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Tensor Networks 2020 – Lecture notes

The course schedule (Stoffplan) can be downloaded here

(Some minor reshuffling of topics might occur during the course of the semester.)

Lecture style

 

DateNotesLecturePagesTopic
28.07.20 Tutorial: MPS-based machine learning (optional)
23.07.20 pdf pdf
ML.1
ML.2
Machine learning
1. Neural networks
2. Supervised learning with tensor networks
22.07.20 pdf pdf
F-PEPS.1
F-PEPS.2
F-PEPS.3
F-PEPS.4
Fermionic PEPS
1. Parity conservation
2. Fermionic signs
3. Jump move
4. Examples
21.07.19 Tutorial: GILT, FET
16.07.20 pdf pdf CanF.1

CanF.2
CanF.3
CanF.4
2D Canonical Forms, Isometric PEPS
1. Canonical form for bond in 2D tensor network
2. Full environment truncation
3. Isometric PEPS: Moses move
4. Isometric PEPS: Applications
15.07.20 pdf pdf TNR.1
TNR.2
TNR.3
TNR.4
TNR.5
TNR.6
TNR: Tensor network renormalization
1. Motivation
2. TNR idea
3. Projective truncation
4. TNR details
5. TNR results in MERA
6. TNR benchmark results
14.07.20 Tutorial: TRG, simple update
09.07.20 pdf pdf TRG-II.1
TRG-II.2
TRG-II.3
TRG-II.4

TRG-II.5
TRG-II.6
TRG-II: Graph-independent local truncations (Gilt)
1. Motivation
2. Why is TRG insufficient?
3. Environment spectrum
4. Gilt: Graph-independent local truncations
5. Gilt-TNR
6. Benchmark results
08.07.20 pdf pdf TRG-I.1

TRG-I.2
TRG-I.3

TRG-I.4
Tensor renormalization group (TRG)
1. TRG for 2D classical lattice models
2. TRG for quantum lattice models
3. Second renormalization (SRG) of tensor network states
4. Core tensor renormalization group (CTRG)
07.07.20 Tutorial: Finite PEPS
02.07.20 pdf pdf PEPS-II.1
PEPS-II.2
PEPS-II.3
PEPS II: contractions via MPS techniques
1. PEPS via finite-size MPS
2. Infinite-size PEPS (iPEPS)
3. Corner transfer matrix (CTM)
01.07.20 pdf pdf PEPS-I.1
PEPS-I.2
PEPS-I.3
PEPS-I.4
PEPS I: Projected entangled-pair states
1. Motivation and Definition
2. Example: RVB state
3. Example: Kitaev's Toric Code
4. Example: Resonating AKLT state
30.06.20 Tutorial: NRG II
25.06.20 pdf pdf NRG-IV.1
NRG-IV.2
NRG-IV.3
NRG-IV.4
NRG IV: Spectral function, fdm-NRG
1. MPS notation for discarded/kept states
2. Complete many-body basis
3. Full-density-matrix NRG (fdmNRG)
4. Spectral functions for SIAM
24.06.20 pdf pdf NRG-III.1
NRG-III.2
NRG-III.3
NRG-III.4
NRG III: Thermal and dynamical quantities
1. Thermodynamic observables
2. Wilson ration. 3. Lehmann representation of spectral functions
4. Single-shell and patching schemes
23.06.20 Tutorial: NRG I
18.06.20 pdf pdf NRG-II.1
NRG-II.2

NRG-II.3

NRG-II.4
NRG-II.5
NRG II: RG flow, fixed points
1. General RG concepts
2. NRG iteration scheme from RG perspective
3. Uncoupled bath Hamiltonian: fixed points
4. Kondo model: fixed points and RG flow
5. Anderson model: fixed points and RG flow
28.05.20 pdf NRG-I
NRG-I.1
NRG-I.2
NRG-I.3
NRG-I.4
NRG I: Numerical Renormalization group - Wilson chain
1. Single-impurity Anderson model
2. Logarithmic discretization
3. Wilson chain
4. Iterative diagonalization
16.06.20 Tutorial: tDMRG. Tangent space methods
11.06.20 Corpus Christi
10.06.20 pdf pdf
TS.1
TS.2
TS.3
TS.4
Tangent space methods (TDVP)
1. MPS and canonical forms.
2. Tangent space.
3. Tangent space projector.
4. Time evolution.
09.06.20 Tutorial: iTEBD
pdf DMRG-III.1-4 DMRG III: tDMRG, finite temperature (purification, XTRG)
1. tDMRG
2. Error analysis
2. Purification
4. Exponential tensor renormalization group (XTRG)
04.06.20 pdf pdf

