prior tools while achieving comparable reductions.
TuniQ uses RL with a dual-encoder, shaped rewards, and action masking to autotune quantum compilation passes, improving fidelity and speed over Qiskit while generalizing across backends and scaling to large circuits.
Cobble is a domain-specific language for quantum block encodings that compiles high-level matrix expressions to optimized circuits using analyses and quantum singular value transformation, achieving 2.6x-25.4x speedups over unoptimized baselines on benchmarks.
Search-based approximate diagonalization followed by analytical inversion yields high-precision multi-qubit Clifford+T circuits with 95% fewer non-Clifford gates on real-algorithm benchmarks.
Models EGS as Erlang loss system, derives blocking probability formulas for three scenarios, proves insensitivity theorem depending only on mean attempt and calibration durations.
Proves finite-shot mean-squared-error laws for virtual distillation and symmetry verification that define certified operating windows and a selection trichotomy for their comparison.
Quokka# is a Python library that converts quantum circuit analysis tasks into #SAT problems, offering multiple encodings, approximate equivalence checking, and depth-optimal synthesis.
Independent quantum signal injection into graph DEQs yields higher test accuracy and fewer solver iterations than state-dependent or backbone-dependent injection and classical equilibrium models on NCI1, PROTEINS, and MUTAG benchmarks.
The Eclipse Qrisp BlockEncoding interface provides high-level programming abstractions for block-encodings, enabling easier implementation of quantum algorithms such as QSVT, matrix inversion, and Hamiltonian simulation.
AutoQ 2.0 verifies quantum programs with classical control flow and successfully checks RUS algorithms instantly plus weak-measurement Grover search on 100 qubits in about 20 minutes.
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.
A variational quantum autoencoder detects anomalies in brain MRI by scoring resistance to compression, reporting slice-level ROC-AUC of 0.95 and outperforming classical autoencoders and PCA on public datasets.
Proposes a heterogeneous quantum repeater network architecture using recursive designs and RuleSets with a new bridging building block, but states that full-scale resource trade-off analysis remains future work.
A quantum algorithm for evolving Schwarzschild spacetime in the WEBB NR formalism is implemented in Qiskit and tested on simulators and IBM quantum computers.
A distributed switching protocol for unbuffered quantum networks uses cooperative BSA selection and bi-path reservations to achieve high link success rates under load in simulations.
New building block and protocol for all-photonic quantum repeaters using repeater graph states that reduces emissive memories at end nodes and integrates with memory-based systems.
Empirical comparison of angle and amplitude encoding in VQCs on Wine and Diabetes datasets shows rotational gate selection in the encoding layer changes accuracy by 10-41 percent and treats embedding as a tunable hyperparameter.
citing papers explorer
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Linear-Time T-Gate Optimization via Random Abstraction
A randomized linear-time phase-folding algorithm using constant-width bitstring abstraction optimizes T-count in quantum circuits orders of magnitude faster than prior tools while achieving comparable reductions.
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Cobble: Compiling Block Encodings for Quantum Computational Linear Algebra
Cobble is a domain-specific language for quantum block encodings that compiles high-level matrix expressions to optimized circuits using analyses and quantum singular value transformation, achieving 2.6x-25.4x speedups over unoptimized baselines on benchmarks.