
Over 14 months, Varo Carballido engineered distributed quantum simulation infrastructure for the CESGA-Quantum-Spain/cunqa repository, focusing on scalable, production-ready workflows. He integrated C++ and Python components to support multi-QPU orchestration, dynamic backend selection, and hybrid quantum-classical communication using technologies like MPI, ZMQ, and CUDA. His work included robust API and simulator adapters, GPU-accelerated simulation with AerSimulator, and circuit conversion frameworks supporting QASM and JSON. By emphasizing code clarity, resource management, and build automation with CMake, Varo delivered maintainable, extensible systems that improved simulation accuracy, reliability, and developer productivity, addressing both algorithmic complexity and operational challenges in quantum computing environments.

January 2026 (2026-01) monthly summary for CESGA-Quantum-Spain/cunqa. Focused on delivering scalable quantum simulation capabilities and stabilizing the build/deploy pipeline, with concrete GPU enablement and robustness improvements that drive business value and developer productivity.
January 2026 (2026-01) monthly summary for CESGA-Quantum-Spain/cunqa. Focused on delivering scalable quantum simulation capabilities and stabilizing the build/deploy pipeline, with concrete GPU enablement and robustness improvements that drive business value and developer productivity.
December 2025 Cunqa monthly summary focusing on delivering core quantum I/O and QPU integration capabilities, stabilizing the baseline for production, and improving maintainability. Highlights include gates integration with bitstring-order correction for accurate results, QMIO/QPU interface enhancements, and a compilable baseline enabling production deployment. Additional improvements covered QM IO compatibility with pyzmq, OpenQasm2.0 circuit handling, and code quality upgrades to reduce maintenance risk.
December 2025 Cunqa monthly summary focusing on delivering core quantum I/O and QPU integration capabilities, stabilizing the baseline for production, and improving maintainability. Highlights include gates integration with bitstring-order correction for accurate results, QMIO/QPU interface enhancements, and a compilable baseline enabling production deployment. Additional improvements covered QM IO compatibility with pyzmq, OpenQasm2.0 circuit handling, and code quality upgrades to reduce maintenance risk.
November 2025 focused on hardening the cunqa Python API and simulator integration in the CESGA-Quantum-Spain/cunqa repository. Delivered a targeted bug-fix cycle that corrects parameter handling, aligns simulator usage with production environments, and reduces onboarding friction for users deploying multi-QPU configurations. No new features were released this month; however, the changes improve reliability, cross-environment compatibility, and overall user confidence in the API.
November 2025 focused on hardening the cunqa Python API and simulator integration in the CESGA-Quantum-Spain/cunqa repository. Delivered a targeted bug-fix cycle that corrects parameter handling, aligns simulator usage with production environments, and reduces onboarding friction for users deploying multi-QPU configurations. No new features were released this month; however, the changes improve reliability, cross-environment compatibility, and overall user confidence in the API.
October 2025 (2025-10) monthly summary for CESGA-Quantum-Spain/cunqa focused on delivering production-ready distributed quantum processing workflows, stabilizing builds, and laying groundwork for Qiskit integration, while improving infrastructure and documentation to accelerate adoption and reliability.
October 2025 (2025-10) monthly summary for CESGA-Quantum-Spain/cunqa focused on delivering production-ready distributed quantum processing workflows, stabilizing builds, and laying groundwork for Qiskit integration, while improving infrastructure and documentation to accelerate adoption and reliability.
September 2025 — Cunqa (CESGA-Quantum-Spain/cunqa) delivered significant advancements in distributed quantum simulation, focusing on scalability, reliability, and resource efficiency. Key features and fixes include: distributed QPE enhancements enabling iterative QPE and distributed operations with improved resource management and logging; Munich simulator stability improvements with enhanced debugging, logging, error handling, and robust execution/communication; Aer simulator enhancements introducing parallel task execution and improved teleportation-like operations; robustness fixes to simulator adapters (notably control qubit handling and remote operation logic); and build/memory management improvements with per-core QPU memory and overall cleanup to optimize resource allocation and simulation tuning.
September 2025 — Cunqa (CESGA-Quantum-Spain/cunqa) delivered significant advancements in distributed quantum simulation, focusing on scalability, reliability, and resource efficiency. Key features and fixes include: distributed QPE enhancements enabling iterative QPE and distributed operations with improved resource management and logging; Munich simulator stability improvements with enhanced debugging, logging, error handling, and robust execution/communication; Aer simulator enhancements introducing parallel task execution and improved teleportation-like operations; robustness fixes to simulator adapters (notably control qubit handling and remote operation logic); and build/memory management improvements with per-core QPU memory and overall cleanup to optimize resource allocation and simulation tuning.
