5,928 research outputs found
Quantum many-body theory for electron spin decoherence in nanoscale nuclear spin baths
Decoherence of electron spins in nanoscale systems is important to quantum
technologies such as quantum information processing and magnetometry. It is
also an ideal model problem for studying the crossover between quantum and
classical phenomena. At low temperatures or in light-element materials where
the spin-orbit coupling is weak, the phonon scattering in nanostructures is
less important and the fluctuations of nuclear spins become the dominant
decoherence mechanism for electron spins. Since 1950s, semiclassical noise
theories have been developed for understanding electron spin decoherence. In
spin-based solid-state quantum technologies, the relevant systems are in the
nanometer scale and the nuclear spin baths are quantum objects which require a
quantum description. Recently, quantum pictures have been established to
understand the decoherence and quantum many-body theories have been developed
to quantitatively describe this phenomenon. Anomalous quantum effects have been
predicted and some have been experimentally confirmed. A systematically
truncated cluster correlation expansion theory has been developed to account
for the many-body correlations in nanoscale nuclear spin baths that are built
up during the electron spin decoherence. The theory has successfully predicted
and explained a number of experimental results in a wide range of physical
systems. In this review, we will cover these recent progresses. The limitations
of the present quantum many-body theories and possible directions for future
development will also be discussed.Comment: 44 pages, 29 figures, corrected many typos and added some reference
Unified theory of classical and quantum signal sensing with a qubit
Quantum sensing protocols typically uses a quantum sensor to sense classical
signals with the standard Ramsey inteferometry measurements. The classical
signals are often real numbers determining the sensor Hamiltonian. However, for
a senor embedded in a quantum environment, the signal to detect may be a
quantum operator on a target quantum system. There is still no systematic
method to detect such a quantum signal. Here we provide a general framework to
sense static quantum signals with a qubit sensor by the Ramsey interferometry
measurements, with the static classical signal sensing incorporated as a
special case. This framework is based on a novel approach to simultaneously
estimating the eigenvalues of the quantum signal operator with sequential
projective measurements of the sensor, which can extract useful information
about the target quantum system. The scheme can also be extended to sense ac
quantum signals with dynamical decoupling control of the sensor. As an example,
we show that a qubit sensor can simultaneously detect the individual coupling
strengths with multiple target qubits in a spin-star model.Comment: 6 pages, 2 figure
The classical nature of nuclear spin noise near clock transitions of Bi donors in silicon
Whether a quantum bath can be approximated as classical noise is a
fundamental issue in central spin decoherence and also of practical importance
in designing noise-resilient quantum control. Spin qubits based on bismuth
donors in silicon have tunable interactions with nuclear spin baths and are
first-order insensitive to magnetic noise at so-called clock-transitions (CTs).
This system is therefore ideal for studying the quantum/classical nature of
nuclear spin baths since the qubit-bath interaction strength determines the
back-action on the baths and hence the adequacy of a classical noise model. We
develop a Gaussian noise model with noise correlations determined by quantum
calculations and compare the classical noise approximation to the full quantum
bath theory. We experimentally test our model through dynamical decoupling
sequence of up to 128 pulses, finding good agreement with simulations and
measuring electron spin coherence times approaching one second - notably using
natural silicon. Our theoretical and experimental study demonstrates that the
noise from a nuclear spin bath is analogous to classical Gaussian noise if the
back-action of the qubit on the bath is small compared to the internal bath
dynamics, as is the case close to CTs. However, far from the CTs, the
back-action of the central spin on the bath is such that the quantum model is
required to accurately model spin decoherence.Comment: 5 pages, 3 figure
Uncovering many-body correlations in nanoscale nuclear spin baths by central spin decoherence
Many-body correlations can yield key insights into the nature of interacting
systems; however, detecting them is often very challenging in many-particle
physics, especially in nanoscale systems. Here, taking a phosphorus donor
electron spin in a natural-abundance 29Si nuclear spin bath as our model
system, we discover both theoretically and experimentally that many-body
correlations in nanoscale nuclear spin baths produce identifiable signatures in
the decoherence of the central spin under multiple-pulse dynamical decoupling
control. We find that when the number of decoupling -pulses is odd, central
spin decoherence is primarily driven by second-order nuclear spin correlations
(pairwise flip-flop processes). In contrast, when the number of -pulses is
even, fourth-order nuclear spin correlations (diagonal interaction renormalized
pairwise flip-flop processes) are principally responsible for the central spin
decoherence. Many-body correlations of different orders can thus be selectively
detected by central spin decoherence under different dynamical decoupling
controls, providing a useful approach to probing many-body processes in
nanoscale nuclear spin baths
Real Estate with AI:An agent based on LangChain
Recent developments in large language models (LLMs) have opened new avenues for the real estate industry. These models not only understand language but also function as intelligent agents, engaging with investors through open-ended conversations and influencing their decision-making. Utilizing unstructured data from a professional Danish real estate website, we developed a real estate AI agent in both English and Danish using LangChain and Pinecone. Through testing and evaluation, our agent has demonstrated superior professional and concise outputs compared to other LLMs like Doubao and ChatGPT 4 and shown excellent performance and effectiveness. Our work serves as a reference for AI in real estate investment-related research and proposes new solutions to the "unprofessional foundation " and " expensive consulting fee" problems encountered by ordinary investors in their investment decisions.</p
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