Xanadu社が量子ソフトウェア勉強会の補足教材を提示

カナダ量子コンピュータ企業のXanadu社から、量子ソフトウェア研究拠点で開催されている量子ソフトウェア勉強会に関心をお持ちいただきました。日本の量子教育活動に貢献したいという思いから、今年度量子ソフトウェア勉強会の講義を補足する自社の教材リンクを紹介いただきました。

教材を通じて、学習者は理論とcodingの両面で量子ソフトウェアに関する理解を深めることが可能です。

Xanadu社の許可をいただき、本ページに掲載させていただきます。

#	講義タイトル	Xanadu社教材リンク
1	量子コンピュータの現状と展望	●    What is quantum computing?
2	量子計算の基礎	●    Qubits, bra-ket notation, superposition, measurements, etc. (Codebook Module I.1). ●    Quantum Circuits (Codebook Module I.2). ●    Unitaries (Codebook Module I.3). ●    Quantum operations and 1-qubit gates (Codebook Module I.4). ●    Global and relative phases (Codebook Module I.5). ●    Rotation gates and Bloch sphere (Codebook Module I.6). ●    Projective measurements, basis, and basis rotations (Codebook Module I.9). ●    Observables and expectation values (Codebook Module I.10). ●    Tensor product and multi-qubit systems (Codebook Module I.11). ●    Entanglement and controlled operations (Codebook Module I.12). ●    Bell states (examples of maximally entangled states) (Codebook Module I.14). ●    Resources for notebooks: ○    Brief introduction to quantum circuits with PennyLane (Explanation)     ○    Quantum operations in PennyLane (Explanation)     ○    Measurements in PennyLane (Explanation) ○ PennyLane devices (Explanation) — In particular, the default.mixed device allows for simulation of noisy circuits.
3	量子アルゴリズムの基礎	●    Variational circuits (Explanation). ●    Differentiable programming (Explanation). ●    Parameter-shift rule (Explanation). ●    Gradients and training with PennyLane (Explanation). ●    Optimizing quantum circuits (Demo). ●    Introduction to QAOA (Demo). ●    QAOA for MaxCut (Demo). ●    A brief overview of VQE (Demo) — Geared towards applications in quantum chemistry. ●    Resources for notebooks: ○    Building molecular Hamiltonians (Demo). ○    Variational Quantum Thermalizer (Demo) — Example with Heisenberg model.
4	量子機械学習の基礎	●    What is Quantum Machine Learning (QML)? (Explanation) ●    Quantum Advantage in QML (Blog) — The associated article “Is quantum advantage the right goal for quantum machine learning?” could be a good source for discussion. ●    Embeddings (Explanation). ○    PennyLane’s different embedding templates (read this blog post on embeddings to learn more). ●    Quantum Feature Map (Explanation). ●    Kernel-based training of quantum models with scikit-learn (Demo). ●    Training and evaluating quantum kernels (Demo). Classical and Quantum Kernels (Demo) — Recommended after the previous 2 demos. ●    Datasets for quantum machine learning (Explanation).
5	量子コンピュータの物理的実現方式	●    Photonic quantum computers (Demo). ○    Additional resource: Xanadu’s fault-tolerant architecture (Video). ●    Trapped ions (Demo). ●    Superconducting qubits (Demo). ●    Neutral-atom quantum computers (Demo).
6	量子コンピュータのための物性物理入門	●    Machine learning for quantum many-body problems (Demo). ○    Additional resource: Classical shadows (Demo). ●    PennyLane datasets (Explanation). ○    Bose-Hubbard model dataset (Explanation). ○    Fermi-Hubbard model dataset (Explanation). ○    Transverse-field Ising model dataset (Explanation). ○ XXZ-Heisenberg model dataset (Explanation). ●    Tensor-network quantum circuits (Demo).
7	量子エラー補償の基礎	●    Noisy circuits (Demo) — Introduction to noisy channels, using Kraus operators and simulating noisy circuits. ●    Zero-Noise Extrapolation and Richardson Extrapolation (Demo). ●    Error mitigation with Mitiq and PennyLane (Demo). ●    Motivation for error correction and repetition codes (Codebook Module E.1). ●    Bit flip and phase errors (Codebook Module E.2). ●    Shor’s 9-qubit code (Codebook Module E.3).
