Products & projects

Machine learning density-based operators.

Poraquê is a software framework for machine learning operators between the real-space fields of density functional theory. Given only a crystal geometry, it predicts the charge density and the kinetic energy density. No wavefunctions, no self-consistency cycle.

• Density-based operators as first-class objects
• Built for the standard scientific Python stack
• Aimed at accelerating electronic-structure workflows

https://poraque.seixas.dev

Visual atomistic modeling.

Calango Studio is a toolkit for visual atomistic modelling. It turns the fiddly part of setting up a simulation, placing atoms, building slabs and supercells, checking a structure before it costs you CPU hours, into something you can see and edit directly, then hand straight to the simulation code you already use.

• Interactive construction and inspection of atomic structures
• Written in C++ for speed on large systems
• Designed to sit alongside existing simulation codes

https://calango-studio.seixas.dev

Fermionic quantum simulation, one API.

Mandacaru is a lightweight, high-performance Python framework for fermionic quantum simulation based on variational quantum algorithms. From a molecular or periodic geometry, it builds real-space grids, evaluates the one- and two-body integrals, maps the Hamiltonian to qubits, and solves it variationally — through a single ASE calculator that runs unchanged on IBM Qiskit, Amazon Braket and Google Cirq.

• VQE, ADAPT-VQE and excited states — deflation and subspace search — sharing one driver
• Localized basis sets and pseudopotentials generated from scratch, not tabulated
• Cross-backend agreement to 1.3×10⁻⁷ Ha, validated on real quantum hardware
• Analytic forces and wavefunction checkpoints, with quantum phase estimation off a checkpoint

https://mandacaru.seixas.dev