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| Require Import List. | |
| Import ListNotations. | |
| Theorem concat_assoc(X: Type): | |
| forall tttx: list (list (list X)), (concat (concat tttx)) = (concat (map (@concat X) tttx)). | |
| Proof. | |
| intros. | |
| induction tttx. | |
| simpl. reflexivity. | |
| simpl. rewrite <- IHtttx. apply concat_app. |
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| from blueqat import Circuit, pauli, vqe | |
| from blueqat.pauli import qubo_bit as q | |
| from math import pi | |
| import numpy as np | |
| def an(index): | |
| return 0.5 * pauli.X[index] + 0.5j * pauli.Y[index] | |
| def cr(index): | |
| return 0.5 * pauli.X[index] - 0.5j * pauli.Y[index] |
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| (* 3.1 *) | |
| Inductive 紅白玉 := | |
| | 赤玉 | |
| | 白玉. | |
| (* 3.2 *) | |
| Print list. | |
| (* | |
| Inductive list (A : Type) : Type := | |
| nil : list A |
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| import optuna | |
| def get_optuna_minimizer(n_trials, study=None): | |
| if study is None: | |
| study = optuna.create_study() | |
| def minimizer(objective, n_params): | |
| def optuna_objective(trial): | |
| params = [trial.suggest_uniform(f'params[{i}]', 0.0, 1.0) for i in range(n_params)] | |
| return objective(params) | |
| study.optimize(optuna_objective, n_trials=n_trials) |
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| FROM nvidia/cuda:9.2-runtime-ubuntu16.04 | |
| RUN apt update && \ | |
| apt install -y --no-install-recommends apt-transport-https curl python-pip python-setuptools ipython && \ | |
| . /etc/lsb-release && \ | |
| (echo "deb [arch=amd64] https://shinmorino.github.io/sqaod/ubuntu ${DISTRIB_CODENAME} multiverse" | tee /etc/apt/sources.list.d/sqaod.list) && \ | |
| (curl -s -L https://shinmorino.github.io/sqaod/gpgkey | apt-key add -) && \ | |
| apt update && apt install -y libsqaodc libsqaodc-dev libsqaodc-cuda-9-2 && pip install sqaod | |
| CMD ipython |
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| function c | |
| if test (count $argv) -eq 0 | |
| cd | |
| else if test (count $argv) -gt 1 | |
| echo "Too many arguments" >&2 | |
| else if test -d $argv[1] | |
| cd $argv[1] | |
| else if test ! -e $argv[1] | |
| echo "Not exists" >&2 | |
| else if test (head -26 $argv[1] | wc -l) -lt 26 |