141 research outputs found
Onsager's Scars in Disordered Spin Chains
We propose a class of non-integrable quantum spin chain models that exhibit
quantum many-body scars even in the presence of disorder. With the use of the
so-called Onsager symmetry, we construct such scarred models for arbitrary spin
quantum number . There are two types of scar states, namely, coherent
states associated to an Onsager-algebra element and one-magnon scar states.
While both of them are highly-excited states, they have area-law entanglement
and can be written as a matrix product state. Therefore, they explicitly
violate the eigenstate thermalization hypothesis. We also investigate the
dynamics of the fidelity and entanglement entropy for several initial states.
The results clearly show that the scar states are trapped in a perfectly
periodic orbit in the Hilbert subspace and never thermalize, whereas other
generic states do rapidly. To our knowledge, our model is the first explicit
example of disordered quantum many-body scarred model.Comment: 5+7 pages, 4+5 figure
Handbook for Efficiently Quantifying Robustness of Magic
The nonstabilizerness, or magic, is an essential quantum resource to perform
universal quantum computation. Robustness of magic (RoM) in particular
characterizes the degree of usefulness of a given quantum state for
non-Clifford operation. While the mathematical formalism of RoM can be given in
a concise manner, it is extremely challenging to determine the RoM in practice,
since it involves superexponentially many pure stabilizer states. In this work,
we present efficient novel algorithms to compute the RoM. The crucial technique
is a subroutine that achieves the remarkable features in calculation of
overlaps between pure stabilizer states: (i) the time complexity per each
stabilizer is reduced exponentially, (ii) the space complexity is reduced
superexponentially. Based on this subroutine, we present algorithms to compute
the RoM for arbitrary states up to qubits on a laptop, while brute-force
methods require a memory size of 86 TiB. As a byproduct, the proposed
subroutine allows us to simulate the stabilizer fidelity up to qubits,
for which naive methods require memory size of 86 PiB so that any
state-of-the-art classical computer cannot execute the computation. We further
propose novel algorithms that utilize the preknowledge on the structure of
target quantum state such as the permutation symmetry of disentanglement, and
numerically demonstrate our state-of-the-art results for copies of magic states
and partially disentangled quantum states. The series of algorithms constitute
a comprehensive ``handbook'' to scale up the computation of the RoM, and we
envision that the proposed technique applies to the computation of other
quantum resource measures as well.Comment: 16+12 pages, 8+1 figure
Universal cost bound of quantum error mitigation based on quantum estimation theory
We present a unified approach to analyzing the cost of various quantum error
mitigation methods on the basis of quantum estimation theory. By analyzing the
quantum Fisher information matrix of a virtual quantum circuit that effectively
represents the operations of quantum error mitigation methods, we derive for a
generic layered quantum circuit under a wide class of Markovian noise that,
unbiased estimation of an observable encounters an exponential growth with the
circuit depth in the lower bound on the measurement cost. Under the global
depolarizing noise, we in particular find that the bound can be asymptotically
saturated by merely rescaling the measurement results. Moreover, we prove for
random circuits with local noise that the cost grows exponentially also with
the qubit count. Our numerical simulations support the observation that, even
if the circuit has only linear connectivity, such as the brick-wall structure,
each noise channel converges to the global depolarizing channel with its
strength growing exponentially with the qubit count. This not only implies the
exponential growth of cost both with the depth and qubit count, but also
validates the rescaling technique for sufficiently deep quantum circuits. Our
results contribute to the understanding of the physical limitations of quantum
error mitigation and offer a new criterion for evaluating the performance of
quantum error mitigation techniques.Comment: 7 + 14 pages, 10 figures. See also a related work by Takagi et al.,
which appears in the same arXiv posting as arXiv:2208.0917
Target-selective homologous recombination cloning for high-throughput generation of monoclonal antibodies from single plasma cells
<p>Abstract</p> <p>Background</p> <p>Molecular cloning of functional immunoglobulin genes from single plasma cells is one of the most promising technologies for the rapid development of monoclonal antibody drugs. However, the proper insertion of PCR-amplified immunoglobulin genes into expression vectors remains an obstacle to the high-throughput production of recombinant monoclonal antibodies.</p> <p>Results</p> <p>We developed a single-step cloning method, target-selective homologous recombination (TS-HR), in which PCR-amplified immunoglobulin variable genes were selectively inserted into vectors, even in the presence of nonspecifically amplified DNA. TS-HR utilizes Red/ET-mediated homologous recombination with a target-selective vector (TS-vector) with unique homology arms on its termini. Using TS-HR, immunoglobulin variable genes were cloned directly into expression vectors by co-transforming unpurified PCR products and the TS-vector into <it>E. coli</it>. Furthermore, the high cloning specificity of TS-HR allowed plasmids to be extracted from pools of transformed bacteria without screening single colonies for correct clones. We present a one-week protocol for the production of recombinant mouse monoclonal antibodies from large numbers of single plasma cells.</p> <p>Conclusion</p> <p>The time requirements and limitations of traditional cloning procedures for the production of recombinant immunoglobulins have been significantly reduced with the development of the TS-HR cloning technique.</p
Adaptive measurement strategy for quantum subspace methods
Estimation of physical observables for unknown quantum states is an important
problem that underlies a wide range of fields, including quantum information
processing, quantum physics, and quantum chemistry. In the context of quantum
computation, in particular, existing studies have mainly focused on holistic
state tomography or estimation on specific observables with known classical
descriptions, while this lacks the important class of problems where the
estimation target itself relies on the measurement outcome. In this work, we
propose an adaptive measurement optimization method that is useful for the
quantum subspace methods, namely the variational simulation methods that
utilize classical postprocessing on measurement outcomes. The proposed method
first determines the measurement protocol based on QSE calculation for
classically simulatable states, and then adaptively updates the protocol
according to the quantum measurement result. As a numerical demonstration, we
have shown for excited-state simulation of molecules that (i) we are able to
reduce the number of measurements by an order of magnitude by constructing an
appropriate measurement strategy (ii) the adaptive iteration converges
successfully even for strongly correlated molecule of H. Our work reveals
that the potential of the QSE method can be empowered by elaborated measurement
protocols, and opens a path to further pursue efficient quantum measurement
techniques in practical computations.Comment: 9 pages, 4 figure
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