Quantum machines, grounded in the principles of quantum mechanics, harness the extraordinary computational power derived from quantum bits (qubits), contrasting with classical machines reliant on classical bits. Qubits, distinguished by properties like superposition and entanglement, empower quantum algorithms to solve intricate problems with exponential speedup. Quantum states, fundamental to quantum mechanics, serve as descriptors for quantum systems, laying the foundation for subsequent calculations. Quantum gates, unitary operators manipulating qubits, are pivotal in quantum computing, extending beyond single-particle systems to encompass multi-particle scenarios. This flexibility finds applications in quantum simulation, optimization, cryptography, machine learning, and more. Quantum computing’s potential to revolutionize fields arises from its ability to tackle computationally intractable problems. Applications span quantum simulation, optimization, cryptography, machine learning, chemistry, materials science, financial modeling, and transportation. quantum protocols, including communication and cryptography, leverage unique quantum properties. Prominent quantum algorithms, such as Deutsch-Jozsa, Bernstein-Vazirani, Grover’s, and Shor’s, exploit qubit features for efficient problem-solving. These algorithms harness superposition and entanglement, allowing parallel calculations across multiple possibilities. In the landscape of quantum computing, the interplay of quantum bits, gates, states, and algorithms showcases the potential for transformative advances in computation.

Chapman & Hall/CRC eBooksOct 1, 20240 citations

Exponentially-enhanced quantum sensing with many-body phase transitions

Saubhik Sarkar, Abolfazl Bayat, Sougato Bose +1 more

Quantum sensors based on critical many-body systems are known to exhibit enhanced sensing capability. Such enhancements typically scale algebraically with the probe size. Going beyond algebraic advantage and reaching exponential scaling has remained elusive when all the resources, such as the preparation time, are taken into account. In this work, we show that many-body systems featuring first order quantum phase transitions can indeed achieve exponential scaling of sensitivity, thanks to their exponential energy gap closing. Remarkably, even after considering the preparation time using local adiabatic driving, the exponential scaling is sustained. Our results are demonstrated through comprehensive analysis of three paradigmatic models exhibiting first order phase transitions, namely Grover, p-spin, and biclique models. We show that this scaling survives moderate decoherence during state preparation and also can be optimally measured in experimentally available basis. Our findings comply with the fundamental bounds and we show that one can harness the exponential advantage through an adaptive strategy even away from the phase transition point.

arXiv:2410.11426Nature CommunicationsJun 3, 202521 citations