A Complete Quantum Circuit to Solve the Information Set Decoding Problem

Author(s):  
Simone Perriello ◽  
Alessandro Barenghi ◽  
Gerardo Pelosi
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Israel F. Araujo ◽  
Daniel K. Park ◽  
Francesco Petruccione ◽  
Adenilton J. da Silva

AbstractAdvantages in several fields of research and industry are expected with the rise of quantum computers. However, the computational cost to load classical data in quantum computers can impose restrictions on possible quantum speedups. Known algorithms to create arbitrary quantum states require quantum circuits with depth O(N) to load an N-dimensional vector. Here, we show that it is possible to load an N-dimensional vector with exponential time advantage using a quantum circuit with polylogarithmic depth and entangled information in ancillary qubits. Results show that we can efficiently load data in quantum devices using a divide-and-conquer strategy to exchange computational time for space. We demonstrate a proof of concept on a real quantum device and present two applications for quantum machine learning. We expect that this new loading strategy allows the quantum speedup of tasks that require to load a significant volume of information to quantum devices.


2021 ◽  
Vol 20 (7) ◽  
Author(s):  
Ismail Ghodsollahee ◽  
Zohreh Davarzani ◽  
Mariam Zomorodi ◽  
Paweł Pławiak ◽  
Monireh Houshmand ◽  
...  

AbstractAs quantum computation grows, the number of qubits involved in a given quantum computer increases. But due to the physical limitations in the number of qubits of a single quantum device, the computation should be performed in a distributed system. In this paper, a new model of quantum computation based on the matrix representation of quantum circuits is proposed. Then, using this model, we propose a novel approach for reducing the number of teleportations in a distributed quantum circuit. The proposed method consists of two phases: the pre-processing phase and the optimization phase. In the pre-processing phase, it considers the bi-partitioning of quantum circuits by Non-Dominated Sorting Genetic Algorithm (NSGA-III) to minimize the number of global gates and to distribute the quantum circuit into two balanced parts with equal number of qubits and minimum number of global gates. In the optimization phase, two heuristics named Heuristic I and Heuristic II are proposed to optimize the number of teleportations according to the partitioning obtained from the pre-processing phase. Finally, the proposed approach is evaluated on many benchmark quantum circuits. The results of these evaluations show an average of 22.16% improvement in the teleportation cost of the proposed approach compared to the existing works in the literature.


Medical Care ◽  
2010 ◽  
Vol 48 (3) ◽  
pp. 217-223 ◽  
Author(s):  
Jeffrey S. Harman ◽  
Sarah Hudson Scholle ◽  
Judy H. Ng ◽  
L Gregory Pawlson ◽  
Russell E. Mardon ◽  
...  

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 255-255
Author(s):  
Jo-Ana Chase ◽  
Lizyeka Jordan ◽  
Christina Whitehouse ◽  
Kathryn Bowles

Abstract Sepsis survivorship is associated with cognitive decline and complex post-acute care needs. Family caregivers may be unprepared to manage these needs, resulting in decline or no improvement in patient outcomes. Using a national dataset of Medicare beneficiaries who were discharged from the hospital for sepsis and received post-acute HHC between 2013 and 2014 (n=165,228), we examined the relationship between unmet caregiving needs and improvement or decline in cognitive functioning. Multivariate logistic regression was used to determine associations between unmet caregiving needs at the start of HHC and changes in cognitive functioning. Unmet caregiving needs included seven items from the start of care Outcome and Assessment Information Set (OASIS). Changes in cognitive functioning were measured using the start of care and discharge OASIS assessments. Twenty-four percent of patients either declined or did not improve in cognitive functioning from HHC admission to discharge, with variation seen by unmet need type. Sepsis survivors with unmet caregiving needs for activities of daily living assistance (OR 1.05, 95% CI 1.01, 1.09), medication assistance (OR 1.06, 95% CI 1.02,1.10), and supervision and safety assistance (OR 1.110, 95% CI 1.06,1.16) were more likely to decline or not improve in cognitive functioning, even after accounting for clinical and demographic characteristics. Older sepsis survivors with both cognitive impairment and unmet caregiving needs in the post-acute HHC setting are at high-risk for worsening cognition. Alerting the care team of cognitively impaired sepsis survivors with unmet caregiving needs may trigger evidence-based strategies to enhance caregiver training and reduce unmet caregiving needs.


2021 ◽  
Vol 2 (1) ◽  
pp. 1-35
Author(s):  
Adrien Suau ◽  
Gabriel Staffelbach ◽  
Henri Calandra

In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some PDE can be solved on a quantum computer, even if the direct quantum algorithm chosen will require error-corrected quantum chips, which are not believed to be available in the short-term.


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