@article {3251, title = {Random Pulse Sequences for Qubit Noise Spectroscopy}, year = {2023}, month = {3/2/2023}, abstract = {

Qubit noise spectroscopy is an important tool for the experimental investigation of open quantum systems. However, conventional techniques for implementing noise spectroscopy are time-consuming, because they require multiple measurements of the noise spectral density at different frequencies. Here we describe an alternative method for quickly characterizing the spectral density. Our method utilizes random pulse sequences, with carefully-controlled correlations among the pulses, to measure arbitrary linear functionals of the noise spectrum. Such measurements allow us to estimate k\&$\#$39;th-order moments of the noise spectrum, as well as to reconstruct sparse noise spectra via compressed sensing. Our simulations of the performance of the random pulse sequences on a realistic physical system, self-assembled quantum dots, reveal a speedup of an order of magnitude in extracting the noise spectrum compared to conventional dynamical decoupling approaches.

}, url = {https://arxiv.org/abs/2303.00909}, author = {Kaixin Huang and Demitry Farfurnik and Alireza Seif and Mohammad Hafezi and Yi-Kai Liu} } @article {2807, title = {Compressed Sensing Measurement of Long-Range Correlated Noise}, year = {2021}, month = {5/26/2021}, abstract = {

Long-range correlated errors can severely impact the performance of NISQ (noisy intermediate-scale quantum) devices, and fault-tolerant quantum computation. Characterizing these errors is important for improving the performance of these devices, via calibration and error correction, and to ensure correct interpretation of the results. We propose a compressed sensing method for detecting two-qubit correlated dephasing errors, assuming only that the correlations are sparse (i.e., at most s pairs of qubits have correlated errors, where s \<\< n(n-1)/2, and n is the total number of qubits). In particular, our method can detect long-range correlations between any two qubits in the system (i.e., the correlations are not restricted to be geometrically local).
Our method is highly scalable: it requires as few as m = O(s log n) measurement settings, and efficient classical postprocessing based on convex optimization. In addition, when m = O(s log^4(n)), our method is highly robust to noise, and has sample complexity O(max(n,s)^2 log^4(n)), which can be compared to conventional methods that have sample complexity O(n^3). Thus, our method is advantageous when the correlations are sufficiently sparse, that is, when s \< O(n^(3/2) / log^2(n)). Our method also performs well in numerical simulations on small system sizes, and has some resistance to state-preparation-and-measurement (SPAM) errors. The key ingredient in our method is a new type of compressed sensing measurement, which works by preparing entangled Greenberger-Horne-Zeilinger states (GHZ states) on random subsets of qubits, and measuring their decay rates with high precision.

}, url = {https://arxiv.org/abs/2105.12589}, author = {Alireza Seif and Mohammad Hafezi and Yi-Kai Liu} } @article {2817, title = {Decoding conformal field theories: from supervised to unsupervised learning}, year = {2021}, month = {7/10/2021}, abstract = {

We use machine learning to classify rational two-dimensional conformal field theories. We first use the energy spectra of these minimal models to train a supervised learning algorithm. We find that the machine is able to correctly predict the nature and the value of critical points of several strongly correlated spin models using only their energy spectra. This is in contrast to previous works that use machine learning to classify different phases of matter, but do not reveal the nature of the critical point between phases. Given that the ground-state entanglement Hamiltonian of certain topological phases of matter is also described by conformal field theories, we use supervised learning on R{\'e}yni entropies and find that the machine is able to identify which conformal field theory describes the entanglement Hamiltonian with only the lowest few R{\'e}yni entropies to a high degree of accuracy. Finally, using autoencoders, an unsupervised learning algorithm, we find a hidden variable that has a direct correlation with the central charge and discuss prospects for using machine learning to investigate other conformal field theories, including higher-dimensional ones. Our results highlight that machine learning can be used to find and characterize critical points and also hint at the intriguing possibility to use machine learning to learn about more complex conformal field theories.

