Classiq/classiq-library
Dec 2024 – Feb 2026
14 Months active
Languages Used
JSONPythonClassiqJupyter NotebookQiskitQmodQModText
Technical Skills
Jupyter NotebooksPythonQuantum Algorithm DevelopmentQuantum ComputingAlgorithm DevelopmentClassiq
Tomer Goldfriend
PROFILE
Tomer Goldfriend
Tomer developed and maintained a broad suite of quantum algorithm workflows in the Classiq/classiq-library repository, focusing on robust, reproducible research and scalable experimentation. He engineered features such as QSVT, Chebyshev solvers, and quantum walk optimizations, integrating Python and Jupyter Notebooks with quantum frameworks like Qiskit. His work included modular refactoring, block-encoding enhancements, and performance tuning, enabling efficient circuit execution and reliable benchmarking. Tomer improved documentation, streamlined test infrastructure, and aligned chemistry modules for evolving libraries. The depth of his engineering is reflected in the library’s maintainability, reproducibility, and readiness for advanced quantum computing and machine learning applications.
Overall Statistics
Feature vs Bugs
71%Features
Repository Contributions
244Total
Bugs
39
Commits
244
Features
95
Lines of code
176,308
Activity Months14
Your Network
80 people
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly work summary focusing on delivering performance optimization for quantum walk computations in Classiq's library. Refactored the symmetric walk operation to utilize the block-encoding quantum function instead of the walk operator directly, resulting in improved efficiency and faster quantum circuit execution. Updated execution time metrics and linked quantum programs to reflect performance improvements. Maintained API compatibility and provided clear commit traceability.
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly work summary focusing on delivering performance optimization for quantum walk computations in Classiq's library. Refactored the symmetric walk operation to utilize the block-encoding quantum function instead of the walk operator directly, resulting in improved efficiency and faster quantum circuit execution. Updated execution time metrics and linked quantum programs to reflect performance improvements. Maintained API compatibility and provided clear commit traceability.
February 2026
January 2026
37 Commits • 11 Features
Jan 1, 2026Month 2026-01 focused on foundational restructuring, quality improvements, and enabling modular usage in Classiq-library. Key activities included comprehensive project structure scaffolding and directory renames to align topics (foundational, search_and_optimization, ground_state_and_spectral_methods, quantum_linear_solvers, quantum_primitives, quantum_walks_and_graph_problems, quantum_state_preparation, amplitude_amplification) and renames (algebraic to number_theory_and_cryptography; differential equations), setting the stage for scalable feature development. Added output cells to the last notebook to improve readability and reproducibility. Introduced standalone HHL QMOD component for modular usage. Updated QPE with a qubitization example to illustrate usage. Performed cleanup to remove deprecated write_qmod and other dead code, reducing technical debt. Also completed several maintenance fixes and documentation improvements to stabilize the project.
January 2026
37 Commits • 11 Features
Jan 1, 2026Month 2026-01 focused on foundational restructuring, quality improvements, and enabling modular usage in Classiq-library. Key activities included comprehensive project structure scaffolding and directory renames to align topics (foundational, search_and_optimization, ground_state_and_spectral_methods, quantum_linear_solvers, quantum_primitives, quantum_walks_and_graph_problems, quantum_state_preparation, amplitude_amplification) and renames (algebraic to number_theory_and_cryptography; differential equations), setting the stage for scalable feature development. Added output cells to the last notebook to improve readability and reproducibility. Introduced standalone HHL QMOD component for modular usage. Updated QPE with a qubitization example to illustrate usage. Performed cleanup to remove deprecated write_qmod and other dead code, reducing technical debt. Also completed several maintenance fixes and documentation improvements to stabilize the project.
December 2025
21 Commits • 11 Features
Dec 1, 2025December 2025 — Classiq-library delivered targeted features for prototyping quantum algorithms, tightened reliability, and enhanced documentation/metadata workflows. Core feature deliveries include an explicit operator transform function, QPE with qubitization (qmod and metadata), a hybrid HHL example, and a Pauli operation refactor with updated imports. Timeouts management updates standardized and expanded timeout handling across the library. These changes, together with notebook/metadata improvements and code hygiene, improved reproducibility, onboarding, and the robustness of demonstrations.
