Articles de recherche quantique, expliqués
Les articles qui ont façonné l'informatique quantique — de Shor et Grover à la suprématie et l'utilité quantiques — résumés en langage simple avec les idées clés et leur importance.
Simulating Physics with Computers
Richard P. Feynman
Argues that simulating quantum systems on classical computers is fundamentally intractable, and proposes building computers that are themselves quantum: the origin of the field.
Quantum Cryptography: Public Key Distribution and Coin Tossing
Charles H. Bennett, Gilles Brassard
Introduces BB84, the first quantum key distribution protocol, whose security rests on physics rather than computational hardness.
Rapid Solution of Problems by Quantum Computation
David Deutsch, Richard Jozsa
Gives the first problem a quantum computer provably solves exponentially faster than any deterministic classical algorithm.
Teleporting an Unknown Quantum State via Dual Classical and Einstein-Podolsky-Rosen Channels
Charles H. Bennett, Gilles Brassard, Claude Crépeau, Richard Jozsa, Asher Peres, William K. Wootters
Shows an unknown quantum state transfers between distant parties using shared entanglement plus two classical bits.
Algorithms for Quantum Computation: Discrete Logarithms and Factoring
Peter W. Shor
Shows a quantum computer factors large integers exponentially faster than the best known classical algorithm: the result that launched quantum cryptanalysis.
Scheme for Reducing Decoherence in Quantum Computer Memory
Peter W. Shor
Presents the first quantum error-correcting code, proving that quantum information can be protected despite the no-cloning theorem.
A Fast Quantum Mechanical Algorithm for Database Search
Lov K. Grover
Provides a provable quadratic speedup for searching an unstructured space: the second foundational quantum algorithm.
Fault-Tolerant Quantum Computation by Anyons
Alexei Yu. Kitaev
Introduces topological quantum codes, including the surface code, where information is protected by global geometry rather than local redundancy.
A Variational Eigenvalue Solver on a Photonic Quantum Processor
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alán Aspuru-Guzik, Jeremy L. O'Brien
Introduces the Variational Quantum Eigensolver, a hybrid quantum-classical method for finding ground-state energies on noisy hardware.
A Quantum Approximate Optimization Algorithm
Edward Farhi, Jeffrey Goldstone, Sam Gutmann
Proposes QAOA, a hybrid variational algorithm that produces approximate solutions to hard combinatorial optimization problems.
Quantum Machine Learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, Seth Lloyd
The standard review of quantum machine learning, surveying where quantum computers might help with learning tasks, and where claimed speedups break down.
Barren Plateaus in Quantum Neural Network Training Landscapes
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, Hartmut Neven
Shows that gradients in randomly initialized variational quantum circuits vanish exponentially with qubit count, making training infeasible at scale.
Quantum Computing in the NISQ Era and Beyond
John Preskill
Coins the term 'NISQ' and sets realistic expectations for what near-term, noisy quantum devices can and cannot do.
Quantum Supremacy Using a Programmable Superconducting Processor
Frank Arute, Kunal Arya, Ryan Babbush, et al. (Google AI Quantum)
Reports the first experimental demonstration that a quantum processor performs a specific task infeasible for classical supercomputers.
Evidence for the Utility of Quantum Computing Before Fault Tolerance
Youngseok Kim, Andrew Eddins, Sajant Anand, et al. (IBM Quantum)
Shows a noisy 127-qubit processor with error mitigation producing accurate results beyond brute-force classical simulation: 'quantum utility'.
Quantum Error Correction Below the Surface Code Threshold
Google Quantum AI and Collaborators
Demonstrates for the first time that adding more physical qubits makes a logical qubit better rather than worse: the threshold crossing fault tolerance requires.
Quantum vs. Classical Machine Learning: A Unified Empirical Comparison
Chuanming Yu, Jiaming Liu, Zihao Ge, Xiongfei Wu, Lulu Zhu, Pengzhan Zhao, Jianjun Zhao
Runs a like-for-like comparison of seven quantum and classical model pairs and finds the quantum models do not beat their classical counterparts.
Efficient Classical Simulation of Two-Dimensional Long-Range Systems: Rydberg Arrays and Beyond
Jia-Lin Chan, Tao Xiang, Yantao Wu
Cuts the cost of a key classical simulation step from cubic to linear, bringing a Rydberg-array experiment previously considered beyond classical reach back within it.
Benchmarking Error Mitigation: Artefactual Improvements in Zero-Noise Extrapolation
Dominik Köster, Wolfgang Mauerer
Identifies a failure mode where zero-noise extrapolation produces convincing but meaningless improvements, and shows deliberately nonsensical inputs can outperform legitimate ones.
Observation of Gravity-Like Signatures in Holographic Codes on a Quantum Computer
Debopriyo Biswas, Gong Cheng, Krishnanand Karthikeyan, Diana Muñoz-Valencia, Vincent P. Su, Hrant Gharibyan, Daiwei Zhu, Grant Salton, Evgeny Epifanovsky, Martin Roetteler, Christopher Monroe, John Preskill, Norbert M. Linke, ChunJun Cao, Crystal Noel
Runs a toy model of the AdS/CFT holographic duality on a trapped-ion quantum computer, reporting the first experimental confirmation of the Faulkner-Lewkowycz-Maldacena formula.
An End-to-End Quantum Algorithm for Weakly Nonlinear Plasma Physics with Superquadratic Speedup
Bjorn K. Berntson, David Jennings, Matteo Lostaglio, Scott Parker
Gives a complete, rigorously analysed quantum algorithm for simulating nonlinear plasma dynamics, including the data-loading and readout steps most speedup claims quietly skip.
Building Shor's Algorithm in Lean: An Agentic Formalization of Quantum Attacks on RSA-2048 and P-256
Lei Zhang, Yusheng Zhao, Hongshun Yao, Xin Wang
Formalizes Shor's algorithm and the resource estimates for breaking RSA-2048 and P-256 in the Lean proof assistant, using AI agents to write and repair the proofs.