Probability for Deep Learning Quantum
portes grátis
Probability for Deep Learning Quantum
A Many-Sorted Algebra View
Giardina, Charles R.
Elsevier Science & Technology
01/2025
362
Mole
9780443248344
15 a 20 dias
Descrição não disponível.
1. Introduction to a many sorted algebra view
2. Information geometry
3. Symplectic tomographic probability
4. Born's rule for quantum probability calculations
5. Msa view for a random variable algebra
6. Algebra illustrations using probability indicators
7. Algebras for complex and quaternion RV
8. Msa for stochastic processes and large deviation theory
9. Probability in canonicle commutational relations
10. Applied probability in quantum
11. Entanglement
12. Quasi probability
13. Noisy Intermediate Scale Quantum NISQ Computing
14. Machine Learning Meets Quantum
2. Information geometry
3. Symplectic tomographic probability
4. Born's rule for quantum probability calculations
5. Msa view for a random variable algebra
6. Algebra illustrations using probability indicators
7. Algebras for complex and quaternion RV
8. Msa for stochastic processes and large deviation theory
9. Probability in canonicle commutational relations
10. Applied probability in quantum
11. Entanglement
12. Quasi probability
13. Noisy Intermediate Scale Quantum NISQ Computing
14. Machine Learning Meets Quantum
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Action; Adjusted Rand index; Algebraic closure; Alphatron; Annihilation operator; Ansatz; Antinormal ordering; Baire set; Bernstein polynomials; Bhattacharyya distance; Borel set; Born rule; Bose-Einstein distributing; Bosons; Canonical commutational relations; Central limit theorem; Circuit depth; Circuit width; Cluster coupled; Condensed matter; Connections; Contingency matrix; Contingency table; Cotangent bundle; CPTP channels; Cramer-von Mises; Creation operator; Decoherence; Decoherence time; Dephasing; Dimension function; Direct integral; Displacement operator; Domain snducement; Domain space; Ehrenfest's theorems; Entanglement; Evaluation space; Expectation indicator; Fatou set; Fermi-Dirac distributing; Fermions; Fiber bundle; Fidelity; Fisher-Rao matrix; Fisher-Rao metric; Fock space; Frechet space; Frobenius automorphism; Frobenius covariants; Galois rings; Gamma function; Gaussian wave packet; Generalized uncertainty principle; Germs; Glauber QPD; Gleason's theorem; Glivenko-Cantelli; Hausdorff space; Heisenberg's uncertainty principle; Hilbert transform; HOG; Husimi QPD; IC-POVM; Independent increments; Julia set; Kirkwood-Dirac QPD; Klein-Gordon probability; Kolmogorov axioms; Kolmogorov distance; Kullback-Liebler divergence; Ladder operator; Lagrange-Sylvester interpolation; Laplace's method; Levi-Civita connection; Levy stochastic process; Lie groups; Mahalanobis distance; Majorana fermions; Manifold; Maxwell-Boltzmann distribution; Metaplectic space; Metric space; Modified Rand index; MUB; Nets; NISQ; Noether's theorem; Normal ordering; Number operator; Parallel transport; Partial trace; Particle in a box; Phase space; Polish space; Polyadic graph; Positive operator valued measure; Positive operator valued measures; Probabilistic closure; Probabilistic coupling; Probability sndicator; Projection-valued measures; Proper random variable; Purification; Quantum interference; Quantum machine learning; Quasiprobability distributions; Radon transform; Ramsey-border interferometer; Rand index; Random walk; Range inducement; Range space; Regular space; Riemannian manifold; Riemannian metric; Rigged Hilbert space; Schmidt decomposition; Second countable; Section; SIC-POVM; Split screen experiment; Stationary increments; Stereographic projection; Stirling approximation; Stochastic process; Symmetrical ordering; Symplectic; Teichmuller set construction; Topological space; Triangle inequality; UCCS; Unitary cluster; Vacuum state; Volume; Volume metric; Wave packet; Weyl CCR; Wiener process; Wigner QPD; Young's experiment; ?Field; ?-locally finite
