Quantum Computation and Quantum Information (10th Anniversary edition)
By Michael A. Nielsen, Isaac L. Chuang. 2011
4,073 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/3bfb6c2d7a301ab094db12ceaa8812782aaac23b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- M. Cerezo
- Ryan Babbush
- Suguru Endo
- Simon C. Benjamin
- Jarrod R. McClean
- Zhenyu Cai
- Ali Javadi-Abhari
- Ying Li
Citations in the corpus
- Cryogenic MOS Transistor Model (2018, unknown): “Digital, analog, and RF CMOS circuits [15]–[17] are then required to operate at millikelvin temperatures for initialization, manipulation, and read-out of the qubits, as well as error correction [18], [19].”
- Discovering physical concepts with neural networks (2018, unknown): “ars. To parameterize a qubit state ψ with two parameters, the Bloch sphere with parameters θ∈[0,π] and φ∈[0,2π) is used: the state ψ can be written as ψ(θ,φ) = (cos(θ/2),eiφsin(θ/2)) (see for example [73] for more details). Ideally, the 8The function f is not a chart, since it is not injective and i”
- Efficient symmetry-preserving state preparation circuits for the variational quantum eigensolver algorithm (2019, background): “[37] M.”
- Cloud Quantum Computing of an Atomic Nucleus. (2018, background): “Quantum computers promise to reduce the computational complexity of simulating quantum many-body systems from exponential to polynomial [8].”
- Quantum algorithms for electronic structure calculations: Particle-hole Hamiltonian and optimized wave-function expansions (2018, unknown): “denotes the unitary operation acting on qubit q at the i-th position of the gate sequence (similarly for Ẑq(θ j )) [3, 53].”
- Qulacs: a fast and versatile quantum circuit simulator for research purpose (2020, background): “The CPTP-map can be created with a CPTP function.”
- Geometric (2019, background): “Classification constitutes a core cognitive challenge for both biological and artificial intelligence systems, with many tasks potentially reducible to classification problems (Cover, 1965; Chung et al., 2018; DiCarlo et al., 2012; Bernardi et al., 2020).”
- Quantum error mitigation (2022, methodology): “, 2017; Nigg et al., 2014; Vuillot, 2018). However, to the best of our knowledge the first experimental demonstration of symmetry verification using natural symmetries ( ∏ i Zi) in a quantum algorithm was by Sagastizabal et al. (2019) through post-processing, as low-cost techniques to measure natura”
- A PUF taxonomy (2019, methodology): “Steps forward in conventional computer power and quantum computing could therefore invalidate or weaken PPUF systems, in the same manner as RSA factorisation key lengths in public key cryptography [26, 27].”
- Introduction to Weak Measurements and Weak Values (2013, background): “This formulation of the principle states that on a large ensemble of identical particles while measuring some of them with a variable X̂ and the others with a variable P̂ conjugate to X̂, the product of the uncertainties satisfies ∆X∆P > ~ [3, 4].”
- Arbitrary quantum control of qubits in the presence of universal noise (2012, background): “” This phenomenon is especially important in quantum information settings where net error rates deep below faulttolerance thresholds (∼ 10−4) are required in order to build scalable quantum computers [8, 9, 10].”
- Experimental comparison of two quantum computing architectures (2017, methodology): “It is possible to implement the Toffoli gate with five entangling gates if the square root of the CNOT operation is available (15), which is the case with the trapped-ion XX gate.”
- Quantum risk analysis (2018, methodology): “Quantum computers process information using the laws of quantum mechanics.(6) This has opened up novel ways of addressing some problems, e.”
- Superconducting Qubits: Current State of Play (2019, background): “(1), but it is designed in the regime EJ/EC & 50, resulting in an exponential reduction of its charge noise sensitivity and making it a “charge-insensitive charge qubit” (charge is no longer a good quantum number).”
- Characterization and Modeling of 28-nm Bulk CMOS Technology Down to 4.2 K (2018, background): “lems [15]—by mitigating wiring challenges and reducing the thermal-noise contribution from a control system operated at room temperature.”