Month: 2026-04 — Focused on delivering a streamlined simulation setup and maintaining external dependency compatibility, with a clear impact on onboarding speed and CI stability.

March 2026 highlights across qibocal, qibolab, and qibolab_platforms_qrc include delivering high-impact features, fixing critical issues, and strengthening documentation and platform configurability. Key outcomes span CI/CD and documentation workflow enhancements, performance-oriented waveform generation refinements, hardware-aware sequencing improvements, and automated platform readme tooling. These efforts collectively improved quality, reliability, and developer productivity while shortening feedback loops and onboarding time.

February 2026 (Month: 2026-02) – Monthly work summary focused on delivering business value through code cleanup, test/document hygiene, and CI improvements. Key features delivered: - qibolab: Envelope module cleanup—removed unused Iir and ECap classes; updated tests and API docs. This reduces API surface area, eliminates deprecated references, and improves user clarity. - qibolab: Pulse module plotting tests cleanup—removed tests related to plotting, reflecting a refactor/deprecation of plotting features and resulting in a leaner test suite. Major bugs fixed: - API/test fragility cleanup: removed references to deprecated waveforms and obsolete plotting tests to align with the current API and prevent flaky failures. - CI reliability improvement: in qibolab_platforms_qrc, decoupled CI jobs and fixed fail-fast setting to ensure complete test runs and comprehensive results. Overall impact and accomplishments: - Cleaner, more maintainable codebase; reduced technical debt from deprecated features; improved developer experience and onboarding. - More reliable, informative CI results across platforms; earlier detection of regressions with robust test coverage. Technologies/skills demonstrated: - Python refactoring, test cleanup, documentation hygiene, deprecation management. - CI/CD improvements, pipeline tuning, and collaboration across repos. Business value: - Faster release cycles, easier onboarding, reduced maintenance costs, clearer API for users, and stronger confidence in test results. Key commits highlights: - dad2f4507cef145e828f7aa154ca78e48fc4f1d4 - fcfe73cc48a6a8d97767516a5610990fcdf529bc - f81c40ffe13660fcec2832654e5f552aeb1b000f - f13a91e556170a811dc9778abd226596a603aa81 - 6499db4b6782ccb10afa69f9b193041bad319c3b - d00bad9afd7fca521871c80cc46b46606c173f6f

January 2026 performance summary: Delivered substantial feature work and fixes across qibolab_platforms_qrc, qibolab, and qibocal, focusing on quantum measurement fidelity, configuration management, and developer ergonomics. Key features delivered include improved D1 readout fidelity for quantum state measurements; qblox oscillator power configuration cleanup with sign correction; refinement of the Qblox mixer configuration by using the correct mixer type and removing dedicated configs; a major overhaul of port configuration generation in qibolab (new mechanism, probe channel support, deduplication) and a port configuration object refactor; and general documentation and parameterization improvements aligning with project conventions. Major bugs fixed include better port direction separation, removal of obsolete generation steps, safeguards around QCM configurations, and fixes to input attenuation and LO/mixer generation constraints. Overall impact: reduced configuration debt, more reliable measurement pipelines, and faster onboarding for new configurations; improved documentation to enable scalable operations. Technologies/skills demonstrated: advanced parameter tuning for readout, large-scale refactoring of configuration builders, rigorous version-control discipline, and comprehensive documentation practices.

December 2025 monthly summary focusing on delivering architectural improvements, compatibility upgrades, and data-model robustness across two repositories. Delivered tangible platform exposure gains, up-to-date runtime requirements, and enhanced observability. Demonstrated strong discipline in configuration hygiene and API safety, underscoring business value through maintainability, interoperability, and reliable performance.

November 2025 delivered a robust set of module-level and platform improvements for qibolab and related components, with a focus on reliability, performance, and maintainability. Key features include end-to-end mixer configuration generation and propagation across the module, enhanced module-level configuration and port handling, and provisioning for distortion corrections via pre-distortions filters. Build and environment stability were strengthened by lowering dependency requirements and simplifying the Qibo integration, while API and architectural cleanups improved typing, platform compatibility, and test reliability. Calibration improvements in the QRC platform contributed to fidelity and operational robustness.

