Welcome to the Quantum Realm. 

Enjoy today’s breakdown of news, research, & events within quantum.

Happy Friday — end it on a good note with (some of) these updates from the industry. Just don’t think too hard about quantum export restrictions or falling behind in the race for quantum security. Cheers 🍻 

🗓️ THIS WEEK

Wednesday, June 5 - Friday, June 14 | IBM Quantum Challenge 2024 — Register here!

Saturday, June 8 | Towards Practical Quantum Computing: Addressing Crosstalk and Circuit Optim w/ Washington DC Quantum Computing Meetup

Sunday, June 9 | QTM-X Weekly Quantum Education Session 3/10: Entanglement

📰 NEWS QUICK BYTES

🏃‍♀️ The Global Race for Quantum Security: Researchers are racing to develop quantum tech for secure data communication. While the EU leads with a clear roadmap for post-quantum cryptography, the U.S. lags. China excels in public funding and workforce development, putting the U.S. at risk of falling behind.

😕 UK Quantum Export Restrictions Spark Confusion: New UK export restrictions on quantum devices are unclear and potentially harmful to the industry. These rules apply to small and large quantum computers, classifying them as "dual-use" items. This could hinder sales and add bureaucracy, discouraging US companies from relocating to the UK.

🖥️ IEEE CS, ACM, and AAAI Release Updated Computer Science Curriculum: "Computer Science Curricula 2023" updates guidance for undergraduates on careers in computer science. It includes new focuses on AI, generative AI, quantum computing, and society, ethics, and the profession. Check out new curricula recommendations here. (CTRL + F “quantum” for the good stuff)

📢 Tackling Quantum Noise with Fourier Transform: JILA and CU Boulder researchers developed Fourier Transform Noise Spectroscopy to better control quantum noise. FTNS is simpler and requires fewer laser pulses, offering a clearer noise spectrum. It is currently being tested in various qubit systems.

🥇 Equal1 Wins Prestigious Quantum Computing Award: Equal1 has won the Institute of Physics' Quantum Business Innovation and Growth prize for its compact, energy-efficient silicon-based quantum computer. This recognition highlights Equal1's advancements in integrating quantum and classical components onto a single chip.

⛓️ QRL's Quantum-Resistant Blockchain Tech: Quantum Resistant Ledger has launched QRL Zond, a post-quantum secure distributed ledger technology. Now in beta-testnet, it allows developers to build quantum-safe applications using Ethereum's architecture, ensuring blockchain security against future quantum threats.

🔈️ Crypto Industry and Quantum Computing Advances: WSJ Crypto reporter Caitlin Ostroff discusses crypto strategy of investing in elections to survive, while WSJ contributor Bob Henderson talks about practical uses for quantum computers on the podcast.

☕️ FRESHLY BREWED RESEARCH

Latent Style-based Quantum GAN for high-quality Image Generation: A hybrid classical-quantum approach, coined the latent style-based quantum GAN, generates large-size images by embedding high-dimensional data into a lower-dimensional latent space using classical auto-encoders. LaSt-QGAN outperforms classical GANs on various datasets while addressing key challenges such as barren plateaus. Breakdown here.

Fault-Tolerant Quantum Computation Using Large Spin-Cat Codes: A fault-tolerant quantum error-correcting protocol using spin-cat codes tailored for large spin systems is introduced. By developing a rank-preserving CNOT gate and a measurement-free error-correction scheme, the study demonstrates higher fault-tolerant thresholds and reduced resource overheads compared to traditional methods, particularly for neutral-atom quantum computing platforms. Breakdown here.

Leakage Mobility in Superconducting Qubits as a Leakage Reduction Unit: Leakage mobility in superconducting qubits can act as a natural leakage reduction unit, meaning improved error correction performance without additional hardware or complex circuits. Simulations show that encouraging leakage movement between qubits actually enhances error suppression, suggesting a cost-effective method to manage leakage noise. Breakdown here.

