Work in progress - build quantum programs that are platform-agnostic - compile for IBM's Qobj and QASM, Rigetti's Quil, Microsoft's Q#, or Google's Cirq.
import { Gates, Program, RigettiProcessor, IBMProcessor } from 'quantum-peep';
// write your quantum gates and measurements into a program
let p = new Program();
p.add(Gates.X(1));
p.measure(1, 2);
// get Microsoft's Q# code
p.code('q#');
// get Python code for Google Cirq
p.code('cirq');
// run on Rigetti QVM Docker container
// For actual QPUs, register for Rigetti Forest and use their endpoint, api_key, and user_id
let q = new RigettiProcessor({
endpoint: URL_of_Rigetti_qvm_docker,
api_key: 'aaa',
user_id: 'uuu'
});
let runTimes = 10;
q.run(p, runTimes, (body) => {
console.log(JSON.parse(body));
});
// fetch device options + status from https://forest-server.qcs.rigetti.com/devices
q.devices((deviceInfo) => {
// { "Aspen-4": { "is_online": false, ... }, "Aspen-3": { ... } }
});
// run on IBM quantum chip
// setting backend: in node_modules/@qiskit/cloud/cfg.json, set URI to https://api.quantum-computing.ibm.com/api
// getting the login: go to https://quantum-computing.ibm.com
// -- go to your profile
// getting the token: inspect your browser's requests to headers on Backends
let q2 = new IBMProcessor({
login: secrets.ibm.login,
token: secrets.ibm.token,
processor: 'ibmq_qobj_simulator'
});
// fetch device options + status from https://api.quantum-computing.ibm.com/api/Backends
// uses given processor type
q2.devices((deviceInfo) => {
// [
// { "name": "ibmq_ourense", "status": "on", "specificConfiguration": { ... }, ... }
// ]
});
q2.run(p, runTimes, (body) => {
console.log(JSON.parse(body));
});
// gate names from different platforms are equivalent
Gates.CNOT(control, target);
Gates.CX(control, target);
// swap operations
Gates.SWAP(qubit1, qubit2);
Gates.CSWAP(conditional, qubit1, qubit2);
// ISWAP and PSWAP are only one-step operations in Quil? Advice welcome
// phase gates: phase is a radian value
// use this shorthand to express on several different platforms
import { pi_multipled_by, pi_divided_by } from 'quantum-peep';
Gates.RX(pi_multiplied_by(0.45), qubit1);
Gates.RY(pi_divided_by(2), qubit2);
Output a circuit diagram with this library ported from QISKit Python: https://github.com/mapmeld/quantum-circuit-viz
import { textViz } from 'quantum-circuit-viz';
...
program.add(Gates.X(1));
program.measure(1, 2);
textViz(program);
┌───┐┌─┐
q_1: |0>┤ X ├┤M├
└───┘└╥┘
c_2: 0 ══════╩═
- work with experimental results from APIs
- more complex conditional / GOTO output in assembly languages
- async/queue support: for newer APIs which put programs in a queue
- browser JS distribution: easier use in web apps
IBM's QISkit (for Python and JS) compile to Qobj and OpenQASM: https://github.com/Qiskit/openqasm
Rigetti's pyQuil (and the previous jsQuil project) compile to Quil: http://docs.rigetti.com/en/stable/compiler.html
Microsoft Q# https://docs.microsoft.com/en-us/quantum/language/?view=qsharp-preview
Google Cirq https://github.com/quantumlib/Cirq
Open source, MIT license