October 2025 — qibolab_platforms_qrc: Delivered a significant platform upgrade for qw21q-d and improved data handling for qw21q-b. Key outcomes include a complete qw21q-d platform deployment with hardware loading via the Hardware class, introduction of initial qw21q-d parameters, and cleanup removing unused D qubits, accompanied by updated documentation and dependencies. Resolved critical stability issues on qw21q-d: resonator and qubit frequencies now reset reliably, and readout attenuation was adjusted to restore stable operation. Implemented a targeted fix for qw21q-b parameter processing to restrict to line B parameters, reducing misconfiguration risks. Documentation scaffolding, dependency hardening, and platform setup improvements reduce onboarding time and maintenance overhead.

September 2025 monthly summary for qibolab (repo: qiboteam/qibolab). Focused on reinforcing CI/CD, improving build quality, and accelerating delivery via automated testing and documentation workflows. Delivered CI/CD workflow enhancements with new configuration files and GitHub Actions to test C and Rust APIs and documentation pipelines. This work included merging the pre-commit CI update config (PR #1285) and a dedicated commit (53b3336605088f6886a4aa7f6db9e512ea6a56c3). No major bugs fixed this month; the emphasis was on pipeline reliability, automated validation, and developer productivity. Technologies demonstrated: GitHub Actions, CI/CD, pre-commit tooling, cross-language (C and Rust) API testing, and docs automation. Business value: faster feedback cycles, reduced manual testing, and higher confidence in releases.

Monthly Summary — 2025-08: Delivered developer tooling enhancements, targeted bug fixes, and improvements to hardware-control workflows across three repositories. Focus areas included reproducible development environments, Qblox debugging support, and timing reliability in pulse generation. These efforts reduce onboarding time, accelerate debugging, and improve the predictability of experimental control, contributing to faster deliverables and more robust user experiences.

July 2025 monthly summary focusing on delivering business value through a targeted bug fix, documentation and tooling improvements, and feature work across two repositories (qibolab, qibocal). The month combined reliability improvements, developer experience enhancements, and new analytical capabilities.”

June 2025 Monthly Summary — qibolab and qibocal Key features delivered and fixes: - Dependency lockfile and tooling updates across Nix, Python, and debugging tooling (flake lock, poetry.lock; replace legacy pdbpp with pudb) to improve compatibility and reproducible builds. - Qibolab: Memory handling and acquisition correctness fixes for Qblox instruments (correct memory limit; use shots-reduced options for shape computation) ensuring accurate data processing and reliable results. - Platform documentation overhaul: comprehensive rewrite clarifying workflow, parameter roles, platform definition, and removal of outdated Zurich Instruments references. - Platform API exposure: publish public 'configs' module as part of the official API under qibolab._core.components for easier configuration management. - Test configuration adjustment: temporarily disable or adjust tests under tests/qblox to stabilize CI during migration and fixes. - qibocal: Interactive Slurm session workflow added via a script that auto-detects local IP/port, provides SSH port forwarding guidance, and enables quick access to Jupyter Lab or a simple HTTP server. - Nix build cleanup: streamline nix files and environment setup for faster, more reliable builds. - Documentation: added a remote connection diagram to help users understand and configure remote access. Overall impact and accomplishments: - Improved build reproducibility, compatibility, and developer efficiency across both repositories. - Stronger API surface for configuration management and clearer platform documentation, reducing onboarding time and support effort. - Faster iteration cycles in CI and more reliable release readiness due to streamlined tooling and stabilized tests. - Practical tooling enhancements supporting scalable research workflows (interactive Slurm sessions and remote access visuals). Technologies/skills demonstrated: - Nix, Flakes, Poetry, Python tooling modernization - Memory management and data acquisition correctness - API design and public module exposure - Comprehensive documentation and onboarding materials - CI stability strategies and test governance

May 2025 monthly summary focusing on key accomplishments across qibolab and qibocal. Delivered density matrix tests and results extraction improvements, refactored emulator results processing for clearer data flow and extended Hamiltonian configuration usage, and implemented performance-oriented vectorization. Documentation overhaul streamlined onboarding and first-experiment workflows. Strengthened data integrity and cross-repo robustness through explicit numpy cast handling and UTF-8 encoding enforcement across file writes.

April 2025 performance-focused month for qibolab: delivered critical correctness fixes, improved observability, and updated dependencies to strengthen stability and future-readiness. Key changes included modulation attribution fix, RF-type metadata exposure, robust shot-count handling, density calculation improvements with tests, and a library upgrade to ensure compatibility with latest tools.

