Related papers: Identifying Pauli spin blockade using deep learnin…
We have developed a novel technique for detection of spin polarization with a quantum dot weakly coupled to the objective device. The disturbance to the object in this technique is very small since the detection is performed through…
The characterization of nuclear spin environments in solid-state devices plays an important role in advancing quantum technologies, yet traditional methods often demand long measurement times. To address this challenge, we integrate…
Recently, machine learning has been widely applied in the field of quantum information, notably in tasks such as entanglement detection, steering characterization, and nonlocality verification. However, few studies have focused on utilizing…
We present a solid-state implementation of ultrafast conditional quantum gates. Our proposal for a quantum-computing device is based on the spin degrees of freedom of electrons confined in semiconductor quantum dots, thus benefiting from…
Scalable quantum information processing in spin-based architectures necessitates the a bility to reliably shuttle quantum states across extended device regions with minimal decoherence. In this work, we present a physics-informed algorithm…
This study presents a machine-learning-based procedure to automate the charge tuning of semiconductor spin qubits with minimal human intervention, addressing one of the significant challenges in scaling up quantum dot technologies. This…
Quantum processor architectures must enable scaling to large qubit numbers while providing two-dimensional qubit connectivity and exquisite operation fidelities. For microwave-controlled semiconductor spin qubits, dense arrays have made…
We employ quantum circuit learning to simulate quantum field theories (QFTs). Typically, when simulating QFTs with quantum computers, we encounter significant challenges due to the technical limitations of quantum devices when implementing…
Identifying the pairing symmetry in unconventional superconductors is essential for reliably characterizing their superconducting states and for enabling their integration into realistic quantum devices. Here, we introduce a…
This study alleviates the low operating temperature constraint of Si qubits. A qubit is a key element for quantum sensors, memories, and computers. Electron spin in Si is a promising qubit, as it allows both long coherence times and…
Effective spin-spin interactions between N+1 qubits enable the determination of the eigenvalue of an arbitrary Pauli product of dimension N with a constant, small number of multi-qubit gates that is independent of N and encodes the…
The detection of nuclear spins using individual electron spins has enabled new opportunities in quantum sensing and quantum information processing. Proof-of-principle experiments have demonstrated atomic-scale imaging of nuclear-spin…
Exploiting the spin-valley degree of freedom of electrons in materials is a promising avenue for energy-efficient information storage and quantum computing. A key challenge in utilizing spin-valley polarization is the realization of…
Spin qubits are contenders for scalable quantum computation because of their long coherence times demonstrated in a variety of materials, but individual control by frequency-selective addressing using pulsed spin resonance creates severe…
Larger arrays of electron spin qubits require radical improvements in fabrication and device uniformity. Here we demonstrate excellent qubit device uniformity and tunability from 300K down to mK temperatures. This is achieved, for the first…
Deep brain stimulation (DBS) is a neurosurgical procedure successfully used to treat conditions such as Parkinson's disease. Electrostimulation, carried out by implanting electrodes into an identified focus in the brain, makes it possible…
Modeling and simulating a power distribution network (PDN) for printed circuit boards (PCBs) with irregular board shapes and multi-layer stackup is computationally inefficient using full-wave simulations. This paper presents a new concept…
In this this paper we present an inexpensive protocol to perform runtime and memory estimation for large-scale experiments with Pauli Path simulators (PPS). Additionally, we propose a conceptually simple solution for studying whether PPS…
We apply the quantum error detection scheme Pauli check sandwiching (PCS) to quantum networks by turning it into a distributed multiparty protocol. PCS provides protection on the targeted qubits and generally requires less resource overhead…
Spin injection and detection in silicon is a difficult problem, in part because the weak spin-orbit coupling and indirect gap preclude using standard optical techniques. We propose two ways to overcome this difficulty, and illustrate their…