PPT-Product-state approximations to quantum ground states

Fernando Brandão UCL Aram Harrow MIT arXiv 13100017 Constraint Satisfaction Problems x 1 c 1 c 2 c 3 k CSP Variables x 1 x n in Σ n Alphabet Σ Constraints . 1 This relation is the socalled binomial expansion It certainly is an improvement over multiplying out ababab by hand The series in eq 1 can be used for any value of n integer or not but when n is an integer the series terminates or ends after n1 te Dieter Jaksch. Outline. Lecture 1: Introduction. What defines a quantum simulator? Quantum simulator criteria. Strongly correlated quantum systems.. Lecture 2: Optical lattices. Bose-Einstein condensation, adiabatic loading of an optical lattice. Hamiltonian . Chapter 12. E-mail: . benzene4president@gmail.com. Web-site: http://clas.sa.ucsb.edu/staff/terri/. Quantum – . ch 12. 1. A photon has a frequency (v) of 5.45 x 10. 8. MHz. a. Calculate the photons wavelength (λ) in nm. Quantum Hamiltonian Complexity. Aram Harrow (MIT). Simons Institute. 16 Jan 2014. Entanglement. Original motivation for quantum computing. [Feynman ‘82]. Nature isn't classical, dammit, and if you want to make a simulation of Nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy.. Collection of two-state quantum systems (. qubits. ). Operations which manipulate isolated . qubits. or pairs of . qubits. Initialise. . qubit. to . single state. Detect . qubit. state. Large scale device:. Groundstates. Fernando . G.S.L. . Brand. ão. Imperial -> UCL. Based on joint work with . A. Harrow . . Paris, April 2013. Quantum Many-Body Systems. Quantum Hamiltonian . Aram Harrow (MIT). Simons Institute 2014.1.17. a theorem. Let M. 2. R. +. m. £. n. .. Say that a set S. ⊆[n]. k. is δ-good if . ∃φ:[m]. k. .  S. such that ∀(j. 1,. …, j. k. )∈S, . f(k,δ):= max{ |S| : ∃S⊆[n]. Local algebraic approximations. Variants on Taylor series. Local-Global approximations. Variants on “fudge factor”. Local algebraic approximations. Linear Taylor series. Intervening variables. Transformed approximation.  . in Various Civilizations. Rachel Barnett.  . BC. Babylon. ∏. = . 3 ⅛ = 3.125. A. B. C. D. E. Egypt. ∏ . = 4(8/9)² = 3.16049…. Problem number 50 . Rhind Papyrus. Quantum Hamiltonian Complexity. Aram Harrow (MIT). Simons Institute. 16 Jan 2014. Entanglement. Original motivation for quantum computing. [Feynman ‘82]. Nature isn't classical, dammit, and if you want to make a simulation of Nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy.. m. otivation, capabilities. 1D theory .  1D-solver for waves. i. mplementation (without and with Lorentz transformation). e. xcitation of waves (single particle). w. ithout self effects. one and few particles with self effects. Insu. Yu. 27 May 2010. ACM Transactions on Applied Perception . (Presented at APGV 2009). Introduction. Can you see difference ? . Traditionally GI (Path tracing, photon mapping, ray-tracing) uses . The Quantum Computer. Quantum computers, like all computers, are machines that perform calculations upon data.. Quantum computers use the principles of superposition and entanglement from the field of quantum mechanics to aid in the performance of these calculations. ” Workshop is to discuss theoretical and experimental hot issues related to quantum physics, from foundational issues (such as findings and ideas to investigate quantum effects in biological systems. The Workshop is supported by .