carcara 26.7.2

A framework for fermionic quantum simulation based on variational quantum algorithms.

Carcará

Carcará is a framework for fermionic quantum simulation based on variational quantum algorithms, engineered from the ground up for deployment on real quantum hardware.

Overview

Carcará connects theoretical condensed matter physics with NISQ-era quantum hardware. Engineered around variational workflows, the framework streamlines the pipeline from mapping complex fermionic Hamiltonians onto qubit operators to optimizing ansatz states and executing error-mitigated circuits on real quantum backends.

Key Features

• Fermion-to-Qubit Mapping: Built-in, optimized transformations including Jordan-Wigner, Bravyi-Kitaev, and parity mappings to translate fermionic creation/annihilation operators into Pauli strings.

• Hardware-Efficient & Physics-Inspired Ansatzes: Ready-to-use ansatz generation, including Unitary Coupled Cluster (UCCSD) and hardware-efficient templates designed to minimize circuit depth and gate errors on real QPUs.

• Hybrid Variational Solvers: Robust implementation of the Variational Quantum Eigensolver (VQE) and its time-dependent variants, coupled with state-of-the-art classical optimizers (e.g., SPSA, COBYLA, SLSQP).

• Real Hardware Deployment: Seamless integration with major quantum cloud providers (IBM Quantum Platform) with native support.

• Advanced Error Mitigation: Built-in noise-resilient pipelines featuring Zero-Noise Extrapolation (ZNE) and symmetry verification.

Installation

From pip

The easiest way to install Carcará is with pip:

pip install carcara

From github

To install Carcará directly from the GitHub repository, run the following commands:

git clone https://github.com/seixas-research/carcara.git
cd carcara
pip install -e .

Getting started

One- and two-body integrals for H2

The carcara.integrals module computes real-space one- and two-body integrals over any localized basis. The example below builds a minimal basis of one hydrogen 1s orbital on each proton and evaluates the core Hamiltonian and the electron-repulsion tensor. The full script lives in examples/h2_integrals.py.

import numpy as np

from carcara.basis import HydrogenicOrbital
from carcara.integrals import Grid, IntegralEngine

# Geometry (atomic units): two protons at the H2 equilibrium bond length.
Z, R = 1.0, 1.4
nuclei = np.array([[0.0, 0.0, -R / 2], [0.0, 0.0, +R / 2]])

def nuclear_potential(x, y, z):
    v = np.zeros_like(x, dtype=float)
    for Rx, Ry, Rz in nuclei:
        r = np.sqrt((x - Rx) ** 2 + (y - Ry) ** 2 + (z - Rz) ** 2)
        v -= Z / np.maximum(r, 1e-12)
    return v

grid = Grid(center=[0.0, 0.0, 0.0], box_size=10.0, points=64)
basis = [HydrogenicOrbital(1, 0, 0, Z=Z, center=nuclei[0]),
         HydrogenicOrbital(1, 0, 0, Z=Z, center=nuclei[1])]

engine = IntegralEngine(basis, grid)

# One-body: kinetic T and nuclear attraction V -> core Hamiltonian.
T, V = engine.one_body(nuclear_potential)
h_core = T + V

# Two-body electron-repulsion tensor (ab|cd) in chemists' notation.
eri = engine.two_body(method="fft")

print("Core Hamiltonian h = T + V (Ha):")
print(h_core.real)
print(f"(00|00) on-site repulsion = {eri[0, 0, 0, 0].real:.4f} Ha")

Running it prints the 2 x 2 core Hamiltonian and the on-site repulsion (00|00) ~ 0.62 Ha, in agreement with the exact hydrogen 1s value of 5/8 Ha.

License

This is an open source code under MIT License.

Acknowledgements

We thank financial support from INCT Materials Informatics (Grant No. 406447/2022-5).