000			02050nam a2200277 4500
005			20250618124644.0
008			250618b |||||||| |||| 00| 0 eng d
020			_a9798886130805
040			_aCSL _cCSL
041			_2eng _aeng
084			_aD65,8(B)5 R4 _qCSL
100			_aSwan, Melanie _eauthor _9813075
245			_aQuantum computing _b: Physics, blockchains, and deep learning smart networks
260			_aSingapore : _bWorld Scientific, _c2024.
300			_axxi, 377p. _b: ill. _c; 23 cm.
490			_aBetween science and economics; 2v.
500			_aIncludes references, glossary and index
520			_aQuantum Computing for the Brain argues that the brain is the killer application for quantum computing. No other system is as complex, as multidimensional in time and space, as dynamic, as less well-understood, as of peak interest, and as in need of three-dimensional modeling as it functions in real-life, as the brain. Quantum computing has emerged as a platform suited to contemporary data processing needs, surpassing classical computing and supercomputing. This book shows how quantum computing's increased capacity to model classical data with quantum states and the ability to run more complex permutations of problems can be employed in neuroscience applications such as neural signaling and synaptic integration. State-of-the-art methods are discussed such as quantum machine learning, tensor networks, Born machines, quantum kernel learning, wavelet transforms, Rydberg atom arrays, ion traps, boson sampling, graph-theoretic models, quantum optical machine learning, neuromorphic architectures, spiking neural networks, quantum teleportation, and quantum walks.
650			_aBlockchains _9813076
650			_aField theory
650			_aSmart networks _9813077
650			_aQuantum computing _9714398
700			_ados Santos, Renato P. _eco-author _9813082
700			_aWitte, Frank _eco-author _9813083
942			_2CC _n0 _cTEXL _hD65,8(B)5 R4
999			_c1431839 _d1431839