Native Approach to Controlled-Z Gates in Inductively Coupled Fluxonium Qubits.

The fluxonium qubits have emerged as a promising platform for gate-based quantum information processing. However, their extraordinary protection against charge fluctuations comes at a cost: when coupled capacitively, the qubit-qubit interactions are restricted to XX interactions. Consequently, effective ZZ or XZ interactions are only constructed either by temporarily populating higher-energy states, or by exploiting perturbative effects under microwave driving. Instead, we propose and demonstrate an inductive coupling scheme, which offers a wide selection of native qubit-qubit interactions for fluxonium. In particular, we leverage a built-in, flux-controlled ZZ interaction to perform qubit entanglement. To combat the increased flux-noise-induced dephasing away from the flux-insensitive position, we use a continuous version of the dynamical decoupling scheme to perform noise filtering. Combining these, we demonstrate a 20 ns controlled-z gate with a mean fidelity of 99.53%. More than confirming the efficacy of our gate scheme, this high-fidelity result also reveals a promising but rarely explored parameter space uniquely suitable for gate operations between fluxonium qubits.

FPGA-based electronic system for the control and readout of superconducting quantum processors.

Electronic systems for qubit control and measurement serve as a bridge between quantum programming language and quantum information processors. With the rapid development of superconducting quantum circuit technology, synchronization in a large-scale system, low-latency execution, and low noise are required for electronic systems. Here, we present a field-programmable gate array (FPGA)-based electronic system with a distributed synchronous clock and trigger architecture. The system supports synchronous control of qubits with jitters of ∼5 ps. We implement a real-time digital signal processing system in the FPGA, enabling precise timing control, arbitrary waveform generation, in-phase and quadrature demodulation for qubit state discrimination, and the generation of real-time qubit-state-dependent trigger signals for feedback/feedforward control. The hardware and firmware low-latency design reduces the feedback/feedforward latency of the electronic system to 125 ns, significantly less than the decoherence times of the qubit. Finally, we demonstrate the functionalities and low-noise performance of this system using a fluxonium quantum processor.

Fluxonium: An Alternative Qubit Platform for High-Fidelity Operations.

Superconducting qubits provide a promising path toward building large-scale quantum computers. The simple and robust transmon qubit has been the leading platform, achieving multiple milestones. However, fault-tolerant quantum computing calls for qubit operations at error rates significantly lower than those exhibited in the state of the art. Consequently, alternative superconducting qubits with better error protection have attracted increasing interest. Among them, fluxonium is a particularly promising candidate, featuring large anharmonicity and long coherence times. Here, we engineer a fluxonium-based quantum processor that integrates high qubit coherence, fast frequency tunability, and individual-qubit addressability for reset, readout, and gates. With simple and fast gate schemes, we achieve an average single-qubit gate fidelity of 99.97% and a two-qubit gate fidelity of up to 99.72%. This performance is comparable to the highest values reported in the literature of superconducting circuits. Thus our work, within the realm of superconducting qubits, reveals an alternative qubit platform that is competitive with the transmon system.

Efficient parallelization of tensor network contraction for simulating quantum computation.

We develop an algorithmic framework for contracting tensor networks and demonstrate its power by classically simulating quantum computation of sizes previously deemed out of reach. Our main contribution, index slicing, is a method that efficiently parallelizes the contraction by breaking it down into much smaller and identically structured subtasks, which can then be executed in parallel without dependencies. We benchmark our algorithm on a class of random quantum circuits, achieving greater than 105 times acceleration over the original estimate of the simulation cost. We then demonstrate applications of the simulation framework for aiding the development of quantum algorithms and quantum error correction. As tensor networks are widely used in computational science, our simulation framework may find further applications.

Thyroid hormone receptor interactor 13 (TRIP13) overexpression associated with tumor progression and poor prognosis in lung adenocarcinoma.

Thyroid hormone receptor interactor 13 (TRIP13) is an AAA+-ATPase that plays a key role in mitotic checkpoint complex inactivation and is associated with the progression of several cancers. However, its role in lung adenocarcinogenesis remains unknown. Here, we report that TRIP13 is highly overexpressed in multiple lung adenocarcinoma cell lines and tumor tissues. Clinically, TRIP13 expression is positively associated with tumor size, T-stage, and N-stage, and Kaplan-Meier analysis revealed that heightened TRIP13 expression is associated with lower overall survival. TRIP13 promotes lung adenocarcinoma cell proliferation, clonogenicity, and migration while inhibiting apoptosis and G2/M phase shift in vitro. Accordingly, TRIP13-silenced xenograft tumors displayed significant growth inhibition in vivo. Bioinformatics analysis demonstrated that TRIP13 interacts with a protein network associated with dsDNA break repair and PI3K/Akt signaling. TRIP13 upregulatesAktSer473 and downregulatesAktThr308/mTORSer2448activity, which suppresses accurate dsDNA break repair. TRIP13 also downregulates pro-apoptotic BadSer136 and cleaved caspase-3 while upregulating survivin. In conclusion, heightened TRIP13 expression appears to promote lung adenocarcinoma tumor progression and displays potential as a therapeutic target or biomarker for lung adenocarcinoma.

Cigarette smoke enhances initiation and progression of lung cancer by mutating Notch1/2 and dysregulating downstream signaling molecules.

Lung cancer is the primary cause of cancer related deaths in the western world and smoking significantly increases the risk of developing lung cancer. Smoking enhances lung cancer initiation and progression. The effects of cigarette smoke on lung cancer are mediated by the presence of highly mutagenic substances, including nicotine, leading to mutations in oncogenes and tumor suppressor genes. An emerging pathway in cancer is the Notch signaling pathway which is essential for embryonic lung development and tissue homeostasis. The role of Notch signaling in lung cancer remains controversial and no studies have directly linked cigarette exposure to mutations in Notch. Therefore, we investigated the direct effect of Notch signaling pathways on cigarette-induced lung tumors and the correlation between smoking and mutations in Notch leading to altered downstream signaling. Human cell lines, mouse models and clinical lung cancer samples were utilized in this study. Cigarette-induced in vitro human lung cancer models and in vivo mouse models demonstrated strong effects of cigarette exposure on the Notch signaling pathway. Immunohistochemistry (IHC) of 50 clinical samples collected from smokers and non-smokers with and without lung cancer also demonstrated a link between smoking and changes in Notch signaling. Finally, 34 lung cancer samples analyzed through direct sequencing indicated smoking significantly increased small nucleotide polymorphisms (SNPs) in Notch 1 and 2 and specific SNPs significantly modulated expression levels of downstream signaling pathway molecules. Taken together, these results demonstrate a direct effect of smoking on the Notch signaling pathway leading to lung cancer initiation and progression.