Zurück zu Fähigkeiten

formulate-quantum-problem

pjt222
Aktualisiert 2 days ago
3 Ansichten
17
2
17
Auf GitHub ansehen
Anderegeneral

Über

Diese Fähigkeit unterstützt Entwickler dabei, Quantenmechanik- oder Chemieprobleme zu formulieren, indem sie den mathematischen Rahmen definiert, einschließlich Hilbert-Raum, Operatoren und Randbedingungen. Sie leitet die Übersetzung physikalischer Szenarien in Formalismen wie die Schrödinger-Gleichung an und wählt geeignete Lösungsmethoden wie Störungstheorie oder DFT aus. Verwenden Sie sie, wenn Sie ein Quantenproblem für eine analytische oder numerische Lösung einrichten.

Schnellinstallation

Claude Code

Empfohlen
Primär
npx skills add pjt222/agent-almanac -a claude-code
Plugin-BefehlAlternativ
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternativ
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/formulate-quantum-problem

Kopieren Sie diesen Befehl und fügen Sie ihn in Claude Code ein, um diese Fähigkeit zu installieren

Dokumentation

Formulate Quantum Problem

Turn physical system into well-posed quantum problem. Find relevant degrees of freedom. Build Hamiltonian + state space. Set boundary conditions. Pick approximation method. Validate formulation vs known limits.

When Use

  • Set up quantum mechanics problem for analytic or numerical solution
  • Formulate quantum chemistry calculation (molecular orbitals, electronic structure)
  • Translate physical scenario into Dirac or Schrodinger formalism
  • Pick between perturbation theory, variational, DFT, exact diagonalization
  • Prep theoretical model for comparison with experimental spectroscopic or scattering data

Inputs

  • Required: Physical system description (atom, molecule, solid, field)
  • Required: Observables (energy spectrum, transition rates, ground state)
  • Optional: Experimental constraints or data (spectral lines, binding energies)
  • Optional: Desired accuracy or computational budget
  • Optional: Preferred formalism (wave mechanics, matrix mechanics, second quantization, path integral)

Steps

Step 1: Find Physical System + Relevant Degrees of Freedom

Characterize system before writing equations:

  1. Particle content: List particles (electrons, nuclei, photons, phonons) + quantum numbers (spin, charge, mass).
  2. Symmetries: Find spatial (spherical, cylindrical, translational, crystal group), internal (spin rotation, gauge), discrete (parity, time reversal).
  3. Energy scales: Find relevant energy scales. Decide which degrees of freedom active, which frozen or adiabatic.
  4. Degrees of freedom shrink: Apply Born-Oppenheimer if nuclear + electronic timescales separate. Find collective coordinates if many-body simplify.
## System Characterization
- **Particles**: [list with quantum numbers]
- **Active degrees of freedom**: [coordinates, spins, fields]
- **Frozen degrees of freedom**: [and justification for freezing]
- **Symmetry group**: [continuous and discrete]
- **Energy scale hierarchy**: [e.g., electronic >> vibrational >> rotational]

Got: Complete inventory — particles, quantum numbers, symmetries, justified active vs frozen degrees of freedom.

If fail: Energy scale hierarchy unclear? Keep all degrees of freedom, flag need for scale analysis. Premature truncation → qualitatively wrong physics.

Step 2: Build Hamiltonian + State Space

Build math framework from degrees of freedom in Step 1:

  1. Hilbert space: Define state space. Finite-dim → specify basis (spin-1/2 |up>, |down>). Infinite-dim → specify function space (L2(R^3) for single particle in 3D).
  2. Kinetic terms: Kinetic operator each particle. Position: T = -hbar^2/(2m) nabla^2.
  3. Potential terms: All interaction potentials (Coulomb, harmonic, spin-orbit, external). Explicit functional form + coupling constants.
  4. Composite Hamiltonian: Assemble H = T + V, group by interaction type. Multi-particle → include exchange + correlation or note approximation entry.
  5. Operator algebra: Verify Hamiltonian Hermitian. Find constants of motion ([H, O] = 0) for block-diagonalization.
## Hamiltonian Structure
- **Hilbert space**: [definition and basis]
- **H = T + V decomposition**:
  - T = [kinetic terms]
  - V = [potential terms, grouped by type]
- **Constants of motion**: [operators commuting with H]
- **Symmetry-adapted basis**: [if block diagonalization is possible]

Got: Complete Hermitian Hamiltonian, all terms explicit. Hilbert space defined. Constants of motion identified.

