A Novel n⁺/i-well Dot Ge₁₋ₓSnₓ-on-Si Single-Photon Avalanche Photodiode for High-Fill-Factor Room-Temperature Quantum Applications

Abstract: We propose a novel design of Ge1-xSnx-on-Si single-photon avalanche photodiodes (SPADs) that aim to enhance the fill factor (FF) and minimize noise at room temperature. The device consists of a n+/i-well dot structure designed to eliminate the need for guard rings and multi-dot or array configurations typically used to enhance the active area. This […]

ZAP: Zoned Architecture and Performant Compiler for Field Programmable Atom Array

Abstract: The scalability of neutral-atom quantum computing is increasingly limited by a compiler–architecture challenge: logical circuits must be mapped onto dynamically reconfigurable atom arrays while controlling crosstalk, transport overhead, and hardware constraints. To address this problem, we present ZAP, a co-designed zoned architecture and deterministic compiler for field-programmable atom arrays. ZAP partitions the array into […]

Perfect Quantum Teleportation in Memory Amplitude-Damping Channels Based on Pre-flipping and Environment-Assisted Measurement

Abstract: Most existing quantum teleportation schemes do not consider the memory effect of noise, which is becoming increasingly serious in practical quantum communication. In this paper, we propose two quantum teleportation protocols for noisy memory channels: one based on pre-flipping (PF) and another incorporating pre-flipping with environment-assisted measurement (PF-EAM). In the PF protocol, a pre-flipping […]

Extrapolating Pauli Checks for Expectation Value Estimation on Noisy Quantum Devices

Abstract: Pauli Check Sandwiching (PCS) is an error detection scheme that protects quantum circuits by inserting pairs of parity checks and discarding runs that signal errors. However, each additional check introduces noise and exponentially increases sampling costs. To address these limitations, we propose Pauli Check Extrapolation (PCE), an error mitigation technique that obtains measured expectation […]

Unified and Generalized Approach to Entanglement-Assisted Quantum Error Correction

Abstract: We introduce a framework for entanglement-assisted quantum error correcting codes that unifies the three original frameworks for such codes called entanglement-assisted quantum error correction, entanglement-assisted operator quantum error correction, and entanglement-assisted classical enhanced quantum error correction under a single umbrella. As a consequence, new types of entanglement-assisted codes are identified and constructed. The unification […]

Quantum Circuit-Based Adaptation for Credit Risk Analysis

Abstract: Noisy and Intermediate-Scale Quantum, or NISQ, processors are sensitive to noise, prone to quantum decoherence, and are not yet capable of continuous quantum error correction for fault-tolerant quantum computation. Hence, quantum algorithms designed in the pre-fault-tolerant era cannot neglect the noisy nature of the hardware, and investigating the relationship between quantum hardware performance and […]

QCHFT: Quantum Cross-Hybrid Fine-Tuning for LLMs

Abstract: When full-parameter updates are impractical for large language models (LLMs), parameter-efficient fine-tuning (PEFT) is commonly employed to reduce the number of trainable parameters. Classical PEFT methods, such as low-rank adaptation (LoRA), are limited to linear transformations and may not capture complex, high-order feature interactions under stringent parameter constraints. In contrast, parameterized quantum circuits (PQCs) […]

Reducing Maximum Subcircuits Depth in Quantum Circuit Cutting

Abstract: Noisy intermediate-scale quantum (NISQ) devices with limited qubit count and connectivity limit the scale of quantum circuits that can be executed. Circuit cutting methods simulate larger quantum computers by decomposing large circuits into small subcircuits that can be executed on NISQ hardware. Existing circuit cutting methods only consider the qubit count of the target […]

Quantum Subroutines in Branch-Price-and-Cut for Vehicle Routing

Abstract: Motivated by recent progress in quantum hardware and algorithms, researchers have developed quantum heuristics for optimization problems, aiming for advantages over classical methods. To date, quantum hardware is still error-prone and limited in size such that quantum heuristics cannot be scaled to relevant problem sizes and are often outperformed by their classical counterparts. Moreover, […]

Quantum Communication Complexity of Regularized Linear Regression Protocols

Abstract: Linear regression is fundamental to statistical analysis and machine learning, but its application to large-scale datasets necessitates distributed computing. The problem also arises in quantum computing, where handling extensive data requires distributed approaches. This paper investigates distributed linear regression in the quantum coordinator model. Building upon the distributed quantum least squares protocol developed by […]