Efficient quantum error correction and fault-tolerant quantum computing require scalable, high-fidelity long-range connectivity. In neutral-atom quantum computers, this is commonly achieved through atom transport, but shuttling introduces latency and motional heating that worsen with system size. Here, we introduce a…
Matrix Product State (MPS) methods are among the most effective approaches for the classical simulation of quantum circuits, but their practical performance depends strongly on simulator hyperparameters, and default settings are often suboptimal. In this work, we propose a two-stage…
We provide a pre-obfuscation circuit-level implementation of an efficient one shot signature scheme, which has known applications to delegated signatures, secured token transfer, and publicly verifiable randomness. The algorithm consists of two stages: a key generation stage where a classical…
Atom loss is a dominant error source in neutral-atom quantum processors, yet its correlated structure remains largely unexploited by existing quantum error correction decoders. We analyze the performance of the surface code equipped with teleportation-based loss-detection units for neutral-atom quantum…
Error mitigation (EM) methods are crucial for obtaining reliable results in the realm of noisy intermediate-scale quantum (NISQ) computers, where noise significantly impacts output accuracy. Some EM protocols are particularly efficient for specific types of noise. Yet the noise in…
Classical quantum emulators are key tools for algorithm design, error correction, and noise mitigation. They rely on a variety of simulation methods such as statevector, tensor networks, matrix product states, decision diagrams and others. Their performance depends not only on…
Quantum computing relies on quantum error correction for high-fidelity logical operations, but scaling to achieve near-term quantum utility is highly resource-intensive. High-rate quantum LDPC codes can reduce error correction overhead, yet realizing high-rate fault-tolerant computation with these codes remains a…
Classical simulation of molecular systems is limited by exponential scaling, a hurdle quantum algorithms like Variational Quantum Eigensolvers (VQEs) aim to overcome. Although ADAPT-VQE enhances VQEs by dynamically building ansätze, it can remain computationally intensive. This work presents K-ADAPT-VQE, which…
Evaluating quantum algorithms at utility-scale—involving more than 100 qubits—is a key step toward advancing real-world applications of quantum computing. In this study, we benchmark seven state-of-the-art quantum emulators employing techniques such as tensor networks, matrix product states (MPS), decision diagrams,…
The dynamics of many-body quantum states in open systems is commonly numerically simulated by unraveling the density matrix into pure-state trajectories. In this work, we introduce a new unraveling strategy that can adaptively minimize the averaged entanglement in the trajectory…
A key requirement for quantum technologies based on atoms, ions, and molecules is the ability to realize precise phase- and amplitude-controlled quantum operations via coherent laser pulses. However, for generating pulses on the submicrosecond timescale, the characteristics of the optical…
We present a quantum algorithm for factoring products of prime numbers which exploits Grover search to factor any n-bit biprime using 2n-5 qubits or less. The algorithm doesn't depend on any properties of the number to be factored, has guaranteed…