21 Commits • 11 Features
Dec 1, 2025December 2025 — Classiq-library delivered targeted features for prototyping quantum algorithms, tightened reliability, and enhanced documentation/metadata workflows. Core feature deliveries include an explicit operator transform function, QPE with qubitization (qmod and metadata), a hybrid HHL example, and a Pauli operation refactor with updated imports. Timeouts management updates standardized and expanded timeout handling across the library. These changes, together with notebook/metadata improvements and code hygiene, improved reproducibility, onboarding, and the robustness of demonstrations.
December 2025
November 2025
12 Commits • 7 Features
Nov 1, 2025In 2025-11, the Classiq/library delivered a focused set of performance, reliability, and maintainability improvements that empower faster quantum simulations, cleaner data handling, and scalable workloads. The work spans data-driven Hamiltonian trimming, enhanced block encoding workflows, robust numerical utilities, and foundational codebase refactors, all accompanied by memory-management refinements and notebook enhancements. These changes reduce runtime and memory footprint, improve solver reliability, and prepare the codebase for Shor-like algorithms and larger-scale experiments.
November 2025
12 Commits • 7 Features
Nov 1, 2025In 2025-11, the Classiq/library delivered a focused set of performance, reliability, and maintainability improvements that empower faster quantum simulations, cleaner data handling, and scalable workloads. The work spans data-driven Hamiltonian trimming, enhanced block encoding workflows, robust numerical utilities, and foundational codebase refactors, all accompanied by memory-management refinements and notebook enhancements. These changes reduce runtime and memory footprint, improve solver reliability, and prepare the codebase for Shor-like algorithms and larger-scale experiments.
October 2025
3 Commits • 2 Features
Oct 1, 2025October 2025 performance highlights for Classiq/classiq-library focused on delivering robust, maintainable quantum algorithm implementations and streamlined examples that reduce external dependencies while improving accuracy and documentation. The month delivered meaningful feature refinements, critical bug corrections, and tangible business value through clearer outputs, reproducible workflows, and shorter iteration cycles for end-to-end quantum workflow experiments.
3 Commits • 2 Features
Oct 1, 2025October 2025 performance highlights for Classiq/classiq-library focused on delivering robust, maintainable quantum algorithm implementations and streamlined examples that reduce external dependencies while improving accuracy and documentation. The month delivered meaningful feature refinements, critical bug corrections, and tangible business value through clearer outputs, reproducible workflows, and shorter iteration cycles for end-to-end quantum workflow experiments.
October 2025
September 2025
54 Commits • 21 Features
Sep 1, 2025During Sep 2025, delivered major feature expansions for QSVT/QMods and Chebyshev solvers, strengthened verification, and advanced notebook tutorials to accelerate onboarding and experimentation. Key features include QSVT integration with qsvt examples/solver and qmods; Chebyshev LCU solver and utilities; and Chebyshev/QMods expansions. Major bug fixes and stability improvements covered banded Be symmetry verification, missing RHS vector, QSVT inversion qmod handling, and targeted post-fix adjustments. Enhanced testing scaffolding and notebooks, including GQSP example and QSP-ready workflows, improve reliability and learning. Ecosystem alignment achieved via migration to Classiq Chem, updated docs and references, and QML installation support in notebooks. These outcomes improve business value by enabling faster prototyping, more reliable solvers, and a smoother onboarding path for users.
September 2025
54 Commits • 21 Features
Sep 1, 2025During Sep 2025, delivered major feature expansions for QSVT/QMods and Chebyshev solvers, strengthened verification, and advanced notebook tutorials to accelerate onboarding and experimentation. Key features include QSVT integration with qsvt examples/solver and qmods; Chebyshev LCU solver and utilities; and Chebyshev/QMods expansions. Major bug fixes and stability improvements covered banded Be symmetry verification, missing RHS vector, QSVT inversion qmod handling, and targeted post-fix adjustments. Enhanced testing scaffolding and notebooks, including GQSP example and QSP-ready workflows, improve reliability and learning. Ecosystem alignment achieved via migration to Classiq Chem, updated docs and references, and QML installation support in notebooks. These outcomes improve business value by enabling faster prototyping, more reliable solvers, and a smoother onboarding path for users.