}, url = {https://arxiv.org/abs/2106.13485}, author = {En-Jui Kuo and Alireza Seif and Rex Lundgren and Seth Whitsitt and Mohammad Hafezi} } @article {2916, title = {Discovering hydrodynamic equations of many-body quantum systems}, year = {2021}, month = {11/3/2021}, abstract = {

Simulating and predicting dynamics of quantum many-body systems is extremely challenging, even for state-of-the-art computational methods, due to the spread of entanglement across the system. However, in the long-wavelength limit, quantum systems often admit a simplified description, which involves a small set of physical observables and requires only a few parameters such as sound velocity or viscosity. Unveiling the relationship between these hydrodynamic equations and the underlying microscopic theory usually requires a great effort by condensed matter theorists. In the present paper, we develop a new machine-learning framework for automated discovery of effective equations from a limited set of available data, thus bypassing complicated analytical derivations. The data can be generated from numerical simulations or come from experimental quantum simulator platforms. Using integrable models, where direct comparisons can be made, we reproduce previously known hydrodynamic equations, strikingly discover novel equations and provide their derivation whenever possible. We discover new hydrodynamic equations describing dynamics of interacting systems, for which the derivation remains an outstanding challenge. Our approach provides a new interpretable method to study properties of quantum materials and quantum simulators in non-perturbative regimes.

}, url = {https://arxiv.org/abs/2111.02385}, author = {Yaroslav Kharkov and Oles Shtanko and Alireza Seif and Przemyslaw Bienias and Mathias Van Regemortel and Mohammad Hafezi and Alexey V. Gorshkov} } @article {2770, title = {Meta Hamiltonian Learning}, year = {2021}, month = {4/9/2021}, abstract = {

Efficient characterization of quantum devices is a significant challenge critical for the development of large scale quantum computers. We consider an experimentally motivated situation, in which we have a decent estimate of the Hamiltonian, and its parameters need to be characterized and fine-tuned frequently to combat drifting experimental variables. We use a machine learning technique known as meta-learning to learn a more efficient optimizer for this task. We consider training with the nearest-neighbor Ising model and study the trained model\&$\#$39;s generalizability to other Hamiltonian models and larger system sizes. We observe that the meta-optimizer outperforms other optimization methods in average loss over test samples. This advantage follows from the meta-optimizer being less likely to get stuck in local minima, which highly skews the distribution of the final loss of the other optimizers. In general, meta-learning decreases the number of calls to the experiment and reduces the needed classical computational resources.

}, url = {https://arxiv.org/abs/2104.04453}, author = {Przemyslaw Bienias and Alireza Seif and Mohammad Hafezi} } @article {2677, title = {Entanglement entropy scaling transition under competing monitoring protocols}, year = {2020}, month = {08/19/2020}, abstract = {

Dissipation generally leads to the decoherence of a quantum state. In contrast, numerous recent proposals have illustrated that dissipation can also be tailored to stabilize many-body entangled quantum states. While the focus of these works has been primarily on engineering the non-equilibrium steady state, we investigate the build-up of entanglement in the quantum trajectories. Specifically, we analyze the competition between two different dissipation channels arising from two incompatible continuous monitoring protocols. The first protocol locks the phase of neighboring sites upon registering a quantum jump, thereby generating a long-range entanglement through the system, while the second one destroys the coherence via dephasing mechanism. By studying the unraveling of stochastic quantum trajectories associated with the continuous monitoring protocols, we present a transition for the scaling of the averaged trajectory entanglement entropies, from critical scaling to area-law behavior. Our work provides novel insights into the occurrence of a measurement-induced phase transition within a continuous monitoring protocol.

}, url = {https://arxiv.org/abs/2008.08619}, author = {Mathias Van Regemortel and Ze-Pei Cian and Alireza Seif and Hossein Dehghani and Mohammad Hafezi} } @article {2466, title = {Machine learning the thermodynamic arrow of time}, journal = {Nat. Phys.}, year = {2020}, month = {09/21/2020}, pages = {1-9}, abstract = {

The mechanism by which thermodynamics sets the direction of time\&$\#$39;s arrow has long fascinated scientists. Here, we show that a machine learning algorithm can learn to discern the direction of time\&$\#$39;s arrow when provided with a system\&$\#$39;s microscopic trajectory as input. The performance of our algorithm matches fundamental bounds predicted by nonequilibrium statistical mechanics. Examination of the algorithm\&$\#$39;s decision-making process reveals that it discovers the underlying thermodynamic mechanism and the relevant physical observables. Our results indicate that machine learning techniques can be used to study systems out of equilibrium, and ultimately to uncover physical principles.

