add google analytics

_bibliography/papers.bib

@@ -9,7 +9,7 @@ @article{Zhang2020_DQAS
 abstract = {Quantum architecture search (QAS) is the process of automating architecture engineering of quantum circuits. It has been desired to construct a powerful and general QAS platform which can significantly accelerate current efforts to identify quantum advantages of error-prone and depth-limited quantum circuits in the NISQ era. Hereby, we propose a general framework of differentiable quantum architecture search (DQAS), which enables automated designs of quantum circuits in an end-to-end differentiable fashion. We present several examples of circuit design problems to demonstrate the power of DQAS. For instance, unitary operations are decomposed into quantum gates, noisy circuits are re-designed to improve accuracy, and circuit layouts for quantum approximation optimization algorithm are automatically discovered and upgraded for combinatorial optimization problems. These results not only manifest the vast potential of DQAS being an essential tool for the NISQ application developments, but also present an interesting research topic from the theoretical perspective as it draws inspirations from the newly emerging interdisciplinary paradigms of differentiable programming, probabilistic programming, and quantum programming.},
 archivePrefix = {arXiv},
 arxivId = {2010.08561},
-author = {Zhang, Shi-Xin and Hsieh, Chang-Yu and Zhang, Shengyu and Yao, Hong},
+author = {Zhang, Shi-Xin and Hsieh†, Chang-Yu and Zhang, Shengyu and Yao†, Hong},
 doi = {10.1088/2058-9565/ac87cd},
 eprint = {2010.08561},
 issn = {2058-9565},
@@ -32,7 +32,7 @@ @article{Zhang2022_tc
 abstract = {TensorCircuit is an open source quantum circuit simulator based on tensor network contraction, designed for speed, flexibility and code efficiency. Written purely in Python, and built on top of industry-standard machine learning frameworks, TensorCircuit supports automatic differentiation, just-in-time compilation, vectorized parallelism and hardware acceleration. These features allow TensorCircuit to simulate larger and more complex quantum circuits than existing simulators, and are especially suited to variational algorithms based on parameterized quantum circuits. TensorCircuit enables orders of magnitude speedup for various quantum simulation tasks compared to other common quantum software, and can simulate up to 600 qubits with moderate circuit depth and low-dimensional connectivity. With its time and space efficiency, flexible and extensible architecture and compact, user-friendly API, TensorCircuit has been built to facilitate the design, simulation and analysis of quantum algorithms in the Noisy Intermediate-Scale Quantum (NISQ) era.},
 archivePrefix = {arXiv},
 arxivId = {2205.10091},
-author = {Zhang, Shi-Xin and Allcock, Jonathan and Wan, Zhou-Quan and Liu, Shuo and Sun, Jiace and Yu, Hao and Yang, Xing-Han and Qiu, Jiezhong and Ye, Zhaofeng and Chen, Yu-Qin and Lee, Chee-Kong and Zheng, Yi-Cong and Jian, Shao-Kai and Yao, Hong and Hsieh, Chang-Yu and Zhang, Shengyu},
+author = {Zhang, Shi-Xin and Allcock, Jonathan and Wan, Zhou-Quan and Liu, Shuo and Sun, Jiace and Yu, Hao and Yang, Xing-Han and Qiu, Jiezhong and Ye, Zhaofeng and Chen, Yu-Qin and Lee, Chee-Kong and Zheng, Yi-Cong and Jian, Shao-Kai and Yao, Hong and Hsieh†, Chang-Yu and Zhang†, Shengyu},
 doi = {10.22331/q-2023-02-02-912},
 eprint = {2205.10091},
 issn = {2521-327X},
@@ -47,3 +47,26 @@ @article{Zhang2022_tc
 google_scholar_id = {4TOpqqG69KYC},
 pdf = {TC.pdf}
 }
+
+@article{Liu2024_MIPT1,
+abbr = {PRL},
+bibtex_show = {true},
+abstract = {In the context of measurement-induced entanglement phase transitions, the influence of quantum noises, which are inherent in real physical systems, is of great importance and experimental relevance. In this Letter, we present a comprehensive theoretical analysis of the effects of both temporally uncorrelated and correlated quantum noises on entanglement generation and information protection. This investigation reveals that entanglement within the system follows $q^{-1/3}$ scaling for both types of quantum noises, where $q$ represents the noise probability. The scaling arises from the Kardar-Parisi-Zhang fluctuation with effective length scale $L_{\text{eff}} \sim q^{-1}$. More importantly, the information protection timescales of the steady states are explored and shown to follow $q^{-1/2}$ and $q^{-2/3}$ scaling for temporally uncorrelated and correlated noises, respectively. The former scaling can be interpreted as a Hayden-Preskill protocol, while the latter is a direct consequence of Kardar-Parisi-Zhang fluctuations. We conduct extensive numerical simulations using stabilizer formalism to support the theoretical understanding. This Letter not only contributes to a deeper understanding of the interplay between quantum noises and measurement-induced phase transition but also provides a new perspective to understand the effects of Markovian and non-Markovian noises on quantum computation.},
+archivePrefix = {arXiv},
+arxivId = {2401.01593},
+author = {Liu, Shuo and Li, Ming-Rui and Zhang†, Shi-Xin and Jian†, Shao-Kai},
+doi = {10.1103/PhysRevLett.132.240402},
+eprint = {2401.01593},
+issn = {0031-9007},
+journal = {Phys. Rev. Lett.},
+month = {jun},
+number = {24},
+pages = {240402},
+title = {{Entanglement Structure and Information Protection in Noisy Hybrid Quantum Circuits}},
+url = {https://link.aps.org/doi/10.1103/PhysRevLett.132.240402},
+html = {https://link.aps.org/doi/10.1103/PhysRevLett.132.240402},
+volume = {132},
+year = {2024},
+pdf = {Liu2024_MIPT1.pdf}
+}
+