QM-DLA: an efficient qubit mapping method based on dynamic look-ahead strategy: QM-DLA is presented as a new qubit mapping method using a dynamic look-ahead strategy to reduce the number of SWAP gates in quantum circuits. By optimizing initial qubit mapping and using a multi-window look-ahead heuristic, QM-DLA decreases the number of SWAP gates compared to state-of-the-art methods.

Assessing the potential of perfect screw dislocations in SiC for solid-state quantum technologies: Advanced ab initio calculations demonstrate that screw dislocations in silicon carbide can help create deterministic arrays of point defects and modulate the spin configuration of defects within their core. This would make such dislocations viable components for future defect-based quantum computers.

Deterministic Preparation of Optical Squeezed Cat and Gottesman-Kitaev-Preskill States: New scalable optical schemes for the deterministic preparation of large-amplitude squeezed cat states and high-quality Gottesman-Kitaev-Preskill states from photon-number states are presented. These schemes improve success probabilities and amplitudes and are technically feasible for near-term experimental implementation.

Quixer: A Quantum Transformer Model: Quixer is a quantum transformer model that uses linear combination of unitaries and quantum singular value transform primitives to perform language modeling tasks. Quixer achieves competitive performance with classical baselines on the Penn Treebank dataset and demonstrates its applicability to practical tasks, providing an open-source implementation for classical simulation and resource estimates for quantum hardware.

Ground-state-energy calculation for the water molecule on a superconducting quantum processor: A superconducting quantum processor is used to calculate the ground-state energy of a water molecule using a quantum computed moments approach combined with noise-mitigation. This method achieves a ground-state energy within 1.0 ± 0.8 milli-Hartree of exact diagonalization, which shows the potential of hybrid quantum-classical algorithms for achieving high accuracy in quantum chemistry calculations on NISQ devices.

UNTIL SUNDAY.

BREAKDOWN

Latent Style-based Quantum GAN for high-quality Image Generation

🔍️ SIGNIFICANCE: 

• The latent style-based quantum GAN (or LaSt-QGAN) is introduced as a potential step towards practical quantum advantage in data analysis. Unlike previous models that primarily focused on small-size data generation, LaSt-QGAN uses a hybrid classical-quantum approach to handle high-dimensional data efficiently. This approach is differentiated by its ability to generate large-size images with a comparable or even better performance than classical GANs on specific datasets, which is a notable advancement over previous quantum generative models.

🧪 METHODOLOGY: 

• Classical auto-encoders are used to map high-dimensional image data into a lower-dimensional latent space. This step reduces the complexity of the data and makes it manageable for the quantum GAN to process.

• The quantum GAN operates in this latent space to generate fake features, which are then decoded back into the original data space to reconstruct the images.

• This hybrid model uses a quantum generator (parameterized quantum circuit) and a classical discriminator. The generator takes random noise inputs and transforms them into latent features, which the discriminator then evaluates for authenticity.

• The study also incorporates the Wasserstein loss with gradient penalty to improve model convergence and stability. A notable modification in this approach is the use of expectation values of multiple observables (Pauli X and Z operators) in the quantum generator, which gives the model the ability to capture complex data distributions.

📊 OUTCOMES & OUTLOOK: 

• The research demonstrated that LaSt-QGAN can successfully generate large-size images with quality and diversity comparable to, and sometimes surpassing, those produced by classical GANs. The empirical results show that LaSt-QGAN outperforms classical GANs on the MNIST, Fashion MNIST, and SAT4 datasets in terms of Fréchet inception distance, inception score, and Jensen-Shannon divergence.

• Additionally, the research highlights that the model exhibits faster convergence and higher stability during training compared to classical GANs.

• The analysis of the model's resilience against statistical noise indicates that the generated images maintain high quality even with a finite number of measurement shots.

• The study also addresses the barren plateau problem in quantum generative models by demonstrating that a small angle initialization around the identity can mitigate this issue and allow the model to train effectively even with deep quantum circuits.