If fail: Not manifestly Hermitian? Check missing conjugate terms or gauge phases. Hilbert space ambiguous (relativistic)? Specify formalism explicit, note issue.

Step 3: Set Boundary + Initial Conditions

Constrain problem for unique solution:

  1. Boundary conditions: Bound state → normalizability (psi -> 0 at infinity). Scattering → incoming wave boundary. Periodic → Bloch or Born-von Karman.
  2. Domain restrictions: Spatial domain. Particle in box → walls. Hydrogen atom → radial + angular. Lattice models → lattice + topology.
  3. Initial state (time-dependent): State at t=0 as expansion in energy eigenbasis or wave packet with center + width.
  4. Constraint equations: Indistinguishable particles → symmetrize (bosons) or antisymmetrize (fermions). Gauge theories → gauge-fixing.
## Boundary and Initial Conditions
- **Spatial domain**: [definition]
- **Boundary type**: [Dirichlet / Neumann / periodic / scattering]
- **Normalization**: [condition]
- **Particle statistics**: [bosonic / fermionic / distinguishable]
- **Initial state** (if time-dependent): [specification]

Got: Boundary conditions physically motivated, mathematically consistent with Hamiltonian domain, sufficient for unique solution (or well-defined scattering matrix).

If fail: Over- or under-determined? Check self-adjointness of Hamiltonian on chosen domain. Non-self-adjoint → careful treatment of deficiency indices.

Step 4: Pick Approximation Method

Pick solution strategy for problem structure:

  1. Check exact solvability: Problem reduces to known exactly solvable model (harmonic oscillator, hydrogen atom, Ising)? Yes → use exact + perturbation for corrections.

  2. Perturbation theory (weak coupling):

    • Split H = H0 + lambda V, H0 exactly solvable
    • Verify lambda V small vs level spacing of H0
    • Check degeneracy; degenerate perturbation theory if needed
    • Good for: weak interaction, few-body, analytic results
  3. Variational methods (ground state):

    • Trial wave function with adjustable parameters
    • Trial function satisfies boundary + symmetry
    • Good for: ground state energy target, many-body
  4. Density Functional Theory (many-electron):

    • Exchange-correlation functional (LDA, GGA, hybrid)
    • Basis set (plane waves, Gaussian, numerical atomic orbitals)
    • Good for: many-electron, ground state density + energy
  5. Numerical exact methods (small, benchmarking):

    • Exact diagonalization for small Hilbert spaces
    • Quantum Monte Carlo for ground state sampling
    • DMRG for 1D or quasi-1D
    • Good for: high accuracy, small system
## Approximation Method Selection
- **Method chosen**: [name]
- **Justification**: [why this method fits the problem structure]
- **Expected accuracy**: [order of perturbation, variational bound quality, DFT functional accuracy]
- **Computational cost**: [scaling with system size]
- **Alternatives considered**: [and why they were rejected]

Got: Justified choice with clear accuracy + cost. Alternatives documented.

If fail: No single method clearly right? Formulate for two methods + compare. Disagreement reveals difficulty + guides refinement.

Step 5: Validate Formulation vs Known Limits

Before solving, verify formulation reproduces known physics:

  1. Classical limit: Take hbar -> 0 (or large quantum numbers), verify Hamiltonian reduces to correct classical mechanics.
  2. Non-interacting limit: Set couplings to zero, verify solution = product of single-particle states.
  3. Symmetry limits: Verify formulation respects all identified symmetries. Check Hamiltonian transforms correctly under symmetry group.
  4. Dimensional analysis: Verify every term has units of energy. Check characteristic length, energy, time scales physically reasonable.
  5. Known exact results: Special cases (hydrogen atom Z=1, harmonic oscillator quadratic potential)? Verify formulation reproduces them.
## Validation Checks
| Check | Expected Result | Status |
|-------|----------------|--------|
| Classical limit (hbar -> 0) | [classical Hamiltonian] | [Pass/Fail] |
| Non-interacting limit | [product states] | [Pass/Fail] |
| Symmetry transformation | [correct representation] | [Pass/Fail] |
| Dimensional analysis | [all terms in energy units] | [Pass/Fail] |
| Known exact case | [reproduced result] | [Pass/Fail] |

Got: All validation checks pass. Formulation self-consistent, ready to solve.

