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Quantifying mixed-state entanglement via partial transpose and realignment momentsquantum-computing

Quantifying mixed-state entanglement via partial transpose and realignment moments

AbstractEntanglement plays a crucial role in quantum information science and many-body physics, yet quantifying it in mixed quantum many-body systems has remained a notoriously difficult problem. Here, we introduce families of quantitative entanglement witnesses, constructed from partial transpose and realignment moments, which provide rigorous bounds on entanglement monotones as well as entanglement dimensionality. Our witnesses can be efficiently measured using SWAP tests or variants of Bell measurements, thus making them directly implementable on current hardware. Leveraging our witnesses, we present several novel results on entanglement properties of mixed states, both in quantum information and many-body physics. We develop efficient algorithms to test whether mixed states with bounded entropy have low or high entanglement, which previously was only possible for pure states. We also provide an efficient algorithm to test the Schmidt rank using only two-copy measurements, and the operator Schmidt rank using four-copy measurements. Further, our witnesses robustly certify the quantum circuit depth in the presence of noise, as well as the Schmidt rank of mixed states. Finally, we show that the entanglement phase diagram of Haar random states, quantified by the partial transpose negativity, can be fully established solely by computing our witness, a result that also applies to any state $4$-design. Our witnesses can also be efficiently computed for matrix product states, thus enabling the characterization of entanglement in extensive many-body systems. Finally, we make progress on the entanglement required for quantum cryptography, establishing rigorous limits on pseudoentanglement and pseudorandom density matrices with bounded entropy. Our work opens new avenues for quantifying entanglement in large and noisy quantum systems.Featured image: Quantitative entanglement witnesses provide experimentally accessible lower bounds on mixed-state entanglement (left), reveal

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Quantum phase estimation with optimal confidence interval using three control qubitsquantum-computing

Quantum phase estimation with optimal confidence interval using three control qubits

AbstractQuantum phase estimation is an important routine in many quantum algorithms, particularly for estimating the ground state energy in quantum chemistry simulations. This estimation involves applying powers of a unitary to the ground state, controlled by an auxiliary state prepared on a control register. In many applications the goal is to provide a confidence interval for the phase estimate, and optimal performance is provided by a discrete prolate spheroidal sequence. We show how to prepare the corresponding state in a far more efficient way than prior work. We find that a matrix product state representation with a bond dimension of 4 is sufficient to give a highly accurate approximation for all dimensions tested, up to $2^{24}$. This matrix product state can be efficiently prepared using a sequence of simple three-qubit operations. When the dimension is a power of 2, the phase estimation can be performed with only three qubits for the control register, making it suitable for early-generation fault-tolerant quantum computers with a limited number of logical qubits.Featured image: Overview of the phase estimation procedure. A matrix product representation is used to prepare a DPSS state, which provides the phase estimate with optimal confidence interval. By utilizing mid-circuit measurements, no more than three qubits are required for the control register to achieve any desired precision. Popular summaryQuantum phase estimation (QPE) is an important and widely used quantum algorithm. The purpose of QPE is to perform a measurement on a quantum computer that determines the value of a phase, corresponding to the eigenvalue of a unitary operator. Like any estimation procedure, QPE's output comes with a confidence interval, a range in which the true phase is likely to lie. In QPE, the size of the confidence interval is determined by a control state prepared on an auxiliary register. In the textbook version of QPE, the proposed control state is a uniform superpositi

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