BREAKDOWN

Fault-Tolerant Quantum Computation Using Large Spin-Cat Codes

🔍 SIGNIFICANCE: 

• A fault-tolerant quantum error-correcting protocol using spin-cat codes which can substantially improve the resilience of quantum computers against dominant error sources like linear or quadratic angular momentum errors is introduced.

• The spin-cat encoding is analogous to the continuous-variable cat encoding but tailored for large spin systems, which makes it particularly useful for neutral-atom quantum computing platforms.

• By addressing specific error sources, this approach can achieve higher fault-tolerant thresholds and reduced resource overhead compared to traditional methods.

• Traditional fault-tolerant methods often address unstructured noise models and in turn, introduce significant overhead. Previous works on qudit systems and large spins have explored error-correcting encodings but lacked fault tolerance. This research differentiates itself by developing a fault-tolerant scheme specifically for spin systems, utilizing spin-cat encoding to correct dominant error sources. Additionally, it introduces a measurement-free error-correction scheme for amplitude errors.

🧪 METHODOLOGY: 

• The qubit states are encoded in spin coherent states along the physical quantization axis.

• Dominant error operators are characterized as linear and quadratic angular momentum operators and codes are designed to correct these errors.

• A rank-preserving CNOT gate is implemented to preserve the rank of spherical tensor operators, ensuring that correctable errors remain within their subspaces.

• Additionally, a measurement-free error-correction scheme is proposed to address amplitude errors without relying on syndrome measurements. This reduces complexity and resource requirements.

• The implementation specifically considers qudits encoded in the nuclear spin of 87Sr atoms, utilizing quantum control and the Rydberg blockade to generate the universal gate set.

📊 OUTCOMES & OUTLOOK: 

• The spin-cat encoding demonstrates a fault-tolerant threshold that surpasses standard qubit-based encodings. This higher threshold indicates improved resilience against dominant error sources.

• The implementation of a universal gate set, including the rank-preserving CNOT gate, allows for effective quantum computation with reduced error propagation.

• The proposed measurement-free error-correction scheme effectively addresses amplitude errors, simplifying the error-correction process and reducing resource overhead.

• These results indicate that spin-cat codes can improve the performance of fault-tolerant quantum computation by targeting specific error sources relevant to the physical platform. The higher fault-tolerant threshold and reduced resource overhead make this approach promising for scalable and efficient quantum computing.

BREAKDOWN

Leakage Mobility in Superconducting Qubits as a Leakage Reduction Unit

🔍 SIGNIFICANCE: 

• Leakage noise in superconducting qubits degrades the performance of quantum operations and cannot be mitigated by standard quantum error correction techniques. This study demonstrates how leakage mobility can actually act as a leakage reduction unit.

• This suggests that encouraging leakage mobility can improve QEC performance without the need for additional hardware or complex circuit modifications, unlike traditional LRUs which can introduce more noise or require extra qubits and gates.

🧪 METHODOLOGY: 

• The team modeled the qubits as qutrits to include leakage states and performed simulations using Qulacs, a classical quantum circuit simulator.

• The simulations incorporated a realistic noise model for superconducting transmon qubits, considering both relaxation and dephasing processes, as well as the effects of leakage.

• The researchers varied the leakage mobility parameter and compared the performance of standard QEC circuits with and without a specific LRU technique called patch wiggling, where qubit roles alternate to facilitate regular resets.

• Qutrits were simulated as pairs of qubits, with the CZ gate being the primary source of leakage noise. The simulations accounted for leakage mobility between qubits during two-qubit gates.

📊 OUTCOMES & OUTLOOK: 

• Increased leakage mobility improved the performance of QEC circuits by facilitating the transfer of leakage from data qubits to auxiliary qubits, where it could be removed upon reset, which shows that it can serve as an effective LRU. The error suppression rate also improved with increased leakage mobility.