_config.yml

@@ -12,13 +12,13 @@ description: > # the ">" symbol means to ignore newlines until "footer_text:"
 footer_text: >
   Powered by <a href="https://jekyllrb.com/" target="_blank">Jekyll</a> with <a href="https://github.com/alshedivat/al-folio">al-folio</a> theme.
   Hosted by <a href="https://pages.github.com/" target="_blank">GitHub Pages</a>.
-keywords: jekyll, jekyll-theme, academic-website, portfolio-website # add your own keywords or leave empty
+keywords: physics, quantum-computing, artificial-intelligence # add your own keywords or leave empty
 lang: en # the language of your site (for example: en, fr, cn, ru, etc.)
 icon: 🌖 # the emoji used as the favicon (alternatively, provide image name in /assets/img/)
 
 url: https://sxzgroup.github.io # the base hostname & protocol for your site
 baseurl: # the subpath of your site, e.g. /blog/. Leave blank for root
-last_updated: false # set to true if you want to display last updated in the footer
+last_updated: true # set to true if you want to display last updated in the footer
 impressum_path: # set to path to include impressum link in the footer, use the same path as permalink in a page, helps to conform with EU GDPR
 back_to_top: true # set to false to disable the back to top button
 
@@ -118,7 +118,7 @@ contact_note:
 
 # For Google Analytics, see https://support.google.com/analytics/answer/10447272?hl=en&ref_topic=14088998&sjid=5129943941510317771-SA#zippy=%2Cgoogle-sites
 # and follow the instructions for Google Sites. You will need to create a Google Analytics property and copy the Google tag ID.
-google_analytics: # your Google Analytics measurement ID (format: G-XXXXXXXXXX)
+google_analytics: G-TP5WKPNVYZ # your Google Analytics measurement ID (format: G-XXXXXXXXXX)
 cronitor_analytics: # cronitor RUM analytics site ID (format: XXXXXXXXX)
 pirsch_analytics: # your Pirsch analytics site ID (length 32 characters)