43 citations · 56 across the 11 of their papers we have counts for
13 papers
Robustness of Quantum Signal Processing and Resource-aware Polynomial Design
Thiago O. Maciel, Giancarlo Camilo, Allan Tosta +3
Quantum signal processing (QSP) realizes operator functions through polynomial transformations of a finite degree. In addition to function approximation errors, realistic implement…
Exponential logical-error reduction in quantum memories via optimal syndrome-measurement timing
Tobias Haug, Kishor Bharti, Leandro Aolita
Syndrome-measurement timing is usually treated as a fixed clock cycle of a quantum error-correcting code. For quantum memories, however, the inter-round interval is itself an optim…
Machine-learned syndrome post-selection for reliable quantum error correction
Tobias Haug, Askery Canabarro, Leandro Aolita
Quantum error correction can be enhanced by post-selecting out runs that are likely to produce a logical failure, but the most accurate measures for that require costly decoder-lev…
Scalable Determination of Penalization Weights for Constrained Optimizations on Approximate Solvers
Edoardo Alessandroni, Sergi Ramos-Calderer, Michel Krispin +7
Quadratic unconstrained binary optimization (QUBO) provides problem formulations for various computational problems that can be solved with dedicated QUBO solvers, based on classic…
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…
Rise and fall of nonstabilizerness via random measurements
Annarita Scocco, Wai-Keong Mok, Leandro Aolita +2
We investigate the dynamics of nonstabilizerness - also known as `magic' - in monitored quantum circuits composed of random Clifford unitaries and local projective measurements. Fo…
Quantum optimization with exact geodesic transport
André J. Ferreira-Martins, Renato M. S. Farias, Giancarlo Camilo +6
We introduce an architecture for variational quantum algorithms that can be efficiently trained via parameter updates along exact geodesics on the Riemannian state manifold. This f…
A competitive NISQ and qubit-efficient solver for the LABS problem
Marco Sciorilli, Giancarlo Camilo, Thiago O. Maciel +3
Pauli Correlation Encoding (PCE) is as a qubit-efficient variational approach to combinatorial optimization problems. The method offers a polynomial reduction in qubit count and a…
Partition function estimation with a quantum coin toss
Thais de Lima Silva, Lucas Borges, Leandro Aolita
Estimating quantum partition functions is a critical task in a variety of fields. However, the problem is classically intractable in general due to the exponential scaling of the H…
Quantum computational complexity of matrix functions
Santiago Cifuentes, Samson Wang, Thais L. Silva +2
We investigate the dividing line between classical and quantum computational power in estimating properties of matrix functions. More precisely, we study the computational complexi…
Quantum encoder for fixed Hamming-weight subspaces
Renato M. S. Farias, Thiago O. Maciel, Giancarlo Camilo +3
We present an exact -qubit computational-basis amplitude encoder of real- or complex-valued data vectors of components into a subspace of fixed Hamming weight $…
Robust ultra-shallow shadows
Renato M. S. Farias, Raghavendra D. Peddinti, Ingo Roth +1
We present a robust shadow estimation protocol for wide classes of low-depth measurement circuits that mitigates noise as long as the effective measurement map including noise is l…
Towards large-scale quantum optimization solvers with few qubits
Marco Sciorilli, Lucas Borges, Taylor L. Patti +4
We introduce a variational quantum solver for combinatorial optimizations over binary variables using only qubits, with tunable . The number of parame…