formulate-quantum-problem
Acerca de
Esta habilidad ayuda a los desarrolladores a formular problemas de mecánica cuántica o química definiendo el marco matemático, incluyendo el espacio de Hilbert, operadores y condiciones de contorno. Asiste en traducir escenarios físicos a formalismos como la ecuación de Schrödinger y en seleccionar métodos de solución apropiados, como la teoría de perturbaciones o DFT. Úsala al configurar un problema cuántico para su solución analítica o numérica.
Instalación rápida
Claude Code
Recomendadonpx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/formulate-quantum-problemCopia y pega este comando en Claude Code para instalar esta habilidad
Documentación
Formulate Quantum Problem
Physical system → well-posed QM problem: ID DOFs → build H + Hilbert space → BCs → pick approx method → validate vs known limits.
Use When
- Set up QM problem for analytic/numerical solution
- QChem calc (MOs, electronic structure)
- Physical scenario → Dirac/Schrödinger
- Choose perturbation / variational / DFT / exact diag
- Theoretical model for spectroscopic/scattering comparison
In
- Required: system desc (atom, molecule, solid, field)
- Required: target observable (spectrum, rates, ground state)
- Optional: experimental constraints
- Optional: accuracy / compute budget
- Optional: formalism (wave mech, matrix mech, 2nd quant, path int)
Do
Step 1: ID system + DOFs
- Particles: list (electrons, nuclei, photons, phonons) + quantum nums (spin, charge, mass)
- Symmetries: spatial (sph/cyl/trans/crystal), internal (spin/gauge), discrete (P, T)
- Energy scales: which DOFs active vs frozen/adiabatic
- Reduction: Born-Oppenheimer if nuclear/electronic timescales separate; collective coords for many-body
## 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]
→ Complete inventory: particles, QNs, symmetries, active vs frozen justified.
If err: hierarchy unclear → keep all DOFs, flag for scale analysis. Premature truncation → wrong physics.
Step 2: Build H + Hilbert space
- Hilbert space: finite-dim → basis (|↑>, |↓>). Infinite → function space (L²(R³) for 3D single particle).
- Kinetic: each particle. Position rep: T = -ℏ²/(2m) nabla².
- Potential: all interactions (Coulomb, harmonic, spin-orbit, external). Explicit form + coupling.
- Composite H: H = T + V, group by type. Multi-particle: exchange/correlation or note via approx.
- Operator algebra: H Hermitian? Constants of motion ([H,O]=0) → block-diagonalize.
## 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]
→ Complete Hermitian H w/ all terms, Hilbert space defined, constants of motion ID'd.
If err: not Hermitian → missing conjugate / gauge phase. Ambiguous Hilbert space (relativistic) → specify formalism.
Step 3: BCs + initial conditions
- BCs: bound → normalizability (psi→0 at ∞). Scattering → incoming wave. Periodic → Bloch / Born-von Karman.
- Domain: spatial. Box walls. H atom: radial + angular. Lattice + topology.
- Initial state (time-dep): t=0 expansion in eigenbasis or wave packet w/ center + width.
- Constraints: indistinguishable → sym (bosons) / antisym (fermions). Gauge → 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]
→ BCs physically motivated, consistent w/ H domain, unique solution (or scattering matrix).
If err: over/under-determined → check self-adjointness on domain. Non-self-adjoint → handle deficiency indices.
Step 4: Pick approx method
-
Exact solvable: matches known model (HO, H atom, Ising)? → exact + perturbation corrections.
-
Perturbation (weak coupling):
- H = H0 + lambda V, H0 solvable
- lambda V small vs H0 level spacing
- Degeneracy? → degenerate perturbation
- Fits: weak interaction, few-body, analytic needed
-
Variational (ground state):
- Trial wf w/ params
- Satisfies BCs + symmetry
- Fits: ground state energy primary, many-body
-
DFT (many-electron):
- XC functional (LDA, GGA, hybrid)
- Basis (plane waves, Gaussian, NAOs)
- Fits: many-electron, ground state density + energy
-
Numerical exact (small/benchmark):
- Exact diag for small Hilbert
- QMC for ground state sampling
- DMRG for 1D/quasi-1D
- Fits: 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]
→ Justified method + expected accuracy + compute cost + alternatives.