If fail: Failed check = error in Hamiltonian construction or boundary. Trace to term or condition, fix before solving.

Checks

  • All particles + quantum numbers explicit
  • Hilbert space defined with clear basis
  • Hamiltonian Hermitian + all terms correct units
  • Constants of motion identified + used for simplification
  • Boundary conditions physically motivated + mathematically sufficient
  • Particle statistics (bosonic/fermionic) correctly enforced
  • Approximation method choice justified + accuracy stated
  • Classical, non-interacting, symmetry limits checked
  • Known exact results reproduced special cases
  • Formulation complete for implementation

Pitfalls

  • Dropping degrees of freedom early: Freezing without energy scale check misses physics. Always justify with scale argument.
  • Non-Hermitian Hamiltonian: Forgetting conjugate terms in spin-orbit or complex potentials. Verify H = H-dagger explicit.
  • Wrong boundary for scattering: Bound-state boundary (normalizability) for scattering discards continuous spectrum. Match boundary to physical question.
  • Ignoring degeneracy in perturbation theory: Non-degenerate on degenerate level → divergent corrections. Check degeneracy before expanding.
  • Over-rely on single approximation: Different methods = complementary failure modes. Variational → upper bounds but miss excited states. Perturbation diverges at strong coupling. Cross-validate when possible.
  • Dimensional inconsistency: Mixing natural units (hbar = 1) with SI in same expression. Pick unit system at start, state it explicit.

See Also

  • derive-theoretical-result -- derive analytic results from formulated problem
  • survey-theoretical-literature -- prior work on similar quantum systems

GitHub Repository

pjt222/agent-almanac
Pfad: i18n/caveman/skills/formulate-quantum-problem
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Verwandte Skills

llamaguard

Andere

LlamaGuard ist Metas 7-8B-Parameter-Modell zur Moderation von LLM-Eingaben und -Ausgaben in sechs Sicherheitskategorien wie Gewalt und Hassrede. Es bietet eine Genauigkeit von 94-95 % und kann mit vLLM, Hugging Face oder Amazon SageMaker eingesetzt werden. Nutzen Sie diese Skill, um Inhaltsfilterung und Sicherheitsguardrails einfach in Ihre KI-Anwendungen zu integrieren.

Skill ansehen

cost-optimization

Andere

Diese Claude Skill unterstützt Entwickler bei der Optimierung von Cloud-Kosten durch Ressourcen-Dimensionierung, Tagging-Strategien und Ausgabenanalysen. Sie bietet einen Rahmen zur Senkung von Cloud-Ausgaben und zur Implementierung von Kosten-Governance für AWS, Azure und GCP. Nutzen Sie sie, wenn Sie Infrastrukturkosten analysieren, Ressourcen richtig dimensionieren oder Budgetvorgaben einhalten müssen.

Skill ansehen

quantizing-models-bitsandbytes

Andere

Diese Fähigkeit quantisiert LLMs auf 8-Bit- oder 4-Bit-Präzision mittels bitsandbytes und erreicht dabei eine Speicherreduzierung von 50–75 % bei minimalem Genauigkeitsverlust. Sie ist ideal für den Betrieb größerer Modelle mit begrenztem GPU-Speicher oder zur Beschleunigung von Inferenzvorgängen und unterstützt Formate wie INT8, NF4 und FP4. Die Fähigkeit integriert sich in HuggingFace Transformers und ermöglicht QLoRA-Training sowie 8-Bit-Optimierer.

Skill ansehen

dispatching-parallel-agents

Andere

Diese Claude-Fähigkeit verteilt mehrere Agenten, um drei oder mehr unabhängige Probleme gleichzeitig zu untersuchen und zu beheben. Sie ist für Szenarien konzipiert, die unabhängige Fehler umfassen, die ohne gemeinsamen Zustand oder Abhängigkeiten gelöst werden können. Die Kernfähigkeit ist die parallele Problemlösung, bei der pro unabhängigem Problembereich ein Agent zugewiesen wird, um die Effizienz zu maximieren.

Skill ansehen