DMRG-II.1
DMRG-II.2
DMRG-II.3
DMRG II: Traditional DMRG, tDMRG, purification
1. Relation to traditional DMRG.
2. tDMRG.
3. Finite temperature: purification.
03.06.20 pdf

pdf
pdf

pdf
MPS-VI.1



iTEBD.1
iTEBD.2

iTEBD.3
iTEBD.4
MPS VI: Vidal's Gamma-Lambda notation
iTEBD: Infinite Time-Evolving Block Decimation
1. Basic iTEBD algorithm
2. iTEBD in Gamma-Lambda notation
3. iTEBD: Hastings' method
4. Orthogonalization
02.06.20 Tutorial: DMRG
28.05.20 pdf pdf


DMRG-I.1
DMRG-I.2
DMRG-I.3
DMRG-I.4
DMRG I: Density Matrix Renormalization Group - ground state search
1. Single-site optimization
2. Lancos Method
3. Excited states
4. Two-site optimization
27.05.20 pdf pdf
MPS-IV.1
MPS-IV.2
MPS-IV.3
MPS IV: Matrix product operators
1. Applying MPO to MPS yields MPS
2. MPO representation of Heisenberg Hamiltonian
3. Applying MPO to mixed-canonical state
26.05.20 Tutorial: Symmetries & QSpace II
21.05.20 Ascension Day (if needed: Symmetries & QSpace IV)
20.05.20 pdf pdf Sym-III.1
Sym-III.2
Sym-III.3
Sym-III.4
Symmetries III: Outer multiplicity, X-symbols.
1. Motivation
2. Outer multiplicity
3. Arrow inversion
4. Pairwise contractions and X-symbols
19.05.20 Tutorial: Symmetries & QSpace I
14.05.20 pdf pdf
Sym-II.1
Sym-II.2
Sym-II.3
Sym-II.4
Sym-II.5
Sym-II.6
Sym-II.7
Symmetries II: Non-Abelian.
1. Motivation, SU(2) basics
2. Tensor product decomposition
3. Tensor operators
4. A-matrix factorizes
5. Example: two spin 1/2's
6. Example: three spin 1/2's
7. Bookkeeping for unit matrices
13.05.20 pdf pdf
Sym-I.1
Sym-I.1
Sym-I.1
Symmetries I: Abelian
1. Example: spin 1/2 XXZ-chain
2. Iterative diagonalization
3. QSpace bookkeeping for unit matrices
12.05.20 Tutorial: Iterative diagonalization, AKLT Model
07.05.20 pdf pdf

MPS-IV.1
MPS-IV.2
MPS-IV.3
MPS-IV.4
MPS-IV.5
MPS-IV.6
MPS-IV.7
MPS IV: Translationally invariant MPS, AKLT model
1. Transfer matrix
2. Correlation functions
3. AKLT model - general remarks
4. Construction of Hamiltonian
5. AKLT ground state
6. Transfer operator
7. String order parameter
06.05.20 pdf pdf

MPS-III.1
MPS-III.2
MPS-III.3
MPS-III.4
MPS III: Diagonalization, fermionic signs
1. Basis transformation
2. Iterative diagonalization
3. Spinless fermions
4. Spinful fermions
05.05.20 Tutorial: MPS I
30.04.20 pdf pdf
MPS-II.1
MPS-II.2
MPS II: Matrix Product States
1. Matrix elements, expectation values
2. Schmidt decomposition
29.04.20
pdf

pdf

MPS-I.1
MPS-I.2
MPS I: Matrix Product States
1. Overlap and normalization.
2. Canonical MPS forms (left, right, site, bond)
28.04.20 Tutorial: Tensor network basics
23.04.19 Tutorial: MATLAB basics
22.04.20 pdf pdf
TNB-II.1
TNB-II.2
TNB-II.3
Tensor Network basics (TNB) II:
1. Entanglement entropy and area laws
2. Tensor network diagrams
3. Singular-value decomposition (SVD)
21.04.20 pdf pdf
TNB-I.1
TNB-I.2
TNB-I.3
Tensor Network basics (TNB) I:
1. Why study tensor networks?
2. Iterative diagonalization
3. Covariant index notation