Modeling noise in superconducting qubits: experiments on an IBM quantum processor and numerical simulations

Eva Gurra, Eric A. Berg, Elizabeth R. Doss +3 more

Siddhartha Patra, Saeed S. Jahromi, Sukhbinder Singh +1 more

We show how quantum-inspired 2D tensor networks can be used to efficiently and accurately simulate the largest quantum processors from IBM, namely Eagle (127 qubits), Osprey (433 qubits), and Condor (1121 qubits). We simulate the dynamics of a complex quantum many-body system—specifically, the kicked Ising experiment considered recently by IBM in Y. Kim , —using graph-based projected entangled pair states (gPEPS), which was proposed by some of us in . Our results show that simple tensor updates are already sufficient to achieve very large unprecedented accuracy with remarkably low computational resources for this model. Apart from simulating the original experiment for 127 qubits, we also extend our results to 433 and 1121 qubits, and for evolution times around eight times longer, thus setting a benchmark for the newest IBM quantum machines. We also report accurate simulations for infinitely many qubits. Our results show that gPEPS are a natural tool to efficiently simulate quantum computers with an underlying lattice-based qubit connectivity, such as all quantum processors based on superconducting qubits. Published by the American Physical Society 2024

PARK KUN HEE

Sumit Chongder

We experimentally study error mitigation and finite-shot sampling on superconducting quantum hardware under a constrained execution budget. The study combines calibration-aware qubit selection, circuit-depth scaling, zero-noise extrapolation, dynamical decoupling, readout-error mitigation, and repeated-shot estimation on an IBM Quantum processor. Experiments are organized across ideal simulation, noise-model simulation, and physical-device execution to separate sampling uncertainty from device-induced error. We investigate how mitigation performance changes with circuit depth, effective noise scale, qubit connectivity, and measurement budget, and quantify accuracy using expectation-value error, mean-squared error, statistical uncertainty, and mitigation gain. A fixed hardware-execution budget is used to evaluate shot allocation strategies and repeated measurements without relying on unlimited sampling. The resulting analysis provides a hardware-aware characterization of when mitigation improves expectation-value estimation and when finite-shot fluctuations offset the benefit of additional mitigation overhead. The implementation uses contemporary Qiskit and IBM Quantum Runtime workflows and is designed to provide reproducible experimental evidence for error-mitigation studies on current quantum processors.

Ayan Majumder, Santanu Mohapatra, Anil Kumar

A scheme for secure multiparty quantum summation was proposed by Run-hau Shi et al.,(SCIENTIFIC REPORTS, 6:19655, DOI:10.1038/srep19655). IBM Corporation has released a superconductivity based 5-qubit quantum computer named "Quantum Experience" and placed it on "cloud". In this paper we take advantage of the online availability of this real quantum processor(ibmqx2) and carry out the above protocol that has never been experimentally demonstrated earlier. Here, we set up experiments for secure quantum summation of one-qubit secret states . Besides, we propose a protocol for square and cubic summation and also simulate the proposed protocol for both cases. Experimental implementation of secure multiparty quantum summation protocol for two or more qubit secret state and the proposed protocol for square(and cubic) summation are not possible using the available 5-qubit quantum processor(ibmqx2). IBM has recently placed a 16-qubit quantum processor(ibmqx3) on the cloud but it is still not accessible for all users. We describe a simulation for two and three qubit secret state and proposed protocol for square(and cubic) summation using a simulator(Custom Topology) which is provided by IBM Corporation.

Abhinav Kandala