Zobrazeno 1 - 10
of 3 096
pro vyhledávání: '"Haddadi P"'
Autor:
Elghaayda, Samira, Ali, Asad, Al-Kuwari, Saif, Czerwinski, Artur, Mansour, Mostafa, Haddadi, Saeed
Finding a quantum battery model that demonstrates a quantum advantage while remaining feasible for experimental production is a considerable challenge. In this paper, we introduce a superconducting quantum battery (SQB) model that exhibits such an ad
Externí odkaz:
http://arxiv.org/abs/2411.19247
Autor:
Ali, Asad, Elghaayda, Samira, Al-Kuwari, Saif, Hussain, M. I., Rahim, M. T., Kuniyil, H., Seida, C., Allati, A. El, Mansour, M., Haddadi, Saeed
We investigate the performance of a novel model based on a one-dimensional (1D) spin-$1/2$ Heisenberg $XY-\Gamma(\gamma)$ quantum chain, also known as 1D Kitaev chain, as a working medium for a quantum battery (QB) in both closed and open system scen
Externí odkaz:
http://arxiv.org/abs/2411.14074
The integration of Inverter-Based Resource (IBR) model into phasor-domain short circuit (SC) solvers challenges their numerical stability. To address the challenge, this paper proposes a solver that improves numerical stability by employing the Newto
Externí odkaz:
http://arxiv.org/abs/2411.12006
The hotspots, which are typically found in nanogaps between metal structures, are critical for the enhancement of the electromagnetic field. Surface-enhanced Raman scattering (SERS), a technique known for its exceptional sensitivity and molecular det
Externí odkaz:
http://arxiv.org/abs/2411.03718
Autor:
Czerwinski, Artur, Haddadi, Saeed
Publikováno v:
Physics Letters A 526, 129972 (2024)
In this paper, we present a Quantum Key Distribution (QKD) protocol that accounts for fundamental practical challenges, including chromatic dispersion, time measurement uncertainty, and dark counts. Our analysis provides a comprehensive framework for
Externí odkaz:
http://arxiv.org/abs/2410.10953
Autor:
Cadet, Xavier F., Borovykh, Anastasia, Malekzadeh, Mohammad, Ahmadi-Abhari, Sara, Haddadi, Hamed
Machine unlearning (MU) aims to remove the influence of particular data points from the learnable parameters of a trained machine learning model. This is a crucial capability in light of data privacy requirements, trustworthiness, and safety in deplo
Externí odkaz:
http://arxiv.org/abs/2410.01276
Though there is much interest in fair AI systems, the problem of fairness noncompliance -- which concerns whether fair models are used in practice -- has received lesser attention. Zero-Knowledge Proofs of Fairness (ZKPoF) address fairness noncomplia
Externí odkaz:
http://arxiv.org/abs/2410.02777
Autor:
Hoffmann, Johannes, de Preville, Sophie, Eckmann, Bruno, Lin, Hung-Ju, Herzog, Benedikt, Haddadi, Kamel, Theron, Didier, Gramse, Georg, Richert, Damien, Moran-Meza, Jose, Piquemal, Francois
In this paper, a definition of the gain and added noise of impedance matching networks for scanning microwave microscopy is given. This definition can be used to compare different impedance matching techniques independently of the instrument used to
Externí odkaz:
http://arxiv.org/abs/2409.11207
We present Nebula, a system for differential private histogram estimation of data distributed among clients. Nebula enables clients to locally subsample and encode their data such that an untrusted server learns only data values that meet an aggregat
Externí odkaz:
http://arxiv.org/abs/2409.09676
We explore the quantum information resources within bipartite pure and mixed states of the quantum spin-1 Heisenberg dimer system, considering some interesting factors such as the $l_{1}$-norm of quantum coherence, relative coherence, entanglement, a
Externí odkaz:
http://arxiv.org/abs/2409.08082