Crate qip

Quantum Computing library leveraging graph building to build efficient quantum circuit simulations. Rust is a great language for quantum computing with gate models because the borrow checker is very similar to the No-cloning theorem.

See all the examples in the examples directory of the Github repository.

Example (CSWAP)

Here’s an example of a small circuit where two groups of Registers are swapped conditioned on a third. This circuit is very small, only three operations plus a measurement, so the boilerplate can look quite large in comparison, but that setup provides the ability to construct circuits easily and safely when they do get larger.

use qip::prelude::*;
use std::num::NonZeroUsize;

// Make a new circuit builder.
let mut b = LocalBuilder::<f64>::default();
let n = NonZeroUsize::new(3).unwrap();

// Make three registers of sizes 1, 3, 3 (7 qubits total).
let q = b.qubit();  // Same as b.register(1)?;
let ra = b.register(n);
let rb = b.register(n);

// Define circuit
// First apply an H to q
let q = b.h(q);
// Then swap ra and rb, conditioned on q.
let mut cb = b.condition_with(q);
let (ra, rb) = cb.swap(ra, rb)?;
let q = cb.dissolve();
// Finally apply H to q again.
let q = b.h(q);

// Add a measurement to the first qubit, save a reference so we can get the result later.
let (q, m_handle) = b.measure(q);

// Now q is the end result of the above circuit, and we can run the circuit by referencing it.

// Run circuit with a given precision.
let (_, measured) = b.calculate_state_with_init([(&ra, 0b000), (&rb, 0b001)]);

// Lookup the result of the measurement we performed using the handle, and the probability
// of getting that measurement.
let (result, p) = measured.get_measurement(m_handle);

// Print the measured result
println!("Measured: {:?} (with chance {:?})", result, p);

The Program Macro

While the borrow checker included in rust is a wonderful tool for checking that our registers are behaving, it can be cumbersome. For that reason qip also includes a macro which provides an API similar to that which you would see in quantum computing textbooks.

use qip::prelude::*;
use std::num::NonZeroUsize;
use qip_macros::program;

fn gamma<B>(b: &mut B, ra: B::Register, rb: B::Register) -> CircuitResult<(B::Register, B::Register)>
   where B: AdvancedCircuitBuilder<f64>
{
    let (ra, rb) = b.toffoli(ra, rb)?;
    let (rb, ra) = b.toffoli(rb, ra)?;
    Ok((ra, rb))
}

let n = NonZeroUsize::new(3).unwrap();
let mut b = LocalBuilder::default();
let ra = b.register(n);
let rb = b.register(n);


let (ra, rb) = program!(&mut b; ra, rb;
    // Applies gamma to |ra[0] ra[1]>|ra[2]>
    gamma ra[0..2], ra[2];
    // Applies gamma to |ra[0] rb[0]>|ra[2]>
    // Notice ra[0] and rb[0] are grouped by brackets.
    gamma [ra[0], rb[0]], ra[2];
    // Applies gamma to |ra[0]>|rb[0] ra[2]>
    gamma ra[0], [rb[0], ra[2]];
    // Applies gamma to |ra[0] ra[1]>|ra[2]> if rb == |111>
    control gamma rb, ra[0..2], ra[2];
    // Applies gamma to |ra[0] ra[1]>|ra[2]> if rb == |110> (rb[0] == |0>, rb[1] == 1, ...)
    control(0b110) gamma rb, ra[0..2], ra[2];
)?;
let r = b.merge_two_registers(ra, rb);

We can also apply this to function which take other argument. Here gamma takes a boolean argument skip which is passed in before the registers. The arguments to functions in the program macro may not reference the input registers

use qip::prelude::*;
use std::num::NonZeroUsize;
use qip_macros::program;

fn gamma<B>(b: &mut B, skip: bool, ra: B::Register, rb: B::Register) -> CircuitResult<(B::Register, B::Register)>
   where B: AdvancedCircuitBuilder<f64>
{
    let (ra, rb) = b.toffoli(ra, rb)?;
    let (rb, ra) = if skip {
        b.toffoli(rb, ra)?
    } else {
        (rb, ra)
    };
    Ok((ra, rb))
}

let n = NonZeroUsize::new(3).unwrap();
let mut b = LocalBuilder::default();
let ra = b.register(n);
let rb = b.register(n);

let (ra, rb) = program!(&mut b; ra, rb;
    gamma(true) ra[0..2], ra[2];
    gamma(0 == 1) ra[0..2], ra[2];
)?;
let r = b.merge_two_registers(ra, rb);

The Invert Macro

It’s often useful to define functions of registers as well as their inverses, the #[invert] macro automates much of this process.

use qip::prelude::*;
use std::num::NonZeroUsize;
use qip_macros::*;

use qip::inverter::Invertable;
// Make gamma and its inverse: gamma_inv
#[invert(gamma_inv)]
fn gamma<B>(b: &mut B, ra: B::Register, rb: B::Register) -> CircuitResult<(B::Register, B::Register)>
   where B: AdvancedCircuitBuilder<f64> + Invertable<SimilarBuilder=B>
{
    let (ra, rb) = b.toffoli(ra, rb)?;
    let (rb, ra) = b.toffoli(rb, ra)?;
    Ok((ra, rb))
}

let n = NonZeroUsize::new(3).unwrap();
let mut b = LocalBuilder::default();
let ra = b.register(n);
let rb = b.register(n);


let (ra, rb) = program!(&mut b; ra, rb;
    gamma ra[0..2], ra[2];
    gamma_inv ra[0..2], ra[2];
)?;
let r = b.merge_two_registers(ra, rb);

To invert functions with additional arguments, we must list the non-register arguments.

use qip::prelude::*;
use std::num::NonZeroUsize;
use qip_macros::*;

use qip::inverter::Invertable;
// Make gamma and its inverse: gamma_inv
#[invert(gamma_inv, skip)]
fn gamma<B>(b: &mut B, skip: bool, ra: B::Register, rb: B::Register) -> CircuitResult<(B::Register, B::Register)>
   where B: AdvancedCircuitBuilder<f64> + Invertable<SimilarBuilder=B>
{
    let (ra, rb) = b.toffoli(ra, rb)?;
    let (rb, ra) = if skip {
        b.toffoli(rb, ra)?
    } else {
        (rb, ra)
    };
    Ok((ra, rb))
}

let n = NonZeroUsize::new(3).unwrap();
let mut b = LocalBuilder::default();
let ra = b.register(n);
let rb = b.register(n);

let (ra, rb) = program!(&mut b; ra, rb;
    gamma(true) ra[0..2], ra[2];
    gamma_inv(true) ra[0..2], ra[2];
)?;
let r = b.merge_two_registers(ra, rb);

Re-exports

pub use rand;

pub use types::*;

Modules

builder

A circuit builder implementation which builds circuits out of simple elements.

builder_traits

Standard traits for circuit builders.

conditioning

Traits for constructing conditioned circuit builders.

errors

Circuit builder error types.

inverter

Functions and traits for inverting circuits.

prelude

Commonly used types and traits.

qfft

Standard quantum fourier transform implementation.

state_ops

Lower-level circuit operations.

types

Reusable types.

utils

Utility functions for bit and index manipulation

Structs

Complex

A complex number in Cartesian form.