March 2025 performance summary for qibolab, qibo, and qibocal focusing on delivering end-to-end experimentation capabilities, stabilizing runtime behavior, and enabling higher-throughput pipelines. Key features delivered include the Pulse duration sweeper with multi-parameter sweep support, The Shots split batches feature enabling batched acquisitions across multiple shots, and emulator-related improvements that streamline sweeps and testing. Significant reliability work addressed waits merging and labeling, acquisition bins handling, memory usage validation, and general execution stability, together with refactors to support parallel sweepers and batch concatenation. Documentation and CI/CD improvements reduced onboarding time and operational risk. Overall impact: faster iteration cycles, improved data quality, and more maintainable codebase across multiple repos. Technologies/skills demonstrated: advanced Python refactoring, parameter handling and roles, vectorization and parallel sweep support, emulator integration and testing, and CI/test optimization.

February 2025 (2025-02) monthly summary for qibolab development. Focus areas: delivering robust parameter handling and channel sweep setup; improving data model robustness; modular architecture; UUID-based tracing; waveform timing and memory constraints; documentation and tooling improvements. Key initiatives and results: - Key features delivered: Parameter handling and channel sweep setup with sweep-related instruction generation for pulse sweeps and wait-loop decomposition; Refactor: data model for updates using a data class; Modularization: program split into modules and standardized loops; Added sweeper methods; UUID-driven pulse tracking with uuid4 propagation; Stretched waveforms and duration-aware generation; Time-of-flight handling; Documentation improvements; Pretty printing and build-tooling upgrades. Major bugs fixed: Channel sweep updates filtering and inclusion of swept registers; Prevent delay duration sweep hijack; Duration propagation to instruction generation; Reset gain to 1 for amplitude sweeps; Sequencer filtering of inactive units and synchronization; Improved probe channel handling, initial parameter handling, and exclusion logic; Time-of-flight corrections; Channel alignment padding; Replacing uuid1 with uuid4; Supplement channel filters for readout operations. Overall impact: Improved reliability, traceability, and maintainability of experiment runs; better timing precision and memory safety in waveform generation; robust parameter and sweep handling across channels and instruments. Technologies/skills demonstrated: Python refactoring and data modeling (data classes); modular architecture; UUID handling and propagation; advanced waveform generation (stretched waveforms, duration-aware generation); time-of-flight calculations; memory constraint validation; enhanced documentation and build tooling.

January 2025 focused on strengthening testability, reliability, and developer productivity for the qibolab repository (qiboteam/qibolab). Major efforts delivered a robust mocking framework for testing, re-enabled qblox cluster connectivity, and expanded mock coverage (including modules, sequencers, and recording/snapshot capabilities). In parallel, the team modernized CI/CD, streamlined dependencies, and improved configuration handling to support stable, data-driven operation in production. Key outcomes include: enhanced testability and reproducibility via comprehensive mocking and recording; reliable end-to-end testing with reflinked qblox connectivity; faster, cleaner builds and fewer linters-related churn through Ruff-based tooling and GitHub Actions v2 workflows; and improved configurability and data extraction to support analytics and optimization of RF workflows.

December 2024: Delivered foundational qblox integration and waveform handling, stabilized platform interactions, expanded observability, and strengthened acquisitions workflows. Key outcomes include an end-to-end qblox trajectory (channels exposure, waveform extraction, and initial program generation), platform reliability improvements across extraction and validation, enhanced deserialization/testing, and extended configurability and logging to support ops and debugging. The month also introduced initial acquisitions, bin-count reuse, and sequence exposure to enable scalable, data-driven experiments.

November 2024 monthly summary for qibolab: Established cluster sequence processing and execution framework, exposed public API for Qblox drivers, enhanced channel/port mapping, improved parameter update flows, and hardened data handling/serialization. This work delivers a scalable, API-driven control surface with stability improvements, enabling faster integration and reliable operation of quantum hardware across workflows.

In October 2024, delivered reliability improvements and parameter management enhancements across qibo and qibolab. Key outcomes include improved error reporting for missing backend providers, a new dictionary-based approach for nested parameter updates via dot-notation, and hardened parameter navigation to correctly handle string indices in nested structures. These changes reduce debugging time, simplify automation, and enhance system stability for experiments and deployments.

Summary for 2024-09: Focused on improving maintainability and reliability in qibolab by restructuring the qblox core, aligning tests with the new layout, and streamlining dependencies. Key outcomes include improved code organization, more reliable tests, and reduced maintenance burden, enabling faster future feature delivery.

April 2024 monthly summary for qibolab: Delivered foundational parser and AST architecture for Q1ASM, strengthened testing and environment readiness, and established a solid platform for reliable, high-quality feature delivery.