}, doi = {https://doi.org/10.1038/s41567-020-1018-2}, url = {https://arxiv.org/abs/1909.12380}, author = {Alireza Seif and Mohammad Hafezi and Christopher Jarzynski} } @article {2632, title = {Optimal control for quantum detectors}, year = {2020}, month = {5/12/2020}, abstract = {

Quantum systems are promising candidates for sensing of weak signals as they can provide unrivaled performance when estimating parameters of external fields. However, when trying to detect weak signals that are hidden by background noise, the signal-to-noise-ratio is a more relevant metric than raw sensitivity. We identify, under modest assumptions about the statistical properties of the signal and noise, the optimal quantum control to detect an external signal in the presence of background noise using a quantum sensor. Interestingly, for white background noise, the optimal solution is the simple and well-known spin-locking control scheme. We further generalize, using numerical techniques, these results to the background noise being a correlated Lorentzian spectrum. We show that for increasing correlation time, pulse based sequences such as CPMG are also close to the optimal control for detecting the signal, with the crossover dependent on the signal frequency. These results show that an optimal detection scheme can be easily implemented in near-term quantum sensors without the need for complicated pulse shaping.

}, url = {https://arxiv.org/abs/2005.05995}, author = {Paraj Titum and Kevin M. Schultz and Alireza Seif and Gregory D. Quiroz and B. D. Clader} } @article {2453, title = {Towards analog quantum simulations of lattice gauge theories with trapped ions}, journal = {Physical Review Research }, volume = {2}, year = {2020}, month = {4/8/2020}, abstract = {

Gauge field theories play a central role in modern physics and are at the heart of the Standard Model of elementary particles and interactions. Despite significant progress in applying classical computational techniques to simulate gauge theories, it has remained a challenging task to compute the real-time dynamics of systems described by gauge theories. An exciting possibility that has been explored in recent years is the use of highly-controlled quantum systems to simulate, in an analog fashion, properties of a target system whose dynamics are difficult to compute. Engineered atom-laser interactions in a linear crystal of trapped ions offer a wide range of possibilities for quantum simulations of complex physical systems. Here, we devise practical proposals for analog simulation of simple lattice gauge theories whose dynamics can be mapped onto spin-spin interactions in any dimension. These include 1+1D quantum electrodynamics, 2+1D Abelian Chern-Simons theory coupled to fermions, and 2+1D pure Z2 gauge theory. The scheme proposed, along with the optimization protocol applied, will have applications beyond the examples presented in this work, and will enable scalable analog quantum simulation of Heisenberg spin models in any number of dimensions and with arbitrary interaction strengths.

}, doi = {https://doi.org/10.1103/PhysRevResearch.2.023015}, url = {https://arxiv.org/abs/1908.03210}, author = {Zohreh Davoudi and Mohammad Hafezi and Christopher Monroe and Guido Pagano and Alireza Seif and Andrew Shaw} } @article {2390, title = {Photon pair condensation by engineered dissipation}, journal = {Phys. Rev. Lett. }, volume = {123}, year = {2019}, month = {04/02/2019}, abstract = {

Dissipation can usually induce detrimental decoherence in a quantum system. However, engineered dissipation can be used to prepare and stabilize coherent quantum many-body states. Here, we show that by engineering dissipators containing photon pair operators, one can stabilize an exotic dark state, which is a condensate of photon pairs with a phase-nematic order. In this system, the usual superfluid order parameter, i.e. single-photon correlation, is absent, while the photon pair correlation exhibits long-range order. Although the dark state is not unique due to multiple parity sectors, we devise an additional type of dissipators to stabilize the dark state in a particular parity sector via a diffusive annihilation process which obeys Glauber dynamics in an Ising model. Furthermore, we propose an implementation of these photon-pair dissipators in circuit-QED architecture.\ 

}, doi = {10.1103/PhysRevLett.123.063602}, url = {https://arxiv.org/abs/1904.00016}, author = {Ze-Pei Cian and Guanyu Zhu and Su-Kuan Chu and Alireza Seif and Wade DeGottardi and Liang Jiang and Mohammad Hafezi} } @article {2509, title = {Broadband optomechanical non-reciprocity}, journal = {Nature Photon }, volume = {12}, year = {2018}, month = {2018/1/26}, pages = {60-61}, abstract = {

Implementing non-reciprocal elements with a bandwidth comparable to optical frequencies is a challenge
in integrated photonics. Now, a phonon pump has been used to achieve optical non-reciprocity over a
large bandwidth.

