Option to load custom RE parameters in DF chemistry sample

samples/estimation/df-chemistry/README.md

@@ -1,10 +1,10 @@
 # Resource Estimation for Double-factorized Chemistry
 
-In this sample we evaluate the physical resource estimates of using the so-called double-factorized qubitization algorithm described in [[Phys. Rev. Research 3, 033055 (2021)](https://doi.org/10.1103/PhysRevResearch.3.033055)] to calculate the energy of a user provided Hamiltonian to chemical accuracy of 1 mHa. 
+In this sample we evaluate the physical resource estimates of using the so-called double-factorized qubitization algorithm described in [[Phys. Rev. Research 3, 033055 (2021)](https://doi.org/10.1103/PhysRevResearch.3.033055)] to calculate the energy of a user provided Hamiltonian to chemical accuracy of 1 mHa.
 
 The Hamiltonian is provided as an FCIDUMP file that is available on your machine or can be downloaded via an HTTPS URL.
 
-```
+```text
 usage: chemistry.py [-h] [-f FCIDUMPFILE]
 
 Double-factorized chemistry sample
@@ -13,20 +13,24 @@ options:
   -h, --help            show this help message and exit
   -f FCIDUMPFILE, --fcidumpfile FCIDUMPFILE
                         Path to the FCIDUMP file describing the Hamiltonian
+  -p [PARAMSFILE ...], --paramsfile [PARAMSFILE ...]
+                        Optional parameter files to use for estimation
 ```
 
 For example, the following command will download the FCIDUMP file `n2-10e-8o` to the working folder and run resource estimation for it:
 
-```
+```shell
 chemistry.py -f https://aka.ms/fcidump/n2-10e-8o
 ```
 
 After that, you can pass the path to the downloaded file to the script instead:
 
-```
+```shell
 chemistry.py -f n2-10e-8o
 ```
 
+By default, physical resources are estimates for a Majorana based qubit with 10⁻⁶ error rates (`qubit_maj_ns_e6`), a Floquet code QEC scheme.  The error budget is set to 0.01 to reach the required chemical accuracy of 1 mHa.  The `-p` program argument can be used to load other resource estimation parameters, specified in JSON files.  The JSON files can either contain a JSON object for one configuration, or an array of JSON objects for multiple configurations.  Make sure to set the error budget to 0.01 to guarantee the correct chemical accuracy.
+
 You can choose some of the following URLs to download example files:
 
 | URL  | Instance name  | Description  |
@@ -37,4 +41,4 @@ You can choose some of the following URLs to download example files:
 | https://aka.ms/fcidump/fe2s2-10e-40o         | fe2s2-10e-40o         | 10 electron, 40 orbital active space of [2Fe, 2S] cluster that is shown in [this paper](https://www.nature.com/articles/nchem.2041) |
 | https://aka.ms/fcidump/polyyne-24e-24o       | polyyne-24e-24o       | 24 electron, 24 orbital active space of the polyyne molecule |
 
-The numbers for the XVIII-cas4-fb-64e-56o instance roughly match the numbers in the paper [Assessing requirements for scaling quantum computers to real-world impact](https://aka.ms/AQ/RE/Paper), as we incorporated a few improvements in the implementation of the double-factorized chemistry algorithm as compared to the version used when the paper was published.
+The numbers for the XVIII-cas4-fb-64e-56o instance roughly match the numbers in the paper [Assessing requirements for scaling quantum computers to real-world impact](https://aka.ms/AQ/RE/Paper), as we incorporated a few improvements in the implementation of the double-factorized chemistry algorithm as compared to the version used when the paper was published.

samples/estimation/df-chemistry/chemistry.py

@@ -1,5 +1,6 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # Licensed under the MIT License.
+import json
 import math
 import numpy as np
 import numpy.typing as npt
@@ -445,6 +446,12 @@ def ndarray2d_to_string(arr):
     default="https://aka.ms/fcidump/n2-10e-8o",
     help="Path to the FCIDUMP file describing the Hamiltonian",
 )
+parser.add_argument(
+    "-p",
+    "--paramsfile",
+    nargs="*",
+    help="Optional parameter files to use for estimation",
+)
 args = parser.parse_args()
 
 # ----- Read the FCIDUMP file and get resource estimates from Q# algorithm -----
@@ -479,23 +486,37 @@ def ndarray2d_to_string(arr):
     "Microsoft.Quantum.Applications.Chemistry.DoubleFactorizedChemistryParameters(0.001,))"
 )
 
-# Get resource estimates
-res = qsharp.estimate(
-    qsharp_string,
-    params={
+# Collect resource estimation parameters
+if args.paramsfile is None:
+    params = {
         "errorBudget": 0.01,
         "qubitParams": {"name": "qubit_maj_ns_e6"},
         "qecScheme": {"name": "floquet_code"},
-    },
+    }
+else:
+    params = []
+    for paramsfile in args.paramsfile:
+        with open(paramsfile) as f:
+            data = json.load(f)
+            if isinstance(data, dict):
+                params.append(data)
+            else:
+                params += data
+
+# Get resource estimates
+res = qsharp.estimate(
+    qsharp_string,
+    params=params,
 )
 
 # Store estimates in json file
 with open("resource_estimate.json", "w") as f:
     f.write(res.json)
 
 # Print high-level resource estimation results
-print(f"Algorithm runtime: {res['physicalCountsFormatted']['runtime']}")
-print(
-    f"Number of physical qubits required: {res['physicalCountsFormatted']['physicalQubits']}"
-)
+if "physicalCountsFormatted" in res:
+    print(f"Algorithm runtime: {res['physicalCountsFormatted']['runtime']}")
+    print(
+        f"Number of physical qubits required: {res['physicalCountsFormatted']['physicalQubits']}"
+    )
 print("For more detailed resource counts, see file resource_estimate.json")