Quantum algorithms for approximate function loading

Loading classical data into quantum computers represents an essential stage in many relevant quantum algorithms, especially in the field of quantum machine learning. Therefore, the inefficiency of this loading process means a major bottleneck for the application of these algorithms. Here, we introduce two approximate quantum-state preparation methods inspired by the Grover-Rudolph algorithm, which partially solve the problem of loading real functions. Indeed, by allowing for an infidelity $\epsilon$ and under certain smoothness conditions, we prove that the complexity of Grover-Rudolph algorithm can be reduced from $\mathcal{O}(2^{n})$ to $\mathcal{O}(2^{k_0(\epsilon)})$, with $n$ the number of qubits and $k_0(\epsilon)$ asymptotically independent of $n$. This leads to a dramatic reduction in the number of required two-qubit gates. Aroused by this result, we also propose a variational algorithm capable of loading functions beyond the aforementioned smoothness conditions. Our variational ansatz is explicitly tailored to the landscape of the function, leading to a quasi-optimized number of hyperparameters. This allows us to achieve high fidelity in the loaded state with high speed convergence for the studied examples

Contaminación microbiana ruminal de la fibra en gramíneas y efectos sobre sus estimas de degradación ruminal in situ.

La concentración de las fracciones de fibra en las muestras de contenido digestivo se asume como real, al no existir componente endógena para estas fracciones. Sin embargo, si las técnicas de aislamiento de estos residuos no permiten una extracción completa de los microorganismos adherentes podrían ocurrir errores de cierta importancia. En este trabajo se examina la contaminación microbiana ocurrida en el rumen en la fibra neutro (FND) y ácido (FAD) detergente y sus fracciones nitrogenadas (N-FND y N-FAD) de henos de ray-grass (HRG) y avena (HA), así como el efecto de su corrección sobre su degradabilidad efectiva (DE)

Potential energy surfaces for singlet and triplet states of the LiH2+ system and quasi-classical trajectory cross sections for H + LiH+ and H+ + LiH

A new set of six accurate ab initio potential energy surfaces (PESs) is presentedfor the first three singlet and triplet states of LiH2+ (1,21A', 11A'', 1,23A', 13A'' states,where four of them are investigated for the first time), which have allowed new detailedstudies gaining a global view on this interesting system. These states are relevant for thestudy of the most important reactions of the lithium chemistry in the early universe.More than 45000 energy points were calculated using the multi-reference configurationinteraction level of theory using explicitly correlated methods (ic-MRCI-F12), and theresults obtained for each individual electronic state were fitted to an analytical function.Using quasiclassical trajectories and considering the initial diatomic fragment in theground rovibrational state, we have determined the integral cross sections for the H +LiH+(X2+, C2) and H+ + LiH(X1+, B1) reactions. In these calculations all availablereaction channels were considered: the chemically most important H or H+transfer/abstraction as well as atom exchange and collision induced dissociation for upto 1.0 eV of collision energ

The impact of financial crisis and austerity policies in Andalusia, Spain: disentangling the mechanisms of social inequalities in health through the perceptions and experiences of experts and the general population

Background: Andalusia has been one of the regions most damaged by the economic crisis in Spain. A qualitative study of the effects of the economic crisis and austerity policies in this region has been conducted within the framework of the IMPACT-A project. This research seeks to analyse the perceived impact of the crisis upon the health of the Andalusian population through the first-hand discourses of professionals from the health and social sectors on the one hand, and citizens of different socioeconomic status (SES) on the other. Methods: A total of five focus groups and ten semi-structured interviews were conducted and analysed following an inductive process based on Grounded Theory (GT). Results: Our results show a general perception among professionals: the financial crisis has either directly or indirectly affected population health in Andalusia, though mostly impacting low-income individuals who were already at risk of social exclusion. Professionals’ perceptions have been confirmed through the discourses of citizens of a lower SES, which differ from those of middle and upper SES. Conclusion: Findings reveal some of the most salient consequences on the socially vulnerable groups and people at risk of social exclusion. In particular, our study highlights the importance of addressing three areas of priority action: mental health, unmet (basic and medical) needs, and decline in the health system

Efficient amplitude encoding of polynomial functions into quantum computers

Loading functions into quantum computers represents an essential step in several quantum algorithms, such as in the resolution of partial derivative equations. Therefore, the inefficiency of this process leads to a major bottleneck for the application of these algorithms. Here, we present and compare two efficient methods for the amplitude encoding of real polynomial functions. The first one relies on the matrix product state representation, where we study and benchmark the approximations of the target state when the bond dimension is assumed to be small. The second algorithm combines two subroutines, initially we encode the linear function into the quantum registers with a swallow sequence of multi-controlled gates that loads its Hadamard-Walsh series expansion, followed by the inverse discrete Hadamard-Walsh transform. Then, we use this construction as a building block to achieve a $\mathcal{O}(n)$ block encoding of the amplitudes corresponding to the linear function and apply the quantum singular value transformation that implements the corresponding polynomial transformation to the block encoding of the amplitudes. Additionally, we explore how truncating the Hadamard-Walsh series of the linear function affects the final fidelity of the target state, reporting high fidelities with small resources