August 2025
16 Commits • 7 Features
Aug 1, 2025During August 2025, delivered a cohesive set of notebook features, tooling improvements, and verification capabilities in Classiq-library, focusing on robustness, accuracy, and alignment with evolving chemistry libraries. Key outcomes include: a new Vlasov-Ampere Qiskit notebook with block-encoding and QSVT steps, plus dedicated tests and extended timeouts; updated exponentiation notebook to reflect OpenFermion/Classiq chemistry definitions with refactored Hamiltonian generation; strengthened Hamiltonian evolution tooling with improved test coverage and OpenFermion/Classiq chemistry module integration; VQLS with LCU notebook enhancements; simplification of the state preparation tutorial; overhauled test infrastructure for stability and faster feedback; and new block-encoding verification in CFD. These efforts improve reproducibility, accelerate experimentation, and deliver business value by enabling robust validation of complex chemistry and quantum algorithms.
16 Commits • 7 Features
Aug 1, 2025During August 2025, delivered a cohesive set of notebook features, tooling improvements, and verification capabilities in Classiq-library, focusing on robustness, accuracy, and alignment with evolving chemistry libraries. Key outcomes include: a new Vlasov-Ampere Qiskit notebook with block-encoding and QSVT steps, plus dedicated tests and extended timeouts; updated exponentiation notebook to reflect OpenFermion/Classiq chemistry definitions with refactored Hamiltonian generation; strengthened Hamiltonian evolution tooling with improved test coverage and OpenFermion/Classiq chemistry module integration; VQLS with LCU notebook enhancements; simplification of the state preparation tutorial; overhauled test infrastructure for stability and faster feedback; and new block-encoding verification in CFD. These efforts improve reproducibility, accelerate experimentation, and deliver business value by enabling robust validation of complex chemistry and quantum algorithms.
August 2025
July 2025
38 Commits • 12 Features
Jul 1, 2025July 2025 performance summary for Classiq/classiq-library: Delivered a broad expansion of model capabilities across quantum and classical analytics, integrated autoencoder with metadata handling and tests, and strengthened testing and reliability through infrastructure enhancements, version alignment, and targeted bug fixes. The work positions the library for broader experimentation with QML models, analytics workloads, and demo-ready capabilities, while improving production stability and reproducibility.
July 2025
38 Commits • 12 Features
Jul 1, 2025July 2025 performance summary for Classiq/classiq-library: Delivered a broad expansion of model capabilities across quantum and classical analytics, integrated autoencoder with metadata handling and tests, and strengthened testing and reliability through infrastructure enhancements, version alignment, and targeted bug fixes. The work positions the library for broader experimentation with QML models, analytics workloads, and demo-ready capabilities, while improving production stability and reproducibility.
June 2025
26 Commits • 12 Features
Jun 1, 2025June 2025: Expanded the Classiq library with broad experimental integrations, multi-module algorithm support, and enhanced release quality. Work delivered across DJ/BV/SIMON integrations, multiple quantum-module integrations (QW, QMCI, AQC, HHL), VQE/QPE capabilities, tutorials, and CI/test improvements, creating new capabilities for experimentation, faster time-to-insight for customers, and more robust release readiness.
26 Commits • 12 Features
Jun 1, 2025June 2025: Expanded the Classiq library with broad experimental integrations, multi-module algorithm support, and enhanced release quality. Work delivered across DJ/BV/SIMON integrations, multiple quantum-module integrations (QW, QMCI, AQC, HHL), VQE/QPE capabilities, tutorials, and CI/test improvements, creating new capabilities for experimentation, faster time-to-insight for customers, and more robust release readiness.
June 2025
May 2025
3 Commits • 1 Features
May 1, 2025May 2025 focused on strengthening the reliability and demonstrability of the quantum program execution path within Classiq's library. Key work included updating and tightening test coverage for quantum programs and updating interactive demos to reflect current execution characteristics. These changes improve validation, reproducibility, and demonstration quality, accelerating QA feedback and customer-facing walkthroughs.
May 2025
3 Commits • 1 Features
May 1, 2025May 2025 focused on strengthening the reliability and demonstrability of the quantum program execution path within Classiq's library. Key work included updating and tightening test coverage for quantum programs and updating interactive demos to reflect current execution characteristics. These changes improve validation, reproducibility, and demonstration quality, accelerating QA feedback and customer-facing walkthroughs.