If err: no single method fits → formulate for 2 + compare. Disagreement reveals difficulty.
Step 5: Validate vs limits
- Classical (ℏ→0 or large QNs): H reduces to classical mech.
- Non-interacting: couplings → 0 → product of single-particle states.
- Symmetry: respects all symmetries. H transforms correctly under group.
- Dimensional: every H term = energy. Length/energy/time scales reasonable.
- Known exact: special cases (H atom Z=1, HO quadratic) → reproduced.
## 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] |
→ All pass. Self-consistent, ready to solve.
If err: fail → err in H construction or BCs. Trace to specific term/condition, fix before solving.
Check
- Particles + QNs listed
- Hilbert space + basis
- H Hermitian + correct units
- Constants of motion used
- BCs physically + mathematically sufficient
- Statistics (bos/ferm) enforced
- Method justified + accuracy stated
- Classical, non-interacting, symmetry limits checked
- Known exact reproduced
- Reproducible
Traps
- Premature DOF drop: freeze w/o energy scale arg → wrong physics. Justify every reduction.
- Non-Hermitian H: missing conjugate in spin-orbit / complex V. Verify H=H† explicitly.
- Wrong scattering BCs: bound-state BCs for scattering → discards continuum. Match to question.
- Degeneracy in perturbation: non-deg perturbation on deg level → divergent. Check first.
- Single-method reliance: variational → upper bound but misses excited; perturbation diverges at strong coupling. Cross-validate.
- Unit inconsistency: mixing natural (ℏ=1) + SI. Pick consistent system, state explicitly.
→
derive-theoretical-result— analytic from formulated problemsurvey-theoretical-literature— prior work on similar QM systems
Repositorio GitHub
Habilidades relacionadas
llamaguard
OtroLlamaGuard es el modelo de Meta de 7-8B parámetros para moderar las entradas y salidas de LLM en seis categorías de seguridad como violencia y discurso de odio. Ofrece una precisión del 94-95% y puede implementarse usando vLLM, Hugging Face o Amazon SageMaker. Utiliza esta skill para integrar fácilmente filtrado de contenido y barreras de seguridad en tus aplicaciones de IA.
cost-optimization
OtroEsta Skill de Claude ayuda a los desarrolladores a optimizar los costes en la nube mediante el ajuste de tamaño de recursos, estrategias de etiquetado y análisis de gastos. Proporciona un marco para reducir los gastos en la nube e implementar una gobernanza de costes en AWS, Azure y GCP. Úsala cuando necesites analizar los costes de infraestructura, ajustar el tamaño de los recursos o cumplir con restricciones presupuestarias.
quantizing-models-bitsandbytes
OtroEsta habilidad cuantiza LLMs a precisión de 8 o 4 bits utilizando bitsandbytes, logrando una reducción de memoria del 50-75% con pérdida mínima de precisión. Es ideal para ejecutar modelos más grandes en memoria GPU limitada o para acelerar la inferencia, admitiendo formatos como INT8, NF4 y FP4. La habilidad se integra con HuggingFace Transformers y permite entrenamiento QLoRA y optimizadores de 8 bits.
dispatching-parallel-agents
OtroEsta Skill de Claude despliega múltiples agentes para investigar y solucionar 3 o más problemas independientes de forma concurrente. Está diseñada para escenarios que involucran fallos no relacionados que pueden resolverse sin estado compartido o dependencias. Su capacidad principal es la resolución paralela de problemas, asignando un agente por cada dominio problemático independiente para maximizar la eficiencia.
