When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...
In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...
WEST LAFAYETTE, Ind. — Quantum information processing promises to be much faster and more secure than what today’s supercomputers can achieve, but doesn’t exist yet because its building blocks, qubits ...
Microchips power almost every modern device — phones, laptops and even fridges. But behind the scenes, making them is a complex process. But researchers say they have found a way to tap into the power ...
This illustration draws a parallel between quantum state tomography and natural language modeling. In quantum tomography, structured measurements yield probability outcomes that are aggregated to ...
Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...
This diagram illustrates how the team reduces quantum circuit complexity in machine learning using three encoding methods—variational, genetic, and matrix product state algorithms. All methods ...
Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization by rapidly predicting molecular interactions and properties. For instance, ...
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