April 2025
20 Commits • 6 Features
Apr 1, 2025April 2025 performance summary: Delivered a cohesive set of features across the quantum algorithm suite with a strong emphasis on test reliability, benchmarking validity, and expanded VQE capabilities. Key outcomes include robust 3SAT oracle tests, enhanced quantum volume validation, updated Deutsch-Jozsa notebooks and tests, improved glued trees testing, expanded Grover/QPE coverage, and a broadened OpenFermion-based VQE workflow with stability enhancements and ExecutionSession usage. Resulting impact: more reliable benchmarks, end-to-end validation, and scalable quantum chemistry tooling for production experiments.
20 Commits • 6 Features
Apr 1, 2025April 2025 performance summary: Delivered a cohesive set of features across the quantum algorithm suite with a strong emphasis on test reliability, benchmarking validity, and expanded VQE capabilities. Key outcomes include robust 3SAT oracle tests, enhanced quantum volume validation, updated Deutsch-Jozsa notebooks and tests, improved glued trees testing, expanded Grover/QPE coverage, and a broadened OpenFermion-based VQE workflow with stability enhancements and ExecutionSession usage. Resulting impact: more reliable benchmarks, end-to-end validation, and scalable quantum chemistry tooling for production experiments.
April 2025
March 2025
5 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for Classiq/classiq-library focused on stabilizing and delivering Quantum Phase Estimation (QPE) workflows for molecular systems, with substantial enhancements to tutorials, testing, and documentation. The work improved accuracy, reliability, and onboarding for users performing molecular energy calculations.
March 2025
5 Commits • 1 Features
Mar 1, 2025March 2025 performance summary for Classiq/classiq-library focused on stabilizing and delivering Quantum Phase Estimation (QPE) workflows for molecular systems, with substantial enhancements to tutorials, testing, and documentation. The work improved accuracy, reliability, and onboarding for users performing molecular energy calculations.
January 2025
7 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for Classiq library highlighting feature delivery and code quality improvements aimed at expanding QSVM capabilities and maintaining robust, clear APIs. Key features delivered: - QSVM: Generalized Bloch-sphere feature map and training/prediction workflow implemented for dimension-agnostic feature vectors; refactored the Pauli feature map into modular components (Hamiltonian connectivity and Hamiltonian generation); updated QSVM training, testing, and prediction flows within the Classiq integration to enable more flexible and robust QSVM workflows. Commits: cd6451d97e7e7431a654122a8a3fec907fad2ffa; 20d5c8d06e277e96d327e3fbef750ca3727b63df; 0d5f775c471ade83295295f77a1e32eb12b7025f. - QSVM & Suzuki-Trotter: Documentation improvements for Suzuki-Trotter; code refactors and clearer API/parameter usage for QSVM and Hamiltonian-simulation components; test-suite adjustments to skip irrelevant Kaggle dataset; minor notebook documentation fixes to maintain consistency. Commits: 0b2fa0b560f8108bc258f8aab7967ebe92224100; 88e0e42cb310b42acbd326446ef3b6281c1f0ea8; 0cfc3cffd28bfe6b91e2c4e14dcfa3a5eb4e0ce9; 3428a9845e9c22a39a22efba1757a268f4ad9dd3. Major bugs fixed: - No major defects reported this month. Several minor fixes and stability improvements were implemented in tandem with feature work, including cr fixes and test-config cleanups to improve reliability and documentation consistency (commit references: 88e0e42cb310b42acbd326446ef3b6281c1f0ea8; 0cfc3cffd28bfe6b91e2c4e14dcfa3a5eb4e0ce9). Overall impact and accomplishments: - Expanded QSVM capabilities with a dimension-agnostic Bloch-sphere feature map and modularized Pauli feature map, enabling broader, more robust QSVM workflows within Classiq. - Improved developer experience and maintainability through API clarity, documentation enhancements, and test configuration optimizations, reducing noise in Kaggle-related tests and ensuring consistent notebook references. - Strengthened business value by enabling more flexible experimentation with QSVM and Hamiltonian-simulation components, accelerating time-to-insight for quantum-accelerated ML use cases. Technologies/skills demonstrated: - Quantum-inspired ML concepts: QSVM, Bloch-sphere feature maps, Hamiltonian connectivity/generation, Suzuki-Trotter integration. - Software engineering: modular refactors, API clarity, comprehensive documentation, test configuration, and notebook documentation.
