Uma abordagem teórica potencialmente revolucionária para o hardware de computação quântica evita grande parte da complexidade problemática encontrada nos computadores quânticos atuais. A estratégia implementa um algoritmo...
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)
Caminhos da direção do campo magnético que muda adiabaticamente b( t )/|b( t )|. O spin-1 está inicialmente no autoestado de projeção zero ao longo do campo. Ele permanece no autoestado instantâneo de projeção zero durante o tempo de evolução até uma fase acumulada. (a) A fase geométrica ao longo do caminho C , onde o campo magnético inverte sua direção, é ?. Um caminho fechado não geraria fase Berry [15]. Portanto, a diferença de fase entre C + e C ? é ?. (b) As fases das trajetórias C ± e C 0 são, respectivamente, ? e zero. Crédito: Revisão Física A(2023). DOI: 10.1103/PhysRevA.108.022412
Uma abordagem teórica potencialmente revolucionária para o hardware de computação quântica evita grande parte da complexidade problemática encontrada nos computadores quânticos atuais. A estratégia implementa um algoritmo em interações quânticas naturais para processar uma variedade de problemas do mundo real mais rapidamente do que os computadores clássicos ou os computadores quânticos baseados em portas convencionais.
“Nossa descoberta elimina muitos requisitos desafiadores para hardware quântico”, disse Nikolai Sinitsyn, físico teórico do Laboratório Nacional de Los Alamos. Ele é co-autor de um artigo sobre a abordagem na revista Physical Review A . "Sistemas naturais, como os giros eletrônicos de defeitos no diamante, têm exatamente o tipo de interação necessária para nosso processo de computação ."
Sinitsyn disse que a equipe espera colaborar com físicos experimentais também em Los Alamos para demonstrar sua abordagem usando átomos ultrafrios. As tecnologias modernas em átomos ultrafrios são suficientemente avançadas para demonstrar tais cálculos com cerca de 40 a 60 qubits, disse ele, o que é suficiente para resolver muitos problemas atualmente não acessíveis pela computação clássica ou binária. Um qubit é a unidade básica de informação quântica, análoga a um bit na computação clássica familiar.
Qubits de vida mais longa
Em vez de configurar um sistema complexo de portas lógicas entre vários qubits que devem compartilhar o emaranhamento quântico , a nova estratégia usa um campo magnético simples para girar os qubits, como os spins dos elétrons, em um sistema natural. A evolução precisa dos estados de spin é tudo o que é necessário para implementar o algoritmo. Sinitsyn disse que a abordagem pode ser usada para resolver muitos problemas práticos propostos para computadores quânticos.
A computação quântica continua sendo um campo nascente prejudicado pela dificuldade de conectar qubits em longas cadeias de portas lógicas e manter o emaranhamento quântico necessário para a computação. O emaranhamento se desfaz em um processo conhecido como decoerência, pois os qubits emaranhados começam a interagir com o mundo fora do sistema quântico do computador, introduzindo erros. Isso acontece rapidamente, limitando o tempo de computação. A verdadeira correção de erros ainda não foi implementada no hardware quântico.
A nova abordagem depende do emaranhamento natural e não induzido, portanto, requer menos conexões entre os qubits. Isso reduz o impacto da decoerência. Assim, os qubits vivem por um tempo relativamente longo, disse Sinitsyn.
O artigo teórico da equipe de Los Alamos mostrou como a abordagem poderia resolver um problema de particionamento de números usando o algoritmo de Grover mais rapidamente do que os computadores quânticos existentes. Como um dos algoritmos quânticos mais conhecidos, ele permite pesquisas não estruturadas de grandes conjuntos de dados que consomem recursos de computação convencionais.
Por exemplo, disse Sinitsyn, o algoritmo de Grover pode ser usado para dividir o tempo de execução de tarefas igualmente entre dois computadores, para que terminem ao mesmo tempo, juntamente com outras tarefas práticas. O algoritmo é adequado para computadores quânticos idealizados e corrigidos por erros, embora seja difícil de implementar nas máquinas propensas a erros de hoje.
Protegido contra erros
Os computadores quânticos são construídos para realizar cálculos muito mais rápido do que qualquer dispositivo clássico pode fazer, mas têm sido extremamente difíceis de realizar até agora, disse Sinitsyn. Um computador quântico convencional implementa circuitos quânticos – sequências de operações elementares com diferentes pares de qubits.
Os teóricos de Los Alamos propuseram uma alternativa intrigante.
“Percebemos que, para muitos problemas computacionais famosos, é suficiente ter um sistema quântico com interações elementares, no qual apenas um único spin quântico – realizável com dois qubits – interage com o restante dos qubits computacionais”, disse Sinitsyn. “Então, um único pulso magnético que atua apenas no spin central implementa a parte mais complexa do algoritmo quântico de Grover ”. Chamada de oráculo de Grover, essa operação quântica aponta para a solução desejada.
“Nenhuma interação direta entre os qubits computacionais e nenhuma interação dependente do tempo com o spin central são necessárias no processo”, disse ele. Uma vez que os acoplamentos estáticos entre o spin central e os qubits são definidos, todo o cálculo consiste apenas na aplicação de pulsos de campo externo dependentes do tempo simples que giram os spins, disse ele.
É importante ressaltar que a equipe provou que tais operações podem ser feitas rapidamente. A equipe também descobriu que sua abordagem é protegida topologicamente. Ou seja, é robusto contra muitos erros na precisão dos campos de controle e outros parâmetros físicos mesmo sem correção de erros quânticos.
Mais informações: Nikolai A. Sinitsyn et al, Topologically protected Grover's oracle for the partition problem, Physical Review A (2023). DOI: 10.1103/PhysRevA.108.022412
Informações do periódico: Revisão Física A