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using-itensors

Execute DMRG and TEBD tensor network simulations for quantum many-body systems with ITensors.jl.

60|92|Updated Apr 30, 2026
Search Tags:#simulation#physics#julia#quantum#tensor-networks#dmrg
One-click install
npx skills add https://github.com/QuantumBFS/quantum.harness --skill using-itensors
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: using-itensors
Source: https://github.com/QuantumBFS/quantum.harness/tree/main/skills/using-itensors
Command: npx skills add https://github.com/QuantumBFS/quantum.harness --skill using-itensors

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ITensors, ITensorMPS, KrylovKit, MPSKit, and includes references (resource) components.

What problem does it solve?

This skill provides a standardized interface for running complex quantum many-body simulations using the ITensors.jl ecosystem, ensuring that researchers follow best practices for DMRG, TEBD, and MPS workflows.

Core Features & Use Cases

  • Workflow Orchestration: Manages the software layer for DMRG ground state searches and real/imaginary-time TEBD evolution.
  • Parameter Guidance: Provides expert-curated starting points for bond dimensions, truncation cutoffs, and sweep schedules to ensure convergence.
  • Use Case: A researcher needs to compute the ground state of a 1D Heisenberg chain; this skill guides the setup of the Hamiltonian MPO, the initial state in the correct symmetry sector, and the iterative DMRG execution.

Quick Start

Use the using-itensors skill to initialize a DMRG simulation for a spin-half chain with conserved quantum numbers.

Frequently Asked Questions about using-itensors

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run DMRG ground state calculations for a 1D Heisenberg chain in Julia?▼

To run DMRG ground state calculations, this skill guides setting up the Hamiltonian MPO, initializing the correct symmetry sector, and executing iterative DMRG using ITensorMPS.jl for your 1D lattice models.

What is the best way to set bond dimensions and truncation cutoffs for tensor network simulations?▼

The best way to set bond dimensions and truncation cutoffs is using the expert-curated starting points and sweep schedules provided, which ensure proper convergence during DMRG and TEBD workflows.

Do I need a specific Julia environment configured to perform TEBD time evolution?▼

Yes, you need a configured Julia environment with the ITensors and ITensorMPS packages installed to perform TEBD time evolution and execute block-sparse tensor contractions.

Can I use ITensors.jl for real and imaginary-time TEBD evolution in quasi-1D lattice models?▼

Yes, you can use ITensors.jl for real and imaginary-time TEBD evolution in 1D and quasi-1D lattice models, managing the software layer to ensure researchers follow best practices.

How does MPS-based measurement work after finding a ground state with DMRG?▼

MPS-based measurement works by evaluating observables on the matrix product state obtained from your DMRG run, utilizing SVD-based truncations and block-sparse tensor contractions within the ITensors ecosystem.

Why should I not use standard tensor contractions when my simulation requires conserved quantum numbers?▼

You should avoid standard contractions because this skill utilizes block-sparse tensor contractions via ITensorMPS.jl to properly handle conserved quantum numbers and maintain the correct symmetry sector during simulations.

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