}, doi = {https://doi.org/10.1038/s41566-018-0091-x}, author = {Alireza Seif and Mohammad Hafezi} } @article {2287, title = {Machine learning assisted readout of trapped-ion qubits}, journal = { J. Phys. B: At. Mol. Opt. Phys.}, volume = {51}, year = {2018}, month = {2018/05/01}, chapter = {174006}, abstract = {

We reduce measurement errors in a quantum computer using machine learning techniques. We exploit a simple yet versatile neural network to classify multi-qubit quantum states, which is trained using experimental data. This flexible approach allows the incorporation of any number of features of the data with minimal modifications to the underlying network architecture. We experimentally illustrate this approach in the readout of trapped-ion qubits using additional spatial and temporal features in the data. Using this neural network classifier, we efficiently treat qubit readout crosstalk, resulting in a 30\% improvement in detection error over the conventional threshold method. Our approach does not depend on the specific details of the system and can be readily generalized to other quantum computing platforms.

}, doi = {https://doi.org/10.1088/1361-6455/aad62b}, url = {https://arxiv.org/abs/1804.07718}, author = {Alireza Seif and Kevin A. Landsman and Norbert M. Linke and Caroline Figgatt and C. Monroe and Mohammad Hafezi} } @article {2507, title = {Thermal management and non-reciprocal control of phonon flow via optomechanics}, journal = {Nat. Commun.}, volume = {9(1)}, year = {2018}, month = {2018/3/23}, abstract = {

Engineering phonon transport in physical systems is a subject of interest in the study of materials and plays a crucial role in controlling energy and heat transfer. Of particular interest are non-reciprocal phononic systems, which in direct analogy to electric diodes, provide a directional flow of energy. Here, we propose an engineered nanostructured material, in which tunable non-reciprocal phonon transport is achieved through optomechanical coupling. Our scheme relies on breaking time-reversal symmetry by a spatially varying laser drive, which manipulates low-energy acoustic phonons. Furthermore, we take advantage of recent developments in the manipulation of high-energy phonons through controlled scattering mechanisms, such as using alloys and introducing disorder. These combined approaches allow us to design an acoustic isolator and a thermal diode. Our proposed device will have potential impact in phonon-based information processing, and heat management in low temperatures.\ 

}, doi = {https://doi.org/10.1038/s41467-018-03624-y}, url = {https://arxiv.org/abs/1710.08967}, author = {Alireza Seif and Wade DeGottardi and Keivan Esfarjani and Mohammad Hafezi} } @article {2508, title = {Measurement Protocol for the Entanglement Spectrum of Cold Atoms}, journal = {Phys. Rev. X }, volume = {6(4)}, year = {2016}, month = {2016/11/22}, abstract = {

Entanglement, and, in particular the entanglement spectrum, plays a major role in characterizing many-body quantum systems. While there has been a surge of theoretical works on the subject, no experimental measurement has been performed to date because of the lack of an implementable measurement scheme. Here, we propose a measurement protocol to access the entanglement spectrum of many-body states in experiments with cold atoms in optical lattices. Our scheme effectively performs a Ramsey spectroscopy of the entanglement Hamiltonian and is based on the ability to produce several copies of the state under investigation together with the possibility to perform a global swap gate between two copies conditioned on the state of an auxiliary qubit. We show how the required conditional swap gate can be implemented with cold atoms, either by using Rydberg interactions or coupling the atoms to a cavity mode. We illustrate these ideas on a simple (extended) Bose-Hubbard model where such a measurement protocol reveals topological features of the Haldane phase.\ 

}, doi = {https://doi.org/10.1103/PhysRevX.6.041033}, url = {https://arxiv.org/abs/1605.08624}, author = {Hannes Pichler and Guanyu Zhu and Alireza Seif and Peter Zoller and Mohammad Hafezi} }