اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدFully-programmable universal quantum simulator with a one-dimensional quantum processor
84
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Current quantum devices execute specific tasks that are hard for classical computers and have the potential to solve problems such as quantum simulation of material science and chemistry, even without error correction. For practical applications it is highly desirable to reconfigure the connectivity of the device, which for superconducting quantum processors is determined at fabrication. In addition, we require a careful design of control lines and couplings to resonators for measurements. Therefore, it is a cumbersome and slow undertaking to fabricate a new device for each problem we want to solve. Here we periodically drive a one-dimensional chain to engineer effective Hamiltonians that simulate arbitrary connectivities. We demonstrate the capability of our method by engineering driving sequences to simulate star, all-to-all, and ring connectivities. We also simulate a minimal example of the 3-SAT problem including three-body interactions, which are difficult to realize experimentally. Our results open a new paradigm to perform quantum simulation in near term quantum devices by enabling us to stroboscopically simulate arbitrary Hamiltonians with a single device and optimized driving sequences
قيم البحث
اقرأ أيضاً
The discrete time crystal (DTC) is a recently discovered phase of matter that spontaneously breaks time-translation symmetry. Disorder-induced many-body-localization is required to stabilize a DTC to arbitrary times, yet an experimental investigation
of this localized regime has proven elusive. Here, we observe the hallmark signatures of a many-body-localized DTC using a novel quantum simulation platform based on individually controllable $^{13}$C nuclear spins in diamond. We demonstrate the characteristic long-lived spatiotemporal order and confirm that it is robust for generic initial states. Our results are consistent with the realization of an out-of-equilibrium Floquet phase of matter and establish a programmable quantum simulator based on solid-state spins for exploring many-body physics.
Machine learning has emerged as a promising approach to study the properties of many-body systems. Recently proposed as a tool to classify phases of matter, the approach relies on classical simulation methods$-$such as Monte Carlo$-$which are known t
o experience an exponential slowdown when simulating certain quantum systems. To overcome this slowdown while still leveraging machine learning, we propose a variational quantum algorithm which merges quantum simulation and quantum machine learning to classify phases of matter. Our classifier is directly fed labeled states recovered by the variational quantum eigensolver algorithm, thereby avoiding the data reading slowdown experienced in many applications of quantum enhanced machine learning. We propose families of variational ansatz states that are inspired directly by tensor networks. This allows us to use tools from tensor network theory to explain properties of the phase diagrams the presented method recovers. Finally, we propose a nearest-neighbour (checkerboard) quantum neural network. This majority vote quantum classifier is successfully trained to recognize phases of matter with $99%$ accuracy for the transverse field Ising model and $94%$ accuracy for the XXZ model. These findings suggest that our merger between quantum simulation and quantum enhanced machine learning offers a fertile ground to develop computational insights into quantum systems.
We explore experimentally a quantum metamaterial based on a superconducting chip with 25 frequency-tunable transmon qubits coupled to a common coplanar resonator. The collective bright and dark modes are probed via the microwave response, i.e., by me
asuring the transmission amplitude of an external microwave signal. All qubits have individual control and readout lines. Their frequency tunability allows to change the number N of resonantly coupled qubits and also to introduce a disorder in their excitation frequencies with preassigned distributions. While increasing N, we demonstrate the expected $N^{1/2}$ scaling law for the energy gap (Rabi splitting) between bright modes around the cavity frequency. By introducing a controllable disorder and averaging the transmission amplitude over a large number of realizations, we demonstrate a decay of mesoscopic fluctuations which mimics an approach towards the thermodynamic limit. The collective bright states survive in the presence of disorder when the strength of individual qubit coupling to the cavity dominates over the disorder strength.
Quantum metrology makes use of coherent superpositions to detect weak signals. While in principle the sensitivity can be improved by increasing the density of sensing particles, in practice this improvement is severely hindered by interactions betwee
n them. Using a dense ensemble of interacting electronic spins in diamond, we demonstrate a novel approach to quantum metrology. It is based on a new method of robust quantum control, which allows us to simultaneously eliminate the undesired effects associated with spin-spin interactions, disorder and control imperfections, enabling a five-fold enhancement in coherence time compared to conventional control sequences. Combined with optimal initialization and readout protocols, this allows us to break the limit for AC magnetic field sensing imposed by interactions, opening a promising avenue for the development of solid-state ensemble magnetometers with unprecedented sensitivity.
Random quantum circuits have played a central role in establishing the computational advantages of near-term quantum computers over their conventional counterparts. Here, we use ensembles of low-depth random circuits with local connectivity in $Dge 1
$ spatial dimensions to generate quantum error-correcting codes. For random stabilizer codes and the erasure channel, we find strong evidence that a depth $O(log N)$ random circuit is necessary and sufficient to converge (with high probability) to zero failure probability for any finite amount below the optimal erasure threshold, set by the channel capacity, for any $D$. Previous results on random circuits have only shown that $O(N^{1/D})$ depth suffices or that $O(log^3 N)$ depth suffices for all-to-all connectivity ($D to infty$). We then study the critical behavior of the erasure threshold in the so-called moderate deviation limit, where both the failure probability and the distance to the optimal threshold converge to zero with $N$. We find that the requisite depth scales like $O(log N)$ only for dimensions $D ge 2$, and that random circuits require $O(sqrt{N})$ depth for $D=1$. Finally, we introduce an expurgation algorithm that uses quantum measurements to remove logical operators that cause the code to fail by turning them into additional stabilizers or gauge operators. With such targeted measurements, we can achieve sub-logarithmic depth in $Dge 2$ below capacity without increasing the maximum weight of the check operators. We find that for any rate beneath the capacity, high-performing codes with thousands of logical qubits are achievable with depth 4-8 expurgated random circuits in $D=2$ dimensions. These results indicate that finite-rate quantum codes are practically relevant for near-term devices and may significantly reduce the resource requirements to achieve fault tolerance for near-term applications.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
