Introduction to MERA Sukhwinder Singh Macquarie University.

Slides:



Advertisements
Similar presentations
MERA in 2D ( Multi-scale Entanglement Renormalization Ansatz )
Advertisements

What Have I Learned From Scott AaronsonDave Bacon PhysicistsComputer Scientists and What Else Would I Like to Learn from Them?
University of Queensland
Identifying universal phases for measurement-based quantum computing Stephen Bartlett in collaboration with Andrew Doherty (UQ)
Sergey Bravyi, IBM Watson Center Robert Raussendorf, Perimeter Institute Perugia July 16, 2007 Exactly solvable models of statistical physics: applications.
APRIL 2010 AARHUS UNIVERSITY Simulation of probed quantum many body systems.
Matrix product states for the absolute beginner
Preparing Projected Entangled Pair States on a Quantum Computer Martin Schwarz, Kristan Temme, Frank Verstraete University of Vienna, Faculty of Physics,
Preparing Topological States on a Quantum Computer Martin Schwarz (1), Kristan Temme (1), Frank Verstraete (1) Toby Cubitt (2), David Perez-Garcia (2)
Quantum Information Theory and Strongly Correlated Quantum Systems
Z. Y. Xie ( 谢志远 ) Institute of Physics, Chinese Academy of Sciences Tensor Renormalization in classical statistical models and quantum.
Tensor Network in Chemistry: Recent DMRG/TTNS Studies and Perspectives for Catalysis Research Naoki Nakatani Catalysis Research Center, Hokkaido University,
Andy Ferris International summer school on new trends in computational approaches for many-body systems Orford, Québec (June 2012) Multiscale Entanglement.
Complexity of simulating quantum systems on classical computers Barbara Terhal IBM Research.
Phase Diagram of One-Dimensional Bosons in Disordered Potential Anatoli Polkovnikov, Boston University Collaboration: Ehud Altman-Weizmann Yariv Kafri.
Quantum fermions from classical statistics. quantum mechanics can be described by classical statistics !
Entanglement Renormalization Frontiers in Quantum Nanoscience A Sir Mark Oliphant & PITP Conference Noosa, January 2006 Guifre Vidal The University of.
Schrödinger’s Elephants & Quantum Slide Rules A.M. Zagoskin (FRS RIKEN & UBC) S. Savel’ev (FRS RIKEN & Loughborough U.) F. Nori (FRS RIKEN & U. of Michigan)
Quantum Mechanics from Classical Statistics. what is an atom ? quantum mechanics : isolated object quantum mechanics : isolated object quantum field theory.
Efficient Quantum State Tomography using the MERA in 1D critical system Presenter : Jong Yeon Lee (Undergraduate, Caltech)
Quantum fermions from classical statistics. quantum mechanics can be described by classical statistics !
Lattice QCD 2007Near Light Cone QCD Near Light Cone QCD On The Lattice H.J. Pirner, D. Grünewald E.-M. Ilgenfritz, E. Prokhvatilov Partially funded by.
Simulating Physical Systems by Quantum Computers J. E. Gubernatis Theoretical Division Los Alamos National Laboratory.
Multipartite Entanglement Measures from Matrix and Tensor Product States Ching-Yu Huang Feng-Li Lin Department of Physics, National Taiwan Normal University.
Quantum Algorithms for Neural Networks Daniel Shumow.
CLARENDON LABORATORY PHYSICS DEPARTMENT UNIVERSITY OF OXFORD and CENTRE FOR QUANTUM TECHNOLOGIES NATIONAL UNIVERSITY OF SINGAPORE Quantum Simulation Dieter.
Entanglement Area Law (from Heat Capacity)
Introduction to Tensor Network States Sukhwinder Singh Macquarie University (Sydney)
Entanglement entropy and the simulation of quantum systems Open discussion with pde2007 José Ignacio Latorre Universitat de Barcelona Benasque, September.
Holographic Entanglement Entropy from Cond-mat to Emergent Spacetime
Germán Sierra, Instituto de Física Teórica UAM-CSIC, Madrid 9th Bolonia Workshop in CFT and Integrable Systems Bolonia, Sept 2014.
Area law and Quantum Information José Ignacio Latorre Universitat de Barcelona Cosmocaixa, July 2006.
Dilations Section 9.7. Dilation A dilation is a transformation that stretches or shrinks a figure to create a similar figure. A dilation is not an isometry.
Implementation of Quantum Computing Ethan Brown Devin Harper With emphasis on the Kane quantum computer.
PEPS, matrix product operators and the algebraic Bethe ansatz
Barriers in Hamiltonian Complexity Umesh V. Vazirani U.C. Berkeley.
Tensor networks and the numerical study of quantum and classical systems on infinite lattices Román Orús School of Physical Sciences, The University of.
A simple nearest-neighbour two-body Hamiltonian system for which the ground state is a universal resource for quantum computation Stephen Bartlett Terry.
Quasi-1D antiferromagnets in a magnetic field a DMRG study Institute of Theoretical Physics University of Lausanne Switzerland G. Fath.
Dilations. Transformation – a change in position, size, or shape of a figure Preimage – the original figure in the transformation Image – the shape that.
Experimental Quantification of Entanglement in low dimensional Spin Systems Chiranjib Mitra IISER-Kolkata Quantum Information Processing and Applications.
Self-assembling tensor networks and holography in disordered spin chains A.M. Goldsborough, R.A. Roemer Department of Physics and Centre for Scientific.
KITPC Max Planck Institut of Quantum Optics (Garching) Tensor networks for dynamical observables in 1D systems Mari-Carmen Bañuls.
A counterexample for the graph area law conjecture Dorit Aharonov Aram Harrow Zeph Landau Daniel Nagaj Mario Szegedy Umesh Vazirani arXiv:
Entanglement Loss Along RG Flows Entanglement and Quantum Phase Transitions José Ignacio Latorre Dept. ECM, Universitat de Barcelona Newton Institute,
E. Todesco, Milano Bicocca January-February 2016 Appendix A: A digression on mathematical methods in beam optics Ezio Todesco European Organization for.
Panjin Kim*, Hosho Katsura, Nandini Trivedi, Jung Hoon Han
Quantum Shift Register Circuits Mark M. Wilde arXiv: National Institute of Standards and Technology, Wednesday, June 10, 2009 To appear in Physical.
Arnau Riera, Grup QIC, Universitat de Barcelona Universität Potsdam 10 December 2009 Simulation of the Laughlin state in an optical lattice.
Real space RG and the emergence of topological order Michael Levin Harvard University Cody Nave MIT.
G. Florio Dipartimento di Fisica, Università di Bari, Italy
Scale vs Conformal invariance from holographic approach
Quantum algorithm for the Laughlin wave function
Quantum Information and Everything.
Generalized DMRG with Tree Tensor Network
2nd Lecture: QMA & The local Hamiltonian problem
The Harmonic Oscillator
On MPS and PEPS… David Pérez-García. Near Chiemsee
OSU Quantum Information Seminar
Quantum Convolutional Neural Networks (QCNN)
Quantum computation with classical bits
Introducing complex networks into quantum regime
Topological Magnon Bands in AFM limit of Shastry-Sutherland Lattice
in collaboration with Andrew Doherty (UQ)
Tensor Network Simulations of QFT in Curved Spacetime
Computational approaches for quantum many-body systems
Computational approaches for quantum many-body systems
Computational approaches for quantum many-body systems
A quantum machine learning algorithm based on generative models
Presentation transcript:

