dqmc-advanced — community dqmc-advanced, community, ide skills

v1.0.0
GitHub

About this Skill

Perfect for Quantum Computing Agents needing advanced DQMC capabilities and unequal-time measurements. Advanced DQMC features including unequal-time measurements, analytic continuation, and queue system internals. Use when enabling dynamical correlations, performing MaxEnt continuation, or understandin

edwnh edwnh
[16]
[4]
Updated: 2/21/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
7/11
Quality Score
30
Canonical Locale
en
Detected Body Locale
en

Perfect for Quantum Computing Agents needing advanced DQMC capabilities and unequal-time measurements. Advanced DQMC features including unequal-time measurements, analytic continuation, and queue system internals. Use when enabling dynamical correlations, performing MaxEnt continuation, or understandin

Core Value

Empowers agents to perform advanced DQMC analysis using unequal-time measurements and analytic continuation, enabling the calculation of zero-frequency susceptibilities and time-dependent correlation functions with maximum entropy methods.

Ideal Agent Persona

Perfect for Quantum Computing Agents needing advanced DQMC capabilities and unequal-time measurements.

↓ Capabilities Granted for dqmc-advanced

Generating advanced DQMC data for quantum many-body systems
Calculating zero-frequency susceptibilities using unequal-time measurements
Performing analytic continuation for real-frequency data

! Prerequisites & Limits

  • Significantly increases runtime and memory usage due to unequal-time measurements
  • Requires specific setup with `period_uneqlt > 0` during file generation

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

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Install Path

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Workflow

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Labs Demo

Browser Sandbox Environment

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FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is dqmc-advanced?

Perfect for Quantum Computing Agents needing advanced DQMC capabilities and unequal-time measurements. Advanced DQMC features including unequal-time measurements, analytic continuation, and queue system internals. Use when enabling dynamical correlations, performing MaxEnt continuation, or understandin

How do I install dqmc-advanced?

Run the command: npx killer-skills add edwnh/dqmc/dqmc-advanced. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for dqmc-advanced?

Key use cases include: Generating advanced DQMC data for quantum many-body systems, Calculating zero-frequency susceptibilities using unequal-time measurements, Performing analytic continuation for real-frequency data.

Which IDEs are compatible with dqmc-advanced?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for dqmc-advanced?

Significantly increases runtime and memory usage due to unequal-time measurements. Requires specific setup with `period_uneqlt > 0` during file generation.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add edwnh/dqmc/dqmc-advanced. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use dqmc-advanced immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

dqmc-advanced

Install dqmc-advanced, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

Advanced Topics

Unequal-Time Measurements

Enable by setting period_uneqlt > 0 during file generation:

bash
1dqmc-util gen period_uneqlt=8 ...

Required for:

  • nnrw0, zzrw0 - Zero-frequency susceptibilities
  • dwq0t - D-wave pair susceptibility
  • Any time-dependent correlation functions

Note: Unequal-time measurements significantly increase runtime and memory usage.

Analytic Continuation

Use maximum entropy for continuing imaginary-time data to real frequencies:

python
1from dqmc_util import maxent
2
3# Solve G = K A given:
4# - G: binned data, shape (nbin, ntau)
5# - K: kernel, shape (ntau, nw)
6# - m: default model, shape (nw,)
7A_omega = maxent.calc_A(G, K, m)

HDF5 File Structure

/metadata/     # Model info (mu, Nx, Ny, beta)
/params/       # Simulation parameters, precomputed matrices
/state/        # RNG state, sweep number, aux field config
/meas_eqlt/    # Equal-time measurements (n_sample, sign, den, ...)
/meas_uneqlt/  # Unequal-time measurements (optional)

Queue System Internals

The sharded queue uses:

  • 128 shards to avoid lock contention on distributed filesystems
  • Atomic rename() operations for task claiming
  • Symlinks moved: todo/ -> running/ -> done/
  • Checkpointed jobs returned to todo/ for resumption

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