8	量子アルゴリズム各論/質問大会	● Grover’s algorithm ○    Introduction to Grover’s Algorithm: Amplitude amplification and the diffusion operator (Codebook Module G.1).     ○    The geometry of Grover Search (Codebook Module G.2). ○ Phase kickback and implementing diffusion and oracle operators using multi-controlled X gates. (Codebook Module G.3).     ○    Grover step and scaling (Codebook Module G.4).     ○     Geometry and scaling of Grover search for multiple solutions (Codebook Module G.5).     ○    Additional resources: ■    Grover’s Algorithm (Demo) — Recommended after introducing material in Codebook.         ■    Grover’s Algorithm in PennyLane (Video). ●    Quantum phase estimation — assumes knowledge of the Quantum Fourier Transform. ○    Phase kickback and QPE Applications (Codebook Module P.1).     ○    QPE circuit (Codebook Module P.2).     ○    QPE for phases that do not have a t-bit binary expansion (Codebook module P.3). ○ Outcomes of the QPE subroutine when the target wires are prepared in an arbitrary state (Codebook module P.4).
9	クラウドで量子計算が行われる仕組み	●    Running PennyLane on IBM Q Hardware (Explanation). ● Optimizing noisy circuits with Cirq (Demo).
10	量子コンピュータと金融実務計算	● The quantum_monte_carlo transform is intended for use when you already have set up the circuit for performing the unitary F in this paper. This transform is compatible with resource estimation and potential hardware implementation. The QuantumMonteCarlo template is only compatible with simulators but may perform faster and is suited to quick prototyping. ● If you want to implement the paper above you might find the qml.apply_controlled_Q function useful.
11	量子コンピュータと量子化学計算の基礎	●    Quantum computing for quantum chemistry: A brief perspective (Blog) by Juan Miguel Arrazola, Head of Algorithms at Xanadu. ●    Introduction to Quantum Chemistry (Video). ●    Variational Quantum Eigensolver (Video). ●    How to use the Hartree-Fock method in PennyLane (Blog). ●    Differentiable Hartree-Fock (Demo). ●    Optimization of molecular geometries (Demo). ●    Givens rotations for quantum chemistry (Demo). ●    Adaptive circuits for quantum chemistry (Demo). ●    Fermionic operators with PennyLane (Demo). ●    Modeling chemical reactions on a quantum computer (Demo). ●    Datasets for quantum chemistry (Explanation). ●    Additional resources for notebooks: ○    Using PennyLane with PySCF and OpenFermion (Demo).
16	Amazon Braket を用いた実機・シミュレータでの開発	●    Computing gradients in parallel with Amazon Braket (Demo). ●    PennyLane-Braket plugin (Documentation).

Xanadu社にはこの場を借りて厚く御礼申し上げます。

Support and additional resources

• Discussion Forum: Where students can ask questions.
• Xanadu Slack: Where students can join the community.
• QHack 2023, QHack 2022, and QHack 2021 coding challenge repositories: For additional practice ideas.
• Xanadu research: Contains research on quantum machine learning, quantum chemistry, photonic quantum computing, quantum software, fault-tolerant architectures, and more.
• Xanadu newsletter: to stay up to date with the latest content and news.

About Xanadu and PennyLane

Xanadu is a Canadian quantum computing company with the mission to build quantum computers that are useful and available to people everywhere. Xanadu is one of the world’s leading quantum hardware and software companies and also leads the development of PennyLane.

PennyLane is an open-source software framework for quantum machine learning, quantum chemistry, and quantum computing, with the ability to run on all hardware.