Towards Prediction of Financial Crashes with a D-Wave Quantum Computer

Prediction of financial crashes in a complex financial network is known to be an NP-hard problem, i.e., a problem which cannot be solved efficiently with a classical computer. We experimentally explore a novel approach to this problem by using a D-Wave quantum computer to obtain financial equilibrium more efficiently. To be specific, the equilibrium condition of a nonlinear financial model is embedded into a higher-order unconstrained binary optimization (HUBO) problem, which is then transformed to a spin-$1/2$ Hamiltonian with at most two-qubit interactions. The problem is thus equivalent to finding the ground state of an interacting spin Hamiltonian, which can be approximated with a quantum annealer. Our experiment paves the way to study quantitative macroeconomics, enlarging the number of problems that can be handled by current quantum computers

Quantum approximated cloning-assisted density matrix exponentiation

Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the embedding techniques based on Hamiltonian simulation techniques enable the loading of matrices into quantum computers. A representative example of these methods is the Lloyd-Mohseni-Rebentrost protocol, which efficiently implements matrix exponentiation when multiple copies of a quantum state are available. However, this is a quite ideal set up, and in a realistic scenario, the copies are limited and the non-cloning theorem prevents from producing more exact copies in order to increase the accuracy of the protocol. Here, we propose a method to circumvent this limitation by introducing imperfect quantum copies that significantly enhance the performance of previous proposals

A proposal for pellet production from residual woody biomass in the island of Majorca (Spain)

The use of residual biomass for energy purposes is of great interest in isolated areas like Majorca for waste reduction, energy sufficiency and renewable energies development. In addition, densification processes lead to easy-to-automate solid biofuels which additionally have higher energy density. The present study aims at (i) the estimation of the potential of residual biomass from woody crops as well as from agri-food and wood industries in Majorca, and (ii) the analysis of the optimal location of potential pellet plants by means of a GIS approach (location-allocation analysis) and a cost evaluation of the pellets production chain. The residual biomass potential from woody crops in Majorca Island was estimated at 35,874 metric tons dry matter (t DM) per year, while the wood and agri-food industries produced annually 21,494 t DM and 2717 t DM, respectively. Thus, there would be enough resource available for the installation of 10 pellet plants of 6400 t·year−1 capacity. These plants were optimally located throughout the island of Mallorca with a maximum threshold distance of 28 km for biomass transport from the production points. Values found for the biomass cost at the pellet plant ranged between 57.1 €·t−1 and 63.4 €·t−1 for biomass transport distance of 10 and 28 km. The cost of pelleting amounted to 56.7 €·t−1; adding the concepts of business fee, pellet transport and profit margin (15%), the total cost of pelleting was estimated at 116.6 €·t−1. The present study provides a proposal for pellet production from residual woody biomass that would supply up to 2.8% of the primary energy consumed by the domestic and services sector in the Balearic Islands

Cost-Effectiveness of Therapeutic Drug Monitoring of Anti-TNF Therapy in Inflammatory Bowel Disease: A Systematic Review

Infliximab and adalimumab are monoclonal antibodies against tumor necrosis factor (anti-TNF) used to manage inflammatory bowel disease (IBD). Therapeutic Drug Monitoring (TDM) has been proven to prevent immunogenicity, to achieve better long-term clinical results and to save costs in IBD treatment. The aim of this study was to conduct a systematic review on cost-effectiveness analyses of studies that apply TDM of anti-TNF in IBD and to provide a critical analysis of the best scientific knowledge available in the literature. The quality of the included studies was assessed using Consolidated Health Economic Evaluation Reporting Standards (CHEERS). Cost-effectiveness of the TDM strategies was presented as total costs, cost savings, quality-adjusted life-years (QALY) and incremental cost-effectiveness ratio (ICER). Thirteen studies that examined the health economics of TDM of anti-TNF in IBD from 2013 to 2021 were included. Eight of them (61.5%) achieved a score between 17 and 23 on the CHEERS checklist. The comparison between the TDM strategy and an empirical strategy was cost saving. The ICER between reactive TDM and an empirical strategy was dominated (favorable) by reactive TDM, whereas the ICER value for proactive TDM compared to an empirical strategy ranged from EUR 56,845 to 3,901,554. This systematic review demonstrated that a TDM strategy is cost-effective or cost-saving in IBD.S.M.-M. received a predoctoral fellowship from Miguel Hernandez University (“Ayudas a la contratación de personal investigador en formación 2021”).S