Monthly summary for 2025-08 for repository CESGA-Quantum-Spain/cunqa. Delivered a set of reliability, interoperability, and infrastructure-driven enhancements to the Cunqa stack, advancing both core capabilities and orchestration of quantum-classical workflows. Key features include a no-dynamic circuits execution method via CunqaSimulator, hybrid resource support with the quantum_comm flag, and the first functional QRaise infrastructure integration with a toy example under examples/. A robust circuit conversion framework (QuantumCircuit, CunqaCircuit, JSON) with QASM interoperability was implemented and consolidated into converters.py, while infrastructure naming was centralized in infrastructure.json for consistency. Classic resource management improvements and groundwork for classical-quantum communications were introduced, laying foundations for scalable backends and multi-QPU orchestration. Documentation updates and branch hygiene were maintained to improve maintainability and developer onboarding.
Monthly summary for 2025-08 for repository CESGA-Quantum-Spain/cunqa. Delivered a set of reliability, interoperability, and infrastructure-driven enhancements to the Cunqa stack, advancing both core capabilities and orchestration of quantum-classical workflows. Key features include a no-dynamic circuits execution method via CunqaSimulator, hybrid resource support with the quantum_comm flag, and the first functional QRaise infrastructure integration with a toy example under examples/. A robust circuit conversion framework (QuantumCircuit, CunqaCircuit, JSON) with QASM interoperability was implemented and consolidated into converters.py, while infrastructure naming was centralized in infrastructure.json for consistency. Classic resource management improvements and groundwork for classical-quantum communications were introduced, laying foundations for scalable backends and multi-QPU orchestration. Documentation updates and branch hygiene were maintained to improve maintainability and developer onboarding.
July 2025: Focused on delivering reliable, scalable quantum simulation workflows in Cunqa. Key outcomes include feature enhancements for quantum communication simulations, robust AerSimulator integration, JSON transpilation fixes, dynamic execution hardening for classical-quantum workflows, and improved observability through enhanced logging and port handling. These changes reduce setup friction, improve accuracy, and enable broader experimentation in quantum-classical pipelines.
July 2025: Focused on delivering reliable, scalable quantum simulation workflows in Cunqa. Key outcomes include feature enhancements for quantum communication simulations, robust AerSimulator integration, JSON transpilation fixes, dynamic execution hardening for classical-quantum workflows, and improved observability through enhanced logging and port handling. These changes reduce setup friction, improve accuracy, and enable broader experimentation in quantum-classical pipelines.
June 2025 focused on delivering Aer-based simulator integration as the primary backend with dynamic conditional execution across simulators, standardizing classical communication across backends, and hardening distributed execution. Key bug fixes improved reliability for distributed QPU runs and ensured correct AER result processing. These efforts improved scalability, correctness, and maintainability, enabling faster, more predictable simulations across multi-QPU configurations.
June 2025 focused on delivering Aer-based simulator integration as the primary backend with dynamic conditional execution across simulators, standardizing classical communication across backends, and hardening distributed execution. Key bug fixes improved reliability for distributed QPU runs and ensured correct AER result processing. These efforts improved scalability, correctness, and maintainability, enabling faster, more predictable simulations across multi-QPU configurations.
May 2025 performance summary for Cunqa (CESGA-Quantum-Spain/cunqa). Focused on enabling scalable distributed classical communications and improving code quality. Delivered functional integrations with MunichSimulator, established default ZMQ-to-MPI communication paths for QPUS, addressed scaling issues in ZMQ communications, and completed a software redesign with distributed examples. Extensive maintenance and cleanup improved readability, testability, and reliability, setting the stage for future expansion and easier collaboration across teams.
May 2025 performance summary for Cunqa (CESGA-Quantum-Spain/cunqa). Focused on enabling scalable distributed classical communications and improving code quality. Delivered functional integrations with MunichSimulator, established default ZMQ-to-MPI communication paths for QPUS, addressed scaling issues in ZMQ communications, and completed a software redesign with distributed examples. Extensive maintenance and cleanup improved readability, testability, and reliability, setting the stage for future expansion and easier collaboration across teams.
April 2025 monthly summary for CESGA-Quantum-Spain/cunqa focused on accelerating distributed quantum workloads, improving reliability of transports, and elevating observability and developer productivity. Delivered core distributed communications enhancements (MPI-based QPU communications), modernized MPI initialization (MPI_Init(NULL, NULL)) and removed argc/argv usage, and aligned transport layers by defaulting to ZMQ when classical communications are selected. Introduced ASIO-based client-server communications for lower latency and consistent performance, enhanced QPU tooling with infoqpus/qinfo and Python-side endpoint exposure, and expanded Cunqasimulator capabilities with dynamic qubit typing and support for personalized 1- and 2-qubit gates. Additional code cleanup and configuration/schema refinements improved maintainability and stability across the project.