7 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for Classiq library highlighting feature delivery and code quality improvements aimed at expanding QSVM capabilities and maintaining robust, clear APIs. Key features delivered: - QSVM: Generalized Bloch-sphere feature map and training/prediction workflow implemented for dimension-agnostic feature vectors; refactored the Pauli feature map into modular components (Hamiltonian connectivity and Hamiltonian generation); updated QSVM training, testing, and prediction flows within the Classiq integration to enable more flexible and robust QSVM workflows. Commits: cd6451d97e7e7431a654122a8a3fec907fad2ffa; 20d5c8d06e277e96d327e3fbef750ca3727b63df; 0d5f775c471ade83295295f77a1e32eb12b7025f. - QSVM & Suzuki-Trotter: Documentation improvements for Suzuki-Trotter; code refactors and clearer API/parameter usage for QSVM and Hamiltonian-simulation components; test-suite adjustments to skip irrelevant Kaggle dataset; minor notebook documentation fixes to maintain consistency. Commits: 0b2fa0b560f8108bc258f8aab7967ebe92224100; 88e0e42cb310b42acbd326446ef3b6281c1f0ea8; 0cfc3cffd28bfe6b91e2c4e14dcfa3a5eb4e0ce9; 3428a9845e9c22a39a22efba1757a268f4ad9dd3. Major bugs fixed: - No major defects reported this month. Several minor fixes and stability improvements were implemented in tandem with feature work, including cr fixes and test-config cleanups to improve reliability and documentation consistency (commit references: 88e0e42cb310b42acbd326446ef3b6281c1f0ea8; 0cfc3cffd28bfe6b91e2c4e14dcfa3a5eb4e0ce9). Overall impact and accomplishments: - Expanded QSVM capabilities with a dimension-agnostic Bloch-sphere feature map and modularized Pauli feature map, enabling broader, more robust QSVM workflows within Classiq. - Improved developer experience and maintainability through API clarity, documentation enhancements, and test configuration optimizations, reducing noise in Kaggle-related tests and ensuring consistent notebook references. - Strengthened business value by enabling more flexible experimentation with QSVM and Hamiltonian-simulation components, accelerating time-to-insight for quantum-accelerated ML use cases. Technologies/skills demonstrated: - Quantum-inspired ML concepts: QSVM, Bloch-sphere feature maps, Hamiltonian connectivity/generation, Suzuki-Trotter integration. - Software engineering: modular refactors, API clarity, comprehensive documentation, test configuration, and notebook documentation.
January 2025
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for Classiq/library: Delivered cross-framework example notebooks for QSVT and discrete quantum walks, demonstrating implementations across Classiq, PennyLane, Qiskit, and PyTket. The notebooks include detailed circuit constructions, framework-specific compilation and execution steps, and a comparative analysis aligned with the Classiq paper, establishing a reproducible research resource and educational material.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 monthly summary for Classiq/library: Delivered cross-framework example notebooks for QSVT and discrete quantum walks, demonstrating implementations across Classiq, PennyLane, Qiskit, and PyTket. The notebooks include detailed circuit constructions, framework-specific compilation and execution steps, and a comparative analysis aligned with the Classiq paper, establishing a reproducible research resource and educational material.
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Quality Metrics
Correctness88.2%
Maintainability86.8%
Architecture84.6%
Performance79.6%
AI Usage26.2%
Skills & Technologies
Programming Languages
ClassiqJSONJupyter NotebookMarkdownPythonQASMQMODQModQiskitQiskit (Qiskit Mod)
Technical Skills
Algorithm DevelopmentAlgorithm ImplementationAlgorithm OptimizationAlgorithm RefactoringAlgorithm RefinementAlgorithm TestingAlgorithm VerificationAnsatz DesignBenchmarkingBlock EncodingCFDCI/CDChebyshev PolynomialsChemistryChemistry Simulation
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