Introduction to MERA Sukhwinder Singh Macquarie University Tensors Multidimensional array of complex numbers Ti1i2 b b a a a B ra : K et : 1 2 3 * 1 * 2 a M a trix * 3 M 11 M 21 M 31 ik M 12 M 22 M 3 2 c R a n k-3 T en so r M 11 c 1 M 21 M 31 M 12 M 22 M 3 2 N 11 c 2 N 21 N 31 N 12 N 22 N 3 2 Cost of Contraction c b R c b P = f e Q a a R abc P ebcf Q aef ef co st a b c e f i1i 2 iN i1 i1 i 2 i2 iN 1 iN Made of layers Total number of components = O( N 4 ) Disentanglers & Isometries U U † W W † 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 W dim (V ) dim (W ) V E xam ple : Isom etry Layer is a coarse-graining transformation Coarse graining of operators Coarse graining of operators Coarse graining of operators Coarse graining of operators Coarse graining of operators Coarse graining of operators Coarse graining of operators Cost of contraction = O( p ) Local operators coarse-grained to local operators. Scaling Superoperator Scaling Superoperator MERA defines an RG flow Scale L3 L2 L1 L0 Wavefunction on coarse-grained lattice with two sites Types of MERA Types of MERA Binary MERA Ternary 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 MERA M ERA O M ERA Perform contraction layer by layer Cost = O( p log 2 N ) Efficient! 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 C (l ) e S ( l ) const l / 2) Critical Hamiltonian C (l ) l a a0 S ( l ) log( l ) l In any MERA Correlations decay polynomially Entropy grows logarithmically Correlations in the MERA log l steps T r ( O C O A R SE ) Tr S log l log l l O1O 2 log l 0 1; q 0 q Correlations in the MERA log l steps M T r ( O C O A R SE ) Tr M log l log log l l O1O 2 M l 0 1; q 0 q † log l Entanglement entropy in the MERA l sites S log l rank ( ) ( const ) log l Entanglement entropy in the MERA Entanglement entropy in the MERA Entanglement entropy in the MERA Entanglement entropy in the MERA l sites log l steps Entanglement entropy in the MERA l sites log l steps Entanglement entropy in the MERA l sites log l steps l d S log l d l log l 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. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Time 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Space 0 0 0 0 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 g g † g g S U (2) g † g g † g MERA and spin networks 0 0 11 2 c a ( ja , m a , t a ) b ( jb , m b , t b ) a 01 b 01 c ( jc , m c , t c ) MERA and spin networks ( jc , t c ) ( jc , m c , t c ) ( jc , m c ) ( j a , m a , t a ) ( jb , m b , t b ) ( ja , t a ) ( jb , t b ) ( ja , m a ) (Wigner-Eckart Theorem) ( jb , m b ) MERA and spin networks MERA and spin networks MERA and spin networks j1 j 2 jR 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.