Em um novo estudo na Nature, os pesquisadores revelam um algoritmo que reduz os erros estatasticos, ou ruado, produzidos por bits qua¢nticos, ou qubits, ao processar equaa§aµes químicas.
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)
O algoritmo habrido usa um computador cla¡ssico e qua¢ntico para calcular a energia do estado fundamental. Isso ajudara¡ os pesquisadores a desenvolver novos materiais para diferentes aplicações, incluindo metas de sustentabilidade. Crédito: Nicoletta Barolini
Os computadores qua¢nticos estãoficando maiores, mas ainda hápoucas maneiras prática s de aproveitar seu poder computacional extra. Para superar esse obsta¡culo, os pesquisadores estãoprojetando algoritmos para facilitar a transição dos computadores cla¡ssicos para os qua¢nticos. Em um novo estudo na Nature, os pesquisadores revelam um algoritmo que reduz os erros estatasticos, ou ruado, produzidos por bits qua¢nticos, ou qubits, ao processar equações químicas.
Desenvolvido pelo professor de química da Columbia David Reichman e pelo pa³s-doutorado Joonho Lee com pesquisadores do Google Quantum AI, o algoritmo usa até16 qubits no Sycamore, o computador de 53 qubits do Google , para calcular a energia do estado fundamental, o estado de energia mais baixo de uma molanãcula. "Estes são os maiores ca¡lculos de química qua¢ntica que já foram feitos em um dispositivo qua¢ntico real", disse Reichman.
A capacidade de calcular com precisão a energia do estado fundamental permitira¡ que os químicos desenvolvam novos materiais, disse Lee, que também épesquisador visitante do Google Quantum AI. O algoritmo pode ser usado para projetar materiais para acelerar a fixação de nitrogaªnio para agricultura e hidra³lise para produzir energia limpa , entre outras metas de sustentabilidade, disse ele.
O algoritmo usa um Monte Carlo qua¢ntico, um sistema de manãtodos para calcular probabilidades quando háum grande número de varia¡veis ​​aleata³rias e desconhecidas em jogo, como em um jogo de roleta. Aqui, os pesquisadores usaram seu algoritmo para determinar a energia do estado fundamental de três molanãculas: heliocadio (H4), usando oito qubits para o ca¡lculo; nitrogaªnio molecular (N 2 ), usando 12 qubits; e diamante sãolido, usando 16 qubits.
A energia do estado fundamental éinfluenciada por varia¡veis ​​como o número de elanãtrons em uma molanãcula, a direção na qual eles giram e os caminhos que percorrem ao orbitar um núcleo. Essa energia eletra´nica écodificada na equação de Schraµdinger. Resolver a equação em um computador cla¡ssico torna-se exponencialmente mais difacil a medida que as moléculas aumentam, embora os manãtodos para estimar a solução tenham tornado o processo mais fa¡cil. Como os computadores qua¢nticos podem contornar o problema de escala exponencial tem sido uma questãoem aberto no campo.
Em princapio, os computadores qua¢nticos devem ser capazes de lidar com ca¡lculos exponencialmente maiores e mais complexos, como os necessa¡rios para resolver a equação de Schraµdinger, porque os qubits que os compõem aproveitam os estados qua¢nticos. Ao contra¡rio dos dagitos binários, ou bits, compostos de uns e zeros, os qubits podem existir em dois estados simultaneamente. Os qubits, no entanto, são fra¡geis e propensos a erros: quanto mais qubits usados, menos precisa seráa resposta final. O algoritmo de Lee aproveita o poder combinado dos computadores cla¡ssicos e qua¢nticos para resolver equações químicas com mais eficiência, minimizando os erros do computador qua¢ntico.
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"a‰ o melhor dos dois mundos", disse Lee. “Aproveitamos ferramentas que já tanhamos, bem como ferramentas consideradas de última geração na ciência da informação qua¢ntica para refinar a química computacional qua¢nticaâ€.
Um computador cla¡ssico pode lidar com a maior parte da simulação qua¢ntica de Monte Carlo de Lee. Sycamore salta para o último e mais complexo passo computacionalmente: o ca¡lculo da sobreposição entre uma função de onda de teste - um palpite na descrição matemática da energia do estado fundamental que pode ser implementada pelo computador qua¢ntico - e uma função de onda de amostra, que faz parte do processo estatastico de Monte Carlo. Essa sobreposição fornece um conjunto de restrições, conhecido como condição de contorno, para a amostragem de Monte Carlo, que garante a eficiência estatastica do ca¡lculo (para mais detalhes sobre a matemática, veja o webinar de Lee ).
O registro anterior para resolver a energia do estado fundamental usava 12 qubits e um manãtodo chamado de autosolver qua¢ntico variacional, ou VQE. Mas o VQE ignorou os efeitos da interação dos elanãtrons, uma varia¡vel importante no ca¡lculo da energia do estado fundamental que o algoritmo qua¢ntico de Monte Carlo de Lee agora inclui. A adição de técnicas de correlação virtual de computadores cla¡ssicos pode ajudar os químicos a lidar com moléculas ainda maiores, disse Lee.
Os ca¡lculos habridos cla¡ssico-qua¢nticos neste novo trabalho foram considerados tão precisos quanto alguns dos melhores manãtodos cla¡ssicos. Isso sugere que os problemas podem ser resolvidos com mais precisão e/ou rapidez com um computador qua¢ntico do que sem osum marco importante para a computação qua¢ntica. Lee e seus colegas continuara£o a ajustar seu algoritmo para torna¡-lo mais eficiente, enquanto os engenheiros trabalham para construir um hardware qua¢ntico melhor.
"A viabilidade de resolver problemas químicos maiores e mais desafiadores são aumentara¡ com o tempo", disse Lee. “Isso nos da¡ esperana§a de que as tecnologias qua¢nticas que estãosendo desenvolvidas sejam praticamente aºteisâ€.