1. Introduction to a many sorted algebra view
2. Information geometry
3. Symplectic tomographic probability
4. Born's rule for quantum probability calculations
5. Msa view for a random variable algebra
6. Algebra illustrations using probability indicators
7. Algebras for complex and quaternion RV
8. Msa for stochastic processes and large deviation theory
9. Probability in canonicle commutational relations
10. Applied probability in quantum
11. Entanglement
12. Quasi probability
13. Noisy Intermediate Scale Quantum NISQ Computing
14. Machine Learning Meets Quantum
2. Information geometry
3. Symplectic tomographic probability
4. Born's rule for quantum probability calculations
5. Msa view for a random variable algebra
6. Algebra illustrations using probability indicators
7. Algebras for complex and quaternion RV
8. Msa for stochastic processes and large deviation theory
9. Probability in canonicle commutational relations
10. Applied probability in quantum
11. Entanglement
12. Quasi probability
13. Noisy Intermediate Scale Quantum NISQ Computing
14. Machine Learning Meets Quantum
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Action; Adjusted Rand index; Algebraic closure; Alphatron; Annihilation operator; Ansatz; Antinormal ordering; Baire set; Bernstein polynomials; Bhattacharyya distance; Borel set; Born rule; Bose-Einstein distributing; Bosons; Canonical commutational relations; Central limit theorem; Circuit depth; Circuit width; Cluster coupled; Condensed matter; Connections; Contingency matrix; Contingency table; Cotangent bundle; CPTP channels; Cramer-von Mises; Creation operator; Decoherence; Decoherence time; Dephasing; Dimension function; Direct integral; Displacement operator; Domain snducement; Domain space; Ehrenfest's theorems; Entanglement; Evaluation space; Expectation indicator; Fatou set; Fermi-Dirac distributing; Fermions; Fiber bundle; Fidelity; Fisher-Rao matrix; Fisher-Rao metric; Fock space; Frechet space; Frobenius automorphism; Frobenius covariants; Galois rings; Gamma function; Gaussian wave packet; Generalized uncertainty principle; Germs; Glauber QPD; Gleason's theorem; Glivenko-Cantelli; Hausdorff space; Heisenberg's uncertainty principle; Hilbert transform; HOG; Husimi QPD; IC-POVM; Independent increments; Julia set; Kirkwood-Dirac QPD; Klein-Gordon probability; Kolmogorov axioms; Kolmogorov distance; Kullback-Liebler divergence; Ladder operator; Lagrange-Sylvester interpolation; Laplace's method; Levi-Civita connection; Levy stochastic process; Lie groups; Mahalanobis distance; Majorana fermions; Manifold; Maxwell-Boltzmann distribution; Metaplectic space; Metric space; Modified Rand index; MUB; Nets; NISQ; Noether's theorem; Normal ordering; Number operator; Parallel transport; Partial trace; Particle in a box; Phase space; Polish space; Polyadic graph; Positive operator valued measure; Positive operator valued measures; Probabilistic closure; Probabilistic coupling; Probability sndicator; Projection-valued measures; Proper random variable; Purification; Quantum interference; Quantum machine learning; Quasiprobability distributions; Radon transform; Ramsey-border interferometer; Rand index; Random walk; Range inducement; Range space; Regular space; Riemannian manifold; Riemannian metric; Rigged Hilbert space; Schmidt decomposition; Second countable; Section; SIC-POVM; Split screen experiment; Stationary increments; Stereographic projection; Stirling approximation; Stochastic process; Symmetrical ordering; Symplectic; Teichmuller set construction; Topological space; Triangle inequality; UCCS; Unitary cluster; Vacuum state; Volume; Volume metric; Wave packet; Weyl CCR; Wiener process; Wigner QPD; Young's experiment; ?Field; ?-locally finite
