62 citations · 136 across the 18 of their papers we have counts for
18 papers
Robust Structure Learning of -local Lindbladians
Tim Möbus, Thiago Bergamaschi, Daniel Stilck França +1
We present an efficient protocol for learning an unknown -local Lindblad generator on qubits using only product-state preparations, short-time evolution, and single-qubit Pa…
Pairwise Liouvillian learning from randomized measurements: practical aspects and guidelines for operating the protocol in large-scale experiments
William T. Lam, Manoj K. Joshi, Daniel Stilck França +1
We review and numerically study a protocol for Liouvillian learning based on randomized Pauli states and measurements. In particular, in the two-body, long-range interactions, and…
Hamiltonian dynamics from pure dissipation
Zhong-Xia Shang, Daniel Stilck França
The fundamental difference between closed and open quantum dynamics lies in their environmental interaction: closed systems are perfectly isolated and evolve reversibly under unita…
Demonstrating and Benchmarking Classical Shadows for Lindblad Tomography
Rune Thinggaard Birke, Johann Bock Severin, Malthe A. Marciniak +15
Spurious couplings and decoherence degrade the performance of solid-state quantum processors, demanding careful design, calibration, and mitigation protocols. These strategies ofte…
Polynomial-time thermalization and Gibbs sampling from system-bath couplings
Samuel Slezak, Matteo Scandi, Álvaro M. Alhambra +2
Many physical phenomena, including thermalization in open quantum systems and quantum Gibbs sampling, are modeled by Lindbladians approximating a system weakly coupled to a bath. U…
Quantum speed-ups for solving semidefinite relaxations of polynomial optimization
Daniel Stilck França, Ngoc Hoang Anh Mai
We study quantum algorithms for approximating Lasserre's hierarchy values for polynomial optimization. Let be real polynomials in variables and the…
Learning and certification of local time-dependent quantum dynamics and noise
Daniel Stilck França, Tim Möbus, Cambyse Rouzé +1
Hamiltonian learning protocols are becoming valuable tools for benchmarking and verifying quantum computers and simulators, yet few rigorous protocols address explicitly time-depen…
Exponential Speed-ups for Structured Goemans-Williamson relaxations via Quantum Gibbs States and Pauli Sparsity
Haomu Yuan, Daniel Stilck França, Ilia Luchnikov +3
Quadratic Unconstrained Binary Optimization (QUBO) problems are prevalent in various applications and are known to be NP-hard. The seminal work of Goemans and Williamson introduced…
Average Contraction Coefficients of Quantum Channels
Ruben Ibarrondo, Daniel Stilck França
The data-processing inequality ensures quantum channels reduce state distinguishability, with contraction coefficients quantifying optimal bounds. However, these can be overly opti…
Compilation-informed probabilistic logical-error cancellation
Giancarlo Camilo, Thiago O. Maciel, Allan Tosta +4
The potential of quantum computers to outperform classical ones in practically useful tasks remains challenging in the near term due to scaling limitations and high error rates of…
Efficient simulation of parametrized quantum circuits under non-unital noise through Pauli backpropagation
Victor Martinez, Armando Angrisani, Ekaterina Pankovets +2
As quantum devices continue to grow in size but remain affected by noise, it is crucial to determine when and how they can outperform classical computers on practical tasks. A cent…
Noise-induced shallow circuits and absence of barren plateaus
Antonio Anna Mele, Armando Angrisani, Soumik Ghosh +4
Motivated by realistic hardware considerations of the pre-fault-tolerant era, we comprehensively study the impact of uncorrected noise on quantum circuits. We first show that in th…
Provably Efficient Learning of Phases of Matter via Dissipative Evolutions
Emilio Onorati, Cambyse Rouzé, Daniel Stilck França +1
The combination of quantum many-body and machine learning techniques has recently proved to be a fertile ground for new developments in quantum computing. Several works have shown…
Quantum metrology in the finite-sample regime
Johannes Jakob Meyer, Sumeet Khatri, Daniel Stilck França +2
In quantum metrology, one of the major applications of quantum technologies, the ultimate precision of estimating an unknown parameter is often stated in terms of the Cramér-Rao bo…
Efficient learning of the structure and parameters of local Pauli noise channels
Cambyse Rouzé, Daniel Stilck França
The unavoidable presence of noise is a crucial roadblock for the development of large-scale quantum computers and the ability to characterize quantum noise reliably and efficiently…
Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision
Guoming Wang, Daniel Stilck França, Ruizhe Zhang +2
A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods. The current understanding…
Noise-robust exploration of many-body quantum states on near-term quantum devices
Johannes Borregaard, Matthias Christandl, Daniel Stilck França
We describe a resource-efficient approach to studying many-body quantum states on noisy, intermediate-scale quantum devices. We employ a sequential generation model that allows us…
Approximate Randomized Benchmarking for Finite Groups
Daniel Stilck França, Anna-Lena Hashagen
We investigate randomized benchmarking in a general setting with quantum gates that form a representation, not necessarily an irreducible one, of a finite group. We derive an estim…