arXiv subjects

Anurag Saha Roy

Publications and source records attributed to Anurag Saha Roy.

4 recordsLinked to original sources

arXiv2026

Effect of isotropic errors on the complexity of Grover's algorithm

Isotropic errors have been shown to be immune to conventional error correction techniques. While general theoretical frameworks have been proposed to model such errors, there have been no studies so far analysing their concrete impact on practical use-cases. Here we explore the effect of isotropic errors on the complexity of Grover's search algorithm through numerical simulations, with an analysis of the impact on the algorithm's performance and success probability. The results provide insights into the robustness of Grover's algorithm against isotropic errors, highlighting potential challenges for implementations on noisy quantum hardware. All results presented here are obtained through numerical simulations using the open-source python library \texttt{isotropic} developed as part of this work. The source code, numerical simulations and documentation for the library are available online at https://www.github.com/lazyoracle/isotropic-error-analysis .

quant-ph↗

arXiv2025

Software tool-set for automated quantum system identification and device bring up

We present a software tool-set which combines the theoretical, optimal control view of quantum devices with the practical operation and characterization tasks required for quantum computing. In the same framework, we perform model-based simulations to create control schemes, calibrate these controls in a closed-loop with the device (or in this demo \textemdash by emulating the experimental process) and finally improve the system model through minimization of the mismatch between simulation and experiment, resulting in a digital twin of the device. The model based simulator is implemented using TensorFlow, for numeric efficiency, scalability and to make use of automatic differentiation, which enables gradient-based optimization for arbitrary models and control schemes. Optimizations are carried out with a collection of state-of-the-art algorithms originated in the field of machine learning. All of this comes with a user-friendly Qiskit interface, which allows end-users to easily simulate their quantum circuits on a high-fidelity differentiable physics simulator.

quant-ph↗

arXiv2024

Open Hardware Solutions in Quantum Technology

Quantum technologies such as communications, computing, and sensing offer vast opportunities for advanced research and development. While an open-source ethos currently exists within some quantum technologies, especially in quantum computer programming, we argue that there are additional advantages in developing open quantum hardware (OQH). Open quantum hardware encompasses open-source software for the control of quantum devices in labs, blueprints and open-source toolkits for chip design and other hardware components, as well as openly-accessible testbeds and facilities that allow cloud-access to a wider scientific community. We provide an overview of current projects in the OQH ecosystem, identify gaps, and make recommendations on how to close them today. More open quantum hardware would accelerate technology transfer to and growth of the quantum industry and increase accessibility in science.

physics.app-ph↗

arXiv2022

Integrated tool-set for Control, Calibration and Characterization of quantum devices applied to superconducting qubits

Efforts to scale-up quantum computation have reached a point where the principal limiting factor is not the number of qubits, but the entangling gate infidelity. However, the highly detailed system characterization required to understand the underlying error sources is an arduous process and impractical with increasing chip size. Open-loop optimal control techniques allow for the improvement of gates but are limited by the models they are based on. To rectify the situation, we provide an integrated open-source tool-set for Control, Calibration and Characterization, capable of open-loop pulse optimization, model-free calibration, model fitting and refinement. We present a methodology to combine these tools to find a quantitatively accurate system model, high-fidelity gates and an approximate error budget, all based on a high-performance, feature-rich simulator. We illustrate our methods using simulated fixed-frequency superconducting qubits for which we learn model parameters with less than 1% error and derive a coherence limited cross-resonance (CR) gate that achieves 99.6% fidelity without need for calibration.

quant-ph↗