adapt.computational_tools

Module Contents

Functions

oo_vqe(params, H, ansatz, ref, singles[, knorm, tnorm])

product_hessian(params, H, ansatz, ref)

ML_M(params, H, ansatz, ref)

Gradient_S(params, H, ansatz, ref)

soln_analysis(params, H, ansatz, ref, label)

ML_M_dumb(params, H, ansatz, ref)

product_gradient(params, H, ansatz, ref)

prep_state(ops, ref, params)

product_energy(params, H, ansatz, ref)

simple_energy(params, H, ansatz, ref)

simple_uccsd_energy(params, H, ansatz, ref)

simple_vccsd_energy(params, H, ansatz, ref)

simple_gradient(params, H, ansatz, ref)

sum_energy(params, H, ansatz, ref)

analytical_hess(H, ansatz, ref)

analytical_grad(H, ansatz, ref)

diagonal_hess(h, H, ansatz, ref)

diag_jerk(h, H, ansatz, ref)

F3(F, ansatz, ref)

deriv(params, H, ansatz, ref)

hess(params, H, ansatz, ref)

jerk(params, H, ansatz, ref)

UCC2_energy(x, E0, deriv, hess)

UCC3_energy(x, E0, deriv, hess, jerk)

EN_UCC3_energy(x, E0, deriv, hess, jerk)

brute_force_energy(param, x0, grad, H, ansatz, ref)

ML_X(params, H, ansatz, ref)

VQITE(H, ansatz, ref, params[, dt, tol])

one_param_energy(param, H, ansatz, ref, param_no, params)

one_param_grad(param, H, ansatz, ref, param_no, params)

best_vqe(results, H, ansatz, ref[, dump_dir, gimbal])

pre_sample(H, ansatz, ref, params[, seeds, norm])

sample_uccsd(H, ansatz, ref, params[, gtol, seeds, ...])

sample_vccsd(H, ansatz, ref, params[, gtol, seeds, ...])

sample_vqe(H, ansatz, ref, params[, gtol, seeds, ...])

sd_energy(step, grad, H, ansatz, ref, params)

simple_vqe(H, ansatz, ref, params[, gtol, gimbal])

adapt_vqe(H, ansatz, ref, params[, include, gtol])

simple_uccsd(H, ansatz, ref, params[, gtol])

simple_vccsd(H, ansatz, ref, params[, gtol])

vqe(H, ansatz, ref, params[, gtol, singles, dump_dir])

resid(x, H, ansatz, ref)

diis(H, ansatz, ref, guess[, gtol, max_vec])

prod_cb(params)

qse(K, L, H, S2, Sz, N)

no_qse(K, L, H, S2, Sz, N)

canonical(S, L)

symmetric(S, L)

rt_inv(S)

rt(S)

adapt.computational_tools.oo_vqe(params, H, ansatz, ref, singles, knorm=1e-08, tnorm=1e-08)[source]
adapt.computational_tools.product_hessian(params, H, ansatz, ref)[source]
adapt.computational_tools.ML_M(params, H, ansatz, ref)[source]
adapt.computational_tools.Gradient_S(params, H, ansatz, ref)[source]
adapt.computational_tools.soln_analysis(params, H, ansatz, ref, label)[source]
adapt.computational_tools.ML_M_dumb(params, H, ansatz, ref)[source]
adapt.computational_tools.product_gradient(params, H, ansatz, ref)[source]
adapt.computational_tools.prep_state(ops, ref, params)[source]
adapt.computational_tools.product_energy(params, H, ansatz, ref)[source]
adapt.computational_tools.simple_energy(params, H, ansatz, ref)[source]
adapt.computational_tools.simple_uccsd_energy(params, H, ansatz, ref)[source]
adapt.computational_tools.simple_vccsd_energy(params, H, ansatz, ref)[source]
adapt.computational_tools.simple_gradient(params, H, ansatz, ref)[source]
adapt.computational_tools.sum_energy(params, H, ansatz, ref)[source]
adapt.computational_tools.analytical_hess(H, ansatz, ref)[source]
adapt.computational_tools.analytical_grad(H, ansatz, ref)[source]
adapt.computational_tools.diagonal_hess(h, H, ansatz, ref)[source]
adapt.computational_tools.diag_jerk(h, H, ansatz, ref)[source]
adapt.computational_tools.F3(F, ansatz, ref)[source]
adapt.computational_tools.deriv(params, H, ansatz, ref)[source]
adapt.computational_tools.hess(params, H, ansatz, ref)[source]
adapt.computational_tools.jerk(params, H, ansatz, ref)[source]
adapt.computational_tools.UCC2_energy(x, E0, deriv, hess)[source]
adapt.computational_tools.UCC3_energy(x, E0, deriv, hess, jerk)[source]
adapt.computational_tools.EN_UCC3_energy(x, E0, deriv, hess, jerk)[source]
adapt.computational_tools.brute_force_energy(param, x0, grad, H, ansatz, ref)[source]
adapt.computational_tools.ML_X(params, H, ansatz, ref)[source]
adapt.computational_tools.VQITE(H, ansatz, ref, params, dt=0.1, tol=1e-10)[source]
adapt.computational_tools.one_param_energy(param, H, ansatz, ref, param_no, params)[source]
adapt.computational_tools.one_param_grad(param, H, ansatz, ref, param_no, params)[source]
adapt.computational_tools.best_vqe(results, H, ansatz, ref, dump_dir='dump', gimbal=False)[source]
adapt.computational_tools.pre_sample(H, ansatz, ref, params, seeds=10000, norm=1)[source]
adapt.computational_tools.sample_uccsd(H, ansatz, ref, params, gtol=1e-16, seeds=125, dump_dir='dump_entangled', singles=False)[source]
adapt.computational_tools.sample_vccsd(H, ansatz, ref, params, gtol=1e-16, seeds=125, dump_dir='dump_vcc')[source]
adapt.computational_tools.sample_vqe(H, ansatz, ref, params, gtol=1e-16, seeds=125, dump_dir='dump_disentangled', singles=None, seed_offset=0, gimbal=False, rscale=1)[source]
adapt.computational_tools.sd_energy(step, grad, H, ansatz, ref, params)[source]
adapt.computational_tools.simple_vqe(H, ansatz, ref, params, gtol=1e-14, gimbal=False)[source]
adapt.computational_tools.adapt_vqe(H, ansatz, ref, params, include=1, gtol=1e-14)[source]
adapt.computational_tools.simple_uccsd(H, ansatz, ref, params, gtol=1e-15)[source]
adapt.computational_tools.simple_vccsd(H, ansatz, ref, params, gtol=1e-15)[source]
adapt.computational_tools.vqe(H, ansatz, ref, params, gtol=1e-15, singles=None, dump_dir=None)[source]
adapt.computational_tools.resid(x, H, ansatz, ref)[source]
adapt.computational_tools.diis(H, ansatz, ref, guess, gtol=1e-10, max_vec=1000)[source]
adapt.computational_tools.prod_cb(params)[source]
adapt.computational_tools.qse(K, L, H, S2, Sz, N)[source]
adapt.computational_tools.no_qse(K, L, H, S2, Sz, N)[source]
adapt.computational_tools.canonical(S, L)[source]
adapt.computational_tools.symmetric(S, L)[source]
adapt.computational_tools.rt_inv(S)[source]
adapt.computational_tools.rt(S)[source]