Introduction to MERA Sukhwinder Singh Macquarie University

Multidimensional array of complex numbers Tensors

Cost of Contraction a bc a d =

Made of layers

Disentanglers & Isometries

Different ways of looking at the MERA 1.Coarse-graining transformation. 2.Efficient description of ground states on a classical computer. 3.Quantum circuit to prepare ground states on a quantum computer. 4.A specific realization of the AdS/CFT correspondence.

Coarse-graining transformation Length Scale

Coarse-graining transformation

Layer is a coarse-graining transformation

Coarse graining of operators

Scaling Superoperator

MERA defines an RG flow Wavefunction on coarse-grained lattice with two sites

Types of MERA

Binary MERATernary MERA

Different ways of looking at the MERA 1.Coarse-graining transformation. 2.Efficient description of ground states on a classical computer. 3.Quantum circuit to prepare ground states on a quantum computer. 4.A specific realization of the AdS/CFT correspondence.

Expectation values from the MERA

“Causal Cone” of the MERA

But is the MERA good for representing ground states? Claim: Yes! Naturally suited for critical systems.

Recall! 1)Gapped Hamiltonian  2)Critical Hamiltonian 

In any MERA Correlations decay polynomially Entropy grows logarithmically

Correlations in the MERA

Entanglement entropy in the MERA

Therefore MERA can be used a variational ansatz for ground states of critical Hamiltonians

Different ways of looking at the MERA 1.Coarse-graining transformation. 2.Efficient description of ground states on a classical computer. 3.Quantum circuit to prepare ground states on a quantum computer. 4.A specific realization of the AdS/CFT correspondence.

Time Space

Different ways of looking at the MERA 1.Coarse-graining transformation. 2.Efficient description of ground states on a classical computer. 3.Quantum circuit to prepare ground states on a quantum computer. 4.A specific realization of the AdS/CFT correspondence.

Figure Source: Evenbly, Vidal 2011

MERA and spin networks

(Wigner-Eckart Theorem)

MERA and spin networks

Summary – MERA can be seen as.. 1.As defining a RG flow. 2.Efficient description of ground states on a classical computer. 3.Quantum circuit to prepare ground states on a quantum computer. 4.Specific realization of the AdS/CFT correspondence.