Abstract:The target-space interpretation of the exact (in α ) reflection coefficient for scattering from Euclidean black-hole horizons in classical string theory is studied. For concreteness, we focus on the solvable SL(2, R) k /U(1) black hole. It is shown that it exhibits a fascinating UV/IR mixing, dramatically modifying the late-time behavior of general relativity. We speculate that this might play an important role in the black-hole information puzzle, as well as in clarifying features related with the non-locality of Little String Theory.

Abstract:We elaborate on the recent claim [1] that non-perturbative effects in α , which are at the core of the FZZ duality, render the region just behind the horizon of the SL(2, R) k /U(1) black hole singular already at the classical level (g s = 0). We argue that the 2D classical SL(2, R) k /U(1) black hole could shed some light on quantum black holes in higher dimensions including large black holes in AdS 5 × S 5 .

Abstract:The potential behind the horizon of an eternal black hole in classical theories is described in terms of data that is available to an external observer -the reflection coefficient of a wave that scatters on the black hole. In GR and perturbative string theory (in α ), the potential is regular at the horizon and it blows up at the singularity. The exact reflection coefficient, that is known for the SL(2, R) k /U(1) black hole and includes nonperturbative α effects, seems however to imply that there is a highly non-trivial structure just behind the horizon.

Abstract:We argue that non-perturbative α stringy effects render the Hartle-Hawking state associated with the SL(2)/U(1) eternal black hole singular at the horizon. We discuss implications of this observation on firewalls in string theory.

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e18725 Background: Healthcare data sharing is important for the creation of diverse and large data sets, supporting clinical decision making, and accelerating efficient research to improve patient outcomes. This is especially vital in the case of real world data analysis. However, stakeholders are reluctant to share their data without ensuring patients’ privacy, proper protection of their data sets and the ways they are being used. Homomorphic encryption is a cryptographic capability that can address these issues by enabling computation on encrypted data without ever decrypting it, so the analytics results are obtained without revealing the raw data. The aim of this study is to prove the accuracy of analytics results and the practical efficiency of the technology. Methods: A real-world data set of colorectal cancer patients’ survival data, following two different treatment interventions, including 623 patients and 24 variables, amounting to 14,952 items of data, was encrypted using leveled homomorphic encryption implemented in the PALISADE software library. Statistical analysis of key oncological endpoints was blindly performed on both the raw data and the homomorphically-encrypted data using descriptive statistics and survival analysis with Kaplan-Meier curves. Results were then compared with an accuracy goal of two decimals. Results: The difference between the raw data and the homomorphically encrypted data results, regarding all variables analyzed was within the pre-determined accuracy range goal, as well as the practical efficiency of the encrypted computation measured by run time, are presented in table. Conclusions: This study demonstrates that data encrypted with Homomorphic Encryption can be statistical analyzed with a precision of at least two decimal places, allowing safe clinical conclusions drawing while preserving patients’ privacy and protecting data owners’ data assets. Homomorphic encryption allows performing efficient computation on encrypted data non-interactively and without requiring decryption during computation time. Utilizing the technology will empower large-scale cross-institution and cross- stakeholder collaboration, allowing safe international collaborations. Clinical trial information: 0048-19-TLV. [Table: see text]