April 2025 monthly summary for CESGA-Quantum-Spain/cunqa focused on accelerating distributed quantum workloads, improving reliability of transports, and elevating observability and developer productivity. Delivered core distributed communications enhancements (MPI-based QPU communications), modernized MPI initialization (MPI_Init(NULL, NULL)) and removed argc/argv usage, and aligned transport layers by defaulting to ZMQ when classical communications are selected. Introduced ASIO-based client-server communications for lower latency and consistent performance, enhanced QPU tooling with infoqpus/qinfo and Python-side endpoint exposure, and expanded Cunqasimulator capabilities with dynamic qubit typing and support for personalized 1- and 2-qubit gates. Additional code cleanup and configuration/schema refinements improved maintainability and stability across the project.
Monthly summary for 2025-03 focused on the Cunqa project (CESGA-Quantum-Spain/cunqa). Delivered backend integration and HPC-ready workflows, with notable progress on the CunqaSimulator backend, classical communications, and SLURM-based provisioning for QPUs, setting the foundation for scalable quantum simulations in HPC environments.
Monthly summary for 2025-03 focused on the Cunqa project (CESGA-Quantum-Spain/cunqa). Delivered backend integration and HPC-ready workflows, with notable progress on the CunqaSimulator backend, classical communications, and SLURM-based provisioning for QPUs, setting the foundation for scalable quantum simulations in HPC environments.
February 2025 monthly summary for CESGA-Quantum-Spain/cunqa focused on delivering robust parameter management, backend reliability, and scalable execution capabilities, with notable architectural and documentation improvements.
February 2025 monthly summary for CESGA-Quantum-Spain/cunqa focused on delivering robust parameter management, backend reliability, and scalable execution capabilities, with notable architectural and documentation improvements.
For January 2025, the Cunqa project (CESGA-Quantum-Spain/cunqa) delivered strong progress across noise-enabled simulation infrastructure, variational-circuit parameter handling, and backend fidelity, while stabilizing resource management. Key features include noise-enabled backends and a JSON-driven simulation configuration with initial noise modeling, build/setup scripts, basis gates handling, and integration with a noise-aware qpu.json workflow. Additional features added: coupling maps and calibration data for the FakeQmio backend to improve simulation accuracy and qubit connectivity modeling. A major bug fix improved stability: server parameter-send handling now closes the connection when parameters are sent without an associated circuit, preventing resource leaks. A targeted enhancement enabled sending only circuit parameters for variational circuits, reducing data transfer and enabling efficient parameterized quantum computations. Overall impact: Improved realism and reliability of simulations, faster experimentation with noisy and variational workloads, and reduced operational risk due to resource-management issues. This supports better algorithm development, planning, and benchmarking against more faithful backend models. Technologies/skills demonstrated: noise modeling and backend integration, JSON-based configuration, basis-gates management and qpu.json tuning, coupling maps and calibration data integration, parameterized circuits, and robust server/resource management and build automation.
For January 2025, the Cunqa project (CESGA-Quantum-Spain/cunqa) delivered strong progress across noise-enabled simulation infrastructure, variational-circuit parameter handling, and backend fidelity, while stabilizing resource management. Key features include noise-enabled backends and a JSON-driven simulation configuration with initial noise modeling, build/setup scripts, basis gates handling, and integration with a noise-aware qpu.json workflow. Additional features added: coupling maps and calibration data for the FakeQmio backend to improve simulation accuracy and qubit connectivity modeling. A major bug fix improved stability: server parameter-send handling now closes the connection when parameters are sent without an associated circuit, preventing resource leaks. A targeted enhancement enabled sending only circuit parameters for variational circuits, reducing data transfer and enabling efficient parameterized quantum computations. Overall impact: Improved realism and reliability of simulations, faster experimentation with noisy and variational workloads, and reduced operational risk due to resource-management issues. This supports better algorithm development, planning, and benchmarking against more faithful backend models. Technologies/skills demonstrated: noise modeling and backend integration, JSON-based configuration, basis-gates management and qpu.json tuning, coupling maps and calibration data integration, parameterized circuits, and robust server/resource management and build automation.
December 2024 monthly summary for CESGA-Quantum-Spain/cunqa: Delivered QPU integration and demo enhancements along with repository hygiene improvements to support scalable demos and production readiness. The work focused on enabling dynamic QPU configuration loading, tightening backend initialization, and providing a concrete demo of new QPU functionality for running quantum circuits. Updates included the example script and cluster module to support QPU configurability and usage demonstrations, while Gitignore housekeeping removed generated scripts and deployment artifacts to keep the repo clean. This period also included cross-language integration work (Aer C++ and Python-C++ module handling) to improve stability and reliability of the quantum backend components.
December 2024 monthly summary for CESGA-Quantum-Spain/cunqa: Delivered QPU integration and demo enhancements along with repository hygiene improvements to support scalable demos and production readiness. The work focused on enabling dynamic QPU configuration loading, tightening backend initialization, and providing a concrete demo of new QPU functionality for running quantum circuits. Updates included the example script and cluster module to support QPU configurability and usage demonstrations, while Gitignore housekeeping removed generated scripts and deployment artifacts to keep the repo clean. This period also included cross-language integration work (Aer C++ and Python-C++ module handling) to improve stability and reliability of the quantum backend components.
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