22 research outputs found
Characterizing the Structure of Topological Insulator Thin Films
We describe the characterization of structural defects that occur during
molecular beam epitaxy of topological insulator thin films on commonly used
substrates. Twinned domains are ubiquitous but can be reduced by growth on
smooth InP (111)A substrates, depending on details of the oxide desorption.
Even with a low density of twins, the lattice mismatch between (Bi,Sb)2Te3 and
InP can cause tilts in the film with respect to the substrate. We also briefly
discuss transport in simultaneously top and back electrically gated devices
using SrTiO3 and the use of capping layers to protect topological insulator
films from oxidation and exposure
Supervised learning with quantum enhanced feature spaces
Machine learning and quantum computing are two technologies each with the
potential for altering how computation is performed to address previously
untenable problems. Kernel methods for machine learning are ubiquitous for
pattern recognition, with support vector machines (SVMs) being the most
well-known method for classification problems. However, there are limitations
to the successful solution to such problems when the feature space becomes
large, and the kernel functions become computationally expensive to estimate. A
core element to computational speed-ups afforded by quantum algorithms is the
exploitation of an exponentially large quantum state space through controllable
entanglement and interference. Here, we propose and experimentally implement
two novel methods on a superconducting processor. Both methods represent the
feature space of a classification problem by a quantum state, taking advantage
of the large dimensionality of quantum Hilbert space to obtain an enhanced
solution. One method, the quantum variational classifier builds on [1,2] and
operates through using a variational quantum circuit to classify a training set
in direct analogy to conventional SVMs. In the second, a quantum kernel
estimator, we estimate the kernel function and optimize the classifier
directly. The two methods present a new class of tools for exploring the
applications of noisy intermediate scale quantum computers [3] to machine
learning.Comment: Fixed typos, added figures and discussion about quantum error
mitigatio
Low temperature saturation of phase coherence length in topological insulators
Implementing topological insulators as elementary units in quantum
technologies requires a comprehensive understanding of the dephasing mechanisms
governing the surface carriers in these materials, which impose a practical
limit to the applicability of these materials in such technologies requiring
phase coherent transport. To investigate this, we have performed
magneto-resistance (MR) and conductance fluctuations\ (CF) measurements in both
exfoliated and molecular beam epitaxy grown samples. The phase breaking length
() obtained from MR shows a saturation below sample dependent
characteristic temperatures, consistent with that obtained from CF
measurements. We have systematically eliminated several factors that may lead
to such behavior of in the context of TIs, such as finite size
effect, thermalization, spin-orbit coupling length, spin-flip scattering, and
surface-bulk coupling. Our work indicates the need to identify an alternative
source of dephasing that dominates at low in topological insulators,
causing saturation in the phase breaking length and time
Interplay between ferromagnetism, surface states, and quantum corrections in a magnetically doped topological insulator
The breaking of time-reversal symmetry by ferromagnetism is predicted to
yield profound changes to the electronic surface states of a topological
insulator. Here, we report on a concerted set of structural, magnetic,
electrical and spectroscopic measurements of \MBS thin films wherein
photoemission and x-ray magnetic circular dichroism studies have recently shown
surface ferromagnetism in the temperature range 15 K K,
accompanied by a suppressed density of surface states at the Dirac point.
Secondary ion mass spectroscopy and scanning tunneling microscopy reveal an
inhomogeneous distribution of Mn atoms, with a tendency to segregate towards
the sample surface. Magnetometry and anisotropic magnetoresistance measurements
are insensitive to the high temperature ferromagnetism seen in surface studies,
revealing instead a low temperature ferromagnetic phase at K.
The absence of both a magneto-optical Kerr effect and anomalous Hall effect
suggests that this low temperature ferromagnetism is unlikely to be a
homogeneous bulk phase but likely originates in nanoscale near-surface regions
of the bulk where magnetic atoms segregate during sample growth. Although the
samples are not ideal, with both bulk and surface contributions to electron
transport, we measure a magnetoconductance whose behavior is qualitatively
consistent with predictions that the opening of a gap in the Dirac spectrum
drives quantum corrections to the conductance in topological insulators from
the symplectic to the orthogonal class.Comment: To appear in Phys. Rev.
Realizing the Nishimori transition across the error threshold for constant-depth quantum circuits
Preparing quantum states across many qubits is necessary to unlock the full
potential of quantum computers. However, a key challenge is to realize
efficient preparation protocols which are stable to noise and gate
imperfections. Here, using a measurement-based protocol on a 127
superconducting qubit device, we study the generation of the simplest
long-range order -- Ising order, familiar from Greenberger-Horne-Zeilinger
(GHZ) states and the repetition code -- on 54 system qubits. Our efficient
implementation of the constant-depth protocol and classical decoder shows
higher fidelities for GHZ states compared to size-dependent, unitary protocols.
By experimentally tuning coherent and incoherent error rates, we demonstrate
stability of this decoded long-range order in two spatial dimensions, up to a
critical point which corresponds to a transition belonging to the unusual
Nishimori universality class. Although in classical systems Nishimori physics
requires fine-tuning multiple parameters, here it arises as a direct result of
the Born rule for measurement probabilities -- locking the effective
temperature and disorder driving this transition. Our study exemplifies how
measurement-based state preparation can be meaningfully explored on quantum
processors beyond a hundred qubits.Comment: 16 pages, 18 figure